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 ...

Objective Although the primary care setting has been recommended as an acceptable environment for pediatric overweight/obesity treatment, a quantitative analysis has not been conducted to determine the effectiveness of pediatric weight management interventions delivered in these settings. Therefore, the purpose of the current study was to conduct a meta-analysis of weight management interventions for youth in primary care settings. Method A literature search using PsycINFO and PubMed was conducted to identify articles published through October 2015. Eighteen studies (3,358 participants) met inclusion criteria; studies included a treatment and comparison group and targeted individuals or families for treatment. Study characteristics were coded, and study rigor of articles was assessed. Results The overall effect size for change in BMI in primary care weight management interventions compared to control groups was small but statistically significant (d = 0.26, 95% CI [0.14, 0.38]). The number of treatment contacts, treatment months, and visits with a pediatrician emerged as significant moderators of outcome, such that BMI reduction was positively related to greater contact. Conclusions In comparison to control conditions, weight management programs in primary care settings can be effective for BMI reduction, suggesting that primary care is a suitable setting for treatment of pediatric overweight/obesity. Additionally, treatments that were longer in duration, included more contacts (in person or phone), and included more contacts by a pediatrician had greater impact on BMI reduction. Future studies should continue to examine other aspects of acceptability and accessibility as well as demonstrate the effectiveness of interventions on improving psychosocial outcomes.

BackgroundYouth are active in multiple locations, but it is unknown whether more physical activity in one location is associated with less in other locations. This cross-sectional study examines whether on days with more physical activity in a given location, relative to their typical activity in that location, youth had less activity in other locations (i.e., within-person associations/compensation).MethodsParticipants were 528 adolescents, ages 12 to 16 (M = 14.12, SD = 1.44, 50% boys, 70% White non-Hispanic). Accelerometer and Global Positioning System devices were used to measure the proportion of time spent in moderate-to-vigorous physical activity (MVPA) in five locations: home, home neighborhood, school, school neighborhood, and other locations. Mixed-effects regression was used to examine within-person associations of MVPA across locations and moderators of these associations.ResultsTwo of ten within-participant associations tested indicated small amounts of compensation, and one association indicated generalization across locations. Higher at-school MVPA (relative to the participant’s average) was related to less at-home MVPA and other-location MVPA (Bs = −0.06 min/day). Higher home-neighborhood MVPA (relative to the participant’s average) was related to more at-home MVPA (B = 0.07 min/day). Some models showed that compensation was more likely (or generalization less likely) in boys and non-whites or Hispanic youth.ConclusionsConsistent evidence of compensation across locations was not observed. A small amount of compensation was observed for school physical activity, suggesting that adolescents partially compensated for high amounts of school activity by being less active in other locations. Conversely, home-neighborhood physical activity appeared to carry over into the home, indicating a generalization effect. Overall these findings suggest that increasing physical activity in one location is unlikely to result in meaningful decreases in other locations. Supporting physical activity across multiple locations is critical to increasing overall physical activity in youth.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-017-0507-x) contains supplementary material, which is available to authorized users.

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