Community-Based Yoga for Women Undergoing Substance Use Disorder Treatment
Bibliographic record
Abstract
BACKGROUND: Women with substance use disorders (SUD) receive medication-assisted treatment (MAT) with behavioral interventions and counseling for recovery. Evidence supports the use of yoga for SUD; however few studies specifically feature women. OBJECTIVES: Community-based yoga may add to health promotion through preferable physical activity for women in recovery. The aims of this study are to explore demographics and quantitative measures relevant to recovery and capture and understand the subjective experience of one session of yoga. STUDY DESIGN: The study design involves Descriptive/Cross-sectional. METHODOLOGY: Women in an inpatient SUD center attending weekly optional off-site yoga for recovery were recruited to capture first-time attendance. Survey data included Medical Outcomes Survey 12-item short-form (SF-12), Toronto Mindfulness Scale (TMS), and Brief Resilience Scale (BRS), demographics, and narrative reflections. Recruitment opportunities occurred weekly during ongoing hour-long classes. RESULTS: Twenty-nine women (average age 36.6) with primarily opiate-based addictions completed surveys. SF-12 was below the normative value of 50 for both subscales. BRS scores showed averages on the low end of normal resiliency. The frequency of responses to writing prompts confirmed physical and mental well-being through yoga intervention. Women shared potential relapse prevention specifically attributed to the mindfulness component of the intervention. CONCLUSION: The SF-12, BRS, and TMS are brief, valid, and reliable and can be easily incorporated in clinical practice or future research. Suboptimal SF-12 scores were found in women with SUD and, therefore important to note in the context of recovery to optimize treatment. Subjective reports from the participants find community-based yoga an enjoyable and beneficial type of physical activity. Yoga may be a viable option for comprehensive mind-body intervention for this population.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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) | 0.009 | 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 teacher head, 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".