“You don’t want to lose that trust that you’ve built with this patient…”: (Dis)trust, medical tourism, and the Canadian family physician-patient relationship
Bibliographic record
Abstract
BACKGROUND: Recent trends document growth in medical tourism, the private pursuit of medical interventions abroad. Medical tourism introduces challenges to decision-making that impact and are impacted by the physician-patient trust relationship-a relationship on which the foundation of beneficent health care lies. The objective of the study is to examine the views of Canadian family physicians about the roles that trust plays in decision-making about medical tourism, and the impact of medical tourism on the therapeutic relationship. METHODS: We conducted six focus groups with 22 family physicians in the Canadian province of British Columbia. Data were analyzed thematically using deductive and inductive codes that captured key concepts across the narratives of participants. RESULTS: Family physicians indicated that they trust their patients to act as the lead decision-makers about medical tourism, but are conflicted when the information they are managing contradicts the best interests of the patients. They reported that patients distrust local health care systems when they experience insufficiencies in access to care and that this can prompt patients to consider going abroad for care. Trust fractures in the physician-patient relationship can arise from shame, fear and secrecy about medical tourism. CONCLUSIONS: Family physicians face diverse tensions about medical tourism as they must balance their roles in: (1) providing information about medical tourism within a context of information deficits; (2) supporting decision-making while distancing themselves from patients' decisions to engage in medical tourism; and (3) acting both as agents of the patient and of the domestic health care system. These tensions highlight the ongoing need for reliable third-party informational resources about medical tourism and the development of responsive policy.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".