Objective: While using digital technologies for social health is widely acknowledged, the relationship between loneliness, social isolation, and digital health literacy remains unknown. This study aimed to assess the levels of loneliness, social isolation, and digital health literacy in older women living alone and to explore the associations between these factors. Methods: In August 2021, a cross-sectional survey was conducted on 145 older women living alone, selected using convenience sampling. The study used the University of California, Los Angeles Loneliness Scale (version 3), Lubben Social Network Scale-6, and Digital Health Technology Literacy-Assessment Questionnaire. The collected data were analyzed using descriptive statistics, the Mann–Whitney U test, the Kruskal–Wallis test, Spearman’s rho correlation, and a generalized linear model (GLM). Results: Of the participants, 22.8% (n=33) reported moderate loneliness, 20.7% (n=30) reported severe loneliness, and 36.6% (n=53) were at risk for social isolation. The mean digital health literacy score among participants was 4.85 (SD=6.92), which is relatively low. Importantly, our findings using a GLM to control for covariates revealed a significant association between loneliness (B=-0.013, p=0.018) and digital health literacy. Conclusion The increased loneliness experienced during the pandemic may contribute to low digital health literacy, alienating these individuals from the benefits of digital technologies. Therefore, in developing digital health programs or policies, it is imperative to consider the psychosocial status of individuals, including loneliness, while enhancing digital health literacy.

Objective: While using digital technologies for social health is widely acknowledged, the relationship between loneliness, social isolation, and digital health literacy remains unknown. This study aimed to assess the levels of loneliness, social isolation, and digital health literacy in older women living alone and to explore the associations between these factors. Methods: In August 2021, a cross-sectional survey was conducted on 145 older women living alone, selected using convenience sampling. The study used the University of California, Los Angeles Loneliness Scale (version 3), Lubben Social Network Scale-6, and Digital Health Technology Literacy-Assessment Questionnaire. The collected data were analyzed using descriptive statistics, the Mann–Whitney U test, the Kruskal–Wallis test, Spearman’s rho correlation, and a generalized linear model (GLM). Results: Of the participants, 22.8% (n=33) reported moderate loneliness, 20.7% (n=30) reported severe loneliness, and 36.6% (n=53) were at risk for social isolation. The mean digital health literacy score among participants was 4.85 (SD=6.92), which is relatively low. Importantly, our findings using a GLM to control for covariates revealed a significant association between loneliness (B=-0.013, p=0.018) and digital health literacy. Conclusion The increased loneliness experienced during the pandemic may contribute to low digital health literacy, alienating these individuals from the benefits of digital technologies. Therefore, in developing digital health programs or policies, it is imperative to consider the psychosocial status of individuals, including loneliness, while enhancing digital health literacy.

Objective: While using digital technologies for social health is widely acknowledged, the relationship between loneliness, social isolation, and digital health literacy remains unknown. This study aimed to assess the levels of loneliness, social isolation, and digital health literacy in older women living alone and to explore the associations between these factors. Methods: In August 2021, a cross-sectional survey was conducted on 145 older women living alone, selected using convenience sampling. The study used the University of California, Los Angeles Loneliness Scale (version 3), Lubben Social Network Scale-6, and Digital Health Technology Literacy-Assessment Questionnaire. The collected data were analyzed using descriptive statistics, the Mann–Whitney U test, the Kruskal–Wallis test, Spearman’s rho correlation, and a generalized linear model (GLM). Results: Of the participants, 22.8% (n=33) reported moderate loneliness, 20.7% (n=30) reported severe loneliness, and 36.6% (n=53) were at risk for social isolation. The mean digital health literacy score among participants was 4.85 (SD=6.92), which is relatively low. Importantly, our findings using a GLM to control for covariates revealed a significant association between loneliness (B=-0.013, p=0.018) and digital health literacy. Conclusion The increased loneliness experienced during the pandemic may contribute to low digital health literacy, alienating these individuals from the benefits of digital technologies. Therefore, in developing digital health programs or policies, it is imperative to consider the psychosocial status of individuals, including loneliness, while enhancing digital health literacy.

Background: Severe fever with thrombocytopenia syndrome virus (SFTSV) is a lethal threat.Increasing Severe fever with thrombocytopenia syndrome (SFTS) risk in Asia and the United States stems from the spread of natural host, Haemaphysalis longicornis. Rapid and accurate SFTSV molecular diagnosis is crucial for treatment decisions, reducing fatality risk. Methods: Blood samples from 17 suspected SFTS patients at Chuncheon Sacred Heart Hospital (September-December 2022) were collected. SFTSV was diagnosed using two reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assays from Gangwon Institute of Health and Environment (RT-qPCR/GIHE) and Asan Medical Center (RT-qPCR/AMC). To address RT-qPCR disparities, amplicon-based MinION sequencing traced SFTSV genomic sequences in clinical samples. Results: In two samples (N39 and N50), SFTSV was detected in both RT-qPCR/GIHE and RTqPCR/AMC. Among 11 samples, RT-qPCR/AMC exclusively detected SFTSV. In four samples, both assays yielded negative results. Amplicon-based MinION sequencing enabled nearly whole-genome sequencing of SFTSV in samples N39 and N50. Among 11 discordant samples, five contained significant SFTSV reads, aligning with the RT-qPCR/AMC findings. However, another six samples showed insufficient viral reads in accordance with the negativity observed in RT-qPCR/GIHE. The phylogenetic pattern of SFTSV demonstrated N39 formed a genetic lineage with genotype A in all segments. SFTSV N50 grouped with the B-1 sub-genotype for L segment and B-2 sub-genotype for the M and S segments, indicating genetic reassortment. Conclusion The study demonstrates the robust sensitivity of amplicon-based MinION sequencing for the direct detection of SFTSV in clinical samples containing ultralow copies of viral genomes. Next-generation sequencing holds potential in resolving SFTSV diagnosis discrepancies, enhancing understanding of diagnostic capacity, and risk assessment for emerging SFTSV.

Background: Severe fever with thrombocytopenia syndrome virus (SFTSV) is a lethal threat.Increasing Severe fever with thrombocytopenia syndrome (SFTS) risk in Asia and the United States stems from the spread of natural host, Haemaphysalis longicornis. Rapid and accurate SFTSV molecular diagnosis is crucial for treatment decisions, reducing fatality risk. Methods: Blood samples from 17 suspected SFTS patients at Chuncheon Sacred Heart Hospital (September-December 2022) were collected. SFTSV was diagnosed using two reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assays from Gangwon Institute of Health and Environment (RT-qPCR/GIHE) and Asan Medical Center (RT-qPCR/AMC). To address RT-qPCR disparities, amplicon-based MinION sequencing traced SFTSV genomic sequences in clinical samples. Results: In two samples (N39 and N50), SFTSV was detected in both RT-qPCR/GIHE and RTqPCR/AMC. Among 11 samples, RT-qPCR/AMC exclusively detected SFTSV. In four samples, both assays yielded negative results. Amplicon-based MinION sequencing enabled nearly whole-genome sequencing of SFTSV in samples N39 and N50. Among 11 discordant samples, five contained significant SFTSV reads, aligning with the RT-qPCR/AMC findings. However, another six samples showed insufficient viral reads in accordance with the negativity observed in RT-qPCR/GIHE. The phylogenetic pattern of SFTSV demonstrated N39 formed a genetic lineage with genotype A in all segments. SFTSV N50 grouped with the B-1 sub-genotype for L segment and B-2 sub-genotype for the M and S segments, indicating genetic reassortment. Conclusion The study demonstrates the robust sensitivity of amplicon-based MinION sequencing for the direct detection of SFTSV in clinical samples containing ultralow copies of viral genomes. Next-generation sequencing holds potential in resolving SFTSV diagnosis discrepancies, enhancing understanding of diagnostic capacity, and risk assessment for emerging SFTSV.

Background: Severe fever with thrombocytopenia syndrome virus (SFTSV) is a lethal threat.Increasing Severe fever with thrombocytopenia syndrome (SFTS) risk in Asia and the United States stems from the spread of natural host, Haemaphysalis longicornis. Rapid and accurate SFTSV molecular diagnosis is crucial for treatment decisions, reducing fatality risk. Methods: Blood samples from 17 suspected SFTS patients at Chuncheon Sacred Heart Hospital (September-December 2022) were collected. SFTSV was diagnosed using two reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assays from Gangwon Institute of Health and Environment (RT-qPCR/GIHE) and Asan Medical Center (RT-qPCR/AMC). To address RT-qPCR disparities, amplicon-based MinION sequencing traced SFTSV genomic sequences in clinical samples. Results: In two samples (N39 and N50), SFTSV was detected in both RT-qPCR/GIHE and RTqPCR/AMC. Among 11 samples, RT-qPCR/AMC exclusively detected SFTSV. In four samples, both assays yielded negative results. Amplicon-based MinION sequencing enabled nearly whole-genome sequencing of SFTSV in samples N39 and N50. Among 11 discordant samples, five contained significant SFTSV reads, aligning with the RT-qPCR/AMC findings. However, another six samples showed insufficient viral reads in accordance with the negativity observed in RT-qPCR/GIHE. The phylogenetic pattern of SFTSV demonstrated N39 formed a genetic lineage with genotype A in all segments. SFTSV N50 grouped with the B-1 sub-genotype for L segment and B-2 sub-genotype for the M and S segments, indicating genetic reassortment. Conclusion The study demonstrates the robust sensitivity of amplicon-based MinION sequencing for the direct detection of SFTSV in clinical samples containing ultralow copies of viral genomes. Next-generation sequencing holds potential in resolving SFTSV diagnosis discrepancies, enhancing understanding of diagnostic capacity, and risk assessment for emerging SFTSV.

Objective: While using digital technologies for social health is widely acknowledged, the relationship between loneliness, social isolation, and digital health literacy remains unknown. This study aimed to assess the levels of loneliness, social isolation, and digital health literacy in older women living alone and to explore the associations between these factors. Methods: In August 2021, a cross-sectional survey was conducted on 145 older women living alone, selected using convenience sampling. The study used the University of California, Los Angeles Loneliness Scale (version 3), Lubben Social Network Scale-6, and Digital Health Technology Literacy-Assessment Questionnaire. The collected data were analyzed using descriptive statistics, the Mann–Whitney U test, the Kruskal–Wallis test, Spearman’s rho correlation, and a generalized linear model (GLM). Results: Of the participants, 22.8% (n=33) reported moderate loneliness, 20.7% (n=30) reported severe loneliness, and 36.6% (n=53) were at risk for social isolation. The mean digital health literacy score among participants was 4.85 (SD=6.92), which is relatively low. Importantly, our findings using a GLM to control for covariates revealed a significant association between loneliness (B=-0.013, p=0.018) and digital health literacy. Conclusion The increased loneliness experienced during the pandemic may contribute to low digital health literacy, alienating these individuals from the benefits of digital technologies. Therefore, in developing digital health programs or policies, it is imperative to consider the psychosocial status of individuals, including loneliness, while enhancing digital health literacy.

Background: Severe fever with thrombocytopenia syndrome virus (SFTSV) is a lethal threat.Increasing Severe fever with thrombocytopenia syndrome (SFTS) risk in Asia and the United States stems from the spread of natural host, Haemaphysalis longicornis. Rapid and accurate SFTSV molecular diagnosis is crucial for treatment decisions, reducing fatality risk. Methods: Blood samples from 17 suspected SFTS patients at Chuncheon Sacred Heart Hospital (September-December 2022) were collected. SFTSV was diagnosed using two reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assays from Gangwon Institute of Health and Environment (RT-qPCR/GIHE) and Asan Medical Center (RT-qPCR/AMC). To address RT-qPCR disparities, amplicon-based MinION sequencing traced SFTSV genomic sequences in clinical samples. Results: In two samples (N39 and N50), SFTSV was detected in both RT-qPCR/GIHE and RTqPCR/AMC. Among 11 samples, RT-qPCR/AMC exclusively detected SFTSV. In four samples, both assays yielded negative results. Amplicon-based MinION sequencing enabled nearly whole-genome sequencing of SFTSV in samples N39 and N50. Among 11 discordant samples, five contained significant SFTSV reads, aligning with the RT-qPCR/AMC findings. However, another six samples showed insufficient viral reads in accordance with the negativity observed in RT-qPCR/GIHE. The phylogenetic pattern of SFTSV demonstrated N39 formed a genetic lineage with genotype A in all segments. SFTSV N50 grouped with the B-1 sub-genotype for L segment and B-2 sub-genotype for the M and S segments, indicating genetic reassortment. Conclusion The study demonstrates the robust sensitivity of amplicon-based MinION sequencing for the direct detection of SFTSV in clinical samples containing ultralow copies of viral genomes. Next-generation sequencing holds potential in resolving SFTSV diagnosis discrepancies, enhancing understanding of diagnostic capacity, and risk assessment for emerging SFTSV.

Objective: While using digital technologies for social health is widely acknowledged, the relationship between loneliness, social isolation, and digital health literacy remains unknown. This study aimed to assess the levels of loneliness, social isolation, and digital health literacy in older women living alone and to explore the associations between these factors. Methods: In August 2021, a cross-sectional survey was conducted on 145 older women living alone, selected using convenience sampling. The study used the University of California, Los Angeles Loneliness Scale (version 3), Lubben Social Network Scale-6, and Digital Health Technology Literacy-Assessment Questionnaire. The collected data were analyzed using descriptive statistics, the Mann–Whitney U test, the Kruskal–Wallis test, Spearman’s rho correlation, and a generalized linear model (GLM). Results: Of the participants, 22.8% (n=33) reported moderate loneliness, 20.7% (n=30) reported severe loneliness, and 36.6% (n=53) were at risk for social isolation. The mean digital health literacy score among participants was 4.85 (SD=6.92), which is relatively low. Importantly, our findings using a GLM to control for covariates revealed a significant association between loneliness (B=-0.013, p=0.018) and digital health literacy. Conclusion The increased loneliness experienced during the pandemic may contribute to low digital health literacy, alienating these individuals from the benefits of digital technologies. Therefore, in developing digital health programs or policies, it is imperative to consider the psychosocial status of individuals, including loneliness, while enhancing digital health literacy.

Purpose: This study aimed to examine the level of digital health literacy and identify factors associated with digital health literacy among older adults living alone in South Korea. Methods: A cross-sectional study was conducted on 140 older adults aged 65 and above who live alone. Descriptive statistics and non-parametric methods were used to explore the relationship between digital health literacy and independent variables. A generalized linear model was used to identify factors associated with digital health literacy. Results: Among 140 smartphone-owning older adults living alone, 52.1% were using the Internet via digital devices, and the participants’ average digital health literacy score was 6.64±7.46. Univariate analysis results showed significant differences in digital health literacy according to age, education level, and multimorbidity. The factors associated with digital health literacy were identified as gender (B=−0.36, p=.031), age (B=−0.06, p<.001), education level (B=0.12, p<.001), and sleep problems (B=−0.06, p=.006). Conclusion Despite widespread Internet and smartphone use, older adults living alone with chronic diseases showed low levels of digital health literacy, which were significantly associated with gender, age, education level, and sleep problems. Enhancing digital health literacy among vulnerable populations is crucial for the effective implementation of digital health services. Collaborative efforts, including tailored digital health interventions to enhance the digital health literacy of vulnerable populations and supportive policies, are essential to bridge the digital divide and promote health equity.