Examining the Moderating Roles of Algorithm Literacy in eHealth Outcomes Across Age Groups

eHealth use increasingly occurs within algorithmically curated environments, yet it remains unclear whether algorithm literacy uniformly enhances eHealth benefits or whether these effects differ for older adults. Guided by the third-level digital divide framework and Structural Influence Model, this study examines whether three dimensions of algorithm literacy, namely algorithmic awareness, ethical awareness, and privacy concern, moderate the associations between eHealth use and perceived benefits, psychological distress, and health information fatigue. Using cross-sectional survey data from 1,308 Hong Kong residents, we examined moderation patterns between older adults (aged 60 and above; n = 554) and general adults (aged 20 to 59; n = 754). Results show that older adults reported significantly lower levels of all three dimensions than general adults, indicating an age-related inequality in algorithm literacy. Among older adults, higher ethical awareness and privacy concern strengthened the positive association between frequent eHealth use and perceived benefits but also amplified the association between frequent use and psychological distress. Higher algorithmic awareness strengthened the association between frequent eHealth use and health information fatigue. Among general adults, moderating effects were limited: ethical awareness attenuated the association between frequent eHealth use and psychological distress but modestly strengthened the association with health information fatigue. These findings suggest that algorithm literacy can amplify both the benefits and burdens of eHealth use, with burden-amplifying effects more pronounced among older adults. Accordingly, digital health equity strategies should move beyond promoting algorithm literacy alone and instead reduce the interpretive demands imposed by algorithmically curated eHealth environments.