Nursing students’ attitudes toward patient-centred care in the United Kingdom
Bibliographic record
Abstract
Background : Respecting the uniqueness of each individual as part of person-centred approach is central to the provision of high quality nursing care. Valuing people as individuals with different needs and aspirations are attitudes to care-giving that student nurses need to develop. There is however, a scarcity of literature which focuses on assessment of student nurses’ patient-centred attitudes. Aim : To examine patient-centred attitudes among pre-registration nursing students. Design : A validated survey tool developed by Rolfe was used to measure the patient centred attitudes of nursing students in a U.K. University. Methods : The patient-centred attitudes of 149 student nurses were measured using a Patient-Centred Multi-Choice Questionnaire. Standard descriptive analyses were performed. Results : Female student nurses (n=119) undertaking undergraduate pre-registration nurse education, 20- to 29- years-old and in their third year of study dominated the sample group. The mean Patient-Centred Multi-Choice Questionnaire scores for the majority of the sample groups fell within the noticeably therapeutic attitude range. Those that scored highest within the noticeably therapeutic attitude range were males, under 20- years-old, second-year students and students studying children’s health. Conclusion: The relatively high levels of patient-centred attitudes which were evidenced, particularly the results from the male students, is reassuring. The conclusions drawn have implications for nurse recruitment strategies, assessment of prospective student patient-centred attitudes and the teaching, learning and assessment strategies deployed by nurse educators.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".