Multischool, International Survey of Medical Students??? Attitudes toward ???Holism???
Bibliographic record
Abstract
PURPOSE: Core and optional courses of study in complementary and alternative medicine (CAM) are being incorporated into medical curricula. The authors carried out this study to validate a tool to examine students' attitudes toward holism and CAM and explore the relationships between their attitudes and other demographic and education-related characteristics in a large, multischool, international sample of medical students. METHOD: In 2003 the authors used a modified version of the Integrated Medicine Attitude Questionnaire (IMAQ) to survey students at a total of six medical schools in the United Kingdom, New Zealand, Canada, the United States, and Hong Kong, China. A three-factor model was tested using confirmatory factor analysis, and the internal consistency of the factors were identified using Cronbach's alpha coefficients. A multiple-indicator multiple-cause (MIMIC) analysis was carried out to determine the relationship between IMAQ factors and student characteristics. RESULTS: The authors validated a three-factor model for the IMAQ: (1) attitudes toward holism, (2) attitudes toward the effectiveness of CAM, and (3) attitudes toward introspection and the doctor-patient relationship. Cronbach's alpha coefficients ranged from .41 to .71. The MIMIC model indicated that various background variables were associated with IMAQ factors (gender, race/ethnicity, and school), depending on whether students had previously visited a CAM practitioner and whether students were willing to undertake a special study module in CAM. CONCLUSIONS: Further development work on the IMAQ is required and qualitative research to verify and examine the reasons behind the relationships found in this study between students' attitudes to holism and their demographic and education-related characteristics.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".