Journal of Medical Internet Research (Jun 2020)

Lifestyle Segmentation to Explain the Online Health Information–Seeking Behavior of Older Adults: Representative Telephone Survey

  • Weber, Winja,
  • Reinhardt, Anne,
  • Rossmann, Constanze

DOI
https://doi.org/10.2196/15099
Journal volume & issue
Vol. 22, no. 6
p. e15099

Abstract

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BackgroundAs a result of demographic changes, the number of people aged 60 years and older has been increasing steadily. Therefore, older adults have become more important as a target group for health communication efforts. Various studies show that online health information sources have gained importance among younger adults, but we know little about the health-related internet use of senior citizens in general and in particular about the variables explaining their online health-related information–seeking behavior. Media use studies indicate that in addition to sociodemographic variables, lifestyle factors might play a role in this context. ObjectiveThe aim of this study was to examine older people’s health-related internet use. Our study focused on the explanatory potential of lifestyle types over and above sociodemographic variables to predict older adults’ internet use for health information. MethodsA telephone survey was conducted with a random sample of German adults aged 60 years and older (n=701) that was quota-allocated by gender, age, educational status, and degree of urbanity of their place of residence. ResultsThe results revealed that participants used the internet infrequently (mean 1.82 [SD 1.07]), and medical personnel (mean 2.89 [SD 1.11]), family and friends (mean 2.86 [SD 1.21]), and health brochures (mean 2.85 [SD 1.21]) were their main sources of health information. A hierarchical cluster analysis based on values, interests, and leisure time activities revealed three different lifestyle types for adults aged over 60 years: the Sociable Adventurer, the Average Family Person, and the Uninterested Inactive. After adding these types as second-step predictors in a hierarchical regression model with sociodemographic variables (step 1), the explained variance increased significantly (R2=.02, P=.001), indicating that the Average Family Person and the Sociable Adventurer use the internet more often for health information than the Uninterested Inactive, over and above their sociodemographic attributes. ConclusionsOur findings indicate that the internet still plays only a minor role in the health information–seeking behavior of older German adults. Nevertheless, there are subgroups including younger, more active, down-to-earth and family-oriented males that may be reached with online health information. Our findings suggest that lifestyle types should be taken into account when predicting health-related internet use behavior.