Traditional perspectives conceptualize resilience as a trait and depression as resulting from resilience deficiency. However, research indicates that resilience varies substantially even among adults who are clinically depressed, as well as across the lifespan of an individual. Few studies have investigated resilience in depression, and even fewer have examined resilience in depressed older adults.

Three hundred thirty-seven adults ≥60 years with major depressive disorder completed the Connor–Davidson Resilience Scale (CD-RISC) and measures of mental health, quality of life (QOL), and medical comorbidity. Exploratory factor analysis was used to explore the factor structure of the CD-RISC. Correlations and general linear models were used to examine associations between resilience and other variables.

The rotated component matrix indicated a four-factor model. Sorting of items by highest factor loading revealed constructs associated with (1) grit, (2) active coping self-efficacy, (3) accommodative coping self-efficacy, and (4) spirituality. Resilience was significantly correlated with increased age, lower cognitive functioning, greater cerebrovascular risk, and greater medical comorbidity. Resilience was negatively associated with mental health symptoms (depression, apathy, and anxiety) and positively associated with QOL. The final optimal model identified less depression, less apathy, greater medical comorbidity, higher QOL, and minority (non-White) race as factors that significantly explained variability in resilience.

Resilience was significantly associated with a range of mental health constructs in a sample of older adults with depression. Future clinical trials and dismantling studies may help determine whether interventions targeting grit, active coping, accommodative coping, and spirituality can increase resilience and help prevent and treat depression in older adults.

Community engagement (CE) has become more prevalent among academic health centers (AHCs), with significant diversity in practices and language. The array of approaches to CE contributes to confusion among practitioners.

We have reviewed multiple models of CE utilized by AHCs, Clinical and Translational Science Awards, and higher education institutions overall. Taking these models into consideration, we propose a comprehensive model of CE that encompasses a broader spectrum of activities and programs.

The CE Components Practical Model includes 5 components: Community Outreach and Service, Education, Clinical Care, Research, and Policy and Advocacy. The components are supported by the foundational elements within administrative functions and infrastructure.

This model will accomplish the following: (1) reduce confusion about CE; (2) provide a broader understanding of CE; and (3) increase the ability of CE practitioners to interact with each other through this common reference and engage in advancing CE scholarship.

The factors influencing successful aging (SA) are of great interest in an aging society. The aims of this study were to investigate the prevalence of SA, the relative importance across age of the three components used to define it (absence of disease and disability, high cognitive and physical function, and active engagement with life), and its correlates.

Data were extracted from the population-based cross-sectional Nord-Trøndelag Health Study (HUNT3 2006–2008). Individuals aged 70–89 years with complete datasets for the three components were included (N = 5773 of 8,040, 71.8%). Of the respondents, 54.6% were women. Univariate and multivariate regression analyses were used to analyze possible correlates of SA.

Overall, 35.6% of the sample met one of the three criteria, 34.1% met combinations, and 14.5% met all of the three criteria. The most demanding criterion was high function, closely followed by absence of disease, while approximately two-thirds were actively engaged in life. The relative change with age was largest for the high cognitive and physical function component and smallest for active engagement with life. The significant correlates of SA were younger age, female gender, higher education, weekly exercise, more satisfaction with life, non-smoking, and alcohol consumption, whereas marital status was not related to SA.

The prevalence of SA in this study (14.5%) is comparable to previous studies. It may be possible to increase the prevalence by intervention directed toward more exercise, non-smoking, and better satisfaction with life.