Increasing coping and strengthening resilience in nurses providing mental health care: Empirical qualitative research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Research on coping and resilience is on the rise. However, there is a paucity of information addressing strengths, assets, competence or resilience that enable nurses to remain committed and cope in their profession despite the adversities they face in their working environment. OBJECTIVE: The purpose of this research was to explore and describe how to strengthen the resilience of nurses in a work environment with involuntary mental health care users. METHOD: An exploratory and descriptive research design, which is contextual in nature, was used. RESULTS: Narrative responses to two open-ended questions (How do you cope with providing mental health care to involuntary admitted mental health care users? and; How can your resilience be strengthened to provide mental health care to involuntary mental health care users?) yielded coping mechanisms and resilience strengthening strategies. CONCLUSION: Nurses caring for involuntary mental health care users are faced with challenging situations while they themselves experience internal conflict and have limited choices available to be assertive. To strengthen their resilience, the following factors should be taken into account: support, trained staff, security measures and safety, teamwork and in-service training and education.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it