Purpose: To present a case of a patient diagnosed with idiopathic hemolacria.Case Summary: A healthy 19-year-old man without pre-existing medical conditions presented to the hospital for treatment of intermittent bloody tears from his right eye. The patient reported experiencing bloody tears in his right eye approximately once per month during stressful events for the preceding 6 years. These episodes were associated with ocular pain, right-eye hyperemia, headaches, and nausea. However, these symptoms of bloody tears spontaneously resolved without intervention. Corrected visual acuity in the right eye was 1.0, and the intraocular pressure was 16 mmHg. There were no abnormalities in the ocular appendages, anterior chamber, or eyelids. Nasolacrimal duct probing and irrigation, as well as fundus examination, revealed normal findings. Brain and orbital magnetic resonance imaging did not show abnormalities in the brain or the orbital region, although slight mucosal thickening was present around the right lacrimal gland. Other examinations, including an electrocardiogram, chest X-ray, blood test, and nasal endoscopy, all revealed normal findings. Conclusions Recurrent bloody tears (hemolacria) occurred in the right eye of a 19-year-old man with no history of trauma, intraocular surgery, or underlying medical conditions. Comprehensive ophthalmic examination and brain and orbital magnetic resonance imaging failed to identify any specific abnormalities leading to a diagnosis of idiopathic hemolacria.

A recent understanding of the dynamic continuous spectrum of Mycobacterium tuberculosis infection has led to the recognition of incipient tuberculosis, which refers to the latent infection state that has begun to progress to active tuberculosis. The importance of early detection of these individuals with a high-risk of progression to active tuberculosis is emphasized to efficiently implement targeted tuberculosis preventive therapy. However, the tuberculin skin test or interferon-γ release assay, which is currently used for the diagnosis of latent tuberculosis infection, does not aid in the prediction of the risk of progression to active tuberculosis. Thus, a novel test is urgently needed. Recently, simultaneous and systematic analysis of differentially expressed genes using a high-throughput platform has enabled the discovery of key genes that may serve potential biomarkers for the diagnosis or prognosis of diseases. This host transcriptional investigation has been extended to the field of tuberculosis, providing promising results. The present review focuses on recent progress and challenges in the field of blood transcriptional signatures to predict progression to active tuberculosis.

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.

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.

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.

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.