Physician behaviours that optimize patient‐centred care: Focus groups with migrant women
Bibliographic record
Abstract
BACKGROUND: No prior research studied how to implement patient-centred care (PCC) for migrant women, who face inequities in health-care quality. This study explored migrant women's views about what constitutes PCC and how to achieve it. DESIGN: We conducted a qualitative study involving three focus groups with migrant women living in Toronto, Canada, recruited from English language classes at a community settlement agency, used constant comparative technique to inductively analyse transcripts and interpreted themes against a published PCC framework. PARTICIPANTS: Twenty-three migrant women aged 25-78 from 10 countries participated. RESULTS: Women articulated 28 physician behaviours important to them across six PCC domains: foster a healing relationship, exchange information, address concerns, manage uncertainty, share decisions and enable self-care. They emphasized the PCC domain of exchanging information, which included 13 (46.4%) of 28 behaviours: listen to reason for visit, ask questions, provided detailed explanations, communicate clearly, ensure privacy and provide additional information. Women said that instead of practising these behaviours, physicians rushed through discussions, and ignored or dismissed their concerns and questions. As a result, women said that physicians may not fully understand their problem, and they may refrain from stating important details or avoid seeking care. CONCLUSIONS: This research characterized the lack of PCC experienced by migrant women and revealed specific physician behaviours to optimize PCC for migrant women. Research is needed to develop and evaluate the impact of strategies targeted at migrant women, physicians and health-care systems to support PCC for migrant women.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".