Group Yoga Effects on Cancer Patient and Caregiver Symptom Distress: Assessment of Self-reported Symptoms at a Comprehensive Cancer Center
Bibliographic record
Abstract
<i>Background.</i> Complementary and integrative health approaches such as yoga provide support for psychosocial health. We explored the effects of group-based yoga classes offered through an integrative medicine center at a comprehensive cancer center. <i>Methods.</i> Patients and caregivers had access to two yoga group classes: a lower intensity (YLow) or higher intensity (YHigh) class. Participants completed the Edmonton Symptom Assessment System (ESAS; scale 0-10, 10 most severe) immediately before and after the class. ESAS subscales analyzed included global (GDS; score 0-90), physical (PHS; 0-60), and psychological distress (PSS; 0-20). Data were analyzed examining pre-yoga and post-yoga symptom scores using paired t-tests and between types of classes using ANOVAs. <i>Results.</i> From July 18, 2016, to August 8, 2017, 282 unique participants (205 patients, 77 caregivers; 85% female; ages 20-79 years) attended one or more yoga groups (mean 2.3). For all participants, we observed clinically significant reduction/improvement in GDS, PHS, and PSS scores and in symptoms (ESAS decrease ≥1; means) of anxiety, fatigue, well-being, depression, appetite, drowsiness, and sleep. Clinically significant improvement for both patients and caregivers was observed for anxiety, depression, fatigue, well-being, and all ESAS subscales. Comparing yoga groups, YLow contributed to greater improvement in sleep versus YHigh (−1.33 vs −0.50, <i>P</i> = .054). Improvement in fatigue for YLow was the greatest mean change (YLow −2.12). <i>Conclusion.</i> A single yoga group class resulted in clinically meaningful improvement of multiple self-reported symptoms. Further research is needed to better understand how yoga class content, intensity, and duration can affect outcomes.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".