Label, codes, and sample tweets by label type.

Mental health literacy has largely been studied via vignettes and surveys. Capturing the reality of the mental health literacy dimensions in a natural setting is an important step for moving towards a more actionable phase for mental health literacy. This study aims to identify the frequency patterns of the four mental health literacy dimensions reflected in the mental health-related tweets specific to information technology professionals. 15,782 tweets from October 2018 to October 2022 were collected from information technology-specific accounts. Content analysis, specifically a multi-class text classification approach, was used to analyze and interpret the tweets and categorize them into themes based on the mental health literacy construct. Tweets on “Knowledge and beliefs about risk factors and causes, self-treatments/interventions, and professional help available” were the most common (n = 6,179), and tweets on “ability to recognize specific disorders” (n = 196) were the least common. The ease of sharing content on X (formerly Twitter) could be leveraged to increase mental health awareness via targeted educational material on how to recognize specific disorders, seek help, and therefore improve mental health. Integrating mental health literacy information with the content being shared by well-established organizations in the information technology sector could help to enhance mental health literacy among information technology professionals.