Individuals facing mental health challenges often find themselves engaging with negative online content, which in turn exacerbates their symptoms. This troubling cycle is revealed in a series of studies conducted by MIT researchers.
In response to these findings, the research team has developed a web plug-in tool designed to empower users to make healthier content choices for their mental well-being.
The insights from this research were published in an open-access paper by Tali Sharot, an adjunct professor of cognitive neuroscience at MIT and a professor at University College London, alongside Christopher A. Kelly, a former visiting PhD student who now serves as a postdoctoral researcher at Stanford University’s Institute for Human-Centered AI. Their findings appeared in the journal Nature Human Behavior on November 21.
“Our research indicates a causal, bidirectional relationship between mental health and online activities. Those already experiencing mental health symptoms tend to seek out negative or fear-inducing information online, which subsequently worsens their condition. This creates a feedback loop,” Sharot explains.
The studies analyzed the web browsing behavior of over 1,000 participants, utilizing natural language processing to evaluate the emotional tone of the content they accessed. Participants completed mental health questionnaires and reported their mood before and after browsing sessions. The findings revealed that better moods followed visits to less-negative websites, while participants with poorer pre-browsing moods gravitated towards more-negative content.
In an additional experiment, participants were presented with information from two randomly selected webpages—either from six negative or six neutral sites. Following their reading sessions, mood levels were assessed. It was determined that those who viewed negative webpages reported lower moods compared to those who accessed neutral pages, and they proceeded to seek out even more negative content in a subsequent 10-minute browsing session.
“Our results contribute to the ongoing discourse around the connection between mental health and online behavior,” the authors noted. “Previous research has largely focused on the quantity of internet use, like screen time or social media frequency, resulting in contradictory findings. Our study shifts the focus to the type of content consumed and its emotional impact, affirming its causal relationship with mental health and mood.”
To evaluate whether intervening could shift browsing habits and enhance mood, the researchers presented participants with search results that included labels indicating the potential emotional impact of each result—from “feel better” to “feel worse.” Those who received these labels tended to avoid negative content and select positive alternatives. A follow-up study confirmed that exposure to more uplifting content significantly improved participants’ moods.
Taking these findings further, Sharot and Kelly developed a downloadable plug-in tool called “Digital Diet,” which evaluates Google search results based on three criteria: emotion (average sentiment of the content), knowledge (helpfulness of the information), and actionability (practical utility of the content). Jonatan Fontanez, an MIT electrical engineering and computer science student who previously researched in Sharot’s lab, also played a crucial role in the tool’s development. This tool was publicly launched alongside the publication of the findings in Nature Human Behavior.
“Those with poorer mental health often seek out negative and fear-driven content, which exacerbates their symptoms, perpetuating a negative cycle,” Kelly explains. “We hope this tool will help individuals regain control over their online experiences and disrupt these harmful patterns.”
Photo credit & article inspired by: Massachusetts Institute of Technology
