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Tytuł pozycji:

Network Structures of Symptoms From the Zung Depression Scale.

Tytuł:
Network Structures of Symptoms From the Zung Depression Scale.
Autorzy:
Briganti G; Unit of Epidemiology, Biostatistics and Clinical Research, Université Libre de Bruxelles, Belgium.
Scutari M; Dalle Molle Institute for Artificial Intelligence Research, Switzerland.
Linkowski P; Unit of Epidemiology, Biostatistics and Clinical Research, Université Libre de Bruxelles, Belgium.
Źródło:
Psychological reports [Psychol Rep] 2021 Aug; Vol. 124 (4), pp. 1897-1911. Date of Electronic Publication: 2020 Jul 19.
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Publication: 2016- : Thousand Oaks, CA : SAGE
Original Publication: Louisville, Ky. : Southern Universities Press,
MeSH Terms:
Psychometrics*
Depression/*diagnosis
Depression/*psychology
Adolescent ; Adult ; Belgium ; Female ; Humans ; Male ; Students/psychology ; Surveys and Questionnaires ; Young Adult
Contributed Indexing:
Keywords: Network analysis; directed acyclic graphs; students
Entry Date(s):
Date Created: 20200721 Date Completed: 20210811 Latest Revision: 20210811
Update Code:
20240104
DOI:
10.1177/0033294120942116
PMID:
32686585
Czasopismo naukowe
The Self-rating Depression Scale (SDS) is a psychometric tool composed of 20 items used to assess depression symptoms. The aim of this work is to perform a network analysis of this scale in a large sample composed of 1090 French-speaking Belgian university students. We estimated a regularized partial correlation network and a Directed Acyclic Graph for the 20 items of the questionnaire. Node predictability (shared variance with surrounding nodes in the network) was used to assess the connectivity of items. The network comparison test was performed to compare networks from female and male students. The network composed of items from the SDS is overall positively connected, although node connectivity varies. Item 11 ("My mind is as clear as it used to be") is the most interconnected item. Networks from female and male students did not differ. DAG reported directed edges among items. Network analysis is a useful tool to explore depression symptoms and offers new insight as to how they interact. Further studies may endeavor to replicate our findings in different samples, including clinical samples to replicate the network structures and determine possible viable targets for clinical intervention.
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