A cross-sectional analysis of yoga experience on variables associated with psychological well-being
Bibliographic record
Abstract
Introduction Previous research has identified numerous physical, psychological, and spiritual benefits associated with the practice of yoga. Indeed, yoga has been linked with improved quality of life, reduced stress, and numerous markers of psychological well-being. In the current research, a cross-sectional design was used to examine whether the psychological benefits associated with yoga only apply to long-term practitioners or whether more “casual,” intermittent yoga experience could produce positive outcomes. Methods An American population of long-term practitioners (n = 129), intermittent practitioners (n = 161), and non-practitioners (n = 164) completed online self-report measures of emotional regulation, trait mindfulness, self-compassion, interoceptive awareness, and spiritual intelligence variables. Results The results indicated that long-term (LT) practitioners scored higher than intermittent experience (IE) practitioners on measures of mindfulness (MLT = 137.3; MIE = 127.6), interoceptive awareness (MLT = 3.4; MIE = 3.1), self-compassion (MLT = 3.4; MIE = 3.1), and spiritual intelligence (MLT = 63.5; MIE = 55.5; all p-value < 0.05). Intermittent practitioners scored higher than no-experience (NE) group on interoceptive awareness (MIE = 3.1; MNE = 2.7) and spiritual intelligence (MIE = 55.5; MNE = 46.6; both p-value < 0.05). Contrary to our hypotheses, yoga experience had no effect on depression, anxiety, or stress levels. Separate mediation analyses demonstrated that interoceptive awareness, spiritual intelligence, mindfulness, and self-compassion each mediated the relationship between yoga experience and emotion dysregulation. Furthermore, emotion dysregulation mediated the relationship between yoga experience and depression, anxiety, and stress. Discussion Taken together, the results of this study suggest that long-term practitioners experience more benefits compared to intermittent and non-practitioners, and that the mechanisms underlying these benefits are multi-faceted.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".