Barriers and enablers of adherence to high-intensity interval training among patients with cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Physical activity confers physical and psychosocial benefits for cancer patients and decreases morbidity and mortality, but adherence varies. High-intensity interval training (HIIT) is time-efficient and may improve adherence. Our aim was to determine barriers and enablers of adherence to HIIT in patients diagnosed with cancer. DESIGN: Systematic review and meta-analysis. DATA SOURCE: PubMed-MEDLINE, Scopus and Web of Science. ELIGIBILITY CRITERIA: Intervention studies including patients diagnosed with any type of cancer, who engaged in HIIT with or without co-intervention in any stage of treatment and have reported outcomes for adherence. RESULTS: Eight hundred articles were screened and 22 were included (n=807); 19 were included in the meta-analysis (n=755). Weighted adherence to HIIT was 88% (95% CI, 81% to 94%). None of the studies reported serious adverse events. Although being a woman and having breast cancer were associated with lower adherence (p<0.05), age was not (p=0.15). Adherence was significantly lower during the treatment phase in comparison with pre- and post-treatment phases, 83% versus 94% and 96%, respectively (p<0.001). Session time of more than 60 min, when unsupervised and combined with other interventions, was associated with decreased adherence (p<0.05). CONCLUSION: Adherence to HIIT programmes among cancer patients varies and is improved when the intervention is supervised, of shorter duration, consists of solely HIIT and not in combination with other exercise and occurs during pre- and post-treatment phases. Strategies to improve adherence to HIIT in specific subpopulations may be needed to ensure all patients with cancer are provided optimal opportunities to reap the benefits associated with physical activity. PROSPERO REGISTRATION: CRD42023430180.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.039 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".