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

Area of Science:

• Neuroscience
• Psychiatry
• Cognitive Psychology

Background:

• The 90-day period post-suicide attempt or hospitalization is critical due to heightened suicide risk.
• Predicting suicidal behavior in this high-risk window remains challenging.
• Neurocognitive tasks like the Death/Suicide Implicit Association Task (D/S IAT) show potential for improving prediction beyond standard clinical assessments.

Purpose of the Study:

• To investigate if D/S IAT performance can prospectively predict suicidal behavior within a 90-day timeframe.
• To explore if drift diffusion modeling (DDM) derived cognitive processes, such as decisional efficiency, enhance prediction of near-term suicidal behavior.

Main Methods:

• Sixty high-risk Veterans completed the D/S IAT over one year, with subsequent 90-day follow-up for suicidal behavior.
• Generalized Estimating Equations (GEE) evaluated the incremental utility of D/S IAT performance and DDM variables.
• Models included standard risk factors (attempt history, depression, ideation), age, and DDM-derived latent variables.

Main Results:

• Weakening implicit bias linking self to life (vs. death) significantly increased odds of 90-day suicidal behavior.
• Reduced decisional efficiency in categorizing life concepts predicted 90-day suicidal behavior.
• D/S IAT performance and decisional efficiency offered incremental predictive value over traditional risk factors.

Conclusions:

• D/S IAT performance shows promise for predicting near-term suicidal behavior.
• Reduced decisional efficiency is an emerging cognitive factor implicated in suicidal behavior.
• Integrating neurocognitive assessments may improve clinical prediction of suicide risk.