ArticleRevista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)2025
First-person pronouns as linguistic markers of depression among Brazilian youths.
Article in Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveMajor depressive disorder (MDD) is a leading cause of disability among youth, yet identifying this condition remains challenging. Naturalistic communication offers a promising approach to enhance depression detection. Increased use of first-person singular pronouns (e.g., ''I'') has been linked to MDD, but its applicability to younger, non-English-speaking populations remains unclear.
methodsThis study examined first-person pronoun use in Brazilian Portuguese-speaking adolescents with and without MDD and its relationship to self-reported and clinician-rated depressive symptoms. Fifty-two adolescents (13 with and 39 without MDD) from the Identifying Depression Early in Adolescence Risk Stratified Cohort (IDEA-RiSCo) sample completed remote data collection using a WhatsApp chatbot, responding to questions via audio recordings. Transcripts were analyzed using the Linguistic Inquiry and Word Count (LIWC).
resultsThe MDD group used significantly more I-pronouns than non-MDD subjects (9.15 vs. 8.02%, t = -2.302, p = 0.026). Self-reported depressive symptomatology correlated with I-pronoun use (rho = 0.366, p = 0.008), but did not reach statistical significance for clinician-rated symptoms (rho = 0.248, p = 0.076).
conclusionsThese findings support first-person singular pronouns as a potential linguistic marker of depression among Brazilian adolescents. This is the first study to replicate such results in a young, non-English-speaking sample using spoken speech, suggesting that integrating linguistic analysis with digital tools could enhance early detection efforts, particularly in resource-limited settings. Future research should explore use of I-pronouns alongside other linguistic and acoustic features to refine digital mental health screening approaches.
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