Objectives: This study explored the psychosocial risk profiles and various characteristics associated with profile membership among Korean older adults living alone.
Methods: Our analyses were based on a cross-sectional cohort of 1030 community-dwelling older adults (≥ 65 years) living alone in one Korean city. Latent profile analysis was used to identify psychosocial risk profiles across a wide range of psychosocial dimensions (depressive symptoms, suicidal ideation, cognitive dysfunction, loneliness, and perceived social support). We then explored the characteristics associated with distinct profiles by conducting bivariate and regression analyses.
Results: The three-profile was selected as the best solution: a group with high cognitive dysfunction, high loneliness, and low social support (profile 1), a group with low psychological risks and high social support (profile 2), and a group with high depression and high suicidal ideation (profile 3). Regression analyses showed that a lower frequency of interaction with neighbors or families, a greater frailty score, and lower quality of life were significantly associated with profile 1 or profile 3 than with profile 2 (p < .05). Further, being male and having a poorer nutritional status was more significantly related to profile 3 than profile 2 (p < .05).
Conclusions: Findings provide evidence for healthcare professionals when developing interventions to prevent and reduce these psychosocial risks for older individuals living alone. In particular, factors associated with profile membership identified in the study may facilitate more tailored interventions.
Keywords: Aged; Korea; Latent class analysis; Psychology; Social support.
Copyright © 2021. Published by Elsevier B.V.