Clinical instruction in mental health nursing: students’ perceptions of best practices
Bibliographic record
Abstract
OBJECTIVES: Negative clinical educational experiences for student nurses are predictors of negative attitudes and perceptions towards mental health. In clinical education, instructors take on this important role often with little to no formal training. This study explored nursing students' perceptions of instructional best practices in mental health clinical education. METHODS: A qualitative descriptive design was used, and 10 Canadian baccalaureate nursing (BN) students were interviewed. These students had completed a six-week practicum on an acute inpatient psychiatric unit in either their second, third or fourth year of study. RESULTS: Through thematic analysis, three themes were identified: (1) Students valued feeling prepared at the beginning of the clinical placement. (2) Students felt empowered when instructors encouraged self-direction. (3) Students appreciated positive role modeling by their instructors. CONCLUSIONS: Suggestions for clinical teaching strategies are made to mitigate student stress, increase confidence, and address the influence of mental health stigma on learning.
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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 | 0.005 | 0.019 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".