Experiences of young adults affected by cancer within an 8-week yoga intervention delivered by videoconference: a qualitative interview study
Bibliographic record
Abstract
Background: Yoga may reduce negative cancer-and treatment-related effects and help improve a range of outcomes, including flexibility, mindfulness, and quality of life among adults affected by cancer.Yet there is little evidence for the role of yoga among young adults (18-39 years) affected by cancer.Purpose: the purpose of this study was to explore the experiences of young adults affected by cancer in an 8-week yoga intervention delivered by videoconference.Methods: Young adults who were diagnosed with cancer between the ages of 18 and 39 years, at any stage of the cancer trajectory, who were living in canada, and who completed an 8-week yoga intervention were approached to complete a semi-structured interview.a social constructivist paradigm was adopted.interviews were transcribed verbatim and analyzed using reflexive thematic analysis.Results: twenty-eight young adults (Mean age = 34.67 ± 5.11 years; n = 25 female) with varied cancer diagnoses participated.Participants' perspectives were represented across 6 themes: ( 1) i was juggling a number of challenges and changes throughout the yoga intervention; (2) i noticed some improvements in my mental and physical health; (3) i made time to discover new strategies to take care of myself; (4) i was able to see what my body is capable of; (5) i was held accountable and i appreciated that, and; (6) i was able to be around similar others in a safe (virtual) space.Conclusions: Findings suggest that an 8-week yoga intervention may offer some benefits for young adults affected by cancer.self-care, self-compassion, mindfulness, feelings of physical competence, establishing a routine, and being around similar others were viewed as important components of the intervention and may have contributed to the benefits experienced.Findings underscore the potential utility of yoga as a supportive care intervention for young adults affected by cancer. KEY MESSAGES1. Young adults affected by cancer described changed physical and mental health after an 8-week yoga intervention delivered by videoconference.2. taking time for oneself, practicing self-compassion and mindfulness, enhanced feelings of physical competence, and establishing a routine were important elements of the intervention.3. Young adults appreciated being around similar others (i.e., other young adults affected by cancer) and felt connected in this videoconference-based intervention.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".