Hospital downsizing, individual resources, and occupational stressors in nurses
Bibliographic record
Abstract
Abstract Restructuring and downsizing are occurring increasingly throughout the workplace. As a result, many individuals are losing their jobs. Many others experience job insecurity as a result of the threat of downsizing. As with most other work spheres, several hospitals are closing, resulting in thousands of layoffs. Since nurses constitute one of the main groups employed in hospitals, they are faced with increasing job shortages. This study examines psychological reactions of nurses in response to stressors resulting from hospital downsizing. Individual resources, particularly coping strategies and self-efficacy, can affect the extent to which individuals experience distress as a result of downsizing. A self-report, anonymous questionnaire was filled out and returned by 1363 nurses employed in hospitals in Canada. Results of this study show that amount of work was a consistent and significant stressor in nurses. The greater the nurse's workload, the greater her emotional exhaustion, cynicism, depression and anxiety. Further results reported here indicated that control coping and self-efficacy lessened distress on the job and increased job satisfaction, while escape coping was associated with greater psychological distress and less job security.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 teacher head, 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".