Student attitude towards integrative medicine in a Caribbean medical school
Bibliographic record
Abstract
Background: Patients in developed nations increasingly use Complementary and Alternative Medicine (CAM) and Integrative Medicine (IM). Previous studies have not examined student attitudes towards IM at Xavier University School of Medicine (XUSOM), a Caribbean medical school. Most students are citizens of the United States or Canada and will practice in these countries after graduation. Hence, the present study was conducted using the integrative medicine attitude questionnaire (IMAQ), a previously validated questionnaire. Methods: First to fourth semester premedical and undergraduate medical (MD) students were involved in the study. Respondents’ gender, semester of study and nationality were noted. Their degree of agreement with a set of 29 statements was studied using a modified Likert-type scale. The total score, openness, and relationship scores were compared among different subgroups. Free text comments were invited. Results: Sixty-two of the 79 students (78.5%) participated; 19 were premedical while 43 were MD students. The mean ± SD total score was 138.85 ± 15.84 (maximum score 203). The mean ± SD openness score was 94.69 ± 10.99 (maximum score being 147). The mean ± SD relationship score was 44.16 ± 8.18 (maximum possible score being 56). The scores were not significantly different among subgroups of respondents. The scores of certain statements were low. Conclusion: Student attitudes towards CAM and IM were positive and these can be considered for possible inclusion in the curriculum. Studies among students in the clinical years and in other medical schools are recommended. A longitudinal follow up of students can be considered.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".