Effects of Job Quality in the Service Sector on Health-Related Outcomes Across the Life Course

项目摘要/摘要 美国服务业雇佣了2,700万名工人，占美国劳动力的20%。在新技术的推动下， 服务部门的雇主已经接受了监督和制裁，这会影响任务的时间和速度 在工作中，不可预测的和受限的调度做法，这会影响上下班时间的组织 工作和自动化，这形成了对未来和工作不安全感的长期预期。我们指的是这些 工作条件，作为工作质量的时间维度，与纯粹的经济情况形成对比 工作质量的各个维度。尽管先前的研究已经在其他方面之间建立了牢固的关系 关于工作条件和健康，人们对这些新的和日益普遍的 工作场所的做法影响工人的健康和健康的老龄化。造成这种差距的一个重要原因是缺乏合适的 现有数据包含这些紧急工作场所做法和工人健康结果的信息， 然而，政策制定者已经开始采取行动来规范这些做法。因此，迫切需要 收集新的数据，使研究人员能够估计暴露在这些临时环境中对健康的影响 员工在整个生命过程中的工作质量维度。这项拟议的研究扩展了一项创新的 从服务部门的目标人群大规模、低成本、快速地收集调查数据的方法 工人们。我们使用Facebook广告平台购买和投放调查招聘广告 在Facebook和Instagram用户的移动和桌面新闻馈送中，针对在零售业和 快餐。这种方法使我们能够针对特定雇主和/或特定地区的用户。我们 建议收集全国9万名劳动者的重复横断面和纵向调查数据。 本研究使用这些数据和方法来实现三个目标。首先，我们估计 工作质量突现时间维度与员工健康和健康老龄化的关系。这个 数据收集的目的是利用自然实验为健康影响提供严格的证据 暂时不稳定的工作。一组分析将利用城市和公司政策的变化来使用严格的 差异法和工具变量法估计工作质量对健康的因果效应。 第二，我们评估监测和制裁的健康后果是否计划不可预测 而约束和自动化在整个生命过程中都是不同的。最后，我们将评估社会和公众的支持 这可能会缓冲和减轻工作质量的这些时间维度对健康的有害影响。总而言之，我们 部署创新的数据收集方法与严格的评估相结合，以利用自然 当劳动法或公司惯例发生变化时实施的实验。我们的重大贡献 该项目需要测试工作质量新维度如何影响健康，评估不同的脆弱性 评估生命历程，衡量保护性支持和政策的重要性。总的来说，这项研究 提供关于工作质量对健康影响的关键缺失证据。

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 of our project entail testing how new dimensions of job quality affect health, estimating differential vulnerabilities across the life course, and gauging the importance of protective supports and policies. Collectively, this research provides key missing evidence on health impacts of job quality.