Implementing precision methods in personalizing psychological therapies: Barriers and possible ways forward

• Authors: Anne-Katharina Deisenhofer, University of Trier; Michael Barkham, University of Sheffield; Esther T. Beierl, University of Oxford; Brian Schwartz, University of Trier; Katie Aafjes-van Doorn, Yeshiva University; Christopher G. Beevers, University of Texas at Austin; Isabel M. Berwian, Princeton University; Simon E. Blackwell, Ruhr University Bochum; Claudi L. Bockting, University of Amsterdam; Eva-Lotta Brakemeier, University of Greifswald; Gary Brown, Royal Holloway University of London; Joshua E. J. Buckman, University College London; Louis G. Castonguay, Pennsylvania State University; Claire E. Cusack, University of Louisville; Tim Dalgleish, University of Cambridge; Kim de Jong, Leiden University; Jaime Delgadillo, University of Sheffield; Robert J. DeRubeis, University of Pennsylvania; Ellen Driessen, Radboud University; Jill Ehrenreich-May, University of Miami; Aaron J. Fisher, University of California, Berkeley; Eiko I. Fried, Leiden University; Jessica Fritz, University of Cambridge; Toshi A. Furukawa, Kyoto University; Claire M. Gillan, Trinity College Dublin; Juan Martin Gomez Penedo, University of Buenos Aires; Peter Frank Hitchcock, Emory University; Stefan G. Hofmann, Philipps University of Marburg; Steven D. Hollon, Vanderbilt University; Nicholas C. Jacobson, Dartmouth Geisel School of Medicine; Daniel R. Karlin, Tufts University; Chi Tak Lee, Trinity College Dublin; Cheri A. Levinson, University of Louisville; Lorenzo Lorenzo-Luaces, Indiana University; Riley McDanal, Stony Brook University; Danilo Moggia, University of Trier; Mei Yi Ng, Florida International University; Lesley A. Norris, Brown University; Vikram Patel, Harvard Medical School; Marilyn L. Piccirillo, University of Washington; Stephen Pilling, University College London; Julian A. Rubel, Osnabrück University; Gonzalo Salazar-de-Pablo, King's College London; Rob Saunders, University College London; Jessica L. Schleider, Stony Brook University; Paula P. Schnurr, National Center for PTSD; Stephen M. Schueller, University of California, Irvine; Greg J. Siegle, University of Pittsburgh; Rudolf Uher, Dalhousie University; Ed Watkins, University of Exeter; Christian A. Webb, Harvard Medical School; Shannon Wiltsey Stirman, Stanford University; Laure Wynants, Maastricht University; Soo Jeong Youn, Harvard Medical School; Sigal Zilcha-Mano, University of Haifa; Wolfgang Lutz, University of Trier; Zachary D. Cohen, University of California, Los Angeles
• Journal Title: Behaviour Research and Therapy
• Volume: Volume 172
• Publisher: Elsevier | 2024-01-01, Pages 104443-None
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1016/j.brat.2023.104443
• Subjects: Psychology, Clinical
• Keywords: Precision mental health care methods; Personalizing psychological treatments; Data-driven psychological therapies; Implementation barriers

Abstract

Personalization of psychological therapies has always been used by clinicians and describes all efforts to select, adjust, or modify a treatment for the individual to improve outcomes. Precision mental health care approaches can be considered under the umbrella term personalization and specify methods that are algorithmic, quantitative, and empirically derived. Despite a growing research literature demonstrating the efficacy of these approaches, they are rarely tested in clinical practice. A statistically optimized, targeted clinical recommendation is not by itself sufficient to influence clinical practice in a beneficial way; barriers related to dissemination and implementation require increased attention. This article describes clinical and practical factors, technical aspects, statistical considerations, and fundamental contextual issues that should be considered to facilitate data-driven treatments in mental health care contexts in clinical practice.