Examining nursing students’ learning through reflective analysis using Ray’s Transcultural Caring Dynamics in Nursing and Health Care Theory
Bibliographic record
Abstract
BACKGROUND: Critical reflection empowers nursing students understanding as they become caring health professionals. Clinical nursing staff must have cultural sensitivity and empathy to provide culturally relevant care that meets the needs of patients from diverse cultures and ethnicities. Currently, the nursing profession is facing a shortage of nurses, which challenges the quality of care in Taiwan and the global community. An important mission of education is to cultivate nursing students with the professional competence to provide appropriate care to patients and families. This study explored nursing students' reflections on the meaning of caring in professional nursing. METHOD: Data were collected from the written reflections of 32 who completed their basic professional nursing courses at a Taiwanese university. A reflective thematic analysis guided by Ray's theory of Transcultural Caring Dynamics in Nursing and Health Care, highlighting the dimensions of caring, transcultural ethics, transcultural context, and universal sources (spirituality), was used to provide an understanding of how students viewed integrative patient-centred caring, and how they gained self-awareness and insights into their family relationships. FINDINGS: Four themes were derived from students' reflective documents. The identified themes included building a caring experience to meet individuals' physical and psychological needs; learning caring ethics by respecting individual's integrity and rights; family, school peers, and communities affecting the caring experience, and exploring teaching and learning approaches to enhance the caring experience. CONCLUSIONS: Findings from students' reflections indicate that individual patient needs should be considered when providing appropriate nursing care. Additionally, multiple teaching-learning strategies demonstrated their effectiveness in enabling nursing students to develop self-awareness in seeking an understanding of culturally appropriate care decisions.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".