Mindfulness-based stress reduction for medical students: a narrative review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Medical students are at high risk of depression, distress and burnout, which may adversely affect patient safety. There has been growing interest in mindfulness in medical education to improve medical student well-being. Mindfulness-based stress reduction (MBSR) is a commonly used, standardized format for teaching mindfulness skills. Previous research has suggested that MBSR may be of particular benefit for medical students. This narrative review aims to further investigate the benefits of MBSR for undergraduate medical students. METHODS: A search of the literature was performed using MedLine, Embase, ERIC, PSYCInfo, and CINAHL to identify relevant studies. A total of 102 papers were identified with this search. After review and application of inclusion and exclusion criteria, nine papers were included in the study. RESULTS: MBSR training for medical students was associated with increased measures of psychological well-being and self-compassion, as well as improvements in stress, psychological distress and mood. Evidence for effect on empathy was mixed, and the single paper measuring burnout showed no effect. Two studies identified qualitative themes which provided context for the quantitative results. CONCLUSIONS: MBSR benefits medical student well-being and decreases medical student psychological distress and depression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.115 | 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 it