Need for Recovery as an Early Sign of Depression Risk in a Working Population
Bibliographic record
Abstract
OBJECTIVE: Insights into early indicators of depression in workers are needed to inform indicated depression prevention programs. This study looked at how a high Need for Recovery (NFR) is related to a higher likelihood of a depressive disorder. Second, the added value of considering NFR over traditional work-related risk factors for depression was investigated. METHODS: A cross-sectional population-based sample of 2188 Canadian workers measuring Job Strain, NFR, and Depression. Logistic regression of the risk of a depressive disorder was performed with Job Strain and NFR as predictors. RESULTS: An elevated depression risk high was associated with a high NFR [odds ratio (OR) 8.3, confidence interval (CI) 6.8 to 10.2], but not with high job strain (OR 1.0; CI 0.82 to 1.25). CONCLUSIONS: NFR may have value for indicated depression prevention.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".