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Empirically Guided Coordination of Multiple Evidence-Based Treatments: Relevance Mapping

  • Author(s): Bernstein, Adam
  • Advisor(s): Chorpita, Bruce F
  • et al.
Abstract

Well-designed studies have produced over 300 effective treatments that have been summarized in numerous lists of evidence-based treatments (EBTs). At the same time, the field is making great gains in the understanding of how to implement those treatments, once chosen. However, there is no structured guidance for how to select an optimal set of EBTs from those lists that is maximally relevant and minimally redundant with respect to its fit for a targeted service sample. This dissertation introduces relevance mapping, a methodology that addresses this problem. This dissertation consists of three studies that respectively describe the methodology, and use it to evaluate two open questions regarding treatment coordination. Relevance mapping uses automated comparison of the characteristics of each child in a targeted service sample to the participant characteristics from every study of every successful treatment. Relevance mapping addresses who is and is not coverable by any EBT in the literature, under configurable assumptions about which features must match between study participants and children in the service sample. Relevance mapping can then identify the minimum set of treatments needed to serve the maximum number of children in the service sample, based on those same user-defined matching features. The first study describes this methodology in detail along with the context of the problem it addresses within the framework of knowledge management in mental health. The second study compares the efficiency of relevance mapping results when treatments are defined as intact programs or as collections of their constituent procedures. Finally, the third study applies relevance mapping to a large mental health service agency sample to assess the degree to which EBTs fit the problems, demographics, and treatment settings of youths served using wraparound process. Wraparound is a widely implemented and highly popular model for organizing individualized treatments and supports for children with complex needs. However its effectiveness has long been in question, making the combination of wraparound and EBTs and intriguing possibility. The dissertation's overarching goal is to illustrate a methodology for better application of the evidence base to applied settings, under a variety of different definitions and assumptions.

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