• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.3
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• pp.464-477
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• 2013

There is a great need to develop a training program proven to change behavior and improve knowledge. The purpose of this study was to evaluate employee hygiene knowledge, hygiene practice, and cleanliness, before and after HACCP system implementation at one small-size restaurant. The efficiency of the system was analyzed using time-temperature control after implementation of u-HACCP$^{(R)}$. The employee hygiene knowledge and practices showed a significant improvement (p<0.05) after HACCP system implementation. In non-heating processes, such as seasoned lettuce, controlling the sanitation of the cooking facility and the chlorination of raw ingredients were identified as the significant CCP. Sanitizing was an important CCP because total bacteria were reduced 2~4 log CFU/g after implementation of HACCP. In bean sprouts, microbial levels decreased from 4.20 logCFU/g to 3.26 logCFU/g. There were significant correlations between hygiene knowledge, practice, and microbiological contamination. First, personnel hygiene had a significant correlation with 'total food hygiene knowledge' scores (p<0.05). Second, total food hygiene practice scores had a significant correlation (p<0.05) with improved microbiological qualities of lettuce salad. Third, concerning the assessment of microbiological quality after 1 month, there were significant (p<0.05) improvements in times of heating, and the washing and division process. On the other hand, after 2 months, microbiological was maintained, although only two categories (division process and kitchen floor) were improved. This study also investigated time-temperature control by using ubiquitous sensor networks (USN) consisting of an ubi reader (CCP thermometer), an ubi manager (tablet PC), and application software (HACCP monitoring system). The result of the temperature control before and after USN showed better thermal management (accuracy, efficiency, consistency of time control). Based on the results, strict time-temperature control could be an effective method to prevent foodborne illness.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.420-427
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• 2016

The purpose of this study was to identify association between total sleep time and suicidal ideation in adults with mental problems and without. The data were derived from the fifth Korea national health and nutrition examination survey and analyzed using the IBM SPSS Statistics version 21.0 software package considering complex samples analysis. The subjects were 6,199 adults. The rate of suicidal ideation was 13.7% (880 people). 13.3% (846 people) of the subjects had experienced depression and out of whom 43.1% (329 people) have had suicidal ideation. 2.7% (164 people) of the subject had received the mental health counseling, and out of whom 40.2% (63 people) have had suicidal ideation. Comparing to group having sleep over 6 hours of more, the group of short sleep had 1.33 times high risk of suicidal ideation among general adults, 1.92 times high risk of suicidal ideation among group who had experienced depression and, 7.10 times high risk of suicidal ideation among group who had received the mental health counseling. Therefore, these results indicate that general adults with short sleep time as well as adults with depression or mental health problems have to be managed to prevent suicide.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.113-117
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• 2016

Quantile regression is an efficient method for predicting and estimating the relationship between explanatory variables and percentile points of the response distribution, particularly for extreme percentiles of the distribution. To study the relationship between urbanization and cancer morbidity, we here applied quantile regression. This cross-sectional study was conducted for 9 cancers in 345 cities in 2007 in Iran. Data were obtained from the Ministry of Health and Medical Education and the relationship between urbanization and cancer morbidity was investigated using quantile regression and least square regression. Fitting models were compared using AIC criteria. R (3.0.1) software and the Quantreg package were used for statistical analysis. With the quantile regression model all percentiles for breast, colorectal, prostate, lung and pancreas cancers demonstrated increasing incidence rate with urbanization. The maximum increase for breast cancer was in the 90th percentile (${\beta}$=0.13, p-value<0.001), for colorectal cancer was in the 75th percentile (${\beta}$=0.048, p-value<0.001), for prostate cancer the 95th percentile (${\beta}$=0.55, p-value<0.001), for lung cancer was in 95th percentile (${\beta}$=0.52, p-value=0.006), for pancreas cancer was in 10th percentile (${\beta}$=0.011, p-value<0.001). For gastric, esophageal and skin cancers, with increasing urbanization, the incidence rate was decreased. The maximum decrease for gastric cancer was in the 90th percentile(${\beta}$=0.003, p-value<0.001), for esophageal cancer the 95th (${\beta}$=0.04, p-value=0.4) and for skin cancer also the 95th (${\beta}$=0.145, p-value=0.071). The AIC showed that for upper percentiles, the fitting of quantile regression was better than least square regression. According to the results of this study, the significant impact of urbanization on cancer morbidity requirs more effort and planning by policymakers and administrators in order to reduce risk factors such as pollution in urban areas and ensure proper nutrition recommendations are made.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.137-144
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• 2020

Delirium is among the most common mental disorders encountered in patients with a temporary cognitive impairment such as consciousness disorder, attention disorder, and poor speech, particularly among those who are older. Delirium is distressing for patients and families, can interfere with the management of symptoms such as pain, and is associated with increased elderly mortality. The purpose of this paper is to generate useful clinical knowledge that can be used to distinguish the outcomes of patients with delirium in long-term care facilities. For this purpose, we extracted the clinical classification knowledge associated with delirium using a local covering rule acquisition approach with the rough lower approximation region. The clinical applicability of the proposed method was verified using data collected from a prospective cohort study. From the results of this study, we found six useful clinical pieces of evidence that the duration of delirium could more than 12 days. Also, we confirmed eight factors such as BMI, Charlson Comorbidity Index, hospitalization path, nutrition deficiency, infection, sleep disturbance, bed scores, and diaper use are important in distinguishing the outcomes of delirium patients. The classification performance of the proposed method was verified by comparison with three benchmarking models, ANN, SVM with RBF kernel, and Random Forest, using a statistical five-fold cross-validation method. The proposed method showed an improved average performance of 0.6% and 2.7% in both accuracy and AUC criteria when compared with the SVM model with the highest classification performance of the three models respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7844-7854
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• 2015

The purpose of this study is to investigate the drinking status, health behaviors, health related quality of life and depression among female problem drinkers and to examine the impact of their health behavior and health related quality of life on depression. The data of this study were derived from the 5th Korea National Health and Nutrition Examination Survey conducted during January 2010-December 2012. As for the subjects of this study, 328 female problem drinkers were selected who were classified as those with 8 or higher scores in the AUDIT, and complex samples analysis was conducted using the IBM SPSS Statistics version 21.0 software package. The study result showed that the risk of experiencing depression increased among subjects with a high level of perceived stress and subjects with a low level of health related quality of life. In addition, the risk of experiencing depression increased among subjects with 1-4 hours of sleep time compared to subjects with 8 or more hours of sleep time. Accordingly, it would be necessary to pay attention to stress, sleep time and health related quality of life that are related influencing factors for the improvement of depression and mental health of Korean female problem drinkers.

• Therapeutic Science for Rehabilitation
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• v.10 no.3
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• pp.43-56
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• 2021

Objective : The objective of this study was to present the components of frailty by organizing the definitions of frail elderly and analyzing the tools used to screen them. Methods : This study searched for articles at involved frailty screening assessments in the elderly. Databases including CINAHL, Embase, Medline Complete, and PubMed were searched. The search terms were "assess" AND "frailty" AND "screening" AND ("frail elderly" OR "elderly"). Results : A total of 539 articles were identified by the search and 11 articles were selected. Frailty occurs due to the depressed function of multidimensional factors, and a frail elderly person is defined as one at high risk of health degeneration, functional impairment, and occurrence of disability, and having a high level of threat to life. Seven tools were selected from 11 articles. The most frequently used tool was the frailty phenotype, which was used in five articles (45.4%). The identified components of frailty were physical, activity participation, nutrition, psychological, social, overall health, and age. Conclusion : The results confirmed the definition and components of frailty. This study is expected to contribute to the future development of standardized evaluation tools for screening frail elderly individuals and intervention programs for the management of the frail elderly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.354-360
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• 2021

People hope to live a healthy and happy life achieving satisfaction by striking a good work-life balance. Therefore, there is a growing interest in well-aging which means living happily to a healthy old age without worry. This study identified important factors related to well-aging by analyzing news articles published in Korea. Using Python-based web crawling, 1,199 articles were collected on the news service of portal site Daum till November 2020, and 374 articles were selected which matched the subject of the study. The frequency analysis results of text mining showed keywords such as 'elderly', 'health', 'skin', 'well-aging', 'product', 'person', 'aging', 'female', 'domestic' and 'retirement' as important keywords. Besides, a social network analysis with 45 important keywords revealed strong connections in the order of 'skin-wrinkle', 'skin-aging' and 'old-health'. The result of the CONCOR analysis showed that 45 main keywords were composed of eight clusters of 'life and happiness', 'disease and death', 'nutrition and exercise', 'healing', 'health', and 'elderly services'.

• Therapeutic Science for Rehabilitation
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• v.11 no.4
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• pp.23-39
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• 2022

Objective : To summarize clinical and demographic variables and machine learning uses for predicting functional outcomes of patients with stroke. Methods : We searched PubMed, CINAHL and Web of Science to identify published articles from 2010 to 2021. The search terms were "machine learning OR data mining AND stroke AND function OR prediction OR/AND rehabilitation". Articles exclusively using brain imaging techniques, deep learning method and articles without available full text were excluded in this study. Results : Nine articles were selected for this study. Support vector machines (19.05%) and random forests (19.05%) were two most frequently used machine learning models. Five articles (55.56%) demonstrated that the impact of patient initial and/or discharge assessment scores such as modified ranking scale (mRS) or functional independence measure (FIM) on stroke patients' functional outcomes was higher than their clinical characteristics. Conclusions : This study showed that patient initial and/or discharge assessment scores such as mRS or FIM could influence their functional outcomes more than their clinical characteristics. Evaluating and reviewing initial and or discharge functional outcomes of patients with stroke might be required to develop the optimal therapeutic interventions to enhance functional outcomes of patients with stroke.

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.65-80
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• 2022

Objective : This study examined the psychometric properties of the 12-item Coping Orientation to Problems Experienced Scale (COPE) using Rasch analysis. COPE is one of the instruments used to measure stress-coping skills. Methods : The study participants were 480 community-dwelling older adults. We tested the instrument's unidimensionality assumption using principal component analysis (PCA). Item fit was examined using infit-and-outfit mean-square (MnSq) and standardized fit statistics (ZSTD). The precision and item difficulty hierarchies of the instrument were examined. The item-difficulty hierarchy was investigated to identify the easy and difficult items. We tested differential item functioning (DIF) for sex and age groups. Results : PCA revealed that the instrument met the unidimensionality assumption (eigenvalue = 1.78). Among the 12 items, item 2 was removed because of misfit (Infit MnSq = 1.33, Infit ZSTD = 5.05, Outfit MnSq = 1.56, Outfit ZSTD = 7.15). The remaining 11 items demonstrated a conceptual item-difficulty hierarchy. The person strata value was 3.10, which is equivalent to a reliability index value of 0.81. There was no DIF for the sex and age groups (DIF contrast <0.27). Conclusion : The findings indicated that the revised COPE-11 has adequate item-level psychometric properties and can accurately measure stress coping skills.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.541-546
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• 2021

Recently, there is a trend of developing various identification and prediction models for hypertension using clinical information based on artificial intelligence and machine learning around the world. However, most previous studies on identification or prediction models of hypertension lack the consideration of the ideas of non-invasive and cost-effective variables, race, region, and countries. Therefore, the objective of this study is to present hypertension prediction model that is easily understood using only general and simple sociodemographic variables. Data used in this study was based on the Korea National Health and Nutrition Examination Survey (2018). In men, the model using the naive Bayes with the wrapper-based feature subset selection method showed the highest predictive performance (ROC = 0.790, kappa = 0.396). In women, the model using the naive Bayes with correlation-based feature subset selection method showed the strongest predictive performance (ROC = 0.850, kappa = 0.495). We found that the predictive performance of hypertension based on only sociodemographic variables was higher in women than in men. We think that our models based on machine leaning may be readily used in the field of public health and epidemiology in the future because of the use of simple sociodemographic characteristics.