Challenges in family practice related to informed and shared decision-making: a survey of preceptors of medical students.
Bibliographic record
Abstract
1leading to important adverse consequences. 2 It can be a communication challenge for clinicians to involve patients in informed and shared decision-making (ISDM). We defined the “competencies” needed for ISDM 3 in order to address this problem systematically through medical education. These competencies are communication skills related to building of partnerships; eliciting of preferences for receiving information and playing a role in decision-making; exploring of ideas, concerns and expectations; presenting of choices and evidence; reaching a decision and resolving conflict; and agreeing on an action plan and follow-up. In this study, we asked, What are the most frequent and challenging situations that require ISDM skills experienced by family practice preceptors of medical students? The information could be used to refine training in communication skills, because students and preceptors are likely to be motivated to learn approaches to difficult and common problems. It has been reported that the “difficult patient” occurs in 10%–20% of primary care encounters, 4 but the terms used in the substantial “difficult patient” literature do not seem to be congruent with the “difficulties” that physicians may have in engaging patients in ISDM. Some examples that do seem relevant have been suggested by Platt and Gordon: 5 “nonadherence,” “the list maker,” “the patient’s companion,” “the patient bearing literature” and, in a survey of general practitioners’ frequent problems, “patient’s noncompliance with treatment and follow-up,” “sharing understanding of the problem with the patient” and “differences in expectations between physician and patient.” 6
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| 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; both teacher heads agree on what is shown here.
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".