@Article{info:doi/10.2196/59878,
author="Noh, Jung Min
and Im, SongHyun
and Park, JooYong
and Kim, Jae Myung
and Lee, Miyoung
and Choi, Ji-Yeob",
title="Validation of Ecological Momentary Assessment With Reference to Accelerometer Data: Repeated-Measures Panel Study With Multilevel Modeling",
journal="J Med Internet Res",
year="2025",
month="Apr",
day="1",
volume="27",
pages="e59878",
keywords="telemedicine; wearable electronic devices; physical activity; mobile phone; wearables; smartphones; ecological momentary assessment; EMA; global physical activity questionnaire; GPAQ; Bouchard's physical activity; multilevel modeling; females; women; males; men; sensors; evaluation; comparative; South Korea",
abstract="Background: There is growing interest in the real-time assessment of physical activity (PA) and physiological variables. Acceleration, particularly those collected through wearable sensors, has been increasingly adopted as an objective measure of physical activity. However, sensor-based measures often pose challenges for large-scale studies due to their associated costs, inability to capture contextual information, and restricted user populations. Smartphone-delivered ecological momentary assessment (EMA) offers an unobtrusive and undemanding means to measure PA to address these limitations. Objective: This study aimed to evaluate the usability of EMA by comparing its measurement outcomes with 2 self-report assessments of PA: Global Physical Activity Questionnaire (GPAQ) and a modified version of Bouchard Physical Activity Record (BAR). Methods: A total of 235 participants (137 female, 98 male, and 94 repeated) participated in one or more 7-day studies. Waist-worn sensors provided by ActiGraph captured accelerometer data while participants completed 3 self-report measures of PA. The multilevel modeling method was used with EMA, GPAQ, and BAR as separate measures, with 6 subdomains of physiological activity (overall PA, overall excluding occupational, transport, exercise, occupational, and sedentary) to model accelerometer data. In addition, EMA and GPAQ were further compared with 6 domains of PA from the BAR as outcome measures. Results: Among the 3 self-reporting instruments, EMA and BAR exhibited better overall performance in modeling the accelerometer data compared to GPAQ (eg EMA daily: $\beta$=.387, P<.001; BAR daily: $\beta$=.394, P<.001; GPAQ: $\beta$=.281, P<.001, based on repeated-only participants with step counts from accelerometer as dependent variables). Conclusions: Multilevel modeling on 3 self-report assessments of PA indicates that smartphone-delivered EMA is a valid and efficient method for assessing PA. ",
issn="1438-8871",
doi="10.2196/59878",
url="https://www.jmir.org/2025/1/e59878",
url="https://doi.org/10.2196/59878",
url="http://www.ncbi.nlm.nih.gov/pubmed/40168069"
}