The Contribution of Work and Non‐work Factors to the Onset of Psychological Distress: An Eight‐year Prospective Study of a Representative Sample of Employees in Canada
Bibliographic record
Abstract
The Contribution of Work and Non‐work Factors to the Onset of Psychological Distress: An Eight‐year Prospective Study of a Representative Sample of Employees in Canada: Alain Marchand, et al. School of Industrial Relations, University of Montreal, Canada Objectives This study examined how occupation and work organization conditions contributed, over 8 yr, to the onset of psychological distress after adjusting for non‐work and individual characteristics. Methods The data came from the five cycles (Cycle 1=1994–1995, Cycle 5=2002–2003) of Statistics Canada's National Population Health Survey. A sample of 5,270 workers nested in 1,122 neighborhoods and aged 15 to 55 yr with no psychological distress at baseline was analyzed with discrete time survival multilevel regression models. Results The onset of psychological distress decreased over time. Occupation was not significant, whereas social support at work decreased the risk. Substantial effects for non‐work and individual factors were found, including neighborhood, social support outside the workplace, demographics, physical health, personality traits, and life habits. Conclusions This study found that work characteristics made a limited contribution to the onset of psychological distress, but social support in the workplace clearly proved to be an important protective factor. Enterprises must pay special attention to how colleagues and supervisors act to help workers complete tasks.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".