Yoga Helps Put the Pieces Back Together: A Qualitative Exploration of a Community‐Based Yoga Program for Cancer Survivors
Bibliographic record
Abstract
Objective . A qualitative research methods approach was used to explore the experiences of participants in an ongoing community‐based yoga program developed for cancer survivors and their support persons. Methods . 25 participants took part in a series of semistructured focus groups following a seven‐week yoga program and at three‐ and six‐month follow‐ups. Focus groups were transcribed verbatim and analyzed using a process of inductive thematic analysis. Results . The group was comprised of 20 cancer survivors, who were diagnosed on average 25.40 (20.85) months earlier, and five support persons. Participants had completed the yoga program an average of 3.35 (3.66) times previously and attended approximately 1.64 (0.70) of three possible focus groups. Four key themes were identified: (1) safety and shared understanding; (2) cancer‐specific yoga instruction; (3) benefits of yoga participation; (4) mechanisms of yoga practice. Conclusions . Qualitative research provides unique and in‐depth insight into the yoga experience. Specifically, cancer survivors and support persons participating in a community‐based yoga program discussed their experiences of change over time and were acutely aware of the beneficial effects of yoga on their physical, psychological, and social well‐being. Further, participants were able to articulate the mechanisms they perceived as underpinning the relationship between yoga and improved well‐being as they developed their yoga practice.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".