Effects of the ACTIVity And TEchnology (ACTIVATE) intervention on health‐related quality of life and fatigue outcomes in breast cancer survivors
Bibliographic record
Abstract
BACKGROUND: The ACTIVATE Trial examined the efficacy of a wearable-based intervention to increase physical activity and reduce sedentary behavior in breast cancer survivors. This paper examines the effects of the intervention on health-related quality of life (HRQoL) and fatigue at 12 weeks (T2; end of intervention) and 24 weeks (T3; follow-up). METHODS: Inactive and postmenopausal women who had completed primary treatment for stage I-III breast cancer were randomized to intervention or waitlist control. Physical activity and sedentary behavior were measured by Actigraph and activPAL accelerometers at baseline (T1), end of the intervention (T2), and 12 weeks follow-up (T3). HRQoL and fatigue were measured using the Functional Assessment of Cancer Therapy-Breast (FACT-B) and the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-Fatigue). Primary intervention effects were evaluated comparing intervention and waitlist group at T2 using repeated measures mixed effects models. RESULTS: Overall, 83 women were randomized and trial retention was high (94%). A 4.6-point difference in fatigue score was observed between groups at T2 (95% CI: 1.3, 7.8) indicating improvement in fatigue profiles in the intervention group. In within groups analyses, the intervention group reported a 5.1-point increase in fatigue from baseline to T2 (95% CI: 2.0, 8.2) and a 3.3-point increase from baseline to T3 (95% CI: 0.1, 6.41). CONCLUSIONS: Despite small improvements in fatigue profiles, no effects on HRQoL were observed. While the ACTIVATE Trial was associated with improvements in physical activity and sedentary behavior, more intensive or longer duration interventions may be needed to facilitate changes in HRQoL.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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".