Different components of cognitive-behavioural therapy affect specific cognitive mechanisms

Abstract

Psychological therapies are among the most effective treatments for a range of common mental health problems – however, we still know relatively little about how exactly they improve symptoms. Here, we demonstrate the power of combing theory with computational methods to parse effects of different components of cognitive-behavioural therapies on to underlying mechanisms. Specifically, we present data from a series of randomized-controlled experiments testing the effects of components of behavioural and cognitive therapies on different cognitive processes, using well-validated behavioural measures and associated computational models (total N=807). We found that a goal-setting intervention, based on behavioural activation therapy, reliably and selectively reduced sensitivity to effort when deciding how to act to gain reward. By contrast, we found that a cognitive restructuring intervention, based on cognitive therapy, reliably and selectively reduced the tendency to attribute negative everyday events to self-related causes. Importantly, the effects of each intervention were specific to these respective measures. Our approach provides a basis for understanding how different elements of common psychotherapy programs work, which may enable theoretically-informed treatment targeting in the future.

A computational approach to understanding effort-based decision-making in depression

“…Elements of behavioural activation (BA) therapy, such as activity scheduling, might play such a role, as these rely on acting on pre-planned activities rather than internal states (71). Interestingly, this BA component has recently been shown to alter effort processing in healthy participants, offering proof-of-concept of this idea (72).…”

Informing the treatment of social anxiety disorder with computational and neuroimaging data

“…Furthermore, this approach requires knowledge regarding the influence of specific interventions to specific underlying mechanisms (Reiter et al ., 2021 ; Berwian et al ., 2023 ). However, progress is being made with determining sources of within-participant parameter variability (Schaaf et al ., 2023 ) and mapping psychotherapy interventions to components of cognition and behaviour (Norbury et al ., 2024 ). It is therefore important to determine the within-subject reliability of model parameters in healthy controls and individuals with SAD when informing the neurocomputational treatment of social anxiety.…”