Integrating Psychological Well-Being and Self-Care Behaviors Into Undergraduate Nursing Education Curriculum
Bibliographic record
Abstract
AIM: The aim of this study was to review literature on integrating psychological well-being and self-care behaviors into the university undergraduate nursing education curriculum. BACKGROUND: Burnout has been recognized as a key contributing factor to nursing shortages. Interventions aiming to improve coping skills and reduce stress have been shown to be effective. Learning coping skills during nursing education would benefit students greatly during their study and beyond. METHOD: The literature review searched four electronic databases including CINAHL, Medline, Embase, and Web of Science to select relevant peer-reviewed articles. RESULTS: Seven studies met the inclusion criteria and were included in this review. Most showed that building resilience and improving self-care behaviors have positive effects on nursing students' psychological well-being. CONCLUSION: To enhance coping skills, reduce stress, and improve well-being in nursing students, university nursing programs should integrate psychological well-being and self-care behaviors into their nursing curricula.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".