Identifying the reciprocal associations between the built environment, social networks, and physical activity among youth in the summer

PROJECT SUMMARY Despite the many physical, psychological, and social benefits that can be gained, many youths do not regularly achieve recommended amounts of physical activity (PA). Summer is a particularly challenging time away from the structure and resources schools provide that facilitate health bringing changes in social relationships as well as the built environment to which youth are exposed. Reviews of existing evidence highlight a significant need for more nuanced measurement including the use of intensive longitudinal data (ILD) to separate the effects of social and built environments as well as their reciprocal determinism and mutual influence on youth PA. Ecological momentary assessment (EMA) is a promising method to collect ILD by gathering real-time self-reports of behaviors, contexts, and perceptions in naturalistic settings. Social network analysis (SNA) has the potential to provide a more nuanced and in-depth information such as dyadic and personal network measures of social bridging, bonding, norms, and influence. To examine these influences on a more granular level, this project will evaluate the feasibility of combining EMA and SNA techniques to collect primary data describing social and built environment associations with PA within a sample of youth during the summer. To examine the feasibility of using both EMA and SNA, 100 youth (12-15 years, going into 7th-9th grade) will be recruited through a partnership with a local school district to participate in a survey, 7-day EMA, and follow-up interview. Youth will report their most salient social connections and built environment perceptions via researcher administered surveys. EMA will elicit momentary perceptions of social and built environments, which will be time matched with the accelerometer assessed PA data. Specific characteristics of youth personal networks will be captured through SNA and momentary perceptions of these networks using EMA. Likewise, we will measure built environment through momentary perceptions and GIS data. Feasibility and acceptability will be assessed by examining predictors of EMA response rate and using qualitative interviews. Further, we will use ILD to uncover micro-temporal dynamics, bidirectional effects unfolding over a short amount of time. We will quantify the heterogeneity between youths in micro-temporal dynamics by identifying ‘digital phenotypes,’ an individual- specific web of links between social and built environmental determinants. The utility of digital phenotypes lies in their ability to identify overlaps in ILD. This proposed K01 will provide developmental support for Dr. Tyler Prochnow to: 1) obtain hands-on experience in the application of EMA methods in PA research; 2) train in the evaluation of the built environment in PA research including geospatial analysis; and 3) develop an understanding of intensive longitudinal data analysis and digital phenotyping applied to health behavior research. The results of this proposed K01 project will generate significant new knowledge describing the built and social environmental determinants of PA behavior among a diverse sample of youth in the summer. This project is innovative in its application of both EMA and SNA techniques to characterize these relationships.