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 The national information systems used to understand health status and health behaviors, including drug use, rely on outdated census categories for self-employed workers.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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improving Identification of Gig Workers in National Health and Behavior Surveys

Marianne Cloeren, Clifford S. Mitchell, Kathleen Hoke, Orrin D. Ware et al.
1 citations
NEW SOLUTIONS A Journal of Environmental and Occupational Health Policy
Digital Economy and Work Transformation
1.13
article

Improving Identification of Gig Workers in National Health and Behavior Surveys

Marianne Cloeren, Clifford S. Mitchell, Kathleen Hoke, Orrin D. Ware, Jodi Jacobson Frey, Michael Chidera Ofonedu
article en
1 citations

Abstract

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 The national information systems used to understand health status and health behaviors, including drug use, rely on outdated census categories for self-employed workers.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.

NEW SOLUTIONS A Journal of Environmental and Occupational Health PolicyVol. 34(3)
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)
Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health
Decent work and economic growth
Openalex Percentile: Top 18%
Digital Economy and Work Transformation
1.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.