Psychological and social work factors as predictors of mental distress: a prospective study.

• Main Authors: Live Bakke Finne, Jan Olav Christensen, Stein Knardahl
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2014-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC4105444?pdf=render

Studies exploring psychological and social work factors in relation to mental health problems (anxiety and depression) have mainly focused on a limited set of exposures. The current study investigated prospectively a broad set of specific psychological and social work factors as predictors of potentially clinically relevant mental distress (anxiety and depression), i.e. "caseness" level of distress. Employees were recruited from 48 Norwegian organizations, representing a wide variety of job types. A total of 3644 employees responded at both baseline and at follow-up two years later. Respondents were distributed across 832 departments within the 48 organizations. Nineteen work factors were measured. Two prospective designs were tested: (i) with baseline predictors and (ii) with average exposure over time ([T1+T2]/2) as predictors. Random intercept logistic regressions were conducted to account for clustering of the data. Baseline "cases" were excluded (n = 432). Age, sex, skill level, and mental distress as a continuous variable at T1 were adjusted for. Fourteen of 19 factors showed some prospective association with mental distress. The most consistent risk factor was role conflict (highest odds ratio [OR] 2.08, 99% confidence interval [CI]: 1.45-3.00). The most consistent protective factors were support from immediate superior (lowest OR 0.56, 99% CI: 0.43-0.72), fair leadership (lowest OR 0.52, 99% CI: 0.40-0.68), and positive challenge (lowest OR 0.60, 99% CI: 0.41-0.86). The present study demonstrated that a broad set of psychological and social work factors predicted mental distress of potential clinical relevance. Some of the most consistent predictors were different from those traditionally studied. This highlights the importance of expanding the range of factors beyond commonly studied concepts like the demand-control model and the effort-reward imbalance model.