Predictors of follow‐up exercise behavior 6 months after a randomized trial of supervised exercise training in lymphoma patients
Bibliographic record
Abstract
OBJECTIVES: Supervised exercise is beneficial for lymphoma patients, but it needs to be maintained to optimize long-term benefits. Here, we report the predictors of follow-up exercise behavior 6 months after a randomized controlled trial in lymphoma patients. METHODS: Lymphoma patients were randomly assigned to 12 weeks of supervised aerobic exercise (n = 60) or usual care (n = 62). At baseline and post-intervention, data were collected on demographic, medical, health-related fitness, quality of life, and motivational variables. At 6-month follow-up, participants were mailed a questionnaire that assessed exercise behavior and were categorized as meeting or not meeting public health exercise guidelines. RESULTS: At 6-month follow-up, 110 participants (90.2%) responded, of which 61 (55.5%) were meeting public health exercise guidelines. In univariate analyses, 16 variables predicted 6-month follow-up exercise behavior. In a stepwise regression analysis, five variables entered the model and explained 38% (p < 0.001) of the variance including the following: accepting a post-intervention exercise prescription (β = 0.33; p < 0.001), achieving a higher peak power output at post-intervention (β = 0.28; p = 0.001), experiencing a larger positive change in perceived behavioral control (β = 0.18; p = 0.028), having Hodgkin lymphoma (β = 0.19; p = 0.025), and having a stronger post-intervention intention (β = 0.18; p = 0.034). CONCLUSION: Exercise behavior in lymphoma patients 6 months after a randomized trial was predicted by a wide range of demographic, medical, health-related fitness, quality of life, and motivational variables. These findings may help facilitate the uptake of self-directed exercise after short-term supervised exercise in lymphoma patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 | 0.000 |
| 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 teacher head, 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".