Self-Reported Benefits and Risks of Yoga in Individuals with Bipolar Disorder
Bibliographic record
Abstract
BACKGROUND: Although hatha yoga has frequently been recommended for patients with bipolar disorder (BD) and there is preliminary evidence that it alleviates depression, there are no published data on the benefits-and potential risks-of yoga for patients with BD. Thus, the goal of this study was to assess the risks and benefits of yoga in individuals with BD. METHODS: We recruited self-identified yoga practitioners with BD (N=109) to complete an Internet survey that included measures of demographic and clinical information and open-ended questions about yoga practice and the impact of yoga. RESULTS: 86 respondents provided sufficient information for analysis, 70 of whom met positive screening criteria for a lifetime history of mania or hypomania. The most common styles of yoga preferred were hatha and vinyasa. When asked what impact yoga had on their life, participants responded most commonly with positive emotional effects, particularly reduced anxiety, positive cognitive effects (e.g., acceptance, focus, or "a break from my thoughts"), or positive physical effects (e.g., weight loss, increased energy). Some respondents considered yoga to be significantly life changing. The most common negative effect of yoga was physical injury or pain. Five respondents gave examples of specific instances or a yoga practice that they believed increased agitation or manic symptoms; five respondents gave examples of times that yoga increased depression or lethargy. CONCLUSIONS: Many individuals who self-identify as having BD believe that yoga has benefits for mental health. However, yoga is not without potential risks. It is possible that yoga could serve as a useful adjunctive treatment for BD.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".