The pervasive use of smartphones for social interaction has changed the landscape of adolescent social life in ways that have not been adequately characterized. Despite this rapid rise in digital social activity (DSA; calls, messaging, and social media app usage), it remains unclear how this dramatic shift has impacted adolescent development and wellbeing. Previous work in this area has been limited by overly general measures that treat DSA as a single construct (e.g., total screentime), inaccurate self-report estimates, cross-sectional studies that cannot speak to dynamic relationships over time, and limited attention to mechanistic markers of risk and resilience.
This project leverages real-time digital phenotyping data and machine learning approaches to characterize how DSA and the developing self-concept interact to shape adolescent resilience and wellbeing. 80 adolescents aged 12-17y will participate in an intensive longitudinal design, providing 8 months of rich multi-modal data that includes: continuous passive collection of DSA via smartphone, ecological momentary assessments (i.e., brief surveys on the smartphone) of wellbeing and virtue embodiment (e.g., gratitude, optimism, curiosity, compassion), monthly measures of wellbeing and virtue embodiment, and experimental task behavior to extract biases in social threat processing.
Identifying factors conferring risk or resilience at a fine-grained level of temporal specificity has the potential to inform individually-targeted and scalable interventions. Thus, we include a pilot intervention study that will leverage real-time data and machine learning to enhance resilience via character virtue embodiment using individually tailored (i.e., idiographic) nudges to smartphones providing the right type of prompt at the right time. The project is poised to significantly advance the field by using innovative methods to characterize how teens shape and are shaped by the digital age of socialization.
