Assessing the Psychosocial Work Environment in Relation to Mental Health: A Comprehensive Approach
Bibliographic record
Abstract
OBJECTIVES: Prevailing job stress models encourage a multidimensional view of the psychosocial work environment and highlight the role that multiple co-occurring stressors play in the aetiology of mental health problems. In this study, we develop a latent typology of psychosocial work environment profiles to describe how a comprehensive array of job stressors are clustered in the Canadian labour market. We also examine the association between these latent psychosocial work environment profiles and several indicators of mental health. METHODS: Data were collected from 6408 workers who completed the Canadian National Psychosocial Work Environment Survey. Psychosocial work exposures were measured using standard items from the Copenhagen Psychosocial Questionnaire. We employed latent profile analyses to identify groups of individuals with similar psychosocial work environment profiles. We used log-linear regression models to examine the association between latent psychosocial work environment profiles and burnout, stress, and cognitive strain. RESULTS: Four distinct groups with highly divergent psychosocial work environment profiles were identified. Adjusting for a range of demographic and socioeconomic factors, latent psychosocial work environment profiles were strongly related to mental health. Individuals who reported exposure to a comprehensive array of psychosocial job stressors (11% prevalence) reported the highest probability of burnout (PR: 7.51, 95% confidence interval [CI]: 5.56-10.15), stress (PR: 8.98, 95% CI: 6.20-13.0), and cognitive strain (PR: 7.29, 95% CI: 5.02-10.60). CONCLUSIONS: Findings suggest that psychosocial work stressors are tightly clustered in the Canadian labour market, and that the clustering of work stressors is strongly associated with adverse mental health outcomes. Future scholarship may benefit from adopting a more comprehensive approach to the assessment of psychosocial job quality as a determinant of health and well-being.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".