Digital Monitoring of Emotion Regulation and Suicidal Ideation among Individuals at Clinical High Risk for Psychosis - PROJECT SUMMARY Individuals clinical high risk for psychosis (CHR-P) are at increased risk for suicide with approximately 66% reporting suicidal ideation and up to 30% reporting suicidal behavior. Despite these high rates, very little is known about the mechanisms that contribute to suicidal thoughts in this population. The proposed study addresses this gap by examining emotion regulation as a mechanism for suicidal ideation using the Extended Process Model as a guiding framework. According to this model, emotion regulation is a dynamic process that involves 1) the identification of the need to regulate, 2) the selection of an emotion regulation strategy, 3) the implementation of that strategy, and 4) ongoing monitoring dynamics to determine whether to maintain, switch, or stop strategies. Our preliminary data using ecological momentary assessment (EMA) suggests that individuals with psychosis exhibit abnormalities across all of these stages. Additionally, we have found that identification, selection, and implementation stage abnormalities are associated with suicidal ideation in real time. More specifically, suicidal ideation is associated with a higher threshold for deciding to regulate, suggesting that this population may be regulating too late. This finding has critical implications, as regulating too late may subsequently influence strategy selection and effectiveness, resulting in emotional cascades that often precede suicidal ideation. This may be particularly relevant for individuals at CHR-P, given the established finding that they have difficulty identifying and recognizing their emotions—critical information that is needed to determine when to regulate. Thus, innovative time-sensitive approaches are needed to detect and assist individuals at CHR-P with identifying when to regulate. To address this gap, the current project will combine EMA, wearable sensors, and smartphone-based technology to study emotion regulation as a mechanism for suicidal ideation in CHR-P using the Extended Process Model as a guiding framework. We will recruit 40 individuals at CHR-P with suicidal ideation/behavior, 40 clinical controls with suicidal ideation/ behavior, and 40 non-clinical controls to complete two research visits (baseline and 1mo follow up) and 28 days of intensive ambulatory assessments (EMA, wearables, smartphone sensing). This data will be used to complete the following aims: 1) Estimate the effect sizes for unique and trans-diagnostic emotion regulation stages predicting time-lagged suicidal ideation in CHR-P; 2) Establish the validity of using wearable and smartphone sensors to objectively detect emotion regulation stages in real time. Findings from this study will inform future grants designed to develop/test prospective algorithms for predicting suicidal ideation and develop/test a just-in-time intervention for reducing suicide risk among individuals at CHR-P.
