Demands, control, and support: A meta-analytic review of work characteristics interrelationships.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The job demands-control-support model (DCS; Karasek, 1979) is an influential theory for understanding how work characteristics relate to employee well-being, health, and performance. However, previous research has largely neglected theory-building regarding the interrelationships between job demands, control, and support. We remedy such theoretical underdevelopment by reviewing and integrating theory on the relationships between demands, control, and support to develop five hypotheses. We test our hypotheses within a meta-analytic framework using a set of 106 studies. Our results show negative demands-supervisor support and demands-coworker support relationships, but no significant demand-control relationship. Our findings also indicate positive control-supervisor support and control-coworker support relationships. Using the meta-analytic effect sizes, we also estimate two competing structural equation models intended to discern which theoretical model using DCS work characteristics to predict occupational strain and well-being is more consistent with our data. Our results suggest that job control and both sources of social support should be treated independently, as opposed to indicators of a shared latent factor, in terms of their prediction of well-being and job demands. Our study offers support for the usefulness of the DCS and more modern conceptualizations of the working environment in understanding the employee work experience and for predicting important work outcomes. (
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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 it