Researchers at the University of Pennsylvania recruited more than 800 people – half of them white, half of them Black, some reporting depression and some not – and employed artificial-intelligence models to examine the language they used in their Facebook posts. Words and expressions used on social media that had been established as predictive of depression only proved to be so for the white participants. The model was three times less likely to accurately predict depression among Black people.
“Our results raise concern that certain psychological processes thought to predict or maintain depression may be less relevant, or even irrelevant, to populations historically excluded from psychological research, including Black individuals,” the researchers wrote in a paper published [March 26] in the Proceedings of the National Academy of Sciences.
The results highlight the need for more awareness about how “race and ethnicity influence the relationship between depression and language expression,” the researchers wrote. The study also accentuates the need to increase representation of Black people and other underrepresented groups in medical research and to establish more accurate predictive models to address more diverse mental health needs, according to the study’s lead author, Sunny Rai, a postdoctoral researcher in Computer and Information Science at Penn.
