Innovative Ways to Address Mental Health Issues

Three of the U01 projects within ILHBN focus on mental health issues targeting individuals from pre-adolescence to adulthood. Those projects were discussed at the ILHBN Annual Conference in October, 2022.

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Dr. Justin Baker discusses deep phenotyping tools with the Network. ​​​

Bipolar Longitudinal Study (BLS) The Robust Predictors of Mania and Psychosis (RPMP) study led by Drs. Justin Baker and Scott Rauch at the McLean Hospital serves to identify early biological, environmental, and social factors that trigger mania and psychosis in individuals known to be at risk for these mental health conditions using smartphone, wearable, GPS, and audio-video data. Use of such passive and active markers helps lay the groundwork for tailored intervention strategies that account for the multifaceted nature and etiologies of psychosis and bipolar disorders so as to maximize intervention efficacy at the individual level.   Publications written by the BLS team include “Case Report of Dual-Site Neurostimulation and Chronic Recording of Cortico-Striatal Circuitry in a Patient With Treatment Refractory”[1] and “Determining sample size and length of follow-up for smartphone-based digital phenotyping studies”[2].


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Nick Allen discussing digital phenotyping with the Network at the ILHBN Annual Conference.​​​​​​

Mobile Assessment for the Prediction of Suicide (MAPS) the Mobile Assessment for the Prediction of Suicide (MAPS) study led by Drs. Nicholas Allen and Randy Auerbach at the University of Oregon and Columbia University, respectively, also leverages mobile technologies, specifically, adolescents' naturalistic use of smartphone technology and phone usage data (e.g., text messages, music choices, ambient light, screen-on time, video and audio diaries) to identify promising short-term predictors of suicide among high-risk adolescents, thereby improving the understanding, prediction, and prevention of suicidal behaviors – the second leading cause of death among adolescents – and associated health outcomes.  Publications include “Short-term prediction of suicidal thoughts and behaviors in adolescents: Can recent developments in technology and computational science provide a breakthrough?”[3] and “The Elusive Phenotype of Preadolescent Suicidal Thoughts and Behaviors: Can Neuroimaging Deliver on Its Promise?”[4] 

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Matt Nock discusses recent advances in mobile technologies.

Sensing and Mobile Assessment in Real Time (SMART)  the Intensive Longitudinal Study of Suicidal Behaviors and Related Health Outcomes (SBRHO), led by Dr. Matthew Nock at Harvard University, capitalizes on recent advancements in mobile technologies to integrate passive (e.g., GPS, accelerometer, physiological measures) and active (e.g., self-reports) markers of risk along with advanced computational modeling (e.g., machine learning) approaches to identify which people with suicidal thoughts are at greatest risk for suicidal behavior, or when and why they are at elevated risk. SMART has produced numerous papers (published or in progress) including “Negative affect is more strongly associated with suicidal thinking among suicidal patients with borderline personality disorder than those without”[5] and “Advancing the Understanding of Suicide: The Need for Formal Theory and Rigorous Descriptive Research”[6] 

[1] Olsen, Sarah T; Basu, Ishita; Bilge, Mustafa Taha; et al.

Barnett, Ian; Torous, John; Reeder, Harrison T; Baker, Justin; Onnela, Jukka-Pekka

Allen, Nicholas B; Nelson, Benjamin W; Brent, David; Auerbach, Randy P;

[4]   Auerbach, Randy P; Chase, Henry W; Brent, David A;

[5] Mou, David; Kleiman, Evan M; Fedor, Szymon; Beck, Stuart; Huffman, Jeff C; Nock, Matthew K;

[6] Millner, Alexander J; Robinaugh, Donald J; Nock, Matthew K;