Five Years after the Fort McMurray Wildfire: Prevalence and Correlates of Low Resilience

Background: The Fort McMurray wildfire of 3 May 2016 was one of the most devastating natural disasters in Canadian history. Although resilience plays a crucial role in the daily functioning of individuals by acting as a protective shield that lessens the impact of disasters on their mental well-being, to date little is known about the long-term impact of wildfires on resilience and associated predictors of low resilience. Objectives: The objective of the study was to assess the prevalence and predictors of resilience among residents of Fort McMurray five years after the wildfires. Method: This was a quantitative cross-sectional study. A self-administered online survey which included standardized rating scales for resilience (BRS), anxiety (GAD-7), depression (PHQ-9), and post-traumatic stress disorder (PTSD)(PCL-C) was used to determine the prevalence of resilience as well as its demographic, clinical, and wildfire-related predictors. The data were collected between 24 April and 2 June 2021 and analyzed using the Statistical Package for Social Sciences (SPSS) version 25 using univariate analysis with a chi-squared test and binary logistic regression analysis. Results: A total of 186 residents completed the survey out of 249 who accessed the online survey, producing a response rate of 74.7%. Most of the respondents were females (85.5%, 159), above 40 years of age (81.6%, 80), employed (94.1%, 175), and in a relationship (71%, 132). Two variables—having had PTSD symptoms (OR = 2.85; 95% CI: 1.06–7.63), and age—were significant predictors of low resilience in our study. The prevalence of low resilience in our sample was 37.4%. Conclusions: Our results suggest that age and the presence of PTSD symptoms were the independent significant risk factors associated with low resilience five years after the Fort McMurray wildfire disaster. Further research is needed to enhance understanding of the pathways to resilience post-disaster to identify the robust predictors and provide appropriate interventions to the most vulnerable individuals and communities.