Effort-Reward Imbalance at Work and Psychological Distress
Bibliographic record
Abstract
OBJECTIVES: To examine whether the psychometric properties of the effort-reward imbalance (ERI) at work scales could be replicated with post-myocardial infarction (post-MI) patients and to measure the criterion validity through its association with psychological distress. METHODS: A cross-sectional survey was conducted among 814 patients (739 men and 75 women) who had returned to work after their first MI and who were followed up by telephone at an average of 2.2 years after their baseline interview (1998-2000). The psychological demands scale of the Karasek Job Content Questionnaire was used to measure effort. Reward was measured with nine items from the original reward scale by Siegrist plus two proxy items. Exploratory and confirmatory factor analyses were used to test the theoretical structure of ERI. Using log-binomial regression models, we evaluated the association between ERI scales and psychological distress measured with the 14-item Psychiatric Symptom Index. RESULTS: ERI scales and subscales demonstrated adequate internal consistencies. Exploratory factor analysis using oblique (promax) rotation yielded a three-factor solution with items representative of extrinsic effort (Factor 1) and reward subscales (Factors 2 and 3). Confirmatory factor analysis demonstrated a good fit with the data. The internal consistencies and discriminant validities of the ERI scales were satisfactory. Furthermore, effort, reward, and ERI ratio were significantly associated with psychological distress (adjusted prevalence ratio [PR] = 1.71, 95% confidence interval [CI] = 1.26-2.31; PR = 1.63, 95% CI = 1.16-2.29; and PR = 1.70, 95% CI = 1.17-2.47, respectively). CONCLUSIONS: The psychometric properties of the ERI scales were generally reproduced among post-MI patients. The associations with psychological distress supported the criterion validity of the ERI scales in this population.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".