Patient perspectives on surgical handover quality: a mixed-methods survey
Bibliographic record
Abstract
BACKGROUND: In-hospital handover of patient care is an essential but high-risk professional activity that often lacks transparency for patients. The purpose of this survey was to gain insight into surgical patients' perceptions of handover communications between doctors, incorporating patient and public involvement to enhance accessibility and understanding. METHODS: A cross-sectional, mixed-methods survey was developed with patient and public involvement and distributed to general surgery patients in two University Teaching Hospitals between 24 October 2023 and 21 July 2024. Comparative analyses of quantitative data were performed using McNemar's test for paired nominal data and Wilcoxon rank-sum test for continuous data. Free-text responses underwent thematic analysis to validate and expand on quantitative findings. Patient and public involvement partners contributed to study design, methodology, and the final manuscript. RESULTS: = 14.53, p = 0.0002). Patient perceptions of the handover process were generally positive; although satisfaction declined significantly with weekend handovers (p < 0.05). Thematic analysis identified four themes: (1) the impact of poor inter-professional communication, (2) the importance of teamwork, (3) external factors influencing handover effectiveness, and (4) patient nonchalance about their care. The use of patient and public involvement in this study improved survey accessibility and understanding of the concept and importance of handover. CONCLUSIONS: This study shows limited prior awareness of handover between doctors among surgical patients, especially the potential hazards that can arise if performed poorly. Patient and public involvement improved accessibility and understanding of the topic; however, challenges such as adequate training for meaningful engagement remain.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".