Feasibility and performance test of a real-time sensor-informed context-sensitive ecological momentary assessment to capture physical activity

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.