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Real-time affective predictors of suicidal thinking: A dynamic structural equation modeling study.

Evan M Kleiman¹, Mariah T Hawes-Sousa², Elizabeth E Edershile³

¹Department of Psychology, Rutgers, The State University of New Jersey, United States of America; Rutgers University Behavioral Healthcare, United States of America; Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, United States of America.

Journal of Affective Disorders

|September 15, 2025

Summary

Affective states like sadness are linked to suicidal thinking, but their ability to predict future suicidal thoughts is limited. This highlights challenges in short-term suicide risk prediction.

Keywords:

DSEM Ecological momentary assessment (EMA)Suicidal ideation Suicide

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Area of Science:

Psychology
Psychiatry
Mental Health

Background:

Ecological momentary assessment (EMA) advances suicidal thinking research by capturing variability.
Limitations include conservative analytics, lack of passive/active suicidal thinking differentiation, and underrepresentation of high arousal negative emotions.

Purpose of the Study:

To examine proximal affective predictors of suicidal thinking using Dynamic Structural Equation Modeling (DSEM).
To differentiate between passive and active suicidal thinking and their relation to affective states.

Main Methods:

Used DSEM to analyze within-person and between-person relationships.
Assessed passive and active suicidal thinking, sadness, anxiety, and emotional distress in 106 adults post-inpatient care.

Main Results:

Strong contemporaneous associations found between affective states and suicidal thinking.
Sadness predicted passive suicidal thinking, but no affective variables predicted active suicidal thinking prospectively.
Sadness showed stronger contemporaneous association with suicidal thinking than anxiety.

Conclusions:

Affective states are closely linked to immediate suicidal thinking but have limited predictive utility for near-future suicidal thoughts.
Highlights challenges in short-term suicide risk prediction.
Emphasizes the need for research on dynamic predictors differentiating passive and active suicidal thoughts.