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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

This cross-sectional study was done to compare factors influencing young adolescents' aggression according to family structure.

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.

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).

Nurses working with young adolescents should consider family structure-specific factors influencing aggression in this population.

This study was conducted to determine the predictors of employment intention for mentally disabled persons.

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.

The predictors influencing employment intention of the mentally disabled person were observed as employment desire (β=.48), guardian's expectation (β=.26), professional's support (β=.23), financial management (β=.10), eating habits (β=.07), and quality of life (β=-.01). Six factors explained 61.1% of employment intention of mentally disabled persons.

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.