A Long Way from Home Investigation of Work Stress and Remoteness in the Mining Industry Funding: APA, UniSA top-up, MAQOHSC Scholarship Wes McTernan (E): wes.mcternan@unisa.edu.au
Presentation Overview • What and why • Theory • Qualitative Research • Quantitative Research • Practical Implications • Thesis progress Wes McTernan (E): wes.mcternan@unisa.edu.au
Economic Considerations The Growth in Australian Mining Employment Figures (1985-2013) Wes McTernan (E): wes.mcternan@unisa.edu.au
Economic Considerations ABS (2011) • High salary average ($117,500) • High profit (43%) • 3 rd largest mining country in the world • 19% of GDP • Mining industry effects everyone in Australia Wes McTernan (E): wes.mcternan@unisa.edu.au
Why • Recent industry growth • “Backbone” of Australian economy • Atypical work rosters • Tough working conditions • Environmental exposure • Remoteness • Long hours • Media interest • (i.e. 2015 parliamentary enquiry) • Lack of empirical research Important but challenging work Wes McTernan (E): wes.mcternan@unisa.edu.au
Broad aims • Identify the unique experience of work stress and health in the mining industry • Identify the role of isolation and remoteness in the experience of mining workers • Identify future industry trends Wes McTernan (E): wes.mcternan@unisa.edu.au
Stress Theory • Explain the experience of stress • What factors in the workplace elicit stress (stressors) • How does stress manifest? Wes McTernan (E): wes.mcternan@unisa.edu.au
Theoretical Framework Yerkes-Dodson Law (1908) Wes McTernan (E): wes.mcternan@unisa.edu.au
Theoretical Framework The Extended JDR Framework Wes McTernan (E): wes.mcternan@unisa.edu.au
Qualitative Research • Lack of empirical research on the psychological health of mining workers • Interviews guide the quantitative component of the project • Experience the industry Wes McTernan (E): wes.mcternan@unisa.edu.au
Qualitative Research Wes McTernan (E): wes.mcternan@unisa.edu.au
Qualitative Research Wes McTernan (E): wes.mcternan@unisa.edu.au
Qualitative Research Emerging project model Wes McTernan (E): wes.mcternan@unisa.edu.au
Qualitative Research Study Findings: Co-workers adopted family-type support roles. “These people become your family essentially” “Because they’re away from their families, people create a family ” “Here it’s a close -knit family ” “We kind of joke sometimes we know each other too well…. We’re like family ” Wes McTernan (E): wes.mcternan@unisa.edu.au
Quantitative Research Chapter IV: AWB Data • 2,793 working Australians (48%M 52%F) • 112 Mining Workers (84%M 16%F) • 12 month time lag • NSW, WA (2009-2010) • Vic, WA, NT, ACT (2010-2011) The Australian Workplace Barometer Project is the result of jointly funded projects funded by: • Australian Research Council (ARC) Discovery Grant: Working wounded or engaged? Australian work conditions and consequences through the lens of the Job Demands-Resources Model • ARC Linkage Grant: State, organisational, and team interventions to build psychosocial safety climate using the Australian Workplace Barometer and the StressCafé • SafeWork SA, and • Safe Work Australia. Wes McTernan (E): wes.mcternan@unisa.edu.au
Hypotheses Wes McTernan (E): wes.mcternan@unisa.edu.au
Analyses • Cross lagged Structural Equation Model (SEM) Mplus v6.11 • Compare models to find most appropriate model (causal, reverse causal, reciprocal) • Interaction terms added to best model Wes McTernan (E): wes.mcternan@unisa.edu.au
Results Wes McTernan (E): wes.mcternan@unisa.edu.au
Conclusion Findings suggest a circumstantial component to social support. Work environments that are more proximate or encourage greater employee interaction are likely to have more alleviative sources of social support. Wes McTernan (E): wes.mcternan@unisa.edu.au
Chapter V • Develop a scale that captures the unique experience of Work-Life Conflict (WLC) associated with working remotely (i.e. FIFO) • Compare its efficacy against the most commonly used WLC measure in the literature • 131 Australian participants • 55 mining workers • 76 partners Wes McTernan (E): wes.mcternan@unisa.edu.au
The following questions are about how work can affect your home and personal life. How well do you agree with the following statements? Strongly Disagree Slightly Neither Slightly Strongly Agree Agree Disagree Disagree Agree Agree nor Disagree 1. My job makes it difficult to maintain social relationships 1 2 3 4 5 6 7 outside of work 2. I find I miss a lot of social activities and opportunities 1 2 3 4 5 6 7 because of my work (such as birthdays and playing sports) 3. My job makes it difficult to form new friendships or 1 2 3 4 5 6 7 romantic relationships 4. My work arrangement makes it difficult to fulfil 1 2 3 4 5 6 7 social responsibilities (such as helping a friend move house or attending a funeral) Wes McTernan (E): wes.mcternan@unisa.edu.au
Table 5 Summary of Hierarchical Regression Analysis for Variables Predicting Depression Variable b t sr ² R R² D R 2 Step 1 .49 .24 Group -.23 -2.99** -.26 WFC .42 5.36*** .43 Step 2 .60 .36 .12*** Group -.39 -4.97*** -.40 WFC .17 1.90* .14 RWLC .45 4.91*** .35 ***p = <.001, **p = <.01, *p= <.05. Group, 1= partner, 2= mining worker. WFC = Work-Family Conflict. RWLC = Remote Work-Life Conflict. b = standardised coefficient. Wes McTernan (E): wes.mcternan@unisa.edu.au
Table 6 Summary of Hierarchical Regression Analysis for Variables Predicting Sleep Variable b T sr ² R R² D R 2 Step 1 .47 .22 Group -.33 -4.16*** -.33 WFC .31 3.97*** .31 Step 2 .58 .33 .11*** Group -.48 -6.00*** -.44 WFC .07 0.79 .06 RWLC .44 4.66*** .34 ***p = <.001, **p = <.01, *p= <.05. Group, 1= partner, 2= mining worker. WFC = Work-Family Conflict. RWLC = Remote Work-Life Conflict. b = standardised coefficient. Wes McTernan (E): wes.mcternan@unisa.edu.au
Chapter V Summary • We developed a tool to assess the unique experience of WLC by mining workers • This tool reflects atypical spatial and temporal conflict between work and non-work domains • This tool was better at predicting depression and sleep problems among mining workers Wes McTernan (E): wes.mcternan@unisa.edu.au
Depression Prevalence Among Mining Workers Wes McTernan (E): wes.mcternan@unisa.edu.au
Wes McTernan (E): wes.mcternan@unisa.edu.au
Wes McTernan (E): wes.mcternan@unisa.edu.au
Key Findings • Mining workers have high rates of depression • Partners of miners also have high rates of depression, suggesting high negative spill-over • Longer swings were associated with much greater rates of depression, approaching MDD Wes McTernan (E): wes.mcternan@unisa.edu.au
Key Findings • Mining workers and partners experience a unique type of WLC associated with an inability to participate in social events/commitments that are important for psychological wellbeing (i.e. sport, hobbies) Wes McTernan (E): wes.mcternan@unisa.edu.au
Key Findings • FIFO rosters lead to a degradation in social relationships at home – but an increase in the support received from co-workers • In the absence of usual support networks, co- workers adopt additional support roles Wes McTernan (E): wes.mcternan@unisa.edu.au
Key Areas for Intervention • Roster Length (Time away from home) • Social Support (co-worker relationships) • Sleep • Depression Wes McTernan (E): wes.mcternan@unisa.edu.au
Examination Results “This thesis presents a well -designed and soundly executed series of studies that seek to identify and assess the specific psychosocial conditions impacting on the health of remote miners, their families and the organisations in which they work. The experiences of miners working in remote locations have been largely overlooked in the academic literature, given the importance of this sector to the economic prosperity of many countries, the candidate should be commended for pursuing this line of enquiry.” Examiner 1 Wes McTernan (E): wes.mcternan@unisa.edu.au
Examination Results “I believe this dissertation is a first rate piece of work and requires no alterations.” Examiner 2 Wes McTernan (E): wes.mcternan@unisa.edu.au
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