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Verfasst von:Deflorin, Hanna M. [VerfasserIn]   i
 Söker, Mara S. [VerfasserIn]   i
 Bauer, Stephanie [VerfasserIn]   i
 Moessner, Markus [VerfasserIn]   i
Titel:Evaluation of symptom network density as a predictor of treatment outcome of inpatient psychotherapy
Verf.angabe:Hanna M. Deflorin, Mara S. Söker, Stephanie Bauer, & Markus Moessner
E-Jahr:2024
Jahr:26 Jun 2024
Umfang:9 S.
Fussnoten:Gesehen am 20.11.2024
Titel Quelle:Enthalten in: Psychotherapy research
Ort Quelle:London [u.a.] : Routledge, part of the Taylor & Francis Group, 1991
Jahr Quelle:2024
Band/Heft Quelle:(2024), Seite 1-9
ISSN Quelle:1468-4381
Abstract:The network approach implies that the persistence of a mental disorder is rooted in a dense causal interconnection of symptoms. This study attempts to replicate and generalize previous findings in support of the assumption that higher density predicts poorer outcomes. The study examines the predictive value of network density at admission for recovery after inpatient treatment. N = 1375 adult patients with various forms of mental illness were classified as recovered (28%) versus not recovered (72%) after inpatient treatment. Recovery was defined as clinically significant improvement in impairment from admission to discharge. Networks of transdiagnostic symptoms at the time of admission were estimated. Network density, measured by global strength d, was compared between the recovered and not recovered groups using a permutation test. Global strength at the time of admission tended to be higher in the No-Recovery group (d = 10.83) than the Recovery group (d = 7.53) but the association was not significant (p = .12). Similar results were found after controlling for group size and symptom severity. The predictive value of network density for treatment outcomes remains unclear. There might be structural differences between the groups that the current measure of network density does not adequately represent.
DOI:doi:10.1080/10503307.2024.2365235
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.1080/10503307.2024.2365235
 Volltext: https://www.tandfonline.com/doi/full/10.1080/10503307.2024.2365235
 DOI: https://doi.org/10.1080/10503307.2024.2365235
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Network analysis
 network density
 prediction
 recovery
 transdiagnostic
 treatment outcome
K10plus-PPN:1909080527
Verknüpfungen:→ Zeitschrift

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