Assessing Resilience and Its Correlates among Residents of Fort McMurray during the COVID-19 Pandemic

Nnamdi Nkire, Reham Shalaby, Gloria Obuobi-Donkor, Belinda Agyapong, Ejemai Eboreime and Vincent I. O. Agyapong ()
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Nnamdi Nkire: Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2R3, Canada
Reham Shalaby: Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2R3, Canada
Gloria Obuobi-Donkor: Department of Psychiatry, Faculty of Medicine, Dalhousie University, Halifax, NS B3H 4R2, Canada
Belinda Agyapong: Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2R3, Canada
Ejemai Eboreime: Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2R3, Canada
Vincent I. O. Agyapong: Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2R3, Canada

IJERPH, 2023, vol. 20, issue 12, 1-13

Abstract: Background: The coronavirus disease of 2019 (COVID-19) pandemic has led to a global health crisis that has affected the psychological well-being of individuals across the world. The persistence of the pandemic and measures to curtail it have tested people’s ability to cope successfully and bounce back from the pandemic, otherwise referred to as resilience. The present study examined resilience levels among residents of Fort McMurray and identified the demographic, clinical and social factors associated with resilience. Methods: The study used a cross-sectional survey design and collected data from 186 participants using online questionnaires. The survey included questions assessing sociodemographic information, mental health history and COVID-19-related variables. The main study outcome was resilience measured using the six-item Brief Resilience Scale (BRS). The data from the survey were analyzed using chi-squared tests and binary logistic regression analyses in the Statistical Package for Social Sciences (SPSS), version 25. Results: The results showed that seven independent variables (age, history of depression, history of anxiety, willingness to receive mental health counselling, support from the government of Alberta and support from employer) were statistically significant within the context of the logistic regression model. A history of an anxiety disorder was demonstrated to best predict low resilience. Participants who had a history of anxiety disorder were five times more likely to show low resilience compared to those without such a history. Participants with a history of depression showed a three-fold likelihood of having low resilience in comparison to those who did not have a history of depression. Individuals who expressed a desire to receive mental health counselling had a four-times likelihood of having low resilience than those who did not express a desire to receive mental health counselling. The results also showed that younger participants were more prone to low resilience compared to older participants. Receiving support from the government and one’s employer is a protective factor. Conclusions: This study highlights the importance of examining resilience and its associated factors during a pandemic such as COVID-19. The results demonstrated that a history of anxiety disorder, depression and being younger were important predictors of low resilience. Responders who reported the desire to receive mental health counselling also reported expressing low resilience. These findings could be used to design and implement interventions aimed at improving the resilience of individuals affected by the COVID-19 pandemic.

Keywords: anxiety; COVID-19; depression; pandemic; predictor; resilience; mental health (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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