Preferences Toward COVID-19 Diagnostic Testing Features: Results From a National Cross-Sectional Survey

• Published in: American journal of health promotion Vol. 36; no. 1; pp. 185 - 189
• Main Authors: Katare, Bhagyashree, Zhao, Shuoli, Cuffey, Joel, Marshall, Maria I., Valdivia, Corinne
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.01.2022; American Journal of Health Promotion
• Subjects: Comfort; Coronaviruses; COVID-19; COVID-19 diagnostic tests; COVID-19 Testing; Cross-Sectional Studies; Diagnostic tests; Discrete choice; Health promotion; Humans; Incentives; Medical diagnosis; Monetary incentives; Polls & surveys; Preferences; Saliva; SARS-CoV-2; discrete choice experiment; monetary incentive; disease prevention; COVID-19 diagnostic testing; health communications
• ISSN: 0890-1171; 2168-6602; 2168-6602
• DOI: 10.1177/08901171211034093

Purpose: Describe preferences toward COVID-19 testing features (method, location, hypothetical monetary incentive) and simulate the effect of monetary incentives on willingness to test. Design: Online cross-sectional survey administered in July 2020. Subjects: 1,505 nationally representative U.S. respondents. Measures: Choice of preferred COVID-19 testing options in discrete choice experiment. Options differed by method (nasal-swab, saliva), location (hospital/clinic, drive-through, at-home), and monetary incentive ($0, $10, $20). Analysis: Latent class conditional logit model to classify preferences, mixed logit model to simulate incentive effectiveness. Results: Preferences were categorized into 4 groups: 34% (n = 517) considered testing comfort (saliva versus nasal swab) most important, 27% (n = 408) were willing to trade comfort for monetary incentives, 19% (n = 287) would only test at convenient locations, 20% (n = 293) avoided testing altogether. Relative to no monetary incentives, incentives of $100 increased the percent of testing avoiders (16%) and convenience seekers (70%) that were willing to test. Conclusion: Preferences toward different COVID-19 testing features vary, highlighting the need to match testing features with individuals to monitor the spread of COVID-19.