Cancer Survivor Preferences, Barriers, And Facilitators To Exercise After Participation In A Cancer-specific Community Exercise Program
Bibliographic record
Abstract
Including cancer survivors and their families in the planning of cancer-specific community exercise programming supports person-centred care, and allows for the identification of exercise barriers, facilitators and preferences to optimize program uptake and sustainability. The Alberta Cancer Exercise (ACE) pilot multi-centre randomized controlled trial examined the feasibility of implementing a cancer specific community-based exercise program. The current project was a sub-study (Edmonton site) utilizing an integrated knowledge translation (iKT) approach to inform future ACE program implementation. IKT can be described as involving knowledge users in the research process, in this case cancer survivors, to yield research that is more applicable and helpful to the knowledge users. PURPOSE: To identify barriers, facilitators and preferences towards exercise of cancer survivors after participation in the ACE pilot study. METHODS: A longitudinal descriptive design using mixed methods research methodology was used to better understand the participant exercise experience. Following study completion, a post-study satisfaction questionnaire was administered and a focus group session was held. Quantitative data were analyzed descriptively and qualitative data used to interpret, clarify and further describe quantitative results. RESULTS: 82% of participants indicated a preference for a combination of unsupervised and supervised exercise, 77% preferring to exercise with other cancer survivors, and 67% for exercise programming to occur in a community facility. 76% perceived little to no difficulty in continuing to exercise independently. A major theme emerging was the lack of counselling from healthcare providers on exercise during the cancer treatment period. Oncologist referral to the ACE pilot was minimal, with 93% of survivors indicating they self-referred to the program. Specifically, participants identified a lack of (1) communication on the value of exercise for recovery and (2) provision of information on the availability of cancer-specific exercise programming. CONCLUSIONS: An iKT approach, involving survivors and their families, can help inform exercise programming issues and the need for program modification to optimize survivor satisfaction and adherence.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".