Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-28T13:45:15.488Z Has data issue: false hasContentIssue false

Quantifying computational mechanisms in psychotherapy

Published online by Cambridge University Press:  19 July 2023

Q. Huys*
Affiliation:
University College London, London, United Kingdom

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Abstract

Despite extensive research, the cognitive processes mediating the impact of psychotherapeutic interventions remain poorly understood, and as a result difficult to quantify. Identifying such mechanisms is likely to be extremely helpful: it could help target interventions better, could support dosing therapy through monitoring, and could heighten the speed at which new interventions can be developed. Mechanisms research in psychotherapy has described a number of key difficulties to achieving this. In this and the next talk, we ask whether advances in cognitive computational neuroscience might provide some support. Specifically, the question is whether precise cognitive probes might identify specific mechanisms of interventions. In support of this, I will first describe a pilot study in participants undergoing an adapted behavioural activation therapy. I will then move to present results from two strands of experiments examining whether interventions derived from components of cognitive-behavioural therapy (CBT) are able to shift computationally-derived measures of their proposed psychological substrates. Findings from both strands will be discussed with respect to challenges in developing brief, reliable, engaging, and user-acceptable measures of cognition. Overall, this outlines some early new results in using computational methods to understand therapeutic processes in the psychotherapy for depression.

Disclosure of Interest

Q. Huys Grant / Research support from: Koa Health, Consultant of: Aya Technologies and Alto Neuroscience

Type
Abstract
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the European Psychiatric Association
Submit a response

Comments

No Comments have been published for this article.