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The associations between interoceptive awareness, emotion regulation, acceptance, and well-being in patients receiving multicomponent treatment: a dynamic panel network model
A. Klocek, T. Řiháček
Status neindexováno Jazyk angličtina Země Itálie
Typ dokumentu časopisecké články
NLK
Directory of Open Access Journals
od 2013
PubMed Central
od 2017
ROAD: Directory of Open Access Scholarly Resources
od 2011
PubMed
37503659
DOI
10.4081/ripppo.2023.659
Knihovny.cz E-zdroje
- Publikační typ
- časopisecké články MeSH
Mechanisms of change represent the cornerstone of the therapeutic process. This study aimed to investigate how network models could be used to test mechanisms of change at a group level. A secondary aim was to investigate which of the several hypothesized mechanisms (emotion regulation, interoceptive awareness, and acceptance) are related to changes in psychological well-being. The sample comprised adult patients suffering from psychological disorders (N=444; 70% women) from 7 clinical sites in the Czech Republic who were undergoing groupbased multicomponent treatment composed mainly of psychodynamic psychotherapy (lasting from 4 to 12 weeks depending on the clinical site). Data were collected weekly using the multidimensional assessment of interoceptive awareness, emotion regulation skills questionnaire, chronic pain acceptance questionnaire-symptoms and outcome rating scale. A lag-1 longitudinal network model was employed for exploratory analysis of the panel data. The pruned final model demonstrated a satisfactory fit. Three networks were computed, i.e., temporal, contemporaneous, and between-person networks. The most central node was the modification of negative emotions. Mechanisms that were positively associated with well-being included modification, readiness to confront negative emotions, activity engagement, and trust in bodily signals. Acceptance of negative emotions showed a negative association with well-being. Moreover, noticing bodily sensations, not worrying, and self-regulation contributed indirectly to changes in well-being. In conclusion, the use of network methodology to model panel data helped generate novel hypotheses for future research and practice; for instance, well-being could be actively contributing to other mechanisms, not just a passive outcome.
Citace poskytuje Crossref.org
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