Olivio J. Clay

Background: Older Black informal caregivers in the U.S. South may face heightened healthcare challenges, yet digital technology may expand access to health resources. Objective: This study examined racial and regional disparities in internet use and digital health engagement among older informal caregivers, focusing on Black caregivers in the South. Methods: Data came from 900 Black and White caregivers aged ≥ 50 in the 2017–2020 Health Information National Trends Survey. Logistic regression models tested race-by-region interactions for general internet use and health-related online activities. Results: Black caregivers in the South had lower odds of general internet use and online communication with doctors, suggesting compounded racial and regional disadvantages. Among internet users, racial disparities in digital health engagement did not vary by region. Findings suggest that disparities may stem more from upstream barriers to digital access and general internet use. Addressing structural barriers to digital access is critical for advancing digital health equity.

As people living with HIV (PLWH) age, they face various stressors that may negatively affect HIV treatment adherence and management. Resilience and personality characteristics have demonstrated associations with better health outcomes among people with various health conditions. The present study examines the association between dispositional resilience, the Big Five personality traits (openness, conscientiousness, extraversion, agreeableness, neuroticism), and locus of control with self-reported perceived HIV treatment management ability among middle-aged and older PLWH. This cross-sectional study included 174 PLWH aged 40 years and older. Treatment management ability was measured by a composite of three HIV health-related perceived treatment management ability measures. After conducting correlations to determine independent variables, a multivariable linear regression predicting treatment management ability was conducted with resilience, all Big Five personality traits, locus of control, and conceptually relevant covariates (health literacy, race, SES, substance use, depression), using a stepwise approach to determine the optimal number of predictors. The overall model predicting treatment management ability was significant, ( F (5,142) = 20.348, p < .001, Adjusted R ² = 0.40), and this model retained resilience, openness, depression, and health literacy. Follow up mediation analysis found that resilience partially mediated the association between openness and treatment management ability. Resilience, openness, depression, and health literacy are important psychosocial factors related to treatment management ability. Interventions targeting resilience, openness to new information, depression, and health literacy may improve HIV treatment management abilities and ultimately health outcomes among older PLWH.

This study examines Black–White disparities in Internet and smart device usage among older informal caregivers. Using pooled data from the 2017–2020 Health Information National Trends Survey ( N = 1,005, aged 50+), we employed logistic regression to assess racial disparities in Internet use, social media engagement, and smart device ownership. Among smart device owners, we further examined different health-related app usage. Older black caregivers were significantly less likely than White caregivers to use the Internet (OR = 0.23, 95% CI = [0.11, 0.46]). However, among smart device owners, Black caregivers were more likely to use apps for health-related goals (OR = 2.42, 95% CI = [1.42, 4.12]) and decision-making (OR = 1.87, 95% CI = [1.11, 3.15]). Despite lower Internet access, Black caregivers demonstrate high engagement with digital health tools when access is available. Bridging the digital divide in underserved communities may improve equity and expand support for older caregivers.

Objective: It is becoming evident that the unique challenges faced by autistic drivers are contingent on the driving context and specific skills required. This meta-analysis examined the driving performance of both autistic and nonautistic drivers, aiming to clarify the reasons behind inconsistencies in published findings and identify the relative strengths and challenges faced by autistic drivers. Method: This study was performed within a theoretical model of driving skills to break down the complex process of driving and identify specific strengths and challenges displayed by autistic drivers. Data were extracted from included studies, and a meta-analysis using random-effects models was conducted. Risk of bias was assessed, and sensitivity analyses were also conducted. Results: The results from 16 studies suggested that autistic drivers show a small yet significant deficit in their overall driving performance compared with nonautistic drivers. Autistic drivers showed significant challenges and variation in performance at the operational level of driving compared with the tactical level of driving. Variation across driving performance was found to be related to licensure status but not age. Conclusion: This paper was able to build upon prior work by clarifying strengths and challenges that are evident in autistic drivers and their driving performance. Notable differences were found to be most related to operational driving skills. These differences may subside with driving experience compared to nonautistic peers. Future studies should further assess potential reasonings for the variation seen across driving performance by examining the interplay of related factors.

Objectives: Social and structural determinants of health (SSDoH) have been linked to racial disparities in Alzheimer’s disease and related dementias (ADRD). Research has established that living in an environment with greater economic stability (ES) or healthcare access (HCA) is associated with better baseline cognition, but the interactive effects between these distinct SSDoH on cognition over time have not been studied. Therefore, the present study examined the independent and interactive effects of ES and HCA on 10-year change in cognitive functioning within a large sample of racially diverse community-dwelling older adults. Methods: Participants included 701 Black/African American and 1804 White older adults from the Advanced Cognitive Training for Independent and Vital Elderly study. Multilevel mixed effects models were used to assess associations between ES and HCA factors on individual-level memory and reasoning trajectories. Results: Results revealed there was no significant ES × HCA interaction on longitudinal cognitive trajectories across the whole sample or within race-stratified groups, but there was a significant interaction on memory level. Higher ES levels were independently associated with slower age-related memory declines among Black/African American older adults. In contrast, higher ES and HCA levels were both independently associated with faster age-related reasoning declines among White participants. Discussion: Results demonstrated that ES and HCA exerted synergistic effects on memory level across ages in the whole sample. Differential associations between SSDoH and cognitive outcomes across racial groups suggest that improving access to economic resources within Black/African American communities may reduce racial disparities in ADRD.

A developmental milestone that both contributes to and facilitates a successful transition into adulthood is the ability to drive. Yet only one in three autistic adolescents successfully obtain a driver’s license by age 21 compared to over three-fourths of non-autistic adolescents. Of those who receive their license, there is inconsistency in driving attitudes, experiences and skills. The current study aimed to (1) provide a systematic review of the driving profile of autistic drivers and (2) structurally organize driving performance within a theoretical driving model – Michon’s Hierarchical Model of Driving. Following PRISMA guidelines, four databases were systematically searched to identify published articles related to autistic drivers. To be included, all studies met the following inclusion criteria: included autistic sample or people representing or working with autistic individuals, peer-reviewed, published between 2000 and 2021 and contained empirical data reporting on an aspect related to driving or motor vehicle transportation. A systematic search yielded 37 articles that met inclusion criteria. Based on the differential results derived from this review, it appears that autistic drivers are not generally at greater risk of negative driving outcomes; instead, they face unique challenges based on the skills necessary to navigate specific driving contexts. However, due to the inconsistency across results, the actual driving performance in autistic drivers remains unclear. Future research should focus on quantifying these results using an evidenced-based, theoretical framework to identify consistent strengths and challenges in driving performance across autistic drivers.

Background: Adverse social determinants of health (SDoH) have been associated with cardiometabolic disease; however, disparities in cardiometabolic outcomes are rarely the result of a single risk factor. Objective: This study aimed to identify and characterize SDoH phenotypes based on patient-reported and neighborhood-level data from the institutional electronic medical record and evaluate the prevalence of diabetes, obesity, and other cardiometabolic diseases by phenotype status. Methods: Patient-reported SDoH were collected (January to December 2020) and neighborhood-level social vulnerability, neighborhood socioeconomic status, and rurality were linked via census tract to geocoded patient addresses. Diabetes status was coded in the electronic medical record using International Classification of Diseases codes; obesity was defined using measured BMI ≥30 kg/m². Latent class analysis was used to identify clusters of SDoH (eg, phenotypes); we then examined differences in the prevalence of cardiometabolic conditions based on phenotype status using prevalence ratios (PRs). Results: Complete data were available for analysis for 2380 patients (mean age 53, SD 16 years; n=1405, 59% female; n=1198, 50% non-White). Roughly 8% (n=179) reported housing insecurity, 30% (n=710) reported resource needs (food, health care, or utilities), and 49% (n=1158) lived in a high-vulnerability census tract. We identified 3 patient SDoH phenotypes: (1) high social risk, defined largely by self-reported SDoH (n=217, 9%); (2) adverse neighborhood SDoH (n=1353, 56%), defined largely by adverse neighborhood-level measures; and (3) low social risk (n=810, 34%), defined as low individual- and neighborhood-level risks. Patients with an adverse neighborhood SDoH phenotype had higher prevalence of diagnosed type 2 diabetes (PR 1.19, 95% CI 1.06‐1.33), hypertension (PR 1.14, 95% CI 1.02‐1.27), peripheral vascular disease (PR 1.46, 95% CI 1.09‐1.97), and heart failure (PR 1.46, 95% CI 1.20‐1.79). Conclusions: Patients with the adverse neighborhood SDoH phenotype had higher prevalence of poor cardiometabolic conditions compared to phenotypes determined by individual-level characteristics, suggesting that neighborhood environment plays a role, even if individual measures of socioeconomic status are not suboptimal.

Background: Cognitive impairment after stroke is common and is present in up to 60% of survivors. Stroke severity, indicated by both volume and location, is the most consequential predictor of cognitive impairment, with severe strokes predicting higher chances of cognitive impairment. The current investigation examines the associations of 2 stroke severity ratings and a caregiver‐report of poststroke functioning with longitudinal cognitive outcomes. Methods and Results: One hundred fifty‐seven caregivers and stroke survivor dyads participated in the CARES (Caring for Adults Recovering From the Effects of Stroke) project, an ancillary study of the REGARDS (Reasons for Geographic and Racial Differences in Stroke) national cohort study. The Glasgow Outcome Scale and modified Rankin Scale scores collected at hospitalization discharge were included as 2 primary predictors of cognitive impairment. The number of caregiver‐reported problems and impairments at 9 months following stroke were included as a third predictor. Cognition was measured using a biennial telephone battery and included the domains of learning, memory, and executive functioning. Multiple cognitive assessments were analyzed up to 5 years poststroke, controlling for prestroke cognition and demographic variables of the stroke survivor. Separate mixed models showed significant main effects of the Glasgow Outcome Scale (b=0.3380 [95% CI, 0.14–0.5]; P =0.0009), modified Rankin Scale (b=−0.2119 [95% CI, −0.32 to −0.10]; P =0.0002), and caregiver‐reported problems (b=−0.0671 [95% CI, −0.09 to −0.04]; P P <0.0001). Conclusions: These findings emphasize the importance of caregiver feedback in predicting cognitive consequences of stroke.

Background and Objectives: Consumer credit has shown increasing relevance to the health of older adults; however, studies have not been able to assess the extent to which creditworthiness influences future health or health influences future creditworthiness. We assessed the relationships between 4-year pre and postmorbid consumer credit history and self-rated physical and mental health outcomes among older adults. Research Design and Methods: Generalized estimating equations models assessed pre and postmorbid credit history (credit scores, derogatory accounts, and unpaid accounts in collections) and the onset of poor self-rated health (SF-36 score <50) among 1,740 participants aged 65+ in the Advanced Cognitive Training for Independent and Vital Elderly study from 2001 to 2017, linked to TransUnion consumer credit data. Results: In any given year, up to 1/4 of participants had a major derogatory, unpaid, or collections account, and up to 13% of the sample had poor health. Each 50-point increase in credit score trended toward a 5% lower odds of poor health in the next 1 year, a 6% lower odds in the next 2 years, and a statistically significant finding of 13% lower odds by 3 years. A drop in credit score was associated with a 10% greater odds of poor health in the next year, and having a major derogatory account was associated with an 86% greater odds of poor health in the next 3 years. After poor health onset, credit scores continued to see significant losses up to the 3 years, with larger decrements over time. Discussion and Implications: Having a major derogatory account or a sudden loss in credit may be a time to monitor older adults for changes in health. After a downturn in health, supporting older adults to manage their debt may help stabilize their credit.