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.

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Background A central component of the public health strategy to control the COVID-19 pandemic involves encouraging mask wearing and social distancing to protect individuals from acquiring and transmitting the virus. Objective This study aims to understand the psychological factors that drive adoption or rejection of these protective behaviors, which can inform public health interventions to control the pandemic. Methods We conducted an online survey of a representative sample of 1074 US adults and assessed three novel potential predictors of COVID-19 behaviors: trait reactance, COVID-19 conspiracy beliefs, and COVID-19 apocalypse beliefs. Key outcomes (dependent variables) included an index of COVID-19 protective behaviors, the number of trips taken from the home, and COVID-19 knowledge. Results In bivariate analyses, all three predictors were significantly correlated in the hypothesized direction with the three COVID-19 outcomes. Specifically, each predictor was negatively (P<.01) correlated with the COVID-19 protective behaviors index and COVID-19 knowledge score, and positively correlated with trips taken from home per week (more of which was considered higher risk). COVID-19 protective behaviors and COVID-19 knowledge were significantly lower in the top median compared to the bottom median for all three predictors. In general, these findings remained significant after adjusting for all novel predictors plus age, gender, income, education, race, political party, and religiosity. Self-identified Republicans (vs other political affiliations) reported the highest values for each of the novel predictors. Conclusions This study can inform the development of health communication interventions to encourage the adoption of COVID-19 protective behaviors. Interestingly, we found that higher scores of all three novel predictors were associated with lower COVID-19 knowledge, suggesting that lack of an accurate understanding of the virus may be driving some of these attitudes; although, it is also possible that these attributes may interfere with one’s willingness or ability to seek and absorb accurate health information. These individuals may be particularly immune to accepting new information and yielding their beliefs. Health communication professionals may apply lessons learned from countering similar beliefs around climate change and vaccine hesitancy. Messages designed for individuals prone to reactance may be more effective if they minimize controlling language and emphasize the individual’s independence in adopting these behavioral recommendations. Messaging for those who possess conspiracy beliefs should similarly not assume that providing evidence contrary to these beliefs will alone alter behavior. Other communication techniques such as rolling with resistance, a strategy used in motivational interviewing, may be helpful. Messaging for those with apocalyptic beliefs may require using religious leaders as the message source and using scripture that would support the adoption of COVID-19 protection behaviors.

Background Vaccination against COVID-19 is an important public health strategy to address the ongoing pandemic. Examination of online search behavior related to COVID-19 vaccines can provide insights into the public's awareness, concerns, and interest regarding COVID-19 vaccination. Objective The aim of this study is to describe online search behavior related to COVID-19 vaccines during the start of public vaccination efforts in the United States. Methods We examined Google Trends data from January 1, 2021, through March 16, 2021, to determine the relative search volume for vaccine-related searches on the internet. We also examined search query log data for COVID-19 vaccine-related searches and identified 5 categories of searches: (1) general or other information, (2) vaccine availability, (3) vaccine manufacturer, (4) vaccine side-effects and safety, and (5) vaccine myths and conspiracy beliefs. In this paper, we report on the proportion and trends for these different categories of vaccine-related searches. Results In the first quarter of 2021, the proportion of all web-based search queries related to COVID-19 vaccines increased from approximately 10% to nearly 50% of all COVID-19–related queries ( P <.001). A majority of COVID-19 vaccine queries addressed vaccine availability, and there was a particularly notable increase in the proportion of queries that included the name of a specific pharmacy (from 6% to 27%; P =.01). Queries related to vaccine safety and side-effects (<5% of total queries) or specific vaccine-related myths (<1% of total queries) were uncommon, and the relative frequency of both types of searches decreased during the study period. Conclusions This study demonstrates an increase in online search behavior related to COVID-19 vaccination in early 2021 along with an increase in the proportion of searches related to vaccine availability at pharmacies. These findings are consistent with an increase in public interest and intention to get vaccinated during the initial phase of public COVID-19 vaccination efforts.

PurposeThe purpose of this paper is to discuss how learning styles and theories are currently used within personalised adaptable e‐learning adaptive systems. This paper then aims to describe the e‐learning platform iLearn and how this platform is designed to incorporate learning styles as part of the personalisation offered by the system.Design/methodology/approachThe paper discusses how learning styles and theories are currently being used within the area of adaptive e‐learning and describes current research within this area. This paper then gives an overview of the iLearn project and describes how iLearn is using the VARK learning style to enhance the platform's personalisation and adaptability for the learner. This research also describes the system's design and how the learning style is incorporated into the system design and semantic framework within the learner's profile.FindingsThe findings describe how the final implemented iLearn platform intends to address the issues found with the limited personalisation within common learning management systems and intends to provide the learner with a personalised learning experience.Originality/valueAdaptability and personalisation are large research areas, however, many limitations have been found during the current research. This research project, therefore adds value to this by proposing a system which will address the current personalisation limitations.