This study was conducted to identify the characteristics of activities of daily living(ADU) and its influencing factors in patients with chronic arthritis. The data were obtained from 104 patients with chronic arthritis in one university hospital from May to August. 2000. For analysing data. SAS program was used for t-test. ANOVA, Schefte test. Pearson correlation. and stepwise multiple regression. The results were as follows: 1. The variables which influenced self-efficacy were duration of disease. number of painful joint, quality of sleep and alcohol drinking. 2. The variables which influenced fatigue were diagnosis and number of painful joint. 3. The variables which influenced ADL were age. duration of disease. diagnosis. number of painful joint. number of exercise and alcohol drinking. 4. ADL was positive correlation with self-efficacy and negative correlation with fatigue. And self-efficacy was negative correlation with fatigue. 5. The predictors to explain ADL were self-efficacy. number of painful joint. lupus. duration of disease and religion. These predictors explained $66.01\%$ of the activites of daily living. According to these findings. the most significant influencing factor of ADL was self-efficacy. therefore the development of nursing intervention for enhancing self-efficacy would be needed. Also. it is suggested that an exercise program should be recommended as one of useful and appropriate nursing intervention for reducing fatigue and increasing ADL.
Objectives : The purposes of this study is to estimate the cost of cancer care after its diagnosis and to identify factors that can influence the cost of cancer care. Methods : The study subjects were patients with an initial diagnosis one of four selected tumors and had their first two-years of cancer care at a national cancer center. The data were obtained from medical records and patient surveys. We classified cancer care costs into medical and nonmedical costs, and each cost was analyzed for burden type, medical service, and cancer stage according to cancer types. Factors affecting cancer care costs for the initial phase included demographic variables, socioeconomic status and clinical variables. Results : Cancer care costs for the initial year following diagnosis were higher than the costs for the following successive year after diagnosis. Lung cancer (25,648,000 won) had higher costs than the other three cancer types. Of the total costs, patent burden was more than 50% and medical costs accounted for more than 60%. Inpatient costs accounted for more than 60% of the medical costs for stomach and liver cancer in the initial phase. Care for latestage cancer was more expensive than care for early-stage cancer. Nonmedical costs were estimated to be between 4,500,000 to 6,000,000 won with expenses for the caregiver being the highest. The factors affecting cancer care costs were treatment type and cancer stage. Conclusions : The cancer care costs after diagnosis are substantial and vary by cancer site, cancer stage and treatment type. It is useful for policy makers and researchers to identify tumor-specific medical and nonmedical costs. The effort to reduce cancer costs and early detection for cancer can reduce the burden to society and improve quality of life for the cancer patients.
Objective : Neuroimaging data are of paramount importance in making correct diagnosis. We herein evaluate the clinical usefulness of image transfer using cellular phones to facilitate neurological diagnosis and decision-making. Methods : Selected images from CT, MRI scans, and plain films obtained from 50 neurosurgical patients were transferred by cellular phones. A cellular phone with a built-in 1,300,000-pixel digital camera was used to capture and send the images. A cellular phone with a 262,000 color thin-film transistor liquid crystal display was used to receive the images. Communication between both cellular phones was operated by the same wireless protocol and the same wireless internet service. We compared the concordance of diagnoses and treatment plans between a house staff who could review full-scale original films and a consultant who could only review transferred images. These finding were later analyzed by a third observer. Results : The mean time of complete transfer was $2{\sim}3\;minutes$. The quality of all images received was good enough to make precise diagnosis and to select treatment options. Transferred images were helpful in making correct diagnosis and decision making in 49/50 [98%] cases. Discordant result was caused in one patient by improper selection of images by the house staff. Conclusion : The cellular phone system was useful for image transfer and delivery patient's information, leading to earlier diagnosis and initiation of treatment. This usefulness was due to sufficient resolution of the built-in camera and the TFT-LCD, the user-friendly features of the devices, and their low cost.
Temporomandibular joint disorders (TMDs) can occur at any age, including childhood and adolescence, and pain-related TMDs can affect growth and quality of life. In the present study, recent trends in the diagnosis and treatment of TMDs in children and adolescents were analyzed over a 10-year period. Using 10 years of data from the Health Insurance Review and Assessment Service (HIRA) and Jeonbuk National University (JBNU) Dental Hospital, patients between 0 and 19 years of age diagnosed with K07.6 (temporomandibular joint disorders) were analyzed by 5-year bins. Both datasets indicated a higher prevalence in females (1.2-fold in HIRA, 1.5-fold in JBNU) and in ages 15 to 19 years (72.1% in HIRA, 74.7% in JBNU). HIRA reported a 42.3% increase in prevalence per 100,000 people, from 651.4 in 2011 to 927.0 in 2020. JBNU reported K07.66 (masticatory muscle disorders) as the most common diagnosis in subjects under 10 years of age and K07.60 (internal derangement of temporomandibular joint) in those over 10 years of age. In addition, both were treated mainly by a combination of physical therapy and medication, and the treatment rate increased in accordance with age. Because TMDs can affect various structures in the orofacial region and cause pain that tends to differ with age, an early and specific diagnosis appropriate for age is important for treatment. Therefore, pediatric dentists need to promptly recognize TMDs in children and adolescents and consult with specialists as the prevalence increases.
Purpose - This study attempts to identify the attributes of home meal replacements (HMR) from the perspective of consumers as well as suggest some directions for HMR. Research Design, Data, and Methodology - For the research, food and nutrition professors were interviewed and surveys were completed using the revised Delphi method to identify attributes of HMR. Subsequently, a total of 140 food and nutrition students already aware of HMR were asked to rate the attributes in terms of importance and satisfaction. In addition, Importance-Performance Analysis (IPA) was conducted. Results - According to the analysis results, a total of seven key factors were deduced from the attributes ratings and the Kaiser-Meyer-Olkin (KMO) criteria, which is used to verify the appropriateness of the selection of the variables. Conclusion - The findings could be helpful in the future as reference data for HMR producers and distributors to assist in the diagnosis of the status of HMR. Additionally, the data may point to some areas that need greater attention in terms of production as well as marketing.
Objectives: The hospital standardized mortality ratio (HSMR) has been widely used because it allows for robust risk adjustment using administrative data and is important for improving the quality of patient care. Methods: All inpatients discharged from hospitals with more than 700 beds (66 hospitals) in 2008 were eligible for inclusion. Using the claims data, 29 most responsible diagnosis (MRDx), accounting for 80% of all inpatient deaths among these hospitals, were identified, and inpatients with those MRDx were selected. The final study population included 703 571 inpatients including 27 718 (3.9% of all inpatients) in-hospital deaths. Using logistic regression, risk-adjusted models for predicting in-hospital mortality were created for each MRDx. The HSMR of individual hospitals was calculated for each MRDx using the model coefficients. The models included age, gender, income level, urgency of admission, diagnosis codes, disease-specific risk factors, and comorbidities. The Elixhauser comorbidity index was used to adjust for comorbidities. Results: For 26 out of 29 MRDx, the c-statistics of these mortality prediction models were higher than 0.8 indicating excellent discriminative power. The HSMR greatly varied across hospitals and disease groups. The academic status of the hospital was the only factor significantly associated with the HSMR. Conclusions: We found a large variation in HSMR among hospitals; therefore, efforts to reduce these variations including continuous monitoring and regular disclosure of the HSMR are required.
Objectives: There are no studies which have investigated the health related quality of life(HRQOL) about stroke patients according to the medical care utilization behavior by longitudinal analysis. The purpose of this study is to analyze the quality of life(QOL) and quality adjusted life years(QALYs) of stroke patients of western and combined treatment group by longitudinal analysis. Methods: A retrospective cohort study was conducted among 37 new patients who initiated diagnosis with stroke in 2009 from Korea Health Panel Data. We analyzed the HRQOL of stroke patients and calculated the QALYs after medical use initiation for up to 3 years according to the medical care utilization behavior. Results: Overall, the quality of life of stroke patients was lowered somewhat from 0.8431 to 0.7864 in 2009~2012. Western treatment group was appeared slightly declined in from 0.8527 to 0.8231 and combined treatment group was shown to be falling from 0.8173 to 0.6875. The QALYs of total patients were calculated 2.3654 and western treatment group were 2.4436, combined treatment group were 2.1542 during the 4 year period. The difference of QALYs between two groups was 0.2894 QALYs. Conclusions: Although there was a small difference in QALYs of the two groups, it is not certain that the difference is come from medical care utilization behavior. Further studies should be needed to confirm the relation of the medical care utilization behavior and quality of life by considering severity of the stroke.
Purpose: The purpose of this study was to examine the mediating effect of marital intimacy on the impact of uncertainty on the quality of life (QoL) of young breast cancer patients. Methods: This study used a pathway analysis with 154 young breast cancer cases in their early diagnosis stage at a medical center in Korea. Data were collected from November 2016 to February 2017 and analyzed using correlation analysis and pathway analysis. Results: Uncertainty, marital intimacy, and 4 sub-scales of QoL showed a significant correlation. Marital intimacy was directly affected by uncertainty (${\beta}=-.39$, p=.013) and 4 sub-scales of QoL were also affected by uncertainty. Among the 4 sub-scales of QoL, physical well-being (PWB) (${\beta}=.17$, p=.026), social well-being (SWB) (${\beta}=.49$, p=.010), and functional well-being (FWB) (${\beta}=.38$, p=.009) were affected by marital intimacy but emotional well-being (EWB) was not affected by it. The mediating effect of marital intimacy on the impact of uncertainty on QoL was confirmed. Marital intimacy showed a significant indirect effect on PWB (${\beta}=-.07$, p=.024), SWB (${\beta}=-.19$, p=.008), and FWB (${\beta}=-.15$, p=.005), and it means that marital intimacy has a partial mediating effect on the impact of uncertainty on PWB, SWB, and FWB. Conclusion: Effects of uncertainty on QoL was mediated by marital intimacy of young breast cancer patients in their early diagnosis stage. It suggests that marital intimacy needs to be considered in providing nursing intervention for young breast cancer patients.
The purpose of this study is to improve the daily prediction results of PM2.5 from the air quality diagnosis and evaluation system operated by the Busan Institute of Health and Environment in real time. The air quality diagnosis and evaluation system is based on the photochemical numerical model, CMAQ (Community multiscale air quality modeling system), and includes a 3-day forecast at the end of the model's calculation. The photochemical numerical model basically has limitations because of the uncertainty of input data and simplification of physical and chemical processes. To overcome these limitations, this study applied DNN (Deep Neural Network), a deep learning technique, to the results of the numerical model. As a result of applying DNN, the r of the model was significantly improved. The r value for GFS (Global forecast system) and UM (Unified model) increased from 0.77 to 0.87 and 0.70 to 0.83, respectively. The RMSE (Root mean square error), which indicates the model's error rate, was also significantly improved (GFS: 5.01 to 6.52 ug/m3 , UM: 5.76 to 7.44 ug/m3 ). The prediction results for each concentration grade performed in the field also improved significantly (GFS: 74.4 to 80.1%, UM: 70.0 to 77.9%). In particular, it was confirmed that the improvement effect at the high concentration grade was excellent.
According to development of power electric technology from industrial field to electronic home appliances, recent SMPS using semiconductor is spread widely. Electric converting instrument uses a sine wave voltage source, namely an usual power source, and it gets a non-sines power source from power source because current flows through one part in waveform of one cycle. This injects higher harmonic source in source part, absorb pollution source. And this cause quality deterioration, durability shortage of electric power instrument, spreading accident of electric solver system, and so on. It can't supply an electric source of good quality in industry, so become an impedimental element in improving productivity and reliance. This study can be used in prediction of hindrance and diagnosis material and intends to suggest a countermeasure about measurement data.
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