The point of diminishing returns in juvenile probation: Probation requirements and risk of technical probation violations among first-time probation-involved youth.

Abstract

Technical probation violations are common among probation-involved youth and, across many jurisdictions, may result in detention or residential placement. The current study examined prevalence of technical violations occurring during one's first probation period, the average time to technical violation, and individual-level and justice-related factors related to technical violations among probation-involved youth in a juvenile justice system. We analyzed electronic criminal records of 18,289 probation-involved youth following their first arrest (68.7% male, 53.9% Black, Mage ϭ 15.2 years). Technical violation was defined as a violation resulting from a noncriminal incident. We examined effects of charge severity, probation conditions (e.g., electronic monitoring), and program referrals (e.g., mental health) on likelihood of technical violation utilizing survival analysis stratified by race. Across 18,289 youth, 15.3% received a technical violation during their first probation; Black youth violated more quickly compared with White youth (log-rank test p Ͻ .001). In multivariate survival analyses, the hazard for time to technical violation was higher for Black youth compared with White youth (p Ͻ .001), males (p ϭ .04), and younger youth (p Ͻ .001). Youth assigned to more probation requirements violated more quickly. Electronic monitoring and education, mental health, and drug programs were associated with shorter time to violation, controlling for race, ethnicity, and charge severity. Black youth violate more quickly compared with White youth. Across all youth, assignment to more probation requirements increased risk of technical violation and shorter time to violation. Despite the benefit of probation interventions, system-level efforts are needed to help youth adhere to probation requirements and successfully complete probation.

Counterintuitive race effects in legal and nonlegal contexts.

“…Examples of studies coded as measuring responses in a legal context include measures of mock jurors’ levels of racial bias (e.g., Morrison et al, 2016) or evaluations of a defendant (e.g., Cooley et al, 2019; Johnson et al, 1995; Maeder et al, 2015; Ratcliff et al, 2010), the proportion of Black jurors removed during voir dire (e.g., Morrison et al, 2016), probation outcomes (e.g., Bechtold et al, 2015; Dir et al, 2021), judgments of a housing applicant with a criminal history (e.g., Berry & Wiener, 2020), race–crime associations (e.g., Dunbar, 2020), the weapon identification task (e.g., Gonsalkorale et al, 2011; Jones & Fazio, 2010; Klauer & Voss, 2008; Thiem et al, 2019), the shoot/don’t-shoot task (e.g., Mendoza et al, 2010; Miller et al, 2012; Plant et al, 2011; Sim et al, 2013), and hiring decisions for a police force made by participants taking the role of police chief (e.g., Bradley-Geist et al, 2010). Examples of studies coded as measuring responses in a nonlegal context include simulated hiring decisions in nonlegal contexts (e.g., Hall et al, 2015; McConahay, 1983), assignment of stereotypes and stereotyped traits (e.g., choosing positive and negative adjectives to describe the stereotypical Black person, Devine & Elliot, 1995; estimating the percentage of Black people who possess positive and negative stereotypical traits, Stangor et al, 2001), measures of intergroup anxiety or physiological reactivity during interracial interactions (e.g., Mendes et al, 2002; Plant & Butz, 2006; Stephan et al, 2002; Towles-Schwen & Fazio, 2003), the race implicit association test (IAT; e.g., Craig & Richeson, 2014; Frantz et al, 2004; Gawronski et al, 2008; Röhner & Lai, 2021; Sawyer & Gampa, 2018), the affect misattribution paradigm (e.g., Cooley et al, 2018, 2019; Gawronski et al, 2017), and general liking for or perceptions of Black and White targets (e.g., Ito et al, 2004; Jacoby-Senghor et al, 2019).…”

“…Legal or Nonlegal Context. Examples of studies coded as measuring responses in a legal context include measures of mock jurors' levels of racial bias (e.g., Morrison et al, 2016) or evaluations of a defendant (e.g., Cooley et al, 2019;Johnson et al, 1995;Maeder et al, 2015;Ratcliff et al, 2010), the proportion of Black jurors removed during voir dire (e.g., Morrison et al, 2016), probation outcomes (e.g., Bechtold et al, 2015;Dir et al, 2021), judgments of a housing applicant with a criminal history (e.g., Berry & Wiener, 2020), race-crime associations (e.g., Dunbar, 2020), the weapon identification task (e.g., Gonsalkorale et al, 2011;Jones & Fazio, 2010;Klauer & Voss, 2008;Thiem et al, 2019), the shoot/don'tshoot task (e.g., Mendoza et al, 2010;Miller et al, 2012;Plant et al, 2011;Sim et al, 2013), and hiring decisions for a police force made by participants taking the role of police chief (e.g., Bradley-Geist et al, 2010). Examples of studies coded as measuring responses in a nonlegal context include simulated hiring decisions in nonlegal contexts (e.g., Hall et al, 2015;McConahay, 1983), assignment This document is copyrighted by the American Psychological Association or one of its allied publishers.…”

Redesigning Juvenile Probation to Align With Behavioral Health and Positive Development Principles: A Quasi-Experimental Study

“…Given the issue of disproportionate minority contact in the youth criminal legal system (Dir et al, 2020; Kimchi, 2019; Saunders et al, 2021), it was important to identify whether outcomes of OBP differed by race/ethnicity to confirm that possible benefits were equitable across groups. Prior reform efforts have highlighted that even well-intentioned program development often benefits White youth more than YOC (Walker et al, 2017).…”

“…Conditions of probation frequently include restriction of behaviors that are normative for adolescents, such as early curfew and movement restriction (e.g., not being allowed to leave their county of residence without probation officer’s approval). Violating these conditions can result in punitive actions such as prolonged probation and detention (Dir et al, 2020; Goldstein et al, 2016), both of which are associated with poor long-term outcomes (e.g., increased likelihood of criminal behavior in adulthood, increased aggression, disruption of normative adolescent development; Gatti et al, 2009; Goldstein et al, 2016; Schwartz, 2018).…”

“…Instituting reforms in juvenile probation is particularly important for reducing the disparities of contact and harm experienced by youth of color (YOC). Black youth are more likely to receive probation violations (Dir et al, 2020; Smith et al, 2009) and may receive harsher consequences for these violations (Krezmien et al, 2008; Leiber & Peck, 2013; Mallett & Stoddard-Dare, 2010; Steinmetz & Anderson, 2016). Young Black people are also more likely to receive a wider range of and more restrictive conditions on probation (Kimchi, 2019).…”