A longitudinal study comparing the effort - reward imbalance and demand - control models using objective measures of physician utilization
Bibliographic record
Abstract
BACKGROUND: The objectives of this study were to compare the predictive validity of the demand-control and effort-reward imbalance models using objective measures of physician utilization. METHODS: Self-reports for psychosocial work conditions were obtained in interviews with 1,028 workers using the demand-control and effort-reward imbalance models. Physician utilization outcomes were obtained through linkage to the British Columbia Linked Health Database. Outcomes were any visit to a physician for mental health reasons and 30 or more physician visits for any reason. The predictive validity of both models was compared in a longitudinal study using logistic regression. RESULTS: Neither job strain nor effort-reward imbalance predicted either outcome. However, low esteem reward and low status control increased the risk for 30 or more physician visits by, respectively, approximately 60% and 30%. CONCLUSIONS: In a sample of middle-aged blue-collar current and ex-sawmill workers in Western Canada, followed prospectively, after controlling for sociodemographic and workplace confounders, and reducing the potential for adverse health selection into high-stress jobs, low esteem reward and low status control were associated with a significantly greater risk for 30 or more physician visits for any reason.
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 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 | 0.011 | 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 | 0.001 |
| 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".