Factors Related to Social Disconnectedness among Older Unpaid Caregivers

Moka Yoo-Jeong^1*Jonathan Singer²Caroline D. Bergeron³Jodi L. Southerland⁴Hye Won Chai⁵Andrew C. Pickett⁶Yuanjin Zhou⁷Christian E Vazquez⁸Juanita-Dawne Bacsu⁹Katherine Kwong¹⁰Wonkyung Jung¹¹Tiffany R Washington¹²Marcia G Ory¹³Matthew Lee Smith¹³

• ¹Northeastern University, Boston, United States
• ²Texas Tech University, Lubbock, Texas, United States
• ³University of Ottawa, Ottawa, Ontario, Canada
• ⁴East Tennessee State University, Johnson City, Tennessee, United States
• ⁵Clemson University, Clemson, South Carolina, United States
• ⁶Indiana University, Bloomington, Indiana, United States
• ⁷The University of Texas at Austin, Austin, Texas, United States
• ⁸University of Texas at Arlington, Arlington, Virginia, United States
• ⁹Thompson Rivers University, Kamloops, British Columbia, Canada
• ¹⁰Connecticut College, New London, Connecticut, United States
• ¹¹Boston College, Chestnut Hill, Massachusetts, United States
• ¹²The University of Tennessee, Knoxville, Knoxville, Tennessee, United States
• ¹³Texas A and M University, College Station, Texas, United States

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, aR2=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, aR2=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, aR2=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, aR2=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. Conclusions: 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.