Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Computationale und kognitive ansätze für die therapieentwicklung bei depressionen

Linden, David Edmund Johannes ORCID: https://orcid.org/0000-0002-5638-9292 2017. Computationale und kognitive ansätze für die therapieentwicklung bei depressionen. Zeitschrift für Psychiatrie, Psychologie und Psychotherapie 65 (1) , pp. 55-60. 10.1024/1661-4747/a000301

Full text not available from this repository.

Abstract

The cognitive model of depression postulates that patients with depression – and people at increased risk – have a negativity bias in attention and memory. The resulting negative interpretation of life experiences and expectancy of negative consequences (catastrophizing) ushers into a circle of negative mood, pessimism and anhedonia. In this model, the dysfunctional cognitive schema, which is caused by a combination of genetic and developmental factors, is a core mechanism of the clinical syndrome and a key target for therapeutic intervention. In this article I discuss the experimental evidence for such dysfunctional schemata especially with regard to negative biases in attention and memory. Computational decision theory can explain how overweighting negative (and underweighting positive) information can lead to behavioural symptoms of depression (psychomotor retardation) and a fundamentally pessimistic outlook. Such a negative bias can hinder healthy emotion regulation and thus establish vulnerability for depression. The increasing understanding of cognitive processes in depression is clinically relevant for the development of early detection tools and forms a basis for the development of new interventions in the fields of computer-based training (for example “cognitive bias modification”) and self-regulation of brain activity (neurofeedback).

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
Language other than English: German
Publisher: Hogrefe
ISSN: 1661-4747
Last Modified: 02 Nov 2022 11:34
URI: https://orca.cardiff.ac.uk/id/eprint/102450

Citation Data

Cited 1 time in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item