Effects of Weekly One-Hour Hatha Yoga Therapy on Resilience and Stress Levels in Patients with Schizophrenia-Spectrum Disorders: An Eight-Week Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To examine the effects of Hatha yoga therapy on resilience, brain-derived neurotrophic factor (BDNF) levels, and salivary alpha amylase (SAA) activity in patients with schizophrenia-spectrum disorders. DESIGN AND PARTICIPANTS: Single-blinded, randomized controlled study in which outpatients with schizophrenia or related psychotic disorders (according to International Classification of Diseases, 10th Revision) were randomly assigned to a yoga or a control group. SETTING: November 2012-April 2013 at Yamanashi Prefectural Kita Hospital, Japan. INTERVENTIONS: In the yoga group, patients received weekly 1-hour Hatha yoga sessions, in addition to regular treatment, for 8 weeks. Those in the control group underwent regular treatment, which included a daycare rehabilitation program. OUTCOME MEASURES: Assessments included the 25-item Resilience Scale (RS), Positive and Negative Syndrome Scale (PANSS), plasma and salivary BDNF level, and SAA activity. RESULTS: Fifty patients participated (25 in each group; mean age±standard deviation, 50.9±11.3 years; mean duration of illness, 25.0±10.3 years; mean total PANSS score, 78.2±17.3). No significant differences in changes in any variable from baseline to week 8 were found between the two groups (changes in the yoga group versus the control group: RS score, -1.6±19.9 versus 0.3±17.2; PANSS score, 0.5±12.0 versus 5.0±15.6; plasma BDNF, 41.6±377.0 pg/dl versus 73.4±346.0 pg/dl; SAA, -26.2±72.6 kU/l versus -13.8±68.0 kU/l, respectively). CONCLUSIONS: Adjunct yoga therapy showed no positive changes in resilience level or stress markers. Duration and intensity of yoga sessions and the focus on patients with chronic illness may explain the negative observations in light of past positive evidence regarding yoga therapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".