Abstract
AbstractTo explore workers’ well-being during COVID-19, researchers have primarily utilized variable-centered approaches (e.g., regression) focusing on describing workers’ general level of well-being. Given the diversity of factors that may have impacted workers’ well-being during the pandemic, focusing on such well-being trends do not provide sufficient insight into the different lived well-being experiences during the pandemic. Moreover, positive well-being in workers’ general lives and work has been understudied in such complex public health crises. To address these issues, we use latent profile analysis, a person-centered analysis, to explore the diverse well-being realities Canadian workers (employed before COVID-19 or working at the time of the survey) experienced at the beginning of COVID-19. Canadian workers (N = 510) were surveyed between May 20-27th, 2020, on positive (meaning in life, flourishing, thriving at work) and negative (distress, stress, impaired productivity, troublesome symptoms at work) well-being indicators, as well as on factors that may be associated with experiencing different well-being profiles. Five well-being profiles emerged: moderately prospering, prospering, moderately suffering, suffering, and mixed. Factors at the self- (gender, age, disability status, trait resilience), social- (marital status, family functioning, having children at home), workplace- (some employment statuses and work industries, financial strain, job security), and pandemic-related (perceived vulnerability to COVID-19, social distancing) ecological levels predicted profile membership. Recommendations for employers, policymakers, and mental health organizations are discussed.
Funder
Social Sciences and Humanities Research Council of Canada
Mitacs
Publisher
Springer Science and Business Media LLC
Reference83 articles.
1. Alegría, M., NeMoyer, A., Falgàs Bagué, I., Wang, Y., & Alvarez, K. (2018). Social determinants of mental health: Where we are and where we need to go. Current Psychiatry Reports, 20(11), 1–20. https://doi.org/10.1007/s11920-018-0969-9.
2. Allan, B. A., Autin, K. L., & Wilkins-Yel, K. G. (2021). Precarious work in the 21st century: A psychological perspective. Journal of Vocational Behavior, 126, 1–13. https://doi.org/10.1016/j.jvb.2020.103491.
3. Asparouhov, T., & Muthén, B. (2021). Auxiliary variables in mixture modeling: Using the BCH method in mplus to estimate a distal outcome model and an arbitrary secondary model. Statmodel. https://www.statmodel.com/examples/webnotes/webnote21.pdf.
4. Babb, J., Sokal, L., & Eblie Trudel, L. (2022). This is us: Latent profile analysis of Canadian teachers’ burnout during the COVID-19 pandemic. Canadian Journal of Education, 45(2), 555–585. https://doi.org/10.53967/cje-rce.v45i2.5057.
5. Bakk, Z., & Vermunt, J. K. (2016). Robustness of stepwise latent class modeling with continuous distal outcomes. Structural Equation Modeling: A Multidisciplinary Journal, 23, 20–31. https://doi.org/10.1080/10705511.2014.955104.