Job Uncertainty and Health Status for Nurses During Restructuring of Health Care in Alberta
Bibliographic record
Abstract
The Alberta health care system experienced dramatic changes after provincial funding cuts to health care from 1993 to 1996. As a result, stressors for nurses increased. The question of whether job uncertainty, working conditions, cognitive appraisal, and coping strategies influence the health of registered nurses in a context of health care restructuring was examined. Lazarus and Folkman's Transactional Model of Stress was used as the conceptual framework. A total of 271 registered nurses employed in a large, urban, acute-care teaching hospital responded to a self-administered survey questionnaire. Using multiple regression analysis, depression and self-reported physical health were analyzed. The data suggest that the threat of being placed on recall, having a coworker bumped or laid off, and perceived job security were adversely related to physical health. High primary appraisal of threat was associated with high levels of depression and poor physical health. In addition, the findings suggest that various coping strategies had both buffering and exacerbating effects on physical health and depression.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".