Demands, control and support: A meta-analytic review of work characteristic interrelationships
Bibliographic record
Abstract
The job demands-control-support model (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 5 main effect hypotheses and 3 moderator research questions. We test our hypotheses within a meta-analytic framework using a set of 106 studies. Our results show negative relationships between demands-control, demands-supervisor support and demands-coworker support. Our findings also indicate a positive control-supervisor support relationship, but no control-coworker support relationship. Moreover, the proportion of female participants moderated 3 effect sizes—suggesting the importance of gender segregation on work characteristics. Finally, average organizational tenure moderated 2 effect sizes, suggesting that firm specific human capital and coworker networks are important for job perceptions. The current study provides groundwork for developing and refining organizational behavior theories by demonstrating how different work characteristics are related. Importantly, our study gives direction to investigation of cognitive, affective and social processes underlying work characteristics as critical areas for investigation in future research.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".