Facilitating Communication of Ideas and Evidence to Enhance Mental Health Service Quality: Coding the Treatment Services Literature Using the Child and Adolescent Needs and Strengths-Mental Health Assessment Scales |
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Authors: | Chad Ebesutani Eric Daleiden Kimberly D. Becker Lauren Schmidt Adam Bernstein Leslie Rith-Najarian John Lyons Bruce F. Chorpita |
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Affiliation: | 1.Department of Psychology,Duksung Women’s University,Seoul,South Korea;2.PracticeWise, LLC,Satellite Beach,USA;3.University of Maryland School of Medicine,Baltimore,USA;4.Chapin Hall at the University of Chicago,Chicago,USA;5.Department of Psychology,University of California,Los Angeles,USA;6.Department of Psychology,University of South Carolina,Columbia,USA |
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Abstract: | The evidence-base services literature is continually growing, providing the field with rich and important sets of information regarding what works for treating different types of youth and families. Given this burgeoning of information, the PracticeWise Evidence-Based Services (PWEBS) Literature Database has been developed to aid in summarizing and delivering aggregated evidence-based treatment information to providers in the field. Meanwhile, the Child and Adolescent Needs and Strengths-Mental Health (CANS-MH) Scale is a youth mental health assessment tool that was developed by a separate team to assist with treatment planning. In the present study, we developed and tested a system for linking these two related ontological systems so that scientific knowledge can be more widely aggregated and made available to a wider set of audiences for enhanced mental health service delivery. Results revealed the following. First, a construct mapping comparison revealed that the CANS-MH and PWEBS ontologies share a strong core of overlapping content, particularly in the areas of Youth Behavioral/Emotional Needs, Youth Risk Behaviors, and Life Domain Functioning. Second, the CANS-MH areas were able to be used to reliably code the following components of published randomized treatment studies: (a) population sample characteristics (e.g., did the characteristics of the treatment study participant population relate to each CANS-MH area?), and (b) outcome measure targets (e.g., did the treatment study outcome measure target areas relate to each CANS-MH area?). The reliability achieved from this coding process supported the linkage between the CANS-MH areas and the PWEBS Literature Database information. Lastly, high agreement was achieved between an automated translation algorithm and the final ratings from the manual coding of published treatment studies using the CANS-MH scale. The importance of such linkages for the communication of ideas, information, and evidence across differing subfields is discussed, as well as examples of achieving enhanced quality of mental health services by linking system ontologies. |
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