Accelerometer measurement error in a randomized physical activity intervention trial in breast cancer survivors was nondifferential but attenuated the intervention effect
Bibliographic record
Abstract
Abstract Background Physical activity reduces morbidity and mortality risk in cancer survivors, but a meaningful proportion of this vulnerable population are physically inactive. Targeted interventions can help cancer survivors adopt a more active lifestyle, but the efficacy of these interventions must be rigorously evaluated in randomized controlled intervention trials. A major barrier to such trials involves the difficulty in obtaining unbiased estimates of physical activity in free-living conditions. Methods We conducted a randomized controlled trial of a 3-month intervention designed to increase physical activity vs. usual care in breast cancer survivors (n = 316). The primary outcome was change in physical activity as estimated by hip-worn accelerometer (MTI/Actigraph, models GT1M and GT3X). The trial included a sub-study (n = 106) wherein unbiased measures of total energy expenditure (doubly labeled water), and resting energy expenditure (indirect calorimetry) were collected. A linear mixed measurement error model characterized the structure of measurement error in accelerometry-estimated physical activity energy expenditure (PAEE), and corrected for bias in the estimated intervention effect due to measurement error. Results Bias in the accelerometer estimates was related to true PAEE (p < 0.001) and baseline body mass index (p < 0.001) but was not related to age (p = 0.13). After correcting for measurement error, the estimated intervention effect at 3 months (change from baseline in PAEE in the intervention arm minus change in the control arm) was 77 kcal/day (95% confidence interval (CI) = 31–125), compared to 48 kcal/day (95% CI = 22–75) when measurement error was ignored. These results indicate a 20% (21%) increase in PAEE kcal x d−1 (kcal x kg−1 × d−1) at month 3 relative to baseline for the corrected model vs. 14% (15%) for the uncorrected model. There was no evidence that measurement error in accelerometry-estimated PAEE was differential (differed by treatment arm) in the trial (p = 0.86). Conclusions Measurement error in accelerometer-estimated PAEE can attenuate the effect size related to intervention effects in randomized controlled trials of physical activity interventions. Sub-studies that collect unbiased measures of PAEE can be used to correct for this short-coming. Trial registration ClinicalTrials.gov; NCT00929617; registered 06/26/2009; https://clinicaltrials.gov/study/NCT00929617
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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 | 0.073 | 0.110 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".