RR866. Influencing dutyholders behaviour regarding the management of noise risks

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1 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

2 Health and Safety Executive Influencing dutyholders behaviour regarding the management of noise risks 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

3 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 write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or 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 ACKNOWLEDGEMENTS The authors would like to thank our HSE customer Tim Ward and colleagues Anne Wright, Beverley Bishop and Simon Armitage for their support throughout the research. Our special thanks go to the 230 companies that participated in this research for giving their time and thoughts generously. We hope that the report does justice to their experiences and views. As a token of our appreciation, donations were made to the following charities: Deafness Research UK; The Royal National institute for the Deaf; The British Tinnitus Association; and Hearing Dogs for Deaf People. ii

4 EXECUTIVE SUMMARY ISSUES INVESTIGATED Anecdotal evidence suggests that dutyholders do not always engage in good practice for noise control despite the plentiful information and advice available to them. This research aims to provide an understanding of how to influence dutyholders 1 to ensure that the risks associated with noise exposure are adequately controlled. The following three research questions are addressed: (1) What factors influence employers decisions and practices in controlling noise risks? (2) What is the relative importance of these factors? and (3) How do these factors vary between high and low performing organisations? KEY FINDINGS 1. Noise management is influenced by three factors: (i) managers own knowledge/awareness of noise as a significant, long-term health risk, as well as knowledge of technical and organisational controls to reduce noise, (ii) the health and safety values or culture of the company towards prevention of ill health and (iii) company size. Of critical importance are: (Knowledge/awareness) Managers general lack of regard for the importance of noise risks and potential health consequences given its long-latency nature. A critical gap is understanding what technical/organisational controls exist and would work for them in practice in order to make an informed choice about which controls to implement. This includes those managers who regularly access noise information sources. (Culture) A tendency for companies to be reactive rather than proactive with noise management (e.g. monitoring audiometry results versus taking a holistic approach to select and monitor controls). An ongoing challenge faced by many managers is knowing how best to encourage appropriate behaviour amongst their workers to make sure that they properly use the selected controls, although the focus of many managers is only on personal hearing protection. (Company size) The size of the company was found to influence the approach taken to noise management; the smaller a company the increased likelihood of reduced quality in the management of noise risks. Small companies find it more difficult than their larger counterparts to find practical and affordable solutions often because they have limited resources (finance and time) for health and safety. There is a tendency for these companies to become preoccupied with taking accurate noise measurements rather than focusing on implementing the right solutions. In addition, while larger companies adopted a more strategic and educational approach to noise management, smaller companies considered machinery replacement as the only ideal solution. 2. These three factors (knowledge/awareness, culture and size) seem to represent the heart of noise management. Even though eight other factors were not shown to be significant influencers (i.e. business motivators, resources, information/communications, autonomy/competence, self-efficacy, attitudes, role as Director and Health and Safety Manager), they are likely to be mediated by the primary three factors. 3. Similar findings were found when comparing high and low performers. Performance was influenced by (1) managers knowledge of what they should be doing in practice, (2) 1 The term dutyholder is used quite loosely to refer to the manager responsible for noise and so may not necessarily refer to employers/dutyholders. This research recognised that whilst the power to make financial decisions resides at the top, practical noise decision-making may be delegated to lower-level management. iii

5 prevailing cultural norms towards ill health prevention, and (3) company size. Managers in high performing (typically large) companies therefore had better knowledge of organisational and technical noise control measures, and had made some progress with translating this knowledge into practice (i.e. implementing these controls and promotion of positive health and safety attitudes/cultural norms). In addition, (4) the level of health and safety resource was found to influence performance levels. High performers had better access to such resources than did low performers. It comes as no surprise, therefore, that the low performers involved in this research tended to be the smaller companies (mostly micros) whereas the high performers were mostly medium-sized or large companies. Hearing protection seemed to be preferred, especially by low performers, because it was considered simple and cheap. Even those small companies guided by external consultants opted for hearing protection without considering whether this was the most effective and cost-effective solution or not in the long-term. 4. Only health surveillance and worker education seemed to be externally motivated, largely through insurers. Those companies undertaking health surveillance (mostly high performing) were doing so because they (i) wanted to protect themselves against potential future health claims and (ii) saw it as a way to gauge the success of implemented noise controls providing evidence that they worked, despite occupational hearing loss taking many years in most cases for symptoms to manifest. Companies were generally unaware, however, of the need to train workers in hearing protection use; managers considered this to be common sense. 5. Future noise interventions need to address the three primary factors found to influence managerial decision-making and practices, namely, knowledge/awareness of noise risks and associated technical/organisational controls, health and safety culture and company size. Regarding company size, interventions need to be appropriately tailored to the constraints (both physical and financial) that companies, particularly small companies, might be facing. Interventions designed to raise managerial knowledge/awareness should not only include the appropriate selection of controls, but also awareness of the long-latency nature of noise. Such knowledge may in turn positively influence prevailing cultural attitudes of the importance of noise as an occupational health risk. The health and safety culture of an organisation should not be underestimated as this was found to be the most influential factor. What do these findings mean in practice? These findings highlight awareness raising and cultural change as key areas for HSE to target. In relation to awareness raising HSE could consider: Appropriately tailoring future noise messages to small manufacturing companies. Current noise guidance appears to be better suited to medium-sized and large companies than the vast majority of small companies that make up the sector. It is the smaller companies, however, that are the ones likely to be struggling to get to grips with what would work for them in practice (i.e. how to make improvements) that is feasible and affordable. The apparent preoccupation with measuring noise, even in circumstances where this may not be necessary, acts as a further barrier to making improvements. HSE needs to fill the gap between current information supplied to employers and the practical application of such guidance. Tailoring the guidance to small companies should in principle make this accessible to organisations of any size. In addition, pitching guidance at the level of similar rather than specific occupational health risks might help to reduce the burden. But, smaller companies need to be made aware of the existence of such guidance and where they can access this. iv

6 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 v

7 distinguishing between high and low performing companies. Such knowledge is valuable for HSE and industry in determining how best to improve the management of noise risks. The manufacturing sector was the focus of this research due to the high levels of noise that characterise the industry. Manufacturing consists of approximately 3.2 million employees; hence a substantial number of people are potentially exposed to unacceptable levels of noise. APPROACH A mixture of methods was used in this study to fully answer the three research questions. A questionnaire developed during a preceding pilot study was completed by 215 managers to identify the influential factors, including how these vary between high and low performing companies, and to gauge their potential level of influence. Interviews were also carried out with 15 managers to provide rich accounts of noise management in practice. Combining both methods enabled a clearer picture to be developed of the real influences on noise management than would be possible with one method alone. Using mixed methods also enhances the robustness of the research because it allows the findings from one source to be crosschecked with the other. The key messages from this research are consistent across participants and settings, which instils confidence that the findings present an accurate picture of the influences on managers responsible for noise in the manufacturing sub-sectors that participated in this research 2. 2 I.e. (1) food and beverages, (2) textiles, (3) wood/products of wood, (4) pulp/paper products, (5) printing, (6) rubber/plastic products, (7) other non-metallic minerals and (8) furniture. vi

8 CONTENTS 1 INTRODUCTION Issue addressed Research aims Background METHODOLOGY Research design Sample and data collection procedure Analysis techniques RESULTS What factors influence managers decisions and practices in controlling noise risks? What is the relative importance of these factors? How do these factors vary between high and low performing organisations? DISCUSSION AND CONCLUSIONS Response to the three research questions Interpretation of results Research caveats Issues for consideration Overall conclusion REFERENCES APPENDICES Appendix 1 Summary of fact-finding results Appendix 2 Pilot study methodology Appendix 3 Questionnaire Appendix 4 Interview protocol Appendix 5 Supplementary material - Sampling Appendix 6 Supplementary material Data analysis Appendix 7 Supplementary material - Results vii

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10 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 noise 3 and on the HSE website. This research was commissioned by HSE to provide an understanding of how to influence employers to better manage noise, ideally going beyond the provision of hearing protection to the adoption of technical (engineering) and/or organisational controls. 1.2 RESEARCH AIMS This research aims to identify the factors that influence managerial noise decision-making and practices and to ascertain how influential their effects are. In the context of the Health and Safety at Work Act ( ), 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 1

11 noisy conditions over the years combines with hearing loss that forms part of the natural ageing process that people realise how deaf they have become. As with other long-latency health conditions (e.g. asthma, cancer, Chronic Obstructive Pulmonary Disease), the tendency for noise-induced hearing loss to remain generally unnoticed until later in life may mean that employers overlook the immediate need to control noise risks. Discussion with HSE inspectors at the outset of this research highlighted the following as common observations during their interactions with dutyholders/managers on noise: Lack of acceptance of noise-induced hearing loss as a significant occupational health issue; Lack of application of technical/engineering and organisational noise controls, including health surveillance for employees considered to be at risk; Failure to access and understand available information on noise control; Failure to produce an action plan to reduce noise exposure levels; and Misunderstanding of the true cost, business benefits, ease of introduction and effectiveness of technical control compared with the provision of hearing protection. Understanding the drivers behind these perceptions and behaviours is vital for knowing how to intervene in order to make improvements. A review of the contemporary evidence base as part of this research highlighted, however, a paucity of studies directly examining factors that influence noise management. Most studies on noise were employee-focused, looking at the impact of noise on health and performance (e.g. 3-5) or the physiological effects of noise (e.g. 6, 7). Although a small number of studies addressed factors influencing the management of noise (e.g. 8-10), none had systematically assessed the specific knowledge, attitudes, values and beliefs that employers hold about noise and the influence of social, environmental and organisational factors, such as health and safety climate/culture. For this reason, the general health and safety literature was reviewed in order to extrapolate all the factors that potentially play an important role in the management of noise. The review identified 17 factors as having the potential to influence noise management, although these studies tended to focus on safety rather than health matters. The factors broadly fell under five overarching categories: (i) business (e.g. corporate reputation; 11, 12), (ii) legal (i.e. compliance with health and safety legislation; 13, 14), (iii) cultural/organisational (e.g. company values, health and safety resources; 15-19), (iv) external (e.g. information/communications; 20, 21) and (v) personal drivers (e.g. risk perception, managerial knowledge and competence; 11, 18, 22-24). The importance of these factors was unclear, however, as few studies had documented their relative strength. (The full literature review can be found in the accompanying Annex to this report). The literature review findings were substantiated by anecdotes of noise management in practice provided during interviews with a sample of six HSE inspectors. Taking two of the five overarching categories that emerged from the literature review as examples, namely, (i) potential business drivers and (ii) organisational/cultural drivers, inspectors anecdotes highlighted that for business drivers, fear of civil claims appeared to be more influential in recent years for motivating managers to implement noise controls than health and safety legislation. Achieving internal quality standards was also considered to exert greater influence than maintaining a good external reputation where health matters were concerned, particularly in large companies. Finally, employers often judged the cost and disruption to the business of controlling noise at source (e.g. retrofitting noise controls to existing machines) as being too great and thus resorted to issuing hearing protection. Anecdotes relating to 2

12 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 3

13 2 METHODOLOGY 2.1 RESEARCH DESIGN 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 triangulation 5 to be realised. This includes better measurement through minimising threats to internal validity, enabling a better understanding of how and why factors exert their influence, and generating more reliable and valid results (e.g. 26) Research stages There were three key stages to the research. Stage 1 - Preliminary fact-finding. As described in section 1.3, fact-finding included a literature review and interviews with six HSE inspectors. A systematic method was followed for the literature review to assess the relevance and quality of the available research and to gauge the potential strength of factors reported to influence managerial health and safety practices (see the accompanying Annex to this report). To increase the likelihood of obtaining an accurate reflection of current noise practice, HSE inspectors were selected for interview that had differing levels of experience with dutyholders in relation to noise management 6, and were based in different regions of the UK. A semi-structured format was followed to ascertain the noise controls implemented and types of behaviours seen in two organisations visited; one considered by inspectors to demonstrate good practice and the other showing a need for improvement. Five interviews were conducted face-to-face, one via videoconferencing, lasting between 50 and 85 minutes. Factors were extracted during thematic analysis of the data where the majority of inspectors (at least three) perceived these as influential for noise management. To minimise interpretation bias, two researchers conducted the analysis and checked one another s outputs. Stage 2 Design and piloting of research tools. Following approval of the research by HSE s Research Ethics Committee, the tools were piloted via 10 telephone interviews with dutyholders 5 The use of more than one method or source of data in the study of a social phenomenon so that findings may be crosschecked [27]. 6 Two specialists, two generalists and two occupational health inspectors took part. 4

14 or the manager responsible for health and safety 7, seven of whom subsequently completed the questionnaire (see Appendix 2 for further details on the methodology). A primarily qualitative approach was considered appropriate at this stage of the research to obtain rich data about the adequacy of the research tools for answering the three research questions (see section 1.2). It also provided a check as to whether the tools were appropriately worded and fit-for-purpose, not too time-consuming for dutyholders/managers. In general, the findings highlighted the benefit of triangulating findings from the quantitative and qualitative components to generate valuable insights into the influences on noise management. Stage 3 Main research. Fifteen semi-structured, in-depth interviews with dutyholders or managers responsible for noise were conducted. In addition, 800 postal questionnaires were distributed to a representative sample of 15 manufacturing sub-sectors. The remainder of this report describes the methodology adopted and the findings from the main research phase Questionnaire design Following best practice in survey design the questionnaire took around minutes to complete (see Appendix 3). It consisted of mostly closed items with Likert scales, appropriate for attitudinal and behavioural ratings (28). The questionnaire was designed around the 15 factors that emerged from the fact-finding research as potentially important determinants of dutyholders noise decision-making and practices (see section 1.3). A minimum of three items per factor was included to obtain reliable measures. Three of the 15 factors were merged with the remaining 12 factors, as shown in Box 2. Values/beliefs and noise risk perception were subsumed under attitudes towards health and safety and capability of making improvements naturally formed part of an assessment of resources. Streamlining the original 15 factors into 12 ensured that the questionnaire was comprehensive yet sufficiently brief. 1. Knowledge, awareness and understanding (of noise risks and controls) 2. Attitudes towards health and safety (values and beliefs and noise risk perception e.g. commitment, fatalism, concern for employee well being) 3. Self-efficacy (i.e. confidence in own ability to implement noise controls) 4. Control (i.e. autonomy to make noise-related decisions) 5. Skills/competence (to develop noise action plans, etc) 6. Resources (capability to make improvements e.g. time, staff, equipment, funds) 7. Information and communications (e.g. sources used and usefulness) 8. Compliance/legislation (i.e. fear of enforcement or civil proceedings) 9. Safety climate/culture (e.g. company values, communication channels) 10. Corporate reputation (both internally and externally) 11. Economic/financial (e.g. civil claims, insurance premiums) 12. Demographics (e.g. company size, managerial role) Box 2 Twelve factors measured by the questionnaire (bold represents merged factors) Appropriate outcome measures (dependent variables) were included for (i) perceived noise exposure levels (i.e. self-reported ratings of noise levels experienced by workers during the 7 Although the research targeted dutyholders, in some cases dutyholders had delegated noise decision-making to one of their managers. As such, the decision was made to interview the manager responsible for health and safety, dutyholder or otherwise. 5

15 most common noisy activities 8 ), (ii) perceived noise risks (i.e. the proportion of the workforce carrying out these noisy activities), and (iii) implemented noise controls (a selection of controls ranging from employee-focused to environmental modifications to technical/organisational). Both face and content validity 9 of the questionnaire was tested during the pilot study and through liaison with key project stakeholders. Testing the construct validity and reliability 10 of the measure formed part of the data analysis (see section 2.3.2) Interview protocol design A semi-structured interview protocol was developed that provided the opportunity to gather rich data relating to dutyholders/managers noise decision-making and practices (see Appendix 4). Such an approach allows a balance to be struck between consistencies across interviews to facilitate comparison with scope for further probing as necessary (29). The questions were designed to elicit insights into the 15 factors that emerged through the fact-finding research whilst being flexible enough to uncover any new factors. Topic areas included noise exposure levels and controls, the decision-making underpinning the selection of controls, noise information/training provided to staff, resources and support for implementing noise controls. 2.2 SAMPLE AND DATA COLLECTION PROCEDURE The research was conducted in the manufacturing sector due to the high levels of noise that characterise the industry. The sector consists of approximately 3.2 million employees 11 ; hence a substantial number of people are potentially exposed to unacceptable levels of noise at work Questionnaire Sample calculations. Given that this research aims to identify and determine the strength of factors that influence noise management, the sample size was chosen on the basis of power calculations. This reduces the likelihood of committing a Type II error with smaller sample sizes, i.e. incorrectly concluding that a given factor does not impact the behaviour of employers (30). Nevertheless, a Type I error remains likely due to the small sample size, i.e. a factor is shown to be influential (i.e. significant) when it might not be with a larger sample. Power calculations were based on a medium effect size: the average size of observed effects in various field studies shown in surveys of effect sizes (31). To achieve the desired power of 0.8 recommended by Cohen, a sample size of at least 200 was required for the planned quantitative analysis (see section 2.3.2), 200 to run the regression analysis and a minimum of 50 participants in each of the high and low performing groups (31). Distributing 800 questionnaires was considered sufficient to obtain the desired 200 responses. Response rates for employee postal surveys generally fluctuate between 30-50% (e.g. 32, 33). A 25% response rate allows for the possibility that noise may not be as high profile in companies as other health and safety concerns. Sample selection. Fifteen manufacturing sub-sectors were chosen to take part in this research in order to establish views from a broad sample and permit greater confidence that the findings accurately represent these sub-sectors. Each sub-sector was classified as either metallic or non-metallic as shown in Table 1. A random sample of approximately 7,000 companies 8 Level 1 - impossible to talk even when shouting in someone s ear; Level 2 - having to shout at a distance of one meter; Level 3 - having to shout at a distance of two meters; Level 4 - noise is intrusive, comparable to a busy street. 9 Face validity - It is obvious what it is measuring; Content validity - The content is representative of the area it intends to cover [28]. 10 Construct validity An accurate measure of the underlying construct(s) i.e. hypothetical constructs, [28]. 11 See 6

16 representing the 15 manufacturing sub-sectors was obtained through HSE s Library and Information Services, taken from the MINT database 12, which provides sufficient coverage of the UK private sector. Of the 800 questionnaires distributed, the sample was stratified to ensure that the number sent out to each metallic and non-metallic sub-sector was proportionate to their overall size; companies were randomly selected within each sub-sector. 302 questionnaires were administered to metallic companies and 498 questionnaires to non-metallic companies (see Table A5.1 in Appendix 5 for further details). To reflect the demographic make up of the manufacturing sector, mostly consisting of small companies 13 (with up to 49 employees 14 ), no more than 5% of questionnaires were sent to medium-sized ( employees) and large (250 plus employees) metallic (n=15) and non-metallic (n=25) companies. None of the 800 companies had experienced HSE enforcement action in the last two years or had previously taken part in the pilot study. Table 1 Metallic and non-metallic sub-sector groupings Metallic (SIC 15 Code) Basic Metals (27) Fabricated metal products (28) Machinery and equipment (29) Motor vehicles & trailers (34) Other transport equipment (35) Recycling (37.1) Non-Metallic (SIC code) Food and Beverages (15) Textiles (17) Wood/Products of wood (20) Pulp/Paper products (21) Printing (22) Rubber/Plastic products (25) Other non-metallic mineral (e.g. glass & ceramics) (26) Furniture (36.1) Recycling (37.2) Administration procedure. All questionnaires were addressed to the manager responsible for health and safety. An information sheet accompanied the questionnaire detailing the purpose of the research, what participation involves and how the data will be used with assurances of anonymity and confidentiality (see Appendix 3). The use of unique numbers as identifiers permitted participants to withdraw from the research at any time 16. Participants were asked to complete the questionnaire and return it to a member of the research team in a freepost envelope provided within a given timeframe. To encourage participation, a 5 donation was made to one of four relevant charities as chosen by participants. Response rates. Of the 800 postal questionnaires distributed, only 47 completed questionnaires were returned; a further 148 were returned to sender 17 (a response rate of 7%). Follow up telephone calls with a random selection of 80 of the 605 companies who had not returned the questionnaire revealed that a large number were either not manufacturing companies or were sole traders, the questionnaire therefore not being relevant to them. In order to obtain a minimum of 200 completed questionnaires, an additional 168 questionnaires were completed via telephone through an external contractor using an additional sample of 2,000 companies sourced through Dunn and Bradstreet. Of the 2,000 companies, 1,443 were contacted (a response rate of 12%). The same stratified sampling procedures were applied. In total, 215 questionnaires were completed (47 postal, 168 telephone). The obtained sample was fairly 12 A public database containing approximately 2.6m UK-wide company records. 13 See 14 Based on the Department of Trade and Industry s definitions of company size - see 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. 7

17 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 Site interviews Sample selection and recruitment. To ensure that companies had not had their level of awareness raised by having been involved in previous aspects of the research, 15 companies that were not issued a questionnaire were randomly selected for interview from the MINT sample. The aim was to recruit two small, two medium-sized, and two large companies from both the metallic and non-metallic groupings (12 in total), with the remaining three randomly selected from small companies in either the metallic or non-metallic categories. To ensure that the findings adequately addressed the 15 sub-sectors (see Table 1), attempts were made to secure one visit for each sub-sector (or SIC code). Dutyholders/managers did not volunteer, however, from Metallic recycling (37.1) and other transport equipment (35), Non-metallic textiles (17), printing (22) and furniture (36.1). Consequently, three metallic companies were recruited from machinery and equipment (29), two from basic metals (27), and two from fabricated metal products (28). Two companies were further recruited from the other non-metallic mineral (26) sub-sector. Although representation from all 15 sub-sectors was not obtained, the sample is considered to be fairly representative of the metallic and non-metallic sub-sectors sampled. Those sub-sectors where more than one company was recruited tended to represent the larger industries (e.g. machinery and equipment, fabricated metal products 18 ). A good spread of UK geographic regions was also obtained. Nevertheless, difficulty recruiting small companies 19 resulted in a substantial proportion of the sample (n=7) being medium-sized companies. (See Table A5.2 in Appendix 5 for full details.) Companies were recruited over the phone. Employers who volunteered to take part provided written consent and were provided with an information sheet detailing the purpose of the research, data use and storage, protection of anonymity and confidentiality. Site visit procedure. Visits generally lasted between 30 and 90 minutes. Following an initial site tour in which researchers collated contextual information relating to noise management, dutyholders/managers were interviewed on their premises for up to 90 minutes. With participants consent, interviews were recorded and transcribed. Finally, researchers examined relevant health and safety documentation (health and safety policy, risk assessments, etc) pertinent to noise control. 18 See 19 Lack of time was the key barrier to participation cited by employers. 8

18 2.3 ANALYSIS TECHNIQUES 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) Importance (Research Question 2) Quantitative: Frequencies, Correlations and Regression Qualitative: Thematic and Content Analysis Quantitative: Regression High versus low performers (Research Question 3) Quantitative: Mann Whitney-U Tests Qualitative: Thematic and Content Analysis Figure 1 Summary of analysis conducted to answer each research question Quantitative Research question 1 - Influencing factors. Correlations were conducted to check whether the conceptualisation of 11 of the 12 factors identified as having the potential to influence noise management in the fact-finding research (see section 2.1.3) was supported by the data. Workplace characteristics were excluded (factor 12), as these were categorical and thus not suitable for correlation analysis. A factor analysis would have provided a robust test on the factor structure and the extent to which they were mutually exclusive. There was an insufficient number of questionnaires returned, however, to permit a reliable and valid exploratory factor analysis (34). To compensate, internal consistency tests were run to check that the items making up each of the 11 factors were reliably measuring that factor. In addition, two (construct) validity tests were conducted in which (i) a second researcher crosschecked the first researcher s categorisation of questionnaire items for each factor, and (ii) a third independent researcher (not involved in the research) examined items falling under each factor to assign a name to each factor. To test whether the 11 factors significantly influence managerial noise decision-making and practices a multiple regression was conducted. A statistical (stepwise) method was selected, as no established theoretical model of the influences on noise management existed. The outcome 9

19 (dependent) measure was a calculated score for implemented noise controls ; a subjective indicator that reflected the extent that dutyholders/managers have gone to in order to protect their employees from noise risks. A score out of a total of 22 was assigned based on respondents answers to the item asking them to tick all the noise controls that they provided. A higher score denoted the use of higher-level, technical/organisational controls and a lower score showed that minimal action had been taken by the dutyholder/manager, mostly implementing worker-focused (basic) controls. This scoring accounted for the selection of up to three red herrings i.e. non-viable noise controls, which were included to gauge participants propensity towards social desirable reporting (i.e. tendency to respond in a way that makes them look good (28). (See Table A6.1 in Appendix 6 for scoring.) Descriptive analysis (frequencies and crosstabulations) was carried out on items not suitable for regression (e.g. scenario-based questions to measure participants knowledge and awareness 20 ). Research question 2 Importance of factors. The regression outputs were examined to see how much variance each factor explained in implemented noise controls and whether their unique and combined contribution was significant. Beta coefficients determined the predicted levels of improvement in implemented noise controls based on one unit increase in each factor. Research question 3 - High versus low performers. As shown in Table 2, participants were categorised into three groups, high, moderate or low performers, based on two scores: i. The outcome measure of implemented noise controls, a score out of 22. There was some degree of overlap between the high and low categorisation for companies that obtained scores ranging from 9 to 13. This overlap was considered acceptable on the premise that a score higher than 8 was unlikely if only basic controls had been implemented 21 and a score higher than 13 was unlikely unless higher-level controls had been implemented 22. As such, companies obtaining a score between 9 and 13 were more likely to be moderate performers. But, level of risk alongside implemented controls is important to differentiate between low and high performers. After all, implementing basic noise controls may be acceptable if noise levels are low or very few workers are exposed to noise. ii. A second outcome measure estimating risk to the business from noise based on perceived noise levels and the proportion of workers exposed to this noise. Companies were assigned to one of six categories and therefore obtained a score ranging from 1 to 6 depending on where they sat on the risk to the business from noise continuum. A score of 1 represented the highest risk (i.e. excessive noise levels with a high proportion of workers exposed). Conversely, a score of 6 represented the lowest risk (i.e. low noise levels and proportion of workers exposed). (See Figure A6.1 in Appendix 6 for categorisation.) Company classification. As shown in Table 2, high performing companies (shaded green) were defined as those that had implemented higher-level (technical/organisational) controls despite noise levels and worker exposure being perceived as low. On the other hand, low performing companies (shaded red) presented a high risk to employee health from noise yet tended to only have basic controls in place. The remaining companies were classified as moderate performers. Performance was therefore a composite of the level of risk and implementation of controls. Contrasting high and low performers in this way highlighted practices associated with better performance. Rather than issuing the small proportion of their workforce exposed to 20 Questions 9 and 10 in the questionnaire (see Appendix 3). 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. 10

20 noise with hearing protection, these companies had focused on noise reduction methods or were trying to eliminate noise from source. Intuitively, there appeared to be something culturally unique about these companies that distinguished them from the remaining groups, which were either doing what was necessary to comply (moderate performers) or were not adequately controlling noise risks (low performers). Further analysis was conducted to compare the high and low performers with the group of moderate performers (shaded yellow in Table 2) where noise presented a low risk to the business and worker-focussed controls were in place (mostly hearing protection). No differences emerged, however, between the low and moderate performers suggesting few differences in the practices of these companies. To gain an understanding of the differences between high and low performers the final analysis excluded the moderate performers. In line with the recommendation that a non-parametric test should be conducted when data is not normally distributed and equal variances between the groups cannot be assumed (35), a series of Mann Whitney-U tests were conducted to compare the high and low performers. This enabled isolation of the factors that differentiated between the high (n=60) and low (n=50) performing companies. Table 2 Categorisation of high (H), moderate (M) and low (L) performers Risk to the business from noise Highest risk (1) High risk (2) High to medium risk (3) Medium risk (4) Medium to low risk (5) Low risk (6) Implemented noise controls Up to 13 9 to 22 L M L M L M M M M M M H Qualitative Research question 1 - Influencing factors. Two types of qualitative analysis were conducted i.e. thematic and content. The former provided rich detail about influences on noise management through the extraction of higher-order and sub-themes. The latter enabled a systematic assessment of the frequency of the higher-level themes across participating companies, which provided a practical base from which to examine differences between company groupings (e.g. small versus medium/large companies, high versus low performers). For the thematic analysis, key themes were identified following a framework analysis approach for qualitative data that is advocated by the National Centre for Social Research, referred to as NatCen s qualitative analysis protocol (36). This comprised three stages. The first two stages involved development of a framework for capturing commentary and quotations from the management interviews. Relevant data gathered from the site tour and review of company health and safety documentation was also incorporated. Higher-level themes and sub-themes were then identified and agreed between two researchers to ensure valid analysis of the data (inter-rater reliability; see 37). The final stage of the analysis involved identification of any patterns in the data according to company groupings (e.g. size, performance levels). The content analysis was conducted by a sole researcher and checked by a second researcher. All companies were colour coded according to whether the higher-order themes that emerged in the thematic analysis (stage 1 of NatCen) were present in the data or not. Key differences between companies of different sizes (small, medium, large) were extracted. 11

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