ArticleBMC geriatrics2024
Exploration of subgroups and predictors of loneliness among older adults in rural China: A latent profile analysis.
Article in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Multidimensional stress among rural older adults in China: status, typology, and mental health associations.BMC geriatrics · 2026Article
- Loneliness Subtypes and Their Association With Prevalent and Incident Dementia.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2026Article
- Latent profiles of occupational stress and their association with premenstrual syndrome: a cross-sectional study of Chinese nurses.Frontiers in public health · 2026Article
- Nurses' work value patterns and their relationship with burnout: a cross-sectional study based on latent profile analysis.BMC nursing · 2025Article
- Multidimensional perspectives on nurse burnout in China: a cross-sectional study of subgroups and predictors.BMC nursing · 2024Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundLoneliness is a negative emotional state that can lead to physical and mental health problems. This study's objective was to acquire an in-depth understanding of the heterogeneity and the predictors of loneliness among older adults in rural China and provide valuable references for practical interventions.
methodsOlder rural adults in China (N = 680) were recruited between January and April 2023. Latent profile analysis (LPA) was employed to identify subgroups of loneliness among participants. Single-factor and multinomial logistic regression analyses were conducted to investigate predictors of loneliness.
resultsThe loneliness of rural older adults could be divided into three subgroups: low interaction loneliness group (55.0%), moderate emotional loneliness group (31.8%), and high loneliness group (13.2%). The subgroup predictors included age, gender, religious beliefs, marital status, living alone, number of chronic diseases, and smartphone use (P < 0.05).
conclusionThis study identified a classification pattern for loneliness among older adults in rural areas of China, revealed the characteristics of different demographic variables in loneliness categories, and highlighted the heterogeneity of loneliness in this population. It serves as a theoretical reference for formulating intervention plans aimed at addressing various loneliness categories for local rural older adults. CLINICAL
trial registrationChiCTR2300071591.
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