Evidence map›Paper›PMID 41033177›Full record

ArticleBehaviour research and therapy2025

Using the death/suicide implicit association task to prospectively predict near-term suicidal behavior in high-risk veterans.

Megan S Chesin, Alejandro Interian, Vibha Reddy, Arlene King, Kayla Maloney, Rachael Miller, Rokas Perskaudas, Kailyn Rodriguez, Lauren St Hill, John Keilp and 1 more

Abstract read
In one paragraph

Article in Behaviour research and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Megan S ChesinDepartment of Psychology, William Paterson University, Wayne, NJ, USA. Electronic address: chesinm@wpunj.edu.
Alejandro InterianMental Health and Behavioral Sciences, VA New Jersey Health Care System, Lyons, NJ, USA; Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers, the State University of New Jersey, Piscataway, NJ, USA.
Vibha ReddyResearch and Development Service, VA New Jersey Health Care System, East Orange, NJ, USA.
Arlene KingMental Health and Behavioral Sciences, VA New Jersey Health Care System, Lyons, NJ, USA.
Kayla MaloneyDepartment of Psychology, William Paterson University, Wayne, NJ, USA.
Rachael MillerMental Health and Behavioral Sciences, VA New Jersey Health Care System, Lyons, NJ, USA.
Rokas PerskaudasMental Health and Behavioral Sciences, VA New Jersey Health Care System, Lyons, NJ, USA.
Kailyn RodriguezResearch and Development Service, VA New Jersey Health Care System, East Orange, NJ, USA; Department of Psychology, Rutgers University, Piscataway, NJ, USA.
Lauren St HillMental Health and Behavioral Sciences, VA New Jersey Health Care System, Lyons, NJ, USA.
John KeilpDepartment of Psychiatry, Columbia University Medical Center, New York, NY, USA.
Catherine E MyersResearch and Development Service, VA New Jersey Health Care System, East Orange, NJ, USA; Department of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers, the State University of New Jersey, Newark, NJ, USA.

Funding

CSRD VA I01 CX001826
6 · The paper itself

Abstract

The 90-day period after a suicide attempt or hospitalization for suicidal behavior is a period of increased risk for psychiatric patients. However, predicting who among patients at suicide risk will engage in suicidal behavior in this window remains an elusive task. Neurocognitive task performance, such as performance on the Death/Suicide Implicit Association Task (D/S IAT), shows some promise for aiding in the prediction of suicidal behavior beyond risk factors routinely assessed in clinical practice, such as self-reported suicidal ideation. This study considered whether performance on the D/S IAT could prospectively predict suicidal behavior within a 90-day window. Sixty Veterans at high risk for suicide completed the D/S IAT at multiple timepoints over a one-year period. Each testing session was then coded according to whether the participant displayed suicidal behavior within 90 days following that testing session. As a secondary aim, drift diffusion modeling (DDM) was used to estimate latent cognitive processes mediating D/S IAT performance, including decisional efficiency. Two applications of the Generalized Estimating Equations (GEE) method were used to evaluate the incremental utility of (1) D/S IAT performance and (2) DDM-derived latent variables on predicting 90-day suicidal behavior over standard suicide risk factors including suicide attempt history, major depressive or bipolar disorder, and suicidal ideation at the time of testing. Age was also included in the models given the impact of age on reaction times and thus D/S IAT performance. The odds of 90-day suicidal behavior were significantly increased as implicit bias linking the self-concept to the concept of life as opposed to death weakened. The latent cognitive process of reduced decisional efficiency towards categorizing the concept of life relative to death as "like me" predicted 90-day suicidal behavior. D/S IAT performance may add to near-term suicidal behavior prediction. Reduced decisional efficiency is emerging as a general cognitive factor implicated in suicidal behavior.

Indexed as

Suicidal IdeationSuicideSuicide, AttemptedVeteransAdultFemaleHumansMaleMiddle AgedNeuropsychological TestsProspective StudiesRisk FactorsDeath/suicide implicit association taskD/S IATNear-term suicidal behaviorPredictionVeterans

Identifiers

PMID41033177
PMCPMC12670172

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.