Dyadic Associations Between Age Stereotypes and Health in Older Couples Coping With Pain
Year: 2018
Type: conference-abstract
Abstract: Negative age stereotypes, or negative beliefs about older people, can lead to adverse health outcomes for individuals. However, little is known about dyadic associations between age stereotypes and health in older couples. We hypothesized that psychological and relational well-being would be negatively associated with an individual’s own and partner’s negative age stereotypes. To test our hypothesis, we assessed depressive symptoms, marital satisfaction, and potential covariates (demographics, comorbidity, pain) in 77 married couples aged 60 years and over with a musculoskeletal condition. Moderating effects of gender caregiver role were examined. Results showed caregivers’ age stereotypes were not significantly different from care-recipients’. Each individual’s age stereotypes were not associated with their own depressive symptoms or marital satisfaction. Gender did not moderate the within-individual and cross-partner associations between age stereotypes and health. However, caregiver role significantly moderated the cross-partner association between age stereotypes and marital satisfaction among caregivers [B = 4.55, SE = 2.27, t (66.86) = 2.01, p=.049], such that caregivers reported particularly low marital satisfaction when their partners reported negative age stereotypes. Additionally, care-recipients had high marital satisfaction regardless of whether or not their partners held positive or negative age stereotypes [B = -1.56, SE = 2.27, t (68.78) = -.69, p=.49]. Our findings provide some of the first evidence for dyadic associations between age stereotypes and health in older adults. Future research should consider assessing the unique interpersonal effects of age stereotypes on health among older couples.
Source: Innovation in Aging
Institution: Yale University
Language: English
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,977
OpenAlex ID: W2901002609