Objectives

A comprehensive examination of resilience by race, ethnicity, and neighborhood socioeconomic status (NSES) among women aged ≥80 is needed, given the aging of the US population, increasing longevity, and growing racial and ethnic diversity.

Methods

Participants were women aged ≥80 enrolled in the Women's Health Initiative (WHI). Resilience was assessed with a modified version of the Brief Resilience Scale. Descriptive statistics and multiple linear regression examined the association of demographic, health, and psychosocial variables with resilience by race, ethnicity, and NSES.

Results

Participants (n=29,367, median age=84.3) were White (91.4%), Black (3.7%), Hispanic (1.9%), and Asian (1.7%) women. There were no significant differences by race and ethnicity on mean resiliency scores (p=0.06). Significant differences by NSES were observed regarding mean resiliency scores between those with low NSES (3.94±0.83, out of 5) and high NSES (4.00±0.81). Older age, higher education, higher self-rated health, lower stress, and living alone were significant positive correlates of resilience in the sample. Social support was correlated with resilience among White, Black, and Asian women, but not for Hispanic women. Depression was a significant correlate of lower resilience, except among Asian women. Living alone, smoking, and spirituality were significantly associated with higher resilience among women with moderate NSES.

Discussion

Multiple factors were associated with resilience among women aged ≥80 in the WHI. Despite some differing correlates of resilience by race, ethnicity, and NSES, there were many similarities. These results may aid in the design of resilience interventions for the growing, increasingly diverse population of older women.

"Race" and "ethnicity" are socially constructed terms, not based on biology - in contrast to biologic ancestry and genetic admixture - and are flexible, contested, and unstable concepts, often driven by power. Although individuals may self-identify with a given race and ethnic group, as multidimensional beings exposed to differential life influencing factors that contribute to disease risk, additional social determinants of health (SDOH) should be explored to understand the relationship of race or ethnicity to health. Potential health effects of structural racism, defined as "the structures, policies, practices, and norms resulting in differential access to goods, services, and opportunities of society by "race," have been largely ignored in medical research. The Women's Health Initiative (WHI) was expected to enroll a racially and ethnically diverse cohort of older women at 40 U.S. clinical centers between 1993 and 1998; yet, key information on the racial and ethnic make-up of the WHI cohort of 161,808 women was limited until a 2020-2021 Task Force was charged by the WHI Steering Committee to better characterize the WHI cohort and develop recommendations for WHI investigators who want to include "race" and/or "ethnicity" in papers and presentations. As the lessons learned are of relevance to most cohorts, the essence of the WHI Race and Ethnicity Language and Data Interpretation Guide is presented in this paper. Recommendations from the WHI Race and Ethnicity Language and Data Interpretation Guide include: Studies should be designed to include all populations and researchers should actively, purposefully and with cultural-relevance, commit to recruiting a diverse sample; Researchers should collect robust data on race, ethnicity and SDOH variables that may intersect with participant identities, such as immigration status, country of origin, acculturation, current residence and neighborhood, religion; Authors should use appropriate terminology, based on a participant's self-identified "race" and "ethnicity", and provide clear rationale, including a conceptual framework, for including race and ethnicity in the analytic plan; Researchers should employ appropriate analytical methods, including mixed-methods, to study the relationship of these sociocultural variables to health; Authors should address how representative study participants are of the population to which results might apply, such as by age, race and ethnicity.

Community-engaged research (CEnR) builds on the strengths of the Clinical and Translational Science Awards (CTSA) framework to address health in underserved and minority communities. There is a paucity of studies that identify the process from which trust develops in CEnR partnerships. This study responds to the need for empirical investigation of building and maintaining trust from a multistakeholder perspective. We conducted a multi-institutional pilot study using concept mapping with to better understand how trust, a critical outcome of CEnR partnerships, can act as "social capital." Concept mapping was used to collect data from the three stakeholder groups: community, health-care, and academic research partners across three CTSAs. Concept mapping is a mixed-methods approach that allows participants to brainstorm and identify factors that contribute to a concept and describe ways in which those factors relate to each other. This study offers important insights on developing an initial set of trust measures that can be used across CTSAs to understand differences and similarities in conceptualization of trust among key stakeholder groups, track changes in public trust in research, identify both positive and negative aspects of trust, identify characteristics that maintain trust, and inform the direction for future research.

Community-engaged research (CEnR) builds on the strengths of the Clinical and Translational Science Awards (CTSA) framework to address health in underserved and minority communities. There is a paucity of studies that identify the process from which trust develops in CEnR partnerships. This study responds to the need for empirical investigation of building and maintaining trust from a multistakeholder perspective. We conducted a multi-institutional pilot study using concept mapping with to better understand how trust, a critical outcome of CEnR partnerships, can act as "social capital." Concept mapping was used to collect data from the three stakeholder groups: community, health-care, and academic research partners across three CTSAs. Concept mapping is a mixed-methods approach that allows participants to brainstorm and identify factors that contribute to a concept and describe ways in which those factors relate to each other. This study offers important insights on developing an initial set of trust measures that can be used across CTSAs to understand differences and similarities in conceptualization of trust among key stakeholder groups, track changes in public trust in research, identify both positive and negative aspects of trust, identify characteristics that maintain trust, and inform the direction for future research.