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Purpose: This study aimed to identify the main keywords, network structures, and topical themes in patient safety incident reports using text network analysis. Methods: The study analyzed patient safety incident reports from a general hospital in Seoul, covering a total of 3,576 cases reported over five years, from 2019 to 2023. Unstructured data were extracted from the text of the incident reports, detailing how the patient safety incidents occurred and how they were managed according to the six-part principles. The analysis was conducted in four steps: 1) word extraction and refinement, 2) keyword extraction and word network generation, 3) network connectivity and centrality analysis, and 4) topic modeling analysis. The NetMiner program was used for data analysis. Results: The analysis of degree, betweenness, and closeness centrality revealed that the most common keywords among the top five were "confirmation," "medication," "inpatient room," "caregiver," and "condition." Topic modeling analysis identified three main topic groups: 1) incidents caused by a lack of awareness of fall risk, 2) incidents of non-compliance with basic medication principles, and 3) incidents due to inaccurate patient identification. Conclusion: To prevent patient safety incidents, it is necessary to promote a culture of safety in hospitals, standardize patient identification procedures, and provide basic training in medication safety and fall prevention to healthcare staff. Furthermore, empirical research on patient safety practices is necessary to encourage active participation in patient safety activities by patients and family caregivers.

Purpose: Inpatient and residential smoking cessation programs in Korea have demonstrated relatively high quit rates, with residential programs consistently outperforming inpatient ones. However, simple comparisons are limited by differences in participant characteristics and eligibility criteria. This study aimed to determine whether program type independently influences quit rates, using both self-reported and biochemically verified outcomes.Methods: This descriptive study conducted a secondary analysis of data from 17,290 participants enrolled in national smoking cessation services across 18 regional tobacco control centers (2018-2020). Data included demographics, smoking history, and program participation. Quit status at 4 weeks, 12 weeks, and 6 months was assessed through self-report and biochemical verification. Multivariate logistic regression was used to evaluate the independent effect of program type on 6-month quit outcomes.Results: The mean age of participants was 54.8 ± 12.0 years, and 14.5% were women. At 6 months, self-reported quit rates ranged from 16.5% to 34.1% for the inpatient program and from 26.0% to 62.8% for the residential program. Biochemically verified rates ranged from 8.6% to 19.0% (inpatient) and 11.9% to 46.7% (residential). After adjusting for confounders, program type was significantly associated with self-reported quitting (aOR = 0.80; 95% CI = 0.72-0.89; p < .001), but not with biochemically verified quitting (aOR = 0.91; 95% CI = 0.82-1.01; p = .082).Conclusion: Although residential programs showed higher self-reported quit rates, program type did not predict verified cessation. This suggests differences in participant characteristics may drive outcomes. Further research should identify effective, evidence-based components for sustained quitting.

Revealing customer satisfaction through big social data has been an interesting research topic in tourism and hospitality. Big data analysis is an effective way to detect customers’ behaviors in their decision-making. This study aims to perform big social data analysis to reveal whether food quality impacts the relationship between hotel performance criteria and travelers’ satisfaction. A two-stage methodology is developed to address the objectives of this study. The findings demonstrated that there is a positive relationship between eco-friendly hotels’ performance criteria and satisfaction. The results and implications for managers and future research directions are discussed.

Purpose: Although digital solutions could mitigate the challenges faced by older adults living alone(OALA), only a few studies investigated the need for and acceptance of digital health interventions forself-management (DHISMs) among this demographic. Thus, we aim to explore this need and acceptance,along with the contextual factors, among OALA. Methods: A mixed-methods research approach was adopted. We conducted 1) a quantitative survey(n ¼ 191) to investigate the need for and acceptance of DHISMs using a numeric rating scale and 2) aqualitative study (n ¼ 24) based on focus group interviews to explore contextual factors related to thequantitative results. Qualitative data were analyzed using thematic analysis. Results: In the quantitative study, the mean scores for the need for and acceptance of DHISMs were 6.41and 6.53 out of 10, respectively. Emergency response systems had the highest need and acceptancescores, whereas digital interventions for behavioral change (medication adherence, sleep, stress, and dietmanagement) had relatively lower scores. The qualitative analysis revealed two themes and five subthemes:the need for inclusive support for independent living (environmental safety and diverseself-management challenges with limited support) and multidimensional factors related to DHISMacceptance (personal, technological, and relational barriers and facilitators). Conclusions: In the future, the unique and multidimensional factors influencing the need for andacceptance of DHISMs among OALA should be carefully considered to support their self-managementand independent living. Blended care, which involves integrating age-friendly technology withpersonalized human interaction, is pivotal for increasing DHISM acceptance in this population.

Purpose: Self-rated health in individuals with chronic diseases is influenced by various factors, including dietary adherence and physical activity. However, limited research has investigated how these factors relate to self-rated health among people with chronic kidney disease. Therefore, this study aimed to describe self-rated health and identify its associated factors in this population. Methods: This cross-sectional, secondary data analysis utilized datasets from the seventh Korea National Health and Nutrition Examination Survey, which were collected between 2016 and 2018. A total of 557 participants (mean age=74.8 years) with a glomerular filtration rate of <60 mL/min/1.73 m² were included. Data from health interviews and examinations were analyzed to assess self-rated health, dietary adherence, and physical activity. Descriptive and inferential statistical methods were employed for analysis. Results: Among the 557 participants, 42.6% rated their health as poor. Factors such as sex, age, income, smoking history, anxiety/depression, number of comorbidities, glomerular filtration rate, and physical activity were significantly associated with self-rated health. In contrast, dietary adherence did not exhibit a significant association. Conclusion: Understanding the factors associated with self-rated health can inform the development of nursing interventions aimed at improving self-rated health among patients with chronic kidney disease.

Purpose: This study aimed to investigate the association among various adolescent prob- lem behaviors in South Korea, focusing on gender differences. Methods: This secondary analysis was conducted using cross-sectional data from the 19th Korea Youth Risk Behavior Survey, conducted in 2023 which included 52,880 mid- dle and high school students in South Korea. They completed an anonymous self-admin- istered survey regarding problem behaviors (drinking alcohol, smoking, drugs use, and sexual experiences). Data were analyzed using complex-samples chi-square and multiple logistic regression models. Results: Among the 52,880 adolescents, the prevalence rates of alcohol use, smoking, drug use, and sexual experiences were 32.6%, 8.6%, 1.7%, and 6.5%, respectively. Gender differences were observed in alcohol use complex-samples multiple logistic regression models. However, no significant gender difference was found in drug use (p=.250). Four problem behaviors were significantly associated with one other when analyzed as inde- pendent variables (odds ratio [OR], 1.33?10.85). The strongest associations were found between alcohol use and smoking (OR, 10.49?10.85), and between smoking and sexual experiences (OR, 4.91?4.96). Conclusion: This study found significant gender differences in adolescent problem be- haviors, with male adolescents exhibiting higher rates of alcohol use, smoking, and sexu- al experience. Strong associations were observed between alcohol use and smoking, as well as between smoking and sexual experience. These findings suggest the need for in- tegrated intervention strategies that target multiple co-occurring problem behaviors.

Purpose: The majority of adolescents use smartphones, and their overdependence on smartphones has emerged as a serious social issue. Although studies have explored the effect of smartphone overdependence on adolescent problem behaviors, research on its influence on sexual behavior is scarce. This study aimed to examine the association be- tween smartphone overdependence and sexual behavior among adolescents. Methods: This study used data from the 19th Korea Youth Risk Behavior Web-Based Survey conducted in 2023. Smartphone overdependence was the independent variable, and sexual behaviors (sexual intercourse and contraceptive use) were the dependent variables. Multivariate regression analysis was performed to control for confounding variables. Results: The study participants included 52,880 adolescents aged 13?18 years. Among them, 28.0% (n=14,672) were classified as smartphone overdependent, 6.5% (n=3,349) had sexual experience, and 65% (n=2,182) of those with sexual experience reported using contraception. Smartphone overdependence was not significantly associated with sexual experience but was significantly associated with contraceptive use. Adolescents in the non-overdependent group were 1.27 times more likely to use contraception than those in the smartphone overdependent group (95% confidence interval, 1.07?1.52; p<.007). Conclusion: The findings highlight a significant association between smartphone over- dependence and contraceptive use among adolescents. Policy interventions and educa- tional strategies that consider adolescents’ smartphone usage patterns and trait factors are necessary.

Purpose: The purpose of this study is to identify the factors influencing generalized anxiety disorder (GAD) in older adults and to provide effective health management directions for GAD patients. Methods: This study used data from the 9th National Health and Nutrition Survey (2022) and selected 1,666 older adults. The analysis was conducted using the SPSS 26.0 program. A complex sample chi-square test was performed to identify factors related to GAD. Complex sample logistic regression was conducted to determine the factors influencing GAD in the participants. Results: The study results indicated that sex (p=.034), smoking (p=.042), alcohol consumption (p=.003), sleep duration (p=.005), chewing discomfort (p<.001), speaking discomfort (p<.001), and self-rated health (p=.016) were statistically significantly associated with GAD. The multivariate analysis considering the interaction between variables, sleep duration (OR=2.07, p=.031) and chewing discomfort (OR=2.49, p=.008) were identified as factors influencing GAD. Conclusion: Chewing discomfort in older adults affects not only GAD but also leads to a decline in aesthetics and social withdrawal. Therefore, improvements in oral health policy support for oral health promotion and prevention are required. Additionally, education and interventions through community systems should be provided to address sleep issues associated with GAD.

Purpose: Emerging evidence indicates that eating patterns?particularly skipping meals and eating alone?are associated with excess body weight. However, few studies have assessed whether these behaviors contribute to weight gain across different age groups. This study examined the associations of skipping breakfast or dinner, and of eating those meals alone, with overweight or obesity among Korean adults compared to children and adolescents. Methods: This cross-sectional secondary analysis used data from the 2019 Korea National Health and Nutrition Examination Survey. Information on skipping meals, eating alone, and sociodemographic characteristics was obtained via self-report for adults and proxy report for participants under 12 years of age. Overweight or obesity was determined from measured height and weight. Multivariable logistic regression analyses were performed separately by age group. Results: Among adults, eating dinner alone was associated with higher odds of obesity (odds ratio [OR]=1.27, 95% confidence interval [CI]=1.06?1.52). Among adolescents, skipping dinner three or more times per week was associated with higher odds of obesity (OR=2.60, 95% CI=1.04?6.54). No significant associations were observed in children. Skipping breakfast or eating breakfast alone was not significantly associated with overweight or obesity in any age group. Conclusion: Although the cross-sectional design precludes causal inference, the findings suggest age-specific links between eating behaviors and weight status. For adults, reducing solitary dinners may help prevent obesity, whereas for adolescents, preventing frequent dinner skipping could be beneficial. Nursing strategies promoting shared mealtimes in adults and regular dinners in adolescents may help address obesity in Korea.

Purpose: The rising prevalence of smartphone overdependence among adolescents and its detrimental impact on mental health have become a growing concern. This study aimed to investigate the association between smartphone overdependence and the mental health of Korean adolescents. Methods: Participants were drawn from the 16th Korea Youth Risk Behavior Web-based Survey conducted in 2020. The dependent variable as smartphone overdependence, while the main exposure of interest was mental health, encompassing generalized anxiety disorder (GAD), perceived stress, sources of perceived stress, perceived loneliness, and perceived depressive symptoms. The study employed the Rao-Scott chi-square test and multiple logistic regression using IBM SPSS version 26.0. Results: The participants comprised 54,948 adolescents aged 13 to 18 years. Among them, 25.1% (n=13,775) were categorized as smartphone overdependence group. Specifically, 20.3% of adolescents who reported GAD ≥10 and 22.5% of those who reported experiencing high levels of perceived loneliness were identified as smartphone overdependent. The GAD increased a risk of smartphone overdependence by 2.61 times (95% confidence interval [95% CI]: 2.46?2.77). Perceived loneliness was associated with 1.98-fold (95% CI: 1.87?2.09) increased risk of smartphone overdependence. Additionally, conflictwith peers was found to increase the risk of smartphone overdependence by 4.63-fold (95% CI: 3.89?5.52), followed by conflict with parents (odds ratio [OR]: 4.52, 95% CI: 3.84?5.31), and family environment (OR: 4.52, 95% CI: 3.75?5.46). Conclusion: The findings underscore a significant association between smartphone overdependence and mental health in Korean adolescents. Healthcare services to improve their emotional coping and interpersonal skills are necessary.

Purpose: This study aimed to identify the general characteristics and health behaviors of students with non-therapeutic substance use. Methods: This secondary data analysis used data from the 17th Korea Youth Risk Behavior Web-based Survey (2021). Analyses of the 54,848 adolescents used descriptive statisics, the Rao?Scott χ2 test, and logistic regression. Results: The risk factors for substance use among students were anxiety, loneliness, living separately from family, suicidal ideation, e-cigarette use, and high stress. Conclusion: The findings help identify the risk factors for non-therapeutic drug use among adolescents. Since South Korea does not have a drug prevention program for its adolescent population, an educational plan based on these findings could help prevent adolescent substance abuse.

Background Pressure pain hypersensitivity (PPH) is used to measure pain sensitivity in deep tissues, but factors contributing to PPH remain unclear. Abnormal neck and scapula posture are thought to play a role in shoulder pain. Traditional statistical methods like logistic regression have limitations in capturing complex relationships, while machine learning (ML) can model nonlinear relationships effectively. Purpose The purpose of the present study was to develop, evaluate, and compare the predictive performance of ML models and logistic regression for classifying food service workers (FWs) with and without PPH based on postural analysis data. Study design Cross sectional study. Methods FWs (n=150) meeting specific criteria were assessed for PPH and underwent postural analysis. ML algorithms (logistic regression, neural network, random forest, gradient boosting, decision tree, and support vector machine) were used for classification. Model performance was evaluated using the area under the curve (AUC), accuracy, recall, precision, and F1 score. Feature importance was assessed. Results Gradient boosting exhibited the best performance (AUC: 0.867) in classifying PPH, followed by random forest (AUC: 0.822) in the test dataset. Logistic regression performed less effectively (AUC: 0.613). For feature importance analysis, scapular downward rotation ratio, forward head posture, BMI and rounded shoulder angle were the top four important predictors of PPH in gradient boosting model. Conclusions Gradient boosting, along with identified predictors, offers promise for early intervention and risk assessment tools in addressing musculoskeletal pain in food service workers.

PurposeThis study aimed to classify self-care patterns among Korean adults with prediabetes using an unsupervised machine learning approach. The classification was grounded in Orem’s Self-Care Theory, focusing on self-care demands, self-care agencies, and self-care behaviors. MethodsA secondary data analysis was conducted using the 2023 Korea National Health and Nutrition Examination Survey. Variables were selected and categorized according to the theoretical components of Orem’s model. Principal component analysis was applied for dimensionality reduction, followed by K-means clustering to identify distinct self-care pattern groups. All variables were standardized using min-max normalization. Group differences were examined using analysis of variance and the chi-square test. ResultsThree self-care pattern groups were identified: the high self-care performance group, the latent self-care risk group, and the self-care vulnerable group. These groups exhibited distinct profiles across self-care demands, agencies, and behaviors. Significant intergroup differences were also observed in education level, income, health literacy, fasting blood glucose, and hemoglobin A1c levels. ConclusionSelf-care patterns among adults with prediabetes can be effectively classified through unsupervised learning techniques. The findings highlight the importance of developing tailored nursing interventions that consider multidimensional self-care profiles. This study underscores the applicability of Orem’s Self-Care Theory and demonstrates the potential of machine learning in identifying at-risk subgroups for early intervention.

Purpose: Patients in the Intensive Care Unit (ICU) experience a variety of symptoms. This descriptive correlational study aimed to determine the prevalence of symptoms and the physiological and situational factors associated with these symptoms in ICU patients. Methods: We analyzed the Electronic Medical Records (EMRs) of 1,214 cases admitted to and discharged from the ICUs of a university hospital in Seoul over a 1-year period from June to September 2022. This analysis utilized standardized instruments embedded in EMRs and a natural language analysis framework developed by the researchers. Descriptive statistics, the χ2 test, the Fisher exact test, and multivariate logistic regression were employed to identify common symptoms and their related factors. Results: In total, 85.7% of the cases had at least one symptom during their ICU stay, and 36.6% experienced 2 symptoms. Pain was the most frequently experienced symptom, affecting 69.5% of cases, followed by agitation (29.7%), dyspnea (29.7%), and delirium (4.8%). Multivariate logistic regression analysis indicated that the length of ICU stay influenced pain (odds ratio [OR]=1.04; 95% confidence interval [CI], 1.02~1.06; p<.001), delirium (OR=1.08; 95% CI, 1.06~1.11; p<.001), agitation (OR=1.07; 95% CI, 1.05~1.10; p<.001), and dyspnea (OR=1.19; 95% CI, 1.13~1.26; p<.001). Conclusion: Pain, agitation, and dyspnea are common in ICU patients and are associated with the length of their ICU stay. Our study identifies factors related to these symptoms that could be targeted to manage and reduce their occurrence, providing a foundation for future research on various symptom assessment tools and natural language transcripts.

Purpose: This study investigated the relationship between allergic diseases, general anxiety disorder, and depressive symptoms among Korean adolescents. Methods: A secondary analysis was conducted on the findings of the 18th Korea Youth Risk Behavior Survey (2022). The study included 51,850 adolescents and analyzed the relationships among allergic diseases, general anxiety disorder, and depressive symptoms using complex samples logistic regression analysis. Results: Among the Korean adolescents, 12.7% experienced general anxiety disorder, while 28.7% experienced depressive symptoms. The prevalence of allergic diseases was 5.7% for asthma, 36.3% for allergic rhinitis, and 22.2% for atopic dermatitis. General anxiety disorder was associated with asthma and allergic rhinitis but not atopic dermatitis. Depressive symptoms were associated asthma, allergic rhinitis, and atopic dermatitis. Conclusion: Examining the correlation among allergic diseases, general anxiety disorder, and depressive symptoms in adolescents underscores the need for implementing suitable strategies. Moreover, when addressing general anxiety disorder and depressive symptoms in adolescents, it becomes crucial to consider the presence of allergic diseases.

Purpose: This study examined the impact of including weekend days in 24-hour dietary recalls on dietary intake patterns and investigated associations between dietary intake?analyzed using nutrient- and food-group?based categories?and cardiovascular risk factors in adults with metabolic syndrome (MetS). Methods: A cross-sectional study analyzed data from 185 adults aged 40-69 years with metabolic syndrome (MetS), who had either a history of cardiovascular disease or an intermediate-to-high 10-year cardiovascular disease risk. Dietary intake was assessed over three days using 24-hour dietary recalls and analyzed with CAN-Pro 4.0. Results: Overall dietary intake did not differ significantly according to the number of weekend days included, except food-group?based protein intake (p = .030). In the no-weekend group, most nutrients and food groups demonstrated relatively consistent correlations between the 3-day average intake and single-day intake (r ≥ .61). In contrast, correlation coefficients varied widely among groups that included weekend days (r = ?.08 to .97). Further analyses stratified by specific weekend days (saturdays, sundays, and national holidays) revealed significant differences in nutrient-based protein intake (F = 3.38, p = .011). Both nutrient- and food-group?based dietary intakes were significantly associated with cardiovascular risk factors. Conclusion: The number of weekend days included in dietary assessment may influence estimated dietary intake. The observed variability across specific weekend days suggests that using multiple 24-hour dietary assessments and developing nutritional interventions that explicitly account for weekend schedules would improve the accuracy of dietary pattern assessment and the effectiveness of interventions in individuals with MetS.

Purpose: Based on the health belief model and theory of planned behavior, this study investigated how age group (adolescence and emerging adulthood) moderated the relative effects of perceived susceptibility, perceived severity, and subjective norms on preventive behavior against coronavirus disease 2019 (COVID-19). Methods: This secondary data analysis utilized data from adolescents (n=272) and emerging adults (n=239). Hierarchical multiple regression analysis was performed to test the moderating effect of age group on the relationships among variables. Results: Higher perceived susceptibility (β=.21, p<.001), perceived severity (β=.14, p=.002), subjective norms (friends) (β=.26, p<.001), subjective norms (parents) (β=.44, p<.001), and subjective norms (schools) (β=.28, p<.001) enhanced COVID-19 preventive behaviors. Moderated regression analysis showed that subjective norms (friends and school) impacted preventive behavior in adolescents more than in emerging adults. Conclusion: Given the need to increase perceived susceptibility and severity among adolescents and emerging adults, these findings provide baseline data for designing effective COVID-19 prevention interventions that consider the developmental characteristics of different age groups. Interventions by health centers at universities can strengthen COVID-19 preventive behavior among emerging adults. As adolescents are influenced by friends, their peer roles must be strengthened to enhance adherence to COVID-19 preventive guidelines.

PurposeAge at menarche (AAM) is influenced by genetic and environmental factors and is associated with reproductive health outcomes. Therefore, understanding its genetic basis may help predict risks to women’s health. This study aimed to identify genetic variants associated with AAM in the Korean population through a genome-wide association study (GWAS) and investigate the relationship between AAM and early menopause. MethodsIn total, 6,150,556 single nucleotide polymorphisms (SNPs) were generated from full genotyping data of the Health Examinee and Korea Association Resource cohorts, and analyses were conducted on 40,570 selected participants. A GWAS was performed using linear regression analysis with age and body mass index as covariates. A polygenic risk score (PRS) for AAM was constructed and categorized into quartiles, and logistic regression analysis was conducted to assess the association between the PRS for AAM and early menopause. ResultsThe GWAS identified 30 significant SNPs associated with AAM. The most significant SNP was rs314275 (beta = 0.0925, p = 2.74 × 10?12) in the Lin-28 homolog B (LIN28B) gene and the SNP with the largest effect estimate was rs67367692 (beta = 0.1238, p = 5.06 × 10?8) in the matrix metallopeptidase 12 (MMP12) gene. Individuals with a higher PRS for AAM showed an increased risk of early menopause. ConclusionGenetic determinants influence AAM and early menopause in the Korean population. These findings suggest that the genetic factors contributing to late menarche may also increase the risk of early menopause, highlighting the importance of considering genetic risks in women’s health strategies.

The aim of this study was to investigate the effects of heat stress on milk traits in South Korea using comprehensive data (dairy production and climate). The dataset for this study comprised 1,498,232 test-day records for milk yield, fat- and protein-corrected milk, fat yield, protein yield, milk urea nitrogen (MUN), and somatic cell score (SCS) from 215,276 Holstein cows (primiparous: n = 122,087; multiparous: n = 93,189) in 2,419 South Korean dairy herds. Data were collected from July 2017 to April 2020 through the Dairy Cattle Improvement Program, and merged with meteorological data from 600 automatic weather stations through the Korea Meteorological Administration. The segmented regression model was used to estimate the effects of the temperature-humidity index (THI) on milk traits and elucidate the break point (BP) of the THI. To acquire the least-squares mean of milk traits, the generalized linear model was applied using fixed effects (region, calving year, calving month, parity, days in milk, and THI). For all parameters, the BP of THI was observed; in particular, milk production parameters dramatically decreased after a specific BP of THI (p < 0.05). In contrast, MUN and SCS drastically increased when THI exceeded BP in all cows (p < 0.05) and primiparous cows (p < 0.05), respectively. Dairy cows in South Korea exhibited negative effects on milk traits (decrease in milk performance, increase in MUN, and SCS) when the THI exceeded 70; therefore, detailed feeding management is required to prevent heat stress in dairy cows.

Purpose: This study aimed to compare the health expenditure and unmet health care needs and factors associated with these, in single-person households pre- and post-baby boomer generation, and of baby boomers. Methods: This cross-sectional study used secondary data from the 2016 Korea Health Panel Study, which was conducted to investigate the factors associated with health expenditures and unmet healthcare needs of single-person households through hierarchical multiple regression analysis. Results: The subjective health status of a single household showed a significant interaction with pre-baby boomers (β=.16, p=.045) in health expenditure. Identifying as men (OR=1.59, p=.046) and subjective health status (OR=1.90, p=.001) were statistically significant in terms of unmet healthcare needs. However, there was no significant interaction between pre-baby boomers and unmet healthcare needs. Conclusion: Baby boomers are the first to be prepared for their later years in the current aging society. Despite a stable financial status due to vital economic activities, social support for baby boomers is inadequate. The rights guaranteed to family members under the system centered around kinship should also be guaranteed to single-person households.