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Resilient outcomes in people with a history of mental disorder during the COVID-19 pandemic: an international 2-years longitudinal prospective study.

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Title: Resilient outcomes in people with a history of mental disorder during the COVID-19 pandemic: an international 2-years longitudinal prospective study.
Authors: Pinucci, I. (AUTHOR), Tedeschi, F. (AUTHOR), Serra, R. (AUTHOR), Patanè, M. (AUTHOR), Acartürk, C. (AUTHOR), Andriani, D. (AUTHOR), Bryant, R. A. (AUTHOR), Burchert, S. (AUTHOR), Caggiu, G. (AUTHOR), Campos, D. (AUTHOR), Conflitti, C. (AUTHOR), Davisse-Paturet, C. (AUTHOR), Felez-Nobrega, M. (AUTHOR), Fuhr, D. (AUTHOR), Hall, B. J. (AUTHOR), Haro, J. M. (AUTHOR), Huizink, A. C. (AUTHOR), Knaevelsrud, C. (AUTHOR), Kurt, G. (AUTHOR), Lam, A. (AUTHOR)
Source: Social Psychiatry & Psychiatric Epidemiology. Jan2026, Vol. 61 Issue 1, p67-80. 14p.
Subjects: COVID-19, Psychological resilience, Social support, Mental health, Psychological distress, Longitudinal method, Social processes, Sociodemographic factors
Abstract: Background: During the COVID-19 pandemic, the global population was exposed to a significant psychological stress, which had an impact on the mental health in individuals with pre-existing mental disorders. Despite their heightened vulnerability, subgroups within this population demonstrated resilient outcomes throughout the pandemic. This study aims to identify predictors of long-term, sustained resilient outcomes among people with a history of mental disorder during the first two years of the pandemic. Methods: In this international 2-year, 5-wave longitudinal online survey, the Patient Health Questionnaire-9, the Generalized Anxiety Disorder Scale, and the PTSD Checklist DSM-5 were used for a proxy measure of psychological distress. As possible predictors of sustained resilient outcomes, we investigated socio-demographic characteristics, economic and housing status, pandemic-related issues, chronic diseases, social support, fear of contamination and personal values which were investigated respectively through the Oslo Social Support Scale, the Padua Inventory, and the Portrait Values Questionnaire. Data were analysed with a Mover-Stayer Latent Transition Analysis model. Results: Nine-hundred and forty-three participants with a mental disorder were included in the analysis. Variables associated with a higher chance of sustained resilient outcomes were older age, maintaining a job, and having more people in the household. In contrast, female gender, losing job, difficulty in meeting basic needs, higher fear of contamination, hedonism, less social support and loneliness resulted in a lower likelihood of presenting sustained resilient outcomes. Conclusion: This study identified factors that predictsustained resilience in people with mental disorders. The newly discovered predictors could prove invaluable in developing strategies to enhance the resilience of people with mental disorders during times of crises, such as pandemics. [ABSTRACT FROM AUTHOR]
Copyright of Social Psychiatry & Psychiatric Epidemiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Resilient outcomes in people with a history of mental disorder during the COVID-19 pandemic: an international 2-years longitudinal prospective study.
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  Data: <searchLink fieldCode="JN" term="%22Social+Psychiatry+%26+Psychiatric+Epidemiology%22">Social Psychiatry & Psychiatric Epidemiology</searchLink>. Jan2026, Vol. 61 Issue 1, p67-80. 14p.
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  Data: Background: During the COVID-19 pandemic, the global population was exposed to a significant psychological stress, which had an impact on the mental health in individuals with pre-existing mental disorders. Despite their heightened vulnerability, subgroups within this population demonstrated resilient outcomes throughout the pandemic. This study aims to identify predictors of long-term, sustained resilient outcomes among people with a history of mental disorder during the first two years of the pandemic. Methods: In this international 2-year, 5-wave longitudinal online survey, the Patient Health Questionnaire-9, the Generalized Anxiety Disorder Scale, and the PTSD Checklist DSM-5 were used for a proxy measure of psychological distress. As possible predictors of sustained resilient outcomes, we investigated socio-demographic characteristics, economic and housing status, pandemic-related issues, chronic diseases, social support, fear of contamination and personal values which were investigated respectively through the Oslo Social Support Scale, the Padua Inventory, and the Portrait Values Questionnaire. Data were analysed with a Mover-Stayer Latent Transition Analysis model. Results: Nine-hundred and forty-three participants with a mental disorder were included in the analysis. Variables associated with a higher chance of sustained resilient outcomes were older age, maintaining a job, and having more people in the household. In contrast, female gender, losing job, difficulty in meeting basic needs, higher fear of contamination, hedonism, less social support and loneliness resulted in a lower likelihood of presenting sustained resilient outcomes. Conclusion: This study identified factors that predictsustained resilience in people with mental disorders. The newly discovered predictors could prove invaluable in developing strategies to enhance the resilience of people with mental disorders during times of crises, such as pandemics. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Social Psychiatry & Psychiatric Epidemiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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