Heterogeneity in suicide risk: Evidence from personalized dynamic models

Area of Science:

• Psychology
• Psychiatry
• Data Science

Background:

• Most suicide theories posit within-person psychological changes drive suicidal ideation and behavior.
• Empirical research often relies on between-person analyses, limiting exploration of hypothesized within-person dynamics.
• The Interpersonal Theory of Suicide (IPTS) is a prominent theory requiring within-person examination.

Purpose of the Study:

• To empirically test the Interpersonal Theory of Suicide (IPTS) using within-person analyses.
• To investigate shared versus individual-specific pathways to suicidal thoughts and behaviors.
• To explore the utility of advanced statistical modeling for suicide research.

Main Methods:

• Utilized group iterative multiple model estimation (GIMME) for personalized statistical modeling.
• Analyzed real-time monitoring data from adult and adolescent samples with histories of suicidal thoughts/behaviors.
• Examined contemporaneous effects from hopelessness to suicidal thinking as theorized by IPTS.

Main Results:

• No theorized IPTS effects were shared at the group level across adult and adolescent samples.
• Significant heterogeneity was observed in personalized models, indicating diverse individual pathways.
• The study found limited empirical support for shared group-level mechanisms in IPTS.

Conclusions:

• Findings challenge the assumption of universally shared psychological mechanisms in suicide.
• Individualized statistical models reveal significant heterogeneity in pathways to suicidal thoughts/behaviors.
• Highlights the need for personalized approaches in suicide risk assessment and prediction.