Background and Objectives: Existing literature presents a widening digital divide among older adults in addition to the consideration of the potential adverse impacts of ageism on internet use among the older adult population. Our study aimed to investigate (a) whether older adults’ perceived ageism will be associated with their use of the internet and (b) whether the relationship between perceived ageism and internet use will be moderated by age groups and binary gender. Research Design and Methods: Using the data from the 2016 Health and Retirement Study, regression analyses were separately performed by gender. Two measures of perceived ageism were considered: (a) self-perception of aging and (b) perceived age discrimination. Results: Our findings suggested that greater exposure to ageism is generally related to less use of the internet. In addition, we found divergent patterns in the relationship between ageism and internet use by gender. For women, a lower level of internet use was predicted by more negative perceptions of aging, whereas men’s internet use was associated with the experience of age discrimination. Furthermore, interaction effects between age groups and ageism varied across gender. The negative perception of aging was more strongly associated with less internet use in older women than middle-aged women. In comparison, the perceived age discrimination predicted less internet use in middle-aged men than older men. Discussion and Implications: Our findings suggest that perceived ageism is significantly associated with internet use, and its association differs by gender.

In response to the coronavirus disease 2019 (COVID-19) pandemic, older adults are advised to follow social distancing measures to prevent infection. However, such measures may increase the risk of loneliness. The current study aimed to investigate (a) whether social distancing measures, particularly limiting close social interactions, are associated with loneliness among older adults, and (b) whether the association between social distancing measures and loneliness is moderated by sociodemographic characteristics. Data were from the fourth wave (April 29 to May 26, 2020) of the nationally representative Understanding America Study COVID-19 Survey. We used data on adults 50 years or older (N = 3,253). Logistic regression models of loneliness were performed. Five indicators of social distancing measures were considered: (a) avoiding public spaces, gatherings, or crowds; (b) canceling or postponing social activities; (c) social visits; (d) no close contact (within 6 feet) with people living together; and (e) with people not living together. Cancelling or postponing social activities and avoiding close contact with people living together were associated with 33% (odds ratio [OR] = 1.33, confidence interval [CI] = 1.06−1.68, p < .05) and 47% (OR = 1.47, CI = 1.09−1.99, p < .05) greater odds of loneliness, respectively. Furthermore, limiting close contact with coresidents increased the probability of loneliness more for males, non-Hispanic Whites, and those with higher levels of education and income. Efforts should be made to help older adults maintain social connectedness with close others by virtual communication methods. Our findings also call special attention to vulnerable groups at elevated risks of loneliness, emphasizing the need for tailored interventions.

Background: There are considerable gaps between the need for assistive technologies and the actual adoption of these technologies among older adults, although older adults are among the groups that most need assistive technologies. Consequently, research is needed in this area because older adults’ technology acceptance and influencing factors may differ depending on their level of frailty. Objective: The objective of this study was to compare frail, prefrail, and robust groups of South Korean adults regarding their behavioral intention to use daily living assistive technologies and the affecting factors—namely, technological context factors, health contexts and abilities, and attitudinal factors—based on a comprehensive senior technology acceptance model. Methods: A nationwide sample of 500 older South Korean adults (aged 55-92 years) was analyzed, and multivariate linear regression analyses of the robust, prefrail, and frail groups were performed. The independent and dependent variables consisted of 3 factors based on previous studies. First, technological context factors consisted of gerontechnology self-efficacy, gerontechnology anxiety, and facilitating conditions. Second, health contexts and abilities consisted of self-reported health conditions, cognitive ability, social relationships, psychological function, and physical function. Third and last, attitudinal factors consisted of behavioral intention to use assistive technologies, attitude toward use, perceived usefulness (PU), and perceived ease of use (PEOU). Results: The results of the analyses showed that technological context factors such as gerontechnology self-efficacy, health contexts and abilities such as self-reported health conditions and psychological function, and attitudinal factors such as attitude toward use, PU, and PEOU had significant effects on behavioral intention to use daily living assistive technologies. In particular, gerontechnology self-efficacy had a significant relationship with behavioral intention to use these technologies in the robust (r=0.120; P=.03) and prefrail (r=0.331; P<.001) groups. Psychological function (life satisfaction) had a significant relationship with behavioral intention to use these technologies in the robust group (r=–0.040; P=.02). Self-reported health conditions had a significant relationship with behavioral intention to use these technologies in the prefrail group (r=–0.169; P=.01). Although each group had a different significant relationship with the variables, attitudinal factors such as attitude toward use affected all groups (robust group: r=0.190; P=.03; prefrail group: r=0.235; P=.006; and frail group: r=0.526; P=.002). In addition, PU and PEOU in the attitudinal factors had a significant relationship with behavioral intention to use assistive technologies in the robust (PU: r=0.160; P=.01; and PEOU: r=0.350; P<.001) and prefrail (PU: r=0.265; P<.001; and PEOU: r=0.120; P=.04) groups. Conclusions: This study found that the comprehensive senior technology acceptance model of daily living assistive technologies had different associations according to the frailty group. These findings provided insights into the consideration of interventions with daily living assistive technologies for older adults with varying levels of frailty.

Despite the overall increase in older adults’ internet use, the digital divide within older Americans remains substantial, particularly for those in rural areas and with racial/ethnic minority backgrounds. The current study examines how one’s residential area and racial/ethnicity relate to internet access, both singularly and in concert. Data were from the 2016 Health and Retirement Study. The sample consisted of 17,372 Americans aged 50 and above. Logistic regression analyses were performed to test the direct effects of residence and race/ethnicity and their interaction effects on internet use. The odds of internet use were significantly lower for older adults living in suburban and rural residences as well as for Black and Hispanic individuals. Furthermore, rural living reduced the probability of using the internet more for Blacks than Whites. These findings underscore the need for targeted interventions to narrow the digital divide, with particular attention required for older Blacks in rural communities.

Extreme heat is well-documented to adversely affect health and mortality, but its link to biological aging—a precursor of the morbidity and mortality process—remains unclear. This study examines the association between ambient outdoor heat and epigenetic aging in a nationally representative sample of US adults aged 56+ ( N = 3686). The number of heat days in neighborhoods is calculated using the heat index, covering time windows from the day of blood collection to 6 years prior. Multilevel regression models are used to predict PCPhenoAge acceleration, PCGrimAge acceleration, and DunedinPACE. More heat days over short- and mid-term windows are associated with increased PCPhenoAge acceleration (e.g., B _{prior7-dayCaution+heat} : 1.07 years). Longer-term heat is associated with all clocks (e.g., B _{prior1-yearExtremecaution+heat} : 2.48 years for PCPhenoAge, B _{prior1-yearExtremecaution+heat} : 1.09 year for PCGrimAge, and B _{prior6-yearExtremecaution+heat} : 0.05 years for DunedinPACE). Subgroup analyses show no strong evidence for increased vulnerability by sociodemographic factors. These findings provide insights into the biological underpinnings linking heat to aging-related morbidity and mortality risks.