Differences in beliefs about COVID-19 by gun ownership: a cross-sectional survey of Texas adults

Johnson, Renee M.; Crifasi, Cassandra; Goodell, Erin M. Anderson; Wisniowski, Arkadiusz; Sakshaug, Joseph W.; Thrul, Johannes und Owens, Mark (2021): Differences in beliefs about COVID-19 by gun ownership: a cross-sectional survey of Texas adults. In: BMJ Open, Bd. 11, Nr. 11, e048094

Abstract

Objectives We investigated the association between gun ownership and perceptions about COVID-19 among Texas adults as the pandemic emerged. We considered perceived likelihood that the pandemic would lead to civil unrest, perceived importance of taking precautions to prevent transmission and perceptions that the threat of COVID-19 has been exaggerated. Methods Data were collected from 5 to 12 April 2020, shortly after Texas' stay-at-home declaration. We generated a sample using random digit dial methods for a telephone survey (n=77, response rate=8%) and by randomly selecting adults from an ongoing panel to complete the survey online (n=1120, non-probability sample). We conducted a logistic regression to estimate differences in perceptions by gun ownership. To account for bias associated with use of a non-probability sample, we used Bayesian data integration and ran linear regression models to produce more accurate measures of association. Results Among the 60% of Texas adults who reported gun ownership, estimates of past 7-day gun purchases, ammunition purchases and gun carrying were 15% (n=78), 20% (n=100) and 24% (n=130), respectively. We found no evidence of an association between gun ownership with perceived importance of taking precautions to prevent transmission or with perceived likelihood of civil unrest. Results from the logistic regression (OR 1.27, 95% CI 0.99 to 1.63) and the linear regression (beta=0.18, 95% CI 0.07 to 0.29) suggest that gun owners may be more likely to believe the threat of COVID-19 was exaggerated. Conclusions Compared with those without guns, gun owners may have been inclined to downplay the threat of COVID-19 early in the pandemic.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Mathematik, Informatik und Statistik > Statistik
• Themengebiete: 500 Naturwissenschaften und Mathematik > 510 Mathematik
• ISSN: 2044-6055
• Sprache: Englisch