Online yoga programme for resident physicians in Québec: an evaluation of feasibility and impact on mental health
Bibliographic record
Abstract
OBJECTIVES: To evaluate the feasibility of the Bali Yoga Programme for Residents (PYB-R), an 8-week virtual yoga-based intervention and determine its impact on the mental health of resident physicians. DESIGN: Single-group repeated measures study. SETTING: Associations from the four postgraduate medical education programmes in Québec, Canada. PARTICIPANTS: Overall, 55 resident physicians were recruited to participate of which 53 (96.4%) completed the assessment pre-PYB-R. The postintervention assessment was completed by 43 residents (78.2%) and 39 (70.9%) completed all phases (including 3-month follow-up). Most were in their first year (43.4%) or second year (32.1%) of residency. The majority were female (81.1%) with a mean age of 28±3.6 years. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome measure was feasibility as measured by participation in the PYB-R. Secondary outcome measures were psychological variables (anxiety, depression, burn-out, emotional exhaustion, compassion fatigue and compassion satisfaction) and satisfaction with the PYB-R. Residents were further subgrouped based on the quality of work life and a number of PYB-R sessions attended. RESULTS: The attrition rate for programme completion was 19%. Of the 43 residents who completed the PYB-R, 90.6% attended between 6 and 8 sessions. Repeated-measures analysis of variances (ANOVAs) at three time points (baseline, PYB-R completion and 3-month follow-up) confirmed a decrease in scores for depression and anxiety, and an increase in scores for compassion satisfaction. No changes were observed in the other psychological variables evaluated. ANOVAs also confirmed that a better quality of life at work helps develop compassion satisfaction, a protective factor to compassion fatigue. Most participants (92.9%) indicated they were satisfied or very satisfied with the quality of the programme. CONCLUSIONS: A virtual yoga-based programme is feasible and has lasting positive effects for up to 3 months on the mental health of resident physicians. Further research is warranted to validate these findings using a larger sample of residents with a control group.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".