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Background During a global pandemic, it is critical that the public is able to rapidly acquire new and accurate health information. The internet is a major source of health information. eHealth literacy is the ability of individuals to find, assess, and use health information available on the internet. Objective The goals of this study were to assess coronavirus-related eHealth literacy and examine the relationship between eHealth literacy and COVID-19−related knowledge, attitudes, and practices (KAPs). Methods We conducted a web-based survey of a representative sample of 1074 US adults. We adapted the 8-item eHealth Literacy Scale to develop the Coronavirus-Related eHealth Literacy Scale (CoV-eHEALS) to measure COVID-19−related knowledge, conspiracy beliefs, and adherence to protective behaviors (eg, wearing facial masks and social distancing). Our analyses identified sociodemographic associations with the participants’ CoV-eHEALS scores and an association between the CoV-eHEALS measure and COVID-19 KAPs. Results The internal consistency of the adapted CoV-eHEALS measure was high (Cronbach α=.92). The mean score for the CoV-eHEALS was 29.0 (SD 6.1). A total of 29% (306/1074) of the survey participants were classified as having low coronavirus-related eHealth literacy (CoV-eHEALS score <26). Independent associations were found between CoV-eHEALS scores and ethnicity (standardized β=–.083, P=.016 for Black participants) and education level (standardized β=–.151, P=.001 for participants with high-school education or lower). Controlling for demographic characteristics, CoV-eHEALS scores demonstrated positive independent associations with knowledge (standardized β=.168, P<.001) and adherence to protective behaviors (standardized β=.241, P<.001) and a negative association with conspiracy beliefs (standardized β=–.082, P=.009). Conclusions This study provides an estimate of coronavirus-related eHealth literacy among US adults. Our findings suggest that a substantial proportion of US adults have low coronavirus-related eHealth literacy and are thus at a greater risk of lower and less-protective COVID-19 KAPs. These findings highlight the need to assess and address eHealth literacy as part of COVID-19 control efforts. Potential strategies include improving the quality of health information about COVID-19 available on the internet, assisting or simplifying web-based search for information about COVID-19, and training to improve general or coronavirus-specific search skills.

In order to maximize online reading performance and comprehension, how should a designer choose typographical variables such as font size and font type? This paper presents an eye tracking study of how font size and font type affect online reading. In a between-subjects design, we collected data from 82 subjects reading stories formatted in a variety of point sizes, san serif, and serif fonts. Reading statistics such as reading speed were computed, and post-tests of comprehension were recorded. For smaller font sizes, fixation durations are significantly longer, resulting in slower reading-but not significantly slower. While there were no significant differences in serif vs. san serif fonts, serif reading was slightly faster. Significant eye tracking differences were found for demographic variables such as age group and whether English is the subject's first language.

Abstract. We present an eye tracking study to measure if and how including pictures -relevant or irrelevant to the text -affects online reading. In a between-subjects design, 82 subjects read a story on a computer screen. The text was accompanied by either: (a) pictures related to the text, (b) pictures unrelated to the text (advertisements), or (c) no pictures. Reading statistics such as reading speed and regressions were computed, as well as measures of picture gazes. When pictures related to the text were replaced with advertisements, we observed a number of significant differences, including speed, regressions, and re-reading.