Implementing physical activity for individuals with cancer during treatment: protocol for the IMPACT implementation–effectiveness trial
Bibliographic record
Abstract
Introduction The prevalence of cancer in Canada is growing, leading to multiple lasting side effects in survivors. The physical and psychosocial benefits of regular physical activity (PA) during and after treatment for individuals with cancer are well established, however, not well implemented in a clinical setting. The overall aim of this project is to build on previous work and conduct a multicentred randomised controlled trial (RCT) and evaluate the effectiveness of a novel implementation strategy using PA and self-management versus usual care during cancer treatment. Methods and analysis Study design: a hybrid implementation–effectiveness RCT will occur at five cancer centres across Ontario, Canada. Participants: eligible participants include adults with a cancer diagnosis (any type or stage) who are receiving treatment and cleared for exercise by their oncology care team. Intervention: participants (n=129) will be randomised to one of three groups: (1) institution-based exercise and self-management (SM) (eight in-person sessions of aerobic exercise and eight SM modules), (2) SM alone (SM only: eight virtual modules) or (3) usual care (no intervention). Outcomes: the Reach, Effectiveness, Adoption, Implementation and Maintenance framework will assess implementation outcomes. The primary effectiveness outcome is self-report PA level postintervention. Data analysis: outcomes will be measured at four time points (baseline, postintervention, 6- and 12-month follow-up). Descriptive statistics will be used to present implementation outcomes. An analysis of covariance will assess change between groups over time. Ethics and dissemination Findings from this trial will build on previous work and inform the way PA services are provided within cancer institutions across Ontario, Canada, and inform decision-making on how to incorporate exercise evidence into real-world clinical practice in cancer care. The Hamilton Integrated Research Ethics Board (ID: 7673 & 17454) has approved this study. Results will be disseminated using a combination of peer-reviewed publications, conference presentations and community organisation presentations. Participants will contribute to dissemination by sharing ‘participant perspectives’, highlighting their experience in the project and thoughts on the implementation strategies used. Trial registration number The study is registered on clinicaltrials.gov (ID: NCT06323707 ).
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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 | 0.044 | 0.034 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.122 | 0.020 |
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".