%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 22
%N 6
%P e15099
%T Lifestyle Segmentation to Explain the Online Health Information–Seeking Behavior of Older Adults: Representative Telephone Survey
%A Weber,Winja
%A Reinhardt,Anne
%A Rossmann,Constanze
%+ University of Erfurt, Nordhaeuser Str 63, Erfurt, Germany, 49 361 737 4175, winja.weber@uni-erfurt.de
%K older adults
%K online health information seeking
%K lifestyle
%K segmentation
%K cluster analysis
%D 2020
%7 12.6.2020
%9 Original Paper
%J J Med Internet Res
%G English
%X Background: As 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. Objective: The 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. Methods: A 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. Results: The 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. Conclusions: Our 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. 
%M 32530433
%R 10.2196/15099
%U http://www.jmir.org/2020/6/e15099/
%U https://doi.org/10.2196/15099
%U http://www.ncbi.nlm.nih.gov/pubmed/32530433