Predictors of public support for social safety net policy during the COVID-19 pandemic.

Details

• Personal Author:
  Barry CL ; Hatton CR ; Levine AS ; McGinty EE ; Topazian RJ
• Description:
  Introduction: U.S. residents had varying experiences of the COVID-19 pandemic and social safety net policy in 2020. Past research has suggested that partisanship, ideology, racial attitudes, and personal experience may each influence policy attitudes. In this study, we explore whether variation in support for social safety net policy in 2020 is predicted by negative experiences of the pandemic when controlling for racial attitudes, partisanship, and ideology. Methods: Support for 12 social safety net policies in 2020 was estimated using data from a nationally representative panel survey of U.S. adults conducted in 2020 (n=1,222). Logistic regression was used to examine differences in the predicted probability of supporting a majority of social safety net policies related to health, housing, and employment by partisanship, ideology, racial attitudes, and negative experiences of the pandemic. Analyses were conducted in 2021. Results: Higher levels of symbolic racism was a consistently strong predictor of lower social safety net policy support across health, housing, and employment policies; as was identifying as either Conservative or Republican. Negative experiences of the pandemic were generally unpredictive of support for the social safety net policy. Conclusions: Despite the pandemic's consequences as well as the potential for social safety net policy to address these consequences, negative experiences of the pandemic failed to predict policy support, even as racial attitudes, partisanship, and ideology strongly predicted these preferences in 2020. Building public support for social safety net policy requires communication strategies that identify the shared benefits of these policies. [Description provided by NIOSH]
• Subjects:
  Behavior Cohort Studies Communicable Diseases Occupational Health Personal Protective Equipment Preventive Medicine Public Health Respiratory Protective Devices Safety
• Keywords:
  Public health; Face masks; Policy; Infection control; Disease prevention; Cohort studies; COVID-19; Coronavirus; Attitude; Behavior patterns; Psychosocial factors; Preventive measures
• ISSN:
  0749-3797
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Maryland ; New York ; OSHA Region 2 ; OSHA Region 3
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  77-84
• Volume:
  63
• Issue:
  1
• NIOSHTIC Number:
  nn:20065402
• Citation:
  Am J Prev Med 2022 Jul; 63(1):77-84
• Contact Point Address:
  C. Ross Hatton, MPA, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 North Broadway, Baltimore MD 21205
• Email:
  chatton2@jhu.edu
• Federal Fiscal Year:
  2022
• Performing Organization:
  Johns Hopkins University
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  American Journal of Preventive Medicine
• End Date:
  20280630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:f016cc2478970e942884aa803594d30333f71242906cb594a3ebdcd36647dd941800d2882efa28cdef03ad3247695448f593a1c633ef997227f819ef81c65a28
• Download URL:
  https://stacks.cdc.gov/view/cdc/249426/cdc_249426_DS1.pdf
• File Type:
  [PDF - 581.50 KB ]