Insights from Nursing Students about Factors Affecting and Strategies Supporting their Mental Health
Bibliographic record
Abstract
Introduction: Nursing students experience high stress and mental health issues. It is essential to pay adequate attention to students’ mental health so they are trained to deliver quality patient care in complex settings. In order to provide a healthy environment to student nurses, it is essential that nursing students’ voices are heard. This study aims to explore nursing students’ perceptions about factors that influence their mental health and understand strategies that support mental health during nursing education. Methods: The study used an exploratory descriptive qualitative design to achieve the objective. Purposive sampling was used to recruit nursing students from a university representing undergraduate and graduate nursing programs. Data were collected using four focus group discussions. All discussions were audio recorded and transcribed. Coding was generated by the research team to drive key themes and sub themes. Results: The 28 participants identified teachers’ attitude, university environment and family responsibilities as key factors influencing their mental health. They also recommended several strategies for nursing institutions to promote students’ mental health during training. Conclusion: Nursing students are the future of healthcare systems. It is important that their mental health is given priority during nursing training. Promoting mental health would help nursing institutions create environments that foster health and well-being of students. These findings may also be useful for promoting mental health of students in other healthcare disciplines.
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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 | 0.000 | 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) | 0.000 | 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".