ArticleSuicide & life-threatening behavior2020
Decomposing implicit associations about life and death improves our understanding of suicidal behavior.
Article in Suicide & life-threatening behavior, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 18 citations in OpenAlex.
- Effects of Cyberball on cognitive vulnerability for suicide in youth with a history of multiple suicide attempts.Frontiers in psychiatry · 2026Article
- Childhood violence exposure and social information processing in young adults: Does relationship with the perpetrator matter?Clinical psychological science : a journal of the Association for Psychological Science · 2025Article
- Using the death/suicide implicit association task to prospectively predict near-term suicidal behavior in high-risk veterans.Behaviour research and therapy · 2025Article
- Exploring Implicit Emotional Associations With Death in Patients With Current Suicidal Ideation: Results From Novel Attitude Implicit Association Tests for Suicide.Suicide & life-threatening behavior · 2025Article
- Brain Activation During Suicide-Specific Cognition in Trauma-Exposed Veterans.Suicide & life-threatening behavior · 2025Article
- Predicting suicidal ideation in psychiatrically hospitalized veterans using the death/suicide Implicit Association Test: A prospective cohort study.Suicide & life-threatening behavior · 2023Article
- Suicidality and mood: the impact of trends, seasons, day of the week, and time of day on explicit and implicit cognitions among an online community sample.Translational psychiatry · 2023Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
The Death/Suicide Implicit Association Test (IAT) is effective at detecting and prospectively predicting suicidal thoughts and behaviors. However, traditional IAT scoring procedures used in all prior studies (i.e., D-scores) provide an aggregate score that is inherently relative, obfuscating the separate associations (i.e., "Me = Death/Suicide," "Me = Life") that might be most relevant for understanding suicide-related implicit cognition. Here, we decompose the D-scores and validate a new analytic technique called the Decomposed D-scores ("DD-scores") that creates separate scores for each category ("Me," "Not Me") in the IAT. Across large online volunteer samples (N > 12,000), results consistently showed that a weakened association between "Me = Life" is more strongly predictive of having a history of suicidal attempts than is a stronger association between "Me = Death/Suicide." These findings replicated across three different versions of the IAT and were observed when calculated using both reaction times and error rates. However, among those who previously attempted suicide, a strengthened association between "Me = Death" is more strongly predictive of the recency of a suicide attempt. These results suggest that decomposing traditional IAT D-scores can offer new insights into the mental associations that may underlie clinical phenomena and may help to improve the prediction, and ultimately the prevention, of these clinical outcomes.
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