Telework (also referred to as telecommuting or remote work), is defined as working outside of the conventional office setting, such as within one’s home or in a remote office location, often using a form of information communication technology to communicate with others (supervisors, coworkers, subordinates, customers, etc.) and to perform work tasks. Remote work increased over the last decade and tremendously in response to the COVID-19 pandemic. The purpose of this article is to review and critically evaluate the existing research about telework and worker health and well-being. In addition, we review and evaluate how engaging in this flexible form of work impacts worker health and well-being. Specifically, we performed a literature search on the empirical literature related to teleworking and worker health and well-being, and reviewed articles published after the year 2000 based on the extent to which they had been discussed in prior reviews. Next, we developed a conceptual framework based on our review of the empirical literature. Our model explains the process by which telework may affect worker health and well-being in reference to individual, work/life/family, organizational, and macro level factors. These components are explained in depth, followed by methodological and fundamental recommendations intended to guide future research, policies, and practices to maximize the benefits and minimize the harms associated with telework, and offer recommendations for future research.
Few longitudinal studies provide detailed information about the characteristics of the jobs older workers engage in, limiting the ability to evaluate the potential consequences of extended working lives. In this session, we introduce a new project linking the 2019 O*NET taxonomy and corresponding data to the Health and Retirement Study for public use. We describe the procedures taken to develop an O*NET linkage to be released to HRS users in the form of a publicly available data file, allowing aging researchers to evaluate detailed aspects of occupations in the 50+ population. We explain the types of variables that will be made available in the O*NET-HRS occupation project, and provide examples for how the measures can be used in longitudinal HRS studies.
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