Generational differences in loneliness and its psychological and sociodemographic predictors: an exploratory and confirmatory machine learning study.

ABSTRACT:

Background

Loneliness is a growing public health issue in the developed world. Among older adults, loneliness is a particular challenge, as the older segment of the population is growing and loneliness is comorbid with many mental as well as physical health issues. Comorbidity and common cause factors make identifying the antecedents of loneliness difficult, however, contemporary machine learning techniques are positioned to tackle this problem.

Methods

This study analyzed four cohorts of older individuals, split into two age groups - 45-69 and 70-79 - to examine which common psychological and sociodemographic are associated with loneliness at different ages. Gradient boosted modeling, a machine learning technique, and regression models were used to identify and replicate as

SUBMITTER: Altschul D 

PROVIDER: S-EPMC8161432 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature