A randomized controlled trial of a wearable technology‐based intervention for increasing moderate to vigorous physical activity and reducing sedentary behavior in breast cancer survivors: The ACTIVATE Trial
Bibliographic record
Abstract
BACKGROUND: The benefits of an active lifestyle after a breast cancer diagnosis are well recognized, but the majority of survivors are insufficiently active. The ACTIVATE Trial examined the efficacy of an intervention (use of the Garmin Vivofit 2 activity monitor coupled with a behavioral feedback and goal-setting session and 5 telephone-delivered health coaching sessions) to increase moderate to vigorous physical activity (MVPA) and reduce sedentary behavior in breast cancer survivors. METHODS: This randomized controlled trial recruited 83 inactive, postmenopausal women diagnosed with stage I-III breast cancer who had completed primary treatment. Participants were randomly assigned to the intervention group or to the control group, and the intervention was delivered over a 12-week period. MVPA and sedentary behavior were measured with Actigraph and activPAL accelerometers at baseline (T1) and at the end of the intervention (T2). RESULTS: Retention in the trial was high, with 80 (96%) of participants completing T2 data collection. At T2, there was a significant between-group difference in MVPA (69 min/wk; 95% CI = 22-116) favoring the intervention group. The trial resulted in a statistically significant decrease in both total sitting time and prolonged bouts (≥20 min) of sitting, with between-group reductions of 37 min/d (95% CI = -72 to -2) and 42 min/d (95% CI = -83 to -2), respectively, favoring the intervention group. CONCLUSION: Results from the ACTIVATE Trial suggest that the use of wearable technology presents an inexpensive and scalable opportunity to facilitate more active lifestyles for cancer survivors. Whether or not such wearable technology-based interventions can create sustainable behavioral change should be the subject of future research.
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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 | 0.000 |
| 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".