1. Symptoms network analysis of serious mental illness: A cross disasters comparison
- Author
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Yafit Levin, Robin Goodwin, Rahel Bachem, and Menachem Ben-Ezra
- Subjects
education.field_of_study ,Population ,Psychological intervention ,Mental illness ,medicine.disease ,Scale (social sciences) ,Pandemic ,medicine ,Anxiety ,medicine.symptom ,Psychology ,education ,Centrality ,Depression (differential diagnoses) ,Clinical psychology - Abstract
BackgroundThe Kessler Psychological Distress Scale (K-6) has been used worldwide in community epidemiological surveys and served as a screening measure for serious mental illness in the general population. We take a novel approach by examining the symptoms network of the K-6 and the exploration of differences between three types of disasters: Nature related, Terror attacks, and COVID-19.AimsTo explore the K-6 symptoms network and its structure replication across the three types of disasters.MethodsA network analysis of psychological distress symptoms as assessed by the K-6 was conducted using data from 9,271 participants from different disaster samples: Terror (n = 5842), COVID-19 (n = 2428), and Nature related (n = 1001).ResultsWhile there were extensive connections between items across all disaster samples, network structure differed across the disaster types. While after a nature related disaster and the COVID-19 pandemic depression- and anxiety-items were interconnected, a terror attack resulted in more separated manifestations of anxiety and depression. Centrality analysis showed “depressed/no cheering up” to be the node with the highest strength centrality in all networks; in the Nature-related network, “restless or fidgety” was also highly central.ConclusionsResults provide evidence of different psychological distress structures in different disasters. Depending on the type of disaster, trauma-focused interventions may need to be augmented, with specific components directed at depression and/or anxiety.
- Published
- 2021
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