Investigating Children's Physical Activity and Sedentary Behavior Using Ecological Momentary Assessment With Mobile Phones

“…In accordance with the stoplight system [16], which divides all foods into three categories (green, yellow, and red) based on the fat and sugar content; respondents were asked to report the number of Bred foods on the spotlight system^they had consumed throughout the day (i.e., foods with more than 7 g of fat or 12 g of sugar). Items included BHow many servings of FRUITS and VEGETABLES (Green Foods on the Stoplight System) have you eaten today?^and BHow many servings of HIGH FAT/ HIGH SUGAR foods (Red Foods on the Stoplight System; e.g., cookies, candy, hamburgers, pizza) have you eaten today?^Response choices were 1-5.…”

Section: Original Researchmentioning

confidence: 99%

The promise of wearable sensors and ecological momentary assessment measures for dynamical systems modeling in adolescents: a feasibility and acceptability study

Brannon

Cushing

Crick

et al. 2016

Behav. Med. Pract. Policy Res.

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Intervention development can be accelerated by using wearable sensors and ecological momentary assessment (EMA) to study how behaviors change within a person. The purpose of this study was to determine the feasibility and acceptability of a novel, intensive EMA method for assessing physiology, behavior, and psychosocial variables utilizing two objective sensors and a mobile application (app). Adolescents (n = 20) enrolled in a 20-day EMA protocol. Participants wore a physiological monitor and an accelerometer that measured sleep and physical activity and completed four surveys per day on an app. Participants provided approximately 81 % of the expected survey data. Participants were compliant to the wrist-worn accelerometer (75.3 %), which is a feasible measurement of physical activity/sleep (74.1 % complete data). The data capture (47.8 %) and compliance (70.28 %) with the physiological monitor were lower than other study variables. The findings support the use of an intensive assessment protocol to study real-time relationships between biopsychosocial variables and health behaviors. KeywordsFeasibility, Ecological momentary assessment, Physical activity, Adolescents, Wearable sensors Understanding how behaviors change within a person has the potential to inform intervention development. To date, however, health behavior data has not been assessed with enough precision or with a high enough sampling rate to use computational modeling approaches to understand dynamic processes [1]. In recent years, wearable sensors combined with subjective reports of internal states (e.g., ecological momentary assessment) have emerged as technologies that hold tremendous potential for identifying drivers of human behavior and accelerating behavioral medicine research. Ecological momentary assessment refers to the collection of behavioral, physiological, or self-reported data in nearly real time and in a person's natural environment. Therefore, this kind of data capture is less susceptible to recall bias and is more sensitive to contextual factors that may influence variables of interest.Wearable sensors provide precise and temporally dense information regarding the behavioral, physiological, and even affective states of individuals throughout the day [1]. With enough observations of intensive longitudinal data combining wearable sensors and ecological momentary assessment technologies, it may be possible to develop dynamical systems models of high value health behaviors such as sedentary activity, moderate to vigorous physical activity, sleep, and diet.Dynamical system modeling, a computational approach to understanding relationships in measured data, allows for the study of the relationships between variables, within a system (i.e., an individual) over time, and provides a comprehensive analytic technique for testing theories of behavior change [2]. In order for dynamical systems models to be maximally effective, high-throughput data indicating the state of the system needs to be available in high temporal density. This ...

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“…A total of five manuscripts, [130][131][132][133][134] describing six measures of sedentary time/behaviour met the eligibility criteria for CoOR (see Appendix 10).…”

Section: Sedentary Behaviour/timementioning

confidence: 99%