The Implementation of Open Disclosure in Asian Culture in Singapore: A systematic literature review
Bibliographic record
Abstract
Objective: Open Disclosure is the process of open and honest discussion between a clinician and the patient and family when an adverse clinical event occurs while the patient is in care or treatment. While open disclosure is now a mandatory practice in many developed countries like the United Kingdom, Australia, the United States and Canada, it has yet to be made mandatory in Singapore. In most healthcare institutions in Singapore, the Clinical Governance or Quality Service Management Department manages the governance of patient safety and medical errors. This systematic literature review aims to understand the effect of Asian culture relating to apologies because of the implementation of Open Disclosure in Singapore's healthcare system. Method: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was used to review and synthesize the contemporary literature qualitatively. Results: This study identified that there are links between culture and apologies and in particular, the expression and acceptance of the apology. This study explored and identified the effects of Asian culture on open disclosure, specifically on apologies, and established that Asian and western cultures offer and accept apologies differently. Also, the study established the public's view and demand for open disclosure and the impact of culture on how a person presents oneself in delivering an apology. Conclusion: The study could only identify five high-quality articles in this systematic literature review; there were no papers on the mindset and perceptions of Asian healthcare professionals on apologies and open disclosure found. This present study has demonstrated a significant research gap that is a significant opportunity for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".