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DNA*

PURPOSE: The purpose of this study was to identify the effect of supportive nursing intervention on the anxiety and nursing satisfaction of mothers with children undergoing open-heart surgery. METHODS: The research design involved a non-equivalent control group pretest-posttest non synchronized design. The subjects consisted of 43 mothers of children who were expected to undergo open heart surgery, and were divided into two groups; an experimental group of 22 and a control group of 21. The experiment was administered to the experimental group a total of four times, following supportive nursing intervention protocols. The research tools used were Spielberger's State Anxiety Inventory for anxiety and Park Jung-Eun's nursing satisfaction. The data were analyzed using the chi-square-test, and t-test with SPSS/WIN 12.0 program. RESULTS: Hypothes 1, 'The experimental group who are given supportive nursing intervention will have a lower anxiety score than the control group' was supported(t=5.658, p=.000). Hypothesis 2, 'The experimental group who are given supportive nursing intervention will have a higher nursing satisfaction score than the control gropu wasl supported(t=-9.549, p=.000). CONCLUSION: The supportive nursing intervention protocol was effective in reducing anxiety and increasing the nursing satisfaction of mothers with children undergoing open-heart surgery.
Anxiety* ; Child* ; Humans ; Mothers* ; Nursing* ; Research Design ; Thoracic Surgery

Purpose: This study aimed to identify the key factors in nursing workforce management for pandemic response in general hospitals and long-term care hospitals and to analyze the relative importance of these factors. Methods: A validity test was conducted with experts to select four categories and 30 key factors related to nursing workforce management for pandemic response. Surveys were collected from 25 nursing managers in general hospitals and 21 nursing managers in long-term care hospitals, and the relative importance of the key factors was analyzed using the analytic hierarchy process method. Results: Differences were found between the two groups in the relative importance of nursing workforce management for pandemic response. Specifically, the highest-ranking category was “workforce recruitment and redeployment” for general hospitals, but “workforce support and protection” for long-term care hospitals. The most important factor regarding nursing workforce management was the “nurse-to-patient ratio” for both general and long-term care hospitals. Conclusion General and long-term care hospitals need to establish nursing workforce management strategies to effectively respond to pandemics with appropriate consideration of the relative importance and prioritization of key factors based on hospital characteristics.

Purpose: This study aimed to identify the key factors in nursing workforce management for pandemic response in general hospitals and long-term care hospitals and to analyze the relative importance of these factors. Methods: A validity test was conducted with experts to select four categories and 30 key factors related to nursing workforce management for pandemic response. Surveys were collected from 25 nursing managers in general hospitals and 21 nursing managers in long-term care hospitals, and the relative importance of the key factors was analyzed using the analytic hierarchy process method. Results: Differences were found between the two groups in the relative importance of nursing workforce management for pandemic response. Specifically, the highest-ranking category was “workforce recruitment and redeployment” for general hospitals, but “workforce support and protection” for long-term care hospitals. The most important factor regarding nursing workforce management was the “nurse-to-patient ratio” for both general and long-term care hospitals. Conclusion General and long-term care hospitals need to establish nursing workforce management strategies to effectively respond to pandemics with appropriate consideration of the relative importance and prioritization of key factors based on hospital characteristics.

Purpose: This study aimed to identify the key factors in nursing workforce management for pandemic response in general hospitals and long-term care hospitals and to analyze the relative importance of these factors. Methods: A validity test was conducted with experts to select four categories and 30 key factors related to nursing workforce management for pandemic response. Surveys were collected from 25 nursing managers in general hospitals and 21 nursing managers in long-term care hospitals, and the relative importance of the key factors was analyzed using the analytic hierarchy process method. Results: Differences were found between the two groups in the relative importance of nursing workforce management for pandemic response. Specifically, the highest-ranking category was “workforce recruitment and redeployment” for general hospitals, but “workforce support and protection” for long-term care hospitals. The most important factor regarding nursing workforce management was the “nurse-to-patient ratio” for both general and long-term care hospitals. Conclusion General and long-term care hospitals need to establish nursing workforce management strategies to effectively respond to pandemics with appropriate consideration of the relative importance and prioritization of key factors based on hospital characteristics.

Purpose: This study aimed to identify the key factors in nursing workforce management for pandemic response in general hospitals and long-term care hospitals and to analyze the relative importance of these factors. Methods: A validity test was conducted with experts to select four categories and 30 key factors related to nursing workforce management for pandemic response. Surveys were collected from 25 nursing managers in general hospitals and 21 nursing managers in long-term care hospitals, and the relative importance of the key factors was analyzed using the analytic hierarchy process method. Results: Differences were found between the two groups in the relative importance of nursing workforce management for pandemic response. Specifically, the highest-ranking category was “workforce recruitment and redeployment” for general hospitals, but “workforce support and protection” for long-term care hospitals. The most important factor regarding nursing workforce management was the “nurse-to-patient ratio” for both general and long-term care hospitals. Conclusion General and long-term care hospitals need to establish nursing workforce management strategies to effectively respond to pandemics with appropriate consideration of the relative importance and prioritization of key factors based on hospital characteristics.

OBJECTIVES: The aim of this study was to assess the change in oral health-related quality of life among patients with head & neck cancer who received radiotherapy. METHODS: A total of 40 patients who were diagnosed as having head and neck cancer and scheduled to have radiotherapy were enrolled in this study; however, only 25 patients were included in the final analysis. Prior to radiotherapy, a dentist performed an oral examination to check for the presence of decayed and missing teeth, plaque, and determine the gingival index. Oral health-related quality of life was assessed using the OHIP-14 questionnaire. Eight weeks after starting radiotherapy, oral health-related quality of life was re-evaluated using the same questionnaire. RESULTS: The mean age of the participants was 60.20 (±7.29) years, and 22 (88.8%) of them were men. The majority of the participants were diagnosed as having squamous cell carcinoma (68.0%). The total OHIP-14 score was significantly decreased from 56.20 (±13.50) at baseline to 45.72 (±10.98) eight weeks after radiotherapy. In addition, according to subjective oral health at baseline, the observed change in the OHIP-14 score was significantly different. CONCLUSIONS: Oral health-related quality of life was significantly lowered after radiotherapy in patients with head and neck cancer.
Carcinoma, Squamous Cell ; Dentists ; Diagnosis, Oral ; Head and Neck Neoplasms* ; Head* ; Humans ; Male ; Oral Health ; Periodontal Index ; Quality of Life* ; Radiotherapy* ; Tooth

BACKGROUND: Mycobacterium tuberculosis is one of the most clinically significant infectious agents. Especially during mass outbreaks, accurate identification and monitoring are required. The proportion of Beijing family members is very high among infecting strains, and spoligotyping is not suitable for strain typing. Therefore, we studied the homogeneity of isolates using the mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR) method and identified its utility for carrying out molecular epidemiologic analysis. METHODS: Eighty-one clinical M. tuberculosis isolates that had previously been analyzed by spoligotyping were used in this study. We used the 12 standard MIRU loci and further four exact tandem repeat (ETR) loci (ETR-A, -B, -C, and -F). Four strains each of randomly selected Beijing and Beijing-like families were subjected to IS6110- restriction fragment length polymorphism analysis. RESULTS: All 81 samples showed amplification products of all VNTR loci, and all of them showed differences in at least one locus. The calculation of the Hunter-Gaston diversity index (HGDI) for MIRU-VNTR gave the value of 0.965. Discriminatory index in the six loci (MIRU-10, -16, -26, -31, -39, and ETR-F) were found to be highly discriminated (HGDI >0.6). Beijing and Beijing-like family isolates were discriminated into different MIRU-VNTR types. CONCLUSIONS: MIRU-VNTR analysis by using well-selected loci can be useful in discriminating the clinical M. tuberculosis isolates in areas where the Beijing family is predominant.
Bacterial Typing Techniques/*methods ; DNA, Bacterial/analysis ; Genotype ; Humans ; *Minisatellite Repeats ; Mycobacterium tuberculosis/*classification/genetics/isolation & purification ; Polymerase Chain Reaction ; Republic of Korea ; Tuberculosis/diagnosis/*microbiology

PURPOSE: This study was done to identify the effects of individual postpartum breast-feeding education on adaptation, attitude and practice of breast-feeding in primiparas. METHODS: A quasi-experimental nonequivalent design was used to examine the effects of individual postpartum breast-feeding education among primiparas. The data were analyzed using chi2-test, Fisher's exact test and paired t-test. RESULTS: There was a significant difference in breast-feeding adaptation (t=-12.94, p<.001), breast-feeding attitude (t=-2.71, p=.011) and breast-feeding practice (chi2=16.47, p<.001) between the group education (experimental group I) and individual education after group education (experimental group II). CONCLUSION: The results indicate that individual education on breast-feeding compared to group education has more positive effects on increasing breast-feeding adaptation, attitude and practice in primiparas. This result also indicates that many primiparas should be given opportunities of various types of education to improve breast-feeding practice such as individual approaches and postpartum breast-feeding education programs.
Breast Feeding ; Postpartum Period

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.
Adult ; Airway Extubation/*psychology ; Female ; Humans ; Intensive Care Units ; Intubation, Intratracheal ; Male ; Middle Aged ; *Models, Theoretical ; Nonlinear Dynamics ; Risk Factors