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Natural Language Processing and Social Determinants of Health in Mental Health Research: AI-Assisted Scoping Review

Natural Language Processing and Social Determinants of Health in Mental Health Research: AI-Assisted Scoping Review

The x-axis represents the number of publications featuring a given social determinant (A) or demographic variable (B). SDOH: social determinants of health. Table 1 shows the most frequently extracted information from the text datasets. The scope of extracted data includes information related to sentiments and emotions, health conditions, health symptoms, personality traits, violence and bullying, suicide indicators, user engagement (likes, shares), survey data, and language features, to name a few.

Dmitry A Scherbakov, Nina C Hubig, Leslie A Lenert, Alexander V Alekseyenko, Jihad S Obeid

JMIR Ment Health 2025;12:e67192

Identifying Communities at Risk for COVID-19–Related Burden Across 500 US Cities and Within New York City: Unsupervised Learning of the Coprevalence of Health Indicators

Identifying Communities at Risk for COVID-19–Related Burden Across 500 US Cities and Within New York City: Unsupervised Learning of the Coprevalence of Health Indicators

Both individual-level factors (eg, diabetes, smoking, and asthma [3,8,10,11]) and geographical-level social determinant factors (eg, census tract–level population density and increased household occupancy) are strong risk factors for COVID-19 infection and risk [24]. Social determinants of health are defined as “conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks” [25].

Andrew Deonarine, Genevieve Lyons, Chirag Lakhani, Walter De Brouwer

JMIR Public Health Surveill 2021;7(8):e26604