A Randomized Control Trial of the Effects of a Hatha Yoga Program on Psychological Well-Being
Bibliographic record
Abstract
Hatha yoga is a common style of yoga used for physical, emotional, mental, and spiritual benefits, enhancing quality of life and well-being. The current study used a randomized control trial (RCT) to investigate whether completing an eight-week posture-based Hatha yoga program would lead to greater psychological benefits than taking part in an eight-week lecture series about the history and philosophy of yoga. Fifty-five participants (42 female, age range 18-32) completed five self-report measures both before and after an eight-week yoga-related intervention (Hatha yoga or yoga lectures). The self-report measures related to participants’ affective state (Depression, Anxiety, and Stress Scale), emotion dysregulation (Difficulties in Emotion Regulation Scale), interoceptive awareness (Multidimensional Assessment of Interoceptive Awareness), trait mindfulness, (Five-Facet Mindfulness Questionnaire), and self-compassion (Self-Compassion Scale). All interventions were taught by the first author, a trained yoga instructor. Results indicated that those in the yoga program, but not in the education program, showed significant improvement on measures of stress, mindfulness, and interoception. Mediation analyses revealed that mindfulness was a mediator between yoga program and depression, anxiety, and stress. Emotion dysregulation was a mediator between yoga program and both depression and stress. Finally, interoceptive awareness was a mediator between yoga program and depression. These results suggest that a short, posture-based yoga practice produces benefits in multiple areas of functioning with underlying mechanisms highlighting the importance of mindfulness, interoceptive awareness, and emotional regulation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".