Category: Treatment - CBT
Therapeutic alliance (TA) plays an important role in the successful delivery of cognitive behavioral therapy (CBT) to patients of all ages (De Nadai & Karver, 2013; Horvath, Del Re, Fluckiger, & Symonds 2011; Shirk, Karver, & Brown, 2011). For youth in particular, a robust relationship between alliance and CBT outcome has been found (Shirk & Karver, 2011). However, previous meta-analyses on TA in youth were not sufficiently powered to appropriately evaluate diversity in a variety of domains such as patient characteristics and treatment targets (e.g., anxiety, disruptive behavior). Additionally, viewpoints on the role of TA have evolved considerably in recent years (e.g., the role of TA varies substantially across treatments for different disorders; Hofmann & Barlow, 2014). Given this background, new information is needed to understand how TA functions differentially across an array of patients, clinical settings, and treatment approaches. This knowledge can facilitate an improved understanding of mechanisms of treatment outcome.
Accordingly, we will present results from an updated meta-analysis of the relationship between TA and treatment outcome in youth, with a particular focus on CBT approaches. The present research utilizes multivariate meta-analysis with robust variance estimation, which can incorporate more than five times the number of effect sizes included in prior meta-analyses. Since the time of the last meta-analysis in TA in youth, we have reviewed 6,930 additional articles for inclusion and added over 55 studies. Preliminary results of this meta-analysis indicate that TA measured at varying time points throughout treatment continues to have a robust relationship with CBT for pediatric psychopathology. Furthermore, the role of alliance appears to vary across CBT interventions for different types of psychopathology. A number of other moderators will also be discussed, including patient diversity, clinician backgrounds (e.g., years of experience, theoretical orientation), method of treatment delivery (e.g., in person, online, phone), and treatment setting (e.g., inpatient, outpatient). These findings will be discussed in the context of ongoing efforts to tailor the delivery of CBT to individual patients based on treatment matching approaches and creative evidence-based treatment delivery mechanisms such as modular treatment frameworks (Chorpita et al., 2017; Weisz et al. 2012).
Miranda Courteaux– Lab Manager, University of South Florida
Maureen Monahan– Graduate Student, University of South Florida
Alessandro De Nadai– PhD candidate, University of South Florida, University of Mississippi Medical Center, Texas State University, Tampa, Florida
Edmund Orlowski– Research Assistant, University of South Florida, Tampa, Florida
Melanie Rosler– Project Lab Manager, University of South Florida, Tampa, Florida
Renee Hangartner– Graduate Student, University of South Florida
Lora Williams– Lab Manger, University of South Florida
Amanda Peterson– Graduate Student, University of South Florida
Stephen Shirk– Professor, University of Denver
Stephanie Boettcher– University of South Florida
Marc Karver– Associate Professor, University of South Florida, Tampa, Florida
University of South Florida, University of Mississippi Medical Center, Texas State University