PROJECT SUMMARY/ABSTRACT Suicide is the second leading cause of death among adolescents and the rates have doubled since 2000. The rise in suicide rates is due in part to a failure to identify short-term risk factors for suicidal thoughts and behaviors. Additionally, most existing research relies primarily on group-level methodological approaches to suicide risk assessment; intraindividual suicide risk processes are largely neglected. Because of the lack of knowledge on short-term and individual-level suicide risk, it remains unclear when and how to intervene with the individual adolescents who need it most. Three particularly promising observable, state-sensitive, temporally delimited, and modifiable proximal indicators of suicide risk among adolescents are social engagement, sleep, and physical activity. Although acute changes in these behavioral processes are often denoted as imminent “behavioral warning signs” of suicide, most existing research has examined these behavioral factors only as distal predictors and correlates of suicide risk. Importantly, their contribution to short- term risk using individual-level approaches (i.e., fully idiographic, “n-of-1” methods) remains unknown. The Candidate’s proposed K23’s overarching goal is to employ mobile sensing and actigraphy to assess whether objectively and passively measured acute behavioral changes from typical patterns of social engagement, sleep, and physical activity indicate proximal risk for increases in suicidal ideation using idiographic n-of-1 models in high-risk adolescents. It further aims to characterize the intraindividual network structure of these behavioral factors and suicidal ideation to enhance suicide risk assessment and guide intervention. Adolescents (N=100) admitted to an inpatient or partial hospital program due to acute suicide risk will be recruited. For a period of 3 months, wearable actigraphs will be used to assess adolescents’ sleep and physical activity and mobile sensing will be used to assess adolescents’ digital social engagement and patterns of movement to approximate additional indices of physical activity. Once-daily mobile surveys will be used to assess suicidal ideation. The proposed training plan complements the Candidate’s research plan and will facilitate training in: conducting translational digital health research in high-risk adolescents, passive mobile sensing, passive adolescent sleep and physical activity assessment via actigraphy, and advanced computational approaches to person-specific intensive data modeling. A team of leading scholars will provide expert mentorship to facilitate the Candidate’s training goals within the highly resourced environment of the Alpert Medical School of Brown University and Rhode Island Hospital. The proposed study will promote the Candidate’s long-term career goal to employ low-burden and scalable methods of assessment to develop personalized risk models that will improve the proximal prediction of suicide risk and...