The most significant change for Colombian medical trainees going transformative learning on cultural safety: qualitative results from a randomised controlled trial
Bibliographic record
Abstract
Abstract Background Cultural safety training is not yet standard in Colombian medical education. If incorporated, it could address currently adversarial interactions between health professionals and the 40% of people who use traditional medicine practices. In 2019, a randomised controlled trial tested the impact of cultural safety training for medical students using participatory serious game design. The quantitative evaluation showed improved cultural safety intentions of Colombian medical trainees. We report here a qualitative evaluation of the most significant change perceived by trial participants. Methods This qualitative descriptive study used the most significant change technique. We invited the trial participants engaged in clinical settings to describe stories of change in their supervised clinical practice that they attributed to the intervention. Using a deductive thematic analysis based on a modified theory of planned behaviour, two independent reviewers coded the stories and, by consensus, created themes and sub-themes. Results From 27 stories of change, we identified seven themes and 15 subthemes: (a) Conscious knowledge: benefits of cultural safety training, consequences of culturally unsafe behaviour, cultural diversity and cultural practices; (b) Attitudes: respect and appreciation for cultural diversity, openness, and self-awareness; (c) Subjective norms: positive perception of cultural practices and less ethnocentrism; (d) Intention to Change; (e) Agency to accept cultural diversity and to prevent culturally unsafe actions; (f) Discussion; and (g) Action: better communication and relationship with patients and peers, improved outcomes for patients, physicians, and society, investigation about cultural health practices, and efforts to integrate modern medicine and cultural health practices. Conclusion The narratives illustrated the transformative impact of cultural safety training on a results chain from conscious knowledge through to action. Our results encourage medical educators to report other cultural safety training experiences, ideally using patient-related outcomes or direct observation of medical trainees in clinical practice. Trial registration Registered on ISRCTN registry on 18/07/2019. Registration number: ISRCTN14261595.
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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 | 0.036 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".