The relationship of work-related psychosocial risk factors with depressive symptoms among Hungarian workers.<i>Preliminary results of the Hungarian Work Stress Survey</i>
Bibliographic record
Abstract
INTRODUCTION: Research has shown that psychosocial stress acts as a risk factor for mental disorders. AIM: The present study aims at processing the preliminary results of the Hungarian Survey of Work Stress, concerning the relationship between depressive symptoms and work stress. METHODS: Cross-sectional survey among Hungarian workers was carried out (n = 1058, 27.5% man, 72.5% woman, age 37.2 years, SD = 11 years). Psychosocial factors were measured using the COPSOQ II questionnaire, while BDI-9 was used for the assessment of depressive symptoms. Statistical analysis was carried out applying Spearman's correlation and logistic regression. RESULTS: A quarter of the workers reported moderate or severe symptoms of depression (BDI≥19). The study confirmed the association between depressive symptoms and work-family conflict (OR = 2.21, CI: 1.82-2.68), possibilities for development (OR = 0.76, CI: 0.59-0.97) meaning of work (OR = 0.69, CI: 0.59-0.89) and commitment (OR = 0.60, CI: 0.47-0.78). CONCLUSION: The results point toward the need of such organizational measures that allow for the reduction of psychosocial stress.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".