Exploring Yoga Instructors’ Experiences Delivering Yoga to Children and Adolescents Affected by Cancer or Blood Disease
Bibliographic record
Abstract
Yoga may offer benefits for children and adolescents affected by cancer or blood disease, yet there are challenges in translating evidence to practice. Yoga instructors are critical for the delivery of yoga. Understanding yoga instructors' experiences offering yoga to children and adolescents affected by cancer or blood disease could provide information to guide required competencies and training, as well as elucidate factors to consider in future research and programs. Therefore, the present study sought to understand yoga instructors' lived experiences preparing for and facilitating yoga for children and adolescents affected by cancer or blood disease. Fourteen yoga instructors with experience facilitating yoga for this population participated in semi-structured interviews, which were transcribed verbatim and analyzed using principles of interpretive description and thematic analysis. Five unique themes were identified: (1) "I believe in and see the perceived benefits of yoga on and off the mat"; (2) "I feel equipped to deliver yoga but desire further training"; (3) "what I need to deliver a safe yoga program"; (4) "I must be adaptable to successfully facilitate a yoga program"; and (5) "what I need to ensure yoga is widely available." Findings highlight the varied and comprehensive training opportunities yoga instructors sought, while elucidating their training limitations. Yoga instructors shared their perspectives on concerted attention to safety, effectiveness, and access when developing research and programs. This study represents a first step toward defining required competencies for delivering yoga to this population and lays the foundation for future research and programs.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".