
Psychiatr Serv 59:738-746, July 2008
doi: 10.1176/appi.ps.59.7.738
© 2008 American Psychiatric Association
An Ethnographic Study of Implementation of Evidence-Based Treatments in Child Mental Health: First Steps
Lawrence A. Palinkas, Ph.D.,
Sonja K. Schoenwald, Ph.D.,
Kimberly Hoagwood, Ph.D.,
John Landsverk, Ph.D.,
Bruce F. Chorpita, Ph.D. and
John R. Weisz, Ph.D., the Research Network on Youth Mental Health
Dr. Palinkas is affiliated with the School of Social Work, University of Southern California, 669 W. 34th St., Los Angeles, CA 90089-0411 (e-mail: palinkas{at}usc.edu). Dr. Schoenwald is with the Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston. Dr. Hoagwood is with the Department of Psychiatry, Columbia University, New York City. Dr. Landsverk is with the Child and Adolescent Services Research Center, Rady Children's Hospital, San Diego. Dr. Chorpita is with the Department of Psychology, University of Hawaii at Manoa. Dr. Weisz is with Judge Baker Children's Center, Harvard Medical School, Boston.
OBJECTIVE: The experiences of clinicians in regard to initial and long-term intention to use evidence-based treatments were examined in order to better understand factors involved in implementation of innovative treatments. METHODS: Ethnographic methods of participant observation and extended semistructured interviews with four trainers, six clinical supervisors, and 52 clinicians at five agencies in Honolulu and six in Boston were used to understand treatment implementation in the Clinic Treatment Project, a randomized effectiveness trial of evidence-based treatments for depression, anxiety, and conduct problems of children. Grounded-theory analytic methods were used to analyze field notes, interview transcripts, and meeting minutes. RESULTS: Three patterns in regard to long-term intention to implement the treatments were evident: application of the treatments with fidelity, abandonment of the treatments, and selective or partial application. These patterns were perceived to be associated with three preimplementation factors: lag time between initial training in the treatment protocol and treatment use in practice, clinician engagement with the project, and clinician-treatment fit. Four additional factors were proximal outcomes of the three determinants as well as first steps of implementation: clinicians' first impressions of the evidence-based treatments after initial use, competence in treatment use, clinician and researcher adaptability, and clinician-researcher interactions. CONCLUSIONS: Interactions between preimplementation factors and initial implementation experiences and between researchers and clinicians during the early implementation steps were related to intentions to sustain treatment.
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