Purpose: The purpose of this study was to develop a tool to assess the severity of illness in high risk newborns. Method: The research design was a methodological study. The tool was developed in 4 stages: first, preliminary items were developed based on a questionnaire about the severity of illness index that was given to 8 health professionals in Neonatal Intensity Care Units (NICU) second, a panel of specialists reduced the preliminary items using 3 validity tests; third, final items were selected from the results of a pre-test. Finally, from July 2005 to May 2006, reliability and validity were tested with a sample of 160 high risk newborns admitted to the NICU. Results: The final tool to identify the severity of illness index in high risk newborns consisted 39 items and Cronbach's alpha coefficient for internal consistency was .922. Using factor analysis, 4 factors were extracted and these factors explained 54.451% of the total variance. Conclusion: The instrument for assessing the severity of illness in high risk newborns developed in this study was identified as a tool with a high degree of reliability and validity. In this sense, this tool can be effectively utilized for assessing and implementing care for high risk newborns.
Rheumatoid arthritis, unlike other chronic diseases, causes the patients to experience uncertainty in their daily lives and thus to feel threat on their emotional comfort because of inconsistent and unpredictable symptoms such as pain. Therefore, a theoretical framework is needed for explanation of uncertainty in patients having rheumatoid arthritis. A hypothetical model was constructed on the basis of Mishel's Uncertainty Theory and other literature review. The model included 9 theoretical concepts and 19 paths. Subjects of the study constituted 330 partients who visited outpatient clinics of two university hospitals and one general hospital in Seoul. Self report questionnaires were used to measure the variables affecting uncertainty. Reliability coefficients of these instruments were found Cronbach's Alpha=$.70{\sim}.94$. In data analysis, SAS program and PC-LISREL 8.03 computer program were utilized for descriptive statistics and covariance structure analysis. The results of covariance structure analysis for model fitness were as follows : 1) Hypothetical model showed a good fit to the empirical data : Chi-square($X^2$)=41.81 (df=11, P=.000), Goodness of Fit Index=.974, Root Mean Square Residual=.049, Normed Fit Index=.928, Non Normed Fit Index=.814. 2) For the validity and the parcimony of model, a modified model was constructed by appending 2 paths and deleting 5 paths according to the criteria of statistical significance and meaningfulness. 3) The results of hypothesis testing were as follows : (1) Educational level, event familiarity and severity of illness had a direct effect on uncertainty : Event congruency had both direct and indirect effect on uncertainty : Credible authority and symptom consistency had a nonsignificant direct effect on uncertainty, (2) Illness duration, symptom consistency, and event congruency had a direct effect on severity of illness ; Credible authority had a both direct and indirect effect on severity of illness ; Event congruency had the greatest effect on severity of illness, and event familiarity had a nonsignificant direct effect on severity of illness.
Purpose - With globalization, medical tourism has developed as a new industry, which attracts practitioners and academics to have more interest in researches on customers' behavior. This research was to investigate empirically WOM effects on the intention of Chinese customers when they select an international medical tourism destination. Interestingly, WOM effects on their choice and decision process may vary by the extent of their severity of illness. Research design, data, and methodology - The data was collected from 1,747 potential Chinese residents in main districts of China. Moderated regression analysis was used to estimate WOM effects on Chinese customers' choice intention. Results - Results imply that WOM determinants of tie strength, credibility, and vividness do interact with medical tourism information and affect customers' intention for health care abroad. Results also reveal that the severity of illness plays a critical moderating role in customers' decision process. Conclusions - WOM and the severity of illness are important moderators for Chinese customers to make a decision for medical tourism. It provides some implications for service organizations for developing and implementing marketing strategies in international health care markets.
Background. Although there have been a great number of research studies based on the model of uncertainty in illness, few studies have considered the appraisal portion of model. Purpose. The purpose of this study was to test the mediating effect of appraisal in the model of uncertainty in illness. Additionally, this study aimed to examine the relationships among uncertainty, symptom severity, appraisal, and anxiety in patients newly diagnosed with atrial fibrillation. Methods. This study employed a descriptive correlational and cross-sectional survey design using a face-to-face interview method. Patients diagnosed with atrial fibrillation within the previous 6 months prior to data collection were interviewed by Mishel Uncertainty in Illness Scale-Community Form, appraisal scale, Symptom Checklist-Severity V.3, and State Anxiety Inventory. Results. A total of 81 patients with atrial fibrillation were recruited from two large urban medical centers in Cleveland, Ohio, U.S.A.. Symptom severity was the significant variable in explaining uncertainty ($\beta$=0.34). Individuals with greater symptom severity perceived more uncertainty. Uncertainty was appraised as a danger rather than opportunity, and those with greater uncertainty appraised a greater danger (p<.0l). While the appraisal of opportunity had the negative relationship with anxiety (r=-0.25), the appraisal of danger was positively associated with anxiety (r=0.78). The measure of goodness of fit (Q) of the model was .7863, and the significant test (X$^2$) for the Q was statistically significant (df =3, p<.00l). Accordingly, the overall mediating model of uncertainty in illness was proven not to be fit to the empirical data of patients with atrial fibrillation. Consequently, the mediating effect of appraisal was not supported by the empirical data of this study. Conclusion. The findings of this study were discussed in terms of their relevance compared with those of previous studies or theoretical framework and the plausible explanations on study findings. Lastly, in order to expand the present body of knowledge on uncertainty in illness model, recommendations for the future nursing studies were included.
Subhanik Purkayastha;Yanhe Xiao;Zhicheng Jiao;Rujapa Thepumnoeysuk;Kasey Halsey;Jing Wu;Thi My Linh Tran;Ben Hsieh;Ji Whae Choi;Dongcui Wang;Martin Vallieres;Robin Wang;Scott Collins;Xue Feng;Michael Feldman;Paul J. Zhang;Michael Atalay;Ronnie Sebro;Li Yang;Yong Fan;Wei-hua Liao;Harrison X. Bai
Korean Journal of Radiology
/
제22권7호
/
pp.1213-1224
/
2021
Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.
Purpose: This study aimed to identify factors related to the workload of intensive care unit nurses through a systematic literature review and meta-analysis to provide basic data to explore the direction of development of nursing staffing standards. Methods: This study involved quantitative studies about nurses working in intensive care units related to nursing workload published in English or Korean since 2000. Search terms included 'intensive care unit', 'nursing workload', and their variations. Databases such as RISS, DBpia, MEDLINE(PubMed), CINAHL, PsycINFO, and Web of Science were utilized. Quality assessment was conducted using the Joanna Briggs Institute's Critical Appraisal Checklist for Analytical Cross-Sectional Studies. JAMOVI software facilitated the analysis of effect sizes, employing a meta-analysis approach for 7 studies with correlational or regression data. Results: From 16 studies on the workload of intensive care unit nurses, a total of 20 patient and nurse-related factors were identified. Patient-related factors included severity of illness, length of stay, and age. Meta-analysis was conducted for three patient-related factors: age, severity of illness measured by SAPS 3, and length of stay. Only severity of illness measured by SAPS 3 was significantly associated with nurse workload (Zr=0.16, p<.001, 95% CI=0.09-0.24). Conclusion: In previous studies, the characteristics of intensive care units and patients varied across studies, and a variety of scales for measuring workload and severity of illness were also used. Sustained research reflecting domestic intensive care unit work environments and assessing the workload of intensive care unit nurses should be imperative.
This study was conducted to investigate the influencing factors on the appraisal of uncertainty in patients having rheumatoid arthritis. Subjects of the study constituted 528 patients who visited outpatient clinics of two university hospitals and one general hospital in Seoul. Self report questionnaires were used to measure the variables influencing the appraisal of uncertainty. Reliability coefficients of these instruments were found Cronbach's Alpha=$.70{\sim}.96$. In data analysis, SPSS PC 6.0 program was utilized for descriptive statistics, Pearson's correlation, logistic and multiple regression analysis. The results of logistic and multiple regression analysis were as follows 1) Among the independent variables, significant factors to explain the appraisal of uncertainty in patients were uncertainty(p<.001), severity of illness(p<.05), educational level (p<.05) and age (p<.05). 2) When patients appraised uncertainty as "Danger", significant factors to explain the appraisal of uncertainty were uncertainty(p<.0001), age(p<.0005), severity of illness(p<.001), educational level (p<.05). 3) When patients appraised uncertainty as "Opportunity", significant factors to predict the appraisal of uncertainty were uncertainty(p<.0005), social support(p<.0005), severity of illness(p<.005), credible authority(p<.05), age(p<.05) and educational level (p<.05).
Purpose This study aims to develop a work-related injury and illness monitoring geographic information system that analyzes and visualizes the types of work-related injury and illness based on workers' compensation insurance big data. Design/methodology/approach Using the developed system, we explained the process of monitoring the areas of the applied workplace, medical care application, index, and medical care institution. We also showed examples of analyzing the index and medical care institution area. By applying the system, we can intuitively recognize the current status of workers' compensation insurance and confirm the basic information necessary for managing the current status of workers' compensation insurance. Findings We generated more helpful information by combining workers' compensation insurance data and designated medical care institution data. We were able to apply the severity score and the vulnerability index of work-related injury and illness to the system as a demonstration. To efficiently manage workers' compensation insurance, it was necessary to integrate workers' compensation insurance and designated medical care institution data, as well as the data from various sources.
Factors related to health promotion activities and quality of life in Korean women with arthritis have not been clearly identified. Predictors of health promotion might be identified that will enhance the well - being of this group. Accordingly, the findings of the study will contribute additional information about the relationship between health promotion and quality of life and will add to the research on quality of life of individuals with a leading cause of disability--arthritis. The purpose of the study was to examine the relationship of selected background factors (years of illness, perceived severity of illness, uncertainty in illness), perceived self- efficacy, and health promoting behaviors to the quality of life of Korean women with arthritis. A cross - sectional descriptive design was used in this study to investigate relationships among the variables of interest. The sample was composed of 96 women who had arhtrits and visited large university hospital in Seoul for regular check up or pre-scription of medication. The purpose of a descriptive correlational design was to determine the absence or presence of relationships among variables that were measurable (Polit & Hungler, 1981, p.147). The design of this study was appropriate because it yielded answers to the research questions and hypotheses regarding the relationships among the model variables. the Questionnaire contained demographic information, translated Mishel Uncertainty in illness Scale-Community form (MUIS-C) (Mishel, 1987), translated and modified Disease Course Graphic Scale(DCGS) which was developed by Braden (1990), translated Sherer. et al.’s General Self-Efficacy Scale (1982), The Health -Promoting Lifestyle Profile (HPLP), developed by Walker, Sechrist, and Fender (1987) and traslated to Korean by Ha, and quality of life was measured by Face Scale (Andrew, 1976). Several steps of verification for the translation process were carefully conducted. Data analysis included descriptive correlational statistics and multiple regression techniques. Health promotion was the only contributor to pre-dict quality of life. Results showed that enabling cognitive perceptual factor (self-efficacy) mediates the disruptive force (uncertainty in ill-ness) on achieving a health promoting self- help behavior. The findings of this study also indicated that illness - related variable of severity of illness was mediated by health promotion, which buffered it's impact on quality of life.
Objectives The purpose of study was to identify cancer related symptoms of Sasang Constitution based on the classic of Sasang Constitutional Medicine (SCM). Methods The bibliographical study was performed with "Dongyisoosebowon-Shinchukbon(東醫壽世保元 辛丑本)", Dongyisoosebowon-Sasangchobongwon(東醫壽世保元 四象草本券), "Cancer", and several review articles. The perspective on severe illness in SCM was investigated. And 'the critical state' of constitutional symptoms based on "Dongyisoosebowon" was identified as cancer related symptoms. Results and Conclusions The perspective on severe illness of SCM was focused on the human being itself, compared with symptom based traditional Chinese medicine. The preservation of requisite energy (保命之主) was a vital factor of longevity to maintain healthy status and the classification of severity of disease. And critical state was an important indicator to control severe illness. Regarding cancer related symptoms in SCM, Janggwol(臟厥), Eumsung-gyeokyang(陰盛隔陽證), Janggyeol(藏結證) of Soeumin symptoms, Hwangdal(黃疸), Haso(下消), Eumheo-oyel(陰虛午熱證), Gochang, Tohyul(吐血) of Soyangin's symptoms, Joyeol(燥熱證), Bokchang-bujong(腹脹浮腫) of Taeeumin's symptoms, and Eolgyek of Taeyangin's symptoms could be shown the association with cancer. According to the prognosis on disease severity, regimens of daily life, behavior modifications as well as medications were also emphasized with great importance to control severe illness in SCM. These holistic approach for controlling severe illness in SCM could lead to the improvement of treatment outcome.
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