Older Adult Experience of Online Diagnosis: Results From a Scenario-Based Think-Aloud Protocol

Background Searching for online information to interpret symptoms is an increasingly prevalent activity among patients, even among older adults. As older adults typically have complex health care needs, their risk of misinterpreting symptoms via online self-diagnosis may be greater. However, limited research has been conducted with older adults in the areas of symptom interpretation and human-computer interaction. Objective The intent of the study was to describe the processes that a sample of older adults may use to diagnose symptoms online as well as the processes that predict accurate diagnosis. Methods We conducted a series of “think-aloud” protocols with 79 adults aged 50 years or older. Participants received one of two vignettes that depicted symptoms of illness. Participants talked out loud about their thoughts and actions while attempting to diagnose the symptoms with and without the help of common Internet tools (Google and WebMD’s Symptom Checker). Think-aloud content was categorized using an adapted Q-sort and general inductive approach. We then compared the think-aloud content of participants who were accurate in their diagnosis with those who were not. Results Nineteen descriptive codes were identified from the think-aloud content. The codes touched upon Web navigation, attempts to organize and evaluate online health information, and strategies to diagnose symptoms. Participants most frequently relied on a strategy where they reviewed and then rejected the online diagnoses if they contained additional symptoms than those that were depicted in the vignette. Finally, participants who were inaccurate in their diagnosis reported being confused by the diagnosis task, lacking confidence in their diagnosis, and using their past experiences with illness to guide diagnosis more frequently than those participants who accurately diagnosed the symptoms. Conclusions Older adult participants tended to rely on matching strategies to interpret symptoms, but many still utilized existing medical knowledge and previous illness experiences as a guide for diagnosis. Many participants also had difficulty navigating the Internet tools, which suggests an increased need for navigation aids in Web design. Furthermore, participants who were inaccurate in their diagnosis had more difficulty with the Internet tools and confusion with the task than those who were accurate. Future work in this area may want to utilize additional study design such as eye-tracking to further understand the coordination between Web navigation, online symptom information processing, and diagnostic strategies.