Bibliographic record
Abstract
BACKGROUND: In a formal needs assessment, conducted prior to the Canadian Headache Society's recent national continuing education workshop, participants expressed particular enthusiasm for enhancing their own communication skills or their teaching of those skills. OBJECTIVES: Responding to both interests, this paper offers a practical conceptual framework for thinking systematically about how to improve physician-patient communication to a professional level of competence. METHODS: The three-part, evidence-based framework first defines communication in medicine in terms of five underlying assumptions about communication and the learning of communication skills. It then discusses three categories of communication skills (content, process, and perceptual skills) and six goals that physicians and patients work to achieve through their communication with each other. The second part of the framework explores "first principles" of effective communication and includes a brief look at the historical context that has significantly influenced our thinking about, and practice of communication in health care. Part three of the framework describes one approach for delineating and organizing the specific skills that research supports for communicating effectively with patients - the Calgary Cambridge Guide. RESULTS: It is clear from the literature that better physician communication skills improve patient satisfaction and clinical outcomes and that good communication skills can be taught and learned. CONCLUSIONS: It is important that physicians learn the principles of good physician-patient communication and apply them in clinical practice. Medical education programs at all levels should include teaching of physician-patient communication.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".