Internet Self-Diagnosis: Mapping the Information Seeking Processes

from THCB at on December 29, 2016 at 12:53PM


We’ve all been there. It’s early morning, and you wake up feeling groggier than usual, sensing the onset of a sore throat and a runny nose. Before crawling out of bed, you grab your smart phone and, naturally, Google “groggy sore throat runny nose symptoms.” Hundreds of results pop up, suggesting various illnesses and links to seemingly promising remedies. How could anyone filter through page after page of links, ranging from everyday allergies to deadly diseases?

Many of our health choices are made outside the doctor’s office. The simple decision of whether symptoms are severe enough to warrant visiting a healthcare provider is one of them. For some patients, that decision is easy, because regardless of the severity of symptoms, from a simple cough to leg pain, getting in to see a healthcare provider is easy. Unfortunately, many people still struggle to find a healthcare provider, get an appointment, and/or obtain transportation. These individuals are left to turn to other health information resources, such as the Internet, to determine whether their symptoms are severe enough to navigate these barriers.

The “digital divide” has become a catchphrase for how differences in educational, social, and economic backgrounds can affect access to web-based tools and services, as well as the general ability to use the Internet.

That divide has serious healthcare consequences: Though the web is not intended to replace traditional medical care, it may offer one of the few available sources of information for those with limited access to health services. While patients who regularly visit a provider are privy to the diagnostic processes of medical professionals, web-based tools may be critical in weighing the severity of symptoms for those with fewer resources and less access. 

The way the Internet is used to investigate and self-diagnose health concerns led my colleagues and me to look deeper into how individuals navigate web-based health information – and how individual experiences and abilities may influence this process.

Against this backdrop, my colleagues and I sought to explore how the digital divide may influence the way individuals seek health information and arrive at health decisions. Our study, “Characterizing internet health information seeking strategies by socioeconomic status: a mixed methods approach,” focused directly on how individuals of different educational, economic, and social backgrounds navigate web-based health information.

To begin, we created two clinical situations, each involving an acute illness of different clinical severity. We then developed two ways for measuring individuals’ information-seeking behavior – one focusing on decision-making processes, the other on the depth of information searched.

Drawing on academic literature related to the psychology of judgment and decision-making, we identified and classified two approaches for the decision-making processes used by individuals when searching the Internet for health information. System 1 processing involves the use of biases and heuristics (e.g., a “rule of thumb”), while System 2 processing is characterized by a careful evaluation of the information presented. System 2 processing, the systematic approach, most resembles the diagnostic process taught to medical professionals as well as information-processing strategies found in other studies to be associated with higher-quality decisions. Participants who had less education and were more reliant on social services, lower socioeconomic status (lower-SES), were more likely to engage in less complex and more intuitive searches.

Our exploration of the depth of searching by individuals making health decisions uncovered real differences in complexity. Those who had higher education and less need for support from social services, higher socioeconomic status (higher-SES), engaged in a more complex and expanded search process; they widened their searches to increase their information input. As a result, higher-SES individuals were exposed to additional information as well as a larger number of options for their decision-making.

While there were significant differences in the complexity of searches, we found that there were no significant differences between lower-SES and higher-SES individuals in whether the Internet search influenced an accurate guess at the cause of the symptoms. For this scenario, the complexity of the search did not result in better overall guesses at the symptoms. This may have to do with previous experiences with the symptoms and the hypothetical nature of the scenario. Overall, participants used three heuristics – the influence of prior clinical or symptom-related experience, how credible the source of information is to the participant, and whether the information found is consistent with other information they encountered during their search – to “fill in” information and guide their process of seeking health information.

We are concerned by the reliance on heuristics and the narrowing of searches by individuals of increased vulnerability, because the way they search for information reduces their exposure to information and results in fewer options for decision-making. Our next step will be to seek to determine what kinds of tools will facilitate more meaningful interaction and engagement for everyone. One big hope involves employing Web 2.0 gamification techniques to guide decision-making and to keep information seekers readily engaged in the decision-making process.