Psychosocial Work Conditions and Mental Health: Examining Differences Across Mental Illness and Well-Being Outcomes
Bibliographic record
Abstract
OBJECTIVES: Psychosocial work conditions are determinants of mental illness among worker populations. However, while the focus on negative aspects of mental health has generated important contributions to the development of workplace interventions, there is less evidence on the factors that support the positive aspects of mental well-being. This study aimed to examine the association between psychosocial work conditions and mental health outcomes among a representative sample of Canadian workers; and to assess whether the relationships are consistent across measures of mental illness versus mental well-being. METHODS: Population-based data were obtained from the cross-sectional 2012 Canadian Community Health Survey. Psychosocial work conditions were measured using an abbreviated version of the Job Content Questionnaire. For mental illness, we focused on major depressive episodes, generalized anxiety disorders, and bipolar disorders in the past 12 months, as measured using Composite International Diagnostic Interview criteria. Mental well-being was defined as having flourishing mental health, based on items from the Mental Health Continuum-Short Form. Regression models provided odds ratios (ORs) and fitted probabilities for the relationship between work conditions and mental health, adjusting for covariates. RESULTS: Higher levels of job control, social support, and job security were associated with being free of disorders (ORs ranging from 1.08 to 1.15) as well as having flourishing mental health (ORs ranging from 1.10 to 1.14). Lower physical effort was associated with decreased odds of having flourishing mental health (OR 0.89). Psychological demands were not associated with any of the mental health outcomes in the fully-adjusted models. The overall pattern of these relationships was consistent across the two outcome models, although there was evidence of heterogeneity on the absolute probability scale. Specifically, there was a relatively stronger relationship between job control/social support/physical demands and well-being outcomes, compared with disorder outcomes. CONCLUSIONS: Psychosocial work conditions were associated with both negative and positive measures of mental health. However, mental illness and mental well-being may represent complementary, yet distinct, aspects in relation to psychosocial work conditions. Interventions targeting the psychosocial work environment may serve to improve both of these dimensions, although the measurement and examination of specific dimensions may be required to obtain an integrated and comprehensive understanding of mental health in the workplace.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".