Study finds link between poor mental health and viewing negative online content

People with poor mental health are more likely to view negative content online, which can make their symptoms worse, a study led by UCL researchers has found.

The relationship between mental health and web browsing is causal and bidirectional, according to a Wellcome-funded study. nature human behavior.

Researchers have developed a plugin tool that adds “content labels” to web pages. Similar to nutrition labels on food, they are designed to help users make healthier, more informed decisions about the content they consume. These labels emphasize the practicality and usefulness of a web page's content, as well as its emotional impact.

Co-lead author Professor Tali Sharot (UCL Psychology and Language Sciences, Max Planck UCL Center for Computation) psychiatry “Our results show that viewing content with a negative valence not only reflects a person's mood, but can actively worsen their mood. This can lead to poor mental health. It creates a feedback loop that can perpetuate the problem over time.”

More than 1,000 study participants answered questions about their mental health and shared their web browsing history with researchers. The researchers used natural language processing techniques to analyze the emotional tone of the web pages visited by participants. They found that participants with worse mood and mental health symptoms tended to view more negative content online, and participants who viewed more negative content felt worse after viewing it.

In an additional study, researchers manipulated the websites people visited, exposing some participants to negative content and others to neutral content. They found that people who were exposed to negative websites reported feeling worse afterwards, proving the causal effect of viewing negative content on mood. These participants were then asked to freely browse the Internet, and participants who had previously visited negative websites and felt bad as a result viewed more negative content. I chose that. This finding emphasizes that the relationship is bidirectional. In other words, negative content affects your mood, and when your mood worsens, you're more likely to consume more negative content.

Co-lead author and PhD student Christopher Kelly (UCL Psychology and Language Sciences, Max Planck UCL Center for Computational Psychiatry and Aging Research, Massachusetts Institute of Technology) said: “These results demonstrate the relationship between mental health and mental health. “We will contribute to the ongoing debate on the subject.” and online behavior.

“Most studies addressing this relationship have focused on the amount of social media usage, such as time and frequency, resulting in mixed conclusions. Here, we instead focus on the amount of content viewed. We focused on the type and found that emotional tone is causally and bidirectionally related to mental health and mood. ”

The researchers conducted further studies to see if interventions could be used to change web browsing choices and improve mood. They added content labels to Google search results and asked participants whether each search result was likely to improve, worsen, or have no effect on their mood. I informed you. They found that participants were more likely to choose sites with positive labels that seemed to improve their mood, and when asked about their mood afterwards, those who had viewed positive websites were more likely than other participants to I was in a good mood.

In response, researchers developed a free browser plugin that adds labels to Google search results. This provides three different ratings of how useful, informative, and how a website's content affects your mood.

We're used to seeing content labels on our groceries, which provide nutritional information such as sugar, calories, protein, and vitamins to help us make informed decisions about what we eat. Masu. A similar approach can be applied to the content consumed online, helping people make healthier choices online. ”

Professor Tali Shalot, UCL Psychology and Language Sciences, Max Planck UCL Center for Computational Psychiatry and Aging Research, and Massachusetts Institute of Technology