Abstract
Precision psychiatry is becoming a realistic ambition for clinical practice. Modern data gathering and data analysis tools create great opportunities for prediction of outcomes, decreased trial and error in selecting treatments, and improved understanding of complex mechanisms leading to more effective treatments. Some current challenges to implementation of these approaches are highlighted in this article. These include the limitations related to characteristics of the statistical methods used for precision medicine, standardization and clinical implementation of the various behavioral research paradigms in use, and the process of defining new outcome measures. Some clinical experiences and possible ways forward are also discussed, including patient and clinician interest in objective measures to complement current clinical assessments, sensitivity to existing workflows, a focus on defining new clinical categories rather than attempting to predict
DSM
diagnosis, and the use of alternative measures as meaningful outcome measures themselves.
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Psychiatr Ann
. 2024;54(4):e108-e112.]