Predictors of medical student interest in Indigenous health learning and clinical practice: a Canadian case study
Bibliographic record
Abstract
BACKGROUND: Including content on Indigenous health in medical school curricula has become a widely-acknowledged prerequisite to reducing the health disparities experienced by Indigenous peoples in Canada. However, little is known about what levels of awareness and interest medical students have about Indigenous peoples when they enter medical school. Additionally, it is unclear whether current Indigenous health curricula ultimately improve students' beliefs and behaviours. METHODS: A total of 129 students completed a 43-item questionnaire that was sent to three cohorts of first-year medical students (in 2013, 2014, 2015) at one undergraduate medical school in Canada. This survey included items to evaluate students' sociopolitical attitudes towards Indigenous people, knowledge of colonization and its links to Indigenous health inequities, knowledge of Indigenous health inequities, and self-rated educational preparedness to work with Indigenous patients. The survey also assessed students' perceived importance of learning about Indigenous peoples in medical school, and their interest in working in an Indigenous community, which were examined as outcomes. Using principal component analysis, survey items were grouped into five independent factors and outcomes were modelled using staged multivariate regression analyses. RESULTS: Generally, students reported strong interest in Indigenous health but did not believe themselves adequately educated or prepared to work in an Indigenous community. When controlling for age and gender, the strongest predictors of perceived importance of learning about Indigenous health were positive sociopolitical attitudes about Indigenous peoples and knowledge about colonization and its links to Indigenous health inequities. Significant predictors for interest in working in an Indigenous community were positive sociopolitical attitudes about Indigenous peoples. Knowledge about Indigenous health inequities was negatively associated with interest in working in an Indigenous community. CONCLUSIONS: Students' positive sociopolitical attitudes about Indigenous peoples is the strongest predictor of both perceived importance of learning about Indigenous health and interest in working in Indigenous communities. In addition to teaching students about the links between colonization, health inequities and other knowledge-based concepts, medical educators must consider the importance of attitude change in designing Indigenous health curricula and include opportunities for experiential learning to shape students' future behaviours and ultimately improve physician relationships with Indigenous patients.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".