| Literature DB >> 36201500 |
Sarah E Gollust1, Chris Frenier2, Margaret Tait1, Colleen Bogucki3, Jeff Niederdeppe4,5, Steven T Moore6, Laura Baum7, Erika Franklin Fowler6,7.
Abstract
Televised public service announcements were one of the ways that the U.S. federal government distributed health information about the COVID-19 pandemic to Americans in 2020. However, little is known about the reach of these campaigns or the populations who might have been exposed to the information these ads conveyed. We conducted a descriptive analysis of federally-affiliated public service announcement airings to assess where they were aired and the market-level social and demographic characteristics associated with the airings. We found no correspondence between airings and COVID-19 incidence rates from March to December 2020, but we found a positive association between airings and the Democratic vote share of the market, adjusting for other market demographic characteristics. Our results suggest that PSAs may have contributed to divergent exposure to health information among the U.S. public during the first year of the COVID-19 pandemic.Entities:
Mesh:
Year: 2022 PMID: 36201500 PMCID: PMC9536622 DOI: 10.1371/journal.pone.0275595
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.752
Fig 1Daily federal PSA Ad airings and COVID-19 cases in the United States, March to December 2020.
Authors’ analysis of data of PSA airings from Kantar/CMAG merged with data on COVID-19 incidence from the New York Times.
Fig 2Maps of COVID-19 cases and PSA Ad airings, by media market in the U.S., March-December 2020.
Authors’ analysis of data of PSA airings from Kantar/CMAG and data on COVID-19 incidence from the New York Times.
Association of PSA airings and market-level factors, overall and by pandemic wave.
| Full Time Period | Wave 1 | Wave 2 | ||||
|---|---|---|---|---|---|---|
| Coeff (SE) | p-value | Coeff (SE) | p-value | Coeff (SE) | p-value | |
| Cases per 100k | 0.00 (0.02) | 0.957 | 0.01 (0.07) | 0.847 | –0.01 (0.01) | 0.452 |
| Vote share for Clinton in 2016 | 20.5 (6.4) | 0.001 | 12.5 (3.9) | 0.001 | 7.0 (2.9) | 0.016 |
| Proportion non-white | –4.2 (4.1) | 0.303 | -2.1 (2.5) | 0.398 | –1.7 (2.0) | 0.378 |
| Proportion age <18 | –5.8 (28.5) | 0.839 | -7.7 (18.3) | 0.675 | 2.5 (13.9) | 0.858 |
| Proportion age 65+ | –40.8 (25.4) | 0.108 | -24.3 (14.7) | 0.098 | –16.4 (12.9) | 0.206 |
| Proportion with some college or more | –21.2 (10.2) | 0.038 | -9.6 (6.0) | 0.107 | –10.4 (4.9) | 0.032 |
| Market population (100k) | 4.0 (1.6) | 0.013 | 3.5 (1.2) | 0.003 | 0.4 (0.7) | 0.571 |
|
| 209 | 209 | 209 | |||
Notes. Authors’ analysis of data of PSA airings from Kantar/CMAG merged with data on COVID-19 incidence from the New York Times and market-level demographic data constructed from data from the Atlas of Presidential Elections and the American Community Survey. Wave 1 refers to March 12 –June 9, 2020; Wave 2 refers to June 10 –December 16, 2020. Coefficients and standard errors are the change in the count of PSAs associated with a one unit change in the independent variable. Results come from a DMA-level generalized linear model with a negative binomial distribution and log link. Robust standard errors in parentheses.
Fig 3Predicted PSA volume by Clinton vote share.
Authors’ analysis of data of PSA airings from Kantar/CMAG merged with data on COVID-19 incidence from the New York Times and market-level demographic data constructed from data from the Atlas of Presidential Elections and the American Community Survey. Figure displays the predicted PSA volume based on the full time period regression model displayed in Table 1, by Clinton vote share, adjusting for all other characteristics listed in Table 1.