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Factors related to social disconnectedness among older unpaid caregivers

Datos Bibliográficos

ID22091039
AutoresMoka Yoo‐jeong (0000-0001-7712-5889, Northeastern University, autor de correspondencia), Moka Yoo-Jeong, Jonathan Singer (0000-0003-2799-3930, Texas Tech University), Caroline D Bergeron (0000-0002-7238-4213, University of Ottawa), Jodi L Southerland (0000-0002-8092-7126, East Tennessee State University), Hye Won Chai (0000-0002-0180-6052, Clemson University), Andrew C Pickett (0000-0003-0454-0517, Indiana University Bloomington), Yuanjin Zhou (0000-0003-2492-346X, The University of Texas at Austin), Christian Vazquez (0000-0002-3792-9150, The University of Texas at Arlington), Juanita-Dawne Bacsu (0000-0002-2819-1617, Thompson Rivers University), Katherine Kwong (Connecticut College), Wonkyung Jung (0000-0002-2778-8710, Boston College), Tiffany Washington (0000-0002-5688-666X, Knoxville College), Tiffany R Washington, Marcia G Ory (0000-0001-8036-2383, Texas A&M Health Science Center), Matthew Lee Smith (0000-0002-8232-9285, Texas A&M Health Science Center)
Año2025
Volumen13
Páginas1589103-1589103
Fecha de publicación2025-04-29
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Public Health (JOURNAL)
Identificadores de la revistaISSN: 2296-2565 • E-ISSN: 2296-2565
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1589103
PMID40365433
OpenAlexW4409959675
IdiomaEN
Referencias citadas45

Background Older unpaid caregivers often face social isolation and loneliness, yet risk factors for social disconnection remain largely unexplored. As the demand for unpaid caregiving rises with an aging population, there is a need for targeted interventions to reduce social disconnectedness in this vulnerable group. This study aimed to identify determinants of social disconnectedness. Methods Data came from a sample of 701 unpaid caregivers aged 60 + who completed an internet-based survey assessing sociodemographics, health status, financial strain, social environment, and social disconnectedness. Four sequential regression models were used to identify the unique contribution of these factors related to social disconnectedness. Results The first model ( F = 3.94, p < 0.001, a R 2 = 0.030) showed that older age ( β = −0.15, p < 0.001), self-identifying as being Black ( β = −0.10, p = 0.008), and higher education ( β = −0.11, p = 0.041) were associated with lower social disconnectedness. Adding health factors in the second model ( F = 15.33, p < 0.001, a R 2 = 0.170) revealed that, in addition to age and education, chronic conditions ( β = 0.12, p = 0.001) and possible depression ( β = 0.35, p < 0.001) were associated with social disconnectedness. Including financial strain in the third model ( F = 15.52, p < 0.001, a R 2 = 0.212) showed that household income ( β = −0.10, p = 0.012) and financial stress ( β = 0.18, p < 0.001) were additionally associated with social disconnectedness. The final model ( F = 23.42, p < 0.001, a R 2 = 0.366) that included social environmental factors showed that age ( β = −0.07, p = 0.033), possible depression ( β = 0.22, p < 0.001), financial stress ( β = 0.16, p < 0.001), and levels of community belonging ( β = −0.20–0.58, p < 0.001) were significantly related to the risk of disconnectedness. Conclusion Findings highlight possible intervention targets that have the potential to reduce social disconnectedness among older unpaid caregivers. Particularly, addressing depressive symptoms, reducing financial stress, and enhancing community belonging are essential components to mitigate social disconnectedness risk in this population

Elder Abuse and Neglect · Health disparities and outcomes · Intergenerational Family Dynamics and Caregiving · Medicine · Psychology · Gerontology

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