ArticlePLOS digital health2025
Exploring mental health literacy among information technology (IT) professionals: Twitter content analysis.
Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Occupational burnout in information technology workers.Frontiers in public health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.