The past year has starkly illustrated how pervasive and deep-rooted the disinformation problem is in American society. We learned, for example, of the shocking revelations that the information associated with 87 million Facebook users had been illegally accessed by Cambridge Analytica. And we have been sequentially disheartened by news of data breach after data breach, each of which has discouraged any faith we might have had that Silicon Valley can effectively regulate itself to fight digital disinformation.

Centrally responsible for the stubbornness of the disinformation problem is the business model that sits at the heart of the internet itself—a business model that is premised on (1) the creation of borderline-addictive web-based services that enjoy a network effect; (2) the unchecked collection of personal data through those services to create behavioral profiles; and (3) the development and implementation of opaque algorithms that curate content in our social feeds and target ads at us.

These practices are as remarkably simple as they are exploitative of our individual autonomy, and they align well with the phenomenon of motivated cognition—the idea that the way in which individuals perceive, interact and operate in their environment is biased towards achieving an outcome most favorable to them. This phenomenon is manifested across a variety of societal contexts, including inflated self-appraisals for positive personality traits and the tendency to consume and endorse new information consistent with one’s prior belief system.

Within the digital realm, this disinformation problem is caused by what could be considered a newer form of motivated cognition: the social media filter bubble. Social media platforms are built to promote the content that we are likeliest to engage with by collecting data about us, create ever more precise advertising profiles. As motivated cognition takes hold of us online, we are increasingly pushed into filter bubbles as a given platform recognizes what kind of person we are—whether NFL watchers or even social hermits.

Algorithm designers want to keep us on the platforms for as long as possible, and they know that to do that they have to show us the content we are likeliest to agree with. Understanding the factors that enable these bubbles to thrive is key to dampening its role in curtailing engagement between individuals or groups holding opposing views.

One potential factor to consider is the reported feelings of loneliness—the perceived mismatch between one’s desired depth of social connectedness and what actually experience—found across all age groups. And while younger individuals may experience feelings of loneliness more than older people, there is a compelling demographic and emerging empirical case to focus on the older population segment. Demographically, with projections of more than 2 billion individuals age 60 and over in 2050 and recent polling data reporting a surge in the percentage of older adults reporting use of social media platforms, it is essential we develop a better sense of how older adults engage with these platforms and how factors affecting this group (i.e. loneliness) may have on their online behavior.

In a nationally representative survey, 36 percent of older adults aged 60-69 and 24 percent aged 70 and over in the survey were found to be lonely on a widely used loneliness index. This is especially alarming when considering the harmful health consequences loneliness has on physical and mental health, including its impacts on cognitive functions. In a well cited review, the authors show that that lonelier individuals exhibit declines in their ability to self-regulate; a heightened awareness of social threats in their environment; a greater attention towards negative social stimuli; and a reappraisal of negative interactions in the service of preserving one’s self esteem.

This constellation of behaviors, which broadly seeks to avoid conflict and minimize disappointment, may make these individuals prone to gravitating towards sources of information that mirror their own worldview thereby maintaining a sense of self. Consequently, they are susceptible to the outcomes of filter bubbles which promote greater in-group engagement.

With recent evidence that older adults are much more likely to disseminate fake news compared with their younger counterparts, coupled with the projected growth for this population segment in the decades to come, it is crucial to advance our understanding of the factors affecting the ways in which older adults engage with these platforms and how-in turn these platforms are affecting how they function in society.