Occupational stress in the Australian nursing workforce: a comparison between hospital‑based nurses and nurses working in very remote communities
Bibliographic record
Abstract
Objective: To compare workplace conditions and levels of occupational stress in two samples of Australian nurses. Design: The research adopted a cross‑sectional design, using a structured questionnaire. Setting: Health centres in very remote Australia and three major Australian hospitals. Subjects: 349 nurses working in very remote Australia and 277 nurses working in three major hospitals in South Australia and the Northern Territory. Main Outcome Measures: The main outcome measures were psychological distress (assessed using the General Health Questionnaire‑12), emotional exhaustion (assessed using the Maslach Burnout Inventory), work engagement (assessed using the Utrecht Work Engagement Scale‑9) and job satisfaction (assessed using a single item measure based on previous relevant research). Results: Results revealed that nurses working in major Australian hospitals reported higher levels of psychological distress and emotional exhaustion than nurses working very remotely. However, both groups report relatively high levels of stress. Nurses working very remotely demonstrated higher levels of work engagement and job satisfaction. There are common job demands and resources associated with outcome measures for both nurses working very remotely and nurses working in major hospitals. Conclusion: This research has implications for workplace interventions and the retention of staff in both hospitals and remote area health care facilities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".