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Identify, Respond, Prevent: Addressing Human Trafficking among Juvenile Justice- and Child Welfare-Involved Youth

Award Information

Award #
Funding Category
Competitive Discretionary
Congressional District
Past Project Period End Date
Funding First Awarded
Total funding (to date)

Description of original award (Fiscal Year 2018, $689,381)

This study will expand on previous data analyses conducted by a NIJ funded project examining human trafficking allegations investigated by the Florida child welfare agency. This project will use matched juvenile justice and child welfare data lifetime records for all youth born between 1996 and 2002 who were served by either system in Florida, building lifetime histories for a 7-year birth cohort of youth involved in either—or both—systems. The resulting analytic data set will include more than 6,000 human trafficking allegations involving more than 4,500 youth. This study will extend our understanding of human trafficking by analyzing the lifetime trajectories of system-involved youth by examining relationships among trafficking victimization, youth characteristics, and experiences in the juvenile justice and child welfare systems.

Analyses will address the following specific study goals: 1) inform identification of trafficking by assessing the predictive utility of Florida’s Human Trafficking Screening Tool, using ordered multinomial regressions and factor analysis; 2) inform practitioner response to trafficked youth by describing characteristics of those who experience trafficking during juvenile justice or child welfare supervision, or who enter juvenile justice supervision with prior human trafficking allegations, using descriptive statistics and linear and logistic regression; and 3) inform secondary prevention for at-risk youth by identifying those at greatest risk throughout adolescence and inform tertiary prevention among trafficked youth by identifying those at greatest risk of subsequent victimization following an initial trafficking allegation, using grow mixture models. Inferential models will be cross-validated using a random 50% sample of cases, and incorporate an estimate of trafficking under-identification into growth mixture models.
Study findings will be shared through multiple channels with practitioners and policy makers, via summary reports, briefs, and webinars.

"Note: This project contains a research and/or development component, as defined in applicable law," and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14).


Date Created: September 27, 2018