Sudarshan Kriya Yoga program in posttraumatic stress disorder: A feasibility study
Bibliographic record
Abstract
Background: Sudarshan Kriya Yoga (SKY), a breath-based yoga intervention, has demonstrated safety and efficacy in posttraumatic stress disorder (PTSD) patients subsequent to natural disaster or war, but has not been explored in civilians with PTSD from a wider range of trauma. We hypothesized that it would be feasible to conduct a clinical trial of SKY in PTSD resulting from a wide range of trauma. Methods: Outcomes were feasibility measures including rates of enrollment and retention, adherence to study protocol; as well as changes in PTSD symptoms, other mood symptoms, and physiological measures. Male and female participants aged 18–75 years were enrolled in a feasibility trial. They attended a 6-day learning phase of SKY followed by 7 sessions over 11 weeks as an adjunct to their usual treatment. Results: Forty-seven participants were screened and 32 were enrolled over 9 months. Consistent with retention rates of other PTSD trials, 13 withdrew from the study prior to week 12. Twenty-one participants met intervention attendance requirements, completed 95% of planned study assessments and were included in final analyses. Participants experienced clinically significant decrease in PTSD symptoms on the posttraumatic stress disorder checklist (PCL-5) scores at week 12 mean difference, Mdiff (standard deviation [SD]) = −10.68 (14.03), P = 0.004; Cohen's d = 0.58, which was sustained at week 24 Mdiff (SD) = −16.11 (15.20), P < 0.001; Cohen's d = 0.91. Conclusions: It is possible to conduct a clinical trial of SKY in a routine psychiatry clinic serving patients with PTSD due to a wide range of trauma. Future studies should include an RCT design.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".