Pedometer-facilitated walking intervention shows promising effectiveness for reducing cancer fatigue: a pilot randomized trial
Bibliographic record
Abstract
OBJECTIVE: Mechanisms for cancer related fatigue suggest that exercise but "not too much and not too little" could be effective. This study aimed to investigate feasibility and estimate the potential effects of a walking exercise program in people with advanced cancer and fatigue. DESIGN: A pilot randomized trial. SETTING: McGill University Health Centre (MUHC), Montreal, Canada. SUBJECTS: People with advanced cancer undergoing interdisciplinary assessment and rehabilitation with a fatigue level of 4 to 10 on a visual analogue scale. INTERVENTIONS: An 8-week fatigue-adapted, walking intervention, facilitated using a pedometer (STEPS), and offered at the same time as or after rehabilitation. MEASURES: Measures of fatigue, physical function and well-being were administered at entry, and 8, 16 and 24 weeks. Generalized estimating equations (GEE) estimated the odds of response for people receiving the STEPS program in comparison to the odds of response in the controls (odds ratio, OR). RESULTS: Twenty-six persons were randomized to three groups: during rehabilitation, after rehabilitation, and usual care. For the fatigue measures the OR for STEPS offered at any time using an intention-to-treat approach was 3.68 (95%CI: 1.05-12.88); for the physical function measures, the OR was 1.40 (95%CI: 0.41- 4.79) and 2.36 (95%CI: 0.66-8.51) for the well-being measures. CONCLUSION: Fifty percent of eligible people were able to participate. This small trial suggests that a personalized exercise program reduces fatigue and that 100 people are needed in a full strength trial.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".