Research Projects

Examining the Non-Suicidal Self-Injury and Suicidal Thoughts and Behaviors Self-Disclosure Process

We are investigating factors that may contribute to willingness to disclose self-injury and suicidal thoughts and behaviors, how others respond in the face of such disclosures, and if these experiences differ by behavior or participant characteristics. One particular barrier that we are focusing on is the experience of self and other stigma. 

 

Interpersonal Contexts as Acute and Chronic RIsk Factors for Non-Suicidal Self-Injury, Suicidal Thoughts and Behaviors, and Other Maladaptive Behavior Engagement

Through experimental and ecological momentary assessment designs we are examining the influence of social processes in the occurrence of self-injurious thoughts and behaviors. Additionally, in a pilot study funded by the Notre Dame Advanced Diagnostics and Therapeutics Discovery Fund, we are focused specifically on the potentially overlapping influence of interpersonal factors in the co-occurrence of substance use and suicidal thoughts and behaviors.

 

Prediction of Suicide Risk and Return for Services among Patients in Suicidal Crisis

We are working in collaboration with colleagues at the Geisinger Healthcare System which aims to utilize electronic medical records, in addition to explicit and implicit measures of symptomatology during patient emergency department visits and psychiatric inpatient stays, to prospectively predict return for services and suicidal thoughts and behaviors. Results have the potential to improve current suicide risk assessment and treatment planning, optimizing patient care while conserving resources.

 

Using Integrative Data Mining to Improve the Prediction of Suicidal Thoughts and Behaviors

We are conducting a pilot study funded by the Notre Dame Advanced Diagnostics and Therapeutics Discovery Fund, in collaboration with Co-PI Jacobucci, which aims to identify important correlates and improve prediction of distinct suicide outcomes. Through the combination of machine learning and data integration, our goal is to elucidate the relationship between risk factors at multiple levels of analysis and the occurrence of suicidal ideation, plans, and attempts.