Student’s Experiences on Learning Therapeutic Relationship: A Narrative Inquiry
Bibliographic record
Abstract
Despite the importance of the therapeutic relationship on nursing practice, the literature regarding teaching and learning therapeutic relationship is limited. This paper discussed how an undergraduate nursing student learned therapeutic relationship in an acute care setting. Narrative inquiry was applied as a research methodology. The student's reflection served as the narrative in this paper. Collaboratively, researchers conducted data analysis, common themes were drawn, and a summative narrative was presented. Based on the student's narrative, a three-dimensional model, including practical knowledge, theory, and reflection, has been created as our summative narrative. This model suggests that, to facilitate a learning process on creating therapeutic nurse-patient relationship, practical knowledge is the foundation, theory is a leading guide, and constant reflection is a learning tool which transforms learning into a reflective and meaningful experience. To promote learning on therapeutic relationship, nurse educators should emphasize the importance of both practical knowledge and theory. Constant reflection as a learning tool should be encouraged and embedded in nursing curriculum. Diverse approaches of reflection should be promoted.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| 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".