Predictors of adherence and contamination in a randomized trial of exercise in colorectal cancer survivors
Bibliographic record
Abstract
The purpose of this study was to examine predictors of exercise adherence (i.e. exercise in the intervention group) and exercise contamination (i.e. exercise in the control group) in a randomized controlled trial of home-based exercise in colorectal cancer survivors. At baseline, 102 participants completed measures of the theory of planned behavior, personality, past exercise, exercise stage of change, physical fitness, and medical/demographics and then were randomly assigned in a 2:1 ratio to an exercise (n=69) or control (n=33) group. Exercise was monitored weekly for 16 weeks using self-reports by telephone. Ninety-three (91%) participants completed the trial. Adherence was 76% in the exercise group and contamination was 52% in the control group. Hierarchical stepwise regression analyses indicated that baseline exercise stage of change (beta=0.35; p=0.001), employment status (beta=-0.28; p=0.010), treatment protocol (beta=-0.26; p=0.018), and perceived behavioral control (beta=0.20; p=0.055) explained 39.6% of the variance in exercise adherence. Intentions (beta=0.36; p=0.049) and baseline exercise stage of change (beta=0.30; p=0.095) explained 29.9% of the variance in exercise contamination. These findings may have implications for conducting clinical trials of exercise in colorectal cancer survivors and for promoting exercise to colorectal cancer survivors outside of clinical trials.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".