Factors Associated with Leading Indicators of Work Health & Safety: Findings from a National Workplace Health & Safety Survey

Transcription

1 Factors Associated with Leading Indicators of Work Health & Safety: Findings from a National Workplace Health & Safety Survey Presenter: Dr Miriam H. Marembo 13 th Australian Injury Prevention & Safety Promotion Conference November 2017

2 Background Economic and social costs of work-related injury and illness account for about 4.1% of Australia s GDP [Safe Work Australia, 2015c]. Workplaces in Australia are becoming safer Evidenced by a steady reduction in lagging indicators Lagging indicators: Measures of harm that has already occurred e.g. incidence of workplace injuries [Government of Alberta, 2015]. There is a need to continue promoting better preventative WHS practices through using leading indicators. Leading indicators: aspects of workplace activities that can be used to improve OHS outcomes prior to an unwanted outcome occurring [Government of Alberta, 2015].

3 Objectives Compare the distributions for each leading indicator by demographic, workplace and occupation characteristics. To assess the degree of overlap and complementarity between three work health and safety (WHS) leading indicator measures. Assessing the degree of overlap or complementarity between leading indicators will help determine whether they all measure similar or unique aspects of prevention and action control.

4 Data Source: National Workplace Health and Safety Survey. Project was led by Monash University, with input from expert researchers from the University of Melbourne, the Institute of Work & Health and Deakin University. The survey was carried out via telephone and internet in June 2016 by Ipsos. 1,130 workers in Australia, aged 18 years and above, who were employed for at least 1 hour of paid work per week completed a 20 minute questionnaire. The questionnaire collected information on: Worker and workplace characteristics, Three leading indicators of work health and safety, The Psychosocial Job Quality (PJQ) scale The Occupational Health and Safety (OHS) vulnerability scale The Organisational Performance Metric-Monash University (OPM-MU), Lagging indicators of work health and safety. National labour force data [ABS 2010;2015a;2015b; 2016].

5 Leading indicators of WHS Indicator Focus Specific measure Risk/ vulnerability criteria Psychosocial Job Quality (PJQ) measure [Butterworth et al., 2011] Occupational Health and Safety (OHS) vulnerability scale [Lay et al., 2016] Organisational Performance Metric-Monash University (OPM-MU) [Shea et al., 2016] Job quality Exposure to OHS hazards at work 3 dimensions of worker protections The presence of OHS leading indicators in the respondent s workplace Job demands & complexity Job control Job security Effort reward fairness Overall PJQ Exposure to hazards Inadequate policies & procedures Inadequate awareness Inadequate empowerment Overall vulnerability Score = all responses for statements corresponding to the indicator Cut-off: scores in quartiles corresponding to the greatest difficulty. Exposure to 2 hazards on a weekly/ daily basis or exposure at any level to 4 specific hazards. Worker protections inadequate if they disagreed or strongly disagreed with 1 of the statements for each measure. OPM-MU score Score = all responses for 8 statements Cut-off: scores in the 1 st quartile corresponding to low OPM-MU.

6 Male Female < 35 years years years 55 years Australia Outside Australia English Not English Full time Part time <1 year 1 year White collar Blue collar Other Percentage Sample characteristics Sex Age Birth location Language Employment type # of employees Job tenure Occupation Total responses: 1,130 Compared to the ABS figures, our sample had fewer males & more females; fewer younger ( 44 years) & more older workers; fewer full-time & more part-time workers; more workers in white collar & fewer workers in blue collar occupations.

7 Percentage Leading indicators distribution Male Female < 35 years years years 55 years Australia Other English Other Sex Age Birth location Language Poor PJQ OPM-MU OHS vulnerability Significantly higher prevalence rates of: OHS vulnerability among younger (<35 years) workers compared to older workers, Low OPM-MU scores & OHS vulnerability among workers born in Australia compared to those born elsewhere.

8 Percentage Leading indicators distribution cont Full time Part time <1 year 1 year White collar Blue collar Other Employment type # of employees Job tenure Occupation Poor PJQ OPM-MU OHS vulnerability Significantly higher prevalence rates of: OHS vulnerability among part-time compared to full-time workers, OHS vulnerability among workers who have been employed in their current job for <1 year compared to those who have been in their current job for longer, OHS vulnerability among blue collar workers compared to workers in other occupations.

9 Overlap between leading indicators 444 [39.9%] Low job quality 170 [15.3%] 75 [6.7%] OHS vulnerable 114 [10.2%] 126 [11.3%] 41 [3.7%] 71 [6.4%] Low OPM-MU 72 [6.5%] Total responses: 1, % met the criteria of being at risk on one of the 3 measures. 16.8% were at risk on two leading indicators. 11.3% were at risk on all three leading indicators. There is some overlap in the constructs being measured by the 3 leading indicators. Each indicator also captures something unique corresponding to the type of prevention & control action being measured.

10 Summary Distributions for each leading indicator by demographic, workplace and occupation characteristics. Distribution varied by age, birth location, employment type, job tenure & occupation. Higher prevalence of OHS vulnerability among younger workers (<35 years), workers born in Australia, part-time workers, workers who have been employed in their current job for < 1 year & blue collar workers. Higher prevalence of low OPM-MU scores among workers born in Australia. Degree of overlap & complementarity between three WHS leading indicator measures. Approximately a third of the respondents were at risk on one of the 3 measures. 16.8% were at risk on two and 11.3% were at risk on three leading indicators. There is an overlap in some constructs being measured by the 3 measures, but each measure also captures something unique corresponding to the type of prevention & control being measured.

11 References Australian Bureau of Statistics. (2010). Australian Labour Market Statistics, Oct 2010, cat. no Australian Bureau of Statistics. (2015a). Education and Work, Australia, May Table 13 - Highest level of eduactional attainment: Level-By state or territory of usual residence and sex, persons aged years, cat. no Australian Bureau of Statistics. (2015b). Labour Force, Australia, Detailed, Quarterly, May 2015, cat. no Australian Bureau of Statistics. (2016). Labour Force, Australia, Detailed, Quarterly, Aug 2016, cat. no Butterworth, P., Leach, L. S., Strazdins, L., Olesen, S. C., Rodgers, B., & Broom, D. H. (2011). The psychosocial quality of work determines whether employment has benefits for mental health: results from a longitudinal national household panel survey. Occupational and Environmental Medicine, 68(11), doi: /oem Government of Alberta, (2015). Leading indicators for workplace health and safety: A user guide., 22/03/2017, from Lay, A. M., Saunders, R., Lifshen, M., Breslin, C., LaMontagne, A., Tompa, E., & Smith, P. (2016). Individual, occupational, and workplace correlates of occupational health and safety vulnerability in a sample of Canadian workers. American Journal of Industrial Medicine, 59(2), doi: /ajim Safe Work Australia (2015c). The Cost of Work-Related Injury and Illness for Australian Employers, Workers and the Community: Canberra. Shea, T., De Cieri, H., Donohue, R., Cooper, B., & Sheehan, C. (2016). Leading indicators of occupational health and safety: An employee and workplace level validation study. Safety Science, 85, doi:

12 Acknowledgements Co-authors: Dr Behrooz Hassani-Mahmooei, Ms Clare Scollay, Prof. Helen De Cieri, Prof. Tony La Montagne, Dr Jason Thompson, Associate Prof. Peter Smith & Prof. Alex Collie. This project was partly funded by enforceable undertakings received via WorkSafe Victoria, through the Institute for Safety Compensation & Recovery Research. The authors would like to acknowledge the contributions of staff of the WorkSafe Victoria & ISCRR for their review of the survey content & support for the project. The authors also thank the survey participants.

13 Thank you Contact: Dr Miriam H. Marembo Phone: