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

Abstract

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 ...

Feasibility and Acceptability of a Personalized Assessment of Chronic Abdominal Pain Triggers

“…While children with chronic abdominal patients appear willing to provide both objective and subjective information about across a variety of variables in order to better understand the biopsychosocial factors that may contribute to their abdominal pain, there appears to be something unique to this aspect of the protocol that represents a significant barrier to compliance. Of note, observed wear rates for the physiological monitor fell short of even conservative estimates based on our previous research in healthy adolescent samples [19]. It is possible that the current sample being younger and experiencing abdominal pain may have contributed to compliance issues.…”

“…Although the overall compliance rate with the daily surveys was lower than hypothesized based on rates from previous healthy samples [19], the density of the data was sufficient to run intraindividual models and identify individualized pain triggers in 80% (24/30) of participants. Rates of compliance with the accelerometer were higher, potentially reflecting the ease of this relatively passive type of monitoring, and were consistent with expectations for both daily and nightly wear.…”

“…The coordinator also instructed children to wear the physiological monitor for 12-hours throughout the day (i.e., put it on in the morning, and take it off before bed). Finally, children received a study-provided Android phone set-up with the survey application (PETE app; for more information see [19]). …”

“…During each child's follow-up visit, both caregiver and child completed brief quantitative and qualitative surveys regarding acceptability of study procedures and overall satisfaction. Specific items were drafted based on similar procedures utilized in a previous pilot EMA study [19]. On a Likert-type scale ranging from 1 (Not at all True) to 7 (Very True) caregivers and children responded to questions regarding their enjoyment of the study, the comfort and ease of using the physiological monitor and accelerometer, and their experiences answering daily surveys.…”

“…During completion of each survey, children provided information regarding their immediate environment utilizing a measure developed for a previous EMA study [19]. Specifically, children responded to questions regarding their current location (e.g., school, home, and vehicle) and details about the environment, including perceived safety, current weather, and traffic.…”