Validity Evidence Based on Relations to Other Variables of the eHealth Literacy Questionnaire (eHLQ): Bayesian Approach to Test for Known-Groups Validity

Abstract

Background As health resources and services are increasingly delivered through digital platforms, eHealth literacy is becoming a set of essential capabilities to improve consumer health in the digital era. To understand eHealth literacy needs, a meaningful measure is required. Strong initial evidence for the reliability and construct validity of inferences drawn from the eHealth Literacy Questionnaire (eHLQ) was obtained during its development in Denmark, but validity testing for varying purposes is an ongoing and cumulative process. Objective This study aims to examine validity evidence based on relations to other variables—using data collected with the known-groups approach—to further explore if the eHLQ is a robust tool to understand eHealth literacy needs in different contexts. A priori hypotheses are set for the expected score differences among age, sex, education, and information and communication technology (ICT) use for each of the 7 eHealth literacy constructs represented by the 7 eHLQ scales. Methods A Bayesian mediated multiple indicators multiple causes model approach was used to simultaneously identify group differences and test measurement invariance through differential item functioning across the groups, with ICT use as a mediator. A sample size of 500 participants was estimated. Data were collected at 3 diverse health sites in Australia. Results Responses from 525 participants were included for analysis. Being older was significantly related to lower scores in 4 eHLQ scales, with 3. Ability to actively engage with digital services having the strongest effect (total effect –0.37; P<.001), followed by 1. Using technology to process health information (total effect –0.32; P<.001), 5. Motivated to engage with digital services (total effect –0.21; P=.01), and 7. Digital services that suit individual needs (total effect –0.21; P=.02). However, the effects were only partially mediated by ICT use. Higher education was associated with higher scores in 1. Using technology to process health information (total effect 0.22; P=.01) and 3. Ability to actively engage with digital services (total effect 0.25; P<.001), with the effects mostly mediated by ICT use. Higher ICT use was related to higher scores in all scales except 2. Understanding health concepts and language and 4. Feel safe and in control. Either no or ignorable cases of differential item functioning were found across the 4 groups. Conclusions By using a Bayesian mediated multiple indicators multiple causes model, this study provides supportive validity evidence for the eHLQ based on relations to other variables as well as established evidence regarding internal structure related to measurement invariance across the groups for the 7 scales in the Australian community health context. This study also demonstrates that the eHLQ can be used to gain valuable insights into people’s eHealth literacy needs to help optimize access and use of digital health and promote health equity.