Original title: Predicting Active Suicidality from Temporal Dynamics of Implicit Life-Death Associations
Pedram Rajaei, Aaron McInnes, Benito Garcia, Shreya Yadav +8 · September 2026
Talking to doctors about suicide does not always catch near-term risk, and there are no strong objective alternatives. Researchers investigated a computer test called the Brief Death Implicit Association Test. This test measures how fast people connect words about themselves to life or death. Usually, scientists simply average these reaction times into a single score, but that old score does not reliably spot suicidal thoughts. Instead, the researchers looked at how reaction times change over time. They tracked how people adjusted across test rounds and how they grew used to conflicting choices. They tested whether these timing patterns match suicidal thoughts recorded in daily life. The patterns showed clear differences between people with and without suicidal thoughts. A computer model reading these timing shifts successfully predicted who was having suicidal thoughts. Tracking these reaction time patterns could provide a useful behavioral marker for near-term risk.
You are learning a new card game and someone times how fast you sort the cards. If you only look at your average time, you miss that you slow down every time the sorting rule changes. In this paper, the researchers looked beyond the average time at how reaction times rose and fell with each rule change in a word-sorting test. That pattern—not the average—could tell which people were having dangerous thoughts.
Suicide risk assessment currently relies on interviews that often miss imminent danger. This study shows that reaction-time dynamics from a simple word-sorting test can flag individuals with active suicidal thoughts with 77% accuracy. If validated in larger groups, such a quick objective measure could help clinicians intervene before a crisis.
The abstract does not explicitly state limitations, but the sample is small (77 participants, only 22 with active ideation) and results rely on cross-validation within that group. Generalizability to other populations and real-world clinical settings is not addressed. The method also requires 18 blocks of a specific test, which may limit practical deployment without further simplification.
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Predicting Active Suicidality from Temporal Dynamics of Implicit Life-Death Associations — Pedram Rajaei, Aaron McInnes, Benito Garcia et al. — medRxiv — doi:10.64898/2026.09.09.26362642
Abstract licence: CC BY
Explanation generated by Synthesis from the abstract — it is not the original paper. This is a preprint, so it hasn't necessarily been peer reviewed.