Pilot Evaluation of an Iyengar Yoga Program for Breast Cancer Survivors
Bibliographic record
Abstract
BACKGROUND: With continual improvements in screening uptake and adjuvant cancer treatments, the number of Canadian women surviving breast cancer continues to grow. Preliminary findings suggest yoga can improve quality of life (QoL) in breast cancer survivors, but few studies have focused on Iyengar yoga (IY). OBJECTIVE: The purpose of this pilot study was to evaluate the impact of IY on QoL and psychosocial functioning in a select sample of breast cancer survivors. METHODS: Breast cancer survivors (N = 24) participating in IY classes completed a questionnaire measuring generic and disease-specific QoL and psychosocial functioning, before and after the 12-week classes. RESULTS: Postprogram questionnaires were completed by 17 participants (71%) who attended an average of 78.9% of the IY sessions. Several indicators of generic QoL improved significantly, including mental health (mean change, +4.2; P = .045), vitality (mean change, +4.9; P = .033), role-emotional (mean change, +6.4; P = .010), and bodily pain (mean change, +4.4; P = .024). Other improvements in QoL and psychosocial functioning were meaningful but were not statistically significant. Findings were further substantiated by participant's evaluation of the program's benefits and motivational value. CONCLUSION: In this pilot study of breast cancer survivors participating in IY, we found improvements in QoL and psychosocial functioning. Moreover, positive program evaluation and motivational profile provide support for the acceptability of IY with breast cancer survivors. Randomized controlled trials comparing IY to usual care and other forms of yoga in breast cancer survivors are warranted. IMPLICATIONS FOR PRACTICE: Nurses may consider IY as a possible intervention strategy to help breast cancer survivors improve their QoL and psychosocial functioning.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".