| Clinical Applications of Behavior Analysis With Justice-Involved Youth|
|Sunday, May 28, 2023|
|10:00 AM–10:50 AM |
|Convention Center Mile High Ballroom 2B|
|Area: CSS; Domain: Translational|
|Chair: Anna Kate Edgemon (Auburn University)|
|CE Instructor: Anna Kate Edgemon, M.S.|
Applied behavior analysis has been demonstrated as effective for addressing a wide variety of socially significant issues across many populations and contexts. Yet many marginalized populations continue to be underserved and understudied. This symposium will cover a range of methods in which behavior analytic methodology may be used in the assessment and treatment of justice-involved youth. The first presentation will describe recent prevention and intervention strategies for juvenile sex trafficking (JST) within the child welfare system. The second presentation will describe a contingency management system used within a juvenile residential treatment facility to improve staff-implemented strategies for improving behavior within the facility. The final presentation uses conditional probabilities to evaluate periods of increased likelihood of challenging behavior displayed by adolescents within a juvenile residential treatment facility. Implications and future directions within juvenile justice will be discussed.
|Instruction Level: Advanced|
|Keyword(s): conditional probabilities, contingency management, juvenile justice, sex trafficking|
|Target Audience: |
Participants should be licensed, certified, or are completing coursework to fulfill BCBA eligibility requirements.
|Learning Objectives: At the conclusion of the presentation, participants will be able to: (1) Identify environmental conditions corresponding with JST victimization, and commonly used lures for abduction and victimization (e.g., coercion, grooming, threats); (2) Gain knowledge of the training components used to train juvenile justice facility staff and be able to identify the challenges of training in this environment; and (3) Identify contexts in which statistical analysis based on behavioral data supports data-based administrative decision-making within a juvenile justice facility.|
| Review of Prevention and Intervention Strategies for Juvenile Sex Trafficking, and Future Directions|
|ARTURO GARCIA (University of South Florida), Kimberly Crosland (University of South Florida)|
|Abstract: Existing literature on human trafficking suggests the vulnerability to sexual exploitation changes by (a) the prevalence of certain risk factors (e.g., runaway, developmental disabilities); (b) the trafficker used lures; and (c) the environmental conditions present at the time of victimization. However, the extent to which vulnerability in the presence of cumulative risk factors could change the value of the lure has not been previously evaluated. Often found, youth involved in the child welfare system are at high risk for juvenile sex trafficking (JST) victimization associated with runaway instances. By assessing the commonly used lures that precede the runaway episode, a functional relationship between the lure and the environment may be established. A scoping analysis approach to screening and assessment, of both published and case studies, could be used to identify (a) prevalent indicators of victimization; (b) risk factors commonly present; and (c) traffickers used lures for the abduction and JST victimization of youth. The current paper will describe the recent prevention and intervention strategies for victims/survivors of JST. This paper will also discuss behavioral strategies that could be used to develop function-based interventions for runaway youth at high risk of victimization and vulnerability.|
| Contingency Management System: Juvenile Justice Facility|
|ASHLEY ANDERSON (Auburn University), Daniel John Sheridan (Auburn University), Anna Kate Edgemon (Auburn University), John T. Rapp (Auburn University)|
|Abstract: Punitive and negative environments contradict evidence-based rehabilitation strategies for juvenile offenders. To facilitate an evidence-based and therapeutic environment, the authors developed a comprehensive model of program-wide behavior-analytic assessments and interventions, which include best practices, a large-scale token economy, and tiered supports for residents in a juvenile justice setting. All residents, regardless of tier, participated in the token economy where residents received pretend cash or fines in correspondence with their behavior recorded through a red, yellow, and green system. Tier 1 consisted of training staff through videos on how and when to give praise, give instructions, and respond to problem behavior (i.e., best practices) as well as how to score residents for the token economy. The authors evaluated implementation fidelity through direct observation with subsequent feedback and used the behavior data acquired through the color system, as well as direct observation of resident behavior, to make data-based decisions for remedial staff training, referral of the resident for additional behavior-analytic services through Tier 2 or 3 services, or both.|
Descriptive Assessment and Analysis of Challenging Behavior Displayed by Adolescents Within a Juvenile Residential Treatment Facility
|ANNA KATE EDGEMON (Auburn University), John T. Rapp (Auburn University)|
Treatment of problematic behavior often begins with functional assessment. However, in many contexts, not all components of functional assessment are possible. That is, components of functional assessment (e.g., functional analysis) may not be feasible ethically or logistically in contexts where problematic behavior is infrequent, presents substantial risk to staff members, or both. In these contexts, behavior analysts may use indirect assessment alone to identify environmental conditions that give rise to problem behavior. Such assessments may inform treatment plans, even when the function of the behavior is unclear. The present study is a descriptive assessment of behavioral data collected by dormitory staff at a juvenile residential treatment facility. We used conditional probabilities and statistical analyses to identify setting events (e.g., days of week, time of day) that predict likelihood of problematic behavior. The findings allow clinicians and administrators within the facility allocate resources strategically to prevent and respond to problematic behavior effectively. Implications, limitations, and future directions are discussed.