Yoga and Positive Education for Student Mental Health, Self-Compassion, and Vitality: A Mixed-Methods Study
Bibliographic record
Abstract
With growing need to mitigate the mental health crisis on university campuses, researchers worldwide are seeking to determine effective student mental health promotion strategies, such as positive education (i.e., the teaching of applied positive psychology) and yoga. Nevertheless, a paucity of research appraises the effects of merging positive education and yoga for mental health. Therefore, the purpose of this study was to investigate the effect of a 6-week hatha yoga program on undergraduate positive education students' mental health, self-compassion, and vitality. In this mixed-methods single-case experimental A1BA2 design, 7 volunteer students enrolled in the positive education course completed a 2-week baseline (A1), followed by a 6-week yoga program that included two ≈ 45-minute weekly virtual yoga classes (B), and another 2-week baseline (A2; post-yoga), all while taking their positive education course. Trait variables (mental health, trait self-compassion, and trait subjective vitality) were assessed via validated questionnaires during the baseline phases preceding and following the yoga program, whereas state variables (state self-compassion and state subjective vitality) were assessed immediately before and after one of the weekly yoga sessions. Participants also responded to open-ended journal prompts related to the outcome variables following one of the sessions. Visual, stability, level, trend, and reflexive thematic analyses revealed that yoga practice was associated with improved trait and state well-being outcomes. This research suggests preliminary evidence for yoga and positive education courses as a means of increasing university students' mental health, self-compassion, and vitality both immediately and over time. Suggestions for yoga program implementation and future research are discussed.
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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 | 0.012 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".