Prepared by the Health and Safety Laboratory for …to correspond with their lack of appreciation of the long-latency nature of noise. HSE HSE should consider ways of overcoming this

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



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-governmentlicence/, 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.

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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 dutyholders1 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.

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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.

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• 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, hardto-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

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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 research2.

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.

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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

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1 INTRODUCTION

1.1 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 noise3 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 (19744), 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

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http://www.hse.gov.uk/legislation/hswa.htm

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

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‘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. Knowledge, awareness and understanding (of noise risks and controls) 2. Attitudes towards health and safety (e.g. commitment, fatalism) 3. Values and beliefs (e.g. concern for the well being of employees) 4. Self-efficacy (i.e. confidence in own ability to implement noise controls) 5. Noise risk perception 6. Workplace characteristics (e.g. company size, managerial role) 7. Skills/competence (to develop noise action plans, etc) 8. Resources (i.e. time, staff, equipment, funds available) 9. Capability of making improvements (or going beyond the provision of PPE) 10. Information and communications (e.g. sources used and usefulness) 11. Compliance/legislation (i.e. fear of enforcement or civil proceedings) 12. Safety climate/culture (e.g. company values, communication channels) 13. Corporate reputation (both internally and externally) 14. Economic/financial (e.g. civil claims, insurance premiums) 15. Control (i.e. autonomy to make noise-related decisions)

Box 1 Factors identified as influential for noise management during fact-finding research

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2 METHODOLOGY

2.1 RESEARCH DESIGN

2.1.1 Overview

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 triangulation5 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 management6, 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.

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or the manager responsible for health and safety7, 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.

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most common noisy activities8), (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 validity9 of the questionnaire was tested during the pilot study and through liaison with key project stakeholders. Testing the construct validity and reliability10 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 employees11; 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

8Level 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].10Construct validity – An accurate measure of the underlying construct(s) i.e. hypothetical constructs, [28]. 11 See www.eef.org.uk

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http://www.eef.org.uk/

representing the 15 manufacturing sub-sectors was obtained through HSE’s Library and Information Services, taken from the MINT database12, 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 companies13 (with up to 49 employees14), 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 (SIC15 Code) Non-Metallic (SIC code) Basic Metals (27) Fabricated metal products (28) Machinery and equipment (29) Motor vehicles & trailers (34) Other transport equipment (35) Recycling (37.1)

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 time16. 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 sender17 (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. 13 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.

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http://www.statistics.gov.uk/

http://www.sbs.gov.uk/

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 products18). A good spread of UK geographic regions was also obtained. Nevertheless, difficulty recruiting small companies19

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 See www.statistic.gov.uk19 Lack of time was the key barrier to participation cited by employers.

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http://www.statistic.gov.uk/

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 (Research Question 2) • Quantitative: Regression

High versus low • Quantitative: Mann Whitney-U Testsperformers

• Qualitative: Thematic and(Research Question 3) 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

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(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 awareness20).

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 implemented21 and a score higher than 13 was unlikely unless higher-level controls had been implemented22. 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).21 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.

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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’ ‘Implemented noise controls’

Up to ‘13’ ‘9’ to ‘22’ Highest risk (1) High risk (2) High to medium risk (3) Medium risk (4) Medium to low risk (5) Low risk (6)

L L L M M M

M M M M M H

2.3.3 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.

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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 subthemes 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.

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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.

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Table 3 Final factor definitions and changes following correlations

Factor name Definition Change following correlations

1. Knowledge and Managers’ own knowledge and awareness awareness of technical and

organisational solutions to reduce noise, including training received

-

2. Attitudes towards Managers’ own attitudes about Includes items from original protecting workers protecting their workers from noise factors – ‘values & beliefs’, against noise risks risks (e.g. whether wearing hearing

protection alone is enough) ‘attitudes’ and ‘risk perception’

3. Self-efficacy Managers’ own beliefs/confidence in their ability to manage noise risks

One item from original ‘control’ factor added23

4. Autonomy and Whether managers are doing what Includes items from original competence 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

‘skills/competency’ factor, two items from original ‘control’ factor24 and one item from original ‘compliance with legislation’ factor25

5. Resources Time management, effort, money and staffing barriers to noise control. Includes feasibility and cost of implementing technical solutions

Includes items from original ‘capability of making improvements’ factor

6. Information and communication

Information/guidance managers’ seek/receive on noise, including information on health surveillance

Removed one item26

7. Organisational ‘The way we do things around here’, Includes two items from health and safety includes senior management original ‘reputation’ factor27

values commitment to eliminating/ minimising noise risks, reactive versus proactive culture, prioritisation of worker health

8. Business motivators Motivated by compliance, potential benefit of investment in human capital, fear of civil proceedings/prosecution

Includes two items from original ‘compliance with legislation’ factor28

9. Company size Micro (up to 10 employees) versus small (11-49), medium (50-249) and large (250 plus)

-

10. Role as Director/ owner

Director/owner versus other managerial roles

-

11. Role as Health & Safety Manager

Health and Safety manager versus other managerial roles

-

23‘The company is run by a few people. There is not much that I can do about noise issues’. 24‘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’.

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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 met29. 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 variables30 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.

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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 sources31 (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 suppliers32, 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).

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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.

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“[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.

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“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

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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 audiometry33, 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.

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(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)

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“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 decision-making, 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

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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 SPSS34 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

Model Standardised Coefficients

Beta Significance Constant - .000

Organisational H&S values .355 .000 Company size .341 .000

Knowledge and awareness .242 .000

3.2.3 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.)


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.

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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 variables35 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<.0136, 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 medium-sized 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.

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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)

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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 TWTTP37, 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.

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“… 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)

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Table 5 Summary of content analysis - high versus low performers

Cas

e

Smal

l Com

pany

Med

ium

Com

pany

Lar

ge C

ompa

ny

PPE

mai

n no

ise

cont

rol

Wea

ring

of P

PE is

man

dato

ry

Hea

ring

Prot

ectio

n D

ispe

nser

s

Trai

ning

on

corr

ect f

it of

hea

ring

prot

ectio

n pr

ovid

ed

Aud

iom

etric

test

ing

take

s pla

ce

Gen

eral

noi

se tr

aini

ng

Des

igna

ted

hear

ing

prot

ectio

n zo

nes

Sign

age

(Noi

se)

Engi

neer

ing

and

othe

r con

trols

in p

lace

Mac

hine

mai

nten

ance

pro

gram

me

in p

lace

Segr

egat

ion

of n

oisy

mac

hine

ry

Noi

se d

ampe

ners

Job

rota

tion

and

brea

ks

Mea

sure

s tas

k an

d pe

rson

bas

ed e

xpos

ure

Noi

se su

rvey

con

duct

ed

Noi

se A

ctio

n Pl

anni

ng

Noi

se h

ealth

and

safe

ty p

olic

y

Purc

hasi

ng p

olic

y co

nsid

ers n

oise

Form

al w

orke

r inv

olve

men

t

Beh

avio

ural

Cha

nge

prog

ram

me

in p

lace

Info

rmal

wor

ker i

nvol

vem

ent

Com

plia

nce/

good

hea

ring

prot

ectio

n us

e

Obs

erva

tion

and

supe

rvis

ion

of c

ontro

ls b

y du

ty h

olde

r

Job

hold

er h

as o

ther

role

s apa

rt fr

om h

ealth

and

safe

ty

Job

hold

er h

as H

& S

qua

lific

atio

ns (e

.g. N

EBO

SH)

Inte

rnal

influ

ence

s cul

ture

Use

of e

xter

nal c

onsu

ltant

Influ

ence

d by

insu

rers

Influ

ence

d by

ext

erna

l age

ncie

s with

legi

slat

ive

pow

ers n

on H

SE

Influ

ence

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38 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. 33


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 decision-making 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.

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4 DISCUSSION AND CONCLUSIONS

4.1 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

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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

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4.3

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.

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 micro-companies (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 sampled39, 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.

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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.

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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

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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 e-learning 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 organisationalwide 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

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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

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4.5

be made to the inspection process as described in section 4.4.1, including a cultural assessment tool.

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.

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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 non-response on US Navy surveys: A closer look. Military Psychology 2004; 16(4): 265276

33. Keisler, S., & Spoull, L. S. Response effects in the electronic survey. Public Opinion Quarterly 2001; 50: 402-413

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http://www.ucalgary.ca/%7Edmjacobs/phd/methods/methods.ppt

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. Quantitative psychological research. Hove, UK: Psychology Press; 2004

41. Kirkpatrick, D. L. Evaluating training programmes. San Francisco: Berrett-Koehler Publishers, Inc; 1994

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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)

Predisposing 1. Knowledge, awareness & understanding:

√ (S) √ (Influential)

- Technical noise knowledge

- Noise legislation

- Health risks/effects of noise

- Business benefits

- Effects of safety culture & own influence

√

√

√

√

√

√

X

X

X

X

2. Heath & safety attitudes: √ (S) √ (Influential) - Senior Management commitment

- Fatalism

- H&S priority

- Worry/emotional outcomes

- Complacency

√

√

√

√

√

√

X

√

X

√

3. Values & beliefs: √ (S) √ (Influential) - Concern for worker well being

- Integrity/honesty

- Positive outlook

- Time management

√

√

√

√

√

X

√

√

4. Self-efficacy √ (S) √ (Influential) 5. Risk perception: √ (S) √ (Influential)

- Locus of control

- Long-term vs. short-term risks

- Noise considered controllable

√

√

√

X

√

√

6. Personality X (W) X (Not influential) 7. Demographics: √ (W) √ (Some influence)

- Organisation size

- Company tenure

- Role of manager

- Geography

- Gender

- Industry type/operation

-Accident/incident/ill-health rates

√

X

√

X

√

√

√

√

X

√

X

X

X

X

Enabling 8. Skills/competence: √ (W) √ (Influential)

-Ability to carry out risk assessments

- Ability to develop action plans

- Ability to determine controls

- Management style/attributes

√

√

√

√

√

√

√

√

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- HSE Inspector competence X √

9. Resources √ (M) √ (Influential) 10. Capability of making improvements

√ (M) √ (Influential)

11. Control √ (S) X (Not influential) 12. Information & communications:

√ (M) √ (Influential)

- HSE information/guidance

- Perception of HSE

- Trust in sources

- Access to sources

- HSE Inspector advice

- Intermediaries

√

√

√

√

√

√

√

X

√

√

√

√

13. Compliance/legislation √ (S) √ (Some influence) 14. Experience of a serious accident &/or enforcement

√ (M) X (Not influential)

15. Customer pressure X (W) X (Not influential) 16. Environment: √ (W) X (Not influential)

- Changing nature of work

- Pressure from suppliers/ contractors

√

√

X

X

Reinforcing 17. Safety climate/culture: √ (S) √ (Influential)

- Social norms/reaction

- Relationships

- Policies, practices, procedures

√

√

√

√

√

√

18. Corporate reputation: √ (M) √ (Some influence) - Credibility of business

- To insurers

- Internal standards

√

X

X

X

√

√

19. Economic/financial: √ (M) √ (Influential) - Ill-health costs

- Insurance premiums

- Civil claims

- Long-term savings

- Winning contracts/survival

√

√

√

√

√

X

√

√

√

X

20. Employee attitudes & motivation

X (M) X (Not influential)

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 social-cognitive 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.

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Table A2.2 Included factors to be measured via questionnaire

Factor Name Elements to Measure Reason for Inclusion/Exclusion of Elements Hypothesised Effect 1. Knowledge, awareness Technical noise knowledge including: To provide insight into current knowledge levels. A predisposing factor - may & understanding 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)

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)

moderate the impact of attitudes on intention and behaviour

2. Heath & safety Senior management commitment (e.g. Important to gain an understanding of level of senior A predisposing factor -attitudes ‘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

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

likely to have a direct influence on behavioural intentions, which in turn affects behaviour

3. Values & beliefs Level of concern for the well being of the workforce, long-term outlook and time management

Closely linked with attitudes. Time management appears particularly important for SMEs

A predisposing factor -likely to have a direct influence on behavioural intentions, which in turn

51

affects behaviour

4. Self-efficacy Confidence and beliefs in own ability to implement noise controls

Essential for translating knowledge into action A predisposing factor -likely to moderate the relationship between intention and behaviour

5. Risk perception Short-term and long-term risks, whether view noise as controllable and locus of control

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)

A predisposing factor -likely to have a direct effect on managers’ intrinsic motivation to act

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?’)

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

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

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

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

A predisposing factor for which the hypothesised effect is unclear. Yet competence is likely to interact with knowledge, awareness and understanding to impact on

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motivation, involving the workforce in positive noise management attitudes towards noise and decision-making, assertiveness, subsequent implementation willingness to listen, proactive, of higher level controls approachable and leading by example

8. Resources 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….?’)

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

9. Capability of making improvements

An item to explore dutyholders’/ managers’ perception of going beyond PPE and implementing engineering/ organisational controls and health surveillance

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

10. Information and HSE information and guidance (e.g. Important to examine the different information sources An enabling factor - likely communications ‘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

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

to have an indirect effect through influencing knowledge and motivation to act

11. Compliance/ legislation

The extent that legislation and/or fear of enforcement and civil proceedings

Although the literature considered this to be a key driver for managers, Inspectors thought that civil claims had

An enabling factor - likely to directly affect behaviour

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influence noise management taken over, hence the requirement to include civil proceedings. Findings suggest some degree of influence and that legislation remains important to assess

and indirectly though creating the motivation to act (externally driven)

12. Safety climate/ culture

Focus on relationships 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

A reinforcing factor -indirectly affects behaviour through influencing knowledge, beliefs, attitudes, and risk perception

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

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)

A reinforcing factor - may moderate managers’ motivation to act and directly affect noise management behaviour

14. Economic/financial 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

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

A reinforcing factor - likely to directly affect noise management behaviour

15. Control Whether manager received any assistance when making noise management decisions and what they could successfully ask for

Although not stated as an influencing factor by Inspectors, the literature shows this as influential for lower level management (Inspectors were focused on dutyholders)

An enabling factor that appears to moderate the intention-behaviour relationship

54

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) Non-Metallic Produce (n=250) • Basic metals (SIC 27) • Fabricated metal products (SIC

28) • Machinery and equipment (SIC

29) • Motor vehicles and trailers (SIC

34) • Other transport equipment (SIC

35) • Recycling (SIC 37.10)

• 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 FOD40

divisions were unable to check whether these companies had been enforced or prosecuted over the last three years, or were currently undergoing either of these41. 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 nonmetallic 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 Field Operations Directorate 41 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

Frequency of Participating Companies Small

(0-49 employees) Medium

(50-249 employees) Large

(250+ employees) Total

Metallic: SIC 27 1 1 SIC 28 1 1 SIC 29 1 1 1 3 Non-Metallic: SIC 15 1 1 SIC 17 1 1 SIC 20 1 1 SIC 21 1 1 2 Total 6 2 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 consent42.

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 experts43 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. 43Two 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 SPSS44

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 � 1 11 - 49 � 2 50 - 249 � 3 250 plus � 4

Q2. What sector is your company in? Food & beverages � 1 Basic metals � 6 Furniture � 11

Textiles � 2 Rubber/Plastic products � 7 Recycling � 12

Wood/Products of wood � 3 Fabricated metal � 8 Other transport � 13

products equipment Pulp/Paper products � 4 Machinery & equipment � 9 Other non-metallic � 14

mineral (e.g. glass & 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 No � 2

Q5. What is your role? Tick the box that best describes your role. Owner � 1 Health & Safety Manager � 4 Works / Production � 7

Manager Director � 2 Manager � 5

Senior Manager � 3 Supervisor � 6

Q6. Is there a health and safety representative within your company? Yes � 1 No � 2 Don't know � 3

Q7. Is there a Trade Union representative within your company? Yes � 1 No � 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? None (0%) � 1 About a half (50%) � 4

Under 10% � 2 About three quarters (75%) � 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%) � 1 About a half (50%) � 4

Under 10% � 2 About three quarters (75%) � 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 Rotate staff in the area � 6

around it Plan to replace it with a quieter one � 2 Introduce hearing tests � 7

Investigate my options � 3 Review work process that leads to the � 8

hazard Have noise levels measured � 4 Reorganise / place it elsewhere � 9

Enclose the machine � 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 � 2 Get workers to sign for hearing protection � 8

Introduce hearing tests for workers � 3 Give training on how to use protection � 9

Ask workers which protectors they prefer � 4 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? Tick all that apply. Training on how to use hearing protection � 1 Hearing protection for workers � 10

Monitor HSE updates on noise � 2 Stop people working when they reach � 11

exposure limits Training on noise risks � 3 Hearing tests for workers � 12

Contact external experts about noise � 4 Limit operator time in noisy areas � 13

Check workers are wearing protection � 5 Building layout to control noise � 14

Replace radios with MP3 players � 6 Buying 'quiet' replacement machine/tools � 15

Noise risk assessments � 7 Record how long workers use hearing � 16

protection Correcting worker poor practice � 8 Regular maintenance of noisy machinery � 17

Barriers / screens / enclosures to reduce � 9 Engineering/technical noise reduction � 18

noise programme

61

YOUR EXPERIENCE OF MANAGING NOISE Q13. To what extent do you agree with the following statements? Please answer honestly.

Strongly agree Agree Neither 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 health-related 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

nor disagree � 1 � 2 � 3

� 1 � 2 � 3

� 1 � 2 � 3

� 1 � 2 � 3

� 1 � 2 � 3

� 1 � 2 � 3

� 1 � 2 � 3

� 1 � 2 � 3

� 1 � 2 � 3

� 1 � 2 � 3

� 1 � 2 � 3

� 1 � 2 � 3

Disagree

� 4

� 4

Strongly disagree � 5

� 5

� 4

� 4

� 5

� 5

� 4 � 5

� 4 � 5

� 4

� 4

� 5

� 5

� 4

� 4

� 4

� 5

� 5

� 5

� 4 � 5

Q14. How do you communicate to workers about noise risks / hearing protection? (Please tick all options that apply)

Briefings / Toolbox talks � 1

Distribute company own noise guidance � 2

Distribute HSE / Industry noise guidance � 3

Distribute minutes from health & safety � 4

meetings Via Union members / worker � 5

representatives

Talk to workers myself � 6

Through managers / supervisors � 7

Signage � 8

Staff inductions � 9

Through occupational health service(s) � 10

Q15. To what extent do you agree with the following statements?

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

Strongly agree Agree Neither agree Disagree Strongly nor disagree 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 � 1 � 2 � 3 � 4 � 5

noise issues in my job I make sure that noise is included in risk � 1 � 2 � 3 � 4 � 5

assessments I have a wealth of experience to draw from � 1 � 2 � 3 � 4 � 5

when making decisions on how to reduce noise I listen to workers views about ways to � 1 � 2 � 3 � 4 � 5

reduce noise I believe it's worth getting my workers' � 1 � 2 � 3 � 4 � 5

hearing tested Nothing stops me from tackling noise � 1 � 2 � 3 � 4 � 5

issues in my company

Q16. How satisfied are you with the following? Very satisfied Satisfied Neutral Dissatisfied Strongly

dissatisfied The amount of training that you have � 1 � 2 � 3 � 4 � 5

received just on noise The quality of training received just on � 1 � 2 � 3 � 4 � 5

noise (i.e. did it help you?) The amount of general health and safety � 1 � 2 � 3 � 4 � 5

training that you have received The quality of general health and safety � 1 � 2 � 3 � 4 � 5

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 Not at all

amount The demands of my job � 1 � 2 � 3 � 4 � 5

Lack of support from my colleagues � 1 � 2 � 3 � 4 � 5

Lack of support from my Directors � 1 � 2 � 3 � 4 � 5

Not knowing what all my options are � 1 � 2 � 3 � 4 � 5

The cost of replacing machinery / tools for � 1 � 2 � 3 � 4 � 5

quieter models Existing machinery / tools are still fit for � 1 � 2 � 3 � 4 � 5

purpose The time that it would take � 1 � 2 � 3 � 4 � 5

Unable to delegate health and safety tasks � 1 � 2 � 3 � 4 � 5

to others Dealing with safety matters � 1 � 2 � 3 � 4 � 5

Building layout / Design � 1 � 2 � 3 � 4 � 5

Health and safety budgets � 1 � 2 � 3 � 4 � 5

NOISE INFORMATION SOURCES Q18. How often do you access the following for information on noise?

Often Sometimes Rarely Never HSE website � 1 � 2 � 3 � 4

Machinery suppliers � 1 � 2 � 3 � 4

Your HSE Inspector � 1 � 2 � 3 � 4

Industry guidance � 1 � 2 � 3 � 4

Published HSE guidance � 1 � 2 � 3 � 4

Other companies / competitors � 1 � 2 � 3 � 4

Internet � 1 � 2 � 3 � 4

63

_____________________________________________________________________________

_____________________________________________________________________________

Insurance companies � 1 � 2 � 3 � 4

Direct call to HSE � 1 � 2 � 3 � 4

Direct contact with your Local Authority � 1 � 2 � 3 � 4

Other (please specify) � 1 � 2 � 3 � 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 � 1 � 2 � 3 � 4 � 5 � 6

Machinery suppliers � 1 � 2 � 3 � 4 � 5 � 6

Your HSE Inspector � 1 � 2 � 3 � 4 � 5 � 6

Industry guidance � 1 � 2 � 3 � 4 � 5 � 6

Published HSE guidance � 1 � 2 � 3 � 4 � 5 � 6

Other companies / competitors � 1 � 2 � 3 � 4 � 5 � 6

Internet � 1 � 2 � 3 � 4 � 5 � 6

Insurance companies � 1 � 2 � 3 � 4 � 5 � 6

Direct call to HSE � 1 � 2 � 3 � 4 � 5 � 6

Direct contact with your Local � 1 � 2 � 3 � 4 � 5 � 6

Authority Other � 1 � 2 � 3 � 4 � 5 � 6


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 Not helpful at all None are given unhelpful [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

Q21. To what extent do you agree with the following statements? Strongly Disagree Neither agree Agree Strongly agree disagree nor disagree

I have all the information I need to � 1 � 2 � 3 � 4 � 5

understand how to deal with noise risks in my company I know where to get help when I have a � 1 � 2 � 3 � 4 � 5

problem with noise We cannot find information on quieter � 1 � 2 � 3 � 4 � 5

models of machinery / tools we use

64

______________________________________________________________________________________________ ______________________________________________________________________________________________ ______________________________________________________________________________________________ ______________________________________________________________________________________________ ______________________________________________________________________________________________ ______________________________________________________________________________________________ ______________________________________________________________________________________________ ______________________________________________________________________________________________ ______________________________________________________________________________________________ ___________________________________________________________

I know where to get information on � 1 � 2 � 3 � 4 � 5

health surveillance / hearing tests

YOUR NOISE DECISIONS AND MANAGEMENT Q22. To what extent do you agree with the following statements?

Strongly agree Agree Neither agree Disagree Strongly nor disagree disagree

My organisation has a well-known � 1 � 2 � 3 � 4 � 5

brand name in our area

companies in our industry

health is a big risk for the business

There is not much that I can do about noise issues

provide hearing protection

what we do about noise

this Company

legislation

noise levels / exposures

not complying

to avoid future claims

noise problems

quieter model makes little difference to noise levels

we use do not exist

us money in the long term

We control noise as well as most other � 1 � 2 � 3 � 4 � 5

The director(s) think that worker ill- � 1 � 2 � 3 � 4 � 5

The Company is run by a few people. � 1 � 2 � 3 � 4 � 5

It is not possible for us to do more than � 1 � 2 � 3 � 4 � 5

Health and safety legislation drives � 1 � 2 � 3 � 4 � 5

I can influence noise management in � 1 � 2 � 3 � 4 � 5

We try our best to comply with noise � 1 � 2 � 3 � 4 � 5

Our insurers have told us to reduce � 1 � 2 � 3 � 4 � 5

We are afraid of the consequences of � 1 � 2 � 3 � 4 � 5

We want to deal with our noise problem � 1 � 2 � 3 � 4 � 5

I try to work out technical solutions to � 1 � 2 � 3 � 4 � 5

Replacing just one machine / tool with a � 1 � 2 � 3 � 4 � 5

Quieter models of machines / tools that � 1 � 2 � 3 � 4 � 5

Eliminating / minimising noise will save � 1 � 2 � 3 � 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)

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.

No. of Employees: 1 – 10 11-49 50-249 250 +

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)?

• How have you found the changes?

5) 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?

6) What information on noise risks and controls is provided to staff?

• 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?

7) 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?)

8) Is there anything else you can think of that your company has done to protect workers from noise risks? (Provide example)

9) How do you keep a balance between controlling noise and getting the job done?

• Control of noise at source? • Balance with productivity? • Any examples where some tough decisions had to be made? • Any consequences?

10) 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

SIC Code Total number of

companies % of sub-sample Number of questionnaires

distributed Metallic Sector 27 2,561 6% 16

28 26,797 57% 173 29 10,944 23% 70 34 2,430 5% 15 35 3,326 7% 22

37.1 835 2% 6 Sub-Totals 46,893 100% 302

% of 800 distributed 38% Non-Metallic Sector 15 9,630 12 60

17 6,900 9 45 20 11,048 14 70 21 2,384 3 15 22 25,982 34 168 25 5,730 7 35 26 6,676 9 45

36.1 7,485 10 50 37.2 1,436 2 10

Sub-Total 77,271 100% 498 % of 800 distributed 62%

Grand total 124,164 100% 800

71

Figures A5.1 and A5.2 Sample obtained for metallic and non-metallic companies respectively

0

5

10

15

20

25

30

35

40

45

50 N

umbe

r of c

ompa

nies

Sample Ideal sample

27 28 29 34 35 37.1

SIC codes/sub-sector

Figure A5.1 Number of returns from metallic companies versus the ideal representation

15 17 20 21 22 25 26 36.1 37.2

SIC codes/sub-sector

0

5

10

15

20

25

30

35

40

45

50

Num

ber o

f com

pani

es

Sample Ideal sample

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 Size SIC code Management position Location Metallic

2 S 27 Head of ‘Chase’ Department with Health & Safety responsibilities

London

4 M 29 Health & Safety Advisor Lincoln 6 M 28 Safety, Health & Environment Manager Doncaster 7 S 29 Owner Southampton

11 L 29 3 interviewees: Safety Engineer, Health & Safety Coordinator & Manufacturing Engineer

Basildon

13 M 34 Health & Safety Advisor Bolton 14 M 27 Health & Safety Manager Ashford 15 L 28 Health, Safety, Environment & Security

Manager Redditch

Non-Metallic 1 M 25 Production Director Skegness 3 S 37 Technical Manager West

Bromwich 5 M 21 Business Manager Corby 8 M 26 2 interviewees: Production Director &

Production Manager Scunthorpe

9 S 20 Director Huddersfield 10 L 26 Health, Safety & Environmental Manager Stoke-on-Trent 12 L 15 Shared Resources Health & Safety

Advisor Bristol

73

APPENDIX 6 SUPPLEMENTARY MATERIAL – DATA ANALYSIS

Table A6.1 Scoring system for implemented noise controls

Controls implemented Score (range) 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

1 (‘0’ - ‘8’)

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

2 (‘0’ to ‘14’)

Red herrings that have little impact on employee health: • Stop people working when they reach exposure limits • Record how long workers use hearing protection

-1 (Subtracted from total score for

each item selected) Red herring that could negatively impact employee health: • Replace radios with MP3 players

-2 (Subtracted from total score if

selected) Total Score - 4 – 22

Figure A6.1 Categorisation of companies according to perceived risk to the business from noise

High Risk to the business from noise Low

1 High noise levels & proportion of

workers exposed

3 Medium noise levels & proportion of workers exposed

Low noise levels & proportion of

workers exposed

6

2 High noise levels & medium proportion of

workers exposed

Medium noise levels & high proportion of

workers exposed

4 High noise levels & low proportion of workers exposed

Low noise levels & high proportion of workers exposed

Medium noise levels & low proportion of

workers exposed

Low noise levels & medium proportion of

workers exposed

5

Noise levels Proportion of workforce exposed High - Impossible to talk even shouting in someone’s ear

High - about three-quarters or all (75/100%)

Medium - Need to shout when talking to a workmate 1 or 2 meters away

Medium - about a quarter or half (25-50%)

Low - Noise is comparable to a busy street Low - under 10%

74

Table A6.2 Performance classification criteria for the company site visits

High performers Moderate performers Low 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)

Low criteria met plus the following: • Check workers wearing hearing

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

• Noise risk assessments • Provide hearing

protection

75

APPENDIX 7 SUPPLEMENTARY MATERIAL - RESULTS

Table A7.1 Internal consistency results

Factor number

Original factor name (internal consistency result)

New factor name (internal consistency result)

1 Knowledge (α = 0.700) Knowledge & awareness (α = 0.700) 2 Attitudes, values & beliefs (α = 0.359) Attitudes, values & beliefs (α = 0.534) 3 Self-efficacy (α = 0.524) Self-efficacy (α = 0.718) 4 Skills/competency (α = 0.648) Autonomy & competence (α = 0.740) 5 Resources (α = 0.872) Resources (α = 0.895) 6 Information and communication (α =

0.576) Information and communication (α = 0.717)

7 Compliance with legislation (α = 0.284)

Organisational health and safety values (α = 0.531)

8 Health & safety culture/climate (α = 0.537)

Business motivators (α = 0.588)

9 Reputation (α = 0.274) 10 Business (α = 0.348) 11 Control (α = 0.525)

Table A7.2 Breakdown of responses to demographic items

Demographic item Response category Number of participants Q1. Company size Micro (up to 10) 107

Small (11-49) 80 Medium (50-249) 24 Large (250 plus) 4

Q2. Sector Food & beverages 12 Textiles 7 Wood/Products of wood 17 Pulp/Paper products 2 Printing 47 Basic metals 4 Rubber/Plastic products 2 Fabricated metal products 28 Machinery & equipment 19 Motor vehicles & trailers 3 Furniture 6 Recycling 0 Other transport equipment 4 Other non-metallic mineral (e.g. glass & ceramics)

4

Other 57 Missing 3

Q4. Company part of a larger group?

Yes No Missing

38 173

4 Q5. Role Owner/Director 97

Senior Manager 28 Health & Safety Manager 35 Manager 40

76

Supervisor Works/Production Manager Missing

2 9 4

Q6. H&S rep in company?

Yes No

162 53

Q7. TU rep in company?

Yes No Don’t know Missing

17 195

2 1

DV IV1 IV2 IV3 IV4 IV5 IV6 IV7 IV8 IV9 IV10 IV11 DV 1.000 IV1 .332 1.000 IV2 .333 .267 1.000 IV3 .271 .294 .398 1.000 IV4 .336 .397 .374 .546 1.000 IV5 .037 .275 .254 .205 .209 1.000 IV6 -.278 -.451 -.182 -.157 -.318 -.228 1.000 IV7 .504 .259 .482 .531 .431 .099 -.200 1.000 IV8 .263 -.021 .064 .107 .215 -.187 -.039 .284 1.000 IV9 .456 .134 .278 .134 .137 -.129 -.068 .291 .180 1.000 IV10 -.363 -.211 -.207 -.121 -.040 -.014 .050 -.198 -.170 -.540 1.000 IV11 .393 .232 .266 .174 .201 -.027 -.173 .245 .148 .565 -.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 Dependent variable – Noise controls implemented IV1 Knowledge IV2 Attitudes towards workers (health risks & behaviours) IV3 Self-efficacy IV4 Autonomy and competence IV5 Resources / barriers IV6 Information and communications IV7 Organisational / cultural (health & safety) IV8 Business motivators IV9 Company size IV10 Manager role (Director/Owner) IV11 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)

Medium (Q10)

High (Q10)

Total

Low (Q10) 23 42 0 65 Medium (Q10) 30 69 1 100 High (Q10) 4 21 0 25 Total 57 132 1 190

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 Response category Number of participants Internet Often 71

Sometimes 62 Rarely 27 Never 51 Missing 4

Published HSE Often 59 guidance Sometimes 55

Rarely 44 Never 53 Missing 4

HSE Website Often 48 Sometimes 54 Rarely 43 Never 67 Missing 3

Industry guidance Often 48 Sometimes 48 Rarely 50 Never 64 Missing 5

Machinery suppliers Often 27 Sometimes 55 Rarely 68 Never 62 Missing 3

Insurance companies Often 19 Sometimes 42 Rarely 40 Never 110 Missing 4

Other companies/ Often 11 competitors Sometimes 32


78

Your HSE inspector Often 7 Sometimes 26 Rarely 79 Never 100 Missing 3

Direct call to HSE Often 2 Sometimes 26 Rarely 52 Never 129 Missing 6

Direct contact with Often 2 your LA Sometimes 14


Other Often 5 (See below for Sometimes 1 Breakdown) Rarely 7

Never 26 Missing 176

Other (breakdown) External consultants/experts 13 Own H&S guidance/policies 3 External H&S company/agency 3 Surveillance 3 External sources (not specified) 1 Other 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 Response category Number of participants Internet Very helpful 45

Helpful 90 Neither helpful nor unhelpful 10 Unhelpful 1 Very unhelpful 2

Published HSE Very helpful 41 guidance Helpful 90

Neither helpful nor unhelpful 10 Unhelpful 1 Very unhelpful 0

HSE Website Very helpful 58 Helpful 64 Neither helpful nor unhelpful 10 Unhelpful 1 Very unhelpful 0

Industry guidance Very helpful 26 Helpful 79 Neither helpful nor unhelpful 20 Unhelpful 4 Very unhelpful 3

79

Machinery suppliers Very helpful 24 Helpful 80 Neither helpful nor unhelpful 25 Unhelpful 3 Very unhelpful 2

Your HSE inspector Very helpful 26 Helpful 43 Neither helpful nor unhelpful 15 Unhelpful 1 Very unhelpful 2

Insurance companies Very helpful 21 Helpful 33 Neither helpful nor unhelpful 23 Unhelpful 5 Very unhelpful 2

Direct call to HSE Very helpful 13 Helpful 33 Neither helpful nor unhelpful 10 Unhelpful 1 Very unhelpful 4

Other companies/ Very helpful 10 competitors Helpful 32


Direct contact with Very helpful 7 your LA Helpful 26


Other45 Very helpful 3 Helpful 3 Neither helpful nor unhelpful 0 Unhelpful 0 Very unhelpful 0

Other (breakdown) External consultants/experts -External H&S company/agency -Surveillance -Other -

45 NB: For the ‘other’ response options specified participants did not rate how helpful these were. 80

Table A7.6 Content analysis of implemented controls according to company size

Cas

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3 7 9 1 4 5 6 8 13 14 10 11 12 15

Evidence of controls in place

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Table A7.7 Company wish lists

Company size One thing that would help to control noise at work?

Small

(Wish list focuses on machinery)

“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)

Medium

(Wish list broadens; still have requests for machinery, but want more guidance, training and changes in worker behaviour)

“Cost of machinery is prohibitive, would welcome proactive advice from HSE.” (2)

“Better understanding and guidance on specific issues.” (4)

“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)

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Table A7.8 Variance of implemented noise controls explained by the three significant factors

Model R R² 46 Adjusted R² Std. Error of the Estimate

Organisational values .507¹ .257 .253 4.097 Company size .608² .370 .364 3.781 Knowledge/awareness .652³ .425 .416 3.621

Table A7.9 Strength of effect on implemented noise controls of each predictor variable

Model Unstandardised Coefficients Standardised Coefficients

B Std. Error Beta T-value

Significance

Constant -16.287 2.498 - - .000 6.521

Values 3.571 .588 .355 6.070 .000 Size 2.258 .378 .341 5.973 .000

Knowledge 2.228 .520 .242 4.285 .000

Table A7.10 Model validation outputs

Model R R² Adjusted R² Std. Error of the Estimate 1 .570¹ .325 .317 4.065 2 .637² .405 .392 3.835 3 .665³ .442 .424 3.734

¹ Organisational values ² Company size ³ Knowledge/awareness

Model 3

Unstandardised Coefficients

Standardised Coefficients

B Std. Error Beta t-value Significance Constant -14.965 4.043 - -3.701 .000

1 3.126 .580 .446 5.393 .000 2 3.103 .893 .286 3.474 .001 3 1.958 .786 .195 2.490 .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 r-values 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 Z-Score R-Value Effect size category Knowledge and awareness -2.876 -0.20 Small Health & safety values -2.521 -0.17 Small Company size -2.500 -0.17 Small Resources -3.376 -0.23 Small

84

Table A7.12 Demographic profile of companies by performance levels C

ase

Sub

Sect

or

Met

allic

Non

-Met

allic

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Per

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ers

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1 25 Small companies 2 27 Medium-sized companies 3 37 Large companies 4 29

5 21 Controls in place 6 28 7 29 8 26 9 20 10 26 11 29 12 15 13 34 14 27 15 28

* Dutyholder in single role (e.g. designated Health and Safety Manager/Advisor, Safety, Health and Environmental Manager). ** NEBOSH or equivalent.

85

86


Influencing dutyholders behaviour regarding the management of noise risks 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.


HSE Books

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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.

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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

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1 INTRODUCTION

1.1 BACKGROUND

This research was commissioned by the Health and Safety Executive (HSE) as part of a long-term 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 non-auditory effects, such as accidents, cardiovascular morbidity and work-related stress (e.g. Welch, 1979), and auditory effects, namely, tinnitus1 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 life2

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 behaviours3 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 See Glossary.2 See Noise at Work. The RoSPA Occupational Safety & Health Journal, April 2008, 15-22. 3 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 leadership4 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 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.

� Make 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.

� Provide 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.

� Carry 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 model5 (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

2.1

2 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 behaviour6.

• 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 HERALD7

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 See Glossary.7 HERALD is currently HSE’s main research database.

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2.2

• High versus low performing organisations.

The HSE search returned a large number of abstracts (n=5478) 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 286 Healsafe 91 Ebsco Business Corporate 43 Medline, Embase, Management and Marketing Abstracts, Management Abstracts, Psyclit and ABI Inform.

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Web of Science 51 Management and Marketing Abstracts 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

2.3

Table 2: Inclusion criteria.

Include articles if they are/cover: Exceptions apply if:

• Occupational-based research and practice. • Behavioural research on noise published • Published within the last 10 years; 5 years over 10 years ago, due to the shortage of

if on leadership behaviour. highly relevant research on noise. • Reviews/meta-analyses in the last 3 years. • Relevant UK research is sparse, in which • UK-based research and practice. case include international papers with • Influences on (managers’/dutyholders’) caveats.

(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.

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-analysis9/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 articles10 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.

Noise Relevance Weighting System Highly Relevant (N)

Evidence includes research specific to noise.

Relevant (H) Evidence includes research from other physical health hazards with latency between exposure and harm.

Generic (G) 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)*** Generally consistent findings provided by (systematic reviews/meta-analysis of) multiple scientific studies or multiple longitudinal studies.

Moderate (M)** Generally consistent findings provided by (reviews of) fewer and/or methodologically weaker scientific studies or fewer longitudinal studies.

Weak (W)* 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.

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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 studies11. 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

3.1

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) Unique Contributing Factors (n=20)

(1) Business � Economic / financial � Corporate reputation � Customer Pressure � Capability / cost of making engineering improvements � Experience of a serious accident and/or enforcement

(2) Legal � Compliance with legislation (3) Cultural/Organisational � Experience of a serious accident and/or enforcement

� Values and beliefs � Perceived / actual control � Culture � Health and Safety attitudes � Resources � Demographics12

� Employee attitudes and motivation (4) External � Information and communications

� Environmental (5) Personal � Knowledge, awareness and understanding

� Health and Safety attitudes � Risk perception � Competence � Self-efficacy / confidence � Personality � Demographics13

� Values and beliefs

Table 5: Five overarching factors and contributing factors.

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 I.e. role/position, industry sector, type of operation and accident/incident/ill health rates. 13 E.g. gender.

12

3.2

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).

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.

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3.3

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.

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 Action14 (TRA: Fishbein & Ajzen, 1975) and Theory of Planned Behaviour15 (TPB: Ajzen & Fishbein, 1980; Ajzen, 1988), attitudes have been shown to influence behavioural intentions16, 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 See Glossary.15 See Glossary.16 See Glossary.

14

Podgorski, 2006). One study found commitment to have the greatest influence over and above other attitudes held by management such as fatalism17 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 Behaviour19 (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 Model20 (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 culture21 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 Effectiveness22 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.18 See Glossary.19 See Glossary.20 See Glossary.21 See Glossary.22 See Glossary.

15

3.4

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).

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

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3.5

concerned other physical health hazards with latency between exposure and harm and most (n=6) were relevant to occupational health and safety hazards generally.

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-efficacy23 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) Self-Regulatory Model24 (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 Theory25 (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 motivation26 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.24 See Glossary.25 See Glossary.26 See Glossary.

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).

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4.1

4 CONCLUSIONS

IMPLICATIONS OF FINDINGS FOR THIS RESEARCH

Given the paucity of research directly examining factors that influence management behaviour with regards to controlling noise risks27 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.

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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 moderate28 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’.

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4.2

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.

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/short-term 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 sizes29 in order to gauge the true extent of their influence.

Overarching Factor (n=5) Contributing Factors (n=17)

Business � Economic / financial � Corporate reputation � Capability / cost of making engineering improvements � Experience of a serious accident and/or enforcement

Legal � Compliance with legislation Cultural/Organisational � Experience of a serious accident and/or enforcement

� Values and beliefs � Perceived / actual control � Culture � Health and Safety attitudes � Resources � Demographics

External � Information and communications � Environmental

Personal � Knowledge, awareness and understanding � Health and Safety attitudes � Risk perception � Competence � Self-efficacy / confidence � Demographics � Values and beliefs

Table 6: Factors to assess in the research.

29 See Glossary.

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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.

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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: Assumed to be the motivational factors that influence actual behaviour.

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).

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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).

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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.

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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.

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7 APPENDICES

7.1 APPENDIX 1: DATA EXTRACTION TABLE

Reference Summary of research (Include Industry and Country)

Potential Influences on Management Behaviour

Noise-relevance

Rating (N, H, G30)

Implications for Research Tools and any Caveats

(E.g. cultural differences – How applicable to UK?)

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 work-related 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].

Other emerging factors: Corporate credibility, customer pressure. [Not significant motivators].

Regulations, hazard awareness, moral beliefs. [Significant motivators].

Moderating factors: Risk awareness, cost/capability of making improvements.

G 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.

30 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).

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of insurance (i.e. a significant decline in premiums with increased health and safety performance). Factors that moderate31

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, A case study of health and safety appraisal within a UK- Financial implications of G An important moderator K. G., & Ellis, M. J. (2005). manufacturing company responsible for constructing pre- poor health and safety. highlighted for financial Assessing attitudes and beliefs using fabricated buildings. The authors used Prochaska and influences i.e. whether the stage of change paradigm – case DeClemente’s (1982) Stage of Change model32 as a framework to company has experienced a study of health and safety appraisal assess attitudes and beliefs of key stakeholders (at three levels: Possible Moderator serious accident/incident case within a manufacturing company. senior-level management, middle-level management and (influence of financial needs to be measured. International Journal of Industrial production-level employees including production supervisors) factors): Whether company Ergonomics, 53, 871-887. within the organisation. A triangulated approach33 was adopted

including stage-targeted questions, supplementary interviews and assessment of safety culture34 . 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.

has experienced a serious accident/incident.

Productivity pressures (to reach set targets) take priority over safety.

Lack of necessary health and safety knowledge.

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.

31 See Glossary under ‘Moderating variables’.

32 See Glossary.

33 See Glossary under ‘Triangulation’.

34 See Glossary.

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3. Rundmo, T., & Hale, A. R. Analysed the relations between managers’ (n=74) safety attitudes, Managers’ safety attitudes G Highlights the eight attitudinal (2003). Managers’ attitudes towards behavioural intentions35 and their self-reported behaviour. In line influence on intentions and dimensions that affect safety and accident prevention. with the Theory of Planned Behaviour36 (TPB) and Theory of behaviour. managers’ safety intentions Safety Science, 41, 557-574. Reasoned Action37 (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 Model38 and Self-Regulatory Model39, 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 fatalism40 , 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.

Knowledge and resources (time, money, competence and equipment) to carry out necessary steps for controlling hazards.

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.

35 See Glossary.36 See Glossary.37 See Glossary.38 See Glossary.39 See Glossary.40 See Glossary.

35

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 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.

5. Krause, T. R. (2004). Influencing the behaviour of senior leadership. Professional Safety, June 2004, 29-33.

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.

Human compassion, integrity and sense of duty.

Good for business.

G 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

36

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.

interventions.

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), 249-268.

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 Model42) and goal theories (e.g. Control Theory43, Theory of Goal Setting44) 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 sizes45). Several methodological issues, however, prevent making inferences about causation (e.g. cause and effect is not determined via correlation, third variable influence, cross-

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.

41 See Glossary.42 See Glossary.43 See Glossary.44 See Glossary.45 See Glossary.

37

sectional studies). As such, the authors conducted a meta-analysis46 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. 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.

7. Gillen, M., Kools, S., McCall, C., The authors looked at American construction managers’ Management commitment G Identifies some key variables Sum, J., & Moulden, K. (2004). perceptions of safety practices, comparing the views of those Safety culture. important to measure with Construction managers’ perceptions belonging to small and large firms. A qualitative investigation47 Enforcement. focus on what enables and of construction safety practices in was carried out involving five focus groups with 22 managers deters safety management. small and large firms: A qualitative (two with managers of small firms, three with managers of large Management characteristics investigation. Work, 23, 233-243. 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

(flexible, innovative and principled).

Financial constraints. Poor training (knowledge).

Note the potential differences between the US and UK enforcement system and the fact this research concerns the construction industry (e.g. the

46 See Glossary.

47 See Glossary under ‘Qualitative research’.

38

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.

Productivity versus safety.

Understanding of the hazards that characterise the industry.

necessary manager characteristics may be different in manufacturing).

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.

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.

A literature review on the application of social cognitive models (i.e. the Health Belief Model, TRA, TPB, and Transtheoretical Model of Change48) 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,

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).

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

48 See Glossary.

39

complacency about farm safety, a low perception of personal risk and cost constraints limiting maintenance and purchase of farm equipment and machinery.

predictive impact of these factors on farmers’ behaviour remains unclear.

9. Wright, M., Marsden, S., Greenstreet Berman administered a survey (via telephone) in General concern G Provides the top five factors Dimopoulos, E. (2006). Health and 2001, 2003 and 2005 (longitudinal) to large public and private for/increased importance of influencing director behaviour safety responsibilities of company organisations covering a range of industries (e.g. Private: retail, health and safety. with regards to directing directors and management board manufacturing, construction, finance, transport; Public: education, health and safety. This covers members: 2001, 2003, and 2005 NHS and LA) in the UK, following release of the HSC guidance Concern about corporate results from three surveys over surveys. HSE Research Report 414. ‘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.

responsibility/image.

HSE Guidance.

Corporate governance requirements.

Fear of company prosecution.

a 4-year time span, the latest being conducting in 2005, rather than relying on the findings from one survey.

10. Shearn, P., & Miller, M. (2005). Similar to the above study by Wright et al (2006), this paper Role within the organisation. G A very useful paper for Director Leadership of Health and summarises a literature review of UK and international Industry sector and type of summarising key factors Safety. HSL Report: SOFS/05/07. 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

operations. Accident, incident and ill-health rates. Knowledge/personal interest in health and safety.

Health and safety legislation. Reputation.

found to influence director-level behaviour (up until 2005).

Most importantly, it points out that factors may have a varying degree of influence on SMEs compared with large

49 See Glossary.

40

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 humanistic49

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).

Competence (knowledge and skills) to manage health and safety.

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’).

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.

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.

11. Bentley, T. A., & Haslam, R. A. A UK study comparing the safety practices (mainly in relation to Attitudes towards safety. G Useful research as it compares (2001). A comparison of safety slips, trips and falls) of a cross section of 20 Delivery Office high and low performing practices used by managers of high Managers (DOMs: supervisor level) in high and low accident Time/workload (safety organisations, which is one of and low accident rate postal delivery rate postal delivery offices. To obtain a list of desirable coming second to the aims of this study. The offices. Safety Science, 37, 19-37. 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

productivity).

Lack of available good safety

focus of Bentley and Haslam’s study, however, centres on the behaviours that managers/

41

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, non-compatibility 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).

Employee attitudes and behaviour (e.g. indifference to safety).

Knowledge / training.

Cost/budget.

Safety not compatible with work quality.

Individual characteristics (charismatic, motivator) and time management.

Management commitment.

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).

Raises some different factors to consider, namely, the influence of employee attitudes and behaviour on managers’ and safety not being compatible with work quality.

12. Petersen, D. (2004). Leadership Based on the author’s experience (in the USA) and Interpersonal characteristics G Shows that leadership and and Safety Excellence: A positive interpretations of the available literature (opinion-based), the (especially important is degree culture are closely interlinked. culture drives performance. process that leaders use when dealing with safety (injury of influence over others). The questionnaire could Professional Safety, Oct Vol, 28-32. 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

Job characteristics (role clarity and ability, work organisation, level of

incorporate items assessing safety culture (to determine whether this is positive or negative).

50 See Glossary.

42

the term is not only describing those in executive positions. The paper refers to Yukl’s (1989b) Conceptual Framework of Leadership Effectiveness50, 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).

Resources.

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.

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 in-house health and safety knowledge and are thus highly dependent on suppliers (e.g. of safety equipment) and external advisors.

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.

43

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.

Perception of health and safety management / implementing controls.

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

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 Highlights the importance of 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 lower-level manager, who has insufficient knowledge and authority to make positive change.

44

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.

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.

commitment.

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 leadership51 on safety-related outcomes as well as active / effective leadership52 . 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 / unethical53 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.

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 safety-related outcomes, rather than what influences these styles/behaviour in the first place, likely to be an interplay

51 See Glossary.52 See Glossary.53 See Glossary.

45

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 and prioritisation.

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., This study examined factors, including management practices, Knowledge and awareness of G Useful for highlighting factors Fonteyn, P. N., & Cross, J. A. that impact on high injury rates resulting from mechanical hazards. likely to influence (1999). Mechanical equipment equipment within small manufacturing high-risk organisations management behaviour in injuries in small manufacturing (with 19 personnel or less). Motivation. small organisations. The businesses. Knowledge, behavioural, Interviews were conducted with 35 business owners in manager-employee

46

and management issues. International Journal of Occupational Safety and Ergonomics, 5(1), 59-71.

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 poor health and safety. 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 poor health and safety.

Risk perception.

Resources (time and money).

Cultural influences (safety rules and procedures, including recording accidents and learning from these, and defined responsibilities for safety).

Manager-employee relationship (friendliness versus assertiveness).

relationship may be an important issue for small organisations given direct contact with staff.

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.

18. Wright, M. A. (1999). A risky business. Environmental Health, 107(3), 90-93.

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.

Need to comply with the law.

Intrinsic and extrinsic motivation55 levels.

Beliefs that health and safety

G 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.

Shows the need to consider

54 See Glossary.55 See Glossary.

47

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 motivate54 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.

Perception of business risks. Cost.

the ‘risk levels’ of participating organisations likely to influence motivation to act. The following questions assess risk56: 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?

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’.

19. Gervais, R. L. (2006). An evaluation of successful communication with small and medium sized enterprises (SMEs). HSL/2006/32.

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.

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.

56 All three questions were extracted from Wright’s article.

48

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.

Third party advice on noise.

Understanding of HSE guidance.

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.

20. Ferguson, E., Lawrence, C., Bibby, P., Leaviss, J., & Moghaddam, N. (2006). Lay conceptualisations of occupational disease. HSE Report 469: HSE Books.

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

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

57 See Glossary.

49

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 representations57 . 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).

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.

21. Addison, N., & Burgess, G. Looked at compliance with manual handling regulations amongst Ease of implementation and G Suggests possible factors (2002). Compliance with Manual UK SMEs (100 companies in Shropshire employing 5-50 resources for control influencing Handling Regulations amongst employees, randomly selected, differing industries). A measures. dutyholders/directors of SMEs Random Selection of Small questionnaire-based study, which achieved a high response rate choice and implementation of Businesses in England. Annual (80%). Perceived competence to noise controls. Occupational Hygiene, 46, 149-155. 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 pre-requisite for assessments as well as the need for additional knowledge to decide on preventative measures (usually involving

carry out risk assessments and determine necessary controls.

Survival of the business.

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.

50

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.

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.

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.

23. Holmes, N., Lingard, H., A qualitative study (15 in-depth interviews) of employers’ and Perceptions of risk control – H A very small sample, focusing Yesilyurt, Z., & De Munk, F. (1999). employees’ meanings of occupational health and safety (OHS) is noise-induced hearing loss on micro-organisations rather An Exploratory Study of Meanings of risk control (for falls from height and skin disease). Five small controllable or not? Cost- (Skin than SMEs. Useful, however, Risk Control for Long Term and (employing 3-10 people) Australian companies took part in the benefit analysis of controlling disease has for breaking down the facets Acute Effect Occupational Health research. the risk? What is the best a latency of risk control and what may and Safety Risks in Small Business Findings showed that risk control involves the following: method of control and why? period) potentially influence Construction Firms. Journal of employers’ perceptions of risk Safety Research, 30 (4), 251-261. 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)

control.

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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., UK cross sectional research (telephone survey of 1,087 SMEs Resource constraints on G Need to consider factors likely Smallbone, D., James, P., & Ekanem, and interviews with 73 SME managers and 21 employees) SMEs. to have an impact on SME I. (2003). Cultural influences on including ethnic minority businesses (EMBs) and small and managers’ decision-making health and safety attitudes and medium sized enterprises (SMEs). Studied internal and external Management Style and and behaviour.

52

behaviour in small businesses. HSE Research Report 150.

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.

Business pressures.

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.

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.


Moral case (care of employees).

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.

G Likely cultural differences as this research was conducted in Poland.

Research highlights the need to consider the maturity of management systems for OHS.

27. Wright, M., Antonellli, A., 39 exploratory discussions were run with employers and key Regulation/fear of G UK based research that Norton Doyle, J., Bendig, M., & stakeholders, such as, CBI and trade associations from a range of enforcement. provides an up to date review Genna, R. (2005). An evidence sectors and sizes of organizations in the UK. Two different of research on factors based evaluation of how best to surveys were developed to assess what motivates organizations to Reputation. motivating compliance with secure compliance with health and comply with health and safety; one for employers and one for health and safety. safety law. HSE Research Report intermediaries. Moral case (especially

53

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.

“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.”

SMEs).

Cost of accidents/incidents. Financial incentives (insurance premiums).

Understanding and awareness.

Access to relevant information.

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., & A study (case study) carried out in the USA in which a safety Clarity of role with regards to G Confirms that there is a lack of Witt, L. A. (1998). Where the Safety climate survey was administered to members of a Federal safety management. research into management Rubber Meets the Shop Floor: A Aviation Logistics Centre. A model is presented that links behaviour and safety. Confirmatory Model of Management management support, organizational climate and self reported Understanding of their Influence on Workplace Safety. safety outcomes, based upon longitudinal data collected over (managers) influence over The survey is included in the

54

Journal of Safety Research, 29(1), 15-24.

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.

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.

30. Wright, M. S. (1998). Factors Motivating proactive health and safety management. HSE Contract Research Report 179.

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.

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.

55

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:

� 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.

Senior level managers: Attitudes towards safety, compliance with regulations, leadership style and management commitment.

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).

Supervisors: Personality characteristics (e.g. openness, trust in others), attitudes towards safety, commitment, control, leadership style, responsibility for safety.

G 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.

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.

32. Rabin, S., Feiner, M., Shaham, J., Yekutieli, D., & Ribak, J. (1998).

Research conducted in Israel involving 460 workers in three industrial sites, one of which is in food manufacturing and the

Self-efficacy. G Highlights the importance of supervisors in health and

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Impact of Managers’ Personal others in high-tech telecoms manufacturing. This paper Expectation of outcome of safety performance. Determinants in Notifying Workplace examines managers’ personal determinants and notification of behaviour (more likely to Hazards. American Journal of work hazards in a sample of 106 managers and 460 workers. enact if positive). Based on questionnaire Industrial Medicine, 33, 493-500 Results suggest that managers rely on personal modes of

communications with immediate supervisors considered as the most important person in notification. Managers’ sense of self-efficacy (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.

research, yet may have benefited more using a mixed methods approach.

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.

Safety culture/climate and organisational support (including resources).

G Limitations with sample size, but safety communication and social exchange needs to be considered within the research.

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.

Locus of control.

Management skills, style and communication skills.

H Points again to the variation in attitudes towards health as opposed to safety risks.

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

57

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.

change workplace health and safety culture (Spilman, 1988, cited in this paper)”.

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 pleasant-unpleasant).

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:

� 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.

Knowledge and motivation to act.

Perceived cost, ease and practicality of implementing noise controls.

Knowledge of controls.

N Provides some useful information about the importance of a motivated manager/OHS officer and a positive attitude to noise control by management.

How informed management is regarding the benefits of noise control is also important to assess.

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� The cost of noise control. � The provision of engineering detail for noise control in the

survey report. 37. Hughson, G. W., Mulholland, R. UK cross sectional research involving SMEs and large companies Understanding of noise N Need to assess understanding E. & Cowie, H.A. (2002). to examine the various factors influencing workers’ attitudes and regulations. of the significance of noise as Behavioural studies of people’s behaviours towards hearing protection. an occupational hazard and attitudes to wearing hearing Findings showed that the Noise at Work Regulations (1989) is External influences (e.g. measure external influences protection and how these might be generally considered as too complex and confusion over when changing nature of work, that may act as barriers or changed. HSE Research Report 028. 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.

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 long-term).


facilitators to implementation of noise controls.

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7.2 APPENDIX 2: TABLE OF EXCLUDED ARTICLES

Paper/Article Reference Reason for Exclusion

1. Arezes, P. M., & Miguel, A. S. (2005). Concerns the influences on employee rather than Individual Perception of Noise Exposure and Hearing management behaviour. Protection in Industry. Human Factors, 47 (4), 683-692. 2. Arezes, P. M., & Sergio Miguel, A. (2005). Hearing protection use in industry: The role of risk perception. Safety Science, 43, 253-267.

Focuses on what influences employee behaviour.

3. Barrett, G. A. (2000). Management’s Impact on Behavioural Safety. Professional Safety. March Edition, 26-28.

Talks about the features of safety systems and how to improve behavioural processes rather than management behaviour.

4. Becker, M. H. (1974). The Health Belief Model and Sick Role Behaviour. Health Education Monographs, 2 (4), 82-92.

Over ten year old paper and not noise research.

5. Birkner, J. (2005). Noise, Under Control. Occupational Health and Safety, June Edition, http://ohsonline.com/Articles/2005/06/Noise-Under-Control.aspx

General information on noise and control measures.

6. Casali, J. G. (2006). Sound and noise. In Salvendy, G. (Ed). Handbook of human factors and ergonomics, 612-642.

Noise engineering rather than human factors.

7. Cheung, C. (2004). Organizational influence on working people’s occupational noise protection in Hong Kong. Journal of Safety Research, 35, 465-475.

Useful for supporting why this research focuses on managers rather than employees, but the main focus concerns influences on employees’ behaviour.

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.

Looks at how managers/leaders can influence employees behaviour rather than what influences their behaviour.

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.

Outdated meta-analysis / review.

10. DeJoy, D. M. (1996). Theoretical models of health behavior and workplace self-protective behavior. Journal of Safety Research, 27(2), 61-72.

Over 10-year old review and focuses on self-protective behaviour.

11. Dejoy, D. M. (2005). Behaviour change versus culture change: Divergent approaches to managing workplace safety. Safety Science, 43, 105-129.

Discusses approaches to safety rather than the factors that influence the management of safety or managers’ behaviour. Over a three-year-old review.

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.

Over 10-year old paper.

13. Finnish Institute of Occupational Health. (1998). International Symposium from Protection to

Papers and abstracts are over 10 years old.

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http://ohsonline.com/Articles/2005/06/Noise-Under-Control.aspx

http://ohsonline.com/Articles/2005/06/Noise-Under-Control.aspx

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 Leader: Personality, Values and Emotional Commitment. Occupational Hazards, 69 (9), 24.

Describes the ideal attributes of a successful safety leader or leadership style i.e. how they influence safety not what influences them.

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). Beyond cognition: Predicting health risk behaviors from instrumental and affective beliefs. Health Psychology, 26(3), 259-267.

Non-occupational research/practice.

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 and control of the risks due to noise. Occupational Environmental Medicine, 57, 361-369.

Talks about a strategy for controlling noise rather than what influences behaviour.

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 Research Report 507. 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 promote a noise control programme. Scandinavian Audiology, 30 (52), 174-176.

Concerns noise measurement and prevalence.

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.

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27. Patel, D. S., Witte, K., Zuckerman, C., Murray- Concerns influences on employee behaviour rather than Johnson, L., Orrego, V., Maxfield, A. M., meadows- management. Hogan, 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 Over three-year old meta-analysis / review that addresses norms as an additional predictor in the theory of theory rather than an occupational based piece of planned behaviour: A meta-analysis. Current research/practice. 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.

Over five year old paper on leadership qualities.

30. Smith, B. J., Peters, R. J., & Owen, S. (1996). Acoustics and noise control (2nd Ed.). Addison Wesley Longman Ltd: Essex, England.

A book on noise engineering rather than human factor issues.

31. Stokols, D., McMahan, S., Clitheroe Jr., H.C. & No mentioned of individual management behaviour. The Wells, M. (2001). Enhancing corporate compliance paper looks into the effectiveness of a training with worksite safety and health legislation. Journal intervention on corporate compliance with health and of Safety Research, 32, 441-463. safety legislation. 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.

Looks at noise and employee behaviour.

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.

Looks into accidents and structural equation modelling rather than management behaviour.

34. Topf, M. D. (2000). Including Leadership in the Safety Process. Occupational Hazards, 62 (3), 57-58.

Advice on how to improve safety within organisations rather and what leaders should do rather than what influences them.

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.

Concerns noise emissions and the effects of noise.

36. Williams, W., & Purdy, S. (2007). Factors in reducing occupational noise exposure. Journal of Occupational Health and Safety, 23(2), 165-177.

Focuses on employee behaviour.

37. Williams, W., Purdy, S. C., Storey, L., Nakhla, Looks at the effectiveness of a training intervention to M., & Boon, G. (2007). Towards more effective raise awareness of noise, rather than influences on methods for changing perceptions of noise in the management behaviour. 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.

A review of the initiatives taken rather than examining influences on management behaviour.

39. Yeomans, L. & Patel, J. (2008). Feedback on the Hand-Arm Vibration Control Campaign: Views of Inspectors. HSL Report NV/07/21.

Focuses on Inspectors views of the campaign rather than influences of management behaviour.

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7.3 APPENDIX 3: FACTOR GROUPINGS

Factor (Overarching Factor)

Source (Paper / Article / Book number in the Data Extraction

Table – See Appendix 2)

Indication of Amount of Influence (Green = Significant; Red = Unclear;

Blue = Not significant)

Other Notes

1. Economic / Financial [Ill health/injury costs to the business; insurance premiums; personal injury scheme; current tax situation (OH as a benefit than investment in human capital); winning contracts; belief that H&S saves money; business survival/pressures; competitiveness; profitability; corporate governance requirement].

(Business)

1, 2, 5, 10, 18, 21, 24, 25, 27, 31.

Mixed findings regarding extent of influence. Not all research has considered economic benefits to be a key influence on employers’ behaviour, but the majority of research shows this as a significant driver (particularly in the USA due to differences in insurance and compensation).

One UK-based study showed that financial incentives provided by insurance premiums had become more influential in recent years.

‘Business survival’ is more influential for SMEs than larger organisations.

2. Corporate Credibility/ Reputation

(Business)

1, 9, 10, 14, 18, 24, 27, 28, 30. Studies generally show this to have a significant influence on management behaviour.

May vary by industry (e.g. more influential in high hazard industries).

3. Experience of a Serious Accident and/or Enforcement [Emotional influence – regret; financial repercussion].

(Organisational/Cultural & Business)

2, 30, 35. Found to have a significant influence, but implicated more in terms of a moderating variable.

Previous experience of a serious accident has been implicated as a moderator of the impact of financial drivers on decision-making.

4. Customer Pressure

(Business)

1. Not a significant motivator.

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5. Compliance with Legislation [Motivated to comply with the law; fear of prosecution]

(Legal)

1, 7, 9, 10, 18, 24, 27, 31. Significant influence, especially if company has been previously prosecuted.

One study looking at different levels of management found that this factor only influenced the behaviour of senior-level management.

6. Information and Communications [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].

(External)

9, 13, 19, 20, 27, 30. Significant influence on managers’ decision making.

External guidance (non-HSE e.g. suppliers, consultants) and perception of HSE appears to have greater influence on SMEs.

7. Values and Beliefs [Ethical principles; human compassion; sense of duty/responsibility; general concern; moral beliefs; integrity/honesty; fairness; time management & prioritisation; beliefs that outcome will be positive]. Also, Incorporates management style.

1, 5, 9, 10, 16, 24, 26, 27, 30, 32.

Significant influence, particularly for SMEs. A key merging belief is managers’ compassion and general concern for the well being of their employees.

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 Helps to build a picture of managers’ Understanding [Technical knowledge 20, 21, 26, 27, 29, 36, 37. seems to be critical in the risk appraisal ‘mental models’. of noise - know what they need to know process. for their business; noise legislation; Knowledge and understanding seem noise risks; health effects of noise; to have greater influence over SMEs

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effectiveness and use of noise controls; H&S systems & procedures; business benefits of compliance (short & long-term) & good H&S; potential effects of a poor safety culture; knowledge of their own influence over safety climate/culture].

(Personal)

than larger organisations.

9. Risk Perception [Long-term vs. 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].

(Personal)

8, 17, 18, 22, 23, 34. A significant motivator of management behaviour, influenced heavily by knowledge of hazards.

Plays an important role in motivation to act (high risk perception results in intrinsic motivation to act, low risk perception requires external motivators).

10. Competence [Skills to manage noise risks; carry out risk assessments & determine necessary controls].

(Personal)

10, 21. A few studies have reported this as potentially influencing managers’ behaviour. No conclusive evidence.

11. Capability/Cost of Making Engineering Improvements [Considered ‘too costly, poor access to services, misconception of the cost of noise controls; ease of introduction of controls; controlling the noise risk is

1, 4, 8, 13, 14, 21, 23, 27, 30, 36.

Appears to act as a moderating variable, forming part of managers’ cost-benefit appraisal. Seems to be more influential for UK companies than ‘cost’ in general (financial motivators).

Has greater influence on SMEs (OH is viewed as ‘too costly’ or ‘too complex/an administrative burden’).

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considered ‘too difficult’].

(Business)

A number of UK studies have shown that the ‘cost’ of making H&S improvements rather than ‘investment’ is a significant de-motivating factor for management.

12. Perceived/Actual Control [Level of authority/influence over workers].

(Organisational/Cultural)

6, 31. A significant moderator of the relationship between intention and behaviour.

Important at lower-level management and supervisory levels rather than at senior management levels.

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 environment – ‘the way we do things around here’, social norms; social reaction; habit formation; safety 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].


6, 7, 8, 12, 15, 17, 29, 31, 33, 36.

A significant influence on behaviour (possibly through commitment) affecting all levels of management. Organisations with a positive safety climate seem more likely to implement noise controls.

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.

15. Attitudes Towards Health and 2, 3, 7, 8, 10, 11, 14, 24, 26, Significant influence on behavioural A pertinent issue for noise is that it is Safety [H&S commitment/personal 31, 34, 35, 37. intentions, which ultimately affect not taken seriously and can be interest, fatalism (‘risks are part of the behaviour. regarded as inevitable. job’), tolerance of rule violations, Acceptance of responsibility appears worry and emotion (e.g. regret or Most influential seems to be senior to be more influential for supervisors. anticipating regret), powerlessness, management commitment and involvement, Affective and cognitive attitudes both H&S priority (e.g. over production), followed by fatalism, safety priority and risk play a role.

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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 A key barrier to implementing H&S staff (workload factors), safety equipment; availability of controls].


30, 31, 33. necessary steps to control hazards (especially middle management and supervisors). Particularly influential for SMEs.

controls. An indication of level of organisational support to lower-level management.

17. Personality/Characteristics [Flexible, innovative, principled; risk taking propensity; charisma / transformational style58; openness & trust in others].

(Personal)

7, 11, 12, 31. 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.

18. Demographics [Position/role -who reports to and who reports to the; role clarity; gender; industry sector; type of operation; accident/incident/illness rates].

(Organisational/Cultural & Personal)

10, 34. Some evidence to suggest demographics influence behaviour at director level and that gender may influence behaviour (less certain).

Likely to link in with control, role clarity and cultural influences.

19. Employee Attitudes & Motivation [Level of subordinate cooperation, including supervisors;

11, 12, 14, 26. Some evidence that influences management behaviour, but one study found employee expectations of improvements to be less

May be more influential in SMEs as managers/directors have more direct contact with workers than larger

58 See Glossary.

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workability with controls; comfort; expectations of improvement].


influential than managers’ own expectations, economic benefits, management commitment and training.

organisations.

20. Environmental [Changing nature of work; pressure from suppliers & contractors].

(External)

26, 37. Seems to influence management, but amount of influence is uncertain and few papers looked at this.

May be more influential for SMEs.

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7.4 APPENDIX 4: QUALITY RATINGS

Factor 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 � 6/6 papers report as a significant influence (consistent findings). � 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).

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9. Risk perception S � 6/6 papers report as a significant influence (consistent findings). � 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 M � 8/10 papers report as a significant influence/moderator, 2/10 as a of making possible influence/moderator (generally consistent findings). engineering � 8/10 cross sectional studies, 1/10 case study, 1/10 literature improvements review (theoretical based on 15 studies).

12. Perceived and S � 2/2 papers report as a significant influence. actual control � 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. Self- S � 3/3 papers report as a significant influence efficacy/confidence � 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 attitude-behaviour 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).

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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.

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Published by the Health and Safety Executive 04/11



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.


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Prepared by the Health and Safety Laboratory for …to correspond with their lack of appreciation of the long-latency nature of noise. HSE HSE should consider ways of overcoming this