A Systematic Review and Narrative Synthesis of Exercise Interventions to Manage Fatigue Among Children, Adolescents, and Young Adults with Cancer
Bibliographic record
Abstract
Exercise is known to improve fatigue among adult cancer patients however there is limited understanding of this relationship in children, adolescents, and young adults (AYA) with cancer. The aim is to evaluate the effect of exercise on fatigue outcomes among children and AYA with cancer and to identify important parameters of exercise (frequency, intensity, time, type, and setting), which may be relevant for future intervention design. A systematic search of PubMed, MedLine, CENTRAL, Embase, and Web of Science databases was conducted in December 2019, for studies within the last decade, reporting the effect of exercise on fatigue among cancer patients and survivors 0–24 years of age. Quality assessment was conducted using the Physiotherapy Evidence Database (PEDro) and “Before/After Studies with No Control Group” scales. Seventeen studies ( n = 681 participants) were included, of which six were randomized controlled trials (RCTs), and the remaining being pilot ( n = 5) or feasibility studies ( n = 6). Across studies there was great heterogeneity in intervention delivery, frequency (range: 1–7 days a week), time (range: 10–60 minutes), and duration (range: 3–24 weeks). A positive effect of exercise on fatigue was observed, however, most changes in fatigue were not statistically significant. Exercise is beneficial for reducing fatigue in young cancer patients. However, due to the heterogeneity and quality of existing interventions, firm conclusions about the most effective mode and format of exercise intervention cannot be drawn. There is a need for more definitive large-scale RCTs that can provide data of sufficient quality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".