Predicting Cognitive Functioning in Later Life through Machine Learning: Implications for Equity Research

Principal Investigator: Dr. Ernest Gonzales, Associate Professor and MSW Program Director, NYU Silver School of Social Work

Collaborators: Dr. Yi Wang, Dr. Forrest Bao, Cliff Whetung, and Natalie Green

Dates of award: 3/23/2022 – 2/28/2023

Amount of award: $10,000. Dean’s Research Fund and C+M Silver Center

Study description: 

Cognitive impairment is a worldwide epidemic and its effects are borne disproportionately by minoritized groups in the United States. Yet, nearly a third of all dementia cases can be prevented and equity is within reach. Longitudinal and experimental studies have identified important predictors to bolster cognitive functioning and brain structure. Machine learning is a novel statistical method that has rarely been utilized with predicting cognitive functioning in later life. While this method holds tremendous promise to interrogate and confirm existing theory, there are also significant ethical and methodological concerns that arise within the context of structural racism. Utilizing 14 years of data from a large representative sample of 15,385 older adult respondents to the Health and Retirement Study (2006-2020), and guided by minority stress theory, this study will compare and contrast traditional statistical approaches with that of machine learning to examine risk and protective factors to cognitive health. The findings from this study will inform methodological innovations to better understand cognitive impairment and socio-environmental factors, and will contribute to the development of theory and knowledge to inform health care policy and practices.

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