Understanding the clinical dilemmas that shape medical students' ethical development: questionnaire survey and focus group study
Bibliographic record
Abstract
Background A patient decision aid (PDA) is a tool for shared decision making (SDM), which emphasises patient empowerment. It is useful in chronic diseases and when there are multiple, no best single treatment option. Although SDM is prevalent in Western countries, its use is limited in Chinese societies, where the adoption of a paternalistic approach is strong. Here, we report the development, acceptance and pilot test results of a PDA targeted at Chinese patients with primary open-angle glaucoma (POAG). Methods We developed a PDA designed for use in Chinese patients with POAG. Recruited subjects were given our PDA. Baseline evaluation included decision conflict scale (DCS), validated glaucoma adherence questionnaires and glaucoma knowledge questionnaire. Subjects were briefed through the PDA and instructed to read it that day. Three to four weeks later, follow-up questionnaire as described above were conducted with the addition of acceptance questionnaires. Results Data from 65 subjects were available. The PDA was well received among subjects. DCS improved from 48.9±20.4 at baseline to 34.3±20.3 during follow-up, with P<0.01. Validated medication adherence questionnaires and knowledge showed improvement from baseline, which was statistically significant. Conclusions The use of PDA among Chinese subjects with POAG demonstrated positive reception and acceptance. Evaluation of its initial effects shows improvement in DCS, medication adherence and glaucoma knowledge. The implementation of SDM and PDA among Chinese subjects with POAG is encouraged. Future studies with randomised design and later evaluation time points can further reveal the impacts of PDA among Chinese subjects with POAG.
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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 | 0.017 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".