• Journal of Korean Public Health Nursing
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• v.35 no.3
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• pp.343-355
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• 2021

Purpose: This study aimed to identify the effects of nursing students' ethical awareness, ethical decision-making and attitude toward performance on intention about performance of infection control guidelines in pandemic infectious diseases. Methods: The survey was performed on 163 nursing students in three universities. Data were collected using a structured questionnaires and analyzed with t-test, analysis of variance (ANOVA), Pearson's correlation and multiple regression analysis. Results: Perceived health status, ethical awareness and attitude toward performance of infection control guidelines about major commitment were significant predictive variables. These variables accounted for 48.1% of the variance in major commitment. Conclusion: The findings indicate the necessity of developing educational programs to enhance nursing students's ethical awareness, and increase performance of control guidelines to prepare for the pandemic infectious diseases.

• Journal of the Korean Chemical Society
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• v.44 no.1
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• pp.68-73
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• 2000

In this study, tlhe relationships of high school students' abilities to solve chemistry problems with cognitive variables (logical thinking ability, mental capacity. and learning strategy) and affective variables(self-efficacy, self-concept of ability, learning goal, and attitude toward science) were investigated. The proportion of variance due to the variables for algorithmic and conceptual problem solving ability was studied by a multiple regression analysis. The results indicated that, among the cognitive variables, the logical thinking ability significantly predicted the algorithmic problem solving ability, and the learning strategy was the best predictor of conceptual problem solving ability although not significant. Among the affective variables studied, the self-concept of alility was the significant predictor of both algorithmic and conceptual problem solving abilities. The seif-efficacy was significantly correlated with conceptual problem solving ability, but it had no predictive power.

• Journal of Korean Academy of Nursing
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• v.28 no.2
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• pp.344-357
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• 1998

This study was designed to construct a model that predicts the quality of life of family caregivers with a chronically ill patient. The hypothetical model was developed based on the findings from past studies on quality of life and on the family with a chronically ill patient. Data were collected by self-reported questionnaires from 200 family caregivers in Seoul & Kyung Gi-Do, from May 1 to July 21, 1997. Data were analyzed using descriptive statistics and correlation analysis. The Linear Structural Relationship(LISREL) modeling process was used to find the best fit model which predicts causal relationships among variables. The results are as follows : 1. The overall fit of the hypothetical model to the data was moderate [X$^2$=31.54(df=23, p=.11), GFI=.96, AGFI=.91, RMR=.04]. 2. Paths of the model were modified by considering both its theoretical implication and the statistical significance of the parameter estimates. Compared to the hypothetical model, the revised model has become parsimonious and had a better fit to the data expect chi-square value(GFI=.95, AGFI=.91, RMR=.04). 3. Some of predictive factors, especially economic status, physical ability to perform daily-life activity, period after disease-onset, social support and fatigue revealed indirect effects on the quality of life of family caregivers with a chronically ill patient. 4. The factors, burden and role satisfaction revealed significant direct effects on the quality of life of family caregivers with a chronically ill patient. 5. All predictive variables of quality of life of family caregivers with a chronically ill patient, especially economic status, physical ability to perform daily-life activity, period after disease-onset, social support, fatigue, burden and role satisfaction explained 38.0% of the total variance in the model. In conclusion, the derived model in this study is considered appropriate in explaining and predicting quality of life of family caregivers with a chronically ill patient. Therefore it can effectively be used as a reference model for further studies and suggests direction in nursing practice.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.1
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• pp.40-49
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• 2004

In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Self-Organizing Polynomial Neural Networks(SOPNN), discuss a comprehensive design methodology and carry out a series of numeric experiments. The conventional SOPNN is based on the extended Group Method of Data Handling(GMDH) method and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons (or nodes) located in each layer through a growth process of the network. Moreover it does not guarantee that the SOPNN generated through learning has the optimal network architecture. But the proposed GA-based SOPNN enable the architecture to be a structurally more optimized network, and to be much more flexible and preferable neural network than the conventional SOPNN. In order to generate the structurally optimized SOPNN, GA-based design procedure at each stage (layer) of SOPNN leads to the selection of preferred nodes (or PNs) with optimal parameters- such as the number of input variables, input variables, and the order of the polynomial-available within SOPNN. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. A detailed design procedure is discussed in detail. To evaluate the performance of the GA-based SOPNN, the model is experimented with using two time series data (gas furnace and NOx emission process data of gas turbine power plant). A comparative analysis shows that the proposed GA-based SOPNN is model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of Korean Academy of Nursing
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• v.42 no.3
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• pp.434-442
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• 2012

Purpose: The purpose of this predictive study was to identify factors affecting health related quality of life (HRQoL) in patients with rheumatoid arthritis (RA). Methods: The participants in this study were 131 patients with RA who were recruited from the outpatient clinic of a university hospital in Seoul. Disease activity in rheumatoid arthritis was evaluated by calculating the Disease Activity Score 28. Disability in activities of daily living (ADL) was assessed with the Korean Health Assessment Questionnaire, and depression with The Center for Epidemiologic Studies Depression Scale. HRQoL was evaluated using The Short Form 36 Health Survey. Data were analyzed using descriptive statistics, correlation, and hierarchical multiple regression. Results: Pain, disability in ADL, disease activity, and depression correlated negatively with physical and mental dimensions of HRQoL. But hierachical multiple regression analysis revealed that disability in ADL and depression were the only variables negatively influencing physical and mental QoL after adjustment for influences of sociodemographic variables. Conclusion: Results of this study suggest that disability in ADL and depression, rather than disease activity and pain have profound effects on HRQoL in patients with RA. Further studies are needed to assess the predictive ability of disease activity and pain on HRQoL in this population.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.3
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• pp.1019-1024
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• 2015

Background: Survival of breast cancer patients depends on a number of factors which are not only prognostic but are also predictive. A number of studies have been carried out worldwide to find out prognostic and predictive significance of different clinicopathological and molecular variables in breast cancer. This study was carried out at Nuclear Medicine, Oncology and Radiotherapy Institute (NORI), Islamabad, to find out the impact of different factors on overall survival of breast cancer patients coming from Northern Pakistan. Materials and Methods: This observational retrospective study was carried out in the Oncology Department of NORI Hospital. A total of 2,666 patients were included. Data were entered into SPSS 20. Multinomial logistic regression analysis was performed to determine associations of different variables with overall survival. P values <0.05 were considered significant. Results: The mean age of the patients was 47.6 years, 49.5% being postmenopausal. Some 1,708 were ER positive and 1,615 were PR positive, while Her 2 neu oncogene positivity was found in 683. A total of 1,237 presented with skin involvement and 426 had chest wall involvement. Some 1,663 had > 5cm tumors. Lymph node involvement was detected in 2,131. Overall survival was less than 5 years in 669 patients, only 324 surviving for more than 10 years, and in the remainder overall survival was in the range of 5-10 years. Conclusions: Tumor size, lymph node metastases, receptor status, her 2 neu positivity, skin involvement, and chest wall involvement have significant effects whereas age and menopausal status have no significant effect on overall survival of breast cancer patients in Pakistan.

• Journal of Trauma and Injury
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• v.22 no.2
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• pp.154-160
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• 2009

Purpose: This study aimed to determine new criteria for detecting independent factors with high sensitivity in cases of cervical spine injury. We compared the sensitivity, the specificity, and the false negative predictive value (NPV) of plain radiographs with those of computed tomography for cervical spine injury in patients with minor head injury. Methods: We retrospectively reviewed the cases of 357 patients who underwent both cervical plain radiographs and computer tomography from January 2006, to September 2008. Patients were divided into two groups: the cervical spine injury group and the no cervical spine injury group. New criteria were organized based on variables that had significant differences in the logistic regression test. Results: Among the 357 patients, 78 patients had cervical spine injuries. The average age was $43.9{\pm}15.2$ yrs old, and the male-to-female ratio was 1.90. The most common mechanism of injury was motor vehicle accidents. There was a significant difference in loss of consciousness, Glasgow Coma Scale (GCS)=14, neurologic deficit, posterior neck tenderness, and abnormality of the cervical plain radiographs between the two groups on the logistic regression test. New criteria included the above five variables. If a patient has at least variable, the area under the ROC curve of the new criteria was 0.850, and the sensitivity and the false NPV were 87.2% and 5.2%, respectively. Conclusion: New criteria included loss of consciousness, GCS=14, neurologic deficit, posterior neck tenderness, and abnormality of the cervical plain radiographs. If the patient had at least 1 variable, he or she could have a of cervical spine injury with a sensitivity of 87.2% and a false NPV of 5.2%.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.16 no.2
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• pp.172-182
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• 2006

Self administered checklist is needed to be developed to evaluate ergonomic risk factors. This study was conducted to develop self administered form of American National Standards Institute (ANSI) Z-365 checklist which represents comprehensive ergonomic risk factors, and to evaluate validity of this checklist. This study had been conducted from May 2004 to July 2005, of which subjects were 147 workers from 4 workplaces. Response rates for every items of self administered form of ANSI Z-365 were evaluated. To estimate the validity of checklist, relationship between the checklist grade that ANSI recommended and work-related musculoskeletal disorders (WMSDs) symptom were calculated with and without adjustment of related variables. To evaluate the utility of checklist, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Because response rates of almost items were over 90 %, item development was successful. Because the checklist was related with WMSDs symptom after adjusting related variables, the checklist might represents ergonomic risk well. Because of low sensitivity and NPV, high specificity and PPV, the checklist is not suitable for screening tool. The checklist has better relationship with more severe symptom. Because of high specificity of the checklist, using it with high sensitive tool would enhance it's utility. Further study to develop high sensitive and comprehensive self administered ergonomic checklist is needed.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.423-434
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• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.227-235
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• 2018

The purpose of this study was to analyze the factors affecting on pre-service early childhood teachers' adoption intention of Robot-based education. For this purpose, the survey was conducted on 259 college students and the collected data was analyzed using SPSS 23.0. T-test and one-way ANOVA were used to compare the differences of adoption intention and predictive factors according to pre-service early childhood teachers' background variables. In addition, multiple linear regression analysis was conducted to analyze influence of perceived ease of use, perceived efficacy, innovative will, and social effect on adoption intention. The results were found that adoption intention and predictive factors did not show any significant difference according to background variables and that perceived ease of use and perceived efficacy influenced on pre-service early childhood teachers' adoption intention. Moreover, innovative will and social effect had an effect on perceived ease of use and perceived ease of use and social effect had an effect on perceived efficacy.