Prediction of Social Engagement in Long-Term Care Homes by Sex: A Population-Based Analysis Using Machine Learning.

The objective of this study was to use population-based clinical assessment data to build and evaluate machine-learning models for predicting social engagement among female and male residents of long-term care (LTC) homes. Routine clinical assessments from 203,970 unique residents in 647 LTC homes i...

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Bibliographic Details
Published in:	Journal of Applied Gerontology Vol. 44; no. 6; pp. 902 - 916
Main Authors:	Abedi, Ali, Khan, Shehroz S., Iaboni, Andrea, Bronskill, Susan E., Bethell, Jennifer
Format:	Article
Published:	Sage Publications Inc. Jun2025
Subjects:	Ontario Cross-sectional method Health status indicators Sex distribution Nursing care facilities Social participation Psychosocial factors Cognition Old age Nursing home residents Random forest algorithms Secondary analysis Prediction models T-test (Statistics) Research funding Functional status Descriptive statistics Machine learning Physical activity
Online Access:	View this record in EBSCOhost

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