Use, beliefs, and attitude towards the use of complementary and alternative medicine in a sample among medical students in Saudi Arabia: A Cross-sectional Study
Bibliographic record
Abstract
Background: Complementary and alternative medicine (CAM) is increasingly recognized globally as a utilized approach and a subject of study. This study aimed to examine the use, beliefs, and attitudes toward the use of CAM in a sample of medical students in Saudi Arabia. Methods: A cross-sectional online survey was undertaken in Saudi Arabia with a sample of medical students between December 2020 and August 2021. A previously developed questionnaire was adapted and used in this study. Results: A total of 502 students were involved in this study. Only one-quarter of the study participants (25.3%; n= 127) confirmed that they had previous exposure to CAM courses. The most commonly agreed upon attitude statement was that "they agree that it is necessary to ask every patient about the previous usage of CAM during history-taking" (87.8%). The study participants showed a low positive attitude toward CAM. This was demonstrated through their mean attitude score, which was 3.2 (SD: 1.7) out of 7 (which is equal to 45.7% of the maximum score). Students who were previously exposed to CAM courses were 2.5-fold more likely to have a positive attitude toward CAM compared to others (p
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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 | 0.002 |
| 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 | 0.000 |
| 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".