Integrating Mindfulness and Physical Exercises for Medical Students: A Systematic Review
Bibliographic record
Abstract
Background: The purpose of this systematic review was to appraise the empirical evidence pertaining to medical students and the integration of mindfulness and physical exercise regimens. Methods: A systematic review was undertaken. Five databases were used to survey the salient literature. Results: The initial search identified 353 potentially relevant articles of which 17 articles were considered for the final review. The findings indicated that the research was mainly conducted in the USA with some research originating from Europe, Canada, Jamaica, and India. In addition, a range of research designs were applied to measure or discuss the efficacy of the integrated intervention. Four key categories captured the essence of the results of our review, namely: (1) quality of evidence and research methods; (2) types of interventions; (3) measurement protocols; and (4) benefits of integrating mindfulness and physical exercises. Conclusions: This systematic review demonstrated that when mindfulness and physical exercises are integrated there are likely to be positive health outcomes for medical students. In the studies that yielded the highest level of evidence it was clear that this combination enhanced mental health, and reduced stress levels amongst students, and the benefits may assist with interpersonal development, such as greater empathetic levels and improved interpersonal responsivity.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".