• The Journal of Information Systems
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• v.30 no.3
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• pp.65-91
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• 2021

Purpose In this study, we investigated the impact of perceived risk and switching costs on switching intention to cloud service based on PPM (Pull-Push-Mooring) model. Design/methodology/approach We focused on revealing the switching factors of the switching intention to the cloud services. The switching factors to the cloud services were defined as perceived risk consisting of performance risk, economic risk, and security risk, and switching costs consisting of financial and learning costs. On the PPM model, we defined the pull factors consisting of perceived usefulness and perceived ease of use, and the push factor as satisfaction of the legacy system, and the mooring factor as policy supports. Findings The results of this study as follows; (1) Among the perceived risk factors, performance risk has a negative effect on the ease of use of pull factors, and finally it was found to affect the switching intention to the cloud services. Therefore, cloud service providers need to improve trust in cloud services, service timeliness, and linkage to the legacy systems. And it was found that economic risk and security risk among the perceived risk factors did not affect the switching intention to the cloud services. (2) Of the perceived risk factors, financial cost and learning cost did not affect the satisfaction of the legacy system, which is a push factor. It indicates that the respondents are positively considering switching to cloud service in the future, despite the fact that the respondents are satisfied with the use of the legacy system and are aware of the switching cost to cloud service. (3) Policy support was found to improve the switching intention to cloud services by alleviating the financial and learning costs required for cloud service switching.

• Journal of Trauma and Injury
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• v.37 no.2
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• pp.124-131
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• 2024

Purpose: The aim of this study was to utilize the American College of Surgeons Trauma Quality Improvement Program (TQIP) database to identify risk factors associated with developing acute compartment syndrome (ACS) following lower extremity fractures. Specifically, a nomogram of variables was constructed in order to propose a risk calculator for ACS following lower extremity trauma. Methods: A large retrospective case-control study was conducted using the TQIP database to identify risk factors associated with developing ACS following lower extremity fractures. Multivariable regression was used to identify significant risk factors and subsequently, these variables were implemented in a nomogram to develop a predictive model for developing ACS. Results: Novel risk factors identified include venous thromboembolism prophylaxis type particularly unfractionated heparin (odds ratio [OR], 2.67; 95% confidence interval [CI], 2.33-3.05; P<0.001), blood product transfusions (blood per unit: OR 1.13 [95% CI, 1.09-1.18], P<0.001; platelets per unit: OR 1.16 [95% CI, 1.09-1.24], P<0.001; cryoprecipitate per unit: OR 1.13 [95% CI, 1.04-1.22], P=0.003). Conclusions: This study provides evidence to believe that heparin use and blood product transfusions may be additional risk factors to evaluate when considering methods of risk stratification of lower extremity ACS. We propose a risk calculator using previously elucidated risk factors, as well as the risk factors demonstrated in this study. Our nomogram-based risk calculator is a tool that will aid in screening for high-risk patients for ACS and help in clinical decision-making.

• International Journal of Human Ecology
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• v.2 no.1
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• pp.135-152
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• 2001

The purpose of this study was to investigate the association of protective and risk factors with adolescent delinquency. Using nationally representative data from the National Longitudinal Study of Adolescent Health (Add Health) project, the delinquency level and the influence of individual characteristics, dyadic relationships in the family, school and peer variables on adolescent delinquency were examined by gender. Boys and girls differed in delinquency level with boys showing significantly higher delinquency than girls. The relative influence of protective and risk factors in individual, familial, peer, and school contexts differed by gender as well. More diverse variables influenced the delinquency level of girls than that of boys.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3039-3056
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• 2020

Beaches have many risk factors that cause various accidents, such as drifting and drowning, these accidents have many risk factors. To analyze them, in this paper, we identify beach risk factors, and define the criteria and correlation for each risk factor. Then, we generate new risk factors based on Fuzzy theory, and define Situation Awareness for each time. Finally, we propose a beach risk assessment and prediction model based on linear regression using the calculated risk result and pre-defined risk factors. We use national public data of the Korea Meteorological Administration (KMA), and the Korea Hydrographic and Oceanographic Agency (KHOA). The results of the experiment showed the prediction accuracy of beach risk to be 0.90%, and the prediction accuracy of drifting and drowning accidents to be 0.89% and 0.86%, respectively. Also, through factor correlation analysis and risk factor assessment, the influence of each of the factors on beach risk can be confirmed. In conclusion, we confirmed that our proposed model can assess and predict beach risks.

• Journal of Korean Neurosurgical Society
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• v.46 no.5
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• pp.451-458
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• 2009

Objective : The purpose of this study was to analyze risk factors that are associated with intracranial lesion, and to propose criteria for classification of mild head injury (MHI), and appropriate treatment guidelines. Methods : The study was based on 898 patients who were admitted to our hospital with Glasgow Coma Scale (GCS) score of 13 to 15 between 2003 and 2007. The patients' initial computerized tomography (CT) findings were reviewed and clinical findings that were associated with intracranial lesions were analyzed. Results : GCS score, loss of consciousness (LOC), age and skull fracture were identified as independent risk factors for intracranial lesions. Based on the data ana lysed in this study, MHI patients were divided into four subgroups : very low risk MHI patients are those with a GCS score of 15 and without a history of LOC or headache; low risk MHI patients have a GCS score of 15 and with LOC and/or headache; medium risk MHI patients are those with a GCS score of 15 and with a skull fracture, neurological deficits or with one or more of the risk factors; high risk MHI patients are those with a GCS score of 15 with abnormal CT findings and GCS score of 14 and 13. Conclusion : A more detailed classification of MHI based on brain CT scan findings and clinical risk factors can potentially improve patient diagnosis. In light of our findings, high risk MHI patients should be admitted and treated in same manner as those with moderate head injury.

• Korea Journal of Hospital Management
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• v.15 no.4
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• pp.125-142
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• 2010

Objective : To determine demographic, clinical, health care utilization factors predicting unplanned readmission(within 28 days) to the hospital. Methods : A case-control study was conducted from January to December 2009. Multiple logistic regression was used to examine risk factors for readmission. 180 patients who had been readmitted within 28 days and 1,784 controls were recruited from an university hospital in Seoul. Results : Six risk factors associated with readmission risk were identified and include mail sex, medical service rather than surgical service, number of comorbid diseases, type of patient's room, lenth of stay, number of admissions in the prior 12 months. Conclusions : One of the association with readmission risk identified was the number of hospital admissions in the previous year. This factor may be the only risk factor necessary for assessing prior risk and has the additional advantage of being easily accessible from computerized medical records without requiring other medical record review. This risk factor may be useful in identifying a group at high readmission risk, which could be targeted in intervention studies. Multiple risk factors intervention approach should be considered in designing future prevention strategies.

• Journal of Preventive Medicine and Public Health
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• v.39 no.3
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• pp.235-242
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• 2006

Objectives: We wanted to determine the distribution of the clustering of the metabolic risk factors and we wanted to evaluate the related factors in young schoolchildren. Methods: A cross-sectional study of metabolic syndrome was conducted in an elementary school in Seoul, Korea. We evaluated fasting glucose, triglyceride, HDL cholesterol, blood pressures and the body mass index, and we used parent-reported questionnaires to assess the potential risk factors in 261 children (136 boys, 125 girls). We defined the metabolic risk factors as obesity or at risk for obesity ($\geqq$ 85th percentile for age and gender), a systolic or diastolic blood pressure at $\geqq90th$ percentile for age and gender, fasting glucose at $\geqq110mg/dl$, triglyceride at $\geqq110mg/dl$ and HDL cholesterol at $\leqq40mg/dl$. Results: There were 15.7% of the subjects who showed clustering of two or more metabolic risk factors, 2.3% of the subjects who showed clustering for three or more risk factors, and 0.8% of the subjects who showed clustering for four or more risk factors. A multivariate analysis revealed that a father smoking more than 20 cigarettes per day, a mother with a body mass index of = $25kg/m^2$, and the child eating precooked or frozen food more than once per day were associated with clustering of two or more components, with the odds ratios of 3.61 (95% CI=1.24-10.48), 5.50 (95% CI=1.39-21.73) and 8.04 (95% CI=1.67-38.81), respectively. Conclusions: This study shows that clustering of the metabolic risk factors is present in young schoolchildren in Korea, with the clustering being associated with parental smoking and obesity as well as the child's eating behavior. These results suggest that evaluation of metabolic risk factors and intervention for lifestyle factors may be needed in both young Korean children and their parents.

• Neonatal Medicine
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• v.28 no.3
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• pp.116-123
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• 2021

Purpose: The aim of this study was to estimate the effect of targeting risk factors for the control of central line-associated bloodstream infection (CLABSI) among high-risk infants in a tertiary neonatal intensive care unit (NICU). Methods: Infants admitted to the NICU and diagnosed with CLABSI from January to December 2013 were eligible for inclusion to the study. The CLABSI group (n=47) was matched in a 1:2 ratio to the control group (n=94) based on gestational age, birth weight, and Score for Neonatal Acute Physiology-II. Risk factors for CLABSI were identified using the Cox proportional hazard model, and analysis of the effect of these risk factors targeting infection control was performed. Results: The risk factors associated with CLABSI were prolonged central line dwell days (adjusted hazard ratio [HR], 1.028; 95% confidence interval [CI], 1.011 to 1.045; P=0.001), use of a silicone catheter (adjusted HR, 5.895; 95% CI, 1.893 to 18.355; P=0.002), surgical treatment (adjusted HR, 3.793; 95% CI, 1.467 to 9.805; P=0.006), and less probiotic supplementation (adjusted HR, 0.254; 95% CI, 0.068 to 0.949; P=0.042). By targeting these risk factors with a quality improvement initiative, the mean CLABSI incidence rate per 1,000 catheter-days decreased from 6.6 to 3.1 (P=0.004). Conclusion: Targeting risk factors for infection control significantly reduced the rate of CLABSI among high-risk infants in the NICU.

• Safety and Health at Work
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• v.14 no.3
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• pp.279-286
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• 2023

Background: This study aimed to evaluate the association between exposure to occupational hazards and the metabolic syndrome. A secondary objective was to analyze the additive and multiplicative effects of exposure to risk factors. Methods: This retrospective cohort was based on 31,615 health examinees at the Pusan National University Yangsan Hospital in Republic of Korea from 2012-2021. Demographic and behavior-related risk factors were treated as confounding factors, whereas three physical factors, 19 organic solvents and aerosols, and 13 metals and dust were considered occupational risk factors. Time-dependent Cox regression analysis was used to calculate hazard ratios. Results: The risk of metabolic syndrome was significantly higher in night shift workers (hazard ratio = 1.45: 95% confidence interval = 1.36-1.54) and workers who were exposed to noise (1.15:1.07-1.24). Exposure to some other risk factors was also significantly associated with a higher risk of metabolic syndrome. They were dimethylformamide, acetonitrile, trichloroethylene, xylene, styrene, toluene, dichloromethane, copper, antimony, lead, copper, iron, welding fume, and manganese. Among the 28 significant pairs, 19 exhibited both positive additive and multiplicative effects. Conclusions: Exposure to single or combined occupational risk factors may increase the risk of developing metabolic syndrome. Working conditions should be monitored and improved to reduce exposure to occupational hazards and prevent the development of the metabolic syndrome.

• The Korean journal of internal medicine
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• v.39 no.1
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• pp.77-85
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• 2024

Background/Aims: There may be many predictors of anticoagulation-related gastrointestinal bleeding (GIB), but until now, systematic reviews and assessments of the certainty of the evidence have not been published. We conducted a systematic review to identify all risk factors for anticoagulant-associated GIB to inform risk prediction in the management of anticoagulation-related GIB. Methods: A systematic review and meta-analysis were conducted to search PubMed, EMBASE, Web of Science, and Cochrane Library databases (from inception through January 21, 2022) using the following search terms: anticoagulants, heparin, warfarin, dabigatran, rivaroxaban, apixaban, DOACs, gastrointestinal hemorrhage, risk factors. According to inclusion and exclusion criteria, studies of risk factors for anticoagulation-related GIB were identified. Risk factors for anticoagulant-associated GIB were used as the outcome index of this review. Results: We included 34 studies in our analysis. For anticoagulant-associated GIB, moderate-certainty evidence showed a probable association with older age, kidney disease, concomitant use of aspirin, concomitant use of the antiplatelet agent, heart failure, myocardial infarction, hematochezia, renal failure, coronary artery disease, helicobacter pylori infection, social risk factors, alcohol use, smoking, anemia, history of sleep apnea, chronic obstructive pulmonary disease, international normalized ratio (INR), obesity et al. Some of these factors are not included in current GIB risk prediction models. such as anemia, co-administration of gemfibrozil, co-administration of verapamil or diltiazem, INR, heart failure, myocardial infarction, etc. Conclusions: The study found that anemia, co-administration of gemfibrozil, co-administration of verapamil or diltiazem, INR, heart failure, myocardial infarction et al. were associated with anticoagulation-related GIB, and these factors were not in the existing prediction models. This study informs risk prediction for anticoagulant-associated GIB, it also informs guidelines for GIB prevention and future research.