OBJECTIVE: We tested a dual-process model based on behavioral and emotional regulation constructs, which posits that good self-control and poor regulation make independent contributions and have different types of pathways to outcomes. The utility of the model for predicting substance use was tested in two diverse populations of younger adolescents. METHOD: A survey was administered in classrooms to middle-school students in Westchester County, New York (N = 601) and Honolulu, Hawaii (N = 881). The New York sample was 8% African American, 5% Asian American, 47% Caucasian, 31% Hispanic, and 9% other ethnicity. The Hawaii sample was 21% Asian American, 8% Caucasian, 26% Native Hawaiian/Pacific Islander, 34% Filipino, and 10% other ethnicity. Structural equation modeling analyses tested pathways from the four regulation variables through six hypothesized mediators to a criterion construct of substance use (tobacco, alcohol, and marijuana). RESULTS: Results were replicated across samples and were consistent with prediction. Unique contributions were found for good self-control and poor regulation, including both behavioral and emotional aspects. Good self-control had an inverse effect on substance use primarily through relations to higher levels of protective factors (e.g., academic competence). Poor regulation independently had a risk-promoting effect on substance use through relations to higher levels of risk factors (e.g., negative life events). CONCLUSIONS: Two field studies showed the dual-process model is robust across different populations. Substance prevention programs should consider approaches for enhancing good self-control as well as procedures for reducing poor regulation and minimizing its impact. Extensions to health behaviors including dietary intake and physical activity are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.
OBJECTIVE: We tested a dual-process model based on behavioral and emotional regulation constructs, which posits that good self-control and poor regulation make independent contributions and have different types of pathways to outcomes. The utility of the model for predicting substance use was tested in two diverse populations of younger adolescents. METHOD: A survey was administered in classrooms to middle-school students in Westchester County, New York (N = 601) and Honolulu, Hawaii (N = 881). The New York sample was 8% African American, 5% Asian American, 47% Caucasian, 31% Hispanic, and 9% other ethnicity. The Hawaii sample was 21% Asian American, 8% Caucasian, 26% Native Hawaiian/Pacific Islander, 34% Filipino, and 10% other ethnicity. Structural equation modeling analyses tested pathways from the four regulation variables through six hypothesized mediators to a criterion construct of substance use (tobacco, alcohol, and marijuana). RESULTS: Results were replicated across samples and were consistent with prediction. Unique contributions were found for good self-control and poor regulation, including both behavioral and emotional aspects. Good self-control had an inverse effect on substance use primarily through relations to higher levels of protective factors (e.g., academic competence). Poor regulation independently had a risk-promoting effect on substance use through relations to higher levels of risk factors (e.g., negative life events). CONCLUSIONS: Two field studies showed the dual-process model is robust across different populations. Substance prevention programs should consider approaches for enhancing good self-control as well as procedures for reducing poor regulation and minimizing its impact. Extensions to health behaviors including dietary intake and physical activity are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Authors: Jeffrey S Simons; Raluca M Simons; Stephen A Maisto; Austin M Hahn; Kyle J Walters Journal: Exp Clin Psychopharmacol Date: 2018-02 Impact factor: 3.157
Authors: Jeffrey S Simons; Raluca M Simons; Carol O'Brien; Scott F Stoltenberg; Jessica A Keith; Jaime A Hudson Journal: Addict Behav Date: 2016-09-04 Impact factor: 3.913