‘They go the extra mile, the extra ten miles . . .’: examining Canadian medical tourists’ interactions with health care workers abroad
Bibliographic record
Abstract
The patient-health care worker relationship can have important implications for people’s health. This chapter provides insights into how patients relate with health care workers abroad, while engaging in medical tourism. Presenting the findings of a thematic analysis that examines 32 telephone interviews with former Canadian medical tourists, the authors discuss participants’ views on clinical interactions with health care workers abroad. The thematic analysis of the interviews led to two main findings: 1) participants perceived that health care workers took a team-based approach and were available and accessible to patients beyond what they had experienced at home; and 2) medical tourists felt that care providers acknowledged their needs and established informal, comfortable relationships that some maintained on return to Canada. The narratives of Canadian medical tourists demonstrate that the medical tourism industry is selling a style of care that patients perceive as highly personalized, attentive, and empathetic. The authors’ findings contribute to understanding what leads individuals to participate in medical tourism. However, it is important not to overemphasize patient satisfaction in medical tourism, which may obscure other important aspects of the treatment experience, such as continuity of care and actual health outcomes.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".