Psychological distress in the workplace: The indirect contribution of work organization conditions to work performance
Bibliographic record
Abstract
BACKGROUND: Psychological distress affects between 5 and 27% of the general population [1]. Workers facing stressful work conditions are especially at high risk for experiencing psychological distress [1]. OBJECTIVES: To evaluate the association between work organization conditions and work performance via psychological distress. While the individual contribution of work organization conditions to psychological distress and work performance has been examined in the scientific literature, their combined influence on work performance remains relatively unknown. METHODS: To adjust for design effects, we relied on cluster sampling (employees working in organizations). MPlus was used to conduct path analyses [2]. RESULTS: While psychological demands, number of hours worked, and job insecurity were positively associated with psychological distress, job recognition was negatively associated with it. In the same vein, irregular work schedules and job insecurity seem to be negatively associated with work performance. On the one hand, skill utilization, decision latitude, recognition, and job promotion, all seemed to be positively associated with employee's work performance. On the other hand, psychological demands, number of hours worked, and job insecurity were negatively and indirectly associated with work performance. CONCLUSIONS: Understanding the indirect association between work variables and workers' psychological distress could promote their work performance. Understanding this association could help shed light on the difficulties employees with psychological distress face while meeting their job requirements. The results of this study should serve as a reminder to intervene on work organization conditions.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".