Topic Modeling and Keyword Network Analysis of News Articles Related to Nurses before and after “the Thanks to You Challenge” during the COVID-19 Pandemic

Purpose@#This study was conducted to assess public awareness and policy challenges faced by practicing nurses. @*Methods@#After collecting nurse-related news articles published before and after ‘the Thanks to You Challenge’ campaign (between December 31, 2019, and July 15, 2020), keywords were extracted via preprocessing. A three-step method keyword analysis, latent Dirichlet allocation topic modeling, and keyword network analysis was used to examine the text and the structure of the selected news articles. @*Results@#Top 30 keywords with similar occurrences were collected before and after the campaign. The five dominant topics before the campaign were: pandemic, infection of medical staff, local transmission, medical resources, and return of overseas Koreans. After the campaign, the topics ‘infection of medical staff’ and ‘return of overseas Koreans’ disappeared, but ‘the Thanks to You Challenge’ emerged as a dominant topic. A keyword network analysis revealed that the word of nurse was linked with keywords like thanks and campaign, through the word of sacrifice. These words formed interrelated domains of ‘the Thanks to You Challenge’ topic. @*Conclusion@#The findings of this study can provide useful information for understanding various issues and social perspectives on COVID-19 nursing. The major themes of news reports lagged behind the real problems faced by nurses in COVID-19 crisis. While the press tends to focus on heroism and whole society, issues and policies mutually beneficial to public and nursing need to be further explored and enhanced by nurses.

Topic Modeling and Keyword Network Analysis of News Articles Related to Nurses before and after “the Thanks to You Challenge” during the COVID-19 Pandemic

Purpose@#This study was conducted to assess public awareness and policy challenges faced by practicing nurses. @*Methods@#After collecting nurse-related news articles published before and after ‘the Thanks to You Challenge’ campaign (between December 31, 2019, and July 15, 2020), keywords were extracted via preprocessing. A three-step method keyword analysis, latent Dirichlet allocation topic modeling, and keyword network analysis was used to examine the text and the structure of the selected news articles. @*Results@#Top 30 keywords with similar occurrences were collected before and after the campaign. The five dominant topics before the campaign were: pandemic, infection of medical staff, local transmission, medical resources, and return of overseas Koreans. After the campaign, the topics ‘infection of medical staff’ and ‘return of overseas Koreans’ disappeared, but ‘the Thanks to You Challenge’ emerged as a dominant topic. A keyword network analysis revealed that the word of nurse was linked with keywords like thanks and campaign, through the word of sacrifice. These words formed interrelated domains of ‘the Thanks to You Challenge’ topic. @*Conclusion@#The findings of this study can provide useful information for understanding various issues and social perspectives on COVID-19 nursing. The major themes of news reports lagged behind the real problems faced by nurses in COVID-19 crisis. While the press tends to focus on heroism and whole society, issues and policies mutually beneficial to public and nursing need to be further explored and enhanced by nurses.

An Exploratory Study on the Policy for Facilitating of Health Behaviors Related to Particulate Matter: Using Topic and Semantic Network Analysis of Media Text

Purpose@#This study aimed to analyze the mass and social media contents and structures related to particulate matter before and after the policy enforcement of the comprehensive countermeasures for particulate matter, derive nursing implications, and provide a basis for designing health policies. @*Methods@#After crawling online news articles and posts on social networking sites before and after policy enforcement with particulate matter as keywords, we conducted topic and semantic network analysis using TEXTOM, R, and UCINET 6. @*Results@#In topic analysis, behavior tips was the common main topic in both media before and after the policy enforcement. After the policy enforcement, influence on health disappeared from the main topics due to increased reports about reduction measures and government in mass media, whereas influence on health appeared as the main topic in social media. However semantic network analysis confirmed that social media had much number of nodes and links and lower centrality than mass media, leaving substantial information that was not organically connected and unstructured. @*Conclusion@#Understanding of particulate matter policy and implications influence health, as well as gaps in the needs and use of health information, should be integrated with leadership and supports in the nurses’ care of vulnerable patients and public health promotion.

Effects of Trait Anger and Anger Expression on Job Satisfaction and Burnout in Preceptor Nurses and Newly Graduated Nurses: A Dyadic Analysis

PURPOSE: The preceptorenewly graduated nurse (NGN) relationship is integral to the successful experience of clinical teaching and learning and new nurses' transition. However, interpersonal conflicts between them are common. Little is known whether their anger contributes to their level of job satisfaction and burnout. This study aimed to examine the effects of each nurse's anger on job satisfaction and burnout in preceptoreNGN dyads.METHODS: A cross-sectional, correlational survey design was used. This study involved 121 preceptor enewly graduate nurse dyads in two hospitals in South Korea. Nurses completed a questionnaire about demographics, the State-Trait Anger Expression Inventory-Korean version, a job satisfaction measure, and the Copenhagen Burnout Inventory. This study adopted the Actor-Partner Interdependence Model to handle dyadic data.RESULTS: Preceptor nurses reported higher frequencies of feeling anger than did new nurses and appear to have higher levels of trait anger, anger-out, and burnout. Both the preceptors' and NGNs' trait anger was positively associated with preceptors' burnout. Suppressing anger was closely related to the nurses' own job satisfaction and burnout. Preceptors with a higher level of anger-control had higher job satisfaction, and NGNs with a higher level of anger-control had less burnout.CONCLUSION: The results indicate that preceptors and new nurses appear to experience significant anger, which is closely associated with their job satisfaction and burnout during their preceptorship. Anger management training programs geared toward educating both preceptors and new nurses about appropriate anger expression in the workplace should be developed to retain valuable nurses.

Development and Analysis of System Dynamics Model for Predicting on the Effect of Patient Transfer Counseling with Nurses

PURPOSE: This study aimed to construct a management model for patient transfer in a multilevel healthcare system and to predict the effect of counseling with nurses on the patient transfer process. METHODS: Data were collected from the electronic medical records of 20,400 patients using the referral system in a tertiary hospital in Seoul from May 2015 to April 2017. The data were analyzed using system dynamics methodology. RESULTS: The rates of patients who were referred to a tertiary hospital, continued treatment, and were terminated treatment at a tertiary hospital were affected by the management fee and nursing staffing in a referral center that provided patient transfer counseling. Nursing staffing in a referral center had direct influence on the range of increase or decrease in the rates, whereas the management fee had direct influence on time. They were nonlinear relations that converged the value within a certain period. CONCLUSION: The management fee and nursing staffing in a referral center affect patient transfer counseling, and can improve the patient transfer process. Our findings suggest that nurses play an important role in ensuring smooth transitions between clinics and hospitals.

Model for Unplanned Self Extubation of ICU Patients Using System Dynamics Approach

PURPOSE: In this study a system dynamics methodology was used to identify correlation and nonlinear feedback structure among factors affecting unplanned extubation (UE) of ICU patients and to construct and verify a simulation model. METHODS: Factors affecting UE were identified through a theoretical background established by reviewing literature and preceding studies and referencing various statistical data. Related variables were decided through verification of content validity by an expert group. A causal loop diagram (CLD) was made based on the variables. Stock & Flow modeling using Vensim PLE Plus Version 6.0b was performed to establish a model for UE. RESULTS: Based on the literature review and expert verification, 18 variables associated with UE were identified and CLD was prepared. From the prepared CLD, a model was developed by converting to the Stock & Flow Diagram. Results of the simulation showed that patient stress, patient in an agitated state, restraint application, patient movability, and individual intensive nursing were variables giving the greatest effect to UE probability. To verify agreement of the UE model with real situations, simulation with 5 cases was performed. Equation check and sensitivity analysis on TIME STEP were executed to validate model integrity. CONCLUSION: Results show that identification of a proper model enables prediction of UE probability. This prediction allows for adjustment of related factors, and provides basic data do develop nursing interventions to decrease UE.

Non-linear System Dynamics Simulation Modeling of Adolescent Obesity: Using Korea Youth Risk Behavior Web-based Survey

PURPOSE: The purpose of this study was to develop a system dynamics model for adolescent obesity in Korea that could be used for obesity policy analysis. METHODS: On the basis of the casual loop diagram, a model was developed by converting to stock and flow diagram. The Vensim DSS 5.0 program was used in the model development. We simulated method of moments to the calibration of this model with data from The Korea Youth Risk Behavior Web-based Survey 2005 to 2013. We ran the scenario simulation. RESULTS: This model can be used to understand the current adolescent obesity rate, predict the future obesity rate, and be utilized as a tool for controlling the risk factors. The results of the model simulation match well with the data. It was identified that a proper model, able to predict obesity probability, was established. CONCLUSION: These results of stock and flow diagram modeling in adolescent obesity can be helpful in development of obesity by policy planners and other stakeholders to better anticipate the multiple effects of interventions in both the short and the long term. In the future we suggest the development of an expanded model based on this adolescent obesity model.

A Development and Evaluation of Nursing KMS using QFD in Outpatient Departments

PURPOSE: This study was done to develop and implement the Nursing KMS (knowledge management system) in order to improve knowledge sharing and creation among clinical nurses in outpatient departments. METHODS: This study was a methodological research using the 'System Development Life Cycle': consisting of planning, analyzing, design, implementation, and evaluation. Quality Function Deployment (QFD) was applied to establish nurse requirements and to identify important design requirements. Participants were 32 nurses and for evaluation data were collected pre and post intervention at K Hospital in Seoul, a tertiary hospital with over 1,000 beds. RESULTS: The Nursing KMS was built using a Linux-based operating system, Oracle DBMS, and Java 1.6 web programming tools. The system was implemented as a sub-system of the hospital information system. There was statistically significant differences in the sharing of knowledge but creating of knowledge was no statistically meaningful difference observed. In terms of satisfaction with the system, system efficiency ranked first followed by system convenience, information suitability and information usefulness. CONCLUSION: The results indicate that the use of Nursing KMS increases nurses' knowledge sharing and can contribute to increased quality of nursing knowledge and provide more opportunities for nurses to gain expertise from knowledge shared among nurses.

Comparison of the Factors Influencing Young Adolescents' Aggression according to Family Structure

PURPOSE: This cross-sectional study was done to compare factors influencing young adolescents' aggression according to family structure. METHODS: Participants were 680 young adolescents aged 11 to 15 years (113 in single father families, 136 in single mother families, 49 in grandparent families, and 382 in both-parent families). All measures were self-administered. Data were analyzed using SPSS 18.0 program and factors affecting young adolescents' aggression were analyzed by stepwise multiple regression. RESULTS: Levels of young adolescents' aggression and all variables were significantly different among the four family structure groups. Factors influencing young adolescents' aggression were also different according to these 4 groups. For single father families, depression-anxiety and family hardiness significantly predicted the level of young adolescents' aggression (adjusted R square=.37, p<.001). For single mother families, depression-anxiety, gender, and friends' support significantly predicted the level of young adolescents' aggression (adjusted R square=.58, p<.001). For grandparent families, depression-anxiety and family support significantly predicted the level of young adolescents' aggression (adjusted R square=.58, p<.001). For both-parent families, depression-anxiety, family hardiness, and friends' support significantly predicted the level of young adolescents' aggression (adjusted R square=.48, p<.001). CONCLUSION: Nurses working with young adolescents should consider family structure-specific factors influencing aggression in this population.

Effects of Sasa Borealis Leaf Extract on the Glucose Tolerance of Major Foods for Carbohydrate

Sasa borealis leaf has been known to have anti-diabetic properties. In this study, we tried to evaluate the effects of Sasa borealis leaf extract (SBE) on the inhibition of alpha-glucosidase activity and postprandial glycemic response following ingestion of four carbohydrate-rich foods; cooked rice, ramen (instant noodle), noodle, and bread. Fourteen healthy female adults consumed 50 g of glucose (control) or one of the four foods containing 50 g of available carbohydrate with or without 2,000 mg of SBE. The activity of alpha-glucosidase was inhibited dose-dependently by SBE. With SBE, blood glucose concentration at 15 min and the positive area under the curve (AUC) of postprandial glycemic response at 15 min and 30 min after consuming each of the four foods were reduced significantly. As the result, total positive AUC during 120 min was decreased in case of taking cooked rice or bread. Glycemic index and glycemic load of the four foods were declined from 13% to 23% with SBE. The results of this study suggest that SBE may be effective for postprandial glucose control by inhibiting alpha-glucosidase activity.

Predictors of Employment Intention for Mentally Disabled Persons / 간호학회지

PURPOSE: This study was conducted to determine the predictors of employment intention for mentally disabled persons. METHODS: Mentally disabled persons who had participated in rehabilitation programs in one of 16 mental health centers and 9 community rehabilitation centers located in Seoul and Kyunggi province were recruited for this study. A random sampling method was used and 414 respondents were used for final analysis. Data was analyzed by Pearson's correlation, and stepwise multiple regression using the SPSS Win 14.0. RESULTS: The predictors influencing employment intention of the mentally disabled person were observed as employment desire (beta=.48), guardian's expectation (beta=.26), professional's support (beta=.23), financial management (beta=.10), eating habits (beta=.07), and quality of life (beta=-.01). Six factors explained 61.1% of employment intention of mentally disabled persons. CONCLUSION: The employment intention of a mentally disabled person was influenced by employment desire, diet self-efficacy, guardian's expectation, professional's support, quality of life, financial management and eating habits.

Clinical and Genetic Characteristics in Patients of Charcot-Marie-Tooth type 2A with Mitofusin 2 (MFN2) Mutations

BACKGROUND: Mitofusin 2 (MFN2) is a membrane protein and is an essential component of mitochondrial fusion machinery. Mitochondrial fusion is essential for various biological functions in mammalian cells. Thus mutations in MFN2 are the underlying cause of Charcot-Marie-Tooth neuropathy type 2A (CMT2A). However, there has been no reports investigating the MFN2 genes in Korean CMT patients. Therefore, we investigated to find the clinical and genetic characteristics in Korean patients with the MFN2 gene mutation. METHODS: We examined the mutations of the MFN2 gene in 137 Korean CMT families. According to criteria from the European CMT consortium, CMT2 was 45 families. Mutations were confirmed by both strands sequencing. Nerve conduction studies were carried out in CMT patients having each mutation. RESULTS: Eight pathogenic mutations were found in 10 families. Six mutations (Leu92Pro, Gly127Asp, His165Arg, Ser263Pro, Arg364Trp, Met376Thr) were determined to be novel, and those were not detected in the 100 healthy controls. A de novo missense mutation was found in three CMT families (30%). The frequency of the MFN2 mutation was 22.2%, which was higher than those found in the Cx32 mutation. In CMT2A, the frequencies with early age at onset (<10 years) and flat feet were 46.2%. CONCLUSIONS: We found MFN2 mutations in patients with sporadic or dominantly inherited CMT. In the majority of cases with CMT type 2, the axonal neuropathy, may be due to MFN2 mutations.

The Impacts of Consumer's Subjective Health Literacy on Health Websites Acceptance and Empowerment / 대한의료정보학회지

OBJECTIVE: The purpose of this study was to analyze the impact of consumer's subjective health literacy on health information websites acceptance and empowerment. METHODS: Data were collected from people who had used health information website. Theoretical model was developed based on TAM(Technology Acceptance Model), and structural equation modeling(SEM) using Lisrel 8.5 was applied to test the relationship of hypotheses. RESULTS: The final trimmed model resulted in a proper solution that exhibited adequate fit. This study supported that consumer's subjective health literacy was found to have a significant effect on empowerment by using health information websites. CONCLUSION: This study showed the use of health information website is worthy of strengthening of consumer's empowerment, which can be expected to contribute to patient's active participation in health management.