Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data
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Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data Lorenzo Lorenzo-Luaces 1 & Allison Peipert 1 & Robinson De Jesús Romero 1 & Lauren A. Rutter 1 & Natalie Rodriguez-Quintana 2 Accepted: 27 October 2020/ # Springer Nature Switzerland AG 2020
Abstract Cognitive-behavioral therapies (CBTs) are the most widely studied form of psychotherapy for disorders like depression and anxiety. Nonetheless, there is heterogeneity in response to CBTs vs. other treatments. Researchers have become increasingly interested in using pre-treatment individual differences (i.e., moderators) to match patients to the most effective treatments for them. Several methods to combine multiple variables to create precision treatment rules (PTRs) that identify subgroups have been proposed. We review the rationale behind multivariable PTRs as well as the findings of studies that have used different PTRs. We identify conceptual and methodological issues in the literature. Multivariable treatment assignment is a promising avenue of research. Nonetheless, effect sizes appear to be small and most of the samples that have been used to study these questions have been grossly underpowered to detect small effects. We recommend researchers explore multivariable treatment selection strategies, particularly those resembling risk stratification, in heterogeneous samples of patients undergoing low-intensity CBTs vs. realistic minimal controls. Keywords Personalized medicine . Machine learning . Cognitive-behavioral therapy .
Depression So-called mental disorders account for a substantial proportion of the disability attributable to health conditions (Whiteford et al. 2013). Depressive disorders account for a substantial amount of that disability, in part due to how common and disabling they are (Patel et al. 2016). An often-cited feature of depression is its heterogeneous symptom
* Lorenzo Lorenzo-Luaces [email protected]
1
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
2
Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
International Journal of Cognitive Therapy
presentation (Fried and Nesse 2015; Zimmerman et al. 2015). Depression is also heterogeneous in its prognosis (Lorenzo-Luaces 2015; Monroe and Harkness 2005, 2011). While most cases in naturalistic samples may remit within a 3–6-month period, a minority of individuals have a chronic or unremitting course. Roughly half of cases that recover do not go on to relapse, but, of individuals who relapse, repeated episodes are common (Lorenzo-Luaces 2015; Monroe and Harkness 2005, 2011). Cognitive-behavioral therapies (CBTs) have been the most widely studied psychological interventions for depression as well as for other common mental disorders (Barth et al. 2016; Lorenzo-Luaces et al. 2020b). We refer to CBTs as a family of interventions which may include mostly components aimed at changing cognitions (e.g., cognitive-processing therapy (CPT)), mostly components aimed at changi
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