BACKGROUND
A key challenge for health systems harnessing digital tools and services is that of digital inclusion. Typically, digital inequalities are conceptualized in relation to unequal access or usage. However, these differences do not fully explain differences in health behavior as a result of health-related internet use.
OBJECTIVE
Our objective was to derive a new typology of health internet users based on their antecedent motivations and enablers, to explain how individuals’ different orientations influence their health behavior.
METHODS
We used a mixed-methods design using (1) qualitative data from 43 semistructured interviews about individuals’ general and health-related internet use, and how this influenced their health perception and their help-seeking decisions, and (2) quantitative data from the Oxford Internet Surveys (OxIS), a household survey of 2150 adults in England about their internet use and other characteristics. We used the interview data to identify constructs that described motivations and enablers affecting how internet use shaped respondents’ health perception and health service use. We then used these constructs to identify variables in OxIS, which provided a quantitative measure of these constructs. We then undertook a hierarchical cluster analysis of these constructs, using the numerical variables, to derive a proposed typology of health information seekers.
RESULTS
Both the qualitative findings and the subsequent cluster analysis suggested the existence of 6 types of individuals, categorized as learners, pragmatists, skeptics, worriers, delegators, and adigitals. Learners had a strong desire to understand health better. They used the internet to make decisions about whether they needed to see a professional and to learn about their and others’ health. Pragmatists primarily used the internet to decide whether seeing a doctor was worthwhile. Skeptics were skeptical of physicians and the medical system and valued the internet for solving health problems that doctors may not be able to deal with. Worriers found it difficult to interpret health information online, described health information seeking online as frightening, and reported a critical attitude toward online health information despite seeking it frequently. Delegators comprised nonusers and users valuing the internet as an information source, but not necessarily wanting or being able to use the internet themselves. Adigitals comprised many nonusers, but also users, who did not see the internet as a useful information tool and presented strong views on its low suitability for health care.
CONCLUSIONS
This research supports a shift in the understanding of the digital divide in health, away from only access and usage issues, toward also conceptualizing an outcomes divide, whereby different types of health behavior result from the differing orientations of internet users accessing online health information. This new typology can be used to inform digital inclusion policies in health systems.
Advancing Health-Related Cluster Analysis Methodology: Quantification of Pairwise Activity Cluster Similarities
