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

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            Background 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 sub-groups 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.

            Methods Over 2,300 adult volunteers (18-89 years, female=74.9%) with access to the study link online were recruited from the UK, 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 =1,599; 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).

            Results 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.

            Conclusion 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

            UCL Open: Environment Preprint
            UCL Press
            17 May 2022
            [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; Department of Psychology, University of Chinese Academy of Sciences, Beijing China
            [3 ] Department of Psychology and Cognitive Science, University of Trento, Rovereto Italy; Psychology Program, School of Social Sciences, Nanyang Technological University, Singapore
            [4 ] Departments of Criminology, Psychiatry, and Psychology, University of Pennsylvania, Philadelphia USA
            Author notes
            Author information

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

            : 2 September 2021
            : 16 August 2022
            UCL Global Engagement Fund 563920.100.177785

            The datasets generated during and/or analysed during the current study are available in the repository: http://www.doi.org/10.5522/04/16583861
            Psychology,Social & Behavioral Sciences
            Network Analysis,Schizotypy,Paranoia,Depression,Loneliness,Anxiety,Sleep,Mental Health,COVID-19,Longitudinal,Health,Public policymaking


            Date: 16 August 2022

            Handling Editor: Prof Dan Osborn

            Editorial decision: Accept. This revised article has been accepted following peer review and it is suitable for publication in UCL Open: Environment.

            2022-08-16 15:27 UTC

            Date: 19 July 2022

            Handling Editor: Prof Dan Osborn

            The article has been revised, this article remains a preprint article and peer-review has not been completed. It is under consideration following submission to UCL Open: Environment for open peer review.

            2022-07-19 13:26 UTC

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