Decomposing implicit associations about life and death improves our understanding of suicidal behavior
| Authors |
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| Publication date | 10-2020 |
| Journal | Suicide and Life-Threatening Behavior |
| Volume | Issue number | 50 | 5 |
| Pages (from-to) | 1065-1074 |
| Number of pages | 10 |
| Organisations |
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| 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. |
| Document type | Article |
| Note | This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 794913. - With supplementary file. |
| Language | English |
| Published at | https://doi.org/10.1111/sltb.12652 |
| Other links | https://www.scopus.com/pages/publications/85088121717 |
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