TY  - JOUR
PY  - 2020//
TI  - Decomposing implicit associations about life and death improves our understanding of suicidal behavior
JO  - Suicide and life-threatening behavior
A1  - O'Shea, Brian A.
A1  - Glenn, Jeffrey J.
A1  - Millner, Alexander J.
A1  - Teachman, Bethany A.
A1  - Nock, Matthew K.
SP  - 1065
EP  - 1074
VL  - 50
IS  - 5
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 0363-0234
UR  - http://dx.doi.org/10.1111/sltb.12652
ID  - ref1
ER  -