Putting informed and shared decision making into practice
Bibliographic record
Abstract
OBJECTIVE: To investigate the practice, experiences and views of motivated and trained family physicians as they attempt to implement informed and shared decision making (ISDM) in routine practice and to identify and understand the barriers they encounter. BACKGROUND: Patient involvement in decision making about their health care has been the focus of much academic activity. Although significant conceptual and experimental work has been done, ISDM rarely occurs. Physician attitudes and lack of training are identified barriers. DESIGN: Qualitative analysis of transcripts of consultations and key informant group interviews. SETTINGS AND PARTICIPANTS: Six family physicians received training in the ISDM competencies. Audiotapes of office consultations were made before and after training. Transcripts of consultations were examined to identify behavioural markers associated with each competency and the range of expression of the competencies. The physicians attended group interviews at the end of the study to explore experiences of ISDM. RESULTS: The physicians liked the ISDM model and thought that they should put it into practice. Evidence from transcripts indicated they were able to elicit concerns, ideas and expectations (although not about management) and agree an action plan. They did not elicit preferences for role or information. They sometimes offered choices. They had difficulty achieving full expression of any of the competencies and integrating ISDM into their script for the medical interview. The study also identified a variety of competency-specific barriers. CONCLUSION: A major barrier to the practice of ISDM by motivated physicians appears to be the need to change well-established patterns of communication with patients.
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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 | 0.132 | 0.137 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.059 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.004 | 0.025 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".