Workplace STRESS Among Psychiatric Nurses
Bibliographic record
Abstract
Vicarious trauma and burnout are serious manifestations of workplace stress. Both can have substantial consequences for health care professionals, health services, and consumers. This article reports results of a study examining the prevalence, distribution, correlates, and predictors of vicarious trauma and burnout among registered psychiatric nurses (RPNs). A survey was distributed to all practicing RPNs in Manitoba, Canada (N = 1,015). The survey contained the Maslach Burnout Inventory, the Traumatic Stress Institute Belief Scale (i.e., a measure of vicarious trauma), and a section on symptoms of posttraumatic stress disorder (PTSD). The RPNs were found to be experiencing high levels of emotional exhaustion (i.e., high burnout) and even higher levels of personal accomplishment (i.e., low burnout). No significant differences were found between respondents' total scores on the Traumatic Stress Institute Belief Scale and instrument norms for mental health care professionals. Predictors of burnout and vicarious trauma also are presented in this article. Stress experienced by RPNs, as well as strengths on which to build, clearly are evident in the study results. Strategies for reduction in workplace stress may benefit psychiatric nurses, clients, and health services.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".