Improving Identification of Gig Workers in National Health and Behavior Surveys
This paper describes the work-related information collected in several important U.S. national health and behavior surveys, to highlight data gaps that prevent identifying responses by vulnerable workers in the gig economy, with emphasis on the growing digital platform sector of the work force. The national information systems used to understand health status and health behaviors, including drug use, rely on outdated census categories for self-employed workers. This paper describes the importance of understanding the needs of this growing part of the labor sector and describes how some of the most well-known and utilized national surveys fail to meet this need. For the agencies conducting national health and behavior surveys, we propose revisions to the categories used to classify type of worker and recommend adoption of a new Worker-Employer Relationship Classification model.
Authors
- Marianne Cloeren (ORCID: https://orcid.org/0000-0003-3805-6504)
- Clifford S. Mitchell
- Kathleen Hoke
- Orrin D. Ware (ORCID: https://orcid.org/0000-0002-3269-5324)
- Jodi Jacobson Frey (ORCID: https://orcid.org/0000-0001-7381-2673)
- Michael Chidera Ofonedu
Institutions
- University of North Carolina at Chapel Hill (US)
- University of Maryland, Baltimore (US)
- George Washington University (US)
- Maryland Department of Health (US)
- University of Baltimore (US)
Publication Details
- Journal
- NEW SOLUTIONS A Journal of Environmental and Occupational Health Policy
- Published
- 2024-08-09
- DOI
- https://doi.org/10.1177/10482911241269313
- Citations
- 1
- Primary Topic
- Digital Economy and Work Transformation
- Type
- article
- Field-Weighted Citation Impact
- 1.13
Funders
- Centers for Disease Control and Prevention
- National Institute for Occupational Safety and Health