Metacognitive Therapy Versus Cognitive Behavioral Therapy:A Network Approach

Abstract

A network perspective on mental problems represents a new alternative to the latent variable perspective. Diagnoses are assumed to refer to a causal network of observable mental problems or symptoms (observables). The observable symptoms that traditionally have been considered indicators of latent traits (disorders) are taken to be directly related causal entities. Few studies have investigated how different therapies affect a network-structure of symptoms and processes. In this study, three anxiety symptoms, three depression symptoms and mechanisms in the form of cognitions, metacognitions, worry and threat monitoring were selected. The network structure over the course of therapy for metacognitive therapy (MCT) and Cognitive behavioral therapy (CBT) was investigated. It was hypothesized that worry, attention, and metacognition would be important nodes in MCT and that cognitions would be important in CBT. The data used in the analysis are from a RCT where 74 patients with comorbid anxiety disorders were randomized to either transdiagnostic MCT or disorder-specific CBT. Symptoms and mechanisms were measured every week. The data was analyzed using the multilevel vector autoregressive (mlVAR) model, which is currently the most developed method to analyze multivariate time series in multiple subjects and construct networks. The results indicate that there were different networks of symptoms and mechanisms in MCT and CBT. Central nodes in both treatments are worry and attention, however, the node of negative metacognitive beliefs about uncontrollability was more central in the MCT treatment. The results are consistent with predictions from the S-REF model.

Breaking the Cybernetic Code: Understanding and Treating the Human Metacognitive Control System to Enhance Mental Health

“…In meta-analyses, MCT demonstrates large treatment effects and appears potentially more effective or more efficient than cognitive behavioral approaches (Normann et al, 2014;Normann and Morina, 2018). In a direct test of transdiagnostic MCT against disorder-specific CBT across anxiety disorders, outcomes favoring MCT were reported (Johnson et al, 2017) and potential mechanisms of change could be distinguished (Johnson and Hoffart, 2018). Several trials have evaluated the effects of MCT against CBT for generalized anxiety.…”

The Recovery Process for Individuals With Schizophrenia in the Context of Evidence-Based Psychotherapy and Rehabilitation

“…Cognitive Behavioral Therapy (CBT) is effective in the reduction of symptoms as well as the improvement of mood and community functioning, and it is more effective in an acute psychotic episode in comparison to chronic schizophrenia; furthermore, it is effective in treatment-resistant schizophrenia (Beck, Rector, Stolar, & Grant, 2009; Burns, Erickson, & Brenner, 2014; Candida et al, 2016; Hofmann, Asnaani, Vonk, Sawyer, & Fang 2012; Johnson & Hoffart, 2018; Kern et al, 2009; Medalia, Beck, & Grant, 2019; Morrison et al, 2018; Mueser et al, 2013).…”

Latent Trait, Latent-Trait State, and a Network Approach to Mental Problems and Their Mechanisms of Change

“…We illustrate the elaborated network approach with a second study (published elsewhere; Johnson & Hoffart, 2018) of the data from our study presented above. Rather than analyzing the within-persons relationships between the latent constructs of this model, in the second study we focused on the network of connections between some of the observables used as indicators of these constructs.…”

“…Nodes of items taken from the Patient Health Questionnaire–9: Int = little interest or pleasure in doing things; Dep = feeling down, depressed, or hopeless; and Sle = trouble falling or staying asleep, or sleeping too much. Adapted from Johnson and Hoffart (2018).…”