Mental Health, Substance Use, and Delinquency Among Truant Youth in a Brief Intervention Project

Abstract

The relationship between substance use, mental health disorders, and delinquency among youth is well documented. What has received far less attention from researchers is the relationship between these issues among truant youth, in spite of studies that document truants are a population at-risk for negative outcomes. The present study bridges this gap by (1) examining psychosocial functioning and delinquency among truants, and (2) assessing the efficacy of a Brief Intervention (BI) in reducing delinquent behavior over time. To meet these objectives, data were collected from 183 truant youth enrolled in an ongoing NIDA-funded BI project. Informed by a developmental damage perspective, a structural equation model was formulated and estimated. Interim results provide overall support for the model, and suggest the BI may be a promising, innovative intervention for truant youth. Service delivery implications and directions for future analyses are discussed.

Impact of Brief Intervention Services on Drug-Using, Truant Youth Arrest Charges Over Time

“…The official record delinquency results we obtained are similar to those resulting from a recent study we completed on the youths’ self-reported delinquency over a 12-month follow-up period (Dembo et al, in press). In that longitudinal study, we examined the relationships between the youth's mental health, substance use and delinquency, and found a marginally significant, direct BI effect on delinquency at 3-month follow-up, and a nearly significant intervention BI effect ( p = 0.052) on delinquency at 12-month follow-up.…”

“…In line with previous research (Dembo et al, in press), CFA, using Bayesian estimation, confirmed the four alcohol/other drug involvement measures (baseline alcohol use, marijuana use, other drug use, and drug use diagnosis) reflected one underlying factor on which each of the measures was significantly loaded (Potential Scale Reduction [PSR] = 1.06; Posterior Predictive P-value [PPP] = 0.338). Hence, an alcohol/drug use factor score was created for further analysis.…”

“…Hence, we decided to use the log transformed measure of total delinquency in our analyses. (A longitudinal study of the youths’ self-reported delinquency data of youths in this study confirmed their validity [Dembo et al, in press]).…”

“…The rates of these problems in the sample and the results of efforts to create summary measures in each domain are presented in Appendix B. CFA, using Bayesian estimation, found a one factor model for each of these four domains (ADHD: PSR = 1.05, PPP = 0.500; mania: PSR = 1.05, PPP = 0.514; anxiety: PSR = 1.08, PPP = 0.315; depression: PSR = 1.07, PPP = 0.369) that was consistent with the data (see Dembo et al, in press; Dembo et al, under review). Based on these results, factor scores for each of these four domains were created for further analyses.…”

Revisión bibliométrica del rechazo escolar: perspectivas de investigación y su análisis

“…Principalmente, los trabajos estudiaban los indicadores de riesgo que empeoran la conducta de rechazo a la escuela ya procedan del ámbito escolar, familiar o social. Los factores de riesgo identificados son variables de desafección escolar (bajas aspiraciones educativas, malas calificaciones), el consumo de sustancias estupefacientes o alcohol, la conducta delictiva o una escasa interacción dentro del marco familiar (Dembo et al 2013;Mason, Chmelka, Howard y Thompson, 2013). En un estudio sobre las variables que predicen el absentismo escolar en base a situaciones de aula y el proceso de enseñanza-aprendizaje, se obtuvo que un ritmo de instrucción rápida y una baja percepción de carga de trabajo se asocia con altos niveles de absentismo escolar, mientras que bajos niveles de absentismo escolar se asocian con altos estándares de logro (Salzer, Trautwein, Ludtke y Stamm, 2012).…”