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. 2020 Feb 28;11:90. doi: 10.3389/fpsyt.2020.00090

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Copyright © 2020 Hoffman, Jacobs, Dennis, McCready, Hickok, Smith and Kohno

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Hierarchical multiple regression analysis to predict criminal offenses. The model includes factors hypothesized to contribute to a history of criminal convictions in the MA group. Model 1 includes PPI-1 and PPI-2 scores, Years of MA use, Average daily MA use and GAD-7 anxiety scores. Model 2 includes variables listed in Model 1 plus corticostriatal RSFC values. (A) Total Convictions: RSFC values improved the model by 1.69%. The most significant predictors are PPI-2 scores, daily MA use and corticostriatal RSFC. (B) Violent Offenses: RSFC values only improved the model by 1.2% and the most significant predictors of violent offenses are PPI-2 and years of MA use. (C) Acquisitive Crimes: RSFC values increased the model by 36.8.5% and indicates that greater daily MA use and greater corticostriatal RSFC are significant predictors of acquisitive crimes. (D) Drug Offenses: The independent variables accounted for the least amount of variance associated with drug offenses with greater PPI-2 scores associated with more drug offenses.