Full report

Transcripción

Full report

Health and Safety
Executive
Influencing dutyholders behaviour
regarding the management of noise risks
Prepared by the Health and Safety Laboratory
for the Health and Safety Executive 2011
RR866
Research Report
Health and Safety
Executive
Nikki Bell and Jennifer Webster
Health and Safety Laboratory
Harpur Hill
Buxton
Derbyshire
SK17 9JN
This research addressed three research questions: (1) What factors influence employers’ decisions and
practices in controlling noise risks? (2) What is the relative importance of these factors? and; (3) How do
these factors vary between high and low performing companies? A mixed methods approach was adopted
in which 215 questionnaires were completed and 15 in-depth interviews carried out with manufacturing
dutyholders.
Three factors were found to influence noise management: (i) managers’ own knowledge/awareness of noise
risks and associated controls, (ii) the health and safety culture of the company and (iii) its size. Health and
safety culture was found to have the greatest influence, indicating that cultural changes could generate
the most improvements. Managers generally underestimated the significance of noise as an occupational
health risk; a critical knowledge gap was understanding what controls exist and would work in practice. The
size of the company influenced the approach taken with smaller companies showing increased likelihood
of reduced quality in noise management (ie low performance). Small companies, or low performers, were
more constrained by health and safety resources than their high performing (generally large) counterparts.
A preoccupation with measuring noise rather than implementing the right solutions was apparent amongst
low performers, creating a barrier to going beyond personal hearing protection. Future noise interventions
should address these factors and not underestimate the potential influence of culture change.
This report and the work it describes were funded by the Health and Safety Executive (HSE). Its contents,
including any opinions and/or conclusions expressed, are those of the authors alone and do not necessarily
reflect HSE policy.
HSE Books
© Crown copyright 2011
First published 2011
You may reuse this information (not including logos) free
of charge in any format or medium, under the terms of the
Open Government Licence. To view the licence visit
www.nationalarchives.gov.uk/doc/open-government
licence/, write to the Information Policy Team,
The National Archives, Kew, London TW9 4DU, or
email [email protected].
Some images and illustrations may not be owned by the
Crown so cannot be reproduced without permission of the
copyright owner. Enquiries should be sent to
[email protected].
ACKNOWLEDGEMENTS
The authors would like to thank our HSE customer
Tim Ward and colleagues Anne Wright, Beverley Bishop and
Simon Armitage for their support throughout the research.
Our special thanks go to the 230 companies that participated
in this research for giving their time and thoughts generously.
We hope that the report does justice to their experiences
and views. As a token of our appreciation, donations were
made to the following charities: Deafness Research UK;
The Royal National institute for the Deaf; The British Tinnitus
Association; and Hearing Dogs for Deaf People.
ii
EXECUTIVE SUMMARY
ISSUES INVESTIGATED
Anecdotal evidence suggests that dutyholders do not always engage in good practice for noise
control despite the plentiful information and advice available to them. This research aims to
provide an understanding of how to influence dutyholders 1 to ensure that the risks associated
with noise exposure are adequately controlled. The following three research questions are
addressed: (1) What factors influence employers’ decisions and practices in controlling noise
risks? (2) What is the relative importance of these factors? and (3) How do these factors vary
between high and low performing organisations?
KEY FINDINGS
1. Noise management is influenced by three factors: (i) managers’ own knowledge/awareness
of noise as a significant, long-term health risk, as well as knowledge of technical and
organisational controls to reduce noise, (ii) the health and safety values or culture of the
company towards prevention of ill health and (iii) company size. Of critical importance are:
• (Knowledge/awareness) Managers’ general lack of regard for the importance of noise
risks and potential health consequences given its long-latency nature. A critical gap is
understanding what technical/organisational controls exist and would work for them in
practice in order to make an informed choice about which controls to implement. This
includes those managers who regularly access noise information sources.
• (Culture) A tendency for companies to be reactive rather than proactive with noise
management (e.g. monitoring audiometry results versus taking a holistic approach to
select and monitor controls). An ongoing challenge faced by many managers is
knowing how best to encourage appropriate behaviour amongst their workers to make
sure that they properly use the selected controls, although the focus of many managers
is only on personal hearing protection.
• (Company size) The size of the company was found to influence the approach taken to
noise management; the smaller a company the increased likelihood of reduced quality in
the management of noise risks. Small companies find it more difficult than their larger
counterparts to find practical and affordable solutions often because they have limited
resources (finance and time) for health and safety. There is a tendency for these
companies to become preoccupied with taking accurate noise measurements rather than
focusing on implementing the right solutions. In addition, while larger companies
adopted a more strategic and educational approach to noise management, smaller
companies considered machinery replacement as the only ideal solution.
2. These three factors (knowledge/awareness, culture and size) seem to represent the heart of
noise management. Even though eight other factors were not shown to be significant
influencers (i.e. business motivators, resources, information/communications,
autonomy/competence, self-efficacy, attitudes, role as Director and Health and Safety
Manager), they are likely to be mediated by the primary three factors.
3. Similar findings were found when comparing high and low performers. Performance was
influenced by (1) managers’ knowledge of what they should be doing in practice, (2)
1
The term ‘dutyholder’ is used quite loosely to refer to’ the manager responsible for noise’ and so may not
necessarily refer to employers/dutyholders. This research recognised that whilst the power to make financial
decisions resides at the top, practical noise decision-making may be delegated to lower-level management.
iii
prevailing cultural norms towards ill health prevention, and (3) company size. Managers in
high performing (typically large) companies therefore had better knowledge of
organisational and technical noise control measures, and had made some progress with
translating this knowledge into practice (i.e. implementing these controls and promotion of
positive health and safety attitudes/cultural norms). In addition, (4) the level of health and
safety resource was found to influence performance levels. High performers had better
access to such resources than did low performers. It comes as no surprise, therefore, that
the low performers involved in this research tended to be the smaller companies (mostly
micros) whereas the high performers were mostly medium-sized or large companies.
Hearing protection seemed to be preferred, especially by low performers, because it was
considered simple and cheap. Even those small companies guided by external consultants
opted for hearing protection without considering whether this was the most effective and
cost-effective solution or not in the long-term.
4. Only health surveillance and worker education seemed to be externally motivated, largely
through insurers.
Those companies undertaking health surveillance (mostly high
performing) were doing so because they (i) wanted to protect themselves against potential
future health claims and (ii) saw it as a way to gauge the success of implemented noise
controls providing ‘evidence’ that they worked, despite occupational hearing loss taking
many years in most cases for symptoms to manifest. Companies were generally unaware,
however, of the need to train workers in hearing protection use; managers considered this to
be ‘common sense’.
5. Future noise interventions need to address the three primary factors found to influence
managerial decision-making and practices, namely, knowledge/awareness of noise risks and
associated technical/organisational controls, health and safety culture and company size.
Regarding company size, interventions need to be appropriately tailored to the constraints
(both physical and financial) that companies, particularly small companies, might be facing.
Interventions designed to raise managerial knowledge/awareness should not only include
the appropriate selection of controls, but also awareness of the long-latency nature of noise.
Such knowledge may in turn positively influence prevailing cultural attitudes of the
importance of noise as an occupational health risk. The health and safety culture of an
organisation should not be underestimated as this was found to be the most influential
factor.
What do these findings mean in practice?
These findings highlight awareness raising and cultural change as key areas for HSE to target.
In relation to awareness raising HSE could consider:
• Appropriately tailoring future noise messages to small manufacturing companies.
Current noise guidance appears to be better suited to medium-sized and large companies
than the vast majority of small companies that make up the sector. It is the smaller
companies, however, that are the ones likely to be struggling to get to grips with what
would work for them in practice (i.e. ‘how to’ make improvements) that is feasible and
affordable. The apparent preoccupation with measuring noise, even in circumstances
where this may not be necessary, acts as a further barrier to making improvements.
HSE needs to fill the gap between current information supplied to employers and the
practical application of such guidance. Tailoring the guidance to small companies
should in principle make this accessible to organisations of any size. In addition,
pitching guidance at the level of similar rather than specific occupational health risks
might help to reduce the burden. But, smaller companies need to be made aware of the
existence of such guidance and where they can access this.
iv
• Communicating to employers that health surveillance results in the short-to-medium
term do not necessarily mean that noise risks are being adequately managed. This
reflects a commonly held misconception amongst managers in this research, and seems
to correspond with their lack of appreciation of the long-latency nature of noise. HSE
should consider ways of overcoming this misconception about health surveillance for
monitoring occupational health conditions.
• While development of HSE’s noise website may continue to assist the high performing,
larger companies likely to use it, this is unlikely to be an effective means of
communicating with hard-to-reach companies. Innovative ways are needed of
providing advice to these (typically small, non-unionised) companies that rarely seek
this out this information. Using larger, high performing companies as a mechanism for
cascading key messages relating to noise management through the supply chain or
industry events might be one way to achieve this. Another potential means for
cascading important messages to managers would be to establish links with external
bodies such as manufacturers/suppliers of manufacturing machinery/tools and hearing
protection, health and safety training providers etc.
• Focused interventions like training might also be effective in educating the small, hard
to-reach companies. This could be as simple as training managers on how to approach
noise control. Training has the added benefit of being more amenable to evaluation
than organisational-wide interventions. Evidence that these simple interventions
actually work could serve as a powerful motivator for their adoption by other managers.
With regards to culture change HSE could consider:
• The current extent to which cultural assessments form part of HSE inspections and the
feasibility of including these and/or providing managers with the tools to initiate cultural
improvements themselves by addressing the behavioural aspects of noise management in
parallel with implementing higher-level (technical/engineering) controls.
• Encouraging organisational culture change through the establishment of industry norms and
the cascading of good practice in noise management to the smaller, hard-to-reach
companies. In collaboration with the larger, high performing companies, HSE could agree
such norms and establish an appropriate means of communicating good practice (e.g.
through a noise forum or community that managers could join).
CONTEXT
This research forms part of the Health and Safety Executive’s (HSE’s) long-term strategy for
the prevention of noise-induced ill health at work. As with other long-latency health conditions
(e.g. asthma, cancer), noise-induced hearing loss (NIHL) may not reach a disabling stage until
later in life, potentially leading employers to overlook the immediate need to control noise risks.
Anecdotal evidence available to HSE suggests a general lack of acceptance amongst employers
of NIHL as a significant occupational health issue, and limited action on their part to reduce
noise levels. Whilst previous research has documented factors that influence management
behaviour, this mostly concerns general health and safety management than noise management
per se. To our knowledge, none has systematically assessed the specific knowledge, attitudes
and beliefs that employers hold about noise and the influence of social, environmental and
organisational factors, such as health and safety culture. This study extends the current
evidence base through isolation of the individual, environmental and social factors that are
pertinent to noise management. In addition, it identifies those factors that are key for
v
distinguishing between high and low performing companies. Such knowledge is valuable for
HSE and industry in determining how best to improve the management of noise risks. The
manufacturing sector was the focus of this research due to the high levels of noise that
characterise the industry. Manufacturing consists of approximately 3.2 million employees;
hence a substantial number of people are potentially exposed to unacceptable levels of noise.
APPROACH
A mixture of methods was used in this study to fully answer the three research questions. A
questionnaire developed during a preceding pilot study was completed by 215 managers to
identify the influential factors, including how these vary between high and low performing
companies, and to gauge their potential level of influence. Interviews were also carried out with
15 managers to provide rich accounts of noise management in practice. Combining both
methods enabled a clearer picture to be developed of the real influences on noise management
than would be possible with one method alone. Using mixed methods also enhances the
robustness of the research because it allows the findings from one source to be crosschecked
with the other. The key messages from this research are consistent across participants and
settings, which instils confidence that the findings present an accurate picture of the influences
on managers responsible for noise in the manufacturing sub-sectors that participated in this
research 2 .
2
I.e. (1) food and beverages, (2) textiles, (3) wood/products of wood, (4) pulp/paper products, (5) printing, (6)
rubber/plastic products, (7) other non-metallic minerals and (8) furniture.
vi
CONTENTS 1 INTRODUCTION......................................................................................... 1
1.1
Issue addressed ...................................................................................... 1
1.2
Research aims......................................................................................... 1
1.3
Background ............................................................................................. 1
2 METHODOLOGY........................................................................................ 4
2.1
Research design...................................................................................... 4
2.2
Sample and data collection procedure..................................................... 6
2.3
Analysis techniques ................................................................................. 9
3 RESULTS ................................................................................................. 13
3.1
What factors influence managers’ decisions and practices in controlling
noise risks? ...................................................................................................... 13
3.2
What is the relative importance of these factors? .................................. 25
3.3
How do these factors vary between high and low performing organisations? .................................................................................................. 27
4 DISCUSSION AND CONCLUSIONS........................................................ 35
4.1
Response to the three research questions ............................................ 35
4.2
Interpretation of results .......................................................................... 35
4.3
Research caveats .................................................................................. 37
4.4
Issues for consideration......................................................................... 38
4.5
Overall conclusion ................................................................................. 42
5
REFERENCES.......................................................................................... 43
APPENDICES .................................................................................................. 46
Appendix 1 Summary of fact-finding results......................................... 47
Appendix 2 Pilot study methodology ...................................................... 55
Appendix 3 Questionnaire ........................................................................ 59
Appendix 4 Interview protocol ................................................................. 67
Appendix 5 Supplementary material - Sampling ................................. 71
Appendix 6 Supplementary material – Data analysis ........................ 74
Appendix 7 Supplementary material - Results .................................... 76
vii
viii
1
1.1
INTRODUCTION ISSUE ADDRESSED
Anecdotal evidence available to the Health and Safety Executive (HSE) suggests that employers
need to do more to ensure that the risks associated with noise exposure are adequately
controlled to prevent employees from developing debilitating health conditions in the future, or
the worsening of conditions amongst those already suffering. It seems that employers do not
always engage in good practice for noise control despite the information and advice available in
HSE publications on noise 3 and on the HSE website. This research was commissioned by HSE
to provide an understanding of how to influence employers to better manage noise, ideally
going beyond the provision of hearing protection to the adoption of technical (engineering)
and/or organisational controls.
1.2
RESEARCH AIMS
This research aims to identify the factors that influence managerial noise decision-making and
practices and to ascertain how influential their effects are. In the context of the Health and
Safety at Work Act (1974 4 ), behaviours pertinent to noise control include: the uptake of
technical and organisational control measures; the purchase of low noise tools and/or
machinery; and the use of health surveillance and provision of hearing protection. It is expected
that some employers will demonstrate high performance and thus exhibit most, if not all, of
these behaviours. Conversely, other employers may demonstrate low performance by relying
on hearing protection when other technical solutions could be considered. Examining
differences between high and low performing companies provides HSE with valuable
information for designing interventions aimed at reducing noise exposure.
The following three research questions will be addressed:
1. What factors influence employers’ decisions and practices in controlling noise risks?
2. What is the relative importance of these factors?
3. How do these factors vary between high and low performing organisations with regard
to controlling noise risks?
The findings will be used as a basis for suggesting appropriate behaviour change
interventions/messages for HSE to consider when designing future noise interventions.
1.3
BACKGROUND
This research forms part of HSE’s long-term strategy for the prevention of noise-induced ill
health at work. Noise is known to be associated with a number of ill health outcomes including
non-auditory effects, such as accidents, cardiovascular morbidity and work-related stress (e.g.
1), and auditory effects, namely, tinnitus and hearing loss, which can be temporary or
permanent. Permanent hearing loss can be caused immediately by sudden, extremely loud,
explosive noises or prolonged exposure to excessive noise levels (2). Hearing loss is usually
gradual due to prolonged exposure to noise. It may only be when damage from working in
3
e.g. Health and Safety Executive (2005). Noise at Work; Guidance for employers on the Control of Noise at Work
Regulations. HSE Books.
4
See www.hse.gov.uk/legislation/hswa.htm
1
noisy conditions over the years combines with hearing loss that forms part of the natural ageing
process that people realise how deaf they have become. As with other long-latency health
conditions (e.g. asthma, cancer, Chronic Obstructive Pulmonary Disease), the tendency for
noise-induced hearing loss to remain generally unnoticed until later in life may mean that
employers overlook the immediate need to control noise risks. Discussion with HSE inspectors
at the outset of this research highlighted the following as common observations during their
interactions with dutyholders/managers on noise:
• Lack of acceptance of noise-induced hearing loss as a significant occupational health
issue;
• Lack of application of technical/engineering and organisational noise controls,
including health surveillance for employees considered to be at risk;
• Failure to access and understand available information on noise control;
• Failure to produce an action plan to reduce noise exposure levels; and
• Misunderstanding of the true cost, business benefits, ease of introduction and
effectiveness of technical control compared with the provision of hearing protection.
Understanding the drivers behind these perceptions and behaviours is vital for knowing how to
intervene in order to make improvements. A review of the contemporary evidence base as part
of this research highlighted, however, a paucity of studies directly examining factors that
influence noise management. Most studies on noise were employee-focused, looking at the
impact of noise on health and performance (e.g. 3-5) or the physiological effects of noise (e.g. 6,
7). Although a small number of studies addressed factors influencing the management of noise
(e.g. 8-10), none had systematically assessed the specific knowledge, attitudes, values and
beliefs that employers hold about noise and the influence of social, environmental and
organisational factors, such as health and safety climate/culture. For this reason, the general
health and safety literature was reviewed in order to extrapolate all the factors that potentially
play an important role in the management of noise. The review identified 17 factors as having
the potential to influence noise management, although these studies tended to focus on safety
rather than health matters. The factors broadly fell under five overarching categories: (i)
business (e.g. corporate reputation; 11, 12), (ii) legal (i.e. compliance with health and safety
legislation; 13, 14), (iii) cultural/organisational (e.g. company values, health and safety
resources; 15-19), (iv) external (e.g. information/communications; 20, 21) and (v) personal
drivers (e.g. risk perception, managerial knowledge and competence; 11, 18, 22-24). The
importance of these factors was unclear, however, as few studies had documented their relative
strength. (The full literature review can be found in the accompanying Annex to this report).
The literature review findings were substantiated by anecdotes of noise management in practice
provided during interviews with a sample of six HSE inspectors. Taking two of the five
overarching categories that emerged from the literature review as examples, namely, (i)
potential ‘business drivers’ and (ii) ‘organisational/cultural’ drivers, inspectors’ anecdotes
highlighted that for ‘business drivers’, fear of civil claims appeared to be more influential in
recent years for motivating managers to implement noise controls than health and safety
legislation. Achieving internal quality standards was also considered to exert greater influence
than maintaining a good external reputation where health matters were concerned, particularly
in large companies. Finally, employers often judged the cost and disruption to the business of
controlling noise at source (e.g. retrofitting noise controls to existing machines) as being too
great and thus resorted to issuing hearing protection.
Anecdotes relating to
2
‘organisational/cultural’ drivers revealed a common characteristic in organisations taking
positive steps to control noise risks, i.e. the presence of a positive health and safety culture
integrated with the business process. Companies considered to be effectively managing noise
risks had senior management commitment to health and safety, a strong ethos of looking after
the workforce and open channels of communication between management, workers and unions
(where present). Conversely, employers in companies with a less mature health and safety
culture tended to view hearing loss as inevitable.
Of the 17 factors that emerged from the literature review, two were not considered by inspectors
as pertinent to occupational health matters like noise, namely ‘previous experience of a serious
accident and/or enforcement’ and ‘environmental’ influences in terms of organisational
hardware, rather than the social environment or culture. Taken together the findings from this
preliminary fact-finding (literature review and inspector interviews) identified 15 factors as
potentially influencing managerial noise decision-making and practices, as shown in Box 1.
This initial fact-finding provided a strong, scientific grounding for the design and conduct of the
research by following a systematic process for the inclusion of factors potentially pertinent to
noise management. (See Appendix 1 for further details.)
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Knowledge, awareness and understanding (of noise risks and controls)
Attitudes towards health and safety (e.g. commitment, fatalism)
Values and beliefs (e.g. concern for the well being of employees)
Self-efficacy (i.e. confidence in own ability to implement noise controls)
Noise risk perception
Workplace characteristics (e.g. company size, managerial role)
Skills/competence (to develop noise action plans, etc)
Resources (i.e. time, staff, equipment, funds available)
Capability of making improvements (or going beyond the provision of PPE)
Information and communications (e.g. sources used and usefulness)
Compliance/legislation (i.e. fear of enforcement or civil proceedings)
Safety climate/culture (e.g. company values, communication channels)
Corporate reputation (both internally and externally)
Economic/financial (e.g. civil claims, insurance premiums)
Control (i.e. autonomy to make noise-related decisions)
Box 1 Factors identified as influential for noise management during fact-finding
research
3
2
2.1
RESEARCH DESIGN
2.1.1
Overview
METHODOLOGY
A multi-method design utilising both quantitative and qualitative methodologies was adopted.
Questionnaires represented the quantitative component, and semi-structured interviews,
supplemented by additional data gathered through site tours and reviewing relevant health and
safety documentation, formed the qualitative element. Conducting semi-structured interviews
in parallel with sending out a questionnaire enabled a clearer picture to be developed of the real
influences on noise management, including an understanding of important contextual issues
than would be possible via questionnaire alone. As De Waele and Harre (25) stated:
“By taking participants’ interpretations more seriously we avoid the falsification of reality
which occurs when self reports are confined to the replies to questionnaires, etc., which have
been designed in advance by the investigator”.
To ensure that the results from the quantitative component did not unduly influence the
qualitative findings (e.g. themes being extracted that supported the factors emerging from the
questionnaire analysis), each component was completed by different researchers who derived
their conclusions separately. Together, the two researchers compared and contrasted the key
findings from both components. This level of rigour in data analysis enabled the benefits of
triangulation 5 to be realised. This includes better measurement through minimising threats to
internal validity, enabling a better understanding of how and why factors exert their influence,
and generating more reliable and valid results (e.g. 26).
2.1.2
Research stages
There were three key stages to the research.
Stage 1 - Preliminary fact-finding. As described in section 1.3, fact-finding included a literature
review and interviews with six HSE inspectors. A systematic method was followed for the
literature review to assess the relevance and quality of the available research and to gauge the
potential strength of factors reported to influence managerial health and safety practices (see the
accompanying Annex to this report). To increase the likelihood of obtaining an accurate
reflection of current noise practice, HSE inspectors were selected for interview that had
differing levels of experience with dutyholders in relation to noise management 6 , and were
based in different regions of the UK. A semi-structured format was followed to ascertain the
noise controls implemented and types of behaviours seen in two organisations visited; one
considered by inspectors to demonstrate good practice and the other showing a need for
improvement. Five interviews were conducted face-to-face, one via videoconferencing, lasting
between 50 and 85 minutes. Factors were extracted during thematic analysis of the data where
the majority of inspectors (at least three) perceived these as influential for noise management.
To minimise interpretation bias, two researchers conducted the analysis and checked one
another’s outputs.
Stage 2 – Design and piloting of research tools. Following approval of the research by HSE’s
Research Ethics Committee, the tools were piloted via 10 telephone interviews with dutyholders
5
‘The use of more than one method or source of data in the study of a social phenomenon so that findings may be
crosschecked’ [27].
6
Two specialists, two generalists and two occupational health inspectors took part. 4
or the manager responsible for health and safety 7 , seven of whom subsequently completed the
questionnaire (see Appendix 2 for further details on the methodology). A primarily qualitative
approach was considered appropriate at this stage of the research to obtain rich data about the
adequacy of the research tools for answering the three research questions (see section 1.2). It
also provided a check as to whether the tools were appropriately worded and fit-for-purpose, not
too time-consuming for dutyholders/managers. In general, the findings highlighted the benefit
of triangulating findings from the quantitative and qualitative components to generate valuable
insights into the influences on noise management.
Stage 3 – Main research. Fifteen semi-structured, in-depth interviews with dutyholders or
managers responsible for noise were conducted. In addition, 800 postal questionnaires were
distributed to a representative sample of 15 manufacturing sub-sectors. The remainder of this
report describes the methodology adopted and the findings from the main research phase.
2.1.3
Questionnaire design
Following best practice in survey design the questionnaire took around 15-20 minutes to
complete (see Appendix 3). It consisted of mostly closed items with Likert scales, appropriate
for attitudinal and behavioural ratings (28). The questionnaire was designed around the 15
factors that emerged from the fact-finding research as potentially important determinants of
dutyholders’ noise decision-making and practices (see section 1.3). A minimum of three items
per factor was included to obtain reliable measures. Three of the 15 factors were merged with
the remaining 12 factors, as shown in Box 2. ‘Values/beliefs’ and ‘noise risk perception’ were
subsumed under ‘attitudes towards health and safety’ and ‘capability of making improvements’
naturally formed part of an assessment of ‘resources’. Streamlining the original 15 factors into
12 ensured that the questionnaire was comprehensive yet sufficiently brief.
1. Knowledge, awareness and understanding (of noise risks and controls)
2. Attitudes towards health and safety (values and beliefs and noise risk perception
e.g. commitment, fatalism, concern for employee well being)
3. Self-efficacy (i.e. confidence in own ability to implement noise controls)
4. Control (i.e. autonomy to make noise-related decisions)
5. Skills/competence (to develop noise action plans, etc)
6. Resources (capability to make improvements e.g. time, staff, equipment, funds)
7. Information and communications (e.g. sources used and usefulness)
8. Compliance/legislation (i.e. fear of enforcement or civil proceedings)
9. Safety climate/culture (e.g. company values, communication channels)
10. Corporate reputation (both internally and externally)
11. Economic/financial (e.g. civil claims, insurance premiums)
12. Demographics (e.g. company size, managerial role)
Box 2 Twelve factors measured by the questionnaire (bold represents merged
factors)
Appropriate outcome measures (dependent variables) were included for (i) perceived noise
exposure levels (i.e. self-reported ratings of noise levels experienced by workers during the
7
Although the research targeted dutyholders, in some cases dutyholders had delegated noise decision-making to one
of their managers. As such, the decision was made to interview the manager responsible for health and safety,
dutyholder or otherwise.
5
most common noisy activities 8 ), (ii) perceived noise risks (i.e. the proportion of the workforce
carrying out these noisy activities), and (iii) implemented noise controls (a selection of controls
ranging from employee-focused to environmental modifications to technical/organisational).
Both face and content validity 9 of the questionnaire was tested during the pilot study and
through liaison with key project stakeholders. Testing the construct validity and reliability 10 of
the measure formed part of the data analysis (see section 2.3.2).
2.1.4
Interview protocol design
A semi-structured interview protocol was developed that provided the opportunity to gather rich
data relating to dutyholders/managers noise decision-making and practices (see Appendix 4).
Such an approach allows a balance to be struck between consistencies across interviews to
facilitate comparison with scope for further probing as necessary (29). The questions were
designed to elicit insights into the 15 factors that emerged through the fact-finding research
whilst being flexible enough to uncover any new factors. Topic areas included noise exposure
levels and controls, the decision-making underpinning the selection of controls, noise
information/training provided to staff, resources and support for implementing noise controls.
2.2
SAMPLE AND DATA COLLECTION PROCEDURE
The research was conducted in the manufacturing sector due to the high levels of noise that
characterise the industry. The sector consists of approximately 3.2 million employees 11 ; hence
a substantial number of people are potentially exposed to unacceptable levels of noise at work.
2.2.1
Questionnaire
Sample calculations. Given that this research aims to identify and determine the strength of
factors that influence noise management, the sample size was chosen on the basis of power
calculations. This reduces the likelihood of committing a Type II error with smaller sample
sizes, i.e. incorrectly concluding that a given factor does not impact the behaviour of employers
(30). Nevertheless, a Type I error remains likely due to the small sample size, i.e. a factor is
shown to be influential (i.e. significant) when it might not be with a larger sample. Power
calculations were based on a medium effect size: the average size of observed effects in various
field studies shown in surveys of effect sizes (31). To achieve the desired power of 0.8
recommended by Cohen, a sample size of at least 200 was required for the planned quantitative
analysis (see section 2.3.2), 200 to run the regression analysis and a minimum of 50 participants
in each of the high and low performing groups (31). Distributing 800 questionnaires was
considered sufficient to obtain the desired 200 responses. Response rates for employee postal
surveys generally fluctuate between 30-50% (e.g. 32, 33). A 25% response rate allows for the
possibility that noise may not be as high profile in companies as other health and safety
concerns.
Sample selection. Fifteen manufacturing sub-sectors were chosen to take part in this research in
order to establish views from a broad sample and permit greater confidence that the findings
accurately represent these sub-sectors. Each sub-sector was classified as either ‘metallic’ or
‘non-metallic’ as shown in Table 1. A random sample of approximately 7,000 companies
8
Level 1 - impossible to talk even when shouting in someone’s ear; Level 2 - having to shout at a distance of one meter; Level 3 - having to shout at a distance of two meters; Level 4 - noise is intrusive, comparable to a busy street. 9
Face validity - It is obvious what it is measuring; Content validity - The content is representative of the area it intends to cover [28].
10
Construct validity – An accurate measure of the underlying construct(s) i.e. hypothetical constructs, [28]. 11
See www.eef.org.uk
6
representing the 15 manufacturing sub-sectors was obtained through HSE’s Library and
Information Services, taken from the MINT database 12 , which provides sufficient coverage of
the UK private sector. Of the 800 questionnaires distributed, the sample was stratified to ensure
that the number sent out to each metallic and non-metallic sub-sector was proportionate to their
overall size; companies were randomly selected within each sub-sector. 302 questionnaires
were administered to metallic companies and 498 questionnaires to non-metallic companies (see
Table A5.1 in Appendix 5 for further details). To reflect the demographic make up of the
manufacturing sector, mostly consisting of small companies 13 (with up to 49 employees 14 ), no
more than 5% of questionnaires were sent to medium-sized (50-249 employees) and large (250
plus employees) metallic (n=15) and non-metallic (n=25) companies. None of the 800
companies had experienced HSE enforcement action in the last two years or had previously
taken part in the pilot study.
Table 1 Metallic and non-metallic sub-sector groupings
Metallic (SIC 15 Code)
Basic Metals (27)
Fabricated metal products (28)
Machinery and equipment (29)
Motor vehicles & trailers (34)
Other transport equipment (35)
Recycling (37.1)
Non-Metallic (SIC code)
Food and Beverages (15)
Textiles (17)
Wood/Products of wood (20)
Pulp/Paper products (21)
Printing (22)
Rubber/Plastic products (25)
Other non-metallic mineral (e.g. glass & ceramics) (26)
Furniture (36.1)
Recycling (37.2)
Administration procedure. All questionnaires were addressed to ‘the manager responsible for
health and safety’. An information sheet accompanied the questionnaire detailing the purpose
of the research, what participation involves and how the data will be used with assurances of
anonymity and confidentiality (see Appendix 3). The use of unique numbers as identifiers
permitted participants to withdraw from the research at any time 16 . Participants were asked to
complete the questionnaire and return it to a member of the research team in a freepost envelope
provided within a given timeframe. To encourage participation, a £5 donation was made to one
of four relevant charities as chosen by participants.
Response rates. Of the 800 postal questionnaires distributed, only 47 completed questionnaires
were returned; a further 148 were returned to sender 17 (a response rate of 7%). Follow up
telephone calls with a random selection of 80 of the 605 companies who had not returned the
questionnaire revealed that a large number were either not manufacturing companies or were
sole traders, the questionnaire therefore not being relevant to them. In order to obtain a
minimum of 200 completed questionnaires, an additional 168 questionnaires were completed
via telephone through an external contractor using an additional sample of 2,000 companies
sourced through Dunn and Bradstreet. Of the 2,000 companies, 1,443 were contacted (a
response rate of 12%). The same stratified sampling procedures were applied. In total, 215
questionnaires were completed (47 postal, 168 telephone). The obtained sample was fairly
12
A public database containing approximately 2.6m UK-wide company records. See http://www.statistics.gov.uk
14
Based on the Department of Trade and Industry’s definitions of company size - see http://www.sbs.gov.uk
15
Standard Industrial Classification code (manufacturing industry). 16
The questionnaire and associated information sheet were given the same number; participants were asked to retain
the latter and quote the number should they wish to withdraw. 17
From businesses ceasing to exist, non-manufacturing companies or sole traders. 13
7
representative of the metallic and non-metallic sub-sectors surveyed, although no responses
were obtained from recycling companies (see Figures A5.1 and A5.2 in Appendix 5). It is
noteworthy that 57 companies belonged to other manufacturing sub-sectors (e.g. windows, sign
makers) or non-manufacturing sub-sectors (e.g. construction, engineering, aerospace)
highlighting inaccuracies with SIC code assignment in the both sample databases. Box 3
provides a snapshot of participating companies.
• Mostly manufacturing companies
• 187 small companies, mostly micros with up to ten employees (n=107); 24
medium-sized and 4 large companies
• 97 Directors/Owners; 28 senior managers; 35 H&S managers; 40 managers; 2
supervisors; 9 works/production managers
• Mostly not part of a larger group (n=173)
• Mostly not unionised/no TU representative in the company (n=195)
Box 3 Demographic profile of the 215 companies that completed the questionnaire
2.2.2
Site interviews
Sample selection and recruitment. To ensure that companies had not had their level of
awareness raised by having been involved in previous aspects of the research, 15 companies that
were not issued a questionnaire were randomly selected for interview from the MINT sample.
The aim was to recruit two small, two medium-sized, and two large companies from both the
metallic and non-metallic groupings (12 in total), with the remaining three randomly selected
from small companies in either the metallic or non-metallic categories. To ensure that the
findings adequately addressed the 15 sub-sectors (see Table 1), attempts were made to secure
one visit for each sub-sector (or SIC code). Dutyholders/managers did not volunteer, however,
from Metallic – recycling (37.1) and other transport equipment (35), Non-metallic – textiles
(17), printing (22) and furniture (36.1). Consequently, three metallic companies were recruited
from machinery and equipment (29), two from basic metals (27), and two from fabricated metal
products (28). Two companies were further recruited from the other non-metallic mineral (26)
sub-sector. Although representation from all 15 sub-sectors was not obtained, the sample is
considered to be fairly representative of the metallic and non-metallic sub-sectors sampled.
Those sub-sectors where more than one company was recruited tended to represent the larger
industries (e.g. machinery and equipment, fabricated metal products 18 ). A good spread of UK
geographic regions was also obtained. Nevertheless, difficulty recruiting small companies 19
resulted in a substantial proportion of the sample (n=7) being medium-sized companies. (See
Table A5.2 in Appendix 5 for full details.)
Companies were recruited over the phone. Employers who volunteered to take part provided
written consent and were provided with an information sheet detailing the purpose of the
research, data use and storage, protection of anonymity and confidentiality.
Site visit procedure. Visits generally lasted between 30 and 90 minutes. Following an initial
site tour in which researchers collated contextual information relating to noise management,
dutyholders/managers were interviewed on their premises for up to 90 minutes. With
participants’ consent, interviews were recorded and transcribed. Finally, researchers examined
relevant health and safety documentation (health and safety policy, risk assessments, etc)
pertinent to noise control.
18
19
See www.statistic.gov.uk
Lack of time was the key barrier to participation cited by employers.
8
2.3
ANALYSIS TECHNIQUES
2.3.1
Overview
Figure 1 provides an overview of the analysis conducted to address each of the three research
questions. Both quantitative and qualitative techniques were applied to the first and the final
research question. Quantitative analysis enabled the factors that have a significant influence on
noise management and those that differed between high and low performers to be identified.
Qualitative analysis provided further insight into how and why the factors uncovered through
the quantitative analysis influence noise management, as well as exploring the influence of any
additional unknown factors. Results for the second research question are solely based on the
quantitative analysis as this concerned strength of effect of the factors. Details of both forms of
analysis are described in the sections that follow.
Influencing factors
(Research Question 1)
• Quantitative: Frequencies,
Correlations and Regression
• Qualitative: Thematic and
Content Analysis
Importance
• Quantitative: Regression
High versus low
performers
• Quantitative: Mann Whitney-U
Tests
• Qualitative:
Thematic and
Content Analysis
Figure 1 Summary of analysis conducted to answer each research question
2.3.2
Quantitative
Research question 1 - Influencing factors. Correlations were conducted to check whether the
conceptualisation of 11 of the 12 factors identified as having the potential to influence noise
management in the fact-finding research (see section 2.1.3) was supported by the data.
‘Workplace characteristics’ were excluded (factor 12), as these were categorical and thus not
suitable for correlation analysis. A factor analysis would have provided a robust test on the
factor structure and the extent to which they were mutually exclusive. There was an insufficient
number of questionnaires returned, however, to permit a reliable and valid exploratory factor
analysis (34). To compensate, internal consistency tests were run to check that the items
making up each of the 11 factors were reliably measuring that factor. In addition, two
(construct) validity tests were conducted in which (i) a second researcher crosschecked the first
researcher’s categorisation of questionnaire items for each factor, and (ii) a third independent
researcher (not involved in the research) examined items falling under each factor to assign a
name to each factor.
To test whether the 11 factors significantly influence managerial noise decision-making and
practices a multiple regression was conducted. A statistical (stepwise) method was selected, as
no established theoretical model of the influences on noise management existed. The outcome
9
(dependent) measure was a calculated score for ‘implemented noise controls’; a subjective
indicator that reflected the extent that dutyholders/managers have gone to in order to protect
their employees from noise risks. A score out of a total of 22 was assigned based on
respondents’ answers to the item asking them to tick all the noise controls that they provided. A
higher score denoted the use of higher-level, technical/organisational controls and a lower score
showed that minimal action had been taken by the dutyholder/manager, mostly implementing
worker-focused (basic) controls. This scoring accounted for the selection of up to three red
herrings i.e. non-viable noise controls, which were included to gauge participants’ propensity
towards social desirable reporting (i.e. tendency to respond in a way that makes them “look
good” (28). (See Table A6.1 in Appendix 6 for scoring.)
Descriptive analysis (frequencies and crosstabulations) was carried out on items not suitable for
regression (e.g. scenario-based questions to measure participants’ knowledge and awareness 20 ).
Research question 2 – Importance of factors. The regression outputs were examined to see how
much variance each factor explained in implemented noise controls and whether their unique
and combined contribution was significant. Beta coefficients determined the predicted levels of
improvement in implemented noise controls based on one unit increase in each factor.
Research question 3 - High versus low performers. As shown in Table 2, participants were
categorised into three groups, ‘high’, ‘moderate’ or ‘low’ performers, based on two scores:
i.
The outcome measure of ‘implemented noise controls’, a score out of 22. There was
some degree of overlap between the high and low categorisation for companies that
obtained scores ranging from 9 to 13. This overlap was considered acceptable on the
premise that a score higher than 8 was unlikely if only basic controls had been
implemented 21 and a score higher than 13 was unlikely unless higher-level controls had
been implemented 22 . As such, companies obtaining a score between 9 and 13 were
more likely to be moderate performers. But, level of risk alongside implemented
controls is important to differentiate between low and high performers. After all,
implementing basic noise controls may be acceptable if noise levels are low or very few
workers are exposed to noise.
ii.
A second outcome measure estimating ‘risk to the business from noise’ based on
perceived noise levels and the proportion of workers exposed to this noise. Companies
were assigned to one of six categories and therefore obtained a score ranging from 1 to
6 depending on where they sat on the ‘risk to the business from noise’ continuum. A
score of 1 represented the highest risk (i.e. excessive noise levels with a high proportion
of workers exposed). Conversely, a score of 6 represented the lowest risk (i.e. low
noise levels and proportion of workers exposed). (See Figure A6.1 in Appendix 6 for
categorisation.)
Company classification. As shown in Table 2, high performing companies (shaded green) were
defined as those that had implemented higher-level (technical/organisational) controls despite
noise levels and worker exposure being perceived as ‘low’. On the other hand, low performing
companies (shaded red) presented a high risk to employee health from noise yet tended to only
have basic controls in place. The remaining companies were classified as ‘moderate’
performers. Performance was therefore a composite of the ‘level of risk’ and ‘implementation
of controls’. Contrasting high and low performers in this way highlighted practices associated
with better performance. Rather than issuing the small proportion of their workforce exposed to
20
Questions 9 and 10 in the questionnaire (see Appendix 3).
There were eight basic controls in the questionnaire, each given a score of 1 if selected/implemented. 22
There were seven higher-level controls in the questionnaire, each given a score of 2 if selected/implemented. 21
10
noise with hearing protection, these companies had focused on noise reduction methods or were
trying to eliminate noise from source. Intuitively, there appeared to be something culturally
unique about these companies that distinguished them from the remaining groups, which were
either doing what was necessary to comply (moderate performers) or were not adequately
controlling noise risks (low performers). Further analysis was conducted to compare the high
and low performers with the group of moderate performers (shaded yellow in Table 2) where
noise presented a low risk to the business and worker-focussed controls were in place (mostly
hearing protection). No differences emerged, however, between the low and moderate
performers suggesting few differences in the practices of these companies. To gain an
understanding of the differences between high and low performers the final analysis excluded
the moderate performers.
In line with the recommendation that a non-parametric test should be conducted when data is
not normally distributed and equal variances between the groups cannot be assumed (35), a
series of Mann Whitney-U tests were conducted to compare the high and low performers. This
enabled isolation of the factors that differentiated between the high (n=60) and low (n=50)
performing companies.
Table 2 Categorisation of ‘high’ (H), ‘moderate’ (M) and ‘low’ (L) performers
‘Risk to the business from noise’
Highest risk (1)
High risk (2)
High to medium risk (3)
Medium risk (4)
Medium to low risk (5)
Low risk (6)
2.3.3
‘Implemented noise controls’
Up to ‘13’
‘9’ to ‘22’
M
L
M
L
M
L
M
M
M
M
H
M
Qualitative
Research question 1 - Influencing factors. Two types of qualitative analysis were conducted i.e.
thematic and content. The former provided rich detail about influences on noise management
through the extraction of higher-order and sub-themes. The latter enabled a systematic
assessment of the frequency of the higher-level themes across participating companies, which
provided a practical base from which to examine differences between company groupings (e.g.
small versus medium/large companies, high versus low performers).
For the thematic analysis, key themes were identified following a framework analysis approach
for qualitative data that is advocated by the National Centre for Social Research, referred to as
NatCen’s qualitative analysis protocol (36). This comprised three stages. The first two stages
involved development of a framework for capturing commentary and quotations from the
management interviews. Relevant data gathered from the site tour and review of company
health and safety documentation was also incorporated. Higher-level themes and sub-themes
were then identified and agreed between two researchers to ensure valid analysis of the data
(inter-rater reliability; see 37). The final stage of the analysis involved identification of any
patterns in the data according to company groupings (e.g. size, performance levels).
The content analysis was conducted by a sole researcher and checked by a second researcher.
All companies were colour coded according to whether the higher-order themes that emerged in
the thematic analysis (stage 1 of NatCen) were present in the data or not. Key differences
between companies of different sizes (small, medium, large) were extracted.
11
Research question 3 - High versus low performers. The classification of company performance
levels as high, moderate or low was based on predetermined criteria (see Table A6.2 in
Appendix 6) and steps were taken to minimise the impact of researcher bias. Criteria included
performance levels assigned by visiting researchers shortly after each visit, performance
decisions based on all available evidence (interview, site tour, documentation review), and all
performance classifications crosschecked by a second and third researcher. Once companies had
been classified as high, moderate or low performers, any differences in the higher-level and sub
themes were identified. This formed part of the final stage of the NatCen approach. In addition,
key differences between high and low performing companies were extracted as part of the
content analysis.
12
3
RESULTS Results are presented for each research question in turn. For the first and final research
questions the results from the quantitative and qualitative analysis are presented separately. Key
findings that emerge from both forms of analysis are then summarised as top-level findings.
Results for the second research question are solely based on the quantitative analysis.
3.1
WHAT FACTORS INFLUENCE MANAGERS’ DECISIONS AND
PRACTICES IN CONTROLLING NOISE RISKS?
3.1.1
Quantitative results
3.1.1.1
What are the influencing factors? Correlation results
The correlation matrix showing all correlations between all items in the questionnaire revealed
correlations ranging from r=0.2-0.4 between a number of items belonging to different factors.
Internal consistency checks of the items making up each factor also showed that only two
(‘knowledge and awareness’ and ‘resources’) of the 11 factors input into the analysis had
sufficient internal consistency (i.e. a Cronbach’s Alpha of 0.7 or above, 38). The remaining
nine factors therefore contained items that did not highly correlate, indicating that they did not
reliably measure the same factor (or underlying construct). (See Table A7.1 in Appendix 7 for
internal consistency results.) Following close inspection of the correlation matrix, the 11 factors
were collapsed into eight and renamed. Table 3 defines each of these eight factors and also
includes three important demographic items, namely, (i) company size, (ii) role as
Director/company owner, and (iii) role as Health and Safety Manager. (See Table A7.2 in
Appendix 7 for a breakdown of responses to the demographic items.)
Internal consistency results for each of these eight factors were acceptable. Five of the eight
factors achieved a Cronbach’s Alpha of 0.7 or above. Although the internal consistency of the
remaining three factors (i.e. ‘attitudes, values and beliefs’, ‘organisational health and safety
values’, and ‘business motivators’) was below the standard aspired to in conventional test
design, each had a Cronbach’s Alpha of at least 0.5, indicating moderate correlations between
the items that make up these three factors. The marked improvements observed in the internal
consistency of these eight factors from the original 11 factors offers some evidence that the
items falling under each factor reliably measure the same factor (see Table A7.1 in Appendix 7).
A second researcher not involved in the research provided an additional check on construct
validity. From examining the questionnaire items that made up each factor, the researcher
independently assigned each factor a name. The names assigned supported those made by the
principal researcher.
13
Table 3 Final factor definitions and changes following correlations
Factor name
1. Knowledge and
awareness
2. Attitudes towards
protecting workers
against noise risks
3. Self-efficacy
4. Autonomy and
competence
5. Resources
6. Information and
communication
7. Organisational
health and safety
values
8. Business motivators
9. Company size
10. Role as Director/
owner
11. Role as Health &
Safety Manager
Definition
Managers’ own knowledge and
awareness
of
technical
and
organisational solutions to reduce
noise, including training received
Managers’ own attitudes about
protecting their workers from noise
risks (e.g. whether wearing hearing
protection alone is enough)
Managers’ own beliefs/confidence in
their ability to manage noise risks
Whether managers are doing what
they know they should be doing to
control noise risks.
Includes
interpersonal skills, technical skills
and autonomy given to put these
skills into practice and/or make own
decisions about improvements
Time management, effort, money and
staffing barriers to noise control.
Includes feasibility and cost of
implementing technical solutions
Information/guidance
managers’
seek/receive on noise, including
information on health surveillance
‘The way we do things around here’,
includes
senior
management
commitment
to
eliminating/
minimising noise risks, reactive
versus
proactive
culture,
prioritisation of worker health
Motivated by compliance, potential
benefit of investment in human
capital,
fear
of
civil
proceedings/prosecution
Micro (up to 10 employees) versus
small (11-49), medium (50-249) and
large (250 plus)
Director/owner
versus
other
managerial roles
Health and Safety manager versus
other managerial roles
23
Change following
correlations
Includes items from original
factors – ‘values & beliefs’,
‘attitudes’
and
‘risk
perception’
One item from original
‘control’ factor added 23
‘skills/competency’
factor,
two items from original
‘control’ factor 24 and one item
from original ‘compliance
with legislation’ factor 25
‘capability
of
making
improvements’ factor
Removed one item 26
Includes two items from
original ‘reputation’ factor 27
Includes two items
original ‘compliance
legislation’ factor 28
from
with
-
‘The company is run by a few people. There is not much that I can do about noise issues’. ‘I can influence noise management in this company; Nothing stops me from tackling noise issues in my company’. 25
‘We try our best to comply with noise legislation.’ 26
‘We cannot find information on quieter models of machinery/tools we use’. 27
‘We control noise as well as most other companies in our industry; The Director(s) think that worker ill health is a
big risk for the business’.
28
‘We are afraid of the consequences of not complying; Health and safety legislation drives what we do about noise’.
24
14
Correlations between these 11 factors and the outcome (dependent) variable ‘implemented noise
controls’ were mostly significant and moderate (around r=0.3). (See Figure A7.1 in Appendix
7.) This fulfils a critical requirement in order to proceed with a regression analysis. The
remaining assumptions for regression were generally met 29 . Three multivariate outlier cases
were removed, which reduced the sample size for the regression from 215 to 212 cases. Some
attitudinal items showed a slight skew in distribution (mostly positive), but the regression test is
robust enough to cope with this (30). The slight positive skew on attitudinal items may indicate
some degree of social desirability (i.e. participants answering in a way that they think the
researcher might view positively; 28). Social desirability was not detected, however, in
responses to the outcome measure of implemented noise controls; selection of the three red
herrings appeared to be random rather than systematic.
3.1.1.2
What are the influencing factors? Regression results
Results from the stepwise regression showed that three of the 11 factors were significant drivers
of the noise controls that managers chose to put in place [R² = .416. F (3, 191) = 47.144, p =
.001]. These were (i) knowledge and awareness of technical and organisational solutions to
reduce noise, (ii) organisational health and safety values towards eliminating/minimising noise
risks and protecting worker health, and (iii) company size, indicating that the size of a company
influences how they approach noise management. The smaller a company the increased
likelihood of reduced quality in the management of noise risks. Taken together these three
factors provide a moderate prediction of implemented noise controls, accounting for 42% of the
overall variance.
The remaining eight variables 30 were not found to be significant factors as they explained little
of the subsequent variance. This is not to say that they did not contribute towards noise
decision-making and selected controls. The fact that these correlated with the three significant
factors indicated some degree of overlap. What this means, however, is that the small amount
of variance explained by these additional eight variables had already been accounted for by (i)
knowledge and awareness of technical and organisational solutions to reduce noise, (ii)
organisational health and safety values towards eliminating noise risks and protecting worker
health and (iii) company size (smaller versus medium-sized and large companies); hence they
did not explain anything extra. An interpretation of these results is that the three significant
factors could reflect underlying or ‘latent’ factors for noise management, which account for any
influence of the remaining factors. Intuitively this makes sense. After all, health and safety
attitudes are often subsumed within an organisation’s culture, as are the business motivators.
Self-efficacy, autonomy/competence and information/communications could be explained by
knowledge (e.g. managers feeling that that they know enough and are confident with selected
controls). Resources and managerial role intuitively overlap with company size with smaller
companies expected to have fewer resources for health and safety at their disposal.
3.1.1.3
Additional descriptive analysis
Analysis of two additional scenario-based questions was carried out to gauge managers’
knowledge levels in response to (i) a machine/tool being identified as a noise hazard and (ii)
workers needing to wear hearing protection when they did not previously. Responses to these
two items indicated that the vast majority of managers opted for individually-focused controls
29
A sufficient number of cases, linearity, homescedasticity & independence of residuals, absence of univariate outliers, no evidence of multicolinearity/singularity. 30
I.e. (i) attitudes towards protecting workers against noise risks; (ii) self-efficacy; (iii) autonomy and competence; (iv) resources; (v) information and communications; (vi) business motivators; (vii) role as Director/owner; (viii) role
as Health and Safety Manager.
15
with some modification to the work environment. None of the managers out of the 190 who
completed both of these questions selected technical/organisational solutions to resolve both of
these noise matters; only one manager selected technical/organisational solutions for the second
scenario (see Table A7.3 in Appendix 7). This supports findings from the regression outputs
that managers generally lack knowledge of technical and organisational solutions to their noise
problems. Instead, their preference is to rely on hearing protection with some environmental
modifications where physically viable (e.g. setting up hearing plug dispensers, introducing
hearing protection zones, reorganise machinery). Another possible interpretation of this finding
is that managers lack understanding of the advantage of collective over individual controls, or
underestimate the burden required for individual controls.
Further support that managers lacked knowledge of how to resolve their noise issues comes
from the analysis of two other questionnaire items asking managers about (i) information
sources accessed and (ii) how helpful these were for noise management. The top three
information sources utilised by approximately half the managers were (1) the internet, (2)
published HSE guidance and (3) the HSE website; most considered these to be helpful. These
findings demonstrate that despite access and use of HSE guidance/publications/website,
managers still lacked knowledge and understanding about how to manage noise in practice.
Whilst the information they access is generally considered ‘helpful’, there appears to be a gap
between understanding what to do in theory with what to do in practice. The latter requires
knowledge gained from these information sources to be processed and applied to their own
situation, i.e. it requires a higher-level understanding or procedural knowledge gained through,
for example, hands-on experience, practice at solving problems and understanding of the
limitations of specific solutions. Nevertheless, it should be borne in mind that a substantial
proportion of companies ‘rarely’ or ‘never’ accessed these and other sources 31 (see Tables A7.4
and A7.5 in Appendix 7).
It is noteworthy that managers seemed to have difficulty finding information on quieter models
of machinery/tools in use. As shown in Figure 2, over half (n=109 out of the 211) of the
managers who responded to the question could not find information on quieter models. This is
an important finding given that HSE noise guidance highlights the need to include noise in
machinery purchasing decisions, yet managers may not know where to access relevant
information. It is also a concern that almost a third of the sample (n=63) neither agreed nor
disagreed with the statement, given that purchasing ‘quiet’ machinery/tools represents a key
organisational control for reducing noise. Responses to a separate questionnaire item asking
managers how often they access information on noise from machinery suppliers 32 , revealed that
more than half (n=130) of the 212 managers who responded to this question ‘rarely’ or ‘never’
accessed such information. Taken together, an interpretation of these findings is that managers
are either not actively searching for information on quieter machinery/tools through, for
example, the websites of machinery suppliers, or that those searching for such information
might be looking in the wrong place.
31
i.e. Machinery suppliers, HSE inspector, industry guidance, other companies/competitors, insurance companies, direct call to HSE and direct call with local authority. 32
Question 18b (see Appendix 3).
16
Figure 2 Level of agreement with the statement - “We cannot find information of
quieter models of machinery/tools we use”
3.1.2
Qualitative results
Qualitative results are reported in three sections. The first two sections report the themes and
sub-themes that emerged as influencing noise management. There was a clear divide between
whether their influence was externally driven (i.e. originating outside of the company) or
internally driven (i.e. originating within the company). The final section summarises the
findings from a content analysis of implemented noise controls according to company size
(small versus medium and large companies). Findings therefore provide insight into how
companies of different size vary in their approach to managing noise.
3.1.2.1
Internal influences on managerial noise decisions and practices
(i) Managers’ perception of noise risks
A consistent theme across all companies was that managers perceived other health risks (e.g.
dermatitis, manual handling, hand-arm vibration) as being more important or detrimental than
noise risks. Although they did not disregard noise risks completely, managers appeared to have
formed their own personal opinions about their relative importance in relation to other issues
facing their company. In these companies, noise did not represent as significant a risk to the
business compared with other risks, such as manual handling, the effects of which on employee
health are often detected earlier.
“I’d say the bigger health risk is repetitive manual handling.” (Company 11)
“…[noise]…pales into insignificance with things like dermatitis problems caused by the
adhesives…” (Company 13)
The ranking of noise risks also seemed to be influenced by managers’ perception as to whether
it was important to ‘hear’ as part of the production process.
17
“[Noise]… can influence health in terms of if you had a risky situation in the pour for instance
you need to be able to hear, it would be influential then.” (Company 2)
There was a general perception that compared to losing your life or being injured, a reduction in
quality of life was less severe, thus noise was not considered as important. The obvious, safety
risks seem to be taking up managers’ time, which may mean that they have little time left to
deal with health matters such as noise.
“So, in balancing it up against other risks I tend to consider the big physical risks as being your
actual risk to life and limb. From then you have the risks that will affect your quality of life but
you're still alive and that’s where hearing comes in…” (Company 4)
One manager commented that the audio demonstration of noise-induced hearing loss on the
HSE website changed their perception of the importance of hearing loss as it enabled them to
personally relate to the issue.
“…one thing I did use on that was a link on the HSE’s Website, which actually is a small audio
clip that shows the impact of noise induced hearing loss… I think that was quite hard hitting
actually to a lot of people” (Company 10).
Some managers mentioned their concerns over having to pick up the pieces and effectively pay
for hearing damage caused by factors outside of their control. Most noteworthy, were
employees’ use of ipods and attendance of noisy social events, such as concerts.
“I suppose my concern in that sense is how I keep these guys focused enough to realise that they
can do as much damage at home as they are in the workplace. And a concern I guess as an
employer is how … do I divorce that from my process?” (Company 13)
(ii) Decision-making about controls
A recurring theme across participating companies was the perception that solutions may in fact
create new, expensive problems. As such, a major influence on managers’ decision-making to
implement noise controls was whether additional risks would be introduced. In some cases,
however, this seemed to reflect a lack of understanding on the managers’ part of the issues at
hand that should not present barriers to making improvements. For example, one company (10)
found that the type of hearing protection they introduced meant they had to spend extra money
increasing the volume of the fire alarm systems to ensure that their workers could hear the
alarm. Rather than trying to understand the problem, for example, discussing the issue with
their workers to come up with an alternative (potentially less expensive) solution (e.g. replacing
the type of hearing protection), this manager decided to spend money on improving the alarm
system. There was some evidence in other companies, however, of managers taking a holistic
approach when trying to reduce noise levels. For example, one company (5) decided not to use
enclosures because it would mean workers working in a confined space nearby heavy
machinery. In this (packaging) company there were two, large industrial machines filling most
of the largest room in the factory. There was enough space for two machinery maintenance
workers to comfortably walk between and around the machines in the designated aisles. Adding
enclosures would reduce this aisle space. The manager was not comfortable with this as he felt
that it presented the danger of workers brushing against the machines. It was also not possible
to move these machines; no other area of the factory would house them together or separately.
There were also concerns over noise controls impacting on the quality of the goods
manufactured. Evidently, managers were trying to achieve a balance between cost, health and
safety and the welfare of their employees.
18
“Whilst obviously there is always a drive for maximising production and minimising losses, we
always stress that it must be done safely.” (Company 10)
(iii) Managers’ knowledge of how to properly manage noise
The nature of hearing loss. A subtle theme that emerged was managers’ lack of awareness of
the nature of hearing loss and its long latency. This was apparent through the responses that
they gave when asked about the success of their current noise controls. Lack of worker
complaints about hearing damage was considered to be a key indicator of success. Where
noise-related ill health was concerned, managers were only aware of the auditory effects of
noise, i.e. deafness or tinnitus, and lacked knowledge of any potential non-auditory ill health
outcomes, such as cardiovascular morbidity and work-related stress.
Difficulty assessing noise exposure when exposure is intermittent. Managers commented on the
difficulty that they had with measuring noise exposure, particularly when exposure is
intermittent. Most had attempted to undertake some form of noise survey; some had hired a
noise meter and tried to make sense of the data. It seems that managers are generally measuring
and checking noise levels as they felt that this was a requirement of their job and gave them a
feeling of having done something concrete, but did not fully understand whether they were
correctly taking measurements. The issue as to whether they actually needed to take such
measurements in the first place had not occurred to managers. It may be that their own
misunderstanding from reading noise guidance of the need to take regular noise measurements,
including measuring its intermittency, acts as a barrier to managers for putting controls in place.
Accordingly, too much focus is given to diagnosis of noise levels rather than implementation of
controls. As managers have to juggle a number of roles, noise surveys were not something that
they tended to do on a regular basis. Whilst they might be confident enough to take ‘spot’
readings, for anything deemed more complex they either did not carry it out or relied on the
services of an external consultant.
“We do have our own noise meters across sites [that] we can do … spot checks for and if they
identify an issue we may get the third party in just to do another more thorough monitoring for
us.” (Company 12)
Selection of appropriate hearing protection. Hearing protection represented the main form of
noise control amongst companies involved in this research. It appears, however, that managers
are unable to make an informed choice about the type of protection that they need to purchase.
As such, they tended to ‘play it safe’ by opting for the highest attenuation and level of
protection rather than selecting suitable protection for the activity in question. There seemed to
be widespread dependency on hearing protection and an apparent disregard of other noise
management methods. This neglect of other methods seemed to reflect managers’ lack of
awareness of what else would work for them.
“They can choose the colour of the earmuffs and they can choose the shape, but it’s got to be
EH12.” (Company 2)
Engineering controls. Some misunderstanding was apparent as to what engineering controls
actually entailed. Managers tended to think of engineering controls as updating their machinery
with quieter models, rather than working with what they have already got, for example,
retrofitting noise dampeners into their existing machinery.
“…the only other thing is … whether newer machinery would help...” (Company 9)
Unaware if they are doing ‘enough’. Managers were either reluctant to say that they were
confident in their approach to noise control or said that they were confident whilst admitting
19
that they could in fact probably do more, with little understanding of what exactly they could
do. Some of that lack of understanding resulted in managers compensating by doing too much.
“…we are over the top and we’re trying to step back a little bit and not overprotect people…”
(Company 11)
Formal training received. With regard to knowledge obtained on noise through formal training,
participating managers in medium-sized and large companies tended to have at least NEBOSH
level qualification in health and safety. Managers in small companies were possibly at a
disadvantage therefore from not having received such training. Nevertheless, NEBOSH appears
to be a general health and safety course covering a range of health and safety matters rather than
providing detailed instruction on noise.
“…there’s a fair coverage on noise in things like the NEBOSH diploma…” (Company 10)
(iv) Autonomy to make decisions regarding noise management
A strong theme that emerged from the management interviews was that, regardless of the
manager’s length of tenure, the final decision regarding health and safety improvements tends to
be made at board or senior management level. Whilst some managers commented that they
could make recommendations for improvements to noise management, few had the financial
authority for health and safety budgets.
“…then it would need to be agreed by the Board…” (Company 5)
“I have to refer to my managing director…” (Company 8)
(v) Production pressures
Some companies had implemented job rotation and were ensuring that their workers take
regular breaks from noisy activities as a method of noise control. Nevertheless, it was apparent
that these practices did not always occur in practice, especially during times when it was
necessary to maintain high levels of production.
“It’s producing a product without putting too many on costs on it…and being able to produce it,
assemble it safely without damaging the people that are putting it together” (Company 11)
Just over half (n=8) of the companies had maintenance programmes in place, but this seemed to
be driven by production requirements (keeping production going with ageing machinery) rather
than a desire to minimise noise levels. None of the managers belonging to companies with
maintenance programmes made reference to the benefits of regular maintenance for keeping
noise levels down.
(vi) Health and safety culture
Listening to workers. Worker involvement, both formal and informal, was apparent in the
majority of companies. It was not possible, however, to judge the quality of that involvement
from the available data, i.e. whether worker involvement was simply ‘done to workers’ or
reflected open, two-way communication between management and staff. Nevertheless, two
companies (8, 10) showed a strong worker involvement ethos. These managers demonstrated
commitment towards health and safety and showed signs of having embedded health and safety
into their ‘way of doing things’, or organisational culture. This was shown in one company (8)
through weekly meetings to discuss health and safety and also a regime of toolbox talks and
training for each area of work.
20
“We have for each individual area, each individual process, a safe system of work …there’s
toolbox talks and training given for each area … dependent [on the] dangers and hazards on
that particular job, including noise. So, when people work on that they’re … signed up [to a]
toolbox talk to know what to do when they’re in that on that job.” (Company 8)
Senior and factory level committee meetings were a regular feature of the other company (10)
where they had also resurrected an employee suggestion scheme to allow workers to put
forward ideas and concerns that they might have. There was also a culture of encouraging
workers to raise their concerns directly with supervisors and managers.
“…they can either raise them with the supervisors, with the health and safety committees, with
the Trade Union reps, with myself…” (Company 10)
Talking a reactive versus proactive approach to health and safety. Around half the companies
involved in this research declared that they used audiometry results to measure the success of
their approach to noise management. This provides further evidence that managers were
generally unaware of the long-latency nature of hearing loss. This also demonstrates a reactive
approach to noise management and somewhat contradicts the view held by a number of
managers that they were proactive in their dealings with noise. Other key measures of success
were the number of worker complaints and seeing workers wearing their hearing protection
during site walkabouts. It should be noted that whilst the majority of managers said that they
spent time on the shop floor, the quality of time spent (e.g. observing, challenging workers)
remains unclear.
“…I've had a complaint that it's noisy loading the back of a lorry…which I thought was unusual
so I went down and did some checks…” (Company 12)
Surface versus deep-rooted change. In a number of companies, especially those with very high
levels of noise (i.e. impossible to talk even when shouting in someone’s ear), hearing protection
was mandatory. There was also evidence of companies including a clause in worker
employment contracts that they would be subject to disciplinary action upon failure to comply
with company health and safety requirements, including the use of hearing protection. As was
the case with the provision of audiometric testing, in companies where noise levels were less
severe (i.e. needing to shout to a colleague at one or two meters), this mandatory approach
seemed to reflect managers wanting a simple solution rather than embarking on the more
difficult approach of developing a culture in which workers look after their health.
“…the next step is to put it in the contracts that you have to wear your ear defenders…”
(Company 9)
3.1.2.2
External influences on managerial noise decisions and practices
(i) Information sources
There was a fair degree of praise for the information provided by the HSE website. The vast
majority of managers in this research utilised the HSE website and noise publications (including
magazines). One manager (company 10) commented, however, that he only became aware of
HSE as a source of information through his NEBOSH course. Information from other health
and safety databases or organisations was also commonly used. The Croner and Barbour
databases were popular, partly because they are accessible through managers professional or
Trade Association memberships. Only three companies used PPE suppliers and four companies
used information from Trade Associations and industry groups as a source of information.
21
(ii) Consultants
The majority (two-thirds) of companies involved in the research interviews were not using
external consultants. Only five of the 15 companies used consultants to assist them with noise.
The following quotation describes the use of consultants in one company where they were not
considered helpful. This quotation provides further evidence that employers perceive the need
for continual surveying of noise.
“We’ve had noise surveys done in the past by outside consultants, but you always find they’re
quite limited, the fact that when you make changes, you’ve got to come back again, another
cost, and we generally found that it’s … in … the £5,000 region for a full survey to be done,
whereas to train me up to do it, and buy a noise meter was actually cheaper.” (Company 11)
Use of external consultants appears to fall into two categories: one where consultants provide
companies with advice, which may be acted upon internally, and the second where the
consultant acts as the decision-maker taking forward their own recommendations. This could
be taking forward recommendations as the result of a noise survey or as part of a generic risk
assessment. From the paperwork presented to the researchers during the site visits there was
little or no evidence of any formal recording of action plans. The second category was clear in
one company (3) in which the participating manager had delegated almost all responsibility for
noise control to the consultant. It is noteworthy that this company was considered to be ‘low
performing’.
(iii) External bodies (especially insurers)
It was apparent in some companies that insurers’ demands appear to override those of HSE. For
example, carrying out audiometric testing to satisfy their insurers. In fact, this appeared to be
the main driver for audiometry 33 , particularly where a claim had previously been made. A key
driver for implementing health surveillance, therefore, seems to be to satisfy insurers, more so
than to protect the workforce against health risks. It was apparent that managers were keen to
keep their paper work up-to-date in anticipation of insurers health and safety audits.
“…we do tend to get regular inspections from our insurers, who are always keen to look at all
… issues.” (Company 10)
The provision of information to workers about noise risks and use of controls appears to be
driven externally rather internally. A number of managers were influenced by the growing
claims culture and had therefore taken steps to educate their workforce, mostly through
induction training. There was some evidence that toolbox talks and other refresher training is
given, but managers were unable to specify how often noise features as a topic. Managers
considered the provision of such training to workers coupled with regular hearing tests to be
sufficient for protecting themselves against future health claims. A recurrent theme and driver
for educating workers and regularly testing their hearing was concern about being held
responsible for hearing damage that may have occurred in workers’ previous employment. This
was a particular concern in industries, such as ceramics, where movement of workers between
factories was commonplace.
“You’ll probably find this in a lot of manufacturing companies that have been in existence for a
lot of years, that there is [a problem with historical noise claims], I know it’s a big problem
across the whole ceramic industry from talking to other safety officers, with historical noise
claims…” (Company 10)
33
Eight of the 15 companies involved in this research said that they were using audiometry to protect the company
against any potential future insurance claims.
22
(iv) Legislation
Health and safety legislation did not emerge as having a strong influence on managerial
decision-making and practices. This is probably because the majority of the companies were
small, yet it was the medium and large-sized companies that were more aware of, and
influenced by, HSE legislation. For example, two companies (5, 8) commented that they looked
at what improvements they could make when an improvement notice or similar was issued to
other companies in their vicinity.
“…one member… was given an improvement notice on the way they dealt with noise…it
certainly made us more aware of our duty.” (Company 5)
3.1.2.3
Differences according to company size
Implemented noise controls. Results from the content analysis of implemented controls
according to company size revealed a notable pattern of a more comprehensive package of noise
controls being provided as company size increased (see Table A7.6 in Appendix 7). The four
small companies rarely went beyond providing hearing protection and this appears to be
unaffected by perceived noise levels and risk to the business from noise. There was limited
evidence of technical and/or organisational controls (e.g. machine segregation, job rotation,
noise dampeners) in these small companies and no noise action planning or health surveillance.
Conversely, in medium and large companies, health surveillance was provided and noise action
planning was generally undertaken. These companies had better provision of training, more
consistent use of technical controls, better supervision and worker involvement (mostly
informal) than small companies. Large companies were also more likely to have embarked on a
behaviour change programme and implemented formal worker involvement processes than
medium-sized or small companies. Interestingly, the majority of medium and large companies
perceived the risk to the business from noise as being ‘high’ despite not having excessive noise
levels, suggesting a greater awareness and acceptance of the potential debilitating effects of
noise-induced ill health amongst these managers.
Wish lists. Responses to an additional question asking managers to name one thing that could
help them to control noise provides further evidence of differing levels of sophistication in
managers thought processes concerning noise improvements in small companies compared with
larger companies. Small companies principally wanted better and quieter machinery.
“Basically it’s if there are any other better equipment available these days?” (Company 7)
Whilst medium-sized companies requested quieter machinery, these managers also mentioned
the need for training on noise risks, including guidance on how to change worker behaviour in
terms of the importance of wearing hearing protection.
“Guidance on specific issues, communication of new issues, some culture change would also
help, i.e. better acceptance by some of the older workers, change of culture balanced with
losing the experienced workers ... we have to manage the ignorance in order to keep the
experience.” (Company 4)
Large companies tended to take a more strategic stance – for example, managers wanted HSE to
tell them the ‘top 10 tips’ relating to noise control and the solutions that other companies have
put in place.
“Top ten approaches to noise reduction from HSE.” (Company 11)
23
“Would like to know what solutions organisations have implemented in response to
prosecutions, improvement notices, etc.” (Company 11)
(See Table A7.7 in Appendix 7 for further details.)
3.1.3
Top-level findings
Taken together, the findings from both the quantitative and qualitative components of the
research to address the first research question (to discern the factors influencing noise
management) highlight the following top-level findings:
1. Influences on noise management mostly originate within companies, predominantly
through:
• The company’s health and safety values towards eliminating/minimising noise risks
and protecting workers against noise induced ill health. A tendency to be reactive
rather than proactive was apparent (e.g. monitoring worker complaints/audiometry
results) as well as little interaction with workers to resolve the issues at hand.
• The company’s size. The size of the company influenced the approach taken to
manage noise risks. Medium-sized and large companies were more likely to have
implemented a comprehensive package of noise controls than small companies.
Differences in levels of sophistication in managers’ decision-making concerning
noise improvements also appeared to be influenced by what was practical and
affordable. Financial considerations seemed to play a role in all facets of decisionmaking, including machinery maintenance; managers were motivated to get their
money’s worth. Managers in small companies orientated towards machinery
replacement as the ideal solution to noise problems, whereas larger companies
preferred a more strategic and educational approach. Regardless of company size,
however, the ultimate decision for making significant noise improvements rests at
very senior levels of the organisation.
• Managers’ own knowledge and awareness of noise risks and
technical/organisational controls. Noise was generally thought not to present a
significant health risk unlike other health and safety risks. The long-latency nature
of noise appeared to underlie this misconception when noise was compared with
those risks that sometimes show an immediate impact on employee health and well
being (e.g. manual handling). Managers generally lacked knowledge of how to
correctly measure noise and seemed to be more concerned with taking accurate
noise measurements (i.e. diagnosis of noise levels) than selecting appropriate
controls (implementation). This seemed to reflect a lack of understanding of what
action to take having read the noise guidance. In addition, managers had difficulty
discerning the solutions (technical) that would work for them in practice other than
hearing protection. Despite accessing and utilising noise information sources,
mostly from HSE, managers had difficulty translating this knowledge into practice
and therefore tended to opt for individual rather than organisationally-focused
solutions.
2. Eight factors do not appear to be important drivers of noise management, namely,
business motivators (including legislation), resources, information/communications,
level of autonomy/competence, self-efficacy, attitudes towards protecting workers
against noise risks and role as a Director or Health and Safety Manager. The three
24
significant drivers accounted for any influence of these factors, namely, (1)
organisational health and safety values, (2) company size, and (3) managers’ own
knowledge and awareness. As such, becoming aware of noise health effects, ‘how to’
take action to make appropriate internal changes, including cultural improvements, and
having the knowledge and scope to make improvements, are all important.
3. Insurers were the driver behind health surveillance and educating workers about noise.
Managers perceived the value of this for (i) protecting the company against potential
future health claims and (ii) gauging the success of implemented noise controls.
Legislation generally had little effect, especially in small companies.
To answer the first research question, therefore, three factors influence managerial approaches
to noise management and practices, namely (1) health and safety values or ‘culture’, (2)
managers’ own knowledge/awareness and (3) the size of the company.
3.2
WHAT IS THE RELATIVE IMPORTANCE OF THESE FACTORS?
Findings from the questionnaire analysis to address the second research question are described
in the sections that follow. The first presents those from the stepwise regression that indicate
the importance of each of the three predictor variables, i.e. the unique variance that they explain
in implemented noise controls. The second details the precise effect that each of these three
predictors has on implemented noise controls and the third describes the results from a model
validation exercise conducted through SPSS 34 to provide some initial insights into the validity
of the regression model.
3.2.1
Importance of the three predictors
The order of influence of the three significant factors driving managerial noise decision-making
and practices was, starting with the highest: (i) organisational values (25% unique variance);
(ii) company size (11% unique variance); and (iii) knowledge/awareness (6% unique variance).
(See Table A7.8 in Appendix 7.)
3.2.2
Strength of effect of each predictor
Table 4 shows the precise effect that each of these three factors has on implemented noise
controls (i.e. the size of the regression coefficients). For example, for every unit increase in
organisational health and safety values, implemented noise controls would increase (or
improve) by 0.355 units. Each factor alone has a subtle impact on noise practice, but taken
together these three predictors produce a large effect according to Cohen’s (31) criteria,
regardless of sample size. (See Table A7.9 in Appendix 7 for further details).
34
Statistical Package for Social Sciences
25
Table 4 Strength of effect on implemented noise controls of each predictor variable
Standardised
Coefficients
Beta
.355
.341
.242
Model
Constant
Organisational H&S values
Company size
Knowledge and awareness
3.2.3
Significance
.000
.000
.000
.000
Model validation
Results from a data splitting exercise showed that these results are consistent across the sample
in this research. The stepwise regression was performed on half the sample (n=99; a random
sub-sample generated by SPSS). Similar results were obtained for this sub-sample as the whole
sample (R² = .424. F (3, 93) = 24.588, p = .001), with the same three predictor variables showing
a similar strength of effect in the sub-sample. Although a larger original sample would have
been preferred, these results lend support for the consistency of the model across participants,
and potentially with other data sources. (See Table A7.10 in Appendix 7.)
3.2.4
Top-level findings
Findings from the quantitative analysis to address the second research question (to discern the
relative importance of the three influential factors) highlight that:
• Organisational health and safety values (culture) have most impact on managerial noise
decision-making and practices, likely to produce improvements in noise control beyond
those capable of other factors.
• Whilst organisational culture emerged as having the most influence on noise
management, focusing on making cultural improvements alone is unlikely to result in
the optimal level of improvement. In addition to health and safety culture, to optimise
the chance of improvements to the management of noise risks, interventions also need
to address managers’ knowledge/awareness of noise as a significant health risk and the
technical and organisational solutions available, as well as helping companies of
varying sizes to select the best possible solutions that are doable and affordable.
• The final regression model showing three significant predictors of noise management
(health and safety values, company size, knowledge/awareness) appears to be valid.
This provides some degree of confidence that the same three factors and strength of
effect would be replicable in other samples. It also supports the notion that the three
influential factors represent latent (or underlying) factors and therefore mediate the
influence of the eight factors not found to be significant drivers of noise management.
26
3.3
HOW DO THESE FACTORS VARY BETWEEN HIGH AND LOW
PERFORMING ORGANISATIONS?
3.3.1
Quantitative results
Results from the Mann Whitney-U test to compare high and low performers on nine of the 11
variables 35 input into the regression analysis (see section 3.1.1.1) showed a significant
difference between the two groups on four of these factors, namely, (1) knowledge and
awareness of technical and organisational solutions to reduce noise, (2) organisational health
and safety values towards eliminating/minimising noise risks and protecting worker health, (3)
company size (small versus medium-sized and large companies), and (4) resources (capability
to make improvements e.g. time, staff, funds and equipment).
• High performers had higher levels of knowledge and awareness of technical and
organisational-level solutions to reduce noise than low performers (U=1023, (z =
2.876), p<.01 36 , N=110).
• High performers demonstrated values more supportive of a positive health and safety
culture than low performers (U=1082, (z=-2.521), p<.01, N=110).
• Low performers were more likely to be smaller in size (micro/small) than high
performers (U=1122, (z=-2.500), p<.01, N=110).
• High performers faced fewer barriers to resourcing noise management (time, money,
staffing) than low performers (U=938, (z=-3.376), p<.001, N=110).
Accounting for differences in sample size, the magnitude of the effect of each of these four
significant differences between high and low performers using Cohen’s (31) criteria was found
to be small in each case. (See Table A7.11 in Appendix 7.) In a health and safety context a
small effect is important given the potential impact on employee health and well being.
To test the final two variables that were input into the regression analysis, and thus examine
whether the two groups differed according to managerial role (‘Director/owner’, ‘Health and
Safety Manager’ or ‘other’ e.g. senior manager, supervisor), a Chi² (χ²) test was conducted. No
significant difference was discovered, indicating that the level of authority of those who
completed the questionnaire had no impact on performance levels.
These findings are consistent with those obtained from the regression analysis, as high and low
performers differed on the three factors found to have the most impact on noise management
(i.e. knowledge/awareness, organisational health and safety values and company size). It is
likely that available resource for health and safety overlaps with company size with mediumsized and large companies having better access to this than small companies. It is not surprising
therefore that the uptake of technical noise solutions became more apparent as company size
increased. Low performers were mostly micro-companies (up to 10 employees) or small
companies (up to 49 employees), whereas high performers were mostly small or medium-sized
companies (up to 249 employees).
35
Please note that variables for this type of analysis need to be continuous; as such two of the demographic (categorical) variables were excluded i.e. (1) role as a Director/owner and (2) role as a Health and Safety Manager. These variables were analysed separately via χ². 36
The probability is exact and was found using SPSS version 14. 27
3.3.2
Qualitative results
Results from the content analysis of companies classified as high and low performing are
summarised in Table 5. Of the 15 companies visited, seven were considered to be high
performing and four low performing; the remaining four companies were classified as moderate
performers and excluded from the analysis (see Table A7.12 in Appendix 7 for a further
demographic breakdowns). Companies were grouped according to specific criteria developed
by the researchers prior to the content analysis. A key distinction according to the criteria
between both groups was that hearing protection was not the main form of noise control adopted
by the high performers. At the very least these managers had researched technical solutions and
had implemented controls that, in their view, kept noise levels to as low as reasonably
practicable. For example, the manager in one company (5) had considered implementing sound
booths, but this was not deemed practicably feasible with the current factory layout. This
manager had considered all options for implementing sound booths, but were restricted by their
current factory layout and size. Conversely, in low performing companies there was heavy
reliance on hearing protection and segregation of noisy machinery. It is a concern that
compliance with hearing protection use was considered by researchers to be poor in three of the
four companies, given that the reliance on this as a control.
Using findings from both the content and thematic analysis, the following section elaborates on
the findings from the questionnaire analysis (see section 3.3.1) by describing how high and low
performers compared on the four group differences found.
1. Company size
It is immediately apparent from inspecting Table 5 that the high performers were all large or
medium-sized companies (mostly large), whereas the low performers were exclusively
small. This supports the findings from the questionnaire analysis showing that company size
influences the comprehensiveness of selected noise controls. The qualitative research revealed
that hearing protection was the main source of noise control used by small companies and
compared with their larger counterparts they did not make use of audiometric testing to check
the hearing of new recruits or established employees. Rather, they relied on workers using their
general practitioners to identify whether they had any hearing problems. Small companies were
also less likely to carry out any form of noise action planning.
2. Knowledge and awareness of technical and organisational noise solutions
A higher level of technical noise knowledge was apparent amongst high performers. Whilst
recognising the benefits of quieter machinery, these managers were thinking through other
options, including a strategy to reduce noise and to encourage behaviour change.
“…I've tried to explain what the problems are…or what potential harm can happen and
explained such things as hierarchy of control. You know you remove the source, you
isolate…etc., etc. And then the last line is PPE” (Company 4)
A prominent knowledge gap amongst managers in the low performing companies was that they
believed new, quieter machinery would solve their noise problems, and rarely looked beyond
this to consider other potential engineering or organisational solutions.
“…there’s no way we can make the machines any quieter because it is a standard manufactured
machine.” (Company 7)
Unlike managers in low performing companies, high performers had all received some form of
health and safety training (e.g. NEBOSH) and commented that the training had motivated them
28
to make improvements to the way that noise was managed. They also made use of Trade
Federations and Trade Associations as an additional source of information and advice.
Managers in low performing companies were less likely to network with similar organisations
or to have the same opportunities to attend larger events that provide a programme of health and
safety topics for their members to guide their learning and understanding.
The use of hearing protection was considered to be ‘common sense’ by most managers. As
such, training on correct use had often not been considered unless requested by insurers. Table
5 shows that high performers tended to be influenced by their insurers. It is not surprising
therefore that they provided some form of noise training for workers. Low performers were not
influenced, however, by their insurers and generally did not provide any noise-related training
(see Table 5). Noise matters were seldom covered in safety briefings or toolbox talks. Instead,
making hearing protection the sole responsibility of the “lads” (company 9) was a common
theme.
“You can’t be stood watching them every minute … they know they’ve got ear defenders… what
they’re for and you know they should be responsible enough to think to put them on…”
(Company 9)
Although low performers relied on hearing protection as their main source of noise control, they
appeared reluctant to encourage the use of hearing protection and would have preferred instead
to have a piece of legislation to hide behind.
“…if legislation were a bit different, you could just say it’s compulsory that you wear them and
… if you don’t wear them its sort of like a warnable offence, but really it’s … down to the lads”
(Company 9)
It is a concern that these managers were generally confident with their approach to noise. This
possibly reflects their lack of knowledge about what they should be doing in practice. Low
performers tended to utilise fewer information sources than high performers, which may partly
explain this potential knowledge gap. Many relied on the HSE website for information,
although there was the suggestion that the guidance was written with larger companies in mind
rather than for smaller companies facing similar situations to their own. Managers in smaller
companies (low performers) commented that technical terms, such as ‘action value’ were new to
them, as they had not previously been exposed to such language through, for example, health
and safety training.
“…half the time you think, well, does that really apply to me because when there’s only four of
us. So I think we have to use our own discretion to a certain level…” (Company 7)
3. Organisational health and safety values (culture)
Managers in both high and low performing companies acknowledged the influence of health
and safety culture on noise management (see Table 5). Differences in perceived level of
cultural maturity were, however, apparent between the two groups, with high performers more
likely to carry out observations of good health and safety practices and initiate discussion with
their workers about good and poor practice in noise control.
“…we covered everybody in the factory [in a] noise awareness session...I did use ...a link on
HSE's Website… [an] audio clip that shows the impact of noise induced hearing loss, which I
think was quite hard hitting actually to a lot of people...” (Company 10)
29
Only two high performers, both large companies, had embarked on a behaviour change
programme to initiate culture change, more specifically, to encourage attitude and behaviour
change amongst employees leading to better use of existing noise controls.
“…we’ve moved forward, trying to step away from the disciplinary side of unsafe acts … into
something called TWTTP 37 , which is the way to teach people…it’s a five question checklist that
you ask them…to find your root cause of why that unsafe act came about and some of them are
down to lack of training, lack of procedure, lack of knowledge, negligence…lack of attention,
for instance… we’ve now started that…moving away from…a… big stick [approach].”
(Company 11)
Performance seemed to be relatively unaffected by the managers’ perception of noise levels on
the shop floor (see Table 5). One health and safety risk having primacy over another was
clearly influenced by where they focused their attention; many made a subjective judgement
based on risk of injury and death. In low performing companies, an absence of worker
complaints about the noise and the manager’s own belief that noise was not a problem resulted
in the belief that it probably was not.
"...in balancing it up against other risks, I tend to consider the big physical risks as being your
actual risk to life and limb ... then you have the risks that will affect your quality of life but
you're still alive, and that's where hearing comes in ..." (Company 4)
"Noise is quite high up there … but manual handling is the worst." (Company 8)
“… I don’t find it particularly noisy at all and I’ve got very good hearing…” (Company 3)
Low performers were more reliant than high performers on external health and safety
consultants to determine what approach they should take with controlling noise risks. They
rarely took action themselves as evidenced by documentation relating to noise surveys being
over five years old in two companies (2, 7). A greater concern about the impact of noise levels
on their neighbours than their workforce was also apparent.
“…we don’t want the neighbours to get so upset that eventually we have to leave.” (Company
2)
4. Resources
There was no indication in high performing companies that money was allocated for noise
management per se other than audiometric testing. Managers said that they had either no budget
or a limited budget to spend on health and safety, many having to defer to senior managers for a
decision based on a business case.
“There’s no real budget for anything to be spent on health and safety issues. We discuss it
and if it’s felt it’s the right thing to do it’s bought…” (Company 14)
Being small companies, low performers tended to have more financial autonomy than high
performers because they were either an owner (7), Director (9) or held a senior position within
the company (2, 3). Their financial spend was directed more towards the purchase of hearing
protection or buying in external consultants. Whilst considered, the relative expense of
machinery replacement in uncertain economic times was given as the reason to delay.
37
i.e. The Way To Teach People (TWTTP) referred to as forming part of the world-class safety
manufacturing/management strategy.
30
“… we can get ourselves a quieter offloading pump, which we’ve had a quote for, we’ve
just got to find four grand to buy it, which in the current economical times is, at the moment
we’re going to stick with the donkey pumps.” (Company 3)
“Newer machinery would help, but obviously it [has] cost implications…” (Company 9)
Whether the financial cost had a bearing on why low performers did not employ health
surveillance is unclear. Even if made aware of the benefits by a third party, whether that was an
external consultant, HSE or Environment Agency inspector, they appeared unmotivated to make
use of their position within the company to instigate change.
Some managers in high performing companies fulfilled dedicated health and safety roles, but
were able to delegate to assistants or had other means of support either from fellow managers,
Trade Union representatives or the workforce.
‘…we task them [the health and safety committee] with producing the risk assessment so the
supervisor, along with an operator, will do a risk assessment and come back with
recommendations.” (Company 5)
31
KEY:
Low performers
High performers
*Denotes evidence where activity takes place within the
company 38
38
33
2
3
7
9
8
11
12
15
5
10
13
Please note: The absence of grey shading does not necessarily mean that companies did not provide these controls; rather evidence that demonstrates the provision of these controls was not uncovered during the site visits.
Information from Trade Associations and industry groups
Information from other H & S databases/organisations
Information from suppliers
Use of HSE Info/website/magazines
Confidence in approach not stated
Duty holder confident but recognises could do more
Duty holder confidence in approach
Duty holder risk perception level 3 (low)
Duty holder risk perception level 2 (medium)
Duty holder risk perception level 1 (high)
Duty holder designates noise level 4 (comparable to a busy street)
Duty holder designates noise level 3 (need to shout at 2 meters)
Duty holder designates noise level 2 (need to shout at 1 meter)
Duty holder designates noise level 1 (excessive noise)
Influenced by HSE legislation
Influenced by external agencies with legislative powers non HSE
Influenced by insurers
Use of external consultant
Internal influences culture
Job holder has H & S qualifications (e.g. NEBOSH)
Job holder has other roles apart from health and safety
Observation and supervision of controls by duty holder
Compliance/good hearing protection use
Informal worker involvement
Behavioural Change programme in place
Formal worker involvement
Purchasing policy considers noise
Noise health and safety policy
Noise Action Planning
Noise survey conducted
Measures task and person based exposure
Job rotation and breaks
Noise dampeners
Segregation of noisy machinery
Machine maintenance programme in place
Engineering and other controls in place
Signage (Noise)
Designated hearing protection zones
General noise training
Audiometric testing takes place
Training on correct fit of hearing protection provided
Hearing Protection Dispensers
Wearing of PPE is mandatory
PPE main noise control
Large Company
Medium Company
Small Company
Case
Table 5 Summary of content analysis - high versus low performers
3.3.3
Top-level findings
Findings from both the quantitative and qualitative analysis to address the third research
question (how the factors vary between low and high performing companies) showed that:
• High and low performing companies differed on the same three factors that emerged
as significant determinants of noise management generally, i.e. organisational health
and safety values (or culture), company size and managerial knowledge/awareness of
technical and organisational solutions to noise. High performers had implemented a
comprehensive package of noise controls including technical and organisational
solutions, and had embedded values that worker health is important. Also,
management displayed behaviours that demonstrated a commitment to employee
health (e.g. worker observations, involvement). They tended to be the larger
companies in the sector and faced fewer barriers to resourcing noise management
than the small companies, all of whom were low performers. It was the low
performers (small/micro-companies) that tended to rely on the services of external
consultants for noise surveys and sometimes for action planning.
• Whilst high performing companies had greater resource for health and safety,
financial authority for change rested with the higher echelons of the organisation,
possibly reflecting the systems and hierarchy that often characterise larger
manufacturing companies. These managers did not have the freedom and the
necessary resources, however, to delegate health and safety tasks. Conversely, low
performers were reluctant to attribute resource to health and safety. The current
economic climate seems to have shifted focus onto ‘costs’ with less attention to
‘benefits’, particularly amongst low performers where resources were limited.
• High performers recognised the importance of changing worker behaviour to ensure
the correct use of the noise controls in place. Unlike low performers, they were more
likely to have established processes for worker involvement to inform their decisionmaking regarding choice and implementation of controls.
• Training on hearing protection use for workers was uncommon despite examples of
misuse, especially in low performing companies, which relied on worker ‘common
sense’. Those providing noise training had been motivated to do so by their insurers.
• In general, noise was not a priority health matter in both groups; safety often took
precedence over health matters. One interpretation is that training and education
might be an appropriate way of motivating managers to make improvements through
increasing knowledge of noise as a long-latency issue. In addition, communicating to
managers the range of options available to them seems important. This is especially
important for the low performers who were less inclined to seek out noise information
and tended to perceive buying ‘quiet’ machinery/tools as ‘the’ technical solution.
34
4
4.1
DISCUSSION AND CONCLUSIONS
RESPONSE TO THE THREE RESEARCH QUESTIONS
The first research question is, what factors influence employers’ decisions and practices in
controlling noise risks? Three factors were found to have a significant influence, namely,
managers’ own knowledge/awareness of noise as a significant health risk and technical and
organisational solutions to reduce noise, organisational health and safety culture towards
prevention of ill-health and protection of employee well being, and the size of the company
(small versus medium-sized and large companies). These three factors account for the
influence of the remaining eight factors not shown to function as significant drivers
themselves
(i.e.
business
motivators,
resources,
information/communications,
autonomy/competence, self-efficacy, attitudes, role as Director and Health and Safety
Manager). Based on both quantitative and qualitative findings, it seems that managers need
to have knowledge of the range of noise controls available to them and the conditions that
need to be present for such controls to work effectively in order to make an informed choice
about which ones to implement. They also need to be aware of the long-latency of noise,
which in turn may influence prevailing cultural attitudes of the importance of noise as an
occupational health risk. These needs seem to relate more to those managers in small
companies than those of larger organisations as the size of the company was also found to
influence the approach taken to manage noise. The differences noted in the level of
sophistication in managers’ decision-making suggested that noise improvements were
contingent on what was practical, affordable and feasible more so in small than larger
companies. Different outlooks regarding ideal control measures were also apparent. Whilst
larger companies adopted a more strategic and educational approach to noise management,
often encompassing behaviour change strategies and a comprehensive package of controls,
smaller companies considered machinery replacement to be the ideal solution.
Secondly, what is the relative importance of these factors? Organisational health and safety
culture had the most influence, followed by company size and managerial
knowledge/awareness of technical/organisational noise solutions. Focusing on cultural
improvements alone, however, will be unlikely to engender optimal improvement; rather it is
the combined influence of the three factors. As such, knowing ‘how to’ take action to make
necessary internal changes, including cultural improvements and implementation of controls
that are practical, affordable and feasible, are all-important.
Thirdly, how do these factors vary between low and high performing organisations? The
same three factors (knowledge/awareness, culture, company size) differentiated the high from
the low performers. Managers in high performing companies therefore had better knowledge
of organisational and technical noise control measures, and had taken steps to promote
positive health and safety attitudes and cultural norms. The high performers tended to be
large companies, which might explain the reason for uncovering a fourth influential factor,
resources, as differentiating between high and low performers. Resources intuitively overlap
with company size, as high performers (larger companies) faced fewer barriers to resourcing
noise management (time, money, staffing) than low performers (small/micro-companies).
4.2
INTERPRETATION OF RESULTS
This research supports the anecdotal evidence available to HSE gathered through company
inspections, suggesting that employers need to do more to protect their workers against noise
risks. Hearing protection was the preferred control whereas technical and organisational
solutions were scarce. This behaviour seems to be driven by factors originating within
organisations predominantly through its culture (‘the way we do things around here’), rather
than through external sources. Only health surveillance and worker education seemed to be
35
driven externally by insurers. In general, noise risks were not considered a priority; other
health and safety risks took precedence. Managers often lacked appreciation of the potential
debilitating effects of noise as a long-latency condition, hence the reason why basic controls
were commonplace. This lack of awareness raises concern as it represents a necessary
precursor to behaviour change; knowledge of health risks and associated consequences helps
to combat fatalistic attitudes. This might explain why managers’ own attitudes did not
emerge as a significant driver of noise management in this research. Rather, cultural attitudes
or ‘norms’ towards health conditions such as noise-induced ill health seem to be at the heart
of managerial noise decision-making and practices. These attitudes may reflect knowledge
picked up through social interactions and industry experience, possibly symptomatic of an
underlying manufacturing industry culture.
Knowing what to do ‘in practice’ and applying noise guidance to their own situation (for
conducting noise measurements, selecting appropriate controls, etc) stood out as a critical
knowledge gap. This was especially evident in the small; low performing companies where
managers thought that they had done enough. It is not surprising therefore that self-efficacy
and managerial competence/autonomy did not emerge as significant drivers because these
managers generally felt competent and confident with the controls that they had implemented.
In effect, they did not know any better. This was true despite access in some cases to HSE
information on noise, showing the difficulty that managers encountered with translating
knowledge of what to do in theory into practice. Information/communication did not emerge
as a significant driver probably because knowledge of what to do in theory was not important
for noise management, rather knowledge of what to do in practice was key.
Noise
information and guidance, HSE or otherwise, seems to be better tailored to medium-sized and
large companies than small companies, which appear to have little time to draw inferences
from the guidance about what they need to do (i.e. translating theory into practice). To reduce
the burden on small companies, HSE guidance could be pitched at occupational health
hazards grouped according to similarities in the nature of the risk (e.g. long latency), rather
than having different sets of guidance for different risks. The use of unfamiliar technical
noise terms in such guidance also seemed to act as a deterrent for these managers to take
action to reduce noise, which may partly explain their preoccupation with diagnosis of noise
levels (measurement) rather than selection of adequate controls (implementation). The
guidance also needs to provide better assistance to managers in small companies with
achieving a balance between effective noise control and the practical constraints that they face
(building size, available resource, etc). This concerns managers at all levels, as noise
decision-making did not always reside at the top; only the financial decisions are made at
senior levels. The higher-level controls that managers tend to know about are the expensive
solutions, such as replacing existing machinery with quieter models. As such, they perceive
effective noise management as expensive, which represents a significant barrier to change in
the current economic climate where the focus seems to be very much on immediate costs.
Although business motivators did not emerge as a significant driver of noise management,
this appears to be reflective of organisations, particularly small companies, wanting to survive
rather than a preoccupation with business promotion (i.e. reaping the benefits and standing
out as the best in the business). This is consistent with the literature on behavioural
economics, which states that people place more weight on protecting what they already have
than potential gains; people do not rationally weight up costs and benefits (39).
These findings are consistent with those from previous studies on noise, which document a
mixture of mostly internal drivers, including organisational culture, managerial knowledge
and motivation to act (e.g. 8-10). Conversely, external drivers (e.g. legislation, company
reputation) seem more pertinent to general health and safety management than noise per se
(e.g. 14). Health and safety studies have also shown that small and medium-sized companies
tend to possess less knowledge and fewer resources than large companies, which impacts on
management behaviour (e.g. 15, 17, 18, 23, 24). This finding is borne out by this research
through the differentiation between high and low performers. Nevertheless, the current
36
research extends the evidence base through isolation of the factors that are pertinent to noise
management accounting for individual, environmental and social factors. In addition, it
identifies those factors that are key for distinguishing between high and low performing
companies. Such knowledge is valuable for HSE and industry in determining how best to
improve the management of noise risks. Perhaps small manufacturing companies could be
targeted in the short-term, although widespread interventions designed to initiate culture or
behaviour change within companies and to improve managerial knowledge of noise (risks,
health effects, controls, practical implementation) appear warranted in the long-term.
4.3
RESEARCH CAVEATS
Certain limitations to this study should be observed, firstly a potential selection bias. It is
possible that the dutyholders/managers who volunteered to be interviewed belonged to those
companies that were engaged in noise management. This may partly explain why almost half
of the qualitative sample was classified as high performers, compared with less than a third of
the quantitative sample. There was also some evidence of socially desirable reporting to
attitudinal items in the questionnaire, although the clear group differences that emerged
suggested that this did not unduly bias the results. Obtaining a motivated sample is a
limitation that not only applies to this study, but to wider research following best practice in
the conduct of research by recruiting volunteers. Nevertheless, adhering to a stringent
sampling strategy, keeping participation time to a minimum and including an incentive to take
part is thought to have minimised the effect of this bias. The large representation of microcompanies (with less than 10 employees) in the questionnaire suggests some degree of
success in targeting hard-to-reach companies.
Secondly, there are limitations with the extent that the findings can be generalised. Whilst the
study included a representative sample of the 15 manufacturing sub-sectors sampled 39 , it is
not possible to confidently generalise the results to other industries or indeed to other
manufacturing sub-sectors. Sampling a range of sub-sectors where noise is problematic to
explore the influences on managerial noise decision-making and practises was the preferred
approach for this exploratory study, rather than focusing on a few sub-sectors to be
generalisable. Given the consistency between the research findings with the existing
literature and the outputs from the model validation exercise showing that the same factors
and strength of effect are likely to be replicated in other samples, some read across to
different sectors and industries seems possible.
The third caveat concerns the reliance on self-report data. Whilst a measure of implemented
noise controls was included in the questionnaire and the distinction between high and low
performers accounted for noise exposure levels and health risks, these were purely subjective.
Adopting a mixed methods approach, however, offset this bias to some extent. Triangulation
of the quantitative and qualitative data demonstrated consistency in findings, which provides
strong evidence that the results portray a realistic picture of noise management. The fact that
it was possible to discriminate between the performance levels of participating companies
suggests that managers provided honest accounts of current noise practice. Furthermore,
following a systematic analysis process in which researchers crosschecked one another’s
outputs at key time points promotes objectivity in the interpretation of self-report data.
Finally, although the factors found to be significant do not fully account for all influences on
noise management, as other, unknown factors seem to be at work, this is fairly typical of
organisational research in which it is impossible to measure or to control all multi-level
influences. Similarly, despite a ‘small’ magnitude of the effect of the differences reported
between low and high performing companies, this is regarded as ‘small, but significant’. As
39
Representation would have been improved if the research databases had accurately recorded company SIC
codes, although this is dependent upon company representatives regularly updating such demographic
information.
37
Rosnow and Rosenthal (40) suggested, a small effect size is important if it means saving even
a few people’s lives. Given the long-term health implications of the findings of this research
as having the potential to prevent or reduce the incidence of noise-induced ill health, there
appears to be a case for acting upon these.
4.4
ISSUES FOR CONSIDERATION
The results of this research highlight issues for HSE to consider when designing subsequent
noise interventions. Based on the findings, three routes are identified as having the potential
to influence dutyholders/managers, namely through (1) the inspection process, (2) influence
through intermediaries/third parties and (3) noise information/guidance. Each of these is
discussed in turn. Suggestions are also provided for further research and ways to evaluate
future interventions.
4.4.1
The inspection process
HSE’s traditional inspection model may be appropriate for unionised, large companies, but
the findings from this research suggest that some modification is required to appropriately
tailor this model to small companies. In particular, consideration should be given as to how
best to provide noise information, guidance and advice to smaller, typically non-unionised
companies that rarely access noise information sources (i.e. the hard-to-reach companies).
Grouping occupational health risks in HSE guidance that are similar in their risk
characteristics might help to streamline guidance/information to these companies, raising
awareness of a number of risks at any one time. The constantly evolving context within
which manufacturing companies operate (e.g. increased automation, downsizing, outsourcing
work abroad) also impacts the utility of the traditional model of inspection. HSE may benefit
from considering more innovative ways of working that will be flexible enough to meet the
challenges that today’s business environment provides.
Factoring in ‘cultural assessments’ into inspections (if not already in place) seems necessary
given the influence that an organisation’s health and safety culture has on managerial noise
decision-making and practices. This could be achieved by inspectors conducting a high-level
cultural audit. Improvements could be suggested based on the outputs of this assessment that
are likely to not only generate improvements to noise management, but to the management of
other health and safety risks generally. This also ensures that due attention is be given to
occupational health matters alongside safety. Whilst it would still be necessary to tailor the
inspection approach to a company’s size, bearing in mind what is practical and feasible for
any given company, this added layer of tailoring to fit cultural maturity should stimulate
awareness amongst dutyholders that behaviour change is as, if not more, important as
implementing the right controls. Should HSE decide to take forward this suggestion for
inspectors to conduct cultural assessments during company visits, an investigation into the
extent to which this is currently in place would need to be conducted.
In terms of ‘who’ to speak to during inspections, findings from this research support
dutyholders as the first point of contact. After all, it is the higher echelons in organisations
that ultimately dictate the direction that noise management takes. Improving dutyholders’
knowledge and awareness of noise risks and controls is important, as well as encouraging
them to cascade this information to their workers and involve their workforce in developing
noise solutions. To increase the likelihood of improvements being made to the management
of noise risks that do not necessarily warrant enforcement action, inspectors need to be aware
that there is not a direct relationship between managerial role and decision-making power. As
such, inspectors may need to speak to managers at a local level that have been given
autonomy (e.g. up to a certain monetary amount) for deciding which noise controls to put in
place.
38
4.4.2
Influence through intermediaries/third parties
Findings suggest the need for HSE to collaborate with various external bodies to achieve the
following:
• Capitalising on the opportunity to convey a strong message to employers about the range of
technical and organisational controls open to them and the likely benefits accrued from
implementing these rather than defaulting to hearing protection. This includes educating
small companies that purchasing quiet machinery/tools is not the only way to reduce noise.
Training providers of health and safety training courses could help to cascade these
messages, bearing in mind that managers belonging to high performing companies in this
research had attended formal health and safety training and subsequently felt motivated to
make improvements to noise management.
• Communicating to employers that health surveillance results in the short-to-medium term
do not necessarily mean that noise risks are being adequately managed. This reflects a
commonly held misconception amongst managers in this research, and seems to
correspond with their lack of appreciation of the long-latency nature of noise. HSE should
consider ways of overcoming this misconception about health surveillance for monitoring
occupational health conditions.
• Encouraging suppliers to ask pertinent questions at the point of sale of manufacturing
machinery/equipment. HSE and suppliers could collaborate to produce a series of case
studies to assist small companies to make an informed decision about noise solutions that
might work for them (i.e. help with practical decision-making). It is important, however,
that small companies are made aware of the existence of this information and where they
can access it.
• Educating insurers as a third party influence to advocate a more sophisticated approach to
health protection during their company audits. Where external bodies were having an
effect on noise management in this research, it tended to be through employers’ motivation
to reduce their insurance premiums. HSE could explore the possibility of introducing
insurance incentives that include the management of noise risks.
• Developing a business case to convince dutyholders of the need to secure resources for
occupational health matters like noise induced ill health by demonstrating that the benefits
of a commitment far outweigh the cost. The benefits need to be framed in business terms.
For example, encouraging machinery maintenance through prolonging the lifespan of
machinery (getting ‘value for money’) and preventing breakdowns that may impede
production.
4.4.3
Noise information/guidance
Implications for the noise information/guidance that HSE provides based on the research
findings include:
• Simplification of existing material. Whilst managers valued the information on HSE’s
website relating to good practice in the management of noise risks, the content was
considered too technical. In addition, managers seemed unaware of when noise
measurements were actually required. The preference was to measure noise, rather than to
take a more considered approach to implementation of control measures as reflected in
general low knowledge levels. A positive intervention from HSE on this matter appears
warranted. Employers might benefit from having access to simple guidance about when
measurements are needed and how these should be conducted. The ‘how to’ nature of the
guidance seems to be missing presently. HSE should therefore consider how to fill the gap
39
detected in this research between the current information provided to employers on noise
management and the practical application of such guidance. Involving small companies in
the process of producing such guidance may be beneficial. This would also provide a
mechanism for testing the feasibility and receptiveness of smaller companies receiving
guidance that covers related occupational health risks rather than focusing on one alone,
such as noise.
• The potential benefits of norms-based communications (or ‘nudges’). Internal health and
safety culture was the most significant driver of noise management in this research.
Finding an appropriate vehicle to communicate what other comparable companies in the
industry are doing on noise could therefore help to overcome two challenges facing HSE:
(1) managers knowing what noise solutions might work for them and (2) managers feeling
motivated to resolve noise issues by appealing to their concerns for business survival and
the need to keep up with other companies or, at the very least, not fall below the general
standard of industry. The latter provides companies with the opportunity to benchmark
their progress in comparison with other companies, which could also be used as evidence
for achieving quality standards including Investors in People.
• Improvements to HSE’s noise website. Managers generally lacked knowledge of what
technical and organisational noise controls entail. The website could therefore signpost
managers to definitions and examples (e.g. the Top 10 controls). Short case studies of
common errors in fellow organisations and solutions adopted may also be beneficial. It
should be borne in mind, however, that the companies likely to use and access this type of
information/guidance are likely to be the better performing, larger companies. HSE should
therefore consider innovative means of communicating with smaller companies, less
inclined to seek out this information, making them aware of the guidance and information
available to them on the website or via other sources. In order to assist managers with the
‘how to’ make improvements to the management of noise, a series of bite-size, simple elearning courses on the website might help all managers and not just those belonging to
small companies. Such training would need to be well communicated through various
channels (e.g. insurers, HSE and industry-specific communications, etc) to ensure that
small companies are aware of its existence and encourage them to visit the website to seek
out such training. Each course could target a different aspects of noise management, for
example, when it is necessary to take noise measurements (course 1), how to carry out and
interpret these (course 2) etc. A selection of example training interventions for different
organisational sizes or cultural maturity could also be placed on the website.
4.4.4
Considerations for future noise interventions
Given that the findings of this research will be used by HSE as a basis for determining future
noise interventions, the following section provides some pointers for what form these
interventions could take and how they could be evaluated. Training and communication is the
obvious vehicle for motivating managers to make improvements to the way they manage
noise risks, whilst building their knowledge of how to do this through communicating the
range of options available. This is especially important for the low performers who were less
inclined to seek out noise information/guidance themselves. Focused interventions like
training have the added benefit of being more amenable to evaluation than organisational
wide interventions.
Example interventions:
• Noise specific training for dutyholders/managers could be implemented by HSE to a
sample of small, hard-to-reach companies. Such training could take the form of e learning
or a highly visual presentation to be less resource-intensive. This would cover the
essentials for effective noise management (i.e. understanding the nature of noise risks and
40
health consequences, knowledge of the range of possible controls, selecting practical and
feasible controls, how to implement solutions, including cultural improvements). Pre-,
during and post-evaluation measures would provide a means of examining the
effectiveness of such training. This should go beyond training evaluation forms (or
reaction to training – see 41) to include measures that examine changes in practice (i.e.
measures of learning and behaviour). This could be achieved, for example, through focus
groups with managers to discern what they have learned from such training and the
improvements that they have made.
• Interventions need to be ideally tailored to company size, cultural maturity and to the level
of knowledge that a dutyholder/manager possesses about noise (i.e. a graded intervention
system). Rather than an enforcement approach to small, possibly low performing,
companies, HSE could exploit its role as an educator through, for example, the
establishment of industry norms. In effect, it would be the larger, high performing
companies in collaboration with HSE that would educate the low, performing, smaller
companies. HSE could act as a conduit for a noise forum or community for managers to
obtain information and advice about how to resolve their noise issues. Collaboration with
large companies at the outset would help to raise awareness of this community through
industry word-of-mouth. This could be hosted by large companies that follow best practice
in noise management to serve as a means of cascading good practice to those companies
that need it. As a means of evaluating the effectiveness of such an initiative, baseline
measures would need to be established at the start to gauge knowledge levels, cultural
maturity and current noise management practices/behaviours. The same measures could be
employed at specified time points (e.g. after three months, six months, one year) to gauge
effectiveness in terms of improvements in knowledge (e.g. knowing how to resolve their
noise issues) and culture (e.g. greater commitment to managing noise risks and awareness
of employee health). This community would provide a means of gathering case study
material of what other companies are doing in relation to noise management, as described
in section 4.4.2.
4.4.5
Considerations for further research
Besides the practical intervention research described in section 4.4.4, further research seems
necessary to address the following questions:
• Do the three drivers of noise management apply to other health risks and are they
consistent across manufacturing sectors and industries? Further research with the same level
of rigour as this research is required to answer these questions. The questionnaire developed
as part of this study would apply to other sectors and occupational health risks, with some
refinement to the terminology used. Nevertheless, prior to carrying out further research it
would be preferential to conduct a validation exercise on the questionnaire through
exploratory factor analysis.
• How do small companies perceive HSE – as an enforcer or educator? This research
showed that managers in small companies were often either unaware that they could approach
HSE for information and guidance, or were hesitant to do so in fear of enforcement.
Understanding how small companies perceive HSE and what would encourage them to seek
advice and guidance through HSE channels would help to reach the out-of-reach companies,
typically small and potentially low performing with regard to health and safety.
In addition, to support the suggested interventions described in section 4.4.4, evaluation tools
need to be developed. Providing tools for managers to use themselves to measure the success
of interventions seems most valuable to help generate their commitment and stimulate
cultural improvements. Tools are also required to assist HSE inspectors should any changes
41
be made to the inspection process as described in section 4.4.1, including a cultural
assessment tool.
4.5
OVERALL CONCLUSION
It seems reasonable to conclude that noise management is primarily influenced by: managers’
own knowledge/awareness of noise as a significant health issue and the various types of noise
controls available to them other than hearing protection, the health and safety values or
culture of the company, and its size. Smaller companies have greater difficulty than their
larger counterparts with embarking on a sophisticated approach to control selection. This
appears to stem from their lack of knowledge of what is available and what controls could
work for them in practice, as well as their apparent reduced capability to make improvements
due to financial constraints or other resource issues. Their apparent preoccupation with
measuring noise rather than implementing effective controls seems to act as a further barrier
to making improvements. These findings are supported by the comparisons made between
high and low performing companies. High performers (larger companies) had better access to
health and safety resources than low performers (smaller companies). Interventions aimed at
improving noise management therefore need to address these influential factors; health and
safety culture in particular should not be underestimated as this has the potential to generate
the most improvement. Managers not only need better knowledge and awareness of noise
risks, health consequences and its long-latency nature, but also what controls/improvements
could work for them in practice given the environmental constraints that typically characterise
small companies. This is an important consideration in the current economic climate where
cost constraints may hamper the uptake of a comprehensive package of controls in small
companies. Whilst development of HSE’s noise website has the potential to assist larger
companies, targeted training interventions alongside inspections and awareness raising
through insurers, for example, should help to motivate and educate the hard-to-reach
companies.
42
5
REFERENCES 1.
Welch, B. L. Extra-auditory health effects of industrial noise: Survey of foreign
literature (Government Rep. No. AMRL-TR-79-41). Aerospace Medical Research
laboratory, Aerospace Medical Division, Air Force Systems Command, WrightPatterson Air Force Base, Dayton, OH; 1979
2.
ACOEM Noise and Hearing Conservation Committee. ACOEM evidence-based
statement: noise-induced hearing loss.
Journal of Occupational Environmental
Medicine 2003; 45: 579-81
3.
Cheung, C. Organizational influence on working people’s occupational noise protection
in Hong Kong. Journal of Safety Research 2004; 35: 465-475
4.
Tafalla, R. J., & Evans, G. W. Noise, physiology, and human performance: The
potential role of effort. Journal of Occupational Health Psychology 1997; 2(2): 148-155
5.
Williams, W., & Purdy, S. Factors in reducing occupational noise exposure. Journal of
Occupational Health and Safety 2007; 23(2): 165-177
6.
Casali, J. G. Sound and noise. In Salvendy, G. (Ed). Handbook of human factors and
ergonomics. 612-642; 2006.
7.
Smith, B. J., Peters, R. J., & Owen, S. Acoustics and noise control. 2nd ed. Addison
Wesley Longman Ltd: Essex, England; 1996
8.
Leinster, P., Baum, J., Tong, D., & Whitehead, C. Management and motivational
factors in the control of noise induced hearing loss. Annals of Occupational Hygiene
1994; 38 (5): 649-662
9.
Foster, G. Factors influencing the implementation of noise control programs in
industry. Journal of Occupational Health Safety 1996; 12(4): 471-475
10. Hughson, G. W., Mulholland, R. E. & Cowie, H.A. Behavioural studies of people’s
attitudes to wearing hearing protection and how these might be changed. HSE Research
Report 028; 2002
11. Barrett, J. H., Haslam, R. A., Lee, K. G., & Ellis, M. J. Assessing attitudes and beliefs
using the stage of change paradigm – case study of health and safety appraisal within a
manufacturing company. International Journal of Industrial Ergonomics 2005; 53: 871
887
12. Smallman, C. & John, G. British directors perspectives on the impact of health and
safety on corporate performance. Safety Science 2001; 38: 227-239
13. Gillen, M., Kools, S., McCall, C., Sum, J., & Moulden, K. Construction managers’
perceptions of construction safety practices in small and large firms: A qualitative
investigation. Work 2004; 23: 233-243
14. Wright, M., Marsden, S., Dimopoulos, E. Health and safety responsibilities of company
directors and management board members: 2001, 2003, and 2005 surveys. HSE
Research Report 414; 2006
15. Bentley, T. A., & Haslam, R. A. A comparison of safety practices used by managers of
high and low accident rate postal delivery offices. Safety Science 2001; 37: 19-37
43
16. Krause, T. R. Influencing the behaviour of senior leadership. Professional Safety 2004;
June Edition: 29-33
17. Timothy, N. Improving health at work: Employers’ attitudes to occupational health.
Association of British Insurers (ABI) proposals and supporting research by Greenstreet
Berman Ltd, in association with the Woodholmes Group; 2006
18. Shearn, P., & Miller, M. Director Leadership of Health and Safety. HSL Report:
SOFS/05/07; 2005
19. Webb, T. L., & Sheeran, P. Does changing behavioural intentions engender behaviour
change? A meta-analysis of the experimental evidence. Psychological Bulletin 2006;
132 (2): 249-268
20. Ferguson, E., Lawrence, C., Bibby, P., Leaviss, J., & Moghaddam, N.
conceptualisations of occupational disease. HSE Report 469: HSE Books; 2006
Lay
21. Gervais, R. L. An evaluation of successful communication with small and medium
sized enterprises (SMEs). HSL/2006/32; 2006
22. Colemont, A., & Van den Broucke, S. Psychological Determinants of Behaviours
Leading to Occupational Injuries and Diseases in Agriculture: A Literature Review.
Journal of Agricultural Safety and Health 2006; 12(3): 227-238
23. Gardner, D., Carlopio, J., Fonteyn, P. N., & Cross, J. A. Mechanical equipment injuries
in small manufacturing businesses. Knowledge, behavioural, and management issues.
International Journal of Occupational Safety and Ergonomics 1999; 5(1): 59-71
24. Rundmo, T., & Hale, A. R. Managers’ attitudes towards safety and accident prevention.
Safety Science 2003; 41: 557-574
25. De Waele, J.-P., & Harre, R. Autobiography as a psychological method. In Ginsburg,
G. P. (Ed.). Emerging strategies in social psychological research. Chichester: Wiley.
145-225; 1979
26. Jacobsen, D. M. Complimentary research methods.
http://www.ucalgary.ca/~dmjacobs/phd/methods/methods.ppt [cited 2010 Oct 20]
27. Bryman, A. Social Research Methods. 3rd ed. Oxford University Press; 2008
28. Coolican, H. Research methods and statistics in psychology. 4th ed. Hodder &
Stoughton: London; 2004
29. Ritchie, J., & Lewis, J. Qualitative research practice: A guide for social science students
and researchers. (Ed.). J. Richie and J. Lewis. London: Sage; 2003
30. Clark-Carter, D. Quantitative psychological research. Taylor & Francis Group: Hove
and New York; 2004
31. Cohen J. Statistical power analysis for the behavioural sciences. London: Wiley; 1988
32. Newell, C. E., Rosenfield, P., Harris, R. N., & Hidelang, R. L. Reasons for nonresponse on US Navy surveys: A closer look. Military Psychology 2004; 16(4): 265
276
33. Keisler, S., & Spoull, L. S. Response effects in the electronic survey. Public Opinion
Quarterly 2001; 50: 402-413
44
34. Comrey, A. L., & Lee, H. B. A first course in factor analysis. 2nd Ed. Hillsdale, NJ: L. Erlbaum Associates; 1992
35. Zimmerman, D. W., & Zumbo, B. D. In D. Clark-Carter. Quantitative psychological
research. Hove, UK: Psychology Press; 2004 36. Pope, C., Ziebland, S., & Mays, N. Analysing qualitative data. In C. Pope and N. May (Eds). Qualitative Research in Health Care. Blackwell Publishing: BMJ Books; 2006 37. Greenhalgh, T., & Taylor, R. How to read a paper: Papers that go beyond numbers (qualitative research). British Medical Journal 1997; 315: 740-743 38. Kline, P. The handbook of Psychological Testing. London: Routledge; 1993 39. Prendergrast, J., Foley, B., Menne, V., & Karalis Isaac, A. Creatures of habit? The art of behavioural change. London: The Social Market Foundation; 2008 40. Rosnow, R. L., & Rosenthal, R. In D. Clark-Carter.
research. Hove, UK: Psychology Press; 2004 Quantitative psychological 41. Kirkpatrick, D. L. Evaluating training programmes. San Francisco: Berrett-Koehler
Publishers, Inc; 1994 45
APPENDICES 46
APPENDIX 1 SUMMARY OF FACT-FINDING RESULTS
Table A2.1 shows (highlighted in yellow) the factors that emerged as having an influence on
dutyholders’/managers’ behaviour from both the literature review and interviews with
Inspectors. This covers the 20 factors discussed in the literature review: the 17 recommended
for inclusion in the questionnaire and the three that were not considered necessary to measure
(i.e. personality, employee attitudes and customer pressure). The factors have been numbered
accordingly (1-20) and elements relating to each are shown beneath each factor. Those
highlighted in yellow emerged as important elements to measure for each factor in both the
literature review and inspector interviews. Factors have been further grouped according to
the type of influence they exert following Green and Kreuter’s, 1991, PRECEDE model.
Indication of their potential strength or degree of influence is also indicated. For the literature
review an objective assessment was made according to the quality of the underlying evidence
and suggested influence according to previous research (strong (S), moderate (M) and weak
(W)). A simple distinction between influential, having some influence, and not being
influential was made according to the findings from the six interviews with Inspectors.
Factors believed to influence noise management that emerged from the interviews with the six
HSE Inspectors were broadly in line with the findings from the literature review. Inspectors
considered 14 of the 17 factors that were identified as important to measure in the literature
review as influential for noise management. Some differences were, however, noted in the
influence of the various factors on noise management. For example, compliance with
legislation was considered a key driver for dutyholders in the literature, yet Inspectors thought
that fear of civil claims was exerting greater influence in recent years. Whilst the interviews
with Inspectors provided some useful insights, findings need to be viewed in light of potential
biases inherent in their answers, given that most of the Inspectors had engaged with
dutyholders as part of an HSE inspection process. Additionally, only a small number (n=6) of
Inspectors were interviewed.
47
Table A2.1 Literature review findings mapped against interview findings
Factor
Literature Review
(strength)
Interviews (perceived level of
influence)
√ (S)
√ (Influential)
- Technical noise knowledge
√
√
- Noise legislation
√
X
- Health risks/effects of noise
√
X
- Business benefits
√
X
- Effects of safety culture & own
influence
√
X
√ (S)
√ (Influential)
- Senior Management commitment
√
√
- Fatalism
√
X
- H&S priority
√
√
- Worry/emotional outcomes
√
X
- Complacency
√
√
3. Values & beliefs:
√ (S)
√ (Influential)
- Concern for worker well being
√
√
- Integrity/honesty
√
X
- Positive outlook
√
√
- Time management
√
√
4. Self-efficacy
√ (S)
√ (Influential)
5. Risk perception:
Predisposing
1. Knowledge,
understanding:
awareness
2. Heath & safety attitudes:
&
√ (S)
√ (Influential)
- Locus of control
√
X
- Long-term vs. short-term risks
√
√
- Noise considered controllable
√
√
6. Personality
X (W)
X (Not influential)
7. Demographics:
√ (W)
√ (Some influence)
- Organisation size
√
√
- Company tenure
X
X
- Role of manager
√
√
- Geography
X
X
- Gender
√
X
- Industry type/operation
√
X
-Accident/incident/ill-health rates
√
X
√ (W)
√ (Influential)
-Ability to carry out risk assessments
√
√
- Ability to develop action plans
√
√
- Ability to determine controls
√
√
- Management style/attributes
√
√
Enabling
8. Skills/competence:
48
- HSE Inspector competence
X
√
√ (M)
√ (Influential)
√ (M)
√ (Influential)
√ (S)
X (Not influential)
√ (M)
√ (Influential)
- HSE information/guidance
√
√
- Perception of HSE
√
X
- Trust in sources
√
√
- Access to sources
√
√
- HSE Inspector advice
√
√
- Intermediaries
√
√
13. Compliance/legislation
√ (S)
14. Experience of a serious
accident &/or enforcement
15. Customer pressure
√ (M)
X (Not influential)
X (W)
X (Not influential)
16. Environment:
9. Resources
10.
Capability
improvements
11. Control
of
making
12.
Information
communications:
&
√ (W)
X (Not influential)
- Changing nature of work
√
X
- Pressure from suppliers/ contractors
√
X
Reinforcing
17. Safety climate/culture:
√ (S)
√ (Influential)
- Social norms/reaction
√
√
- Relationships
√
√
- Policies, practices, procedures
√
√
√ (M)
- Credibility of business
√
X
- To insurers
X
√
- Internal standards
X
√
19. Economic/financial:
√ (M)
√ (Influential)
- Ill-health costs
√
X
- Insurance premiums
√
√
- Civil claims
√
√
- Long-term savings
√
√
- Winning contracts/survival
√
X
X (M)
X (Not influential)
18. Corporate reputation:
20.
Employee
motivation
attitudes
&
Based on these results, Table A2.2 summarises the 15 recommended factors to be measured
in the research via questionnaire. These cover the 14 that emerged as influential from both
the literature review and interviews and an additional factor, ‘control’, that emerged as
important in the literature review for lowerlevel management. Given that the questionnaire
will target those who make the health and safety decisions, which dutyholders sometimes
delegate to lowerlevel managers, it is important to include items on control or perceived level
of influence. Whilst a reduction from the 17 factors recommended in the literature review to
49
these 15 factors does not represent a significant reduction, the elements recommended for
measuring within each factor are now more focused (as shown in Table A2.2). Care will be
taken to ensure that the questionnaire is a suitable length (e.g. four or five sides of A4) to
encourage participation.
A hypothesised effect of each of the included factors is shown in Table A2.2. This is based
on interpretations of various well-known psychological theories and established socialcognitive models during the literature review (e.g. Fishbein & Ajzen’s, 1975, 1980, Theory of
Reasoned Action and Theory of Planned Behaviour). The type and strength of influence will
be explored through the analysis of the questionnaire data.
50
Table A2.2 Included factors to be measured via questionnaire
Factor Name
1. Knowledge, awareness
& understanding
Elements to Measure
Technical noise knowledge including:
training/education received on noise
(usefulness & type) and general health
and safety; how equipped managers
feel to interpret noise surveys and
implement controls; a scenario to test
knowledge of noise (intermittent
exposure)
2. Heath & safety
attitudes
Senior management commitment (e.g.
‘To what extent do you have the
support of senior managers to
implement noise controls?’), health
and safety priority (e.g. ‘How seriously
do you / senior managers / employees
take health and safety?), complacency
and fatalism
3. Values & beliefs
Level of concern for the well being of
the workforce, long-term outlook and
time management
Reason for Inclusion/Exclusion of Elements
To provide insight into current knowledge levels.
Including a scenario to assess knowledge will account
for managers thinking they know enough about noise
when in actual fact they do not. Using an example of
intermittent noise exposure seems appropriate as
Inspectors commented that this is more complicated to
deal with. This would also provide insight into
knowledge of the legislation, health effects, risk
perception and whether managers view noise as
controllable or not. Knowledge of business benefits and
effects of the culture and own influence will not be
directly measured, but some insight will be gained in
questions on other factors (i.e. economic/financial,
safety climate/culture and skills/competence)
Important to gain an understanding of level of senior
management buy in. Assessing attitudes will give
insight into the health and safety culture given the
interrelationship between management attitudes/beliefs
and culture. This will also indicate the level of
employee buy-in. Fatalism is included due to the strong
evidence reported in the literature, but worry/emotional
outcomes are excluded as Inspectors highlighted that
these are less common for health issues
Closely linked with attitudes. Time management
appears particularly important for SMEs
51
Hypothesised Effect
A predisposing factor - may
moderate the impact of
attitudes on intention and
behaviour
A predisposing factor likely to have a direct
influence on behavioural
intentions, which in turn
affects behaviour
A predisposing factor likely to have a direct
influence on behavioural
intentions, which in turn
affects behaviour
4. Self-efficacy
Confidence and beliefs in own ability
to implement noise controls
Essential for translating knowledge into action
5. Risk perception
Short-term and long-term risks,
whether view noise as controllable and
locus of control
6. Demographics
Organisation size, role of manager,
access to the internet, whether the
organisation has a Trade Union (TU)
representative, and demographic
makeup of the company (e.g. ‘What
percentage of your workforce has
English as their second language?’)
7. Skills/competence
Ability to carry out risk assessments,
develop action plans, determine and
implement noise controls, experience
of dealing with noise (e.g. workers
suffering occupational hearing loss).
Also includes questions relating to
management style/attributes: drive and
All elements are important to measure and can be
examined through a scenario question (as suggested for
Factor 1). Although not mentioned by Inspectors, locus
of control is included based on the strong influence
apparent in the literature. This ties in with whether noise
is viewed as controllable (e.g. internally or externally
driven)
On the basis of the literature no items should be included
as the evidence was weak. The report on the Inspector
interviews, however, recommended reducing the
demographic items, in particular excluding geography
and gender. Only organisation size and managerial role
emerged as potentially having some influence. Access
to the internet and companies demographic makeup are
also recommended for adding important contextual
information when examining answers to questions on
communications. TU representatives tend to have had
health and safety training; an additional resource for the
company
Although the evidence in the literature was weak, this
was due to the absence of empirical studies and
inconclusive findings to date. The report on the
Inspector interviews recommended including items on
management style rather than personality. Inspectors
considered this as well as confidence to make decisions
and act on these as being instrumental in driving through
52
A predisposing factor likely to moderate the
relationship between
intention and behaviour
A predisposing factor likely to have a direct effect
on managers’ intrinsic
motivation to act
A predisposing factor potential moderators. For
example, knowledge,
training, access to
information etc, may vary
according to company size.
Whether managers have a
dedicated health and safety
role may also partly explain
variations in answers
A predisposing factor for
which the hypothesised
effect is unclear. Yet
competence is likely to
interact with knowledge,
awareness and
understanding to impact on
8. Resources
9. Capability of making
improvements
10. Information and
communications
11. Compliance/
legislation
motivation, involving the workforce in
decision-making, assertiveness,
willingness to listen, proactive,
approachable and leading by example
Perception of time, effort, equipment,
staff and funds to carry out engineering
changes. Again this could be
examined through a scenario-based
question (e.g. ‘If your Inspector
suggested that you retrofit noise
dampeners to your machinery, would
you….?’)
An item to explore dutyholders’/
managers’ perception of going beyond
PPE and implementing engineering/
organisational controls and health
surveillance
HSE information and guidance (e.g.
‘Do you know what to ask for of
Occupational Health consultants?’),
other external sources/intermediaries,
access to sources (e.g. ‘How accessible
is the HSE website/OH providers?’),
trust in sources (e.g. ‘How often have
you gone through the supplier of
machines, the HSE website, OH
providers, your Inspector, etc., to get
information on noise?’), effectiveness
of sources (e.g. ease to understand),
HSE Inspector advice and relationship
The extent that legislation and/or fear
of enforcement and civil proceedings
positive noise management
attitudes towards noise and
subsequent implementation
of higher level controls
Considered and influential drivers for SMEs than larger
companies in the literature, although this may have
changed in the current economic climate. Inspectors
also commented on the influence of resources. After all,
organisations will implement what is reasonably
practicable for them
An enabling factor - may
directly affect managers’
behaviour and indirectly
through encouraging the
acquisition of knowledge,
supporting attitudes etc
Relates to items on resources and self-efficacy and
seems pertinent for SMEs in the literature
An enabling factor –
implicated as a moderating
variable of managers’
motivation manage health
and safety
An enabling factor - likely
to have an indirect effect
through influencing
knowledge and motivation
to act
Important to examine the different information sources
that dutyholders/managers use as this guides their
decision-making and will therefore provide insights into
channels that HSE can influence. Intermediaries appear
to be particularly important for SMEs. Questions
surrounding advice given by HSE Inspector (if received)
will provide insight into Inspector competence (e.g.
whether focusing on PPE or recommending engineering
controls). Managers’ perception of their relationship
with the Inspector (e.g. coach/enforcer) and the HSE
guidance will illustrate their perception of HSE
Although the literature considered this to be a key driver
for managers, Inspectors thought that civil claims had
53
An enabling factor - likely
to directly affect behaviour
influence noise management
12. Safety climate/
culture
Focus on relationships
13. Corporate reputation
Include a scaled response question
(e.g. ‘To what extent have the
following had an impact on your
decision-making about noise
controls?’) with the following options:
meeting internal health and
safety/quality standards, reputation to
insurers, external reputation
Items examining the influence of
insurance premiums and civil claims
could be included in a scaled response
question as suggested above. Also, the
triggers for employees submitting civil
claims (e.g. visit to the doctor) and the
extent that managers have considered
long-term cost savings when
implementing noise controls
14. Economic/financial
15. Control
Whether manager received any
assistance when making noise
management decisions and what they
could successfully ask for
taken over, hence the requirement to include civil
proceedings. Findings suggest some degree of influence
and that legislation remains important to assess
Important to examine the channels of communication in
place between management, unions and the workforce
(e.g. toolbox talks, health and safety committee meetings
involving staff, etc). Other aspects regarding
organisational culture can be gleaned from items on
attitudes, beliefs and resources
Important to examine all aspects identified in the
literature review and interviews with Inspectors due to
differing views that emerged (i.e. external reputation
stressed as important in the literature, but internal
standards emphasised by Inspectors)
and indirectly though
creating the motivation to
act (externally driven)
A reinforcing factor indirectly affects behaviour
through influencing
knowledge, beliefs,
attitudes, and risk
perception
A reinforcing factor - may
moderate managers’
motivation to act and
directly affect noise
management behaviour
The report on the Inspector interviews recommended
including questions around the impact of insurance
premiums/insurers. Recognition of long-term cost
savings through implementation of higher-level controls
is also important. Ill-health costs are not applicable to
noise as workers rarely take time off due to hearing
problems. As such, the ill health costs associated with
noise are often hidden from employers. Similarly,
winning contracts was not deemed relevant as these tend
to feature safety rather than health concerns
Although not stated as an influencing factor by
Inspectors, the literature shows this as influential for
lower level management (Inspectors were focused on
dutyholders)
A reinforcing factor - likely
to directly affect noise
management behaviour
54
An enabling factor that
appears to moderate the
intention-behaviour
relationship
APPENDIX 2 PILOT STUDY METHODOLOGY
1.
Sample
A public database (MINT) containing approximately 2.6m UK-wide company records was used
to obtain the pilot sample. HSE’s Resource and Planning Directorate’s Information
Management Unit (IMU) supply MINT to the rest of HSE. While only 15% of the database is
accessible at any one time, it was considered to provide sufficient coverage of the private sector
for this research. HSE’s library and information services initially provided a random sample of
500 companies that were classified under one of 15 manufacturing SIC (Standard Industrial
Classification) codes selected by the HSE customer on the basis of noise being a known hazard
in these industries. Table A3.1 shows that these 15 SIC codes were further categorised into two
groups (i.e. metallic produce manufacturers and non-metallic produce manufacturers, a 50:50
split). This strategy was adopted to increase the likelihood of a representative sample being
obtained during the main research, which is more difficult with a large number of categories
(i.e. 15 SIC codes). These groupings also account for the noise levels in companies producing
metallic goods potentially being higher than the non-metallic produce group.
Table A3.1. Pilot sample classification
•
•
•
•
•
•
Metallic Produce (n=250)
Basic metals (SIC 27)
Fabricated metal products
28)
Machinery and equipment
29)
Motor vehicles and trailers
34)
Other transport equipment
35)
Recycling (SIC 37.10)
•
•
•
•
•
•
•
(SIC
(SIC
(SIC
(SIC
•
•
Non-Metallic Produce (n=250)
Food and beverages (SIC 15)
Textiles (SIC 17)
Wood and products of wood (SIC 20)
Pulp and paper products (SIC 21)
Printing (SIC 22)
Rubber and plastic products (SIC 25)
Other non-metallic mineral (glass and
ceramics) (SIC 26)
Furniture (SIC 36.1)
Recycling (SIC 37.20)
From the sample of 500 (250 metallic and 250 non-metallic) obtained, a very small proportion
was medium and large companies (reflective of the manufacturing sector mostly consisting of
small companies). Researchers therefore requested a further sample of companies, mostly
medium and large-sized. The total sample included 777 companies (with roughly an equal
divide between metallic and non-metallic), consisting of 428 small, 248 medium-sized and 101
large companies. Of the 777 companies provided, 205 could not be used as HSE FOD 40
divisions were unable to check whether these companies had been enforced or prosecuted over
the last three years, or were currently undergoing either of these 41 . Out of the 572 remaining
companies in the sample, 35 were removed that had recently experienced or were experiencing
formal enforcement action, leaving a total sample size of 537.
HSL researchers recruited 10 companies to take part in the pilot study. Table A3.2 shows the
participating companies according to size and SIC code. A good spread of metallic and non
metallic companies took part (five of each), mostly small companies (60%). Although this
representation of small companies falls short of the 90% cited above, it was considered
important to include medium and large companies for piloting the research tools because they
40
41
Field Operations Directorate The sample was sent to each of HSE’s FOD divisions to crosscheck against HSE’s enforcement database. 55
may have different experiences of noise management than smaller companies. Seven out of a
possible 15 manufacturing sectors (SIC codes) participated, which is reasonable for a sample of
10. Three participants belonged to SIC 29 (Machinery and Equipment), one of the largest
manufacturing sectors. Evidently, this sample is not representative and findings are only
indicative of what might be happening across the seven SIC codes included. It is important to
bear in mind that some industries (SIC codes) were not represented in the pilot study (e.g.
recycling, motor vehicles/transport equipment, and a range of non-metallic producers, such as
glass and ceramics).
Table A3.2 Participating companies broken down by size and SIC code
Group &
Primary SIC
Code
Metallic:
SIC 27
SIC 28
SIC 29
Non-Metallic:
SIC 15
SIC 17
SIC 20
SIC 21
Total
Small
Frequency of Participating Companies
Medium
Large
(0-49 employees)
(50-249 employees)
1
1
1
1
1
1
1
1
1
6
1
2
Total
(250+ employees)
2
1
1
3
1
1
1
2
10
Of the 10 companies that took part in the telephone interviews, seven completed and returned a
draft version of the questionnaire in the two months following the interview.
Although the sample was not representative of the UK population, this approach was deemed
acceptable for piloting the research tools. The main research will adopt a more stringent
approach to sampling (e.g. stratified for each SIC code and use of power analysis).
2.
Participants
Of the 10 participants that took part in this research, five held the title ‘Health and Safety
Manager’ (or equivalent); two were company Directors and three held a
‘Senior/Middle/Production Manager’ position with a health and safety remit. The majority
(n=6) had been in post and had been working within their company (n=7) for a minimum of two
years. The same sample was used for both the qualitative and quantitative aspects of the pilot
study. Seven of the 10 dutyholders/managers who took part in the telephone interview
completed the questionnaire.
3.
Procedure
HSL researchers contacted individual companies by phone and asked to speak to the health and
safety manager or equivalent, briefly describing the research process before asking if managers
would be willing to take part in the pilot study. The participant’s contact details were then
checked and a date and time for the telephone interview arranged. HSL researchers sent a
confirmation email and information sheet to managers detailing further information about the
56
research and the contact numbers of the research team should they have any questions prior to
the interview. All managers were asked to provide written consent 42 .
Telephone interviews generally lasted between 20 and 40 minutes. All participants gave
consent for their interview to be digitally recorded and transcribed. HSL researchers followed
the interview schedule asking follow up questions as appropriate. At the end of the interview
managers were asked if they would be willing to complete a questionnaire up to eight weeks
after the interview and provide written feedback at the end of the questionnaire (on clarity,
relevance of items, etc). The questionnaire was sent to managers in an electronic format as
requested with a twoweek completion deadline.
Given that only seven of the 10 managers that participated in the pilot study returned
questionnaires, a group of 11 HSE/HSL subject matter experts 43 were contacted and asked to
complete the questionnaire. This was carried out purely to provide an additional check on the
face and content validity of the questionnaire, not as a means of gathering further data. Experts
were asked to think of a manufacturing company, preferably small in size, that they had
previously visited where noise was/is a problem and answer questions as if they were the health
and safety manager of that company. Experts were also asked to provide written feedback on
the questionnaire items. Four of the 11 experts completed the questionnaire and provided
feedback.
4.
Data analysis process
4.1
Telephone interviews
The analysis of the 10 telephone interviews was separated into two stages:
Stage 1
• One researcher developed a spreadsheet to capture separate information from each of
the 10 participants that was relevant to the 19 questions covered during the interviews.
Two other researchers checked this.
• The transcripts were then divided between three researchers who populated the
spreadsheet with commentary and quotations, which were line referenced. Researchers
checked a random 20% of each other’s inputs.
Stage 2
• One researcher was allocated the demographic items and questions 1-4 of the interview
schedule and a second researcher was allocated questions 5-16.
Both researchers analysed the data identified at stage one for each of the 10 participating
companies and refined it down, firstly into overarching themes and finally down to elements (or
sub-themes). Researchers checked one another’s themes and elements extracted.
42
Please note: Nine out of the 10 managers that participated completed written consent forms; one manager gave
verbal consent on three separate occasions due to IT difficulties with returning the consent form.
43
Two were HSE Specialist Noise Inspectors; four were HSL Occupational Hygienists; three were HSL noise
researchers/practitioners; and two were HSL employees who had previously worked on the area of noise in either
HSE/HSL (e.g. previously a noise inspector).
57
4.2
Questionnaire
Seven completed questionnaires do not permit any robust quantitative testing to be conducted.
As such, analysis of the draft version of the questionnaire (both from managers and subject
matter experts) was mostly qualitative in nature, focusing on the written feedback on the draft
questionnaire and eyeballing responses given by participants. Descriptive analysis on SPSS 44
was carried out to draw inferences about whether the current questions would yield data that
adequately addresses the research aims rather than to report on managers’ attitudes and
behaviours towards noise control. More specifically, quantitative (descriptive) and qualitative
analysis of the questionnaire examined whether:
• Individual questionnaire items discriminate. The vast majority of participants did not
score high or low on one item unless there appears to be a valid explanation (e.g.
attitudinal items may yield similar responses across participants, which is valid
providing that individual participants consistently display similar attitudes in their
responses to related questionnaire items).
• Missing data is random and not systematic. The latter refers to situations where
participants consistently choose not to answer particular items.
• Checking whether overall responses are in line with researchers’ expectations (i.e.
participants’ responses to different items do not contradict one another). This is
particularly important for examining the effectiveness of the two dependent variables
on noise levels and current management behaviours/noise controls.
• Checking for evidence of participants providing socially desirable responses (i.e.
responding in a way that they think the researcher will consider favourable). This can
be achieved through examining responses to one of the dependent variable assessing
current noise controls/practices. More specifically, checking whether participants had
selected all of the available response options including the three options that are not
necessary for effective noise management (referred to as ‘red herrings’).
This preliminary analysis is considered sufficient for suggesting necessary modifications to the
draft version of the questionnaire prior to the main research.
44
The Statistical Package for the Social Sciences version 14.
58
APPENDIX 3 QUESTIONNAIRE
HSL Ref: _________________________________________
HOW DO YOU MANAGE NOISE AT WORK?
HELP US TO HELP YOU MANAGE NOISE AT WORK
The Health and Safety Laboratory has been commissioned by government to find out how noise advice and guidance
for employers and managers, like yourself, can be improved. We want to know how you manage noise at work,
where you get your information from, what helps you to make your decisions.
Neither you nor your company will be identified in the research report.
Please don’t waste your chance to steer us in the right direction. The more people who respond, the more convincing researchers at the Health and Safety Laboratory can be on your behalf. Tell us - Your views are important and will be heard!
Once we receive your completed questionnaire we will send a £5 donation to one of the following charities of your choice - Please select one (tick one box).
I would like £5 to go to:
Royal National Institute for the Deaf
British Tinnitus Association
Deafness Research UK
Hearing Dogs for Deaf People

Your completed questionnaire will be treated in confidence. Researchers from the Health and Safety Laboratory will
process the questionnaire. Responses from individuals or organisations will not be identified in any way.
Please fill in this questionnaire as fully and honestly as you can, telling us what you would do, not what you think you
should do.
Please read the whole question carefully before answering. A few questions will require a written answer - please
write clearly in BLOCK CAPITALS.
Once completed please return the questionnaire using the prepaid envelope provided BY [INSERT DATE].
59
ABOUT YOU AND YOUR COMPANY
Q1. How many people does your company employ?
Up to 10
11 - 49 2
1
Q2. What sector is your company in?
Food & beverages
1
Textiles 2
Wood/Products of wood 3
Pulp/Paper products
4
50 - 249
Basic metals
Rubber/Plastic products
Fabricated metal
products
Machinery & equipment
3
6
7
8
250 plus
Furniture
Recycling
Other transport
equipment
Other non-metallic
mineral (e.g. glass &
9
4
11
12
13
14
ceramics)
Printing 5
Motor vehicles & trailers 10
Other sector (please state 15
below)
If you selected other, please specify:
_____________________________________________________________________________
Q3. What is your company's main product/service?
Please write in BLOCK CAPITALS
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
___________________________________
Q4. Is your company part of a larger group?
Yes
1
Q5. What is your role?
No
2
Tick the box that best describes your role.
Owner
1
Director 2
Senior Manager 3
Health & Safety Manager 4
Manager
Supervisor
Works / Production 7
Manager
5
6
Q6. Is there a health and safety representative within your company?
Yes
No
1
2
Don't know
3
Q7. Is there a Trade Union representative within your company?
Yes
No
1
2
Don't know
3
NOISE LEVELS AND CONTROLS IN YOUR COMPANY
Q8a. Think about the most common noisy activities that are carried out by your workers. Please tick the
statement that best describes the noise levels experienced by workers during these activities.
Impossible to talk even by shouting in someone's ear
1
Noise level means people have to shout when talking to a workmate 1 metre away
2
Noise level means people have to shout when talking to a workmate 2 metres away
3
No need to shout at 2 metres but the noise is intrusive, comparable to the noise in a busy street
4
60
Q8b. Approximately, what proportion of your workforce carries out these noisy activities?
About a half (50%)
None (0%)
1
4
Under 10%
About
three
quarters
(75%)
2
5
About a quarter (25%) 3
All or almost all 6
Q9. Approximately, what proportion of your workers routinely makes use of hearing protection during the
working day?
None (0%)
About a half (50%)
1
4
Under 10%
About three quarters (75%)
2
5
About a quarter (25%) 3
All or almost all 6
Q10. What three things would you do if one of your machines/tools were identified as a noise hazard?
(Tick the
three that you feel are most worthwhile).
Set up hearing protection zone / signs 1
around it
Plan to replace it with a quieter one
2
Investigate my options 3
Have noise levels measured
Enclose the machine
Rotate staff in the area
6
Introduce hearing tests 7
Review work process that leads to the 8
hazard
Reorganise / place it elsewhere 9
4
5
Q11. What three things would you do if some of your workers now need to wear hearing protection, when
they didn't previously? (Tick the three that you feel are most worthwhile).
Set up earplug dispensers in the work areas 1
Look into costs of different protectors
7
Put up hearing protection zone signs
Get workers to sign for hearing protection 8
2
Introduce hearing tests for workers
3
Ask workers which protectors they prefer 4
Give training on how to use protection
9
Find out what types of protector are suitable 10
Brief workers on where the noisy areas are 5
Brief supervisors on problems to look out 11
for
Review your disciplinary procedures
6
Q12. Which of the following do you currently undertake or provide?
Training on how to use hearing protection 1
Monitor HSE updates on noise
2
Training on noise risks
Contact external experts about noise
Check workers are wearing protection
Replace radios with MP3 players
3
4
5
6
Tick all that apply.
Hearing protection for workers
Stop people working when they reach
exposure limits
Hearing tests for workers
Limit operator time in noisy areas
Building layout to control noise
Buying 'quiet' replacement machine/tools
10
11
12
13
14
15
Correcting worker poor practice 8
Record how long workers use hearing 16
protection
Regular maintenance of noisy machinery 17
Barriers / screens / enclosures to reduce 9
noise
Engineering/technical noise reduction 18
programme
Noise risk assessments 7
61
YOUR EXPERIENCE OF MANAGING NOISE
Q13. To what extent do you agree with the following statements?
Strongly agree
Agree
Being deaf can affect your life
We only make significant improvements if
something goes wrong
Noise regulations are not a burden
I have an open door policy on healthrelated issues
We tell workers how to protect their
hearing; it's then up to them
Sometimes production is given priority over
health matters like noise
Noise is not one of our top priorities
Workers do not need telling about noise
risks when they have been working in the
industry for years
Senior managers take noise risks seriously
Workers do not take noise risks seriously
Noise problems are solved by workers
wearing their hearing protection
Tasks that workers are doing put them at
risk of going deaf in the future
Please answer honestly.
Neither agree
nor disagree
Disagree
Strongly
disagree
1
1
2
2
3
3
4
4
5
5
1
1
2
2
3
3
4
4
5
5
1
2
3
4
5
1
2
3
4
5
1
1
2
2
3
3
4
4
5
5
1
1
1
2
2
2
3
3
3
4
4
4
5
5
5
1
2
3
4
5
Q14. How do you communicate to workers about noise risks / hearing protection?
(Please tick all options that
apply)
Briefings / Toolbox talks
Distribute company own noise guidance
Distribute HSE / Industry noise guidance
Distribute minutes from health & safety
meetings
Via Union members / worker
representatives
1
2
3
4
Talk to workers myself
Through managers / supervisors
Signage
Staff inductions
5
Through occupational health service(s)
Strongly agree
Agree
I am concerned about the health of my
workers
It is only wishful thinking to believe that I
can influence company noise decisions
Risks from noise cannot be controlled by
management
When I have a noise related problem, I can
usually find the right solution
I do not have enough time to deal with
heath issues like noise
I am confident in my ability to make
decisions on noise
I develop action plans for resolving noise
issues and drive through changes
I do not have difficulty motivating workers
to protect themselves against industrial
deafness
6
7
8
9
10
Neither agree
nor disagree
Disagree
Strongly
disagree
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
62
I often feel helpless about dealing with
noise issues in my job
I make sure that noise is included in risk
assessments
I have a wealth of experience to draw from
when making decisions on how to reduce
noise
I listen to workers views about ways to
reduce noise
I believe it's worth getting my workers'
hearing tested
Nothing stops me from tackling noise
issues in my company
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
Satisfied
Neutral
Dissatisfied
Strongly
dissatisfied
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
Q16. How satisfied are you with the following?
Very satisfied
The amount of training that you have
received just on noise
The quality of training received just on
noise (i.e. did it help you?)
The amount of general health and safety
training that you have received
The quality of general health and safety
training received (i.e. did it help you?)
Q17. How much does each of the following prevent you from tackling noise in your company?
A great deal
Quite a lot
Moderate
Just a little
amount
The demands of my job
2
3
4
1
Lack of support from my colleagues
2
3
4
1
Lack of support from my Directors
2
3
4
1
Not knowing what all my options are
2
3
4
1
The cost of replacing machinery / tools for
2
3
4
1
quieter models
Existing machinery / tools are still fit for
2
3
4
1
purpose
The time that it would take
2
3
4
1
Unable to delegate health and safety tasks
2
3
4
1
to others
Dealing with safety matters
2
3
4
1
Building layout / Design
2
3
4
1
Health and safety budgets
2
3
4
1
Not at all
5
5
5
5
5
5
5
5
5
5
5
NOISE INFORMATION SOURCES
Q18. How often do you access the following for information on noise?
Often
Sometimes
HSE website
2
1
Machinery suppliers
2
1
Your HSE Inspector
2
1
Industry guidance
2
1
Published HSE guidance
2
1
Other companies / competitors
2
1
Internet
2
1
63
Rarely
Never
3
3
3
3
3
3
3
4
4
4
4
4
4
4
2
2
2
2
1
1
1
1
Insurance companies
Direct call to HSE
Direct contact with your Local Authority
Other (please specify)
3
3
3
3
4
4
4
4
_____________________________________________________________________________
Q19. How helpful is the following for understanding what you need to do to protect your workforce from
noise risks?
Very helpful Helpful
Neither helpful Unhelpful Not helpful
Not
nor unhelpful
at all
applicable
HSE website
2
3
4
5
6
1
Machinery suppliers
2
3
4
5
6
1
Your HSE Inspector
2
3
4
5
6
1
Industry guidance
2
3
4
5
6
1
Published HSE guidance
2
3
4
5
6
1
Other companies / competitors
2
3
4
5
6
1
Internet
2
3
4
5
6
1
Insurance companies
2
3
4
5
6
1
Direct call to HSE
2
3
4
5
6
1
Direct contact with your Local
2
3
4
5
6
1
Authority
Other
2
3
4
5
6
1
_____________________________________________________________________________
Q20a. How often do you call for expert advice (e.g. noise consultants, occupational health/surveillance) on
noise matters?
1
2
3
4
Often
Sometimes
Rarely
Never
Q20b. How helpful are recommendations given to you by these experts for making improvements?
1
2
3
4
5
6
Very helpful
Helpful
Neither helpful nor
unhelpful
Unhelpful
Not helpful at all
None are given
[GO TO Q21]
Q20c. Of these recommendations have you acted on:
1
2
3
4
5
A lot
Most
Some
A few
None at all
Strongly
Disagree
Neither agree
disagree
nor disagree
I have all the information I need to
2
3
1
understand how to deal with noise risks
in my company
I know where to get help when I have a
2
3
1
problem with noise
We cannot find information on quieter
2
3
1
models of machinery / tools we use
64
Agree
Strongly agree
4
5
4
5
4
5
I know where to get information on
health surveillance / hearing tests
2
1
3
4
5
YOUR NOISE DECISIONS AND MANAGEMENT
Strongly agree
Agree
Neither agree
nor disagree
My organisation has a well-known
2
3
1
brand name in our area
We control noise as well as most other
2
3
1
companies in our industry
The director(s) think that worker ill2
3
1
health is a big risk for the business
The Company is run by a few people.
1
2
3
There is not much that I can do about
noise issues
It is not possible for us to do more than
2
3
1
provide hearing protection
Health and safety legislation drives
2
3
1
what we do about noise
I can influence noise management in
2
3
1
this Company
We try our best to comply with noise
2
3
1
legislation
Our insurers have told us to reduce
2
3
1
noise levels / exposures
We are afraid of the consequences of
2
3
1
not complying
We want to deal with our noise problem
2
3
1
to avoid future claims
I try to work out technical solutions to
2
3
1
noise problems
Replacing just one machine / tool with a
2
3
1
quieter model makes little difference to
noise levels
Quieter models of machines / tools that
2
3
1
we use do not exist
Eliminating / minimising noise will save
2
3
1
us money in the long term
Disagree
Strongly
disagree
4
5
4
5
4
5
4
5
4
5
4
5
4
5
4
5
4
5
4
5
4
5
4
5
4
5
4
5
4
5
YOUR COMMENTS
Q23. Please use this box if there is anything else you would like to add about how you manage
noise__________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
______________________________________________________________________________________________
___________________________________________________________
65
Harpur Hill, Buxton
Derbyshire, SK17 9JN
Telephone +44 (0)1298 21800
Facsimile +44 (0)1298 218590
[Questionnaire Reference Number]
[Company Name & Address]
[Date]
Dear Sir/Madam,
I am a Senior Psychologist working at the Health and Safety Laboratory (HSL) in Buxton. We
are currently carrying out research on the management of noise risks at work. You are one of
800 manufacturing companies randomly selected to take part.
In order to make sure that future noise guidance is helpful for employers, we would appreciate
hearing your views by filling in this short questionnaire. It should take you about 15 minutes.
It asks about what you have put in place to protect your employees against hearing damage/loss
and the information sources that you use. It also asks a range of questions relating to your
attitudes and beliefs about noise. Any information that you can give us would be valuable for
our research.
Taking part in this research is entirely voluntary. You may withdraw from the research at any
time without giving a reason. You do not have to answer any questions that you do not want to.
The information is both anonymous and confidential and will be considered as part of a
group, not an individual response. The number at the top of this letter and the questionnaire
represents your response reference number. This letter is for you to keep. Your questionnaire
will be stored under this reference number, not your name or your company’s name. It will not
be possible for anyone to identify you or your company from your questionnaire responses.
Please use the reference number in any correspondence with HSL researchers especially if you
wish to withdraw from the research after returning the questionnaire. Under no circumstances
will you or your company be identified in research reports/articles. HSL’s data
management systems abide by the requirements of the Data Protection Act. Your questionnaire
will be held at HSL in a locked cabinet and will only be used by researchers involved in the
project for the purposes of this research.
A FREEPOST envelope is provided for you to return your questionnaire to me. Please return
it by [Date]. Upon receipt of your completed questionnaire, we will make a £5 contribution to
your choice of one of the four selected charities.
I would like to thank you for helping us with our research. Feel free to contact me directly with
any questions that you have relating to this research.
Yours kindly,
[Researcher singature]
66
APPENDIX 4 INTERVIEW PROTOCOL
Interview Schedule for Dutyholders / Managers
Influences on dutyholder behaviour on the control of noise risk
Introduction:
• The Health and Safety Executive want to gain a better understanding what influences how
dutyholders’ control noise risks so they can improve HSE advice and guidance to dutyholders.
They have asked us at HSL to carry out the research on their behalf.
• We have sent out 800 questionnaires and your organisation is one of approximately 15 businesses
that have agreed to be interviewed for this research. We would really appreciate honest answers, as
this is crucial for this research to make a difference.
• Any data gathered in this study will be treated as commercial in confidence, and findings will only
be published without identifying which individuals or businesses participated. A written report on
findings will be available from the HSE. All participating organisations will also receive a copy of
the final report produced towards the end of next year.
• Your interview will take around an hour (no longer than 90 minutes).
• For research purposes only, with your permission, we would like to audio-record your interview
so that we can have an accurate record of our discussion. Only work psychologists at HSL will
listen the recording and we will store all your information in a secure, locked cabinet that only we
have access to, and destroy it after the research project.
• Any questions before we start?
NB: Follow up prompts have been suggested, if relevant and not covered by interviewees
in their response.
Questions:
Interviewer:
Date:
Interview with: (Please introduce yourself)
Notes by:
Name of Organisation:
What does the organisation do?
What does it make?
What services does it provide?
(Categorise sector later)
No. of Employees:
1 – 10
11-49
50-249
250 +
How noisy is the workplace?
•
•
•
•
Impossible to talk even shouting in someone’s ear.
Noise level means people have to shout when talking
to a workmate 1 metre (approx. 3 ft.) away.
Noise level means people have to shout when talking
to a workmate 2 metres (approx. 6 ft.) away.
No need to shout in conversation at 2 metres (approx.
67
6 ft.) but the noise is intrusive, comparable to the
noise in a busy street.
Job Title and Job Role (management level)
Length of Time in Post:
Length
of
Time
in
organisation:
You said you’ve been in this role X years. Can you give me an overview of your
(employment) background?
Have you done any health and safety related training?
General H&S training
Noise control specific training
NEBOSH, IOSH, etc.
Usefulness?
Any recognised TU on site and which one(s)?
1)
What are your company’s main problem areas for noise? Or: I see that your workers
use X machine / carry out Y process – Does this pose the biggest noise risk to your workers?
• The level of risk this/these areas present? (High / Medium / Low) (E.g. harm – could
affect everyone, some, a few).
• Why are these areas problematic for noise?
•
Any formal assessment of this?
2) Roughly, what proportion of your workforce actually experiences this level of noise / carry
out these noisy activities?
3) What is your company doing / done about the noise that workers are exposed to?
Has your organisation / is your organisation planning to –
• Put in place engineering controls? (e.g. OH surveillance, limit operator time, machinery
purchase policy, noise policy, risk assessments, maintenance programme).
• Put in place organisational controls? (e.g. segregating noisy activities, modified paths
by which noise travels through the air, building layout, buying quiet machinery/tools, noise
reduction programme).
• Provided training to staff (risks / PPE).
• Monitoring updates (HSE / Industry).
• If only personal hearing protection has been implemented – Probe why?
• What are these controls doing? How do you know this?
4)
How did you decide on the controls you’ve currently got in place?
• Who decided?
68
• Were there any controls you decided not to go ahead with? (Probe reason and decision
makers/making behind these).
•
If only personal hearing protection has been implemented – Probe why?
• If workers get hearing protection what type (is it based on individual need or company
buying policy)?
•
5)
How have you found the changes?
Where do you go to, to get your information about noise risks and noise controls
(including hearing protection)?
•
•
Have you always used these sources of information?
What prompted you to use them in the first place?
What information on noise risks and controls is provided to staff?
6)
•
•
•
•
•
•
7)
What does this cover?
How is this supplied? (E.g. word of mouth, leaflets, training – formal vs. informal)
How receptive are workers to this?
Do workers have a good understanding of what the risks are?
Is it working? How do you know?
What are the arrangements for taking into account the views of workers?
What is your company doing in terms of regular checks on workers’ hearing, carried out
by a medical professional?
•
•
•
•
•
•
•
How go about this? (E.g. in-house OH, contractor)
Why decide to do this? (E.g. requirement of insurance companies)
Is this considered important? (NB: probe for honest answer)
How use this information?
Any hearing issues (tinnitus/hearing impairment)?
Is noise a big health risk in your business / sector?
Are there other greater health risks in your business / sector? (What?)
Is there anything else you can think of that your company has done to protect workers
from noise risks? (Provide example)
8)
9)
How do you keep a balance between controlling noise and getting the job done?
•
•
•
•
10)
Control of noise at source?
Balance with productivity?
Any examples where some tough decisions had to be made?
Any consequences?
How confident are you that what your company has done is sufficient?
•
•
•
Are the controls working? (How do you know?)
Right type of PPE? (How do you know?)
Any concerns?
69
• Any limitations to the approach adopted?
• How do you know that the system you have in place is continuing to do what is was set
up to do? [Maintenance & ongoing monitoring]
11)
What might make you and/or other managers take another look at how your
organisation controls noise risks?
12)
Is there anything else that has impacted on the way your company has tackled noise?
• Within the organisation?
• External influences? (E.g. court cases, other companies, insurers, reputation)
13)
How much influence/power do you have to make financial decisions about health and
safety in your business?
• Capability to make decisions that have potential to affect production e.g. equipment
moves (get example if possible)?
Level of financial responsibility for H&S budgets? 14)
If you have responsibility for other members of staff, in what ways do they support your
health and safety role?
• Ability to delegate tasks to others?
• Time to get away from the paper work to see what is happening on the shop floor?
15)
Where would you say that you get most support and least support for implementing
noise controls? (Give an example how that has been demonstrated)
• Senior Managers
• Workers
• Trade Union Rep
16)
In order to deal with noise, what would help you the most? Where would you like to
get this support from?
• Is there anything else HSE can do?
Final Question:
17)
Is there anything else you would like to add?
Thank you very much for your time.
70
APPENDIX 5 SUPPLEMENTARY MATERIAL - SAMPLING
Table A5.1 Sample breakdown for 800 postal questionnaires administered Metallic Sector
Sub-Totals
% of 800 distributed
Non-Metallic Sector
Sub-Total
% of 800 distributed
Grand total
SIC Code
27
28
29
34
35
37.1
15
17
20
21
22
25
26
36.1
37.2
Total number of
companies
2,561
26,797
10,944
2,430
3,326
835
46,893
9,630
6,900
11,048
2,384
25,982
5,730
6,676
7,485
1,436
77,271
124,164
% of sub-sample
6%
57%
23%
5%
7%
2%
100%
38%
12
9
14
3
34
7
9
10
2
100%
62%
100%
71
Number of questionnaires
distributed
16
173
70
15
22
6
302
60
45
70
15
168
35
45
50
10
498
800
Figures A5.1 and A5.2 Sample obtained for metallic and non-metallic companies
respectively
50
45
Number of companies
40
35
30
Sample
25
Ideal sample
20
15
10
5
0
27
28
29
34
35
37.1
SIC codes/sub-sector
Figure A5.1 Number of returns from metallic companies versus the ideal representation 50
45
Number of companies
40
35
30
Sample
25
Ideal sample
20
15
10
5
0
15
17
20
21
22
25
26
36.1
37.2
SIC codes/sub-sector
Figure A5.2 Number of returns from non-metallic companies versus the ideal
representation
72
Table A5.2 Demographic profile of 15 site interviews
Case
Metallic
2
Size
SIC code
Management position
S
27
4
6
7
11
M
M
S
L
29
28
29
29
13
14
15
M
M
L
34
27
28
Head of ‘Chase’ Department with Health
& Safety responsibilities
Health & Safety Advisor
Safety, Health & Environment Manager
Owner
3 interviewees: Safety Engineer, Health &
Safety Coordinator & Manufacturing
Engineer
Health & Safety Advisor
Health & Safety Manager
Health, Safety, Environment & Security
Manager
Non-Metallic
1
M
3
S
25
37
Production Director
Technical Manager
Business Manager
2 interviewees: Production Director &
Production Manager
Director
Health, Safety & Environmental Manager
Shared Resources Health & Safety
Advisor
5
8
M
M
21
26
9
10
12
S
L
L
20
26
15
73
Location
London
Lincoln
Doncaster
Southampton
Basildon
Bolton
Ashford
Redditch
Skegness
West
Bromwich
Corby
Scunthorpe
Huddersfield
Stoke-on-Trent
Bristol
APPENDIX 6 SUPPLEMENTARY MATERIAL – DATA ANALYSIS
Table A6.1 Scoring system for implemented noise controls
Controls implemented
Basic controls included:
• Hearing protection for workers
• Training on how to use hearing protection
• Monitoring HSE updates on noise
• Training on noise risks
• Contacting external experts on noise
• Checking workers are wearing hearing protection
• Noise risk assessments
• Correct worker poor practice
Higher level controls included:
• Barriers/screens/enclosures to reduce noise
• Hearing tests for workers
• Limit operator time in noisy areas
• Building layout to control noise
• Buying ‘quiet’ replacement machinery/tools
• Regular maintenance of noisy machinery
• Engineering/technical noise reduction programme
Red herrings that have little impact on employee health:
• Stop people working when they reach exposure limits
• Record how long workers use hearing protection
Red herring that could negatively impact employee health:
• Replace radios with MP3 players
Total Score
Score (range)
1
(‘0’ - ‘8’)
2
(‘0’ to ‘14’)
-1
(Subtracted from total score for
each item selected)
-2
(Subtracted from total score if
selected)
- 4 – 22
Figure A6.1 Categorisation of companies according to perceived risk to the business
from noise
High
1
Risk to the business from noise
High noise levels &
proportion of
workers exposed
2
3
High noise levels &
medium proportion of
workers exposed
Medium noise levels
& high proportion of
workers exposed
Medium noise levels
& proportion of
workers exposed
4
Low
Low noise levels &
proportion of
workers exposed
High noise levels &
low proportion of
workers exposed
Medium noise levels
& low proportion of
workers exposed
Low noise levels &
high proportion of
workers exposed
Low noise levels &
medium proportion of
workers exposed
Noise levels
High - Impossible to talk even shouting in
someone’s ear
Medium - Need to shout when talking to a
workmate 1 or 2 meters away
Low - Noise is comparable to a busy street
6
5
Proportion of workforce exposed
High - about three-quarters or all (75/100%)
Medium - about a quarter or half
(25-50%)
Low - under 10%
74
Table A6.2 Performance classification criteria for the company site visits
High performers
Medium and Low criteria
plus the following:
• Hearing protection/noise
risk training
• Compliance/good use of
hearing protection
• Noise action planning
• Researched/implemented
engineering/technical
noise reduction
programme
• Regular maintenance of
noisy machinery/tools
• Job rotation/limit worker
exposure
• Worker involvement
(formal and/or informal)
Moderate performers
Low performers
Low criteria met plus the • Noise risk assessments
following:
• Provide hearing
• Check workers wearing hearing
protection
protection/general compliance
• Noise measurements/survey
• Noise policy
• Audiometry/health surveillance
• Barriers/screens/enclosures/
hearing protection zones
• Possible – Included noise in
machinery/tool purchasing
decisions
• Possible – Hearing protection/
noise risk training
75
APPENDIX 7 SUPPLEMENTARY MATERIAL - RESULTS
Table A7.1 Internal consistency results
Factor
number
1
2
3
4
5
6
7
Original factor name (internal
consistency result)
Knowledge (α = 0.700)
Attitudes, values & beliefs (α = 0.359)
Self-efficacy (α = 0.524)
Skills/competency (α = 0.648)
Resources (α = 0.872)
Information and communication (α =
New factor name (internal consistency
result)
Knowledge & awareness (α = 0.700)
Attitudes, values & beliefs (α = 0.534)
Self-efficacy (α = 0.718)
Autonomy & competence (α = 0.740)
Resources (α = 0.895)
Information and communication (α =
0.576)
0.717)
Compliance with legislation (α = Organisational health and safety values (α
0.284)
= 0.531)
8
Health & safety culture/climate (α = Business motivators (α = 0.588)
9
10
11
Reputation (α = 0.274)
Business (α = 0.348)
Control (α = 0.525)
0.537)
Table A7.2 Breakdown of responses to demographic items
Demographic item
Q1. Company size
Q2. Sector
Q4. Company part of
a larger group?
Q5. Role
Response category
Micro (up to 10)
Small (11-49)
Medium (50-249)
Large (250 plus)
Food & beverages
Textiles
Wood/Products of wood
Pulp/Paper products
Printing
Basic metals
Rubber/Plastic products
Fabricated metal products
Machinery & equipment
Motor vehicles & trailers
Furniture
Recycling
Other transport equipment
Other non-metallic mineral (e.g. glass
& ceramics)
Other
Missing
Yes
No
Missing
Owner/Director
Senior Manager
Health & Safety Manager
Manager
76
Number of participants
107
80
24
4
12
7
17
2
47
4
2
28
19
3
6
0
4
4
57
3
38
173
4
97
28
35
40
Supervisor
Works/Production Manager
Missing
Yes
No
Yes
No
Don’t know
Missing
Q6. H&S rep in
company?
Q7. TU rep in
company?
DV
IV1
IV2
IV3
IV4
IV5
IV6
IV7
IV8
IV9
IV10
IV11
DV
1.000
.332
.333
.271
.336
.037
-.278
.504
.263
.456
-.363
.393
2
9
4
162
53
17
195
2
1
IV1
IV2
IV3
IV4
IV5
IV6
IV7
IV8
IV9
IV10
IV11
1.000
.267
.294
.397
.275
-.451
.259
-.021
.134
-.211
.232
1.000
.398
.374
.254
-.182
.482
.064
.278
-.207
.266
1.000
.546
.205
-.157
.531
.107
.134
-.121
.174
1.000
.209
-.318
.431
.215
.137
-.040
.201
1.000
-.228
.099
-.187
-.129
-.014
-.027
1.000
-.200
-.039
-.068
.050
-.173
1.000
.284
.291
-.198
.245
1.000
.180
-.170
.148
1.000
-.540
.565
1.000
-.411
1.000
**Correlation is significant at the 0.01 level (green-shaded cells).
*Correlation is significant at the 0.05 level (yellow shaded cells).
Table Key:
DV
IV1
IV2
IV3
IV4
IV5
IV6
IV7
IV8
IV9
IV10
IV11
Dependent variable – Noise controls implemented
Knowledge
Attitudes towards workers (health risks & behaviours)
Self-efficacy
Autonomy and competence
Resources / barriers
Information and communications
Organisational / cultural (health & safety)
Business motivators
Company size
Manager role (Director/Owner)
Manager role (H&S Manager)
Figure A7.1 Correlation matrix between the 11 factors (IVs) and the outcome variable
(DV) ‘implemented noise controls’
77
Table A7.3 Descriptive outputs for two scenario items
Knowledge level
Low
(Q10)
Low (Q10)
Medium (Q10)
High (Q10)
Total
23
30
4
57
Medium
(Q10)
42
69
21
132
High
(Q10)
Total
0
1
0
1
65
100
25
190
Tables A7.4 and A7.5 Descriptive outputs of items relating to noise information
sources
Table A7.4 Breakdown of responses to Q18 - ‘How often do you access the following
information on noise? (In order of frequency)
Information source
Internet
Published HSE
guidance
HSE Website
Industry guidance
Machinery suppliers
Insurance companies
Other companies/
competitors
Response category
Often
Sometimes
Rarely
Never
Missing
Often
Sometimes
Rarely
Never
Missing
Often
Sometimes
Rarely
Never
Missing
Often
Sometimes
Rarely
Never
Missing
Often
Sometimes
Rarely
Never
Missing
Often
Sometimes
Rarely
Never
Missing
Often
Sometimes
Rarely
Never
Missing
78
71
62
27
51
4
59
55
44
53
4
48
54
43
67
3
48
48
50
64
5
27
55
68
62
3
19
42
40
110
4
11
32
55
111
6
Your HSE inspector
Direct call to HSE
Direct contact with
your LA
Other
(See below for
Breakdown)
Other (breakdown)
Often
Sometimes
Rarely
Never
Missing
Often
Sometimes
Rarely
Never
Missing
Often
Sometimes
Rarely
Never
Missing
Often
Sometimes
Rarely
Never
Missing
External consultants/experts
Own H&S guidance/policies
External H&S company/agency
Surveillance
External sources (not specified)
Other
7
26
79
100
3
2
26
52
129
6
2
14
47
145
7
5
1
7
26
176
13
3
3
3
1
4
Table A7.5 Breakdown of responses to Q19 - ‘How helpful is the following for
understanding what you need to do to protect your workforce from noise risks? (In
order of frequency)
Information source
Internet
Published HSE
guidance
HSE Website
Industry guidance
Response category
Very helpful
Helpful
Neither helpful nor unhelpful
Unhelpful
Very unhelpful
Very helpful
Helpful
Unhelpful
Very unhelpful
Very helpful
Helpful
Unhelpful
Very unhelpful
Very helpful
Helpful
Unhelpful
Very unhelpful
79
45
90
10
1
2
41
90
10
1
0
58
64
10
1
0
26
79
20
4
3
Machinery suppliers
Your HSE inspector
Insurance companies
Direct call to HSE
Other companies/
competitors
Direct contact with
your LA
Other 45
Other (breakdown)
45
Very helpful
Helpful
Unhelpful
Very unhelpful
Very helpful
Helpful
Unhelpful
Very unhelpful
Very helpful
Helpful
Unhelpful
Very unhelpful
Very helpful
Helpful
Unhelpful
Very unhelpful
Very helpful
Helpful
Unhelpful
Very unhelpful
Very helpful
Helpful
Unhelpful
Very unhelpful
Very helpful
Helpful
Unhelpful
Very unhelpful
External consultants/experts
External H&S company/agency
Surveillance
Other
24
80
25
3
2
26
43
15
1
2
21
33
23
5
2
13
33
10
1
4
10
32
27
4
4
7
26
15
2
1
3
3
0
0
0
-
NB: For the ‘other’ response options specified participants did not rate how helpful these were.
80
2
3
7
9
1
4
5
6
8
13
14
10
11
12
15
Evidence of controls in place
81
Duty holder risk perception level 3 (low)
Duty holder risk perception level 2 (medium)
Duty holder risk perception level 1 (high)
Duty holder designates noise level 4
Observation and supervision of controls by duty holder
Compliance/good hearing protection use
Informal worker involvement
Behavioural Change programme in place
Formal worker involvement
Purchasing policy considers noise
Noise health and safety policy
Noise Action Planning
Noise survey conducted
Measures task and person based exposure
Measures average daily exposures
Job rotation and breaks
Noise dampeners
Segregation of noisy machinery
Machine maintenance programme in place
Engineering and other controls in place
Signage (Noise )
Designated hearing protection zones
General noise training
Audiometric testing takes place
Training on correct fit of hearing protection provided
Hearing Protection Dispensers
Wearing of PPE is mandatory
PPE main noise control
Large Company
Medium Company
Small Company
Case
Table A7.6 Content analysis of implemented controls according to company size
Table A7.7 Company wish lists
Company size
Small
(Wish list focuses
on machinery)
One thing that would help to control noise at work?
“Would like a sound absorption system to dampen the sound of bell-like
sculptures, can't think of anything else.” (1)
“Quieter equipment [and] sound proofing.” (3)
“Basically it’s if there are any other better equipment available these
days?” (7)
“If the machines could be silenced, that would help.” (9)
“Cost of machinery is prohibitive, would welcome proactive advice from
HSE.” (2)
Medium
“Better understanding and guidance on specific issues.” (4)
(Wish list
broadens; still
have requests for
machinery, but
want more
guidance,
training and
changes in
worker
behaviour)
“Guidance on specific issues, communication of new issues, some culture
change would also help, i.e. better acceptance by some of the older
workers, change of culture balanced with losing the experienced workers
... we have to manage the ignorance in order to keep the experience.” (4)
“Formal training like IOSH.” (5)
“Silent grinder.” (8)
“Personal calibrated sound meter.” (6)
“Low velocity air that would still test the components thoroughly would
be helpful because [we] could then reduce noise at source - technical
solution, nothing more HSE could do…” (13)
“…Bottomless pit of money would help manage noise risks, could then
afford air conditioned booths…” (14)
Large
(Wish list is more
high
level/strategic)
"…it's good to be able to lift something out like that (HSE Website video
clips) into an awareness presentation …they're quite hard hitting rather
than sort of hitting somebody with a load of PowerPoint slides, it's
something very simple and gets the message across." (10)
“Top ten approaches to noise reduction from HSE.” (11)
“Ideas about practical solutions.” (11)
“Would like to know what solutions organisations have implemented in
response to prosecutions, improvement notices, etc.” (11)
“Simpler ways of determining if noise is an issue as current advice too
complex.” (12)
“Would welcome [an] evolution in technology.” (15)
82
Table A7.8 Variance of implemented noise controls explained by the three significant
factors
46
Model
R
R²
Organisational values
Company size
Knowledge/awareness
.507¹
.608²
.652³
.257
.370
.425
Adjusted R²
.253
.364
.416
Std. Error of the
Estimate
4.097
3.781
3.621
Table A7.9 Strength of effect on implemented noise controls of each predictor variable
Model
Standardised
Coefficients
Beta
Unstandardised Coefficients
B
Std. Error
Constant
-16.287
2.498
-
Values
Size
Knowledge
3.571
2.258
2.228
.588
.378
.520
.355
.341
.242
Tvalue
6.521
6.070
5.973
4.285
Significance
.000
.000
.000
.000
Table A7.10 Model validation outputs
Model
1
2
3
R
.570¹
.637²
.665³
R²
.325
.405
.442
Adjusted R²
.317
.392
.424
Std. Error of the Estimate
4.065
3.835
3.734
¹ Organisational values
² Company size
³ Knowledge/awareness
Model 3
Constant
1
2
3
Unstandardised
Coefficients
B
-14.965
3.126
3.103
1.958
Std. Error
4.043
.580
.893
.786
Standardised
Coefficients
Beta
.446
.286
.195
t-value
-3.701
5.393
3.474
2.490
Significance
.000
.000
.001
.015
¹ Organisational values
² Company size
³ Knowledge/awareness
Table A7.11 Effect sizes for Mann Whitney-U tests
Following Cohen’s (1988) effect size classification, individual z-scores were converted into rvalues for each of the four factors that showed a significant difference between high and low
46
An estimate of R² in the population, taking into account the sample size and the number of IVs.
83
performers in the Mann Whitney U tests. Resulting r-values were then categorised into
‘insubstantial’ (r<0.1), ‘small’ (r=0.1-0.3), ‘medium’ (r=0.3-0.5) or ‘large’ effect (r>0.5).
Factor
Knowledge and awareness
Health & safety values
Company size
Resources
Z-Score
-2.876
-2.521
-2.500
-3.376
R-Value
-0.20
-0.17
-0.17
-0.23
84
Effect size category
Small
Small
Small
Small
No TU on site
Recognised TU on site
Duty holder multiple roles
Duty holder has H & S qualifications**
Duty holder single role *
Large size company
Medium size company
Small size company
High Performers
Medium Performers
Low Performers
25
27
37
29
21
28
29
26
20
26
29
15
34
27
28
Non-Metallic
Sub Sector
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Metallic
Case
Table A7.12 Demographic profile of companies by performance levels
Small companies
Medium-sized companies
Large companies
Controls in place
* Dutyholder in single role (e.g. designated Health and Safety Manager/Advisor, Safety, Health and Environmental
Manager). ** NEBOSH or equivalent.
85
86
Health and Safety
Executive
Annex report
Nikki Bell and Jennifer Webster
Health and Safety Laboratory
Harpur Hill
Buxton
Derbyshire
SK17 9JN
This literature review represents the first deliverable of a broader research project being conducted by the Health
and Safety Laboratory (HSL). The research was commissioned by the Health and Safety Executive (HSE) to
provide a greater understanding of how to influence dutyholders to exhibit the desired behaviour in managing
noise risks. This project forms part of HSE’s long-term strategy for the prevention of noise-induced ill health at
work.
This report and the work it describes were funded by the Health and Safety Executive (HSE). Its contents,
including any opinions and/or conclusions expressed, are those of the authors alone and do not necessarily
reflect HSE policy.
HSE Books
ii
EXECUTIVE SUMMARY
BACKGROUND
This literature review represents the first deliverable of a broader research project being
conducted by the Health and Safety Laboratory (HSL). The research was commissioned by the
Health and Safety Executive (HSE) to provide a greater understanding of how to influence
dutyholders to exhibit the desired behaviour in managing noise risks. This project forms part of
HSE’s long-term strategy for the prevention of noise-induced ill health at work.
AIMS AND OBJECTIVES
The research aims to provide an analysis of the various factors that may influence employers’
control of noise risks. Another aim is to determine the strength of effect of each factor to
suggest appropriate interventions/messages to influence behaviour change. As such, the present
literature review seeks to identify the salient factors documented within the literature likely to
influence dutyholders’/employers’ decision-making and behaviour. The review includes
research looking at varying levels of management in recognition of the fact that the
dutyholder/employer might delegate health and safety responsibilities to his/her managers. The
outcome of this review will be a clear understanding about what factors should be measured in
future research.
MAIN FINDINGS
Based on the literature it would appear that the following 13 factors are likely to influence
managers’ behaviour regarding the control of noise risks, independent of organisation size:
knowledge, awareness and understanding, risk perception, corporate reputation, compliance
with legislation, experience of a serious accident and/or enforcement, attitudes, values and
beliefs, control, self-efficacy, safety culture, competence, environment and certain demographic
characteristics (e.g. gender, role). Four factors were reported to have greater influence on
managers of small and medium sized enterprises (SMEs) than those in larger organisations:
economic/financial, capability/cost of making improvements, resources, information and
communication. Future research that targets the manufacturing sector should focus on these
factors since the sector mostly consists of SMEs. Conversely, three factors, i.e., employee
attitudes/motivation, customer pressure and personality, were shown to have little influence on
managers’ health and safety behaviour.
RECOMMENDATIONS
The 17 factors shown to influence managers’ health and safety behaviour (excluding employee
attitudes/motivation, customer pressure and personality) were recommended as important to
measure in the research. This encompasses individual level, social and organisational level
factors as well as allowing for the influence of external/wider societal influences. None of these
should be overlooked if a thorough understanding of influences on management behaviour is to
follow. It should be borne in mind, however, that the conclusions drawn from this review are
based largely on findings from previous studies looking at general health and safety
management, rather than noise specifically. New factors may emerge from noise reduction
management research and the extent of their influence on noise reduction behaviour will be
clarified.
iii
iv
CONTENTS 1 INTRODUCTION......................................................................................... 1
1.1
Background ............................................................................................. 1
1.2
Aims and Objectives ................................................................................ 4
1.3
About this Report ..................................................................................... 4
2 METHODOLOGY........................................................................................ 5
2.1
Search Strategy....................................................................................... 5
2.2
Selection of Papers ................................................................................. 6
2.3
Procedure ................................................................................................ 7
3 RESULTS ................................................................................................. 10
3.1
Business Drivers.................................................................................... 12
3.2
Legal Drivers ......................................................................................... 13
3.3
Organisational/Cultural Drivers.............................................................. 14
3.4
External Drivers ..................................................................................... 16
3.5
Personal Drivers .................................................................................... 17
4 CONCLUSIONS........................................................................................ 19
4.1
Implications of Findings for this Research ............................................. 19
4.2
Overall Summary ................................................................................... 22
4.3
Next Steps ............................................................................................. 23
5
GLOSSARY .............................................................................................. 24
6
REFERENCES.......................................................................................... 28
7 APPENDICES........................................................................................... 33
7.1
Appendix 1: Data Extraction Table ....................................................... 33
7.2
Appendix 2: Table of Excluded Articles ................................................ 60
7.3
Appendix 3: Factor Groupings .............................................................. 63
7.4
Appendix 4: Quality Ratings ................................................................. 69
v
vi
1
1.1
INTRODUCTION BACKGROUND
This research was commissioned by the Health and Safety Executive (HSE) as part of a longterm strategy for the prevention of noise-induced ill health at work, the desirable outcome of
which is minimisation or, ideally, elimination of ill-health and injury due to occupational noise
exposure. Discussions at a Noise and Vibration Planning Workshop in July 2007 identified the
need for research to identify gaps in HSE’s ability to influence employers and/or to develop its
ability to apply specific enabling factors.
1.1.1
Why is noise an occupational health problem?
Noise at work is known to be associated with a number of ill health outcomes including nonauditory effects, such as accidents, cardiovascular morbidity and work-related stress (e.g.
Welch, 1979), and auditory effects, namely, tinnitus 1 and temporary or permanent hearing loss.
Permanent hearing loss can be caused immediately by sudden, extremely loud, explosive noises
or prolonged exposure to excessive noise levels (ACOEM, 2003). But hearing loss is usually
gradual due to prolonged exposure to noise. It may only be when damage caused by noise over
years combines with hearing loss due to aging that people realise how deaf they have become.
The tendency for noise-induced hearing loss to remain generally unnoticed until later in life 2
might partly explain why the immediate need to control noise at work is less apparent to
dutyholders. Recent statistics show that 1.1 million employees are exposed the levels of noise
above the upper action value set in regulation (a daily personal noise exposure of 85 dB), and
are relying on Personal Protective Equipment (PPE) for protection (HSE SIM 03/2007/08).
This suggests that dutyholders need to do more to ensure that the risks associated with noise
exposure are controlled in order to prevent employees from developing health conditions in the
future. Furthermore, corrective action to reduce noise exposure can reduce the rate of
progression of the condition in individuals and help prevent the conditions of those already
suffering from worsening.
1.1.2
Why does this research focus on dutyholders / employers?
Whilst the attitudes and behaviours 3 of suppliers and operatives/employees have a role to play
in achieving the overall outcome of minimisation or elimination of noise-induced ill health, it is
not within the scope of this report to explore these groups in any depth. Rather, the research
aims to gain a clearer understanding of the various factors that influence employers’ control of
noise risks. The rationale for focusing on employers rather than employees is provided in Box
1.
1
2
3
See Glossary.
See Noise at Work. The RoSPA Occupational Safety & Health Journal, April 2008, 15-22.
See Glossary. 1
• A substantial amount of literature already exists on employee judgements regarding
safety and risk issues. Conversely, ‘there is a lack of studies measuring managers’
subjective evaluations’ (Holmes et al, 1997).
• Studying managers is important as their attitude and behaviour may influence
employee attitudes as well as their own. It is widely accepted that directors who set a
good example in their attitudes and actions towards health and safety promote similar
attitudes and behaviour in their workforce (Shearn and Miller, 2005).
• There is an apparent widespread reliance amongst workers on managers being
responsible for and taking the initiative to protect their hearing (Leinster et al, 1994). As
such, ‘resources should be directed towards convincing management rather than workers
of the need to give more attention to hearing conservation’.
• A number of research studies (see Kelloway et al, 2006) have shown that when leaders
actively promote safety, organisations have better safety records and more positive safety
outcomes. ‘Leadership is crucial to safety results (as it) creates and maintains the
culture that determines what will and will not work’ (Petersen, 2004).
• DeJoy et al’s (2000) research indicated the need for making safety equipment readily
available and reducing job-related barriers to compliance, both of which inevitably
fall to management.
• Organisational regulation of occupational noise protection has been shown to be more
influential on workers’ protective behaviour compared with their knowledge about the
protection (Cheung, 2004).
Box 1: Rationale for focusing the research on employer behaviour.
It is clear that a considerable amount of research points to the importance of effective and active
leadership 4 to improve health and safety of which noise forms part. As depicted in Figure 1,
leadership occurs at varying levels of organisations starting at the top with the
dutyholder/employer and ending at the supervisors on the shop floor. Given that health and
safety decisions are ultimately the dutyholder’s/employer’s responsibility, senior-level
managers are the focus of this research. It is recognised, however, that within some
organisations, particularly larger companies, the authority for making health and safety
decisions may be delegated to lower-level management. ‘A leader can be not only an executive,
but also a manager, supervisor or other person’ (Petersen, 2004). It is therefore important to
examine the broader literature on leadership and not only that on director leadership.
4
See Glossary.
2
Directors/Owners/
Senior management
Middle management
Supervisors
Operatives
Figure 1: Typical organisational levels.
1.1.3
What are dutyholders’/employers’ noise responsibilities?
How noise risks are managed can have a significant impact upon how associated ill health is
perceived and are crucial to the desired outcome of minimisation/elimination of ill health due to
occupational noise exposure. Risks from noise can in many cases be tackled by the adoption by
the dutyholder, of established control measures and strategies (HSE SIM 03/2007/08). In the
context of the Health and Safety at Work Act (1974), it is to be expected that the actions or
behaviour necessary to achieve the desired outcome will be undertaken by, or made possible
through the action of the employer. The following four actions are considered necessary in
order for the outcome to be achieved:
1. Application of technical/organisational noise control measures;
2. Use of low noise/low exposure tools/machines;
3. Full and proper use of PPE for residual/short-term risk; and
4. Health surveillance for those at risk, and use of the results.
The Control of Noise at Work Regulations (2005) replaced the Noise at Work Regulations
(1989) and emphasise the need to identify measures to eliminate or reduce risks from exposure
to noise at work (actions 1 and 2 above) rather than simply relying on hearing protection (action
3 above), although this may be needed in the short-term. Employers are required to ensure that
exposures to, and risks from, noise are as low as reasonable practicable (ALARP) (Regulation
6) and to take specific action at certain action values depending on employee’s average level of
exposure to noise over a working day or week and the maximum noise to which employees are
exposed to in a working day.
HSE Noise at Work guidance (2005) outlines that employers have duties under the Regulations
to:

Assess
the risks to employees from noise at work to identify where there may be a risk
and who is likely to be affected, provide a reliable estimate of noise exposures and
identify, in an action plan, what needs to be done to comply with the law.
3

Take
action to reduce the noise exposure that produces those risks by looking for
alternative equipment, process and/or working methods that will reduce employees’
exposure to noise or make work quieter (ALARP).

Provide

Make

Provide

Carry
employees with suitable hearing protection if the noise exposure cannot be
reduced by other methods (available on request at 80 dB; ensuring it is worn at 85dB)
and ensuring that protectors are worn properly, at all times that they should be worn.
sure the legal limits of noise exposure (87 dB daily or weekly exposure or peak
sound pressure of 140 dB taking account of hearing protection) are not exceeded by
keeping systems and action plans under constant monitoring and review.
employees with information, instruction and training so that they understand
the risks that they are exposed to, how they can protect themselves, what their employer
is doing to protect them, and how they can assist with this.
out health surveillance where there is a risk to health to monitor employees’
hearing and provide feedback on the effectiveness of noise controls implemented.
Current understanding suggests that, in general employers do not always engage in good
practice for noise control, despite the availability of relevant information and advice. Anecdotal
evidence implies a widely held belief that the problem of noise is ‘solved’ with issuing hearing
protection, and that engineering noise control is difficult and/or expensive. The research will
enable HSE to gain a better understanding of its ability to influence employers by providing
scientific evidence about the key influences for good practice in the control of noise risks for
dutyholders and managers alike to engage with.
1.2
AIMS AND OBJECTIVES
The research aims to provide an analysis of the various factors that may influence employers’ in
controlling noise risks, and to categorise and weight the factors according to their potential
effect. As such, the present literature review seeks to identify the salient factors documented
within the literature likely to influence employers’/managers’ decision-making and behaviour.
Factors identified in the review will be categorised according to an appropriate, well-established
psychological model, namely the PRECEDE model 5 (Green et al, 1980; Green & Kreuter,
1991) and weighted based on researchers’ judgement regarding the strength of the available
evidence for each factor. The outcome will be a clear understanding of what factors need to be
measured in the research.
1.3
ABOUT THIS REPORT
This report represents the first deliverable from the initial fact finding stage of this two-year
project. The sections that follow give an explanation of the methodology adopted for this
review, a summary of the key factors that emerged from reviewing available and relevant
literature, and recommendations for areas to measure in the research. This report does not
contain details of the broader research project.
5
See Glossary.
4
2
2.1
METHODOLOGY
SEARCH STRATEGY
HSL researchers carried out an initial literature search in June 2008 as part of the development
of the research proposal. This involved searches of the following: HSE/HSL Intranet (to assess
unpublished research), Internet (Google), Science Direct and PsychInfo. Search terms included:
• Management of noise risks.
• Noise control practices/behaviours.
• Director leadership (health and safety) behaviour.
• Employers/managers/dutyholders (noise/health and safety/risk control) compliance
behaviour 6 .
• Employers/managers/dutyholders (noise/health and safety) knowledge/attitudes/
behaviours/risk perceptions/judgments.
• Factors influencing employers/managers/dutyholders (noise/health and safety/compliance) behaviours/decision-making/noise management. A selection of relevant papers was used to inform the design of the research. At this stage,
however, a thorough search and review of the available literature had not been conducted. Part
of the research proposal identified the need for an initial ‘fact finding’ stage, which included a
comprehensive review of the literature to ensure that all relevant factors, likely to influence
dutyholders’/managers’ behaviour regarding the uptake of noise controls, were included.
The original papers used for proposal development were also included in this review. The
references cited in these papers were studied to ensure that all relevant literature was collated
and examined. Researchers also repeated the search on the HSE/HSL intranet to access any
relevant, new papers. Furthermore, the HSE Project Officer conducted a search on HERALD 7
for previous HSE/HSL reports that may be of relevance to the research. Out of the 17 search
results from HERALD, four papers were obtained. Thirteen papers were excluded because they
did not examine managers’/dutyholders’ health and safety behaviour and/or decision-making.
HSE’s Information Services conducted a literature search in November 2008 across a wide
range of databases. The same search terms were utilised as above with the addition of the
following:
• Barriers to controlling noise risks.
• Health and safety leadership behaviours / style.
• Social / organisational influences on employers’/managers’ health and safety
behaviours.
• SMEs versus large organisations.
6
7
See Glossary.
HERALD is currently HSE’s main research database.
5
•
High versus low performing organisations.
The HSE search returned a large number of abstracts (n=547 8 ) from various search engines as
detailed in Table 1.
Table 1: HSE database search results.
Database
Number of Abstracts
HSELINE, RILOSH, OSHLINE, CISDOC and NIOSHTIC
Healsafe
Ebsco Business Corporate
Medline, Embase, Management and Marketing Abstracts,
Management Abstracts, Psyclit and ABI Inform.
Web of Science
Management and Marketing Abstracts
286
91
43
68
2.2
51
8
SELECTION OF PAPERS
Relevant articles to include in the review were selected based on specific inclusion criteria
detailed in Table 2. Papers were included if they were published within the last 10 years to
ensure that the review is up-to-date, with the exception of any behavioural research focusing on
noise due to the apparent shortage of such highly relevant research. Articles on leadership
behaviours were only included if published within the last 5 years due to the sheer volume of
research that has been carried out in this area to date. Reviews and meta-analyses were only
included if conducted within the last 3 years as the nature of these articles means that earlier
reviews are cited, the only exception being any behavioural research on noise published over 10
years ago because of the scarcity of research in this area. Although UK-based articles were
preferred, the realisation that UK-based research on factors influencing management behaviour
concerning health and safety issues might be small in number, led to the inclusion of
international papers with appropriate caveats (i.e., any potential cultural influences meaning that
replication of the research in the UK might not yield the same findings).
8
Final number after the removal of duplicates.
6
Table 2: Inclusion criteria.
Include articles if they are/cover:
Exceptions apply if:
• Occupational-based research and practice.
• Published within the last 10 years; 5 years
if on leadership behaviour.
• Reviews/meta-analyses in the last 3 years.
• UK-based research and practice.
• Influences on (managers’/dutyholders’)
(health & safety compliance) behaviour(s).
• Director leadership and health and safety.
• Leaders’/dutyholders’/employers’ health
and safety decision-making.
• Management/control of noise risks.
• Health and safety management in SMEs
and high/low performing organisations.
2.3
• Behavioural research on noise published
over 10 years ago, due to the shortage of
highly relevant research on noise.
• Relevant UK research is sparse, in which
case include international papers with
caveats.
PROCEDURE
A systematic approach was followed during this review in order to minimise researcher bias
(e.g., in the selection of articles) and improve the reliability of the outcome of the review.
Identifying relevant articles: Two reviewers independently assessed article titles produced by
computerised searches to gauge their potential relevance. At this stage, titles and abstracts were
scanned and those demonstrating potential to inform the research were judged as relevant (i.e.,
those that were closely aligned with the search terms contained in section 2.1). Of the 547
abstracts that the HSE search returned (as detailed in Table 1), 65 full articles were retrieved.
The two reviewers met to ensure decision unanimity. This combined with the 27 articles
retrieved by the researchers themselves through searching the HSE/HSL Reports database
combined with the articles retrieved during the literature search in June 2008 for proposal
development (see section 2.1), meant that 92 articles were selected. Eight of the 92 were
retained as useful background articles on noise and its potential effects.
Application of inclusion criteria: The two reviewers independently examined half of the
abstracts of the full articles retrieved (scanning the remainder of each article) to determine
whether they would be included in the review, based on the inclusion criteria specified in Table
2. The top five reasons for excluding articles were that the research (1) concerned employee
rather than employer behaviour, (2) looked at the actual behaviour that managers display rather
than the psychological precursors to that behaviour, (3) concerned noise prevalence, physiology,
measurements and effects, (4) looked at intervention effectiveness and (5) represented outdated
reviews/meta-analysis 9 /leadership papers (see Appendix 2 for the list of excluded articles and
reasons for their exclusion). Researchers crosschecked 50% of the decisions made by their
fellow researcher to ensure consistency in the application of the inclusion criteria. Researchers
discussed any articles for which they disagreed (n=3) with the decision to include or exclude
and reached a joint final decision. After reviewing the 92 full articles, 38 articles were included
to inform the results of the literature review, as they proved most pertinent to the research.
9
See Glossary.
7
Data extraction: Data was extracted from the 38 articles 10 included in the review. Researchers
independently extracted data from half of the included papers and crosschecked 20% (n=4) of
each other’s data extraction to promote consistency and reliability. Each researcher entered data
into a data extraction sheet (see Appendix 1 for the full Data Extraction Table), which covered
the following areas:
1. Source/Reference.
2. Summary of the research.
3. Potential influences on management behaviour.
4. Noise relevance rating.
5. Implications for research tools and any caveats.
To determine relevance of the literature to this research (point four above), each article was
judged against the Noise Relevance Weighting System shown in Table 3.
Table 3: Noise Relevance Weighting System.
Highly Relevant
(N)
Relevant (H)
Generic (G)
Noise Relevance Weighting System
Evidence includes research specific to noise.
Evidence includes research from other physical health hazards with
latency between exposure and harm.
Evidence does not include research specific to noise or related
physical hazards but is relevant to occupational health and safety
hazards generally.
One researcher examined the potential influences on management behaviour that emerged as
relevant for this research and grouped these into distinct factors. The factors were further
grouped according to their overarching factor (see Appendix 3 for factor groupings). The
researcher also assessed the available evidence for each factor in terms of its strength of
influence on the behaviour of managers. Additionally, the researcher assessed the quality of the
available evidence relating to each factor using the Quality Rating System shown in Table 4
(see Appendix 4 for the actual quality ratings). Finally, the researcher categorised the emerging
factors according to the PRECEDE model to determine their potential causal role. All factor
groupings, quality ratings and data categorisation were double checked by the second
researcher.
10
Please Note: Two articles by Holmes are counted as one article in the Data Extraction Table in Appendix 2 (see entry number
22) because they refer to the same study. As such, 38 articles were reviewed in the research although 37 are listed in the Data
Extraction Table.
8
Table 4: Quality Rating System.
Quality Weighting System*
Strong (S)***
Moderate (M)**
Weak (W)*
Generally consistent findings provided by (systematic reviews/metaanalysis of) multiple scientific studies or multiple longitudinal studies.
Generally consistent findings provided by (reviews of) fewer and/or
methodologically weaker scientific studies or fewer longitudinal
studies.
Supporting evidence is inconsistent.
Or supporting evidence is only based very few cross-sectional studies.
9
3
RESULTS Twenty factors emerged from the review as having the potential to influence the behaviour of
managers with regards to controlling noise risks (i.e. going beyond reliance on hearing
protection to implementing higher-level technical/organisational controls). As such, a wide
range of psychological (e.g. managers’ level of self-efficacy to control noise risks, technical
knowledge and understanding of noise risks), social (e.g. safety culture, general attitudes
towards and beliefs about noise exposure), organisational (e.g. attributed responsibility for noise
control, health surveillance) and environmental factors (e.g. the changing nature of work,
pressure from suppliers and contractors) were found to influence health and safety management.
These factors have been categorised according to the PRECEDE model as shown in Figure 2.
The quality of the available evidence for each factor is also indicated in brackets in line with the
Quality Rating System shown in Table 4 (see Section 2.3 of this report). Justification for
quality ratings can be found in Appendix 4.
PRECEDE (Green & Kreuter, 1991; Green, Kreuter, Deeds & Partridge, 1980) is an appropriate
theoretical framework to adopt for this research as it is capable of accommodating a disparate
range of individual and organisational factors. Unlike traditional models of behaviour change, it
goes beyond individual-level variables to consider important social-environmental factors
of/and the context within which behaviour occurs (Dejoy, 1996; Sheehy & Chapman, 1987;
Smith & Beringer, 1987). According to the model, three sets of diagnostic factors drive the
development of intervention strategies (as shown in Figure 2). Predisposing factors are the
characteristics of the individual that facilitate or hinder the uptake of noise controls; they are
conceptualised as providing the motivation to act. Enabling factors refer to objective aspects of
the environment or system that block or promote the uptake of noise controls. Most barriers and
costs associated with the uptake of noise controls would be classified as enabling factors as
these represent aspects of the environment/system (e.g. safety culture) that block the uptake of
noise controls. Reinforcing factors involve any reward or punishment that follows or is
anticipated as a consequence of behaviour. This model does not claim to have watertight
reliability and validity for all possible occupational contexts. Rather, it provides a scientific
framework for selecting important contributors to dutyholders decisions on noise control.
10
Figure 2: Categorisation of factors according to the PRECEDE model. In order of ‘causation’:
1. Predisposers create the motivation to act 2. Appropriate resources enable action 3. Behaviour
is reinforced, resulting in 4. Repetition of Behaviour. 5. Reinforcement or punishment of the
behaviour either strengthens or weakens motivation, as do 6. Enabling factors (Dejoy et al,
2000; Green et al, 1980).
The following section provides a summary of the literature relating to each factor. The focus
concerns the overall relevance and quality of the evidence as well as potential strength of
influence on managers’ noise control behaviour guided by previous research rather than
providing details of specific research studies 11 . This will enable future research to gain an
understanding of all the important factors (knowledge, competencies, attitudes and beliefs, etc.)
that prevent managers’ from going beyond reliance on hearing protection to implementing
higher-level technical/organisational controls within their organisation. This section has been
structured in line with the five overarching factors that emerged when grouping the twenty
factors (see Appendix 3). These were: (1) Business, (2) Legal, (3) Cultural/Organisational, (4)
External and (5) Personal. Table 5 summarises the factors that constitute these five overarching
factors. Further breakdown of these contributing factors can be found in Appendix 3. It should
11
Full details of each contributing study can be found in Appendix 2.
11
be recognised, however, that it is very difficult to separate out the effects of each factor. In
some instances factors overlap (shown in italics in Table 5), for example, values and beliefs
may result from both personal and cultural/organisational factors. Where possible, factors have
been grouped under one (the most appropriate) overarching factor.
Overarching Factor (n=5)
(1) Business
(2) Legal
(3) Cultural/Organisational
(4) External
(5) Personal
Unique Contributing Factors (n=20)

Economic / financial
Corporate reputation
Customer Pressure
Capability / cost of making engineering improvements
Experience of a serious accident and/or enforcement
Compliance with legislation
Values and beliefs
Perceived / actual control
Culture
Health and Safety attitudes
Resources
Demographics 12
Employee attitudes and motivation
Environmental
Knowledge, awareness and understanding
Risk perception
Competence
Self-efficacy / confidence
Personality
Demographics 13
Values and beliefs
Table 5: Five overarching factors and contributing factors.
3.1
BUSINESS DRIVERS
Of the five contributing factors, economic/financial and corporate reputation represent
reinforcing factors, i.e. the anticipated consequence of managing noise risks (see Figure 2).
Experience of a serious accident and/or enforcement, customer pressure and capability/cost of
making engineering improvements represent enabling factors that either encourage or
discourage the desired behaviour (i.e. managers taking the necessary steps to control noise
risks).
Of the 20 articles reviewed that investigated at least one of these five factors, there was general
consensus within the literature that three factors, namely corporate reputation, capability/cost of
making improvements and experience of a serious accident and/or enforcement had a significant
affect on management health and safety behaviour. In all cases the quality of the evidence was
12
13
I.e. role/position, industry sector, type of operation and accident/incident/ill health rates.
E.g. gender.
12
moderate (see Appendix 4 for all quality ratings). With regards to corporate reputation, research
suggests that this may vary by industry, being most influential for managers within high hazard
industries (e.g. Leinster et al, 1994; Smallman & John, 2001). The latter two factors have been
implicated more in terms of moderating variables. For example, experience of a serious
accident has been implicated as moderating the impact of economic/financial drivers on
management decision-making (e.g. Barrett et al, 2005). Capability/cost of making engineering
improvements seems to moderate managers’ motivation to manage health and safety (e.g.,
Foster, 1996; Holmes et al, 1999; Wright & Marsden, 2002). A number of studies have shown
that the perceived cost of making health and safety improvements rather than perceived
investment is a significant demotivating factor for management, particularly for SMEs (e.g.,
Holmes et al, 1999; Timothy, 2006; Wright, 1998). It should be noted, however, that managers’
perceptions of the cost might not reflect the true reality (e.g. Leinster et al, 1994).
In relation to economic/financial drivers, the evidence was less clear-cut. Despite the moderate
quality of the underlying evidence, not all research reviewed considered this factor to be a key
influence on health and safety management (e.g. Wright & Marsden, 2002). Financial reasons
may not be a prime motivator for well resourced companies in which cost savings can be
achieved in areas other than health and safety (Hopkins, 1995). Studies targeting SMEs tended
to report economic/financial outcomes as having a significant influence on health and safety
management (e.g. Addison & Burgess, 2002; Vickers et al, 2003). Research conducted in the
USA has reported this as a top driver for management. Differences in insurance and
compensation schemes between the USA and UK, however, may mean that economic/financial
outcomes have greater influence on health and safety management in the USA compared with
the UK (e.g. Wright, 1999). One UK-based study, however, reported that financial incentives
had become more influential in recent years (Wright et al, 2005). Only one paper (Wright &
Marsden, 2002) commented on customer pressure and concluded that this was not a significant
motivator for management. As such, the quality of the evidence was considered weak.
Of the 20 papers reviewed that assessed business drivers, only two specifically addressed noise
(i.e., Leinster, Baum, Tong, & Whitehead, 1994 and Foster, 1996), two concerned other
physical health hazards with latency between exposure and harm and the majority (n=16) were
relevant to occupational health and safety hazards generally. Findings from the two papers that
addressed noise both reported cost factors to be a key driver influencing managers’ decisions
about noise controls. The study by Leinster et al (1994) also reported PR concerns (e.g. bad
publicity) as a key driver and in the study by Foster (1996) ease and practicability of
implementing noise controls emerged as a factor that encouraged implementation. (See
Appendix 1 for further details).
3.2
LEGAL DRIVERS
Legal drivers simply refer to how motivated managers are to comply with the current noise
legislation/guidance and covers fear of prosecution. This represents an enabling factor that
seems to promote health and safety management (see Figure 2). There was a strong consensus
in the eight papers reviewed that legislation has a significant motivating effect on health and
safety management at a senior-level (e.g. Hopkins, 1995; O’Dea & Flin, 2003; Shearn & Miller,
2005; Wright & Marsden, 2002; Wright et al, 2006). Although motivation to comply has been
reported as a factor influencing the management of organisations of all sizes, Wright (1999)
pointed out that motivation may be low as detection and prosecution levels are low.
Additionally, the latency period between ill-health triggers and the onset of ill-health conditions
may not motivate managers to act on the health aspects of regulations.
13
The overall quality of the available evidence was considered strong, yet none of the articles
specifically addressed noise or other physical health hazards. All eight papers concerned
generic occupational health and safety hazards.
3.3
ORGANISATIONAL/CULTURAL DRIVERS
Of the eight contributing factors, three of these, namely, health and safety attitudes, values and
beliefs and demographic characteristics, were classified as predisposing factors (see Figure 2).
Although representing characteristics of the individual that facilitate or hinder health and safety
management, these might be influenced by an organisation’s culture. For this reason all three
factors were categorised as both personal and organisational/cultural drivers. Resources, control
and experience of a serious accident and/or enforcement represent three enabling factors. The
final two factors, safety climate/culture and employee attitudes/motivation, represent reinforcing
factors.
Of the 30 papers reviewed that discussed at least one of these eight factors, there was general
agreement that six of these had a significant influence on managers’ health and safety
behaviour. These were (1) experience of a serious accident and/or enforcement, (2) resources,
(3) values and beliefs, (4) attitudes, (5) control and (6) safety climate/culture. For the latter four
factors, the underlying evidence was strong and for the first two (resources and experience of a
serious accident and/or enforcement) the underlying evidence was moderate. Section 3.1
highlights the potential moderating effect that the experience of a serious accident and/or
enforcement has on the relationship between economic/financial drivers and decision-making.
With regards to resources, the vast majority of papers reported this as a significant barrier to
managers’ carrying out the necessary steps to control workplace hazards (Gillen et al, 2004;
Holmes et al, 1999; Maierhofer et al, 2000; Petersen, 2004; Rundmo & Hale, 2003). This
seemed to have greater influence on lower-level management, possibly because it falls to middle
managers and/or supervisors to deal with health and safety issues (e.g. Bentley & Haslam, 2001;
O’Dea & Flin, 2003). Furthermore, resources appear to influence the behaviour of SME
managers more than those in larger organisations, likely due to the limited pool of resource that
small companies typically have (e.g. Vickers et al, 2003).
In relation to 1) values and beliefs and 2) health and safety attitudes, a recurrent theme in the
literature was that these have a significant impact on managers’ health and safety behaviour.
The underlying evidence was strong in both cases. More specifically, in line with the Theory of
Reasoned Action 14 (TRA: Fishbein & Ajzen, 1975) and Theory of Planned Behaviour 15 (TPB:
Ajzen & Fishbein, 1980; Ajzen, 1988), attitudes have been shown to influence behavioural
intentions 16 , which in turn affect behaviour (see Webb & Sheeran, 2006). A key belief found to
influence the behaviour of managers in a number of studies was ‘compassion’ and a ‘general
concern’ for the well being of their workforce, particularly in research involving SMEs where
managers are likely to know staff on a personal level (e.g. Hopkins, 1995; Krause, 2004;
Podgorski, 2006; Wright, 1998; Wright et al, 2005; Wright & Marsden, 2002). The attitude that
productivity takes precedence over safety was reported in studies of organisations of all sizes
(e.g. Barrett et al, 2005; Gillen et al, 2004; Leinster et al, 1994; Shearn & Miller, 2005).
Although management style may be partly influenced by values and beliefs, some evidence
suggests that a positive culture can be created regardless of managerial style (e.g. Petersen,
2004). Senior management commitment was found to have a significant effect on behavioural
intentions in a number of studies (e.g. Gillen et al, 2004; Hopkins, 1995; O’Dea & Flin, 2003;
14
15
16
See Glossary.
See Glossary.
See Glossary.
14
Podgorski, 2006). One study found commitment to have the greatest influence over and above
other attitudes held by management such as fatalism 17 and safety priority (see Rundmo & Hale,
2003). A pertinent issue for noise, however, might be that it is not taken seriously by
management and is regarded as inevitable. As Leinster et al (1994) stated, ‘noise at work is
widely taken for granted, adapted to and considered inevitable. The fact that noise induced
hearing loss is not life threatening, has a delayed onset and does not lead to absence from work
means that noise is not viewed seriously by both management and workforce’ (pp.656-66). As
such, complacency might emerge as an influential attitude in this research affecting managers’
motivation to go beyond reliance on hearing protection to implementing higher-level
technical/organisational controls. Acceptance of responsibility for health and safety appears to
be more influential for driving lower-level management behaviour (see O’Dea & Flin, 2003),
perhaps because such responsibility is implicit in the role of senior managers. Kelloway et al.
(2006) noted the possibility that in some cases leaders simply ignore safety related concerns
(known as ‘passive leadership’ 18 ) and considered these types of leaders to be more prevalent
than those who blatantly disregard the safety of their employees. One study also reported that
affective attitudes (e.g. regret), as well as cognitive attitudes, play a role in decision-making (see
Sandberg & Conner, 2008). Such emotional outcomes might be closely aligned with
experiences (e.g. regret from experiencing a serious accident).
With regards to control, perceived levels of authority over the workforce appeared to be more
influential at lower-level management levels rather than senior management level (see O’Dea &
Flin, 2003). In line with the TPB and Model of Interpersonal Behaviour 19 (MIB: Triandis,
1977), the literature purports control as a significant moderator of the intention-behaviour
relationship (see Webb and Sheeran, 2006). As such, the supporting evidence was considered to
be strong. The same applies to safety climate/culture, also shown to have a significant influence
on health and safety management in a number of studies (e.g. Gardner et al, 1999; Kelloway et
al, 2006; Thompson et al, 1998). The TRA, TPB and Prototype Willingness Model 20 (PWM:
Gibbons et al, 1998; Gibbons et al, 2003) all suggest that social pressure from significant others
and collective attitudes and behaviours (subjective norms) are powerful influences on a person’s
behaviour. A consistent message within the literature was that organisations with a positive
safety climate/culture are those likely to implement health and safety controls (e.g. Colemont &
Van den Broucke, 2006; Hofman & Morgeson, 1999; Petersen, 2004). Research has
commented on the inter-relationship between culture and leadership as leadership at the top can
have an influence on safety culture and similarly, the culture of the organization can influence
leadership behaviour and style (see Petersen, 2004). Safety culture 21 and the attitudes and
behaviours of senior managers may therefore influence lower-level management.
For the remaining two out of the eight factors that contribute to organisational/cultural drivers
(i.e. employee attitudes and motivation and demographic characteristics), the evidence was less
consistent. There was moderate evidence to suggest that employee attitudes and general level of
motivation influence health and safety management (e.g. Bentley & Haslam, 2001; Petersen,
2004) and noise management specifically (e.g. Leinster et al, 1994). Yukl’s (1989b) Conceptual
Framework of Leadership Effectiveness 22 highlights subordinate effort and cooperation/team
work as key intervening variables that influence leadership behaviour. One study claimed,
however, that managers’ own attitudes, knowledge and economic/financial reasons were more
important than worker attitudes (see Podgorski, 2006). Nevertheless, this research involved
larger organisations with varying levels of management. Employee attitudes may have greater
influence on the behaviour of SME managers (e.g. type of hearing protection selected, whether
17
See Glossary.
See Glossary.
See Glossary.
20
See Glossary.
21
See Glossary.
22
See Glossary.
18
19
15
technical/organisational controls are implemented or not) more likely to experience regular
direct contact with workers (e.g. Leinster et al, 1994). With regards to the demographic
characteristics of managers, at the organisational level this concerns actual position/role, role
clarity, type of industry and operation and frequency rates of accidents, incidents and ill health.
There is some evidence to suggest that these demographic features influence director behaviour
(see Shearn and Miller, 2005), but overall the evidence was weak due to few studies reporting
this as a significant factor. Furthermore, the strength of influence remains unclear.
Of the 30 papers reviewed that assessed organisational/cultural drivers, only three specifically
addressed noise (i.e., Leinster, Baum, Tong, & Whitehead, 1994; Foster, 1996; and Hughson,
Mulholland, & Cowie, 2002), three concerned other physical health hazards with latency
between exposure and harm and the majority (n=24) were relevant to occupational health and
safety hazards generally. Findings from the three papers that specifically addressed noise
emphasised that senior management commitment is vital to drive through the noise policy plan
by, for example, allocating sufficient resource to noise control and demonstrating to the
workforce that noise is not taken for granted. (See Appendix 1 for further details).
3.4
EXTERNAL DRIVERS
Two factors summarise external influences on organisations, namely, information and
communications and environmental influences, both of which represent enabling factors that
potentially encourage or discourage desired behaviour (see Figure 2).
There was consensus within the literature reviewed that information and communications had a
significant affect on management behaviour. The quality of the evidence was moderate. A
number of studies have looked at the influence of different information sources (including HSE
guidance and advice/guidance from HSE Inspectors and intermediaries) on SME managers (e.g.
Ferguson et al, 2006; Wright, 1998). For example, Wright (1998) stated that “advice from
professional health and safety advisors can overcome ingrained management attitudes that
certain hazards are part of the job.” Ponting (2001) further pointed out that “small businesses
often lack in-house health and safety knowledge and are thus highly dependent on suppliers and
external advisors. Such information may in some cases be misleading.” These inter-personal
(less scientific) sources of information are sometimes considered by SMEs to be most
trustworthy (see Ferguson et al, 2006). There was also evidence to suggest that managers of
small companies perceive HSE as being unaware of the difficulties they face (see Gervais,
2006). It seems that SME managers are more likely to seek non-HSE guidance, likely to have a
significant influence on the level of noise control implemented (e.g. providing hearing
protection versus implementation of technical/organisational controls).
For environmental influences the evidence was considered weak due to the limited number of
studies examining this as a factor and uncertainty over the extent of its influence. Only two
papers discussed potential environmental influences, namely, the changing nature of work and
pressure from suppliers and contractors. The latter were considered key drivers for managers’
relying on hearing protection than other measures to reduce noise exposure in a study conducted
within the construction sector (see Hughson et al, 2002). A study carried out by Podgorski
(2006), however, reported sudden deterioration of working conditions as having the least impact
on implementation of occupational health management systems in Australia compared with
their level of commitment and expectations for reducing accidents/incidents, moral beliefs,
knowledge and economic benefits.
Of the eight papers reviewed that assessed external drivers, only one specifically addressed
noise (i.e. Hughson, Mulholland, & Cowie, 2002; see Appendix 1 for further detail), one
16
concerned other physical health hazards with latency between exposure and harm and most
(n=6) were relevant to occupational health and safety hazards generally.
3.5
PERSONAL DRIVERS
Of the eight contributing factors, seven of these, namely, knowledge, awareness and
understanding, risk perception, self-efficacy, personality, values and beliefs, attitudes and
demographic characteristics, represent predisposing factors (see Figure 2). The latter three
factors, however, were also considered to be organisational/cultural drivers for reasons outlined
in Section 3.3. Competence was categorised as an enabling factor as it goes beyond having the
necessary health and safety knowledge to being able to carry out the desired behaviours in an
organisational context, which can be improved via, for example, receiving relevant training.
Of the 24 papers reviewed that discussed at least one of these eight factors, there was general
agreement that five of these had a significant influence on managers’ health and safety
behaviour. These were (1) self-efficacy, (2) knowledge, awareness and understanding, (3) risk
perception, (4) attitudes and (5) values and beliefs. In all cases the underlying evidence was
strong. Section 3.3 summarises key aspects to consider regarding the influence of attitudes,
values and beliefs on health and safety management. Research relating to self-efficacy 23 has
shown this to be a significant moderator of the relationship between intention or expectation of
behavioural outcomes and behaviour (e.g. Rabin et al, 1998; Webb & Sheeran, 2006). With
regards to knowledge, awareness and understanding, all studies reviewed considered this to be a
significant precursor to behaviour; in some cases this was argued as critical for positive health
and safety attitudes and behaviours (e.g. Addison & Burgess, 2002; Bentley & Haslam, 2001;
Gardner et al, 1999; Leinster et al, 1994). Hughson et al (2002) found that smaller companies
relied more heavily on hearing protection than other measures to reduce noise exposure largely
due to managers’ perceived complexity of the issue. As Leventhal et al’s (1984) SelfRegulatory Model 24 (SRM) proposes, the individual has to first understand that there is a health
issue that will affect them as well as having an understanding of the factors involved with that
particular health issue. Research relating to risk perception showed this to be heavily influenced
by managers’ knowledge of hazards (e.g. Gardner et al, 1999; Holmes et al, 1997). These
findings are consistent with Roger’s (1983) Protection Motivation Theory 25 (PMT), which
argues that both threat appraisal (perceived vulnerability to and severity of disease) and coping
appraisal (perceived costs of recommended response) determine protection motivation. Wright
(1999) takes this a step further by claiming that high risk perception is associated with intrinsic
motivation 26 to act, whereas managers who perceive business risks resulting from health and
safety failures to be low tend to be motivated more by external factors. Furthermore, Wright
claims that “although the same factors influence both SMEs and large companies, motivation
levels are more likely to be lower in SMEs as they are not in the public eye, have fewer
resources and inspections.”
For the remaining three factors that contribute to personal drivers (i.e. demographic
characteristics, personality and competence), the evidence was less clear-cut. Section 3.3
outlines the seemingly weak influence of organisational level demographic characteristics (e.g.
industry, role). One potentially influential personal characteristic mentioned in a study by
Lingard and Holmes (2001) is gender. Male managers were found to be less welcoming of
health and safety culture change programmes. As previously mentioned, however, the overall
23
See Glossary.
See Glossary.
25
See Glossary.
26
See Glossary.
24
17
evidence relating to this factor is weak and the extent of influence remains unclear. The same
applies to the influence of personality characteristics on management behaviour. Findings from
studies were inconsistent with regards to the extent of influence that a managers’ personality
(e.g. charisma, innovation, propensity for risk taking, trust in others) has on their health and
safety behaviour. Findings may vary according to sector type. For example, being principled,
flexible and innovative were considered key characteristics for managers within construction
(see Gillen et al, 2004), yet charisma and ability to motivate others were regarded as important
in the service industry (see Bentley & Haslam, 2001). In general, it seems that openness and
trust are important for managers at all levels (see O’Dea & Flin, 2003).
With regards to competence, a small number of studies have reported this as a factor influencing
health and safety management behaviour. For example, Shearn and Miller (2005) reported that
directors might not have the competence required to lead effectively on health and safety.
Addison and Burgess (2002) found that manual handling assessments had not been carried out
because of the perceived lack of skills amongst directors. Overall, the evidence was rated as
weak due to the absence of relevant empirical studies and inconclusive findings to date.
Of the 24 papers reviewed that assessed personal drivers, only three specifically addressed noise
(i.e., Leinster, Baum, Tong, & Whitehead, 1994; Foster, 1996; Hughson, Mulholland, & Cowie,
2002), four concerned other physical health hazards with latency between exposure and harm
and most (n=17) were relevant to occupational health and safety hazards generally. The three
papers that addressed noise highlighted the importance of managers’ technical knowledge of
noise as a factor that encouraged positive attitudes towards noise and subsequent
implementation of noise controls (e.g. understanding of engineering detail for noise control).
(See Appendix 1 for further details).
18
4
4.1
CONCLUSIONS IMPLICATIONS OF FINDINGS FOR THIS RESEARCH
Given the paucity of research directly examining factors that influence management behaviour
with regards to controlling noise risks 27 inferences have been made from the general health and
safety literature base. There will inevitably be some overlap between findings that emerge from
this research and the general health and safety literature since noise comes under the umbrella of
health and safety management. Little research to date has examined the psychological, social,
organisational and environmental influences in relation to noise management. As such, this
research aims to provide novel insights into the specific knowledge, attitudes, values, beliefs
and perceptions that managers’ hold about noise and how these interact with
social/environmental influences to result in the following:

Lack of application of technical/organisational noise control measures and health
surveillance for employees deemed to be at risk.

Misunderstandings of the true cost, business benefits, ease of introduction and
effectiveness of technical control compared with the provision of hearing protection.

Failure to access and understand available information on noise control.

Failure to produce an action plan to reduce exposure levels within their organisation.

Lack of acceptance of noise induced hearing loss as a significant occupational health
issue.
It will be interesting to see whether certain factors play a more prominent role in influencing
noise management behaviour compared with general health and safety management and
whether indeed any new factors emerge. Furthermore, examining the extent of influence of
differing factors requires greater attention than received to date. For example, managers’
knowledge of the health risks that working in a noisy environment may incur could act as a
stronger driver to go beyond the provision of hearing protection and implement
technical/organisational noise control measures than their beliefs about how such behaviour
could positively influence the business (e.g. reputation, financial gains). The research will also
seek to understand any third factor influences on identified relationships, such as previous
experience of a serious accident/incident.
For a number of factors extracted from the literature the extent of influence on management
health and safety behaviour remains unclear (i.e. economic/financial, competence, personality,
employee attitudes and motivation, environmental and demographic characteristics). For the
purpose of this review, the following sections summarise factors that emerged from this review
to influence organisations of all sizes, those that seem pertinent to SME managers and those that
appear to have little influence. Recommendations are made about what aspects to measure in
the research via the proposed methodology, questionnaire and interviews.
27
Only three papers out of the 38 selected articles in this review addressed noise.
19
4.1.1
Factors influencing organisations of all sizes
Based on the literature it would appear that the following factors are likely to influence noise
management behaviour (i.e. going beyond reliance on hearing protection to implementing
higher-level technical/organisational controls), regardless of organisation size:

Knowledge, awareness and understanding.

Risk perception.

Corporate reputation.

Compliance with legislation.

Experience of a serious accident and/or enforcement.

Health and safety attitudes, values and beliefs.

Control.

Self-efficacy.

Safety culture.

Competence.

Environment.

Demographics.
As such, questions addressing each of the above factors will be incorporated into the research
tools. It should be borne in mind, however, that managers might believe that they have
sufficient knowledge of noise risks, but in actual fact they may not posses this. As such,
questions to examine managers’ level of noise knowledge should be included in the research.
Furthermore, questions about attitudes should not only assess cognitive aspects (e.g. good
versus bad) but also affective aspects (e.g. unpleasant versus pleasant). The attitude that
productivity takes precedence over safety is also important to measure, as this may be
prominent in the manufacturing sector, which is the focus of this research. Evidently, attitudes,
values and beliefs are closely intertwined with an organisation’s culture. As such, gaining an
understanding of the level of safety culture maturity seems important or, at the very least, some
questions should be included to ascertain whether organisations have a positive safety culture or
not. Rather than focusing on management style, questions should explore relationships with
other leaders and levels of influence (control) given that it is possible for a positive safety
culture to be developed regardless of actual style.
Although the extent of influence was less certain for competence, environmental influences and
demographic characteristics, these factors are important to measure in this research. It is likely
that methodological issues surrounding the few studies conducted to date has led to these
inconclusive findings, rather than the factors themselves not playing a significant role. After all,
management competence concerning the required actions (risk assessments, determining
necessary controls, etc) to minimise noise hazards interacts with knowledge, awareness and
understanding of noise. The environment represents the social context in which behaviour
20
occurs and demographic characteristics (e.g. role, managerial level, gender) are important to
assess given their potential to moderate 28 the impact of other factors.
4.1.2
Factors pertinent to SMEs
The literature suggests the following as having a significant influence on SME noise
management behaviour over and above the influence each has on managers in larger
organisations:

Economic/financial.

Capability/cost of making improvements.

Resources.

Information and communications.
Given that the research sample will mainly consists of SMEs, it is important to include
questions covering the above factors. Evidently, the majority of these reflect financial and
business concerns. Time as well as money emerged as a significant barrier for SMEs, thus
questions relating to time management need to be included in the research. It is also important
to gain an understanding of managers’ perceptions of the cost of making improvements to
control noise risks within their organisations, providing an explanation for this. This will
provide some indication as to how realistic managers’ perceptions are regarding the true cost of
noise controls.
Although the research reviewed pointed to the limited impact of
economic/financial drivers on managers of large organisations, this may have changed in recent
times reflecting changes in the broader economy. As such, this may emerge as a significant
driver regardless of organisation size.
4.1.3
Factors showing less impact on management behaviour
The following factors were shown in the literature to have little influence on noise management
behaviour in comparison to those factors listed in Sections 4.1.1 and 4.1.2:

Employee attitudes and motivation.

Customer pressure.

Personality.
Based on these results, it is recommended that questions concerning customer pressure are not
included in the research tools. Should this have a significant influence on noise management
behaviour, it will emerge through the interviews with managers. The same applies to employee
attitudes and motivation. This may emerge as a significant driver for SMEs given the direct
contact that senior managers tend to have with front line workers. With regards to personality,
it is recommended that questions do not focus on measuring the personality attributes of
managers. Although personality influences behaviour, there is little that HSE can do to change
this. To some extent this can be assessed through questions on safety climate/culture (e.g.
openness and trust) for which interventions can be implemented to change safety culture
28
See Glossary under ‘moderating variables’.
21
maturity levels. After all, a manager may intend to behave in a certain way but the work
environment may not support this behaviour meaning that the intended behaviour is not carried
out. PRECEDE and the social cognitive models/theories cited in this review attach considerable
importance to these social influences in workplace settings as opposed to individual-level
factors. The changes in the broader economy may also result in different drivers.
4.2
OVERALL SUMMARY
This literature review has identified a number of factors likely to influence management
behaviour with regards to controlling noise risks. To summarise, behaviour of interest to this
research includes the application of technical/organisational noise control measures, use of low
noise/low exposure tools/machines, full and proper use of hearing protection for residual/shortterm risk and health surveillance for employees at risk. Seventeen factors have been identified
as important to measure in the research as shown in Table 6. The five overarching factors
provide a useful structure for the research tools. It should be borne in mind, however, that these
factors are based largely on findings from previous studies looking at general health and safety
management rather than noise specifically. As such, new factors may emerge through the
interviews with managers or, at the very least, clarification as to the extent of their influence.
Much of the research reviewed did not document actual effect sizes 29 in order to gauge the true
extent of their influence.
Overarching Factor (n=5)
Business
Legal
Cultural/Organisational
External
Personal
Contributing Factors (n=17)

Economic / financial
Corporate reputation
Capability / cost of making engineering improvements
Compliance with legislation
Values and beliefs
Perceived / actual control
Culture
Resources
Demographics
Environmental
Knowledge, awareness and understanding
Risk perception
Competence
Self-efficacy / confidence
Demographics
Values and beliefs
Table 6: Factors to assess in the research.
29
See Glossary.
22
4.3
NEXT STEPS
Interviews are currently being arranged with specialist and general HSE Inspectors to gather
further information to inform the development of the research tools. In particular, they will
identify from their experience and expertise what factors they consider influence noise
management behaviour (i.e. implementation of technical/organisational and engineering noise
control measures, the provision of health surveillance and hearing protection), differences in and
possible reasons for the behaviours exhibited by managers of high performing and low
performing organisations and the key differences, if any, between noise as an occupational
health hazard and other forms of health hazard. This is crucial given the paucity of literature
that has examined management behaviours and noise. The interviews with the six Inspectors
will therefore assist in finalising the areas of questioning for the research. This may also help to
reduce the overall number of variables included in the questionnaire, which needs to be a
suitable length so as not to discourage employers from completing them. The interview
questions will also need to target key areas to allow adequate coverage and time for probing
important areas in the allotted time (approximately one hour). Combining the key themes that
emerge from these interviews with the results from this review will ensure that a balanced set of
questions is developed. Key factors will be covered in the questioning as well as scope to
reveal any unknown influencing factors. Consequently, the research tools will not be biased by
Inspectors’ perceptions, given that employers may not be wholly truthful and open with
Inspectors.
23
5
GLOSSARY Abusive / unethical leadership: Leaders who are overly punitive or aggressive and may
violate commonly accepted codes of conduct (see Kelloway et al, 2006).
Active / effective leadership: Otherwise referred to as ‘transformational leadership’ (Bass,
1985, cited in Kelloway et al, 2006), this style characterises leaders who show concern for the
well-being of their workforce and is considered to be highly effective through, for example,
encouraging organisational commitment, high performance and employee satisfaction.
Behaviour: In this context, behaviour refers to an overt visible action or practices that affect
the risks of noise exposure. Behaviour, in turn, is influenced by a range of factors that occur at
a psychological, social, and organisational level. The terms action and practices are used in this
brief to refer to behaviour.
Behavioural intentions:
behaviour.
Assumed to be the motivational factors that influence actual
Charismatic Leadership: House (1971) defined charismatic leadership behaviours as,
achievement-oriented, directive, participative, and supportive. See also transformational
leadership.
Compliance Behaviour: Individual’s are more likely to comply when they can perceive there
are advantages to be gained if they do a task or action.
Control Theory (Carver & Scheier, 1982, 1998): States that people compare their ongoing
performance with a desired standard and make adjustments to behaviour accordingly. Intention
(or reference value) for performance is a key determinant of behaviour change.
Effect size (Cohen, 1992 – standard estimates of effect sizes): Measures the strength of the
relationship between two variables.
Extrinsic Motivation: An external motivator, usually money, but can also be incentives such
as coercion, threat of disciplinary action, dismissal, redundancy, withholding/offering overtime.
(See also Intrinsic Motivation).
Fatalism: A belief that events or actions are predetermined and outcomes cannot be changed
or altered.
Health Belief Model (Rosenstock, 1974): The individual is only likely to change their
behaviour when they perceive the advantages of avoiding a perceived threat to be in excess of
any disadvantages through a cost-benefit trade-off.
Humanistic approach (management style): A high regard for individuals’ personal and work
problems. Direct and rapid action is taken to identify and resolve any uncovered problems in a
caring and concerned manner.
Intrinsic motivation (Deci, 1975): Intrinsic motivation comes from the pleasure one gets from
the task itself or from the sense of satisfaction in completing or even working on a task.
Someone who is intrinsically motivated may still seek some form of reward whether it be
financial or some other form of recognition, but if they are not interested in what they are doing
then rewards alone will not be enough to motivate them to do the task (see extrinsic
motivation).
24
Mental representations: Otherwise known as ‘mental models’, refers to the processing of new
information in the context of peoples’ existing beliefs.
Meta-analysis: Combines the results from a number of studies related to the same research
hypothesis and determines the strength of the overall value (see also effect size).
Model of Interpersonal Behaviour (MIB - Triandis, 1977): Consistent with the TPB,
intention is a key determinant of behaviour, which requires control over behaviour (or
‘facilitating conditions’). A second moderating variable is proposed, however, namely, the
extent to which the behaviour is ‘habitual’. Intentions have less impact on behaviour when the
behaviour has become a habit due to reduced control over that behaviour.
Moderating variables: Baron and Kenny (1986) provide a classic definition; “…a moderator
is a qualitative (e.g. sex, race, class) or quantitative (e.g. level of reward) variable that effects
the direction and/or strength of the relation between an independent or predictor (causal)
variable and a dependent or criterion (outcome) variable.’
Passive / ineffective leadership: Leaders who lack positive leadership skills and do not
achieve desired outcomes. It comprises elements of ‘management-by-exception’ (passive) and
‘laissez-faire’ styles (Bass and Avolio, 1990, cited in Kelloway et al, 2006). In the former,
leaders fail to intervene until problems are either brought to them or become too serious to
ignore. In the latter, leaders avoid the responsibilities of leadership including decision-making.
Both types of passive leadership are considered ineffective.
PRECEDE Model (Green & Kreuter, 1991; Green et al, 1980): PRECEDE stands for
Predisposing, Reinforcing and Enabling Causes in Educational Diagnosis and Evaluation.
Originally developed as a planning framework for health education programmes, the model has
been applied to self-protective behaviour at work. The model promotes the identification of
behavioural causes of health problems and the analysis of factors related to these causes. The
factors form three categories namely, (1) Predisposing (motivating – have a direct effect on
compliance behaviour) – individual characteristics (attitudes, values, beliefs, etc) that facilitate
or hinder self-protective behaviour, (2) Enabling (have direct and indirect influences on
compliance behaviour) – environmental/system features that facilitate or hinder self-protective
behaviour (e.g. knowledge, skill, availability of PPE), and (3) Reinforcing (have direct and
indirect influences on compliance behaviour) – the reward or punishment that follows the
behaviour (feedback, social dis/approval, etc). The model attaches considerable importance to
social-environmental factors in workplace settings as opposed to individual-level factors.
Protection Motivation Theory (PMT - Rogers, 1983): Rogers defines protection motivation
as intention to perform the recommended behavioural response. Consistent with the TRA, TPB
and MIB, intention is construed as the most immediate predictor of health behaviours. Two
processes determine protection motivation i.e. (1) threat appraisal (perceived vulnerability to
and severity of disease) and (2) coping appraisal (perceived costs of recommended response).
Prototype-Willingness Model (PWM - Gibbons et al, 1998; Gibbons et al, 2003): States
that there are two routes to behaviour, namely, (1) reasoned action route (similar to TRA as
health protective behaviours result from intentions, the product of attitudes, norms and past
behaviour), and (2) social reaction route (people may not intend to perform risky health
behaviours but may do so if the social environment is conducive). Social settings may therefore
provide opportunities for risky behaviours that might override a person’s good intentions. As
such, although intentions are the most important predictor of health behaviours, engaging in
risky behaviour if generally a reaction to risk-conducive circumstances (determined by
willingness) than a deliberate decision (determined by intention).
25
Qualitative research: Seeks to find meaning in a natural setting.
Safety culture: ‘The way things are done around here’. Safety culture is positive when
employees genuinely believe that safety is high on the list of their organisation’s priorities
(safety is crucial).
Self-Efficacy: A person’s belief or confidence in their ability to perform the desired behaviour.
This ties in with their level of self-esteem in that performing the behaviour will result in them
feeling good about themselves.
Self-Regulatory Model (SRM – Leventhal et al, 1984): Provides an understanding of
people’s reponses to threats to their health. The individual has to first understand that there is a
health issue that will affect them and the factors involved with that issue. The individual is
responsible for developing an action plan to resolve the health issue and is involved in
monitoring and checking the action plan.
Stage of Change model (Prochaska and DeClemente, 1982): See also the Transtheoretical
Model of Change (TMC) that describes the stages an individual must go through before
achieving behavioural change. This model also assumes that to relapse and to return to past
patterns of behaviour is a typical part of the process and an individual may relapse many times
before a more stable pattern of behavioural change is achieved.
Theory of Goal Setting (Locke & Latham, 1990): The key act that promotes goal
achievement is the formation of an intention to undertake certain tasks.
Theory of Planned Behaviour (TPB - Ajzen & Fishbein, 1980; Ajzen, 1988): Builds on the
TRA through recognition that people do not always have a great deal of control over their
behaviour. Personal control is key for intention to perform behaviour and enacting the
intention. Behavioural control is an additional predictor of intention with attitudes and
subjective norms. Control can directly predict behaviour and/or moderate the impact of
intention on behaviour.
Theory of Reasoned Action (TRA - Fishbein & Ajzen, 1975): A major assumption of this
theory is that people deliberately use information from their environment and consider
implications of their actions to decide whether to behave in a certain way or not. It states that
two processes explain the relationship between attitude and behaviour. Firstly, social pressure
from significant others (i.e. subjective norms) determines whether a person performs a
behaviour that they hold favourable attitudes towards. Secondly, intention is the most
immediate and important predictor of behaviour. Attitudes and subjective norms determine
whether a person ‘intends to act’ a certain way; it is this intention that ultimately leads to the
behaviour.
Tinnitus:
A condition characterised by noises, usually, ringing, whistling, buzzing or
humming that can be heard in one or both ears or in “the head.” The noise may come and go
and in some cases it is continuous which can lead to disturbed sleep, resultant fatigue and poor
concentration. It can also make it difficult to hear conversations either in a work or social
setting, which can be extremely isolating. Tinnitus can occur at any age and people most at
risk are those who have frequent and prolonged exposure to loud noises. There is currently no
cure for tinnitus.
Transformational Leadership (Burns, 1978): A leadership style characterised by the ability
to instil commitment and direction within the workforce through communication and
engagement. Such leaders tend to be innovative, enthusiastic and confident and get the best out
of their people.
26
Transtheoretical Model of Change (TMC - Prochaska & DiClemente, 1983): Describes the
process of behaviour change through a sequence of five stages. (1) Precontemplation – a person
is unaware of the problem and has no intention to change, (2) Contemplation – the person
acknowledges the problem and considers changing their behaviour in the next six months, (3)
Preparation – the person aims to change their behaviour in the near future, (4) Action – intention
is acted upon, and (5) Consolidation – occurs when the new behaviour occurs for at least six
months; otherwise the person relapses back to and earlier stage.
Triangulation (Denzin, 1978): Developed as a means of cross checking data from multiple
sources to increase the reliability and validity of a study, Denzin identified four basic methods
of triangulation that could be used to reduce any innate bias that is introduced into single
method, single-observer, single-theory studies. The four basic methods of triangulation are a
Data triangulation which involves time, space and persons; Investigator triangulation involving
more than one investigator; Theory triangulation using more than one theoretical perspective to
interpret the data and Methodological triangulation which involves using more than one method
to collect data. Triangulation is used in both qualitative and quantitative studies.
Yukl’s (1989b) Conceptual Framework of Leadership Effectiveness: The model depicts
that organisational effectiveness (end results) is mediated by a core set of intervening variables,
which are themselves influenced by a complex interaction of leader traits, power, influence and
situational variables. Leader behaviour is influenced by a variety of factors including leader
attributes, situational demands and constraints and information about intervening variables and
end results. The model recognises, however, that other influences on performance may override
the leaders influence.
27
6
REFERENCES ACOEM Noise and Hearing Conservation Committee. (2003). ACOEM evidence-based
statement: noise-induced hearing loss. Journal of Occupational Environmental Medicine, 45,
579-81.
Addison, N., & Burgess, G. (2002). Compliance with Manual Handling Regulations amongst
Random Selection of Small Businesses in England. Annual Occupational Hygiene, 46, 149155.
Ajzen, I. (1988). In T. L. Webb & P. Sheeran (2006). Does changing behavioural intentions
engender behaviour change? A meta-analysis of the experimental evidence. Psychological
Bulletin, 132 (2), 249-268.
Ajzen, I., & Fishbein, M. (1980). In T. L. Webb & P. Sheeran (2006). Does changing
behavioural intentions engender behaviour change? A meta-analysis of the experimental
evidence. Psychological Bulletin, 132 (2), 249-268.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social
psychological research: Conceptual, strategic, and statistical considerations. Journal of
Personality and Social Psychology, 51, 1173-1182.
Barrett, J. H., Haslam, R. A., Lee, K. G., & Ellis, M. J. (2005). Assessing attitudes and beliefs
using the stage of change paradigm – case study of health and safety appraisal within a
manufacturing company. International Journal of Industrial Ergonomics, 53, 871-887.
Bentley, T. A., & Haslam, R. A. (2001). A comparison of safety practices used by managers of
high and low accident rate postal delivery offices. Safety Science, 37, 19-37.
Burns, J. M. (1978). Leadership. New York: Harper and Row Publishers Inc.
Carver, C. S., & Scheier, M. F. (1982). In T. L. Webb & P. Sheeran (2006). Does changing
Carver, C. S., & Scheier, M. F. (1998). In T. L. Webb & P. Sheeran (2006). Does changing
Cheung, C. (2004). Organizational influence on working people’s occupational noise
protection in Hong Kong. Journal of Safety Research, 35, 465-475.
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159.
Colemont, A., & Van den Broucke, S. (2006). Psychological Determinants of Behaviours
Leading to Occupational Injuries and Diseases in Agriculture: A Literature Review. Journal of
Agricultural Safety and Health, 12(3), 227-238.
Controlling noise at work. The Control of Noise at Work Regulations (2005). HSE Books.
Deci, E. L. (1975). Intrinsic motivation. New York: Plenum.
28
DeJoy, D. M. (1996). In D. M. DeJoy, C. A. Searcy, L. R. Murphy, & R. R. M. Gershon,
(2000). Behavioural-Diagnostic Analysis of Compliance with Universal Precautions Among
Nurses. Journal of Occupational Health Psychology, 5(1), 127-141.
DeJoy, D. M., Searcy, C. A., Murphy, L. R., & Gershon, R. R. M. (2000). BehaviouralDiagnostic Analysis of Compliance with Universal Precautions Among Nurses. Journal of
Occupational Health Psychology, 5(1), 127-141.
Denzin, K. (1978). The Research Act: A Theoretical Introduction to Sociological Methods,
New York: McGraw-Hill.
Ferguson, E., Lawrence, C., Bibby, P., Leaviss, J., & Moghaddam, N. (2006).
conceptualisations of occupational disease. HSE Report 469: HSE Books.
Lay
Fishbein, M., & Ajzen, I. (1975). In T. L. Webb & P. Sheeran (2006). Does changing
Foster, G. (1996). Factors influencing the implementation of noise control programs in
industry. Journal of Occupational Health Safety, 12(4), 471-475.
Gardner, D., Carlopio, J., Fonteyn, P. N., & Cross, J. A. (1999). Mechanical equipment
injuries in small manufacturing businesses. Knowledge, behavioural, and management issues.
International Journal of Occupational Safety and Ergonomics, 5(1), 59-71.
Gervais, R. L. (2006). An evaluation of successful communication with small and medium
sized enterprises (SMEs). HSL/2006/32.
Gibbons, F. X., Gerrard, M., Blanton, H., & Russell, D. W. (1998). In T. L. Webb & P.
Sheeran (2006). Does changing behavioural intentions engender behaviour change? A metaanalysis of the experimental evidence. Psychological Bulletin, 132 (2), 249-268.
Gibbons, F. X., Gerrard, M., & Lane, D. J. (2003). In T. L. Webb & P. Sheeran (2006). Does
changing behavioural intentions engender behaviour change? A meta-analysis of the
experimental evidence. Psychological Bulletin, 132 (2), 249-268.
Gillen, M., Kools, S., McCall, C., Sum, J., & Moulden, K. (2004). Construction managers’
perceptions of construction safety practices in small and large firms: A qualitative investigation.
Work, 23, 233-243.
Green, L. W., & Kreuter, M. W. (1991). In D. M. DeJoy, C. A. Searcy, L. R. Murphy, & R. R.
M. Gershon (2000).
Behavioural-Diagnostic Analysis of Compliance with Universal
Precautions Among Nurses. Journal of Occupational Health Psychology, 5(1), 127-141.
Green, L. W., Kreuter, M. W., Deeds, S. G., & Partridge, K. B. (1980). In D. M. DeJoy, C. A.
Searcy, L. R. Murphy, & R. R. M. Gershon (2000). Behavioural-Diagnostic Analysis of
Compliance with Universal Precautions Among Nurses. Journal of Occupational Health
Psychology, 5(1), 127-141.
Health and Safety at Work Act. (1974). See www.hse.gov.uk/legislation/hswa.htm
Health and Safety Executive (2005). Noise at Work; Guidance for employers on the Control of
Noise at Work Regulations. HSE Books.
29
Hofman, D. A., & Morgeson, F. P. (1999). Safety-Related Behaviour as a Social Exchange:
The role of Perceived Organizational Support and Leader-Member Exchange. Journal of
Applied Psychology, 84(2), 286-296.
Holmes, N., Gifford, S.M., & Triggs, T.J. (1998). Meanings of Risk Control in Occupational
Health and Safety Among Employers and Employees. Safety Science, 28(3), 141-154.
Holmes, N., Lingard, H., Yesilyurt, Z., & De Munk, F. (1999). An Exploratory Study of
Meanings of Risk Control for Long Term and Acute Effect Occupational Health and Safety
Risks in Small Business Construction Firms. Journal of Safety Research, 30 (4), 251-261.
Holmes, N., Triggs, T. J., Gifford, S. M., Dawkins, A. W. (1997). Occupational injury risk in
blue collar small business industry: Implications for prevention. Safety Science, 25, 67-78.
Hopkins, A. (1995). Making Safety Work. Getting Management Commitment to Occupational
Health and Safety. St. Leonards, NSW: Allen & Unwin Pty Ltd.
House, Robert J. (1971). "A path-goal theory of leader effectiveness". Administrative Science
Quarterly, 16, 321-339.
Hughson, G. W., Mulholland, R. E. & Cowie, H.A. (2002). Behavioural studies of people’s
attitudes to wearing hearing protection and how these might be changed. HSE Research Report
028.
Kelloway, E. K., Mullen, J., & Francis, L. (2006). Divergent effects of transformational and
passive leadership on employee safety. Journal of Occupational Health Psychology, 11(1), 7686.
Krause, T. R. (2004). Influencing the behaviour of senior leadership. Professional Safety, June
Edition, 29-33.
Leinster, P., Baum, J., Tong, D., & Whitehead, C. (1994). Management and motivational
factors in the control of noise induced hearing loss. Annals of Occupational Hygiene, 38 (5),
649-662.
Leventhal, H., Nerenz, D. R. & Steele, D. J. (1984). Illness representations and coping with
health threats. In: A. Baum, S. E. Taylor & J. E. Singer (Eds.). Handbook Of Psychology and
Health, 4, 219-252. Hillsdale, NJ: Erlbaum.
Lingard, H., & Holmes, N. (2001). Understandings of occupational health and safety risk
control in small business construction firms: Barriers to implementing technological controls.
Construction Management and Economics, 19, 217-226.
Locke, E. A., & Latham, G. P. (1990). In T. L. Webb & P. Sheeran (2006). Does changing
Maierhofer, N. I., Griffin, M. A., & Sheehan, M. (2000). Linking manager values and
behaviour with employee values and behaviour: A study of values and safety in the
hairdressing industry. Journal of Occupational Health Psychology, 5(4), 417-427.
O’Dea, A., & Flin, R. (2003). The role of managerial leadership in determining workplace
safety outcomes. HSE Research Report 044.
30
Petersen, D. (2004). Leadership and Safety Excellence: A positive culture drives performance.
Professional Safety, Oct Edition, 28-32.
Podgorski, D. (2006). Factors Influencing Implementation of Occupational Safety and Health
Management Systems by Enterprises in Poland. Human Factors and Ergonomics in
Manufacturing, 16 (3), 255-267.
Ponting, L. (2001). Changing necessity into a benefit in small firms. Health and Safety
Bulletin, 296, 20-22.
Prochaska J.O., & DiClemente C.C. (1982). Transtheoretical therapy: Toward a more
integrative model of change. Psychotherapy Theory, Research and Practice, 19, 276-288.
Prochaska, J. O., & DiClemente, C. C. (1983). In A. Colemont & S. Van den Broucke (2006).
Psychological Determinants of Behaviours Leading to Occupational Injuries and Diseases in
Agriculture: A Literature Review. Journal of Agricultural Safety and Health, 12(3), 227-238.
Rabin, S., Feiner, M., Shaham, J., Yekutieli, D., & Ribak, J. (1998). Impact of Managers’
Personal Determinants in Notifying Workplace Hazards. American Journal of Industrial
Medicine, 33, 493-500.
Rogers, R. W. (1983). In T. L. Webb & P. Sheeran (2006). Does changing behavioural
intentions engender behaviour change? A meta-analysis of the experimental evidence.
Psychological Bulletin, 132 (2), 249-268.
Rosenstock, I. M. (1974). The health belief model and preventative health behaviour. Health
Education Monographs, 2, 354-356.
Rundmo, T., & Hale, A. R. (2003).
prevention. Safety Science, 41, 557-574.
Managers’ attitudes towards safety and accident
Sandberg, T., & Conner, M. (2008). Anticipated regret as an additional predictor in the theory
of planned behaviour: A meta-analysis. British Journal of Social Psychology, 47, 589-606.
Shearn, P., & Miller, M. (2005). Director Leadership of Health and Safety. HSL Report:
SOFS/05/07.
Sheehy, N. P., & Chapman, A. J. (1987). In DeJoy, D. M., Searcy, C. A., Murphy, L. R., &
Gershon, R. R. M. (2000). Behavioural-Diagnostic Analysis of Compliance with Universal
Smallman, C. & John, G. (2001). British directors perspectives on the impact of health and
safety on corporate performance. Safety Science, 38, 227-239.
Smith, M. J., & Beringer, D. B. (1987). In DeJoy, D. M., Searcy, C. A., Murphy, L. R., &
Gershon, R. R. M. (2000). Behavioural-Diagnostic Analysis of Compliance with Universal
Thompson, R.C., Hilton, T. F., & Witt, L. A. (1998). Where the Safety Rubber Meets the Shop
Floor: A Confirmatory Model of Management Influence on Workplace Safety. Journal of
Safety Research, 29(1), 15-24.
Timothy, N. (2006). Improving health at work: Employers’ attitudes to occupational health.
Association of British Insurers (ABI) proposals and supporting research by Greenstreet Berman
Ltd, in association with the Woodholmes Group.
31
Triandis, H. C. (1977). In T. L. Webb & P. Sheeran (2006). Does changing behavioural
intentions engender behaviour change? A meta-analysis of the experimental evidence.
Psychological Bulletin, 132 (2), 249-268.
Vickers, I., Baldock, R., Smallbone, D., James, P., & Ekanem, I. (2003). Cultural influences
on health and safety attitudes and behaviour in small businesses. HSE Research Report 150.
Webb, T. L., & Sheeran, P. (2006). Does changing behavioural intentions engender behaviour
change? A meta-analysis of the experimental evidence. Psychological Bulletin, 132 (2), 249268.
Welch, B. L. (1979). Extra-auditory health effects of industrial noise: Survey of foreign
literature (Government Rep. No. AMRL-TR-79-41). Aerospace Medical Research laboratory,
Aerospace Medical Division, Air Force Systems Command, Wright-Patterson Air Force Base,
Dayton, OH.
Wright, M. S. (1998). Factors Motivating proactive health and safety management. HSE
Contract Research Report 179.
Wright, M. A. (1999). A risky business. Environmental Health, 107(3), 90-93.
Wright, M., Antonelli, A., Norton Doyle, J., Bendig, M., & Genna, R. (2005). An evidence
based evaluation of how best to secure compliance with health and safety law. HSE Research
Report 334.
Wright, M., & Marsden, S. (2002). Changing business behaviour – Would bearing the true
cost of poor health and safety performance make a difference? HSE Books. ISBN 0 7176 2362
9.
Wright, M., Marsden, S., Dimopoulos, E. (2006). Health and safety responsibilities of
company directors and management board members: 2001, 2003, and 2005 surveys. HSE
Research Report 414.
Yukl, G. (1989b). Managerial leadership: a review of theory and research.
Management, 15(2), 251-289.
32
Journal of
7
7.1
APPENDICES
APPENDIX 1: DATA EXTRACTION TABLE
Reference
Summary of research
(Include Industry and Country)
Potential Influences on
Management Behaviour
1. Wright, M., & Marsden, S.
(2002). Changing business behaviour
– Would bearing the true cost of poor
health and safety performance make a
difference? HSE Books. ISBN 0
7176 2362 9.
UK-based research conducted for HSE by Greenstreet Berman to
increase employers’ motivation to improve health and safety and
rehabilitation through the UK insurance process. This is based on
the premise that previous research has shown that the cost of
occupational ill health and injuries and, specifically, the cost of
employers’ liability insurance, does not motivate UK employers
as intended. A survey of 1,800 UK employers by Wright et al
(2000) found that only 8% of respondents were prompted to make
improvements due to business impacts / bad PR / customer
pressure. The main motivators reported were regulations,
awareness of hazards and the belief that it is necessary and
morally correct to comply with health and safety regulations.
Furthermore, the majority of respondents thought that workrelated ill health costs them between ‘a little’ and ‘nothing
significant’.
In the present study, a survey of the UK businesses (3,500
administered to a cross representation of sectors including
manufacturing; 18% response rate) revealed that UK employers
would be motivated to improve occupational health and safety
and rehabilitation if the cost of insurance increased and they
believed there was a link between their performance and the cost
Financial motivators – Ill
health and injury costs
(insurance premiums)
associated with poor health
and safety performance as a
potential motivator for
employers. [Not a significant
motivator].
30
Other emerging factors:
Corporate credibility,
customer pressure. [Not
significant motivators].
Noiserelevance
Rating
(N, H, G 30 )
G
Implications for Research
Tools and any Caveats
(E.g. cultural differences –
How applicable to UK?)
Financial drivers do not seem
to be key influences on
employers’ behaviour.
Although important to include
some questions on this for the
purpose of modelling the
interplay between factors (and
the fact that moderators appear
to exist), questions should be
kept to a minimum.
See Questionnaire developed
by Greenstreet Berman for
example questions.
Regulations, hazard
awareness, moral beliefs.
[Significant motivators].
Moderating factors: Risk
awareness, cost/capability of
making improvements.
H = Highly Relevant (research specific to noise), R = Relevant (other physical health hazards with latency between exposure and harm), and G = Generic (occupational health and safety hazards
generally).
33
of insurance (i.e. a significant decline in premiums with increased
health and safety performance). Factors that moderate 31
employers’ motivation to manage health and safety were noted,
including their awareness of risk and cost of improvements (i.e.
knowing they are capable of making these).
2. Barrett, J. H., Haslam, R. A., Lee,
K. G., & Ellis, M. J. (2005).
Assessing attitudes and beliefs using
the stage of change paradigm – case
study of health and safety appraisal
within a manufacturing company.
International Journal of Industrial
Ergonomics, 53, 871-887.
A case study of health and safety appraisal within a UKmanufacturing company responsible for constructing prefabricated buildings. The authors used Prochaska and
DeClemente’s (1982) Stage of Change model 32 as a framework to
assess attitudes and beliefs of key stakeholders (at three levels:
senior-level management, middle-level management and
production-level employees including production supervisors)
within the organisation. A triangulated approach 33 was adopted
including stage-targeted questions, supplementary interviews and
assessment of safety culture 34 . Focusing on responses obtained
from senior-level management (i.e. the Managing Director (MD)
and the Production Director (PD)), the MD had developed plans
and begun acting upon these to address the health and safety
issues prevalent within the company. Motivation stemmed from
the MD’s awareness of the financial implications of poor health
and safety following a serious incident at the company (a
medium-sized enterprise).
Interviews with both senior and middle-level management
revealed conflict between production and safety. For example,
the Managing director believed that safety should be prioritised
over production, but there is the need for occasional compromise
and supervisors tend to think about production rather than safety.
The PD also cited conflict between his responsibilities for
achieving production targets and for ensuring safety.
The PD also recognised that he did not have the health and safety
knowledge required for the safety side of his role.
31
See Glossary under ‘Moderating variables’.
See Glossary.
See Glossary under ‘Triangulation’.
34
See Glossary.
32
33
34
Financial implications of
poor health and safety.
Possible Moderator
(influence of financial
factors): Whether company
has experienced a serious
accident/incident.
Productivity pressures (to
reach set targets) take priority
over safety.
Lack of necessary health and
safety knowledge.
G
An important moderator
highlighted for financial
influences i.e. whether
company has experienced a
serious accident/incident case
needs to be measured.
Productivity conflict is likely
to be a pertinent factor in
manufacturing companies
hence necessary to measure.
Knowledge of health and
safety is likely to vary by
organisation size and whether
a Health and Safety Officer is
in post.
3. Rundmo, T., & Hale, A. R.
(2003). Managers’ attitudes towards
safety and accident prevention.
Safety Science, 41, 557-574.
Analysed the relations between managers’ (n=74) safety attitudes,
behavioural intentions 35 and their self-reported behaviour. In line
with the Theory of Planned Behaviour 36 (TPB) and Theory of
Reasoned Action 37 (TRA) it was hypothesised that attitudes affect
intentions, which in turn affect behaviour.
The attitudes of presidents, vice-presidents and managers (n=210)
towards safety in a Norwegian industrial company (case study),
Norsk Hydro, were examined during attendance at a management
safety course.
The author’s point out that to control hazards managers ideally
have to do the following: detect hazards, find ways to control
them, prioritise them, select good solutions, implement solutions,
monitor change and learn from experience. As such, managers
need to have the necessary knowledge and resources (time,
money, competence and equipment) to carry out these steps.
Consistent with Rundmo’s previous research (1998a, 1998b,
1992), the TPB, TRA, the Health Belief Model 38 and SelfRegulatory Model 39 , managers’ attitudes were shown to influence
behavioural intentions and behaviour. A Principle Components
Analysis revealed that eight attitudinal dimensions explained up
to 40% of the variance in behaviour. Ideal attitudes for managers
therefore appear to be high safety commitment, low fatalism 40 ,
low tolerance of rule violations, high worry and emotion, low
powerlessness, high safety priority, high mastery and high-risk
awareness. The most influential attitudes on safety seem to be (1)
high management commitment and involvement, (2) low fatalism
concerning accident prevention, (3) high safety priority and (4)
high risk awareness.
35
See Glossary.
See Glossary.
37
See Glossary.
38
See Glossary.
39
See Glossary.
40
See Glossary.
36
35
Managers’ safety attitudes
influence on intentions and
behaviour.
Knowledge and resources
(time, money, competence and
equipment) to carry out
necessary steps for controlling
hazards.
G
Highlights the eight attitudinal
dimensions that affect
managers’ safety intentions
and behaviour, four of which
were found within this study
to play an influential role
(management commitment,
fatalism, safety priority, risk
awareness).
Also implicates the
importance of knowledge and
resources for controlling
hazards.
Note that this research is
restricted to one Norwegian
company although the
managers were operating all
over the world.
See paper for attitudinal items
included in the questionnaire.
4. Timothy, N. (2006). Improving
health at work: Employers’ attitudes
to occupational health. Association
of British Insurers (ABI) proposals
and supporting research by
Greenstreet Berman Ltd, in
association with the Woodholmes
Group.
ABI (Association of British Insurers) commissioned Greenstreet
Berman in 2006 to investigate employers’ attitudes towards
occupational health (OH). A telephone survey of 435 UK
directors and managers responsible for OH, representative cross
section of small and large organisations in both the public and
private sectors, was conducted. Findings showed that although
employers are becoming increasingly aware of the benefits
associated with OH provision, regard it as effective, see it as key
to managing sickness absence, productivity and fulfilling duty of
care to employees, some employers, particularly smaller
companies, regard OH as too costly. Others considered OH to be
a ‘low priority’ for them, access to the services to be ‘patchy’,
that the personal injury scheme ‘gets in the way’ and that the
current tax situation (treating OH as a benefit rather than
investment in human capital) deters them from doing more.
Financial barriers towards
OH – too costly (particularly
SMEs), considered a low
priority, patchy access to
services, personal injury
scheme, and current tax
situation.
G
5. Krause, T. R. (2004). Influencing
the behaviour of senior leadership.
Professional Safety, June 2004, 2933.
Based on the author’s 20 years of experience (opinion-based)
working with management in the USA to develop methods for
safety improvement and studying factors that distinguish
successful organisations from the less successful, the author
concludes that the quality of leadership is the single most
important factor and provides insights into how to influence
senior leaders in order to help them become great safety leaders.
Based on the author’s experience, senior leaders are primarily
motivated by ‘human compassion’. Although other reasons exist
(e.g. recognition that safety improvement is good for business),
the true motive is a sense of integrity, grounded in ethical
principles, and a sense of duty.
Based on a comparison of the author’s experiences with the
literature on leadership influences on safety and organisational
culture (e.g. Kotter; Erikson; Fairhurst et al), eight leadership
practices were connected to the development of a positive safety
culture. These are: (1) vision (seeing what safety performance
excellence would look like in their company and actively convey
this to staff), (2) credibility (e.g. giving honest information about
safety performance even if not well received, uniformly applying
Quality of safety leadership.
G
36
Human compassion,
integrity and sense of duty.
Good for business.
Provision of OH services is
embedded within HSE’s
hierarchy of controls.
Differences between SMEs
and large organisations are
likely concerning the extent
and degree that financial
factors influence managers’
behaviours.
Identifies the eight aspects of
high quality safety leadership,
a key component of improving
health and safety.
Singles out human
compassion as the main
influence on managers’ safety
behaviour.
Important to note that this is
not an empirical piece of
research, rather a summary of
the author’s experience within
American organisations.
Points to the importance of
following the general
principles of behaviour change
when conducting
safety standards), (3) collaboration (e.g. promoting cooperation in
safety, encouraging input), (4) feedback and recognition (on
accomplishments), (5) accountability (fostering the sense that
people are responsible for their own safety), (6) communication
(e.g. encouraging people to deliver honest, complete information
about safety, keeping all employees informed), (7) values safety
(acting to support safety values, leading by example) and (8)
action orientated (proactive rather than reactive in addressing
safety issues).
The author claims that ‘senior leaders are often highly motivated
and do not resist change and the tasks before them are highly
enabled’. The same principles of behaviour change apply to
senior leaders, however, as to supervisors, frontline workers and
people generally (e.g. the need for timely constructive feedback
on actions taken). It is crucial for senior leaders to understand
what critical behaviours are important to perform and how these
relate to a given objective.
6. Webb, T. L., & Sheeran, P.
(2006). Does changing behavioural
intentions engender behaviour
change? A meta-analysis of the
experimental evidence.
Psychological Bulletin, 132 (2), 249268.
Theories of attitude-behaviour relations (e.g. TRA, TPB, Model
of Interpersonal Behaviour 41 ), models of health behaviour (e.g.,
Protection Motivation Theory, Prototype-Willingness Model 42 )
and goal theories (e.g. Control Theory 43 , Theory of Goal
Setting 44 ) all put forward the idea that intention is a key
determinant of behaviour. Meta-analyses based on a large
number of correlational studies have yielded a large effect on
behaviour (according to Cohen’s, 1992, standard estimates of
effect sizes 45 ). Several methodological issues, however, prevent
making inferences about causation (e.g. cause and effect is not
determined via correlation, third variable influence, cross-
41
See Glossary.
See Glossary.
43
See Glossary.
44
See Glossary.
45
See Glossary.
42
37
interventions.
Affects of intention on
behaviour.
Important moderators that
impact the affect of intention
of behaviour, the most
important being – perceived or
actual control/self-efficacy
over behaviour, social
reaction and whether the
behaviour has become a habit
G
Provides further evidence for
the potential influence of
cultural elements on
managers’ behaviour – in
particular ‘social reaction’. A
manager may intend to behave
in a particular way, but the
work environment may not
support this behaviour and
may in fact be conducive to
risky health behaviours.
7. Gillen, M., Kools, S., McCall, C.,
Sum, J., & Moulden, K. (2004).
Construction managers’ perceptions
of construction safety practices in
small and large firms: A qualitative
investigation. Work, 23, 233-243.
46
47
sectional studies).
As such, the authors conducted a meta-analysis 46 of 47
experimental studies (mostly correlational) designed to influence
intention and subsequent follow-up behaviour. The following
categories of moderating variables was assessed: (1) Conceptual
(control/self efficacy, social reaction, habitual control), (2)
measurement (time interval between intention and behaviour, type
of behaviour measure (objective versus self-report), nature of the
control group), (3) study characteristics (sample type, published
versus unpublished works).
The authors’ reported that a medium-large change in intention
(d=0.66) leads to a small-medium change in behaviour (d=0.36).
Consistent with the correlational studies, intention has a
significant impact upon behaviour, but, contrary to the
correlational studies, the effect size is much smaller than they
suggest. This finding does, however, support arguments put
forward by the social and health psychology theories i.e. that
changing peoples’ intentions leads to behaviour change.
Results also showed that, intentions have less impact on
behaviour when people lack control over behaviour, when there is
potential for social reaction and when habits have been formed
(the conceptual moderators). Measurement and study
characteristics also impacted the intention-behaviour relationship.
or not.
The authors looked at American construction managers’
perceptions of safety practices, comparing the views of those
belonging to small and large firms. A qualitative investigation 47
was carried out involving five focus groups with 22 managers
(two with managers of small firms, three with managers of large
firms). A semi-structured interview guide was followed to obtain
information on both direct and indirect safety practices.
Results revealed the following as key for maintaining safe
worksites: broad commitment to safety, training, workplace
culture and uniform enforcement. To be successful at managing
Management commitment
Safety culture.
Enforcement.
See Glossary.
See Glossary under ‘Qualitative research’.
38
Habit formation also links to
culture – ‘the way things are
done around here’. It may be
that managers have slipped
into poor habits with regards
to health and safety
management.
Control over behaviour is also
important to consider.
Managers may intend to e.g.
promote safety, yet lack
control (either perceived or
actual) over their behaviour
and as such do not.
Measuring these three
elements will provide a good
indication of managers’
behavioural intentions, which
in turn impacts their actual
behaviour.
Management characteristics
(flexible, innovative and
principled).
Financial constraints.
Poor training (knowledge).
G
Identifies some key variables
important to measure with
focus on what enables and
deters safety management.
Note the potential differences
between the US and UK
enforcement system and the
fact this research concerns the
construction industry (e.g. the
8. Colemont, A., Van den Broucke,
S. Psychological Determinants of
Behaviours Leading to Occupational
Injuries and Diseases in Agriculture:
A Literature Review. Journal of
Agricultural Safety and Health,
12(3), 227-238.
48
safety in construction managers need to be ‘principled’,
‘innovative’ and ‘flexible’ (e.g. using different management
techniques with different groups of workers), largely due to the
complex and varied workforce that characterises construction.
Managers of both large and small firms identified obstacles to
safety management, mostly concerning ‘time and money’,
‘culture’ (in need of changing with e.g. worker training), and
‘scheduling’ (production schedules). ‘Profit’ was also a recurrent
theme with managers stating that productivity takes precedence
over safety to keep the business operating. They were fully
aware, however, of the long-term benefits associated with
increased safety (e.g. reduced lost work days). There was also
mention of a general lack of understanding of hazards within
construction at all levels of the organisation.
A literature review on the application of social cognitive models
(i.e. the Health Belief Model, TRA, TPB, and Transtheoretical
Model of Change 48 ) for preventing disease and injuries amongst
agricultural workers. This is because disease and injury is
typically the result of the interplay between behavioural and
contextual factors. A limited number of studies (n=15), however,
were found that employed interventions involving these models
and these generally did not incorporate effect sizes / predictive
values. Interventions to encourage healthier behaviour amongst
farmers are generally unsuccessful. This seems to be the result of
reliance on increasing awareness and risk analysis, rather than
addressing other relevant factors including, attitudes, perceived
social norms, self-efficacy and elements of the physical
environment that promote behaviour.
The review concluded that although some studies purport a
positive relationship between knowledge and safety behaviour,
the majority of studies reviewed found no association. Rather,
positive safety attitudes and beliefs were related to protective
behaviour. Furthermore, a number of barriers were identified as
keeping farmers from applying safety measures, namely,
See Glossary.
39
Productivity versus safety.
necessary manager
characteristics may be
different in manufacturing).
Understanding of the
hazards that characterise the
industry.
Awareness of hazards,
associated health outcomes
and controls.
Risk perception /
complacency.
Attitudes and beliefs.
Perceived social norms.
Self-efficacy.
Elements of the physical
environment (e.g. cost
constraints).
Knowledge.
Cost constraints (engineering
controls).
Also, many of the managers
interviewed were members of
trade associations hence likely
to be actively promoting
safety in construction or at the
very least, aware of the issues.
H
The context of agriculture
varies considerably from that
in manufacturing, bearing in
mind that in the former the
farmer is often the manager
and worker (performing both
roles), where as management
and workforce are generally
clearly distinguished in the
latter. Nevertheless, the same
core factors emerge as in
research conducted in other
sectors and types of
organisations, such as attitudes
and social norms.
Note the poor documentation
of research studies reviewed in
this review and the lack of
effect sizes; hence the
complacency about farm safety, a low perception of personal risk
and cost constraints limiting maintenance and purchase of farm
equipment and machinery.
9. Wright, M., Marsden, S.,
Dimopoulos, E. (2006). Health and
safety responsibilities of company
directors and management board
members: 2001, 2003, and 2005
surveys. HSE Research Report 414.
10. Shearn, P., & Miller, M. (2005).
Director Leadership of Health and
Safety. HSL Report: SOFS/05/07.
49
predictive impact of these
factors on farmers’ behaviour
remains unclear.
Greenstreet Berman administered a survey (via telephone) in
2001, 2003 and 2005 (longitudinal) to large public and private
organisations covering a range of industries (e.g. Private: retail,
manufacturing, construction, finance, transport; Public: education,
NHS and LA) in the UK, following release of the HSC guidance
‘Directors’ responsibilities for health and safety’ to examine the
extent of board level direction of health and safety. Between
2001 and 2005 the proportion of boards with a named health and
safety director rose from 75% to 85%. The top five reasons for
this apparent increase in directing health and safety at board level
include: An increase in ‘general concern for health and safety
performance’ or increase in the ‘importance of health and safety’
(ranked as the top factor across all three surveys), ‘concern about
corporate image/responsibility (ranked second in 2003, 2005),
‘HSE/C guidance’ (ranked third in 2001, fourth in 2003 and fifth
in 2005), ‘corporate governance requirements’ and ‘fear of
company prosecution’ (ranked eighth in 2005). Little variation
was found between public and private sector directors.
General concern
for/increased importance of
health and safety.
Similar to the above study by Wright et al (2006), this paper
summarises a literature review of UK and international
literature on directors’ (senior and board-level decision makers)
responsibilities for health and safety, which mostly included
opinion-based papers and HSE reports. Part of the review
looks at factors influencing directors’ behaviour. The authors
claim that directors’ role within the organisation, industry sector,
type of operations, prevalence of accidents, incidents and ill
health and knowledge and personal interest in health and safety
all influence the way directors’ behave. Specifically, findings
Role within the organisation.
Industry sector and type of
operations.
Accident, incident and illhealth rates.
Knowledge/personal interest
in health and safety.
See Glossary.
40
G
Provides the top five factors
influencing director behaviour
with regards to directing
health and safety. This covers
results from three surveys over
a 4-year time span, the latest
being conducting in 2005,
rather than relying on the
findings from one survey.
G
A very useful paper for
summarising key factors
found to influence directorlevel behaviour (up until
2005).
Concern about corporate
responsibility/image.
HSE Guidance.
Corporate governance
requirements.
Fear of company
prosecution.
Health and safety legislation.
Reputation.
Most importantly, it points out
that factors may have a
varying degree of influence on
SMEs compared with large
11. Bentley, T. A., & Haslam, R. A.
(2001). A comparison of safety
practices used by managers of high
and low accident rate postal delivery
offices. Safety Science, 37, 19-37.
indicate that the following factors influence directors’ behaviour:
‘compliance with legislation’, ‘fear of loss of reputation’ due to
prosecution/bad publicity, ‘direct financial considerations’ (health
and safety is good for business) with added benefits such as
increased morale, retention and profit, a key component of
‘winning contracts’ (especially for smaller businesses as larger
companies specify the required health and safety standards for
their suppliers), and ‘morale responsibility’ (especially on SMEs
in which directors are likely to know their workforce).
There appear to be clear differences between SMEs and large
organisations in terms of what influences director behaviour as
shown in the above findings.
The review also highlighted that directors may not have the
competence (knowledge and skills) required to lead effectively on
health and safety.
Senior management commitment is also key to health and safety
management as cited in other empirical research documented in
this paper (e.g. Cox and Flin, 1998; Turner, 1991; Pidgeon and
O’Leary, 1994).
Furthermore, management style, namely, a humanistic 49
approach, is considered effective.
The authors’ cite a survey by MORI (2000) of 204 senior
directors. Generally, directors were aware of the negative impact
that a poor safety culture can have on the organisation. 90% cited
morale and retention as being the most impacted areas, followed
by reputation (80%), insurance costs (80%), accidents at work
(78%), productivity/efficiency, customer satisfaction and
sales/profit were also mentioned.
Financial considerations.
Winning contracts (SMEs).
Morale responsibility
(especially in SMEs).
A UK study comparing the safety practices (mainly in relation to
slips, trips and falls) of a cross section of 20 Delivery Office
Managers (DOMs: supervisor level) in high and low accident
rate postal delivery offices. To obtain a list of desirable
management safety practices, a number of sources were utilised.
Previous research data was analysed to identify factors that might
be associated with accident risk, semi-structured interviews were
Attitudes towards safety.
41
organisations. The results
from this research will mostly
be from SMEs (to be
representative of the
manufacturing sector). It is
therefore important to include
factors shown to have a
significant influence on SMEs.
Competence (knowledge and
skills) to manage health and
safety.
Similar key factors emerge as
in other papers previously
cited. A new factor, however,
subsumed under ‘knowledge’
appears worthy of
consideration, namely,
‘knowledge of the potential
effects of a poor safety
culture’. This could
potentially be a strong
motivator for managers in
terms of whether they strive to
develop a positive safety
culture or not.
Senior management
commitment.
Management style.
Knowledge of the potential
effects of a poor safety
culture. This includes
managers’ understanding of
the link between health and
safety and business outcomes
(i.e. the ‘business case’).
Time/workload (safety
coming second to
productivity).
Lack of available good safety
G
Useful research as it compares
high and low performing
organisations, which is one of
the aims of this study. The
focus of Bentley and Haslam’s
study, however, centres on the
behaviours that managers/
12. Petersen, D. (2004). Leadership
and Safety Excellence: A positive
culture drives performance.
Professional Safety, Oct Vol, 28-32.
50
conducted with senior delivery managers (n=3) and DOMs (n=3)
to ascertain safety practices used, and a focus group was held with
senior managers (n=12) in Royal Mail to consider use and
effectiveness of a range of safety practices.
Findings showed that the impact of supervisors’ on the
occurrence of slips, trips and falls, arises from both their attitudes
and actions. Those working in low accident rate offices had
improved performance regarding quality of safety
communication, dealt with hazards encountered on delivery
walks, conducted accident investigations and took remedial
action.
The following factors were reported to limit DOMs ability to
undertake various safety practices (in order of frequency
mentioned): Time/workload factors (competing demands), lack of
availability of good safety equipment/footwear, postal delivery
officer indifference towards safety/rushing, lack of
training/knowledge of health and safety, cost/budget factors, noncompatibility with quality considerations. No differences were
detected between those in high and low accident offices.
The authors also stated that ‘the safety performance of DOMs is
likely to be affected by their general qualities, including their
charisma, ability to motivate people, and time management’.
Lack of time emerged as a key barrier to safe working, largely
due to the prioritisation of production (e.g. prompt delivery of
mail) over safety. Increased commitment to safety from senior
managers and the organisation itself was considered paramount.
equipment (resources).
Based on the author’s experience (in the USA) and
interpretations of the available literature (opinion-based), the
process that leaders use when dealing with safety (injury
prevention and reduction) is explored. The focus is on the
interpersonal influence that a leader can exercise within their
organisation to accomplish safety goals. Petersen points out that
‘leaders’ exist at varying levels within an organisation and that
Interpersonal characteristics
(especially important is degree
of influence over others).
See Glossary.
42
supervisors exhibit (i.e. safety
practices) rather than what
actually influences their safety
behaviour. Some insight into
the latter was gleaned in terms
of the factors that limited
supervisors’ ability to
undertake safety practices. A
key barrier in this research
was ‘time’ (productivity/safety
clash).
Employee attitudes and
behaviour (e.g. indifference
to safety).
Knowledge / training.
Cost/budget.
Safety not compatible with
work quality.
Raises some different factors
to consider, namely, the
influence of employee
attitudes and behaviour on
managers’ and safety not
being compatible with work
quality.
Individual characteristics
(charismatic, motivator) and
time management.
Management commitment.
Job characteristics (role
clarity and ability, work
organisation, level of
G
Shows that leadership and
culture are closely interlinked.
The questionnaire could
incorporate items assessing
safety culture (to determine
whether this is positive or
negative).
the term is not only describing those in executive positions.
The paper refers to Yukl’s (1989b) Conceptual Framework of
Leadership Effectiveness 50 , part of which describes intervening
variables likely to influence leadership behaviour. These are:
subordinate effort, role clarity and ability, organisation of work,
cooperation/teamwork, resources and external coordination.
In the author’s opinion, the two most important aspects to
consider when deciding what needs to be present to achieve safety
are ‘leadership’ and ‘culture’. Petersen continues to argue that an
organisation’s culture determines whether or not any element of a
safety programme is effective or not, claiming that almost any
element will work in a positive safety culture.
A positive safety culture can be created regardless of management
style (e.g. authoritarian versus participative) and approach to
safety.
subordinate cooperation and
motivation).
Highlights the importance of
focusing on the relationships
that leaders have with other
leaders and their employees.
Rather than looking at
‘management style’, the focus
of this research should
concern the relationships and
influence of leaders. For
example, including some
attitudinal items in the
questionnaire to measure
control and influence.
Resources.
Also, the need to understand
the position of the leaders
(level within the
organisational structure, who
s/he reports to and who reports
to him/her).
13. Ponting, L. (2001). Changing
necessity into a benefit in small
firms. Health and Safety Bulletin,
296, 20-22.
Provides anecdotal evidence of the business benefits that SMEs
can accrue from making health and safety an integral part
business management. An example case study is provided of a
small UK plastics manufacturing company that used risk
assessments to involve employees, improve production, reduce
risks, accidents and ill-health and introduce new ways of working.
The result was a significant reduction in absence and accidents
rates and a notable improvement in the working environment and
the organisation of production processes. Improved employee
commitment and communication between all levels of the
hierarchy were also noted.
The author also points out that small businesses often lack inhouse health and safety knowledge and are thus highly dependent
on suppliers (e.g. of safety equipment) and external advisors.
43
Knowledge of the business
benefits from health and
safety management (especially
amongst SMEs) – and
whether these convince
them.
Knowledge of health and
safety systems and
procedures.
Information provided by
suppliers / external
consultants.
G
Shows factors that potentially
impact the behaviour of SME
directors/managers in terms of
health and safety management.
These factors may not feature
amongst large organisations,
likely to have a dedicated
health and safety manager.
Such information may in some cases be misleading. Furthermore,
systems designed for large organisations may present an
administrative burden for smaller organisations for which a more
simple method may be acceptable.
14. Leinster, P., Baum, J., Tong, D.,
& Whitehead, C. (1994).
Management and motivational factors
in the control of noise induced
hearing loss. Annals of Occupational
Hygiene, 38 (5), 649-662.
This paper looked into the individual and organisational factors
that affect both management and worker attitudes towards noise
induced hearing loss (NIHL) and subsequent action taken. 48
British organisations were surveyed (a variety of small and
large, public and private sector, range of industries including
manufacturing), 10 of which underwent a more detailed
investigation as case studies. 1514 questionnaires were
completed which corresponded to a response rate of 69%.
Interviews were conducted with senior managers, middle
managers, personnel with health and safety responsibilities,
supervisors and the workforce from the organisations selected as
case studies.
Key findings pertinent to this research include the following:
An assumption amongst (case study) managers that engineering
controls are expensive despite little evidence of thorough
investigation of noise control measures.
Worker complaints that noise control measures made their work
‘difficult’ (e.g. limited working space as a result of
soundproofing, humidity and poor ventilation in soundproof
cabs).
Noise at work is widely taken for granted, adapted to and
considered inevitable. The fact that NIHL is not life threatening,
has a delayed onset and does not lead to absence from work
means that noise is not viewed seriously by both management and
workforce.
Managers made it clear that performance or cost factors heavily
influenced their decisions about noise controls.
PR concerns (avoidance of bad publicity, especially in the
chemical industry) emerged as a key driver for managers.
Differing attitudes towards cost control and productivity were
evident amongst managers with some seeing the value of
44
Perception of health and
safety management /
implementing controls.
Management perception of
the cost of engineering
controls.
Employee perceptions of
noise controls implemented
(e.g. engineering controls
changing work design,
comfort levels of PPE) may
influence managers’
behaviour, particularly in
SMEs in which senior
managers tend to have direct
contact with their workforce.
Knowledge of health effects
and business benefits.
Resources.
Reputation.
Attitudes towards
productivity versus safety.
Awareness of legal duties,
technical knowledge of noise
and authority to deal with
noise issues.
Senior management
N
employee perceptions and the
potential impact this has on
managers’ behaviour,
particularly in SMEs.
Also, managers’ perceptions
of the cost of noise controls
may not reflect the reality.
Reputation may be more of an
issue for high hazard
industries (e.g. the chemical
industry).
Useful for highlighting the
issue of authority if the
responsibility for noise has
been delegated to a lowerlevel manager, who has
insufficient knowledge and
authority to make positive
change.
employees working in quieter, less stressful situations for quality
of outputs and thought it sensible to reduce compensation claims
and non-compliance fines. Others, however, thought that noise
control measures slowed down production and required large
capital expenditure.
In the worst case study organisations, those responsible for
carrying their noise regulation duties were not aware of the extent
of their legal duties and delegated responsibility to lower-level
management who often lacked the technical noise knowledge to
deal with this or had insufficient authority within the organisation.
The most important factor for good practice with regards to noise
control was senior management commitment, which ensures
sufficient resources for noise control and demonstrates to the
workforce that noise is taken seriously. Middle managers often
followed the priorities set by senior managers.
commitment.
The authors pointed out that professional training in industrial
management including a component on noise appeared to be
effective in achieving positive attitudes and behaviour towards
noise.
15. Kelloway, E. K., Mullen, J., &
Francis, L. (2006). Divergent effects
of transformational and passive
leadership on employee safety.
Journal of Occupational Health
Psychology, 11(1), 76-86.
Examined the effects of leaders ‘turning a blind eye’ to safety
issues by looking at the impact of passive leadership 51 on safetyrelated outcomes as well as active / effective leadership 52 . Much
of the documented research has focused on the latter rather than
the former. It has become apparent in recent years, however, that
more research is needed to examine the effects of poor leadership.
The authors outline the two categories of poor leadership, namely,
(1) abusive / unethical 53 and (2) passive / ineffective. Given that
leaders who ignore safety issues are likely to be more prevalent in
industries than those who completely disregard the safety of their
workforce, passive leadership was selected to represent ‘poor
leadership’ in this research.
51
See Glossary.
See Glossary.
53
See Glossary.
52
45
Safety consciousness levels.
Safety
climate/culture
perceptions.
G
A useful piece of research for
understanding
different
leadership styles, in particular
the importance of ‘passive’
leadership for organisational
safety outcomes. However,
the focus concerns the impact
of leadership styles of safetyrelated outcomes, rather than
what
influences
these
styles/behaviour in the first
place, likely to be an interplay
Employed working undergraduate students (n=101)
participated in this questionnaire study. The authors conducted a
series of analyses (factor analysis, hierarchical regression and
structural equation modelling) to test the relationships between
passive and active leadership styles and prediction of
organisational outcomes (e.g. safety consciousness, climate,
injuries).
Results showed that, consistent with the literature, active
leadership has a positive effect on safety outcomes. In addition,
passive leadership was found to have a significant, unique,
negative effect on such outcomes.
A key implication of this research is there is no neutral position
when it comes to safety. Taking no action negatively impacts
safety outcomes by diminishing employees’ safety consciousness
levels and perceptions of their safety climate.
between the interpersonal
characteristics of the leader
and the organisational culture
in which they are embedded.
As such, this research should
assess
cultural
(safety
consciousness, perception of
safety
climate)
and
interpersonal
influences,
rather
than
measuring
leadership style per se.
16. Maierhofer, N. I., Griffin, M. A.,
& Sheehan, M. (2000). Linking
manager values and behaviour with
employee values and behaviour: A
study of values and safety in the
hairdressing industry. Journal of
Occupational Health Psychology,
5(4), 417-427.
A cross-sectional questionnaire study was conducted involving
219 employees and their managers in the Australian
hairdressing industry.
Results showed that managers’ value of time urgency was related
to employees’ value of time urgency. A significant negative
relationship between employees’ time urgency and safety
behaviour was discovered. As such, time management values
seem to be more important for safe behaviour than values
concerning prevention. The management of time and priorities is
an important consideration when assessing the impact of values
on safety behaviour.
Time
management
prioritisation.
and
G
Highlights
the
potential
impact of ‘time urgency’ as a
value held by managers on
safety behaviour shown by
employees.
However, no
direct effect was reported
between
managers’
time
urgency and their own actual
behaviour. Issues related to
time are likely to emerge from
examining
‘productivity
versus safety’, which can be
further explored in the
interviews with managers.
17. Gardner, D., Carlopio, J.,
Fonteyn, P. N., & Cross, J. A.
(1999). Mechanical equipment
injuries in small manufacturing
businesses. Knowledge, behavioural,
This study examined factors, including management practices,
that impact on high injury rates resulting from mechanical
equipment within small manufacturing high-risk organisations
(with 19 personnel or less).
Interviews were conducted with 35 business owners in
Knowledge and awareness of
hazards.
G
Useful for highlighting factors
likely to influence
management behaviour in
small organisations. The
manager-employee
46
Motivation.
and management issues.
International Journal of Occupational
Safety and Ergonomics, 5(1), 59-71.
18. Wright, M. A. (1999). A risky
business. Environmental Health,
107(3), 90-93.
54
55
Australia. 145 employees completed questionnaires and a
technical checklist was used during observations of un/safe
conditions.
Knowledge and awareness of hazards was found to be relatively
low with few managers having received adequate training on
occupational health and safety issues. Managers of small
companies tend to be involved in a range of tasks as a result of
their direct involvement in the day-to-day running of the business.
As such, they generally do not have expertise in all relevant areas,
particularly health and safety. It is worth noting, however, that
the managers themselves thought that they had a good level of
understanding of the hazards and risks in their workplace.
Managers did not consider the identification and control of risks
as a priority, which ties in with their general low level of
awareness of health and safety standards / regulations.
Lack of resources (time and money) was also reported as an
influencing factor as well as lack of knowledge of the costs of
Cultural influences were also reported including lack of the
following: safety procedures, rules and regulations, clearly
defined responsibilities for safety and procedures for learning
from accidents.
Managers also commented that they found it difficult to be
assertive with employees about health and safety matters, as they
wanted to maintain a friendly relationship with staff.
Knowledge of the costs of
This article summarises the views of the author (opinion-based)
towards the management of health and safety behaviour based on
his own experiences (including conducting research for HSE) and
knowledge of the literature.
‘Fear of adverse publicity’ has been shown to be a strong
motivator, particularly for high-risk industries (e.g. chemical and
transport). Other factors grouped under this ‘fear’ banner include:
prosecution, enforcement notices, and experience of a major
Fear of adverse publicity.
See Glossary.
See Glossary.
47
relationship may be an
important issue for small
organisations given direct
contact with staff.
Risk perception.
Resources (time and money).
There is a need to consider in
this research how to deal with
the issue that managers may
believe that they have
sufficient knowledge of the
risks and hazards within their
organisation, yet in actual fact
may not. The questionnaire
and interviews could ask
managers to, for example,
name the top three hazards
and explain why these are
hazards.
Cultural influences (safety
rules and procedures,
including recording accidents
and learning from these, and
defined responsibilities for
safety).
Manager-employee
relationship (friendliness
versus assertiveness).
Intrinsic and extrinsic
motivation 55 levels.
Illustrating how factors can be
grouped under ‘core’ factors
e.g. ‘fear’. This will be
necessary due to the large
number of factors emerging
from the literature.
Beliefs that health and safety
Shows the need to consider
Need to comply with the law.
G
19. Gervais, R. L. (2006). An
evaluation of successful
communication with small and
medium sized enterprises (SMEs).
HSL/2006/32.
56
incident.
‘Need to comply with the law’ has been reported as a factor
influencing the management of organisations of all sizes, yet
motivation may to comply may be low as detection and
prosecution levels are low. Furthermore, the latency period
between ill-health triggers and the onset of ill-health conditions
may not motivate employers to act on the health aspects of
regulations.
‘Cost’ is reported far less in UK literature compared to the USA
literature, in which it is considered to be a strong motivating
factor. This difference is likely due the differences in health care
insurance and compensation arrangements. This does not mean,
however, that the ‘belief that health and safety improvements save
money’ is not important.
Perception of risks to the business from health and safety failures
may intrinsically motivate 54 managers to improve without the
need for external factors (e.g. regulation). Conversely, those who
perceive their risk to be low may be affected more by external
factors. The author argues that although the same factors
influence both SMEs and large companies, motivation levels are
more likely to be lower in SMEs, especially those considered low
risk as, unlike large organisations, they are not in the public eye,
have fewer resources and inspections.
improvements save money.
A review of the literature (29 empirical studies) aimed at
identifying communication techniques that work with SMEs,
reported that while regulations are necessary in business, some
businesses tend to see them as a hindrance rather than as a way to
assist in maintaining a safe workplace. This may affect their
Perceptions of HSE and
regulation requirements.
All three questions were extracted from Wright’s article.
48
the ‘risk levels’ of
participating organisations
likely to influence motivation
to act. The following
questions assess risk 56 :
Is health and safety
performance considered to be
a critical commercial success
factor?
Are the costs of ill health and
injury perceived to be
significant?
Do customers or standards
bodies exert pressure to
achieve certain health and
safety standards?
Perception of business risks.
Cost.
If the answer to one or more
of these is ‘yes’, health and
safety is likely to be a core
management responsibility.
Also shows that ‘cost’ in not a
driving factor in the UK,
rather the important factor
concerns ‘beliefs in the cost of
health and safety
improvements’.
Inspector visits /
enforcement.
G
Provides insight into reasons
why SMEs in particular may
not comply with health and
safety standards, which may
include those on noise.
responsiveness to receiving and acting on communication about
obligatory regulations for the workplace.
Other factors reported as important to bear in mind when
communicating with SMEs that bear relevance to the current
research on noise include:
The perception amongst small companies that HSE is not aware
of the ‘real world’ and the difficulties they face in running their
business.
SMEs tend to prefer face-to-face interaction and this may in turn
influence compliance behaviour (e.g. through inspector visits).
SMEs may be influenced by Intermediaries’ (e.g. accountants,
trade associations) provision of health and safety information.
Guidance on ‘what is essential for them’ seems paramount for
SMEs (sector specific information).
Lack of understanding of HSE guidance as it is too complex
impacts communication with SMEs as well as lack of resources
(financial, human). Simple and layperson terms, rather than
expert terminology, is vital when communicating with SMEs.
20. Ferguson, E., Lawrence, C.,
Bibby, P., Leaviss, J., &
Moghaddam, N. (2006). Lay
conceptualisations of occupational
disease. HSE Report 469: HSE
Books.
57
This research examined differences between lay and expert
models of illness (multiple sclerosis, lung cancer, stress and
asthma) to examine any potential for miscommunication between
lay and expert groups. Interviews were conducted with 21
experts (occupational physicians, occupational psychologists)
and 19 laypersons, following which a field experiment
(questionnaire-based) was conducted involving a random sample
of the UK population (n=1947:17% response rate) compared
with a sample of experts (n=240: 37% response rate). Cognitive
mapping was also carried out with experts (n=15) and laypersons
(n=15).
Results showed that lay and expert differences exist with
laypersons, on the whole, viewing inter-personal (less scientific)
sources of information as more trust worthy. Laypeople based
their inter-personal actions (e.g. stopping working, informing
See Glossary.
49
Managers are likely to respond
to an external source that
communicates to them in their
language i.e. in a simple
manner explaining what they
need to do in their own
organisation.
Third party advice on noise.
Understanding of HSE
guidance.
Knowledge/mental models of
illnesses, risks, health effects
and consequences.
Information sources (trusted
and used).
H
It may be that some managers
do not have an accurate
understanding of the
associated risks, ill health
outcomes/ consequences of
noise and, conversely, the
benefits to taking action,
which may partly explain why
the uptake of noise control
measures within organisations
appears to be below the
desired threshold.
Information sources used may
not be the most reliable for
their employer) on trusted advice from their GPs and family and
friends, where as they trusted advice from HSE or occupational
physicians on practical work-related issues (e.g. information
about the diseases).
These findings highlight the importance of how subject matter
experts communicate health risks to lay people. The authors’
stressed the importance that information provided by experts to
managers needs to be congruent with their mental
representations 57 . Expert and lay people have very different
models of illness. If they lack knowledge of the topic, the new
message will be incomprehensible or if they hold erroneous
beliefs then a new message may be misconstrued. Other research
has reported this to be an essential consideration when
communicating with, particularly, SMEs (e.g. Gervais, 2006,
Williamson & Weyman, 2005, Weyman, Chambers & Keen,
2002 – all cited in this paper).
21. Addison, N., & Burgess, G.
(2002). Compliance with Manual
Handling Regulations amongst
Random Selection of Small
Businesses in England. Annual
Occupational Hygiene, 46, 149-155.
Looked at compliance with manual handling regulations amongst
UK SMEs (100 companies in Shropshire employing 5-50
employees, randomly selected, differing industries). A
questionnaire-based study, which achieved a high response rate
(80%).
Findings showed that over a third of the companies claimed that
they had never heard of the regulations and almost half had not
carried out an assessment. Similar levels of non-compliance and
ignorance were reported in research by Honey et al (1996, 1997)
on the Noise at Work Regulations and the Display Screen
Equipment Regulations. The authors also claimed that methods
used to reduce manual handling risks possible reflects the ease
with which these can be introduced. The research further
suggests that assessments were not performed because of
perceived lack of skills amongst directors. It may be that
directors perceive the need for specialist knowledge and/or
resources that are not easily available to them as a necessary prerequisite for assessments as well as the need for additional
knowledge to decide on preventative measures (usually involving
50
informing them about what
they need to do to control
noise at work.
Refer to measures used in the
research (contained in
Appendix 4 of the report) for
actual questions utilized.
Ease of implementation and
resources for control
measures.
Perceived competence to
carry out risk assessments and
determine necessary controls.
Survival of the business.
G
Suggests possible factors
influencing
dutyholders/directors of SMEs
choice and implementation of
noise controls.
Important caveats are that the
companies involved were
based in Shropshire hence not
representative of small
businesses in England.
Furthermore, the research was
conducted in 1998/99 prior to
HSE’s introduction of manual
handling guidance targeted at
specific industries and
targeting of SMEs.
multiple interventions).
The companies that indicated full compliance (n=21) stated that
the benefits of compliance to the business far outweighed the cost
(namely effort to obtain information on legislation). Survival in a
competitive market place was a key theme expressed.
22. Holmes, N., Triggs, T. J.,
Gifford, S. M., & Dawkins, A. W.
(1997). Occupational Injury Risk in
a Blue Collar, Small Business
Industry: Implications for
Prevention. Safety Science, 25(1-3),
67-78.
Holmes, N., Gifford, S.M., & Triggs,
T.J. (1998). Meanings of Risk
Control in Occupational Health and
Safety Among Employers and
Employees. Safety Science, 28(3),
141-154.
23. Holmes, N., Lingard, H.,
Yesilyurt, Z., & De Munk, F. (1999).
An Exploratory Study of Meanings of
Risk Control for Long Term and
Acute Effect Occupational Health
and Safety Risks in Small Business
Construction Firms. Journal of
Safety Research, 30 (4), 251-261.
Australian research in the SME Painters industry looking at
perceptions and understandings of risk in OHS among employers
(n=87) and employees (n=81) influence on the control of risks at
work. Explanations of risk judgements were elicited and
subjected to ethnographic content analysis to reveal underlying
meanings of risk and its control.
The research provides evidence that participants make a
distinction between immediate effect injuries and delayed effect
injuries. Employers tend to rate risks linked to immediate effect
injuries more highly than employees who tend to judge delayed
effect injuries more highly than employers.
Risk perception - Perceptions
of long-term versus short-term
risks.
A qualitative study (15 in-depth interviews) of employers’ and
employees’ meanings of occupational health and safety (OHS)
risk control (for falls from height and skin disease). Five small
(employing 3-10 people) Australian companies took part in the
research.
Findings showed that risk control involves the following:
Perceptions of risk control –
is noise-induced hearing loss
controllable or not? Costbenefit analysis of controlling
the risk? What is the best
method of control and why?
Locus of control: I.e. whether the cause resulting in the risk is
internal (individual) or external to the person (DeJoy, 1994). If
the former is believed to be true, risk control is likely to focus on
individual rather than technological control measures.
Controllability of the risk: When the risk is perceived as being
uncontrollable, fatalistic attitudes are likely to prevail.
Estimated effort to control the risk: Individuals weigh up the
costs and benefits of controlling the risk. When this is believed to
Resources (cost and time
constraints)
51
G
Employers and managers risk
perception needs to be
measured.
The paper recognises that
there is a different decision
making process for short term
compared with long term risk,
which may be important to
consider in this research.
Note, however, that Australian
research is based on different
OHS regulation.
H
(Skin
disease has
a latency
period)
A very small sample, focusing
on micro-organisations rather
than SMEs. Useful, however,
for breaking down the facets
of risk control and what may
potentially influence
employers’ perceptions of risk
control.
be too difficult (or costly), the risk is likely to be accepted.
Individual biases: For example, beliefs that ‘it won’t happen to
me’ (individual susceptibility) or attributing the behaviour of
others to internal factors (e.g. carelessness, lack of concentration)
and their own behaviour to situational factors.
Cost and time constraints imposed in the construction industry
were reported as barriers to implementation of technological risk
controls (e.g. provision of suitable scaffolding for falls from
heights). Acceptance of this leads to acceptance of the risk being
‘part of the job’ and any attempts to control the risk of falling
were an individual issue.
24. Hopkins, A. (1995). Making
Safety Work. Getting Management
Commitment to Occupational Health
and Safety. St. Leonards, NSW:
Allen & Unwin Pty Ltd.
Australian book discussion including the petrochemical,
mining, communications, transport and metal manufacturing
industries. The authors claim that risk has to be managed from
the top down. They also state that company Occupational Health
and Safety (OHS) officers have an important role in bringing
consequences to the attention of management. They further points
out that safety leaders tend to focus on zero lost time injury to the
detriment of other factors.
“Managers are influenced by a
variety of motives, among
them, economic incentives,
fear of legal consequences,
moral commitment and
concern for their own good
reputations. There are
numerous ways in which these
motives can lead to action to
improve occupational health
and safety. But none of these
is automatic. These motives
will come into play only if
management’s attention is
drawn to the relevant
information.”
Management commitment is
also key.
G
Funded by the Australian
equivalent of HSE thus has an
Australian bias. Points out
that safety leaders focus on
zero lost time injury to the
detriment of other factors.
Noise risks tend not to lead to
lost time, which may be a
reason why noise controls are
not extended beyond PPE
supply.
25. Vickers, I., Baldock, R.,
Smallbone, D., James, P., & Ekanem,
I. (2003). Cultural influences on
health and safety attitudes and
UK cross sectional research (telephone survey of 1,087 SMEs
and interviews with 73 SME managers and 21 employees)
including ethnic minority businesses (EMBs) and small and
medium sized enterprises (SMEs). Studied internal and external
Resource constraints on
SMEs.
G
Need to consider factors likely
to have an impact on SME
managers’ decision-making
and behaviour.
52
Management Style and
behaviour in small businesses. HSE
26. Podgorski, D. (2006). Factors
Influencing Implementation of
Occupational Safety and Health
Management Systems by Enterprises
in Poland. Human Factors and
Ergonomics in Manufacturing, 16
(3), 255-267.
27. Wright, M., Antonellli, A.,
Norton Doyle, J., Bendig, M., &
Genna, R. (2005). An evidence
based evaluation of how best to
secure compliance with health and
safety law. HSE Research Report
influences on health and safety attitudes and behaviour, including
the degree of formality/informality in managements’ approach,
incidence of management training, values and behavioural traits
of managers and employees. The authors argue that resource
constraints on SMEs need to be understood. Small businesses
have limited resources to invest in health and safety management,
including time, competency, information, training and plant and
equipment.
The tensions that arise between regulatory enforcement and
understanding the pressures faced by small businesses are also
important.
values.
A questionnaire study conducted within Polish companies (40
enterprises from various branches of manufacturing) looking at
factors influencing decisions on OHS Management Systems (MS)
implementation. Four groups of professionals who participated in
the decision-making process related to OHS MS were
interviewed, namely, 1) the most senior managers, 2)
representatives of top management for implementation and
management of OHS MS, 3) safety and health managers and 4)
workers’ safety representatives.
Significant internal factors were top managers’ aim to improve
management of the enterprise, top managers’ care of the safety
and health of employees and participation of safety and health
managers in training courses in OSH Management. Of medium
significance were managers’ expectations concerning a reduction
in the number of occupational accidents and diseases, economic
benefits and participation in training. Of least significance was
sudden deterioration of working conditions and workers
expectations of an improvement in their working conditions.
39 exploratory discussions were run with employers and key
stakeholders, such as, CBI and trade associations from a range of
sectors and sizes of organizations in the UK. Two different
surveys were developed to assess what motivates organizations to
comply with health and safety; one for employers and one for
intermediaries.
53
Business pressures.
G
Moral case (care of
employees).
Likely cultural differences as
this research was conducted in
Poland.
Research highlights the need
to consider the maturity of
management systems for
OHS.
Knowledge/training on OSH
management.
Reducing accidents/incidents
and economic benefits had
less impact.
Deterioration in working
conditions and workers’
expectations to improve this
had even less impact.
Regulation/fear of
enforcement.
Reputation.
Moral case (especially
G
UK based research that
provides an up to date review
of research on factors
motivating compliance with
health and safety.
334.
Findings showed that motivational factors remained largely
unchanged from previous research in the area hence
enforcement/regulation, risk to reputation, the moral case
(especially in SMEs), avoiding the cost of accidents and business
incentives were documented. Understanding and awareness
remain key precursors to compliance. The authors also reported,
however, that financial incentives provided by insurance
premiums had become more influential.
The research showed that a ‘one size fits all’ approach is unlikely
to work and no single “lever” is likely to be effective for all
organizations.
SMEs).
“Bounded rationality” (Hopkins, 1999) is also an important
influence, where managers lack access to all relevant information
leading to faulty decision making on their part. Furthermore,
thinking about the costs of complying with health and safety
legislation over too short a period of time makes the costs of
compliance seem a financial burden, leading to flawed thinking
“Institutionalized irrationality.”
Cost-benefit analysis of
compliance.
28. Smallman, C. & John, G.
(2001). British directors perspectives
on the impact of health and safety on
corporate performance. Safety
Science, 38, 227-239.
A UK qualitative study in which eight business leaders were
interviewed, four of which belonged to manufacturing, two
worked in construction, one in services and one in logistics. The
interview covered directors’ attitudes to, and priorities in, health
and safety and company practices in health and safety at a senior
level.
Findings highlight the importance of corporate reputation in
influencing director decision-making and behaviour.
Furthermore, the higher up the corporate chain of command, the
less in touch managers were with OHS.
Corporate reputation.
G
Serves as a reminder to be
mindful of the corporate
culture/hierarchy in this
research when contacting
companies to participate.
29. Thompson, R.C., Hilton, T. F., &
Witt, L. A. (1998). Where the Safety
Rubber Meets the Shop Floor: A
Confirmatory Model of Management
Influence on Workplace Safety.
A study (case study) carried out in the USA in which a safety
climate survey was administered to members of a Federal
Aviation Logistics Centre. A model is presented that links
management support, organizational climate and self reported
safety outcomes, based upon longitudinal data collected over
Clarity of role with regards to
safety management.
G
Confirms that there is a lack of
research into management
behaviour and safety.
54
Cost of accidents/incidents.
Financial incentives
(insurance premiums).
Understanding and
awareness.
Access to relevant
information.
Understanding of their
(managers) influence over
The survey is included in the
Journal of Safety Research, 29(1),
15-24.
30. Wright, M. S. (1998). Factors
Motivating proactive health and
safety management. HSE Contract
three years.
The authors claim that, “Without some dynamic model to indicate
how their organization’s work climate relates to safety, it is
difficult for managers to understand their role in creating and
maintaining a safe workplace. This might help explain why many
managers express concern that despite stated support for their
safety programmes, workplace safety does not seem to improve.”
safety climate and
performance.
UK-wide research, including SMEs, suggests that two main
factors in the UK motivate organizations to initiate health and
safety improvements, namely, (1) the fear of loss of corporate
credibility and (2) a belief that it is necessary and morally correct
to comply with health and safety regulations. Other factors were
also found to have an important influence on management
motivation by moderating management’s propensity to act. For
example, the experience of serious incidents or contact with a
regulator can motivate increased levels of safety management and
advice from professional trained health and safety advisors can
overcome ingrained management attitudes that certain hazards are
“part of the job”.
Authors also cite American research that suggests the need to
reduce the costs of ill health and injury as a motivating factor. A
number of UK studies have found, however, that the perception
that health and safety improvements are a ‘cost’ rather than an
‘investment’ is a significant de-motivating factor amongst
management. This research highlights the need to neutralise cost
concerns by demonstrating the commercial benefits of health and
safety improvements to directors/managers.
Main factors: Corporate
reputation and moral case.
55
Appendix, which could be
adapted for use in this
research.
Importantly, this paper points
to the need to make a clear
distinction between managers
and supervisors as they appear
to have different spheres of
influence. Managers influence
safety by influencing the
politics of communication,
whereas supervisors influence
the fairness by which they
interact with employees.
Moderators include:
Experience of
accidents/incidents and
advice from trained
professionals, need to reduce
the costs of ill health and
injury.
Concerns about cost of
improvements.
G
In Appendix A of the paper is
a copy of ‘Attitudes towards
Noise as an Occupational
hazard’. Noise is seen as
different because it is not life
threatening, there is no
immediate evidence of
damage, and no lost time.
Clearly, if managers adopt this
way of thinking, it will impact
the adoption of noise controls.
The research needs to explore
employer attitudes towards
noise as a risk.
31. O’Dea, A., & Flin, R. (2003).
The role of managerial leadership in
determining workplace safety
outcomes. HSE Research Report
044.
A review of the theoretical and empirical literature that
examines the role of managerial leadership (at three levels i.e.
senior managers, middle level managers and supervisors) in
determining organisational safety outcomes.
Factors associated with positive safety outcomes at the different
levels of leadership include:

32. Rabin, S., Feiner, M., Shaham,
J., Yekutieli, D., & Ribak, J. (1998).
Senior management - Safety is viewed as integral to
competitiveness and profitability, perceived the importance of
statutory compliance, adopt transformational leadership/show
charisma and show commitment to developing trusting
relationships with subordinates.
Middle management - Resources given to safety, safety
programme, policies and procedures in place, visibility at the
worksite, informal communications with workers, retaining
personal responsibility for safety, work planning and
scheduling, safety practices intrinsic to production,
decentralisation of power, decisiveness, transformational
leadership style, co-operation and informal contact between
workers and management, multiple communication vehicles,
open door policy by management, feedback to employees,
appreciating employees, demonstrating concern for
employees, health promotion policies and practices.
Supervisors - Openness on safety issues, initiating safety
discussions, providing feedback, fairness, regular safety
meetings with workers, involvement in safety programs and
training, involvement in inspections and investigations,
supervisory influence in decision making, supervisory
control, participative style, emphasis on importance of team
work, valuing the workgroup, recognition of safety as major
part of the job and trust in subordinates.
Research conducted in Israel involving 460 workers in three
industrial sites, one of which is in food manufacturing and the
56
Senior level managers:
Attitudes towards safety,
compliance with regulations,
leadership style and
management commitment.
G
Middle-level managers:
Resources, safety
culture/climate, attitudes and
commitment towards safety,
acceptance of responsibility
for safety, /power, leadership
style and relationships with
workers (including
supervisors).
Highlights that findings
regarding influences on
behaviour may vary according
to managerial level. Factors
that emerged as important for
all three levels of leadership
were attitudes, style, and
commitment. Factors that
emerged at both management
and supervisory levels were
attitudes, commitment,
responsibility, control and
style.
Supervisors: Personality
characteristics (e.g. openness,
trust in others), attitudes
towards safety, commitment,
control, leadership style,
responsibility for safety.
Self-efficacy.
Confirms the need to be aware
of whom the research is
directed at due to the
difference noted between
managers and direct
supervisors. Also important is
the relationship between
managers and supervisors.
G
supervisors in health and
Impact of Managers’ Personal
Determinants in Notifying Workplace
Hazards. American Journal of
Industrial Medicine, 33, 493-500
others in high-tech telecoms manufacturing. This paper
examines managers’ personal determinants and notification of
work hazards in a sample of 106 managers and 460 workers.
Results suggest that managers rely on personal modes of
communications with immediate supervisors considered as the
most important person in notification. Managers’ sense of selfefficacy (self-confidence), and positive expectation of notification
positively predicted their behaviour (i.e. to notify supervisors).
Outcome denial and coping by distancing themselves were seen
as negative.
Expectation of outcome of
behaviour (more likely to
enact if positive).
33. Hofman, D. A., & Morgeson, F.
P. (1999). Safety-Related Behaviour
as a Social Exchange: The role of
Perceived Organizational Support
and Leader-Member Exchange.
Journal of Applied Psychology,
84(2), 286-296.
A study conducted in the USA in a manufacturing facility that
produces commercial heating and air conditioning systems. Data
were collected from a cross section of 49 supervisor group
leader dyads. Results suggest that perceived organizational
support was significantly related to safety communication and
leader-member exchange was significantly related to safety
communication, safety commitment, and accidents.
These findings highlight the influence that organizationally
based social exchanges may have on safety.
“It appears that the support organizations show for their
employees and the quality of exchange relationships with
supervisors are associated with safety-related communication.
This safety-related communication is significantly related to
safety commitment, which ultimately is predictive of accidents.”
Relationships with other
leaders/managers/
Supervisors and employees.
34. Lingard, H., & Holmes, N.
(2001). Understandings of
occupational health and safety risk
control in small business construction
firms: Barriers to implementing
technological controls. Construction
Management and Economics, 19,
217-226.
A qualitative study (case study of 5 small businesses, 15
participants) carried out in the Australian construction industry
to understand OHS risk control amongst a sample of small
businesses. They looked at one risk, namely, skin disease, which
represented a long-term health effect.
Results showed a fatalistic resignation to OHS risks being an
unavoidable part of the job, which leads to an emphasis being
placed on individual rather than technological controls for OHS
risks (representing an internal locus of control).
Small businesses are often characterized by poor management
Attitudes towards
occupational health risks with
latency period between cause
and symptom onset.
57
safety performance.
Based on questionnaire
research, yet may have
benefited more using a mixed
methods approach.
G
Limitations with sample size,
but safety communication and
social exchange needs to be
considered within the
research.
H
Points again to the variation in
attitudes towards health as
opposed to safety risks.
Safety culture/climate and
organisational support
(including resources).
Locus of control.
Management skills, style and
communication skills.
As a possible aside, the
research should consider the
‘gender’ of managers as
“males have been found to be
more resistant to participation
in programmes designed to
skills (Johns et al., 1989) and authoritarian management styles
(Orlandi, 1986; Witte, 1993). They are poorer than larger
organisations at implementing OHS programmes (Hollander and
Lengerman, 1988; Fielding and Piserchia, 1989; Eakins, 1992;
Holmes, 1995; Mayhew, 1995) and are characterised by poor
communication between employees and management on OHS
(Williams, 1991; Rundmo, 1994).
Knowledge and ability to
implement health and safety
programmes.
35. Sandberg, T., & Conner, M.
(2008). Anticipated regret as an
additional predictor in the theory of
planned behaviour: A meta-analysis.
British Journal of Social Psychology,
47, 589-606.
The authors present a meta-analysis of the theory of planned
behaviour (TPB) studies to determine the additive effects of
anticipated regret (AR) both to the prediction of ‘intention’ and to
the direct impact on ‘behaviour’.
Evidence suggests that the TPB does not take into account
affective processes despite evidence that emotional outcomes are
commonly factored into decision-making. Regret is an example
of this.
“Regret itself is a negative, cognitive-based emotion that is
experienced when we realize or imagine that the present situation
could have been better had we acted differently. However, it is
also possible to anticipate regret pre-behaviourally and thus
avoid actually experiencing this unpleasant emotion” (Simonson,
1992).
Affective (emotional) and
cognitive attitudes that affect
decision-making. Affective
attitudes includes ‘regret’ (e.g.
from not acting differently in
the past, perhaps to avoid an
accident). Ties in with
‘experience of accidents/ill
health and enforcement’.
G
Highlights the need for the
research to consider the
difference between affective
and cognitive aspects of
attitudes. Measures of attitude
should incorporate items that
tap into the evaluative aspect
(instrumental measures such
as good-bad) and affective
outcomes (experiential
measures such as pleasantunpleasant).
36. Foster, G. (1996). Factors
influencing the implementation of
noise control programs in industry.
Journal of Occupational Health
Safety, 12(4), 471-475.
This is a follow up survey of 14 Australian workplaces to
identify the factors, which encouraged or discouraged the
companies involved to implement noise control treatments. Half
of the industries surveyed were metal fabrication processes,
printing, aluminium casting, pharmaceuticals and
petrochemical plants.
Factors that encouraged the implementation of noise controls
included:
Knowledge and motivation
to act.
N
Provides some useful
information about the
importance of a motivated
manager/OHS officer and a
positive attitude to noise
control by management.
Well-informed and motivated management.
The presence of a noise policy plan and a knowledgeable and
motivated person to drive the noise control program.
Ease and practicability of implementing engineering controls.
58
Perceived cost, ease and
practicality of implementing
noise controls.
Knowledge of controls.
change workplace health and
safety culture (Spilman, 1988,
cited in this paper)”.
How informed management is
regarding the benefits of noise
control is also important to
assess.
37. Hughson, G. W., Mulholland, R.
E. & Cowie, H.A. (2002).
Behavioural studies of people’s
attitudes to wearing hearing
protection and how these might be
changed. HSE Research Report 028.
The cost of noise control.
The provision of engineering detail for noise control in the
survey report.
UK cross sectional research involving SMEs and large companies
to examine the various factors influencing workers’ attitudes and
behaviours towards hearing protection.
Findings showed that the Noise at Work Regulations (1989) is
generally considered as too complex and confusion over when
and where hearing protection should be worn was evident. The
frequently changing nature of work in many SMEs who
participated in the research, meant that managers struggled to
keep up-to-date with their noise assessments. As such, large work
zones were marked as hearing protection zones, which were often
ignored by workers, as they were aware that this was irrelevant in
some areas and at certain times of the day. Smaller companies
rely more on hearing protection than other measures to reduce
noise exposure.
Another important influence on management behaviour within the
construction sector that emerged from this research is external
pressures exerted by principle contractors and planning
supervisors.
It was also clear that many companies that have a noise problem
do not always recognise the significance of the problem. Senior
management commitment increases likelihood that employees
will commit to any controls implemented.
59
Understanding of noise
regulations.
External influences (e.g.
changing nature of work,
pressure from suppliers and
contractors).
Understanding of the
seriousness of the hazard
(noise), Health effects of
noise at work and impact on
the business (short and longterm).
N
Need to assess understanding
of the significance of noise as
an occupational hazard and
measure external influences
that may act as barriers or
facilitators to implementation
of noise controls.
7.2
APPENDIX 2: TABLE OF EXCLUDED ARTICLES
Paper/Article Reference
Reason for Exclusion
1. Arezes, P. M., & Miguel, A. S. (2005).
Individual Perception of Noise Exposure and Hearing
Protection in Industry. Human Factors, 47 (4), 683692.
2. Arezes, P. M., & Sergio Miguel, A. (2005).
Hearing protection use in industry: The role of risk
perception. Safety Science, 43, 253-267.
3. Barrett, G. A. (2000). Management’s Impact on
Behavioural Safety. Professional Safety. March
Edition, 26-28.
4. Becker, M. H. (1974). The Health Belief Model
and Sick Role Behaviour.
Health Education
Monographs, 2 (4), 82-92.
5. Birkner, J. (2005). Noise, Under Control.
Occupational Health and Safety, June Edition,
http://ohsonline.com/Articles/2005/06/Noise-UnderControl.aspx
6. Casali, J. G. (2006). Sound and noise. In
Salvendy, G. (Ed). Handbook of human factors and
ergonomics, 612-642.
7. Cheung, C. (2004). Organizational influence on
working people’s occupational noise protection in
Hong Kong. Journal of Safety Research, 35, 465475.
8. Clarke, S., & Ward, K. (2006). The role of leader
influence tactics and safety climate in engaging
employees’ safety participation.
Risk Analysis,
26(5), 1175-1185.
9. Cooke, R., & Sheeran, P. (2004). Moderation of
cognition-intention
and
cognition-behaviour
relations: A meta-analysis of properties of variables
from the theory of planned behaviour. British
Journal of Social Psychology, 43, 159-186.
10. DeJoy, D. M. (1996). Theoretical models of
health behavior and workplace self-protective
behavior. Journal of Safety Research, 27(2), 61-72.
11. Dejoy, D. M. (2005). Behaviour change versus
culture change: Divergent approaches to managing
workplace safety. Safety Science, 43, 105-129.
12. Falconer, L. (1998). A review of fuzzy
decision-making and its application to managing
occupational risks. Journal of the Institution of
Occupational Safety and Health, 2(1), 29-36.
13. Finnish Institute of Occupational Health. (1998).
International Symposium from Protection to
Concerns the influences on employee rather than
management behaviour.
Focuses on what influences employee behaviour.
Talks about the features of safety systems and how to
improve behavioural processes rather than management
behaviour.
Over ten year old paper and not noise research.
General information on noise and control measures.
Noise engineering rather than human factors.
Useful for supporting why this research focuses on
managers rather than employees, but the main focus
concerns influences on employees’ behaviour.
Looks at how managers/leaders can influence employees
behaviour rather than what influences their behaviour.
Outdated meta-analysis / review.
Over 10-year old review and focuses on self-protective
behaviour.
Discusses approaches to safety rather than the factors that
influence the management of safety or managers’
behaviour. Over a three-year-old review.
Over 10-year old paper.
Papers and abstracts are over 10 years old.
60
Promotion: Occupational Health and Safety in
Small-scale Enterprises. Helsinki.
14. Handley, L. (2008). Taking the lead on Safety. Aimed more at HSE as the article details measures to take
Construction News, April Edition, Issue 7063.
to improve safety management (e.g. target middle
management also), rather than looking at influences on
behaviour.
15. Hofmann, D. A., & Stetzer, A. (1996). A cross- Over 10 years old and focuses on employees’ safety
level investigation of factors influencing unsafe behaviour/team processes rather than management
behaviours and accidents. Personnel Psychology, 49, behaviour.
307-339.
16. Krause, T. R. (2007). The Effective Safety Describes the ideal attributes of a successful safety leader
Leader:
Personality, Values and Emotional or leadership style i.e. how they influence safety not what
influences them.
Commitment. Occupational Hazards, 69 (9), 24.
17. Krause, T. R. (2007). The Effective Safety Provides background information on leadership styles and
Leader:
Leadership Style and Best Practices. best practices to help understand effective safety
Occupational Hazards, 69 (12), 19.
leadership in concrete behavioural terms, does not detail
what influences actual behaviour.
18. Lawton, R., Conner, M., & Parker, D. (2007). Non-occupational research/practice.
Beyond cognition: Predicting health risk behaviors
from instrumental and affective beliefs. Health
Psychology, 26(3), 259-267.
19. Lutman, M. E., Davis, A. C., & Ferguson, M. A. Looks at the impact of the regulations rather than the
(2008).
Epidemiological evidence for the management of noise at work.
effectiveness of the noise at work regulations. HSE
Report 669.
20. Malchaire, J. (2000). Strategy for prevention Talks about a strategy for controlling noise rather than
and control of the risks due to noise. Occupational what influences behaviour.
Environmental Medicine, 57, 361-369.
21. Meyer, J.D., Chen, Y., McDonald, J.C., & Talks about the prevalence of hearing loss and
Cherry, N.M. (2002). Surveillance for work-related surveillance schemes.
hearing loss in the UK: OSSA and OPRA 1997-2000.
Occupational Medicine, 52 (2), 75-79.
22. Michaelis, C., & McGuire, M. (2006). Scoping Discusses influencing farmers via the supply chain, which
study determining the potential of engaging is beyond the scope of this research.
stakeholders in the food supply chain to support and
influence farmers to promote health and safety. HSE
23. Nardo, M. (2004). Noise pollution: an overview Looks at noise level, auditory effects and types of noise
of management strategies. International Journal of management.
Environmental Technology and Management, 4 (4),
300-322.
24. Niskanen, J. and Anttonen, H. (2001). Ways to Concerns noise measurement and prevalence.
promote a noise control programme. Scandinavian
Audiology, 30 (52), 174-176.
25.
O’Beirne, M.
(2008).
HSE’s External Focuses on an evaluation of an intervention (i.e.
Communication Campaigns (2004-08):
Lessons communication campaigns).
learned and suggestions for future activities. Internal
HSE Paper.
26. O’Regan, S., Tyers, C., Hill, D., & Gordon- Concerns
employee
behaviour
rather
than
Dseagu, V. (2007). Taking risks with asbestos: director/manager behaviour.
What influences behaviour of maintenance workers?
HSE Research Report 558.
61
27. Patel, D. S., Witte, K., Zuckerman, C., MurrayJohnson, L., Orrego, V., Maxfield, A. M., meadowsHogan, S., Tisdale, J., & Thimons, E. D. (2001).
Understanding barriers to preventative health actions
for occupational noise-induced hearing loss. Journal
of Health Communication, 6, 155-168.
28. Rivis, A., & Sheeran, P. (2003). Descriptive
norms as an additional predictor in the theory of
planned behaviour: A meta-analysis. Current
Psychology: Developmental, Learning, Personality,
Social, 22(3), 218-233.
29. Scott Geller, E. (2000). 10 Leadership Qualities
for a Total Safety Culture. Professional Safety, May
Edition, 38-41.
30. Smith, B. J., Peters, R. J., & Owen, S. (1996).
Acoustics and noise control (2nd Ed.). Addison
Wesley Longman Ltd: Essex, England.
31. Stokols, D., McMahan, S., Clitheroe Jr., H.C. &
Wells, M. (2001). Enhancing corporate compliance
with worksite safety and health legislation. Journal
of Safety Research, 32, 441-463.
32. Tafalla, R. J., & Evans, G. W. (1997). Noise,
physiology, and human performance: The potential
role of effort. Journal of Occupational Health
Psychology, 2(2), 148-155.
33. Tomas, J. M., Melia, J. L., & Oliver, A. (1999).
A cross validation of a structural equation model of
accidents:
Organisational and psychological
variables as predictors of work safety. Work and
Stress, 13(1), 49-58.
34. Topf, M. D. (2000). Including Leadership in the
Safety Process. Occupational Hazards, 62 (3), 5758.
35. Vlek, C. (2005). “Could we all be a little more
quiet, please?” A behavioural science commentary
on research for a quieter Europe in 2020. Noise and
Health, 26, 59-70.
36. Williams, W., & Purdy, S. (2007). Factors in
reducing occupational noise exposure. Journal of
Occupational Health and Safety, 23(2), 165-177.
37. Williams, W., Purdy, S. C., Storey, L., Nakhla,
M., & Boon, G. (2007). Towards more effective
methods for changing perceptions of noise in the
workplace. Safety Science, 45, 431-437.
38. Wright. M., Streatfeild, C., Williams, N.,
Solanki, A., Beardwell, C., Sant, A., Caldwell. H., &
Yeo, I. (2008). Review of targeted initiatives in the
manufacturing sector. HSE Research Report 620.
39. Yeomans, L. & Patel, J. (2008). Feedback on
the Hand-Arm Vibration Control Campaign: Views
of Inspectors. HSL Report NV/07/21.
Concerns influences on employee behaviour rather than
management.
Over three-year old meta-analysis / review that addresses
theory rather than an occupational based piece of
research/practice.
Over five year old paper on leadership qualities.
A book on noise engineering rather than human factor
issues.
No mentioned of individual management behaviour. The
paper looks into the effectiveness of a training
intervention on corporate compliance with health and
safety legislation.
Looks at noise and employee behaviour.
Looks into accidents and structural equation modelling
rather than management behaviour.
Advice on how to improve safety within organisations
rather and what leaders should do rather than what
influences them.
Concerns noise emissions and the effects of noise.
Focuses on employee behaviour.
Looks at the effectiveness of a training intervention to
raise awareness of noise, rather than influences on
management behaviour.
A review of the initiatives taken rather than examining
influences on management behaviour.
Focuses on Inspectors views of the campaign rather than
influences of management behaviour.
62
7.3
APPENDIX 3: FACTOR GROUPINGS
Source (Paper / Article / Book
Indication of Amount of Influence
number in the Data Extraction
(Green = Significant; Red = Unclear;
Table – See Appendix 2)
Blue = Not significant)
1.
Economic / Financial [Ill 1, 2, 5, 10, 18, 21, 24, 25, 27, Mixed findings regarding extent of
health/injury costs to the business; 31.
influence. Not all research has considered
insurance premiums; personal injury
economic benefits to be a key influence on
scheme; current tax situation (OH as a
employers’ behaviour, but the majority of
benefit than investment in human
research shows this as a significant driver
capital); winning contracts; belief that
(particularly in the USA due to differences
H&S
saves
money;
business
in insurance and compensation).
survival/pressures;
competitiveness;
profitability; corporate governance
One UK-based study showed that financial
requirement].
incentives provided by insurance premiums
had become more influential in recent years.
(Business)
2. Corporate Credibility/ Reputation 1, 9, 10, 14, 18, 24, 27, 28, 30. Studies generally show this to have a
significant influence on management
behaviour.
(Business)
Found to have a significant influence, but
3. Experience of a Serious Accident 2, 30, 35.
implicated more in terms of a moderating
and/or
Enforcement
[Emotional
variable.
influence
–
regret;
financial
repercussion].
Factor
(Overarching Factor)
(Organisational/Cultural & Business)
4. Customer Pressure
1.
Not a significant motivator.
(Business)
63
Other Notes
‘Business survival’ is more influential
for SMEs than larger organisations.
May vary by industry (e.g. more
influential in high hazard industries).
Previous experience of a serious
accident has been implicated as a
moderator of the impact of financial
drivers on decision-making.
1, 7, 9, 10, 18, 24, 27, 31.
5. Compliance with Legislation
[Motivated to comply with the law; fear
of prosecution]
Significant influence, especially if company One study looking at different levels
has been previously prosecuted.
of management found that this factor
only influenced the behaviour of
senior-level management.
(Legal)
6. Information and Communications 9, 13, 19, 20, 27, 30.
[HSE guidance; perception of HSE;
advice/guidance from intermediaries;
general information source(s) used for
noise; trust in information source(s)
used; access to relevant information;
advice from trained H&S advisors or
HSE Inspectors].
Significant influence on managers’ decision External guidance (non-HSE e.g.
making.
suppliers, consultants) and perception
of HSE appears to have greater
influence on SMEs.
(External)
7.
Values and Beliefs [Ethical 1, 5, 9, 10, 16, 24, 26, 27, 30, Significant influence, particularly for SMEs.
A key merging belief is managers’
principles; human compassion; sense of 32.
compassion and general concern for the well
duty/responsibility; general concern;
being of their employees.
moral
beliefs;
integrity/honesty;
fairness;
time
management
&
prioritisation; beliefs that outcome will
be positive].
Also, Incorporates
management style.
Management style may be partly
influenced by values and beliefs. In
this research questions should concern
what influences style (i.e. a
behaviour) rather than the type of
style adopted.
Some evidence
suggests that a positive culture can be
created regardless of managerial style.
(Organisational/Cultural & Personal)
8.
Knowledge, Awareness and 1, 7, 8, 10, 11, 13, 14, 17, 19, Significant precursor to behaviour as it
Understanding [Technical knowledge 20, 21, 26, 27, 29, 36, 37.
seems to be critical in the risk appraisal
of noise - know what they need to know
process.
for their business; noise legislation;
noise risks; health effects of noise;
64
Helps to build a picture of managers’
‘mental models’.
Knowledge and understanding seem
to have greater influence over SMEs
effectiveness and use of noise controls;
H&S systems & procedures; business
benefits of compliance (short & longterm) & good H&S; potential effects of
a poor safety culture; knowledge of
their own influence over safety
climate/culture].
than larger organisations.
(Personal)
9. Risk Perception [Long-term vs. 8, 17, 18, 22, 23, 34.
short-term risks; whether noise is
considered
controllable
or
not;
Individual biases/Locus of Control – It
won’t happen to me, attributing worker
behaviour to internal factors (e.g.
carelessness, lack of concentration); &
own behaviour to situational factors].
A significant motivator of management Plays an important role in motivation
behaviour, influenced heavily by knowledge to act (high risk perception results in
of hazards.
intrinsic motivation to act, low risk
perception
requires
external
motivators).
(Personal)
10. Competence [Skills to manage 10, 21.
noise risks; carry out risk assessments
& determine necessary controls].
A few studies have reported this as
potentially influencing managers’ behaviour.
No conclusive evidence.
(Personal)
1, 4, 8, 13, 14, 21, 23, 27, 30, Appears to act as a moderating variable, Has greater influence on SMEs (OH
11. Capability/Cost of
forming part of managers’ cost-benefit is viewed as ‘too costly’ or ‘too
Making Engineering Improvements 36.
complex/an administrative burden’).
appraisal.
[Considered ‘too costly, poor access to
Seems to be more influential for UK
services, misconception of the cost of
companies than ‘cost’ in general (financial
noise controls; ease of introduction of
motivators).
controls; controlling the noise risk is
65
considered ‘too difficult’].
(Business)
12. Perceived/Actual Control [Level 6, 31.
of authority/influence over workers].
A number of UK studies have shown that the
‘cost’ of making H&S improvements rather
than ‘investment’ is a significant demotivating factor for management.
A significant moderator of the relationship Important at lower-level management
between intention and behaviour.
and supervisory levels rather than at
senior management levels.
(Organisational/Cultural)
13. Self-Efficacy / Confidence
(Personal)
6, 8, 32.
A significant moderator of the relationship
between intention/expectation of behavioural
outcomes and behaviour.
14. Safety Climate/Culture [Work 6, 7, 8, 12, 15, 17, 29, 31, 33, A significant influence on behaviour
(possibly through commitment) affecting all
environment – ‘the way we do things 36.
levels of management. Organisations with a
around here’, social norms; social
positive safety climate seem more likely to
reaction; habit formation; safety
implement noise controls.
consciousness/perceptions of safety
climate; type of relationships formed –
friendly vs. assertive; relationships with
other
leaders
&
employees;
organisational
policies,
practices,
procedures; defined responsibilities for
H&S/role clarity].
15. Attitudes Towards Health and 2, 3, 7, 8, 10, 11, 14, 24, 26, Significant influence on behavioural
Safety [H&S commitment/personal 31, 34, 35, 37.
intentions,
which
ultimately
affect
interest, fatalism (‘risks are part of the
behaviour.
job’), tolerance of rule violations,
worry and emotion (e.g. regret or
Most influential seems to be senior
anticipating regret), powerlessness,
management commitment and involvement,
H&S priority (e.g. over production),
followed by fatalism, safety priority and risk
66
Leadership at the top influences safety
culture, hence the attitudes and
behaviours
of
senior-level
management are likely to influence
those of lower-level management.
A pertinent issue for noise is that it is
not taken seriously and can be
regarded as inevitable.
Acceptance of responsibility appears
to be more influential for supervisors.
Affective and cognitive attitudes both
play a role.
mastery and risk awareness; attitudes
towards risks (e.g. complacency);
acceptance of responsibility].
awareness.
Productivity vs. safety appears to be more
influential for SMEs.
16. Resources [Time & effort, money, 3, 7, 11,12, 14, 17, 21, 23, 25, Influence managers’ ability to carry out
staff (workload factors), safety 30, 31, 33.
necessary steps to control hazards
equipment; availability of controls].
(especially middle management and
supervisors).
Particularly influential for SMEs.
17.
Personality/Characteristics 7, 11, 12, 31.
[Flexible, innovative, principled; risk
taking
propensity;
charisma
/
transformational style 58 ; openness &
trust in others].
A key barrier to implementing H&S
controls.
An
indication
of
level
of
organisational support to lower-level
management.
Unclear (mixed), but likely to have some
influence, although people can behave in a
‘less preferred’ way that suits the
environment that they are working in. As
such, personality characteristics may be less
influential than other factors.
(Personal)
18. Demographics [Position/role - 10, 34.
who reports to and who reports to the;
role clarity; gender; industry sector;
type
of
operation;
accident/incident/illness rates].
Some evidence to suggest demographics Likely to link in with control, role
influence behaviour at director level and that clarity and cultural influences.
gender may influence behaviour (less
certain).
(Organisational/Cultural & Personal)
19.
Employee Attitudes & 11, 12, 14, 26.
Motivation [Level of subordinate
cooperation, including supervisors;
58
Some evidence that influences management May be more influential in SMEs as
behaviour, but one study found employee managers/directors have more direct
expectations of improvements to be less contact with workers than larger
See Glossary.
67
workability with controls; comfort;
expectations of improvement].
influential than managers’ own expectations, organisations.
economic
benefits,
management
commitment and training.
20. Environmental [Changing nature 26, 37.
of work; pressure from suppliers &
contractors].
Seems to influence management, but amount May be more influential for SMEs.
of influence is uncertain and few papers
looked at this.
(External)
68
7.4
APPENDIX 4: QUALITY RATINGS
Quality Rating
S = Strong;
M = Moderate;
W = Weak
Rationale
1. Economic /
Financial
M
7/10 papers/books report as a significant influence (generally
consistent findings).
4/10 cross sectional studies, 1/10 case study, 3/10 opinion-based
papers/books and 2/10 literature reviews.
2. Corporate
reputation
M
7/8 papers/books report as a significant influence (generally
consistent findings).
Implications in papers that findings are consistent with previous
research.
4/8 cross sectional studies, 1/8 longitudinal study, 1/8 review,
2/8 opinion-based paper.
3. Experience of a
serious accident
and/or enforcement
M
3/3 papers report as a significant influence (consistent findings).
1/3 case study in one company, 1/3 UK-wide cross sectional
study, but 1/3 meta-analysis of multiple studies.
4. Customer
pressure
W
Only one (cross sectional) study reported this factor and found to
be non-significant.
5. Compliance with
legislation
S
8/8 papers/books report as a significant influence (consistent
findings).
Implications in papers that findings are consistent with previous
research.
3/8 cross sectional studies, 1/9 longitudinal study, 2/8 literature
reviews (one empirical), 2/8 opinion-based paper.
6. Information and
communications
M
3/6 cross sectional studies, 1/6 longitudinal study, 1/6 literature
review of 29 empirical studies, 1/6 case study.
More prominent in SME research.
7. Values and beliefs
S
10/10 papers report as a significant influence (consistent
findings).
7/10 cross sectional studies, 1/10 longitudinal, 1/10 literature
review (opinion & HSE reports), 1/10 opinion-based paper.
8. Knowledge,
awareness and
understanding
S
16/16 papers/books report as a significant influence (consistent
findings).
10/16 cross sectional studies, 2/16 case studies, 3/16 literature
reviews (one based on opinion & HSE reports, one theoretical
based on 15 studies and one review of 29 empirical studies),
1/16 opinion-based (book).
Factor
69
9. Risk perception
S
3/6 cross sectional studies, 1/6 literature review (theoretical), 1/6
opinion-based paper, 1/6 case study.
Results support PMT and SRM theories.
10. Competence
W
2/2 papers report as being a potential influence on managers’
behaviour.
1/2 cross sectional study, 1/2 literature review (opinion-based
papers and HSE reports).
No conclusive findings and a small number of empirical studies.
11. Capability/cost
of making
engineering
improvements
M
8/10 papers report as a significant influence/moderator, 2/10 as a
possible influence/moderator (generally consistent findings).
8/10 cross sectional studies, 1/10 case study, 1/10 literature
review (theoretical based on 15 studies).
12. Perceived and
actual control
S
2/2 papers report as a significant influence.
1/2 meta-analysis of 47 experimental studies, 1/2 literature
review (empirical).
Consistent with theories of attitude-behaviour relations (e.g.
TRA, TPB, MIB).
13. Selfefficacy/confidence
S
3/3 papers report as a significant influence
1/3 meta-analysis of 47 experimental studies, 1/3 literature
review (empirical), 1/3 cross sectional study.
Consistent with theories of attitude-behaviour relations (e.g.
TRA, TPB).
14. Cultural
S
8/10 papers report as a significant influence.
1/10 meta-analysis of 47 experimental studies, 5/10 cross
sectional studies, 2/10 literature reviews. (theoretical/empirical),
1/10 opinion-based paper, 1/10 case study.
Consistent findings that organisational and safety culture has a
significant influence.
Social influences are also implicit in theories of attitudebehaviour relations (e.g. TRA, TPB, PWM, MIB).
15. Attitudes
towards health and
safety
S
13/13 papers/books report as a significant influence.
1/13 meta-analysis of TPB studies, 5/13 cross sectional studies,
3/13 literature reviews (theoretical, opinion-based & HSE
reports, empirical), 3/13 case studies, 1/13 opinion-based (book).
Consistent findings that attitudes influence intentions/behaviour
from, mostly, correlational studies.
Findings support theories of attitude-behaviour relations (e.g.
TRA).
16. Resources
M
11/12 papers report as a significant barrier, 1/12 as a potential
barrier (but based in Shropshire only) - Generally consistent
findings.
1/12 case study, 9/12 cross sectional studies, 1/12 opinion-based
paper, 1/12 literature review (empirical).
70
17. Personality
characteristics
W
Mixed results/inconsistent evidence - 2/4 papers report as a
significant, 1/4 as potentially significant, 1/4 as less influential
than the culture of an organisation.
2/4 cross sectional studies, 1/4 opinion-based paper, 1/4
literature review (empirical).
18. Demographic
characteristics
W
Unclear findings as to strength of influence with few papers
reporting as an influential factor.
1/2 papers report as a significant, 1/2 as potentially significant.
1/2 case study, 1/2 literature review (opinion & HSE reports).
19. Employee
attitudes and
motivation
M
Seems to have a significant influence (generally consistent
findings), but other factors (e.g. commitment, economic benefits)
may be more influential.
1/4 opinion-based paper, 3/4 cross sectional studies.
20. Environmental
W
Very limited studies - only two papers (cross sectional studies).
One paper reported as having a significant influence, but the
other as being less significant in comparison with management
commitment and expectations, moral beliefs, knowledge of OHS
and economic benefits.
71
Published by the Health and Safety Executive
04/11
Health and Safety
Executive
This research addressed three research questions:
(1) What factors influence employers’ decisions and
practices in controlling noise risks? (2) What is the
relative importance of these factors? and; (3) How do
these factors vary between high and low performing
companies? A mixed methods approach was adopted
in which 215 questionnaires were completed and 15
in-depth interviews carried out with manufacturing
dutyholders.
Three factors were found to influence noise
management: (i) managers’ own knowledge/awareness
of noise risks and associated controls, (ii) the health
and safety culture of the company and (iii) its size.
Health and safety culture was found to have the
greatest influence, indicating that cultural changes
could generate the most improvements. Managers
generally underestimated the significance of noise as
an occupational health risk; a critical knowledge gap
was understanding what controls exist and would
work in practice. The size of the company influenced
the approach taken with smaller companies showing
increased likelihood of reduced quality in noise
management (ie low performance). Small companies, or
low performers, were more constrained by health and
safety resources than their high performing (generally
large) counterparts. A preoccupation with measuring
noise rather than implementing the right solutions was
apparent amongst low performers, creating a barrier to
going beyond personal hearing protection. Future noise
interventions should address these factors and not
underestimate the potential influence of culture change.
This report and the work it describes were funded by
the Health and Safety Executive (HSE). Its contents,
including any opinions and/or conclusions expressed,
are those of the authors alone and do not necessarily
reflect HSE policy.
RR866
www.hse.gov.uk

Full report

Transcripción

Documentos relacionados

Benefits - Nanometrics

Temporal Variability and Public Perception

Families receive valuable insights from second opinions