P02.72. A pilot investigation of alignment-based yoga for pediatric obesity
Bibliographic record
Abstract
Adolescents referred to a pediatric weight management clinic (BMI > 95th percentile and ≥ 1 co-morbidity) were recruited to participate in an 8-week study involving bi-weekly, 60-minute Iyengar style yoga classes. All questionnaires and assessments of physical functioning were conducted immediately before and after the 8-week intervention. Assessments included prior experience and expectations, health-related quality of life (HRQOL), state anxiety, and functional limitations. Standardized assessments of participants’ physical abilities included push-ups, sit-ups, a step test, and sit to reach. PA levels were objectively assessed using a hip-mounted Actical accelerometer worn 7 consecutive days (pre and post-yoga). Sixteen youth (11-17 years, M 13) attended at least 7 classes. Half reported experiencing pain in the 2 weeks prior to consent (usual pain intensity M 5.88 ± 2.30). Sit-to-reach improved (p < .05) from pre (M 6.20 cm ± 8.86) to post (M 8.83 cm ± 5.62) intervention. Across almost all domains, participant and parent reports of HRQOL significantly improved (p’s < .05). Self-reports of state-anxiety decreased (p < .05). Whereas time spent in Sedentary, Light and Vigorous PA did not change, time spent in Moderate intensity PA increased (p = .05) from pre- (M 21.82 min. per day ± 25.71) to post-yoga (M 27.26 min. per day ± 16.44) intervention. These preliminary findings are encouraging, and suggest that alignment-based yoga may be a safe and effective intervention for pediatric obesity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".