Society for Social Work and Research

Sixteenth Annual Conference Research That Makes A Difference: Advancing Practice and Shaping Public Policy
11-15 January 2012 I Grand Hyatt Washington I Washington, DC

126P A Pilot Application of Maximum Individualized Change Analysis to the Evaluation of An In-Home Family Intervention Program

Saturday, January 14, 2012
Independence F - I (Grand Hyatt Washington)
* noted as presenting author
Ronald W. Thompson, PhD, Director, Father Flanagan's Boys Home (Boys Town), Boys Town, NE
Eric C. Brown, PhD, Research Scientist, University of Washington, Seattle, WA
W. Alex Mason, PhD, Associate Director, Father Flanagan's Boys Home (Boys Town), Boys Town, NE
Roger A. Boothroyd, PhD, Chair and Professor, University of South Florida, Tampa, FL
Stephanie Ingram, BA, Research Analyst, Boys Town, Boys Town, NE

Purpose: In-home family interventions are widely used in Child Welfare, but few evidence-based programs have been developed and evaluated in this population. One of the unique challenges is that very diverse families are referred who require individualized intervention plans. Families present with children in different or multiple age groups; physical, sexual, and/or emotional abuse or neglect; and a variety of additional risk and protective factors for both adults and children ranging from environmental issues such as adequate housing and finances to mental health and substance abuse challenges. This makes intervention effects difficult to detect as families may improve only in areas where intervention strategies are targeted. To address these issues, the authors designed an in-home family intervention program with an individualized assessment-driven service planning process which allows family workers to target interventions based on family characteristics and presenting problems. This is a pilot study of this program which was first delivered to a traditional Child Welfare population and later applied to children and their families referred by schools after a county-wide screening of children enrolled in kindergarten and first grade.

Method: The intervention program combines a strong emphasis on family engagement, cognitive-behavioral skill teaching, and connecting families with informal and formal supports. The Strengths and Stressors tool is used to assess risk and protective factors at intake and progress at case closure across the following domains: Environment, Social Support, Parental Capabilities, Family Interactions, Family Safety, and Child Well-Being. To compare outcomes for the Child Welfare group with those for the school-referral group while accounting for the variability in targeted outcomes, the data were analyzed using both traditional mean comparisons and also Maximum Individualized Change Analysis (MICA). Designed as a statistically powerful alternative to Multivariate Analysis of Variance for evaluations of individualized interventions, MICA is used to conduct comparisons on a single summary outcome that reflects the largest amount of change for each family among a set of potential outcomes measures. Pre-post mean scores were analyzed for each group using separate one way ANOVAs for each outcome domain and overall using the MICA approach.

Results: The results indicate that the Child Welfare group made the greatest gains in the Family Safety domain and the school referral group made the greatest gains in the Child Well-Being domain. Using MICA, results revealed a statistically significant group difference indicating higher scores on the maximum change index for Child Welfare families compared to school-referral families, suggesting that the former experienced greater overall gains associated with involvement in the in-home family intervention.

Conclusion: Because family interventions in Child Welfare require individualized interventions based on risk and protective factors, traditional pre-post evaluation methods using mean comparisons across a broad set of outcomes may not detect intervention effects. The Maximum Individualized Change Analysis (MICA) is a promising alternative analytic strategy, with potential application not only in experimental contexts, as originally designed, but also in quasi-experimental and non-experimental contexts.