Open AccessFeasibility and Performance Test of a Real-Time Sensor-Informed Context-Sensitive Ecological Momentary Assessment to Capture Physical Activity
Author(s) -
Genevieve F. Dunton,
Eldin Dzubur,
Stephen Intille
Publication year - 2016
Publication title -
jmir. journal of medical internet research/journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/jmir.5398
Subject(s) - context (archaeology) , test (biology) , ecology , computer science , psychology , environmental resource management , environmental science , geography , biology , archaeology
Background Objective physical activity monitors (eg, accelerometers) have high rates of nonwear and do not provide contextual information about behavior. Objective This study tested performance and value of a mobile phone app that combined objective and real-time self-report methods to measure physical activity using sensor-informed context-sensitive ecological momentary assessment (CS-EMA). Methods The app was programmed to prompt CS-EMA surveys immediately after 3 types of events detected by the mobile phone’s built-in motion sensor: (1) Activity (ie, mobile phone movement), (2) No-Activity (ie, mobile phone nonmovement), and (3) No-Data (ie, mobile phone or app powered off). In addition, the app triggered random (ie, signal-contingent) ecological momentary assessment (R-EMA) prompts (up to 7 per day). A sample of 39 ethnically diverse high school students in the United States (aged 14-18, 54% female) tested the app over 14 continuous days during nonschool time. Both CS-EMA and R-EMA prompts assessed activity type (eg, reading or doing homework, eating or drinking, sports or exercising) and contextual characteristics of the activity (eg, location, social company, purpose). Activity was also measured with a waist-worn Actigraph accelerometer. Results The average CS-EMA + R-EMA prompt compliance and survey completion rates were 80.5% and 98.5%, respectively. More moderate-to-vigorous intensity physical activity was recorded by the waist-worn accelerometer in the 30 minutes before CS-EMA activity prompts (M=5.84 minutes) than CS-EMA No-Activity (M=1.11 minutes) and CS-EMA No-Data (M=0.76 minute) prompts ( P ’s<.001). Participants were almost 5 times as likely to report going somewhere (ie, active or motorized transit) in the 30 minutes before CS-EMA Activity than R-EMA prompts (odds ratio=4.91, 95% confidence interval=2.16-11.12). Conclusions Mobile phone apps using motion sensor–informed CS-EMA are acceptable among high school students and may be used to augment objective physical activity data collected from traditional waist-worn accelerometers.