The combined effects of job demand and control, effort-reward imbalance and work-family conflicts on the risk of major depressive episode: a 4-year longitudinal study
Bibliographic record
Abstract
PURPOSE: Work-related psychosocial factors may precipitate the onset of depression. In occupational mental health research, there are three widely used theoretical models, namely, job demand and control (JD-C), effort-reward imbalance (ERI) and work-family conflicts (WFC). However, the interaction between these models and their combined effect on the risk of major depression in the workplace is largely unknown. The aim of this study is to examine the longitudinal combined effects of JD-C, ERI and WFC on the risk of major depression in the working population. METHODS: Longitudinal data (2008-2013) were collected on randomly selected participants (n=4200) from the working population of the province of Alberta, Canada, at baseline and 1-, 2-, 3- and 4-year follow-up. Data about JD-C, ERI, WFC and major depression were collected by trained interviewers using a computer-assisted telephone interviewing method. Generalised estimating equations for longitudinal modelling were used. RESULTS: (OR 1.56, 95% CI 1.25 to 1.96; OR 1.33, 95% CI 1.16 to 1.52), respectively. The combined effects of JD-C and ERI, ERI and WFC, and WFC and JD-C on the risk of major depression were as follows: OR 1.71, 95% CI 1.22 to 2.42, OR 2.47, 95% CI 1.99 to 3.49 and OR 2.21, 95% CI 1.48 to 3.30, respectively. The relative excess risks attributable to the interactions were statistically non-significant. CONCLUSIONS: Work-related psychosocial factors are associated with increased risk of major depression over time, but their combined effect is not synergistic. The effects of the factors depicted in the three occupational health models on the risk of major depression appear to be additive.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".