In South Korea, digital literacy education programs are expected to help its older population participate in online welfare services to increase their social support, self-esteem and well-being. This quasi-experimental study assesses the effects of digital literacy education on digital device usage among rural-dwelling adults aged 65 and above and evaluates the positive effects of digital literacy education on depression, happiness, quality of life, self-efficacy and cognitive function. A digital literacy education program and a customized questionnaire survey were conducted to evaluate smartphone use competency and the program’s effects, respectively. We also conducted a chi-square test, paired t-test and difference-in-differences regression analysis. The experimental group showed a significant increase in smartphone usage and video recording capacity than the control group. The happiness and cognitive function scores for dementia screening increased significantly by a mean of 3.7 and 1.1 points, respectively, after digital literacy education. Cognitive function increased significantly by 1.305 points in the experimental group compared to the control group (β = 1.305, p = 0.05 *). Digital literacy education for older adults in rural areas greatly increased smartphone use, video recording capacity, happiness and cognitive function. Based on these findings, it is recommended that the government should implement digital literacy education for older adults in rural areas to increase their happiness and cognitive function.

The World Health Organization (WHO) declared a COVID-19 pandemic on March 12, 2020. Several studies have indicated that densely populated urban environments and the heavy dependence on traffic could increase the potential spread of COVID-19. This study investigated the association between changes in traffic volume and the spread of COVID-19 in South Korea. This study analyzed the daily national traffic and traffic trend for 3 months from January 1, 2020. Traffic data were measured using 6307 vehicle detection system (VDS). This study analyzed the difference in traffic levels between 2019 and 2020. Non-linear regression was performed to analyze the change in traffic trend in 2020. The relationship between traffic and confirmed COVID-19 cases was analyzed using single linear regression. The mean daily nationwide level of traffic for the first 3 months of 2020 was 143 655 563 vehicles, which was 9.7% lower than the same period in 2019 (159 044 566 vehicles). All regions showed a decreasing trend in traffic in February, which shifted to an increasing trend from March. In Incheon there was a positive, but insignificant, linear relationship between increasing numbers of newly confirmed cases and increasing traffic (β = 43 146; p = 0.056). Numbers of newly confirmed COVID-19 patients have been decreasing since March, while the traffic has been increasing. The fact that traffic is increasing indicates greater contact between people, which in turn increases the risk of further COVID-19 spread. Therefore, the government will need to devise suitable policies, such as total social distancing.

Background: eHealth literacy is an essential skill for pursuing electronic health information, particularly for older people whose health needs increase with age. South Korea is now at the intersection of a rapidly digitalizing society and an increasingly aged population. eHealth literacy enables older people to maximize the effective use of emerging digital technology for their health and quality of life. Understanding the eHealth literacy of Korean older adults is critical to eliminating the gray digital divide and inequity in health information access. Objective: This study aims to investigate factors influencing eHealth literacy in older Korean adults and its impact on health outcomes and eHealth use. Methods: This was a cross-sectional survey. Community-dwelling older adults 65 years and older in 2 urban cities in South Korea were included. eHealth literacy was measured by the eHealth Literacy Scale. Ordinal logistic regression was used to analyze factors associated with eHealth literacy and multivariate ANOVA for the impact of eHealth literacy on health outcomes and eHealth use. Results: In total, 434 participants were analyzed. A total of 22.3% (97/434) of participants had high eHealth literacy skills. Increasing age, higher monthly income, and time spent on the internet were significantly associated with eHealth literacy (P<.001), and social media users were 3.97 times (adjusted odds ratio 3.97, 95% CI 1.02‐15.43; P=.04) more likely to have higher skill. Higher eHealth literacy was associated with better self-perceived health and frequent use of digital technologies for accessing health and care services (P<.001). Conclusions: Disparity in socioeconomic status and engagement on the internet and social media can result in different levels of eHealth literacy skills, which can have consequential impacts on health outcomes and eHealth use. Tailored eHealth interventions, grounded on the social and digital determinants of eHealth literacy, could facilitate eHealth information access among older adults and foster a digitally inclusive healthy aging community.

Background: With rapidly aging populations in most parts of the world, it is only natural that the need for caregivers for older adults is going to increase in the near future. Therefore, most technologically proficient countries are in the process of using artificial intelligence (AI) to build socially assistive robots (SAR) to play the role of caregivers in enhancing interaction and social participation among older adults. Objective: This study aimed to examine the effect of intervention through AI SAR on the cognitive function of older adults through a systematic literature review. Methods: We conducted a meta-analysis of the various existing studies on the effect of AI SAR on the cognitive function of older adults to standardize the results and clarify the effect of each method and indicator. Cochrane collaboration and the systematic literature review flow of PRISMA (Preferred Reporting Item Systematic Reviews and Meta-Analyses) were used on original, peer-reviewed studies published from January 2010 to March 2022. The search words were derived by combining keywords including Population, Intervention, and Outcome—according to the Population, Intervention, Comparison, Outcome, Time, Setting, and Study Design principle—for the question “What is the effect of AI SAR on the cognitive function of older adults in comparison with a control group?” (Population: adults aged ≥65 years; Intervention: AI SAR; Comparison: comparison group; Outcome: popular function; and Study Design: prospective study). For any study, if one condition among subjects, intervention, comparison, or study design was different from those indicated, the study was excluded from the literature review. Results: In total, 9 studies were selected (6 randomized controlled trials and 3 quasi-experimental design studies) for the meta-analysis. Publication bias was examined using the contour-enhanced funnel plot method to confirm the reliability and validity of the 9 studies. The meta-analysis revealed that the average effect size of AI SAR was shown to be Hedges g=0.43 (95% CI –0.04 to 0.90), indicating that AI SAR are effective in reducing the Mini Mental State Examination scale, which reflects cognitive function. Conclusions: The 9 studies that were analyzed used SAR in the form of animals, robots, and humans. Among them, AI SAR in anthropomorphic form were able to improve cognitive function more effectively. The development and expansion of AI SAR programs to various functions including health notification, play therapy, counseling service, conversation, and dementia prevention programs are expected to improve the quality of care for older adults and prevent the overload of caregivers. AI SAR can be considered a representative, digital, and social prescription program and a nonpharmacological intervention program that communicates with older adults 24 hours a day. Despite its effectiveness, ethical issues, the digital literacy needs of older adults, social awareness and reliability, and technological advancement pose challenges in implementing AI SAR. Future research should include bigger sample sizes, pre-post studies, as well as studies using an older adult control group.

Noh EB, et al. Infect Chemother. 2021 Jun;53(2):261-270. https://doi.org/10.3947/ic.2021.0029

This study analyzed the perceptions and emotions of Korean and Japanese citizens regarding coronavirus disease 2019 (COVID-19). It examined the frequency of words used in Korean and Japanese tweets regarding COVID-19 and the corresponding changes in their interests. This cross-sectional study analyzed Twitter posts (Tweets) from February 1, 2020 to April 30, 2020 to determine public opinion of the COVID-19 pandemic in Korea and Japan. We collected data from Twitter (https://twitter.com/), a major social media platform in Korea and Japan. Python 3.7 Library was used for data collection. Data analysis included KR-WordRank and frequency analyses in Korea and Japan, respectively. Heat diagrams, word clouds, and rank flowcharts were also used. Overall, 1,470,673 and 4,195,457 tweets were collected from Korea and Japan, respectively. The word trend in Korea and Japan was analyzed every 5 days. The word cloud analysis revealed "COVID-19", "Shinchonji", "Mask", "Daegu", and "Travel" as frequently used words in Korea. While in Japan, "COVID-19", "Mask", "Test", "Impact", and "China" were identified as high-frequency words. They were divided into four categories: social distancing, prevention, issue, and emotion for the rank flowcharts. Concerning emotion, "Overcome" and "Support" increased from February in Korea, while "Worry" and "Anxiety" decreased in Japan from April 1. As a result of the trend, people's interests in the economy were high in both countries, indicating their reservations on the economic downturn. Therefore, focusing policies toward economic stability is essential. Although the interest in prevention increased since April in both countries, the general public's relaxation regarding COVID-19 was also observed.