# Dynamic Network Analysis of Social Cognition and Suicide in Psychosis

> **NIH NIH F31** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2024 · $18,842

## Abstract

PROJECT SUMMARY/ABSTRACT
People with serious mental illness (SMI; i.e., schizophrenia, schizoaffective disorder, bipolar disorder, and
major depressive disorder with psychotic features) are at an increased risk of suicidal ideation and behavior as
compared to the general population. Despite this, there is still relatively little understanding of the mechanisms
that contribute to suicidal ideation in SMI, and people with SMI are excluded in almost 80% of biobehavioral
clinical trials. Recent research indicates that aberrant social cognitive emotion processing, in particular over-
attribution of threat, is common in psychosis and is associated with suicide ideation and behavior. Our prior
work indicates that perceived burdensomeness and thwarted belongingness can be measured validly with
ecological momentary assessment (EMA) in SMI and relate to suicidal ideation in this population. However, the
relationships social cognitive abilities and biases, which can be objectively measured, have not been explored
in a dynamic fashion. Social cognitive interventions are effective in psychosis but to date have not been
evaluated as a component of suicide prevention. This project will evaluate real-time dynamic and longitudinal
linkages between social cognitive abilities and biases measured by a validated mobile social cognitive testing
tool, in a large sample of people SMI stratified by suicide ideation. Furthermore, the candidate will apply a
novel computational technique, network analysis adapted for EMA data, to understand time-varying factors
affecting these modifiable constructs related to suicide in psychosis. Network analyses augment traditional
within-person analyses with EMA data to evaluate complex time interdependencies among variables, including
density and time-lagged relationships. This project will utilize existing EMA, mobile cognitive, and longitudinal
in-lab data collected from an NIMH supported study that includes 304 people with SMI. This proposed F31
project aims to understand the individual time-varying relationships between over-attribution of threat, social
variables, perceived burdensomeness, and thwarted belongingness using traditional mixed-effects models,
and utilize network analyses to evaluate the interdependencies among these constructs and symptoms
between people with and without suicidal ideation. Then, this project aims to examine how these baseline
associations and networks predict ideation trajectories and suicidal behavior at 12-month follow-up. In
conjunction, the training opportunities afforded by the F31 funding mechanism will facilitate the applicant’s
long-term goal of becoming an independent investigator in the psychological and social cognitive contributors
to suicide in psychotic disorders, capable of applying sophisticated computational approaches to inform new
translational interventions including those delivered in real time through digital health. This proposal is
consistent with NIMH strategy aim 2.2.A. by eva...

## Key facts

- **NIH application ID:** 10892045
- **Project number:** 5F31MH131368-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Emma Marie Parrish
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $18,842
- **Award type:** 5
- **Project period:** 2023-04-28 → 2025-04-27

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10892045

## Citation

> US National Institutes of Health, RePORTER application 10892045, Dynamic Network Analysis of Social Cognition and Suicide in Psychosis (5F31MH131368-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10892045. Licensed CC0.

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