Passive Assessment of Behavioral Warning Signs for Suicide Risk in Adolescents: An Idiographic Approach

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 inform intervention for
youth. Through the execution of this research and training plan, the Candidate will be positioned to become a
leader in the field of adolescent suicide.

Grant Number: 5K23MH126168-06
NIH Institute/Center: NIH
Principal Investigator: Taylor Burke