“Teach for Dignity”: Longitudinal Evaluation of Training on Dignity-in-Care Relationships for Nursing Students
Bibliographic record
Abstract
BACKGROUND: Patient dignity is a critical component of health care; however, evidence suggests that it is often inadequately maintained, particularly among nursing students. PURPOSE: To assess the impact of a dignity-in-care training intervention on nursing students' knowledge and explore how they apply it in their practice after graduation. METHODS: This was a mixed-methods study involving second-year nursing students with interventions provided by a psycho-oncologist. Quantitative data were collected through pre- and post-training questionnaires on dignity, while qualitative data were obtained from focus groups and semi-structured interviews conducted 1 and 2 years after the training. The analysis included McNemar's test for quantitative data and thematic analysis for qualitative results. RESULTS: Sixty-four students completed the pre- and post-training assessments. Significant improvements were observed in emotional and psychosocial dignity-related domains; however, declines were noted in procedural domains. CONCLUSIONS: Future interventions should adopt a comprehensive approach, possibly co-led by nurses and psychologists, to uphold dignity in care.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".