Kristi N. Lavigne, M.A., Saint Louis University; Andrea Cornelius, M.A., Saint Louis University; Matthew J. Grawitch, Ph.D, Saint Louis University
The Personal Resource Allocation (PRA) framework (Grawitch et al., 2010) is leveraged as the lens for understanding the impact of the demands introduced by the COVID pandemic. We tested (1) whether the perceived impact of the pandemic on work (quality, quantity) and health behaviors (eating habits, exercise habits, sleep) in June 2000 were differentially associated with general wellbeing and work engagement and (2) whether resilience played an important explanatory role beyond other potential control variables. We specifically proposed:
H1: Self-reported impact of the pandemic on general health behaviors of sleep (H1a), exercise (H1b), and eating habits (H1c) will be significant predictors of general wellbeing.
H2: Self-reported impact of the pandemic on work quality (H2a) and quantity (H2b) will be significant predictors of work engagement.
H3: Those with higher resilience will be less likely to report the pandemic had a negative impact on their general health behaviors (H3a) and work (H3b) and more likely to report higher levels of work engagement (H3c) and general wellbeing (H3d).
Exercise, eating, and sleep are commonly associated with work and general wellbeing (Litwiller, 2017; Walsh, 2011). The more people report that a significant event alters health-related behaviors for the better (or worse), the more they should report higher (or lower) levels of general wellbeing. Such events may also alter quality or quantity of work and result in lower (or higher) work engagement, given the associations observed between work engagement and emotional demands (Xanthopoulou et al., 2013).
However, trait resilience, defined as an individual’s capacity to bounce back from adversity or unexpected circumstances, is an important determinant of the degree to which such circumstances lead to negative outcomes (Smith et al., 2008). Trait resilience has consistently been shown to be a positive indicator of mental health, especially in adverse situations (Hu et al., 2015). More resilient individuals may be less likely to report a negative impact of the pandemic on different aspects of their lives and more likely to report greater work engagement and general wellbeing during the early stages of lockdown.
A multinational sample of 652 workers were solicited from CINT to participate in an online survey. We do not report data by country due to lack of differences in means/correlations among respondents from any of the countries.
Pandemic Impact. Changes as a result of COVID-19 were assessed, including the amount of impact the pandemic had on work output (quality and quantity) and health behaviors (sleep, exercise, eating habits) using a sliding scale (-3=very negative; 3=very positive).
General Well-Being. The 18-item General Well-Being Schedule (Taylor et al., 2003) captures aspects of mental wellbeing using a 5-point scale (1=all of the time; 5=none of the time).
Work Engagement. Work engagement was assessed using an adapted 9-item Utrecht Work Engagement Scale (Schaufeli et al., 2006). Respondents were asked how often each item applied to them in the past month (1=Never; 5=Every day).
Resilience. The three positively keyed items (due to poor correlations with the negatively keyed items) from the Brief Resilience Scale (Smith et al., 2008) were employed to measure resilience to setbacks. The items were rated on a 7-point scale (1=Strongly Disagree; 7=Strongly Agree).
Demographics. As control variables, we assessed several demographics that played a role in the way the pandemic impacted workers: post-COVID-19 pay cut (yes/no), essential worker status (yes/no), prior remote work experience (yes/no) and remote work training (3 items adapted from Staples et al., 1999).
Table 1 presents descriptive statistics. We used path modeling for hypothesis testing (Tables 2-3, Figure 1). H1a and H1b were supported, but H1c was not. H2a was supported, but H2b was not. Additionally, work quality impact was associated with general wellbeing. Finally, H3 was supported; resilience demonstrated a significant association with all pandemic impact items, work engagement, and general wellbeing.
Overall, those who reported more negative impact of the pandemic on their work and health behavior also reported lower levels of work engagement and general wellbeing. Trait resilience was associated with perceptions of a less negative (and more positive) impact of the pandemic on work and health behaviors and greater levels of both work engagement and wellbeing. Of the control variables, taking a pay cut and possessing prior remote work experience were associated with pandemic impact, and having more remote work training was associated with work engagement.
The results suggest that trait resilience is a critical individual difference that influenced people’s ability to adapt during the early stages of the pandemic. While future research cannot build on these results in the context of a global pandemic, it is important to consider the role of trait resilience in future studies that focus on people’s responses to significant adversity.