The Use of Risk Assessment to Predict Recurrent Maltreatment: A Classification and Regression Tree Analysis (CART)

Abstract

Research has suggested that recurrent maltreatment may be best predicted by a combination of factors that vary across families. The present study set out to determine whether a pattern-centered analytic approach would better predict families at high risk for recurrence when compared to logistic regression methods. Archival data from substantiated investigations during 2003 were collected from a Connecticut Department of Children and Families county branch. Families (n=244) with a substantiated index case were followed for 18 months to identify the presence of additional substantiated cases within the CPS system. Classification and Regression Tree (CART) analyses revealed that prior CPS involvement was the best predictor of recurrent maltreatment. Further, risk items that were associated with recurrence were different for families with and without previous CPS investigations. Families with only prior unsubstantiated CPS investigations and poor child visibility within the community were at high risk for recurrence. Families without prior CPS involvement that were not actively involved in case planning and had a history of domestic violence were at high risk for recurrence. These findings suggest that pattern-centered analyses may be a useful approach to informing site-specific predictors of maltreatment recurrence by creating clear decision points that delineate high risk subgroups.Keywords child abuse and neglect; recurrent maltreatment; risk assessment; classification and regression tree analysis The primary goal of child protective services (CPS) is to reduce the likelihood of child maltreatment and its recurrence by providing appropriate services to families (Brookes & Webster, 1999); however, approximately 1/3 to 1/2 of families will have a recurret episode of maltreatment with subsequent reentry into the CPS system (DePanfilis & Zuravin, 1998;DePanfilis & Zuravin, 1999; Fluke, Shusterman, Hollinshead, & Yuan, 2005;Inkelas & Halfon, 1997). Risk assessment instruments were developed to aid caseworkers in identifying children who were at high risk for future abuse and neglect (Cash, 2001;Jagannathan & Camasso, 1996;Johnson & L'Esperance, 1984;Pecora, 1991). Although these assessments are now routinely administered during CPS investigations in 42 states (US Department of Health and Human Services, 2003); there remains no standard risk assessment model that clearly informs caseworker case planning and management (Schwalbe, 2004 Camasso & Jagannathan, 1995; Fluke et al., 2005;Hindley, Ramchandani, & Jones, 2006;Johnson & L'Esperance, 1984;Marks & McDonald, 1989;McDonald & Marks, 1991). Families are classified as low, moderate, or high risk for recurrence based on caseworker ratings of these items. An early review comparing eight risk assessment instruments (McDonald & Marks, 1991) found that perpetrator access predicted recurrent maltreatment in three prospective studies (Baird, 1988;Johnson & L'Esperance, 1984; Weedon, Torti, & Zunder, 1988) and a large family size predicted reabuse in two prospective ...

Factors associated with caregiver stability in permanent placements: A classification tree approach

“…In contrast, research on re-entry following reunification has tended to focus more on caregiver mental health, family stressors such as poverty, and case variables such as type of maltreatment (e.g., neglect), substantiation status, and prior Child Protective Services (CPS) involvement (Connell, Bergeron, Katz, Saunders, & Tebes, 2007; Connell et al, 2009; Drake, Jonson-Reid, & Sapokaite, 2006; Hindley, Ramchandani, & Jones, 2006; Sledjeski, Dierker, Brigham, & Breslin, 2008). Adoption research, on the other hand, has found evidence that older child age, behavioral problems, and placement with a nonrelative predict disruption (Coakley & Berrick, 2008; Rushton & Dance, 2006; Smith, Howard, Garnier, & Ryan, 2006).…”

“…CART analysis and related approaches have long been used in the areas of medical and marketing decision-making research, and have gained increasing popularity within the human services field, including child welfare and mental health (Alegria et al, 2004; Dean et al, 2009; Frisman, Prendergast, Lin, Rodis, & Greenwell, 2008; Johnson, Brown, & Wells, 2002; Kerby, 2003; Kriston, Berner, Ruf, Mundle, & Härter, 2008; Mann et al, 2008; Montoya, 2008; Müller, Weijers, Böning, & Wiesbeck, 2008; Neuner, Schmid, Wolfersdorf, & Spiessl, 2008; Seroczynski, Cole, & Maxwell, 1997; Sledjeski et al, 2008; Stice, Presnell, & Spangler, 2002; Swan, Jack, Javitz, McAfee, & McClure, 2008). …”

What Happened Next

“…Child welfare caseworkers are asked by the state to provide resources to prevent future episodes of maltreatment and to remedy the “conditions that brought the children and their family to the attention of the agency” (USDHHS, 2015). Child welfare response to maltreatment is guided by administrative data describing the demographics (race, age, marital status); social risk indicators (caregiver mental health, substance use or abuse, family violence); and case characteristics (abuse type, severity, chronicity) closely associated with recidivism (Dakil et al, 2011; Drake & Jonson-Reid, 1999; Horwitz et al, 2011; Jonson-Reid, Emery, Drake, & Stahlschmidt, 2010; Shlonsky, 2007; Sledjeski, Dierker, Brigham, & Breslin, 2008). This aggregate data guides critical safety decisions regarding the need for out-of-home placement of a child or for protective orders against a violent caregiver.…”

Factors Predicting Child Maltreatment Fatalities: A Competing Risk Model

“…As Peddle, Wang, Diaz, and Reid (2002) noted, prevention activities must address risk factors, and there is an increasing recognition that assessment procedures need to be empirically valid (Shlonsky & Wagner, 2005). However, there is currently no standard risk assessment tool to inform caseworkers about case planning (Sledjeski, Dierker, Brigham, & Breslin, 2008).…”