Background
University of Toronto has led one of the most extensive longitudinal studies on work, economic life and well-being in North America. Under the direction of Professor of Sociology Scott Schieman, the research has tracked tens of thousands of workers, examining how employment conditions shape identity, health and overall life satisfaction.
The Canadian Quality of Work and Economic Life Study (C-QWELS) was designed as an ongoing, nationally representative effort, capturing worker experiences over time. The first wave was conducted before the pandemic, creating a rare and valuable baseline for understanding how conditions changed during and after a period of disruption.
As the study expanded through multiple waves, it generated a substantial body of academic work exploring job insecurity, financial strain, social isolation and mental health.
Challenge
Longitudinal research of this scale presents a unique set of challenges.
Maintaining consistency across waves while adapting to rapidly changing real-world conditions requires rigorous sampling and fielding. The pandemic introduced sudden shifts in employment, economic stability and daily life, making it essential to capture change as it happened without compromising quality.
Ensuring nationally representative samples over multiple waves also becomes more complex over time, particularly when tracking the same themes across different stages of disruption and recovery.
As the study progressed, there was a need to scale data collection efficiently while preserving the methodological consistency required for long-term trend analysis and academic publication.
Solution
Starting in 2019, University of Toronto partnered with Angus Reid on the study, combining academic design with large-scale research execution.
Drawing on proprietary panels and established sampling expertise, Angus Reid helped ensure nationally representative coverage and consistent fielding across waves. This allowed the research team to continue tracking worker experiences as conditions evolved through the pandemic and into the post-pandemic period.
The partnership enabled the study to maintain continuity while scaling efficiently, supporting both the depth required for academic research and the speed needed to capture real-time shifts.
Results
The collaboration supported one of the most comprehensive, multi-wave datasets on work and well-being available.
Key outcomes include:
• A continuous dataset spanning pre-pandemic, pandemic and post-pandemic periods
• Clear visibility into how job insecurity, financial strain and work-life disruption evolved over time
• Deeper insight into the relationship between work conditions and mental, social and physical health
• A strong body of academic output, including working papers and peer-reviewed publications across leading journals
Because the study began before the pandemic, it provides a uniquely clear view of change over time, helping distinguish between pre-existing trends and pandemic-driven shifts.
Additional context
The research was later extended to the United States through the Quality of Employment Survey–Updated (QES-UP), where University of Toronto and Angus Reid fielded nationally representative samples of American workers, building on the same longitudinal approach.
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