Citation
Nelson, Sandahl H.; Natarajan, Loki; Patterson, Ruth E.; Hartman, Sheri J.; Thompson, Caroline A.; Godbole, Suneeta V.; Johnson, Eileen; Marinac, Catherine R.; & Kerr, Jacqueline (2019). Physical Activity Change in an RCT: Comparison of Measurement Methods. American Journal of Public Health, 43(3), 543-555. PMCID: PMC6812571Abstract
Objectives: We aimed to quantify the agreement between self-report, standard cut-point accelerometer, and machine learning accelerometer estimates of physical activity (PA), and exam- ine how agreement changes over time among older adults in an intervention setting.Methods: Data were from a randomized weight loss trial that encouraged increased PA among 333 postmenopausal breast cancer survivors. PA was estimated using accelerometry and a validated questionnaire at baseline and 6-months. Accelerometer data were processed using standard cut-points and a validated machine learning algorithm. Agreement of PA at each time-point and change was assessed using mixed effects regression models and concordance correlation.
Results: At baseline, self-report and machine learning provided similar PA estimates (mean dif- ference = 11.5 min/day) unlike self-report and standard cut-points (mean difference = 36.3 min/ day). Cut-point and machine learning methods assessed PA change over time more similarly than other comparisons. Specifically, the mean difference of PA change for the cut-point versus machine learning methods was 5.1 min/day for intervention group and 2.9 in controls, whereas it was
URL
http://dx.doi.org/10.5993/ajhb.43.3.9Reference Type
Journal ArticleYear Published
2019Journal Title
American Journal of Public HealthAuthor(s)
Nelson, Sandahl H.Natarajan, Loki
Patterson, Ruth E.
Hartman, Sheri J.
Thompson, Caroline A.
Godbole, Suneeta V.
Johnson, Eileen
Marinac, Catherine R.
Kerr, Jacqueline