Effects of Supervised Exercise on Motivational Outcomes and Longer-Term Behavior
Bibliographic record
Abstract
INTRODUCTION: Supervised exercise may have positive effects on motivation and continued exercise in cancer survivors, but few randomized controlled trials have examined this issue. Here, we report the motivational outcomes and longer-term exercise behavior from the Healthy Exercise for Lymphoma Patients trial. METHODS: Lymphoma patients were randomly assigned to 12 wk of supervised aerobic exercise (SUP, n = 60) or usual care (UC, n = 62). Motivational outcomes from the theory of planned behavior were assessed at baseline, after intervention, and at 6-month follow-up using standardized measures. Exercise behavior was self-reported at baseline and 6-month follow-up using the Godin Leisure Time Exercise Questionnaire. RESULTS: Data were available from 95% of participants after intervention and 90% at 6-month follow-up. SUP attended a median of 92% of the supervised exercise sessions. After intervention, SUP was superior to UC for intention (+0.41 (+0.09 to +0.72), P = 0.012) and perceived behavioral control (+0.36 (+0.01 to +0.72), P = 0.047) and borderline superior for self-efficacy (+0.35 (-0.02 to +0.72), P = 0.060). At 6-month follow-up, SUP reported significantly more exercise minutes compared with UC (+133 (+38 to +227), P = 0.006), and a higher percentage of SUP participants were meeting public health exercise guidelines (+25.6% (+8.2% to +43.0%), P = 0.004). Path analysis showed that perceived behavioral control partially mediated the effects of supervised exercise (group assignment) on exercise behavior at 6-month follow-up (meeting exercise guidelines). CONCLUSIONS: Supervised exercise has motivational effects in lymphoma patients and improves longer-term exercise behavior. Strategies to further enhance the motivational value of supervised exercise are warranted.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".