Modeling types of informal care dyads by gender, primary condition, and relative age

Background: While women remain the majority of caregivers, gender parity is reported among Millennials, people of color, and LGBTQ caregivers. Such dynamics of care dyads are rarely explored in relationship with caregiver selection, social support, or care outcomes, and without standardized measures we are uncertain whether this trend is associated with youth, demographic changes, or a societal shift. Methods: Utilizing the Caregiving in the US 2015 data set, this exploratory, quantitative study examines relationships between gender, primary condition, and two social designations around age (kinship generations and birth cohorts) to develop a preliminary categorization of informal caregivers in the United States by reviewing descriptives and correlations, then testing with multivariate regression. Results: A model combining Millennial caregivers, same-generation dyads, and two primary conditions (mental illness and stroke) successfully predicts variance as to whether a dyad will comprise one woman caring for another woman, the most common dyad. Conclusions: Findings demonstrate the interconnectedness of caregiving generational models, suggesting that categorizing dyads from such variables is viable. This study deepens inquiry into intergenerational caregiving and makes a case for generationality and caregiving to be studied together.