A Protocol for a Mixed Methods, Single-Arm, Hybrid Effectiveness-Implementation Trial Evaluating a 12-week Yoga Intervention Delivered by Videoconference for Young Adults Diagnosed With Cancer
Bibliographic record
Abstract
Background: Cancer among young adults (18-39 years) is relatively rare, but remains a leading cause of disability, morbidity, and mortality. Identifying strategies to support young adults' health following a diagnosis of cancer is important. Yoga may enhance health and could be delivered by videoconference. However, little research exploring yoga, and no research exploring videoconference delivery of yoga has been conducted with this cohort. We worked with young adults affected by cancer and developed, piloted, and refined a yoga intervention delivered by videoconference. Objective: To evaluate our yoga intervention in a full-scale, mixed methods, single-arm, hybrid effectiveness-implementation trial. Methods: Young adults 18 years or older, diagnosed with cancer between the ages of 18-39 years of age, and at any stage along the cancer trajectory are eligible. Participants receive 2 yoga classes/week over 12-weeks by videoconference and complete assessments at baseline, post-intervention, and 6- and 12-month follow-ups. Assessments include self-reported questionnaires (ie, stress, yoga barriers, physical activity behaviour, fatigue, cognition, cancer-related symptoms, general health, health-related quality of life, self-compassion, mindfulness, group identification), physical assessments (ie, aerobic endurance, flexibility, range of motion, balance, functional mobility), and a semi-structured interview (post-intervention only; exploring perceptions of acceptability, feasibility, and experiences). Quality improvement cycles occur every 6 months. Repeated measures analysis of variance will be conducted to explore effectiveness, descriptive statistics and responder/non-responder analyses will be used to explore implementation, and qualitative interview data, analyzed using content analysis and reflexive thematic analysis, will bolster effectiveness and implementation findings. Discussion: As the first full-scale trial to evaluate yoga delivered by videoconference for this cohort, findings will make substantial contributions to young adults' supportive cancer care. Conclusion: This protocol, reporting on yoga delivered by videoconference for young adults diagnosed with cancer, will enhance transparency and reproducibility and provide a reference for forthcoming trial results. Trial registration: NCT05314803 at clinicaltrials.gov.
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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 | 0.054 | 0.042 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.079 | 0.012 |
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".