Objectives There is strong evidence of a relationship between psychosocial job stressors and mental health at the population level. There has been no longitudinal research on whether the experience of job stressors is also associated with greater mental health service use. We seek to fill this gap.
Methods The Household Income Labour Dynamics in Australia survey cohort was used to assess the relationship between exposure to self-reported psychosocial job quality and reporting attendance at a mental health professional during the past 12 months. We adjusted for time-varying and time-invariant confounders. The study was conducted in 2009 and 2013.
Results In the random effects logistic regression model, increasing exposure to psychosocial job stressors was associated with an increased odds of mental health service use after adjustment (one stressor: OR 1.26, 95% CI 1.01 to 1.56; two stressors: OR 1.33, 95% CI 1.02 to 1.73; three stressors: OR 1.82, 95% CI 1.28 to 2.57). However, once the between person effects were controlled in a fixed effects model, the within-person association between change in job stressors and change in mental health service use was estimated to be close to zero and not significant.
Conclusions More work is needed to understand the relationship between job stressors and service use. However, when taken with past findings on job stressors and mental health, these findings highlight the importance of considering policy and clinical practice responses to adverse working contexts.
- job stress
- mental health
- health services research
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Contributors The article was conceived by AM, who also conducted analysis. DP and PB contributed to analytic design, analyses and to the interpretation of results. ADLM contributed to analytic design and the interpretation of results. AM drafted the manuscript with feedback from all authors. All authors contributed to the final draft of the manuscript.
Funding AM was supported by a Victorian Health and Medical Research Fellowship. No financial disclosures were reported by the authors of this paper. DP was supported under Australian Research Council’s Discovery Early Career Awards funding scheme (project DE150100309). PB supported by ARC Future Fellowship (FT130101444) and a University of Melbourne Faculty of Medicine, Dentistry and Health Sciences Research Fellowship.
Disclaimer The findings and views reported in this paper are those of the author and should not be attributed to either DSS or the Melbourne Institute.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement This paper uses unit record data from the Household, Income and Labour Dynamics in Australia HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Social Services DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research Melbourne Institute). The data used in this paper was extracted using the Add-On Package PanelWhiz for Stata. PanelWhiz (http://www.PanelWhiz.eu) was written by Dr. John P. Haisken-DeNew (john@PanelWhiz.eu).
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