Attention to principles of exercise training: a review of exercise studies for survivors of cancers other than breast
Bibliographic record
Abstract
OBJECTIVES: Randomised controlled trials (RCTs) can evaluate how well a particular exercise programme reduces cancer treatment-related side effects. Adequate design and reporting of the exercise prescription employed in RCTs is central to interpreting study findings and translating effective interventions into practice. Our previous review on the quality and reporting of exercise prescriptions in RCTs in breast cancer survivors revealed several inadequacies. This review similarly evaluates exercise prescriptions used in RCTs in patients with cancers other than the breast. METHODS: The literature was searched for RCTs in persons diagnosed with a cancer other than breast. Data were extracted to evaluate the attention to the principles of exercise training in the study design and the reporting of and adherence to the exercise prescription used for the intervention. RESULTS: Of the 33 studies reviewed, none attended to all of the exercise training principles. Specificity was applied by 89%, progression by 26%, overload by 37%, initial values by 26%, diminishing returns by 9% and reversibility by 3%. Only 2 of 33 studies (6%) reported both the exercise prescription in full and adherence to each individual component of the prescription. CONCLUSIONS: Application of the principles of training in exercise RCTs of non-breast cancer survivors was incomplete and inconsistent. Given these observations, interpretation of findings from the reviewed studies should consider potential shortcomings in intervention design. Though the prescribed exercise programme was often described, adherence to the entire prescription was rarely reported providing a less accurate picture of dose-response and challenges in translating programmes to community settings.
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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 | 0.017 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".