The 2015 Middle East respiratory syndrome (MERS) outbreak in South Korea was a serious threat to public health, and was exacerbated by the inappropriate responses of major institutions and the public. This study examined the sources of confusion during the MERS outbreak and identified the factors that can affect people's behavior. An online survey of the risk perception of university students in South Korea was performed after the epidemic had peaked. The questionnaire addressed the major social determinants in South Korea during the MERS epidemic. The analysis included data from 1,470 subjects who provided complete answers. The students had 53.5% of the essential knowledge about MERS. Women showed higher risk perception than men, and trust in the media was positively associated with risk perception (P < .001). Additionally, risk perception was positively associated with overreaction by the public (odds ratio, 2.80; 95% confidence interval, 2.17-3.60; P < .001). These findings suggest that media content affected the public's perception of MERS risk and that perception of a high level of risk led to overreaction. Risk perception was associated with most of the social factors examined and overreaction by the public. Therefore, providing accurate information and data to the public, establishing trust, and facilitating the development of an attitude will all be important in future crises.

Background: The number of mobile health apps is rapidly increasing. This means that consumers are faced with a bewildering array of choices, and finding the benefit of such apps may be challenging. The significant international burden of breast cancer (BC) and the potential of mobile health apps to improve medical and public health practices mean that such apps will likely be important because of their functionalities in daily life. As the app market has grown exponentially, several review studies have scrutinized cancer- or BC-related apps. However, those reviews concentrated on the availability of the apps and relied on user ratings to decide on app quality. To minimize subjectivity in quality assessment, quantitative methods to assess BC-related apps are required. Objective: The purpose of this study is to analyze the content and quality of BC-related apps to provide useful information for end users and clinicians. Methods: Based on a stepwise systematic approach, we analyzed apps related to BC, including those related to prevention, detection, treatment, and survivor support. We used the keywords “breast cancer” in English and Korean to identify commercially available apps in the Google Play and App Store. The apps were then independently evaluated by 2 investigators to determine their eligibility for inclusion. The content and quality of the apps were analyzed using objective frameworks and the Mobile App Rating Scale (MARS), respectively. Results: The initial search identified 1148 apps, 69 (6%) of which were included. Most BC-related apps provided information, and some recorded patient-generated health data, provided psychological support, and assisted with medication management. The Kendall coefficient of concordance between the raters was 0.91 (P<.001). The mean MARS score (range: 1-5) of the apps was 3.31 (SD 0.67; range: 1.94-4.53). Among the 5 individual dimensions, functionality had the highest mean score (4.37, SD 0.42) followed by aesthetics (3.74, SD 1.14). Apps that only provided information on BC prevention or management of its risk factors had lower MARS scores than those that recorded medical data or patient-generated health data. Apps that were developed >2 years ago, or by individuals, had significantly lower MARS scores compared to other apps (P<.001). Conclusions: The quality of BC-related apps was generally acceptable according to the MARS, but the gaps between the highest- and lowest-rated apps were large. In addition, apps using personalized data were of higher quality than those merely giving related information, especially after treatment in the cancer care continuum. We also found that apps that had been updated within 1 year and developed by private companies had higher MARS scores. This may imply that there are criteria for end users and clinicians to help choose the right apps for better clinical outcomes.

Particulate matter (PM) air pollution has challenged the global community and the International Agency for Research on Cancer (IARC) classified airborne particulate matter as carcinogenic to humans. However, while most studies of cancer examined a single cancer type using different cohorts, few studies compared the associations of PM between different cancer types. We aimed to compare the association of long-term exposure to PM (PM₁₀ and PM_2.5) and cancer mortality across 17 different types of cancer using a population-based cohort in the Seoul Metropolitan Area (SMA), South Korea; Our study population includes 87,608 subjects (mean age: 46.58 years) residing in the SMA from the National Health Insurance Services–National Sample cohort (NHIS–NSC) and followed up for 2007–2015. We used the time-dependent Cox proportional hazards model to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of each cancer mortality per 10 μg/m³ increase in PM concentrations, after adjusting for individual and areal characteristics. During eight years of follow-up, 1487 people died with any of 17 cancer types. Lung cancer death was the highest, followed by liver and stomach cancer. Although we did not find the association for all cancer types, possibly because of limited cancer cases, HRs of PM_2.5 were relatively high for lung, stomach, pancreas, non-Hodgkin’s lymphoma, prostate, esophagus, oral and pharynx, and brain cancer mortality (HRs = 1.44–7.14). High HRs for pancreas, non–Hodgkin’s lymphoma, esophagus, and oral and pharynx cancer were also seen for PM₁₀; our findings suggest PM air pollution as a potential risk factor of cancer mortality for upper digestive tracts, mouth, pancreas, and non–Hodgkin’s lymphoma in a highly urbanized population with high exposure to PM for a long time.

Background: Mobile health (mHealth) holds promise for enhancing patient care, yet attrition in its use remains a major barrier. Low retention rates limit its potential impact, while barriers to accessing or adopting mHealth vary across populations and countries. These differences in utilization of mHealth may exacerbate health inequalities, contributing to the digital health divide. Objective: We aimed to conduct a systematic review and meta-analysis to investigate the factors associated with inequalities in mHealth utilization across different implementation phases, including access, adoption, adherence, and maintenance. Methods: This systematic review and meta-analysis analyzed mHealth research from 2000 to May 30, 2024, using databases, including PubMed, Web of Science, MEDLINE, and ProQuest. Eligible studies included smartphones, mHealth apps, wearables, and inequality indicators across 4 mHealth phases: access, adoption, adherence, and maintenance. Excluded studies were nonpeer-reviewed, opinion-based, or not in English. Extracted data included study characteristics, target populations, health outcomes, and inequality factors like age, gender, socioeconomic status, and digital literacy. Factors were categorized using a digital health equity framework (biological, behavioral, sociocultural, digital, health care system, and physical domains). Meta-analyses were performed using a random-effects model for factors reported in at least three studies, with heterogeneity assessed by the I² statistic. Results: Among 1990 studies, 62 studies met the inclusion criteria, and 30 studies underwent meta-analysis. The phases of mHealth utilization were access (n=23, 37%), adoption (n=47, 76%), adherence (n=9, 15%), and maintenance (n=2, 3%). Meta-analysis showed older age was negatively associated with mHealth adoption (odds ratio [OR] 0.47, 95% CI 0.23‐0.93), while higher education and income were positively associated in both access and adoption phases. Employment showed significant associations in the access phase (OR 1.49, 95% CI 1.08‐2.05), whereas comorbidities (OR 1.39, 95% CI 1.03‐1.86) and private insurance (OR 1.63, 95% CI 1.07‐2.48) were significantly associated with adoption of mHealth. Women (OR 1.24, 95% CI 1.06‐1.45) and physically active individuals (OR 1.64, 95% CI 1.07‐2.50) were more likely to adopt mHealth. Conclusions: The conceptual framework outlined in this study highlights the multifaceted nature of mHealth utilization across all the phases of mHealth engagement. To address these inequalities, tailored and personalized interventions are required at each phase of mHealth utilization. Targeted efforts can enhance digital access for older and low-income adults while promoting engagement through education, insurance support, and healthy behaviors, thereby promoting equitable and effective mHealth use. By recognizing the interconnectedness of these domains, policy makers and health care stakeholders can design interventions that not only address the phase-specific barriers but also bridge broader inequalities in health care access and engagement.

Background: As the rapid advancement of digital health technologies has significantly improved health management, digital health literacy (DHL) has emerged as a crucial determinant of health outcomes. Objective: The aim of this study was to assess DHL among Korean adults using a task-based assessment tool and to examine how sociodemographic and health literacy factors are associated with DHL, with the goal of identifying vulnerable groups and informing equitable digital health strategies. Methods: This cross-sectional survey was conducted from July 20 to July 31, 2022, among adults aged 19 years and older in South Korea. Participants were recruited nationally, with those younger than 55 years completing an online survey and those aged 55 years and older participating in face-to-face interviews to address the digital divide. Participants’ DHL was assessed using the 34-item Digital Health Technology Literacy Assessment Questionnaire, a tool designed to evaluate practical task-based competencies. Results: Among 1041 Korean adults, 27.8% (n=289) demonstrated low DHL, with the largest gaps observed in mobile app use and critical evaluation of health information. The mean DHL score (on a 100-point scale) was 73.8 (SD 29.7). The high and low DHL groups scored 90.3 (SD 35.6) and 31.5 (SD 20.0), respectively. Specifically, only 49 (17%) of the low DHL group were able to sign up for an app, compared with 716 (95.2%) in the high DHL group. Similarly, 52 (18%) of the low DHL group could update an app, whereas 712 (94.7%) could in the high DHL group. Multivariate analysis revealed that older age (≥60 years), lower income (≤US $2000/month), unemployment, and inadequate general health literacy were significantly associated with lower DHL, highlighting the need to target modifiable factors beyond age. Conclusions: This study highlights the ongoing digital health disparities, emphasizing the need for tailored strategies in mobile apps and digital health technologies. Addressing modifiable factors such as health literacy is key to ensuring equitable access and the effective use of digital health resources.