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Low eHealth literacy

Low eHealth literacy is defined as lacking the ability to seek, find and understand health information from electronic sources and apply the gained knowledge to address or solve a health problem. This lack of understanding essential health care information can lead to difficulties in making informed decisions about health.

Therefor addressing low eHealth literacy requires clear and effective communication, as well as the development of health education materials that are fitting and effective for people with low health literacy . The amount of literature on the subject of (low) eHealth literacy shows that the topic is an acute and urgent one and shows e.g. that issues regarding inequitable access, usage or skills relating to ICT (also known as the digital divide) can be strongly affected by sociodemographic factors associated with health disparities, such as age, income, education, and ethnicity. Especially socially disadvantaged groups, such as people of older age, with less education, and lower income are at a higher risk of becoming digitally marginalized, which then could lead to a potential widening of health disparities. The impact of low eHealth literacy on health disparities can not be denied and limited health literacy has already been stated as a public health problem by many countries. With eHealth having the capacity to improve health outcomes, its systems need to match the (potentially low) eHealth literacy needs of users.

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Social Network Analysis

To find out how individual topics and keywords regarding low eHealth literacy are connected with each other, if patterns emerge, and where there are still blind spots in terms of research, we performed a social network analysis (SNA). This interdisciplinary approach is generally defined as mapping and measuring the relationships and flows between actors in a network. Pivotal points of the analysis (so called ‘nodes’) were the keywords eHealth, eHealth literacy, health literacy, age and older adults. This also made four thematic clusters visible.

The first cluster revolves around the technical health sector with keywords like consumer health, digital diversity, digital health, app, user experience and health services.

Cluster two we called sociodemographic and socioeconomic data, because it revolves around topics such as disability, ethnicity, diversity and gender. Another cluster is the education sector, as a lot of publications thematize (learning) behavior, (adult) education, lifelong learning, training concepts, eLearning and social support.

When talking about the specific target groups, frequent keywords were age, adults, (college) students, adolescence and older adults. Missing connections between keywords (of different clusters) allow conclusions to be drawn about (potential) research gaps. A lot of potential therefore lies especially in the technical health sector with keywords such as health services, health systems, consumer health or digital diversity having few connections to others and standing relatively alone.

What could be done with this information is to recognize needs and gaps, bridge various clusters and look into a potential expansion of e.g. specially targeted health marketing and health communication towards people with low eHealth literacy. Efforts should also be addressing structural characteristics that create and sustain conditions of low eHealth literacy and could integrate perspectives such as community mobilizing and organizing, as well as stakeholder network building.

References on eHealth literacy