TY  - JOUR
AU  - Noh, Jung Min
AU  - Im, SongHyun
AU  - Park, JooYong
AU  - Kim, Jae Myung
AU  - Lee, Miyoung
AU  - Choi, Ji-Yeob
PY  - 2025
DA  - 2025/4/1
TI  - Validation of Ecological Momentary Assessment With Reference to Accelerometer Data: Repeated-Measures Panel Study With Multilevel Modeling
JO  - J Med Internet Res
SP  - e59878
VL  - 27
KW  - telemedicine
KW  - wearable electronic devices
KW  - physical activity
KW  - mobile phone
KW  - wearables
KW  - smartphones
KW  - ecological momentary assessment
KW  - EMA
KW  - global physical activity questionnaire
KW  - GPAQ
KW  - Bouchard’s physical activity
KW  - multilevel modeling
KW  - females
KW  - women
KW  - males
KW  - men
KW  - sensors
KW  - evaluation
KW  - comparative
KW  - South Korea
AB  - 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: β=.387, P<.001; BAR daily: β=.394, P<.001; GPAQ: β=.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. 
SN  - 1438-8871
UR  - https://www.jmir.org/2025/1/e59878
UR  - https://doi.org/10.2196/59878
UR  - http://www.ncbi.nlm.nih.gov/pubmed/40168069
DO  - 10.2196/59878
ID  - info:doi/10.2196/59878
ER  -