PROJECT SUMMARY/ABSTRACT The U.S. service sector employs 27 million workers, 20% of the U.S. workforce. Abetted by new technologies, employers in the service sector have embraced surveillance and sanctioning, which affect time and pace of tasks on the job, unpredictable and constrained scheduling practices, which affect the organization of time on and off work, and automation, which shapes longer-term expectations for the future and job insecurity. We refer to these working conditions, collectively, as temporal dimensions of job quality to draw a contrast with purely economic dimensions of job quality. Although prior research has established a robust relationship between other aspects of job conditions and health, there is a gap in knowledge about how these new and increasingly prevalent workplace practices affect worker health and healthy aging. One important reason for this gap is a lack of suitable existing data containing information on both these emergent workplace practices and workers’ health outcomes, yet policy makers have already begun to take action to regulate these practices. There is thus a critical need to collect new data that will allow researchers to estimate the health effects of exposure to these temporal dimensions of job quality for workers across the life course. The proposed research expands upon an innovative method for collecting survey data at scale, at low-cost, and with speed from a target population of service-sector workers. We use the Facebook advertising platform to purchase and place survey recruitment advertisements in the mobile and desktop newsfeeds of Facebook and Instagram users, targeting those who work in retail and fast food. This approach allows us to target users with particular employers and/or in specific localities. We propose to collect repeated cross-sectional and longitudinal survey data from 90,000 workers across the country. The proposed research uses these data and methods to accomplish three aims. First, we estimate the relationship between emergent temporal dimensions of job quality and worker health and healthy aging. The data collection is designed to capitalize on natural experiments to provide rigorous evidence on the health effects of temporally precarious work. One set of analyses will exploit city and company policy changes to use rigorous difference-in-differences and instrumental variable methods to estimate causal effects of job quality on health. Second, we assess whether the health consequences of surveillance and sanctioning, schedule unpredictability and constraint, and automation vary across the life course. Finally, we will assess the social and public supports that may buffer and mitigate the harmful health effects of these temporal dimensions of job quality. In sum, we deploy an innovative data collection approach combined with rigorous estimation to take advantage of natural experiments implemented when labor laws or company practices change. The significant contributions o...