Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Apr 24, 2024
Open Peer Review Period: Apr 30, 2024 - Jun 25, 2024
Date Accepted: Jan 22, 2025
(closed for review but you can still tweet)
Validation of Ecological Momentary Assessment with Reference to Accelerometer Data: A Multilevel Modeling Approach
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 physical activity to address these limitations.
Objective:
To evaluate the usability of EMA by comparing its measurement outcomes with two self-report assessments of physical activity: Global Physical Activity Questionnaire (GPAQ) and a modified version of Bouchard’s Physical Activity Record (BAR).
Methods:
235 participants (137 females, 98 males, 94 repeated) participated in one or more 7-day study. Waist-worn sensors provided by Actigraph™ captured accelerometer data while participants completed three self-report measures of physical activity. The multilevel modeling method was used with EMA, GPAQ, and BAR as separate measures, with six sub-domains of physiological activity (overall physical activity; overall excluding occupational; transport; exercise; occupational; sedentary) to model accelerometer data. Additionally, EMA and GPAQ were further compared with six domains of PA from the BAR as outcome measures.
Results:
Among the three self-reporting instruments, EMA and BAR exhibited better overall performance in modeling the accelerometer data compared to GPAQ (e.g. EMA daily: β = .387, p < .001; BAR daily: β = .394, p < .001; GPAQ: β = .281, p < .001, based on repeated-only participants with stepscounts from accelerometer as dependent variables).
Conclusions:
Multilevel modeling on three self-report assessments of physical activity indicates that smartphone-delivered EMA is a valid and efficient method for assessing physical activity.
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