KLOCEK, Adam and Tomáš ŘIHÁČEK. A multicomponent psychodynamic treatment for comorbid disorders : a baseline and post-treatment network comparison. Counselling Psychology Quarterly. Abingdon: Routledge Journals, Taylor & Francis, 2023, neuveden, neuveden, p. 1-26. ISSN 0951-5070. Available from: https://dx.doi.org/10.1080/09515070.2023.2292212.
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Basic information
Original name A multicomponent psychodynamic treatment for comorbid disorders : a baseline and post-treatment network comparison
Authors KLOCEK, Adam and Tomáš ŘIHÁČEK.
Edition Counselling Psychology Quarterly, Abingdon, Routledge Journals, Taylor & Francis, 2023, 0951-5070.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 50100 5.1 Psychology and cognitive sciences
Country of publisher United Kingdom of Great Britain and Northern Ireland
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 3.000 in 2022
Organization unit Faculty of Social Studies
Doi http://dx.doi.org/10.1080/09515070.2023.2292212
UT WoS 001118793300001
Keywords in English Network model; psychotherapy; wellbeing; depression-anxiety; comorbidity
Tags online first
Tags International impact, Reviewed
Changed by Changed by: Mgr. Blanka Farkašová, učo 97333. Changed: 28/3/2024 13:52.
Abstract
This study aims to assess pre-post change of 439 patients undergoing a multicomponent treatment (psychodynamic psychotherapy complemented with other treatment components) using a novel network methodology targeting symptoms comorbidity. Patients were recruited from seven clinical sites in the Czech Republic. First, the effectiveness of the treatment was assessed traditionally as a pre-post change in wellbeing, depression, and anxiety using a Bayesian mixed model. The Bayesian factors of time effect (pre-post comparison) on the three outcomes indicate evidence in favor of hypotheses suggesting psychotherapy effectiveness. Second, a network analysis of individual items measuring all three outcomes (Gaussian Graphical Model) was conducted to compare baseline and post-treatment patients’ networks in global edge strength, the topography of the network, the centrality of nodes, and the clique percolation. The network density represented by global edge strength was not affected by the treatment. Nevertheless, the network structure changed in a more qualitative manner into a clearer and separated set of node communities, potentially showing a reduction in comorbidity. The central position of the depression node community in the patients’ self-reported outcome assessment network was replaced by anxiety and wellbeing node communities after treatment.
Links
EF19_073/0016943, research and development projectName: Interní grantová agentura Masarykovy univerzity
GA18-08512S, research and development projectName: Účinnost psychoterapie u pacientů s medicínsky nevysvětlenými tělesnými symptomy: Multicentrická naturalistická studie
Investor: Czech Science Foundation
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