ArticleJMIR infodemiology2026
Characterizing Family Abuse in Suicidal Ideation Posts on Reddit: Large Language Model-Assisted Content Analysis.
Article in JMIR infodemiology, 2026. 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
backgroundSuicidal ideation is a significant global public health concern, with family abuse recognized as a key risk factor. Although clinical studies have examined the link between family abuse and mental health, its representation in social media discussions-particularly in relation to suicidal ideation-remains largely unexplored.
objectiveThis study aimed to examine how family abuse manifests in suicidal ideation narratives on social media, focusing on the demographic characteristics of individuals reporting abuse, the types of abuse described, and relationships to perpetrators.
methodsWe analyzed 27,434 posts from the Reddit SuicideWatch forum to identify posts in which suicidal ideation and family abuse co-occurred. Using a combination of manual review, large language model-assisted keyword expansion, natural language processing-based information extraction, and human validation, we examined self-disclosed age and gender among Reddit users who reported family abuse in suicidal ideation posts, along with abuse types and relationships to perpetrators.
resultsAmong posts with self-reported age information, individuals aged 18 to 24 years accounted for the largest proportion (144/313, 46.0%). Among posts with self-reported gender information, men represented 57.3% (86/150). Physical abuse was the most frequently reported form of family abuse (683/975, 70.1%; 95% CI 67.18%-72.93%), followed by emotional or psychological abuse (350/975, 35.9%; 95% CI 32.89%-38.91%) and sexual abuse (296/975, 30.4%; 95% CI 27.47%-33.25%). The parent category was the most frequently identified perpetrator category (435/975, 44.6%; 95% CI: 41.52%-47.75%).
conclusionsThis study enhances our understanding of how family abuse appears in social media posts involving suicidal ideation. The findings demonstrate the potential of computational social media analysis to support descriptive, hypothesis-generating research and inform the design of online support resources for family abuse-related suicidal distress.
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