Evaluating Predictors of Participation in Telephone-Based Social-Connectedness Interventions for Older Adults: A Dual Machine-Learning and Regression Approach.

Social isolation is a well-documented contributor to poor mental and physical health, and interventions promoting social connectedness have been associated with various health benefits. This study examined predictors of participation in a telephone-based social connectedness intervention for socially isolated older adults. Data were obtained from a social-connectedness intervention that paired college students with Houston-area, community-dwelling adults aged 65 years and older and enrolled in Medicare Advantage plans. We combined machine learning and regression techniques to identify significant predictors of program participation. The following machine-learning methods were implemented: (1) k-nearest neighbors, (2) decision tree and ensembles of decision trees, (3) gradient-boosted decision tree, and (4) random forest. The primary outcome was a binary flag indicating participation in the telephone-based social-connectedness intervention. The most predictive variables in the ML models, with scores corresponding to the 90th percentile or greater, were included in the regression analysis. The predictive ability of each model showed high discriminative power, with test accuracies greater than 95%. Our findings suggest that telephone-based social-connectedness interventions appeal to individuals with disabilities, depression, arthritis, and higher risk scores. scores. Recognizing features that predict participation in social-connectedness programs is the first step to increasing reach and fostering patient engagement.

Optimizing Disaster Preparedness Planning for Minority Older Adults: One Size Does Not Fit All.

By 2050, one in five Americans will be 65 years and older. The growing proportion of older adults in the U.S. population has implications for many aspects of health including disaster preparedness. This study assessed correlates of disaster preparedness among community-dwelling minority older adults and explored unique differences for African American and Hispanic older adults. An electronic survey was disseminated to older minority adults 55+, between November 2020 and January 2021 (n = 522). An empirical framework was used to contextualize 12 disaster-related activities into survival an0000000d planning actions. Multivariate logistic regression models were stratified by race/ethnicity to examine the correlates of survival and planning actions in African American and Hispanic older adults, separately. We found that approximately 6 in 10 older minority adults did not perceive themselves to be disaster prepared. Medicare coverage was positively associated with survival and planning actions. Income level and prior experience with disaster were related to survival actions in the African American population. In conclusion, recognizing the gaps in disaster-preparedness in elderly minority communities can inform culturally sensitive interventions to improve disaster preparedness and recovery.

COVID-19 and Telehealth Operations in Texas Primary Care Clinics: Disparities in Medically Underserved Area Clinics.

The COVID-19 pandemic has dramatically altered the landscape of health care delivery, prompting a rapid, widespread adoption of telehealth in primary care practices. Using a pooled sample of 1,344 primary care clinics in Texas, we examined the adoption of telehealth in Texas during the initial months of the COVID-19 pandemic, by comparing medically underserved area (MUA) clinics and non-medically underserved area (non-MUA) clinics. Our analysis suggests that compared with MUA clinics, clinics in non-MUAs were more likely to conduct a majority of their visits via telehealth before May 1st, 2020. However, later surveys indicated that differences in telehealth use between MUA and non-MUA clinics lessened, suggesting that some of the barriers that MUA clinics initially faced might have resolved over time. This research provides an additional perspective in discussions about telehealth adoption on a widespread, permanent basis in Texas and the U.S.