GPs' strategies in intercultural clinical encounters
Bibliographic record
Abstract
BACKGROUND: In North America and Europe, patients and physicians are increasingly likely to come from non-Western cultural backgrounds. The expectations of these patients may not match those of physicians. OBJECTIVE: To identify strategies used by GPs with patients from cultures other than their own. METHODS: We conducted a qualitative inductive study based on 25 semi-structured interviews with family physicians practising in Montreal, Canada. We elicited physicians' strategies when dealing with patients from a cultural background different from their own. We began by asking physicians to describe an encounter they found difficult and one they found easy. RESULTS: Physicians reported three types of strategies: (i) insistence on patient adaptation to local beliefs and behaviours; (ii) physician adaptation to what he or she assumed patients wanted; and (iii) negotiation of a mutually acceptable plan. Individual physicians did not adopt the same strategy in all situations. Their choice of strategy depended on the topic. When dealing with issues they felt deeply about, such as the autonomy of women, many physicians insisted on patient adaptation. Physicians used a patient-centred model of care, but had no framework to elicit information about patients' culture. CONCLUSIONS: A patient-centred model of care enables physicians to consult effectively despite a wide range of cultural differences between themselves and their patients. However, their lack of a conceptual framework for addressing cultural difference prevents systematic data collection and consideration of challenges to respect for individual autonomy. Physician training should include the provision of an explicit conceptual framework for approaching patients from a different culture.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| 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".