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Brain potentials predict substance abuse treatment completion in a prison sample

2016; Wiley; Volume: 6; Issue: 8 Linguagem: Inglês

10.1002/brb3.501

2162-3279

Brandi C. Fink, Vaughn R. Steele, Michael Maurer, Samantha J. Fede, Vince D. Calhoun, Kent A. Kiehl,

Functional Brain Connectivity Studies

Abstract Introduction National estimates suggest that up to 80% of prison inmates meet diagnostic criteria for a substance use disorder. Because more substance abuse treatment while incarcerated is associated with better post‐release outcomes, including a reduced risk of accidental overdose death, the stakes are high in developing novel predictors of substance abuse treatment completion in inmate populations. Methods Using electroencephalography ( EEG ), this study investigated stimulus‐locked ERP components elicited by distractor stimuli in three tasks ( VO ‐Distinct, VO ‐Repeated, Go/NoGo) as a predictor of treatment discontinuation in a sample of male and female prison inmates. We predicted that those who discontinued treatment early would exhibit a less positive P3a amplitude elicited by distractor stimuli. Results Our predictions regarding ERP components were partially supported. Those who discontinued treatment early exhibited a less positive P3a amplitude and a less positive PC 4 in the VO ‐D task. In the VO ‐R task, however, those who discontinued treatment early exhibited a more negative N200 amplitude rather than the hypothesized less positive P3a amplitude. The discontinuation group also displayed less positive PC 4 amplitude. Surprisingly, there were no time‐domain or principle component differences among the groups in the Go/NoGo task. Support Vector Machine ( SVM ) models of the three tasks accurately classified individuals who discontinued treatment with the best model accurately classifying 75% of inmates. PCA techniques were more sensitive in differentiating groups than the classic time‐domain windowed approach. Conclusions Our pattern of findings are consistent with the context‐updating theory of P300 and may help identify subtypes of ultrahigh‐risk substance abusers who need specialized treatment programs.