Building machine learning prediction models for well-being using | ResearchBunny

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Abstract

This study uses longitudinal data from the Netherlands Twin Register (1991–2022) to build machine learning prediction models for adult well-being using exposome and genome data. The specific exposome (psychosocial factors) proved highly predictive (R² = 0.702), while the general exposome (objective environmental exposures) showed modest predictive power (R² = 0.047). Genetic data (polygenic scores) were not predictive. Optimism, personality, social support, and neighborhood housing characteristics were the most predictive factors.

Publisher

Nature Mental Health

Published On

Aug 14, 2024

Authors

Dirk H M Pelt, Philippe C Habets, Christiaan H Vinkers, Lannie Ligthart, Catharina E M van Beijsterveldt, René Pool, Meike Bartels

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