Integration of traditional and complementary medicine into medical school curricula: a survey among medical students in Makerere University, Uganda
Bibliographic record
Abstract
OBJECTIVE: To describe the disposition and sociodemographic characteristics of medical students associated with inclusion of traditional and complementary medicine in medical school curricula in Uganda. DESIGN: A cross-sectional study conducted during May 2017. A pretested questionnaire was used to collect data. Disposition to include principles of traditional and complementary medicine into medical school curricula was determined as proportion and associated factors determined through multivariate logistic regression. PARTICIPANTS AND SETTING: Medical students in their second to fifth years at the College of Health Sciences, Makerere University, Uganda. Makerere University is the oldest public university in the East African region. RESULTS: 393 of 395 participants responded. About 60% (192/325) of participants recommended inclusion of traditional and complementary medicine principles into medical school curricula in Uganda. The disposition to include traditional and complementary medicine into medical school curricula was not associated with sex, age group or region of origin of the students. However, compared with the second year students, the third (OR 0.34; 95% CI 0.17 to 0.66) and fifth (OR 0.39; 95% CI 0.16 to 0.93) year students were significantly less likely to recommend inclusion of traditional and complementary medicine into the medical school curricula. Participants who hold positive attributes and believe in effectiveness of traditional and complementary medicine were statistically significantly more likely to recommend inclusion into the medical school curricula in Uganda. CONCLUSIONS: Inclusion of principles of traditional and complementary medicine into medical school curricula to increase knowledge, inform practice and research, and moderate attitudes of physicians towards traditional medicine practice is acceptable by medical students at Makerere University. These findings can inform review of medical schools' curricula in Uganda.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".