The Society for Social Work and Research

2014 Annual Conference

January 15-19, 2014 I Grand Hyatt San Antonio I San Antonio, TX

A Method to Analyze Initial CANS Assessments to Identify Profiles of High Need Youth Served Through Family-Based Interventions

Saturday, January 18, 2014: 10:00 AM
HBG Convention Center, Room 003A River Level (San Antonio, TX)
* noted as presenting author
Katharan Cordell, MPH, Graduate Student Researcher at Seneca Family of Agencies, University of California, Berkeley, Plumas Lake, CA
Shannon Dickerson, BS, Performance Improvement Project Manager, Seneca Family of Agencies, Oakland, CA
Melissa Mollard, PhD, Director of Strategic Initiatives and Performance Improvement, Seneca Family of Agencies, Oakland, CA
Purpose:  This study explores the profiles of incoming youth referred to a child mental health agency in order to identify factors associated with the most severe youth in need of intensive services. Seneca Family of Agencies serves families of youth using a model of unconditional care based on three streams:  1) a relational stream based on attachment theory (Bowlby, 1982), 2) a behavior stream based on learning theory (Rushton & Teachman, 1978), and 3) an ecological stream which recognizes the importance of contextual factors in the environment (Bronfenbrenner, 1988). At the beginning of service, a customized Child Adolescent Needs and Strengths (CANS) assessment identifies up to 315 actionable items associated with these streams to direct services. A high number of total actionable items (TAI) on the CANS represents a need for more intensive services. For example, youth with 50 TAI, represent a higher need as compared to youth with 10 TAI. It was of interest to explore if there existed a pattern of individual actionable CANS items which strongly predicted a high number of TAI, and to identify if the combination of the most predictive items predominantly represented one or more of the streams within the model of unconditional care.

Methods:  A total of 2,729 initial CANS were extracted from the agency’s electronic health record since 2009. CANS items were coded as actionable (2 or 3) or not actionable (0, 1, null), and the TAI per youth was identified. A method of classification and regression tree (CART) using linear regression was utilized to identify individual CANS actionable items which most strongly predicted the TAI for youth. Information from the resulting tree was used to make logical combinations of three-four CANS items most predictive of TAI, and the average number of TAI for each of the resulting profiles was identified. 

Results: Four main predictors of severity emerged from the analysis. The most significant predictor was issues with Judgment for Risk Behaviors (“p”<0.001); followed by Environmental Influences for Juvenile Justice involvement (“p”<0.001); Frustration Management for Violence (“p”<0.001); and the presence of any Neglect, Attachment or Adjustment to Trauma related to Abuse (“p”<0.001). The profile of youth who were not actionable in any of these four areas had average 9.5 (SD 7.3) TAI. On average, youth who were actionable in 1) any one of these areas had 18-20 TAI, 2) any two areas had 26-30 TAI, 3) any three of these areas had 37-42 TAI, and 4) all four areas had 50.8 (SD 11.9) total actionable CANS items.

Implications: CART provided a method to identify the most predictive factors associated with high need youth served by the agency. Areas related to behavioral (Judgment for Risk Behaviors and Emotional Frustration for Violence), relationship (Abuse) and Ecological (Environmental Influences for Juvenile Justice involvement) steams were all strongly predictive of severity of incoming youth, and a combination of issues in all three streams resulted in the highest need youth served. This exploration validated the importance of addressing all three steams for the population of youth served.