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      A three-timepoint network analysis of Covid-19’s impact on schizotypal traits, paranoia and mental health through loneliness

      research-article
      1 , * , , 2 , 3 , 4 , 5 , 6
      UCL Open Environment
      UCL Press
      network analysis, schizotypy, paranoia, anxiety, depression, stress, loneliness, sleep, Covid-19, longitudinal, mental health
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            Abstract

            The 2019 coronavirus (Covid-19) pandemic has impacted people’s mental wellbeing. Studies to date have examined the prevalence of mental health symptoms (anxiety and depression), yet fewer longitudinal studies have compared across background factors and other psychological variables to identify vulnerable subgroups in the general population. This study tests to what extent higher levels of schizotypal traits and paranoia are associated with mental health variables 6- and 12-months since April 2020. Over 2300 adult volunteers (18–89 years, female = 74.9%) with access to the study link online were recruited from the UK, the USA, Greece and Italy. Self-reported levels of schizotypy, paranoia, anxiety, depression, aggression, loneliness and stress from three timepoints (17 April to 13 July 2020, N 1 = 1599; 17 October to 31 January 2021, N 2 = 774; and 17 April to 31 July 2021, N 3 = 586) were mapped using network analysis and compared across time and background variables (sex, age, income, country). Schizotypal traits and paranoia were positively associated with poorer mental health through loneliness, with no effect of age, sex, income levels, countries and timepoints. Loneliness was the most influential variable across all networks, despite overall reductions in levels of loneliness, schizotypy, paranoia and aggression during the easing of lockdown (time 3). Individuals with higher levels of schizotypal traits/paranoia reported poorer mental health outcomes than individuals in the low-trait groups. Schizotypal traits and paranoia are associated with poor mental health outcomes through self-perceived feelings of loneliness, suggesting that increasing social/community cohesion may improve individuals’ mental wellbeing in the long run.

            Author and article information

            Journal
            UCL Open Environ
            UCLOE
            UCL Open Environment
            UCL Open Environ
            UCL Press (UK )
            2632-0886
            01 November 2022
            2022
            : 4
            : e044
            Affiliations
            [1 ]Department of Psychology and Human Development, University College London, London, UK
            [2 ]Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
            [3 ]Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
            [4 ]Department of Psychology and Cognitive Science, University of Trento, Rovereto, Italy
            [5 ]Psychology Program, School of Social Sciences, Nanyang Technological University, Singapore, Singapore
            [6 ]Departments of Criminology, Psychiatry, and Psychology, University of Pennsylvania, Philadelphia, PA, USA
            Author notes
            *Corresponding author: E-mail: keri.wong@ 123456ucl.ac.uk
            Author information
            https://orcid.org/0000-0002-2962-8438
            Article
            10.14324/111.444/ucloe.000044
            10208351
            37228468
            72603996-debb-4f50-9928-a222569be629
            © 2022 The Authors.

            This is an open access article distributed under the terms of the Creative Commons Attribution Licence (CC BY) 4.0, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

            History
            : 02 September 2021
            : 16 August 2022
            Page count
            Figures: 12, Tables: 7, References: 54, Pages: 23
            Categories
            Research Article

            Covid-19,sleep,loneliness,stress,depression,anxiety,paranoia,schizotypy,network analysis,mental health,longitudinal

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