Mental Health Disorder Detection Beyond Social Media: A Systematic Review of Available Datasets

Detecting mental health disorders in a timely manner is an important societal challenge. NLP and machine learning (ML) methods used to assist with detection rely on data collected primarily from social media. However, such datasets often have sampling biases and inherent ethical and privacy issues. One avenue to overcome these limitations is non-social media data. We present the first comprehensive review of non-social media, free-text datasets for mental health research. We use the PRISMA metho

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ethics.ai (3 July 2026), “Mental Health Disorder Detection Beyond Social Media: A Systematic Review of Available Datasets,” evidence record 3016, https://ethics.ai/record/3016 (originally published by arXiv cs.CL (ethics-relevant NLP)).

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