Generational differences in loneliness and its psychological and sociodemographic predictors: an exploratory and confirmatory machine learning study.
Psychol Med
; 51(6): 991-1000, 2021 04.
Article
em En
| MEDLINE
| ID: mdl-32146913
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 associations with loneliness.RESULTS:
In all cohorts, higher emotional stability was associated with lower loneliness. In the older group, social circumstances such as living alone were also associated with higher loneliness. In the younger group, extraversion's association with lower loneliness was the only other confirmed relationship.CONCLUSIONS:
Different individual and social factors might underlie loneliness differences in distinct age groups. Machine learning methods have the potential to unveil novel associations between psychological and social variables, particularly interactions, and mental health outcomes.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Contexto em Saúde:
1_ASSA2030
Problema de saúde:
1_desigualdade_iniquidade
Assunto principal:
Casamento
/
Solidão
Tipo de estudo:
Etiology_studies
/
Incidence_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Aspecto:
Equity_inequality
Limite:
Aged
/
Female
/
Humans
/
Male
/
Middle aged
País/Região como assunto:
Europa
Idioma:
En
Revista:
Psychol Med
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Reino Unido