Status quo of advanced cancer patients participating in shared decision- making in China: A mixed study
Bibliographic record
Abstract
Abstract Purpose Patients with advanced cancer are usually willing to participate in shared decision-making (SDM), but in clinical practice, the participation of patients is easily ignored due to many factors. This study aimed to analyze the current status of SDM among patients with advanced cancer in China and the related factors affecting patient participation. Methods A cross-sectional survey was conducted on 513 advanced cancer patients in 16 tertiary hospitals of China. The general situation questionnaire, the Control Preference Scale (CPS) and Perceived-involvement in Care Scale (PICS) were used to analyze the current status of SDM and influencing factors. Based on the Ottawa Decision Support Framework (ODSF), 17 advanced cancer patients were interviewed to explore the perceptions of advanced cancer patients on SDM. Results There is a difference between actual situation and expectation of patients' participation in decision-making tendency, and the statistically significant influencing factors were age, payment, and whether worried about the therapeutic effect. We also found the dynamic change of decision-making mode, the acquisition of disease information, the obstacles of decision-making participation and the role of family members would effect the type of patients' SDM. Conclusion The SDM status of advanced cancer patients in China is dominated by sharing, and in a continuous dynamic change. Influenced by Chinese traditional culture, family members play an important role in shared decision-making.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".