Multisite Prevention of Conduct Problems (Fast Track)

National Institute on Drug Abuse (NIDA), U.S. Department of Education, National Institute of Mental Health (NIMH)

The primary aim of this project is to evaluate the effects of a comprehensive intervention to prevent severe and chronic conduct problems in a sample of children selected as high-risk when they first entered school. It is hypothesized that the intervention will have positive effects on proximal child behavior in middle school, and high school affecting long-term adolescent outcomes such as conduct disorder, juvenile delinquency, school dropout, substance use, teen pregnancy, relational competence with peers, romantic partners and parents, education and employment and social and community integration.

This study is a comprehensive intervention project designed to look at how children develop across their lives by providing academic tutoring and lessons in developing social skills and regulating their behaviors. There can be multiple stressors and influences on children and families that increase their risk levels. In such contexts, some families that experience marital conflict and instability can cause inconsistent and ineffective parenting. These children can sometimes enter school poorly prepared for the social, emotional, and cognitive demands of this setting. Often the child will then attend a school with a high number of other children who are similarly unprepared and are negatively influenced by disruptive classroom situations and punitive teacher practices. Over time, children in these circumstances tend to demonstrate particular behaviors, are rejected by families and peers, and tend to receive less support from teachers, further increasing aggressive exchanges and academic difficulties. Thus, this project is based on the hypothesis that improving child competencies, parenting effectiveness, school context and school-home communications will, over time, contribute to preventing certain behaviors across the period from early childhood through adolescence. Four geographic sites were selected for the study: Durham, NC, a small city with a large low-income population that is primarily African American; Nashville, TN, a moderated-sized city with a mix of low-to-middle income and African American and European-American population; Seattle, WA, a moderate-sized city with a low-to-middle ethnically diverse population; and central PA, a mostly rural area with low-to-middle income European American population. These sites varied widely in ethnicity (most minorities were African American, with some Latino) and poverty (as measured by free/reduced lunch rates) as follows: Durham, NC, 90% minority and 80% reduced lunch; Nashville, TN, 54% minority and 78% reduced lunch; rural PA; 1% minority and 39% reduced lunch; and Seattle, WA, 52% minority and 46% reduced lunch. "High risk" schools within each site (12 in Durham, 9 in Nashville, 18 in PA, and 16 in Seattle) were selected based on crime and poverty statistics of the communities that they served. Within each site, schools were divided into one to three paired sets matched for demographics (size, percentage free or reduced lunch, and ethnic composition), and one set within each pair was randomly assigned to intervention and one to control condition. Students at these elementary schools moved into middle school at grade 5, 6 or 7. A multiple-gating screening procedure that combined teacher and parent ratings of disruptive behavior was applied to all kindergarteners across three cohorts (1991-93) in these 55 schools. Children were screened initially for classroom conduct problems by teachers, using the Teacher Observation of Child Adjustment-Revised (TOCA-R) Authority Acceptance Score. Those children scoring in the top 40% within cohort and site were then solicited for the next stage of screening for home behavior problems by the parents, using a novel 22-item instrument that included items from the Child Behavior Checklist (Achenbach, 1991a), the Revised Behavior Problem Checklist, and novel items that we created for this study. 91% (n=3,274) completed the home-behavior screen. The teacher and parent screening scores were then standardized within site, based on screening a representative sample of approximately 100 children within each site (which also served as a normative comparison), and then summed to yield a total severity-of-risk screen score. Children were selected for inclusion into this study based on this screen score, moving from the highest score downward until desired sample sizes were reached within sites, cohorts, and conditions. Exceptions to this inclusion rule were made when a child failed to matriculate in the first grade at a core school (n=59) or refused to participate (n=75), or to accommodate a superceding rule that no child would be the only female in an intervention group. The outcome was that three successive cohorts were recruited in 1991, 1992, and 1993 to yield a sample of 891 children (445 in the intervention group and 446 in the control group).

Participants in the Experimental group received the "Fast Track" intervention. Intervention included school-based curriculum attended by high-risk children, parents, program staff, and occasionally teachers, home visiting, the the in-class PATHS prevention program.

Participants in the Control group were not eligible to receive the Fast Track intervention. These children received other services as usual, and served as the randomized comparison group for examining Fast Track program impacts

First grade intervention included a weekly two-hour curriculum-based day that was attended by high-risk children, parents, program staff, and teachers of the high-risk children. During each session, the staff modeled academic tutoring with target children in the presence of their parents. In 3rd and 4th grades, intervention consisted of monthly parent and child curriculum-based sessions during the academic year, home visiting, and teachers implementing the in-class PATHS prevention program. In 5th and 6th grades, intervention included monthly parent and child groups and home visiting. In grades 8, 9 and 10 staff developed sessions on an as needed basis to cover topics like transition to high school, note-taking, and study skills.

Assessment of participant rates of anti-social behaviors (e.g., fighting, criminal activity) in Grades 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10.

Assessment of participant drug, alcohol, and tobacco use (e.g., any use, frequency of use) in Grades 6, 7, 8, 9, and 10.

Assessment of participant engagement in various sexual activities (e.g., sexual intercourse) in Grades 6, 7, 8, 9, and 10.

Assessment of participant rates of psychiatric disorders (e.g., clinical depression) in Grades 6, 7, 8, 9, and 10.

Assessment of participant academic achievement (e.g., grades, standardized test scores) in Grades 6, 7, 8, 9, and 10.

Inclusion Criteria: must be in public schools in 4 study sites must be in 1st grade Exclusion Criteria: cannot be older than 1st grade could not score in the top 40% on the TOCA-R

The Fast Track Project is committed to a policy of allowing the research community access to data, under conditions that strictly protect the rights and privacy of Fast Track participants. The research design that has guided Fast Track data collection over the entire study period requires a restricted-use mechanism for sharing the data with the research community. As noted, the restricted-use data policy currently applies to data from years 1 through 15 of the study. The full terms of the Fast Track data sharing plan and access criteria exceed the 1000 character limit. Full information about the data-use policy and application forms can be found at http://fasttrackproject.org/request-use-data.php

Eligibility of Investigators and Receiving Institutions In order to be considered eligible to receive Fast Track data, an investigator must have a Ph.D. or other terminal degree, and hold a faculty appointment or other research position at the receiving institution. Graduate students who wish to use Fast Track data for dissertation research must apply through their faculty advisors. Eligible receiving institutions include not-for-profit research organizations, government agencies, and institutions of higher education. Receiving institutions must have established protocols for reviewing research using sensitive data, through an Institutional Review Board or equivalent body.

Jones D, Godwin J, Dodge KA, Bierman KL, Coie JD, Greenberg MT, Lochman JE, McMahon RJ, Pinderhughes EE. Impact of the fast track prevention program on health services use by conduct-problem youth. Pediatrics. 2010 Jan;125(1):e130-6. doi: 10.1542/peds.2009-0322. Epub 2009 Dec 14.

Slough NM, McMahon RJ, Bierman KL, Coie JD, Dodge KA, Foster EM, Greenberg MT, Lochman JE, McMahon RJ, Pinderhughes EE. Preventing Serious Conduct Problems in School-Age Youths: The Fast Track Program. Cogn Behav Pract. 2008 Feb 1;15(1):3-17. doi: 10.1016/j.cbpra.2007.04.002.

Bierman KL, Coie JD, Dodge KA, Foster EM, Greenberg MT, Lochman JE, McMahon RJ, Pinderhughes EE; Conduct Problems Prevention Research Group. The effects of the fast track program on serious problem outcomes at the end of elementary school. J Clin Child Adolesc Psychol. 2004 Dec;33(4):650-61. doi: 10.1207/s15374424jccp3304_1.

Bierman KL, Coie JD, Dodge KA, Greenberg MT, Lochman JE, McMahon RJ, Pinderhughes EE; Conduct Problems Prevention Research Group. Using the Fast Track randomized prevention trial to test the early-starter model of the development of serious conduct problems. Dev Psychopathol. 2002 Fall;14(4):925-43. doi: 10.1017/s0954579402004133.

Kam CM, Greenberg MT, Bierman KL, Coie JD, Dodge KA, Foster ME, Lochman JE, McMahon RJ, Pinderhughes EE; Conduct Problems Prevention Research Group. Maternal depressive symptoms and child social preference during the early school years: mediation by maternal warmth and child emotion regulation. J Abnorm Child Psychol. 2011 Apr;39(3):365-77. doi: 10.1007/s10802-010-9468-0.

Conduct Problems Prevention Research Group. The effects of the fast track preventive intervention on the development of conduct disorder across childhood. Child Dev. 2011 Jan-Feb;82(1):331-45. doi: 10.1111/j.1467-8624.2010.01558.x.

Conduct Problems Prevention Research Group. Fast Track intervention effects on youth arrests and delinquency. J Exp Criminol. 2010 Jun;6(2):131-157. doi: 10.1007/s11292-010-9091-7.

Conduct Problems Prevention Research Group. The effects of a multiyear universal social-emotional learning program: The role of student and school characteristics. J Consult Clin Psychol. 2010 Apr;78(2):156-68. doi: 10.1037/a0018607.

Dodge KA, Godwin J; Conduct Problems Prevention Research Group. Social-information-processing patterns mediate the impact of preventive intervention on adolescent antisocial behavior. Psychol Sci. 2013 Apr;24(4):456-65. doi: 10.1177/0956797612457394. Epub 2013 Feb 13.

Bierman KL, Coie J, Dodge K, Greenberg M, Lochman J, McMohan R, Pinderhughes E; Conduct Problems Prevention Research Group. School outcomes of aggressive-disruptive children: prediction from kindergarten risk factors and impact of the fast track prevention program. Aggress Behav. 2013 Mar-Apr;39(2):114-30. doi: 10.1002/ab.21467. Epub 2013 Feb 5.

Sorensen LC, Dodge KA; Conduct Problems Prevention Research Group. How Does the Fast Track Intervention Prevent Adverse Outcomes in Young Adulthood? Child Dev. 2016 Mar-Apr;87(2):429-45. doi: 10.1111/cdev.12467. Epub 2015 Dec 16.

Dodge KA, Bierman KL, Coie JD, Greenberg MT, Lochman JE, McMahon RJ, Pinderhughes EE; Conduct Problems Prevention Research Group. Impact of early intervention on psychopathology, crime, and well-being at age 25. Am J Psychiatry. 2015 Jan;172(1):59-70. doi: 10.1176/appi.ajp.2014.13060786. Epub 2014 Oct 31. Erratum In: Am J Psychiatry. 2015 Jan;172(1):100.

Albert D, Belsky DW, Crowley DM, Latendresse SJ, Aliev F, Riley B, Sun C; Conduct Problems Prevention Research Group; Dick DM, Dodge KA. Can Genetics Predict Response to Complex Behavioral Interventions? Evidence from a Genetic Analysis of the Fast Track Randomized Control Trial. J Policy Anal Manage. 2015 Summer;34(3):497-518. doi: 10.1002/pam.21811.

Albert D, Belsky DW, Crowley DM, Bates JE, Pettit GS, Lansford JE, Dick D, Dodge KA. Developmental mediation of genetic variation in response to the Fast Track prevention program. Dev Psychopathol. 2015 Feb;27(1):81-95. doi: 10.1017/S095457941400131X.

Zheng Y, Albert D, McMahon RJ, Dodge K, Dick D; Conduct Problems Prevention Research Group. Glucocorticoid Receptor (NR3C1) Gene Polymorphism Moderate Intervention Effects on the Developmental Trajectory of African-American Adolescent Alcohol Abuse. Prev Sci. 2018 Jan;19(1):79-89. doi: 10.1007/s11121-016-0726-4.

Goulter N, McMahon RJ, Dodge KA; Conduct Problems Prevention Research Group. Does the Fast Track Intervention Prevent Later Psychosis Symptoms? Prev Sci. 2019 Nov;20(8):1255-1264. doi: 10.1007/s11121-019-01041-1.

Godwin JW; Conduct Problems Prevention Research Group. The Fast Track intervention's impact on behaviors of despair in adolescence and young adulthood. Proc Natl Acad Sci U S A. 2020 Dec 15;117(50):31748-31753. doi: 10.1073/pnas.2016234117. Epub 2020 Dec 1.

Rothenberg WA, Lansford JE, Godwin JW, Dodge KA, Copeland WE, Odgers CL, McMahon RJ, Goulter N; Conduct Problems Prevention Research Group. Intergenerational effects of the Fast Track intervention on the home environment: A randomized control trial. J Child Psychol Psychiatry. 2023 May;64(5):820-830. doi: 10.1111/jcpp.13648. Epub 2022 Jun 15.