Affiliation:
1. Department of Psychiatry and Behavioral Sciences University of Minnesota Medical School Minneapolis Minnesota USA
2. Institute for Health Informatics, University of Minnesota Minneapolis Minnesota USA
3. Center for Biobehavioral Research, Sanford Research Fargo North Dakota USA
4. Accanto Health St Paul Minnesota USA
5. Department of Psychiatry and Behavioral Health Penn State Hershey Medical Center Hershey Pennsylvania USA
Abstract
AbstractObjectivePrecision medicine (i.e., individually tailored treatments) represents an optimal goal for treating complex psychiatric disorders, including eating disorders. Within the eating disorders field, most treatment development efforts have been limited in their ability to identify individual‐level models of eating disorder psychopathology and to develop and apply an individually tailored treatment for a given individual's personalized model of psychopathology. In addition, research is still needed to identify causal relationships within a given individual's model of eating disorder psychopathology. Addressing this limitation of the current state of precision medicine‐related research in the field will allow us to progress toward advancing research and practice for eating disorders treatment.MethodWe present a novel set of analytic tools, causal discovery analysis (CDA) methods, which can facilitate increasingly fine‐grained, person‐specific models of causal relations among cognitive, behavioral, and affective symptoms.ResultsCDA can advance the identification of an individual's causal model that maintains that individuals' eating disorder psychopathology.DiscussionIn the current article, we (1) introduce CDA methods as a set of promising analytic tools for developing precision medicine methods for eating disorders including the potential strengths and weaknesses of CDA, (2) provide recommendations for future studies utilizing this approach, and (3) outline the potential clinical implications of using CDA to generate personalized models of eating disorder psychopathology.Public Significance StatementCDA provides a novel statistical approach for identifying causal relationships among variables of interest for a given individual. Person‐specific causal models may offer a promising approach to individualized treatment planning and inform future personalized treatment development efforts for eating disorders.
Funder
National Institute of General Medical Sciences
National Institute of Mental Health
Clinical and Translational Science Institute, University of Minnesota
Subject
Psychiatry and Mental health
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献