• PNF and Movement
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• v.22 no.1
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• pp.101-111
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• 2024

Purpose: The purpose of this study was to investigate physical activity as a risk factor for neck pain recurrence using the National Health Insurance Data Sharing Service that utilizes a nationwide cohort in South Korea. Methods: Medical records spanning a two-year period were extracted from the National Health Insurance database for 541,937 patients who sought healthcare services for neck pain (ICD 10 codes: M54.2) in 2020 and completed the national health examination survey. Selected variables for analysis included age, gender, health insurance premium decile, regional health vulnerability index, body mass index (BMI), acuity, blood pressure, and types of physical activity. A mixed-effect multivariate logistic regression analysis was conducted to examine the recurrence rate of neck pain and identify risk factors for neck pain recurrence. Results: Among the participants, 124,433 patients (23.0%) experienced a recurrence of neck pain within two years, with higher recurrence rates observed among older individuals and females. Regression analysis revealed that the risk of neck pain recurrence increased with age (OR=1.51), being female (OR= 1.10), being a medical aid recipient (OR=1.51), and having anaerobic (OR=1.04) or vigorous physical activities (OR=1.06). By contrast, an increased health insurance premium decile (OR=0.96) and having moderate physical activity (OR=0.97) were associated with a decreased risk of neck pain recurrence. Conclusion: This study highlights the importance of moderate physical activity as an effective strategy for reducing the recurrence of nonspecific neck pain, underscoring the necessity for personalized physical activity programs for patients.

• Journal of dental hygiene science
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• v.24 no.1
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• pp.9-21
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• 2024

Background: The purpose of this study was to utilize text network analysis and topic modeling to identify interconnected relationships among keywords present in patent information related to oral health, and subsequently extract latent topics and visualize them. By examining key keywords and specific subjects, this study sought to comprehend the technological trends in oral health-related innovations. Furthermore, it aims to serve as foundational material, suggesting directions for technological advancement in dentistry and dental hygiene. Methods: The data utilized in this study consisted of information registered over a 20-year period until July 31st, 2023, obtained from the patent information retrieval service, KIPRIS. A total of 6,865 patent titles related to keywords, such as "dentistry," "teeth," and "oral health," were collected through the searches. The research tools included a custom-designed program coded specifically for the research objectives based on Python 3.10. This program was used for keyword frequency analysis, semantic network analysis, and implementation of Latent Dirichlet Allocation for topic modeling. Results: Upon analyzing the centrality of connections among the top 50 frequently occurring words, "method," "tooth," and "manufacturing" displayed the highest centrality, while "active ingredient" had the lowest. Regarding topic modeling outcomes, the "implant" topic constituted the largest share at 22.0%, while topics concerning "devices and materials for oral health" and "toothbrushes and oral care" exhibited the lowest proportions at 5.5% each. Conclusion: Technologies concerning methods and implants are continually being researched in patents related to oral health, while there is comparatively less technological development in devices and materials for oral health. This study is expected to be a valuable resource for uncovering potential themes from a large volume of patent titles and suggesting research directions.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.34 no.2
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• pp.38-52
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• 2021

Objectives : The purpose of this study is to analyze the use of insured herbal extracts and Korean medicinal treatments, which are mainly used to treat allergic rhinitis in Korean medicine. Methods : Among all HIRA(Health Insurance Review and Assessment Service) claims data in 2016, we included all statements that included J30(vasomotor and allergic rhinitis) or a subcategory of J30(J30.0, J30.1, J30.2, J30.3, or J30.4) as the main disease, using the Korean Standard Classification of Diseases(KCD-7). This study analyzed the most frequently used insured herbal extracts and Korean medicinal treatments for allergic rhinitis in Korean medicine. We performed a frequency analysis on subgroups based on treatment type(inpatient or outpatient), sex, age, insurance type, and medical institution type. Results : The result shows the 10 most frequently used insured herbal extracts and Korean medicinal treatments for allergic rhinitis. The total number of insured herbal extracts prescriptions was 82,533, and the most commonly prescribed insured herbal extracts was socheongryong-tang(35,131 prescriptions), followed by hyeonggaeyeongyo-tang(18,157 prescriptions), samsoeum(6,257 prescriptions), and galgeun-tang(4,465 prescriptions). The total number of Korean medicinal treatments prescriptions was 1,878,541, of which the most common Korean medicinal treatments was acupuncture(922,977 prescriptions), followed by moxibustion(372,120 prescriptions), cupping(242,094 prescriptions), and segmental acupuncture(161,553 prescriptions). Conclusions : It is expected that the results of this study can be used as a basis for establishing the priorities of evidence-based clinical research topics in the field of Korean medicine and making health care policy decisions to strengthen coverage in the future.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.2
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• pp.229-238
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• 2023

The objective of this study was to investigate trends in ankyloglossia and its surgical treatment among pediatric patients in South Korea from 2011 to 2020. Data from Health Insurance Review and Assessment Service (HIRA)'s Healthcare Bigdata Hub were used for analysis of the ankyloglossia diagnosis rate and frenum surgery rate. Considering annual population change, crude rates per 100,000 were calculated and analyzed. To investigate other factors of frenum surgery incidence besides gender and age, pediatric patient sample data from HIRA were used. The diagnosis rate of ankyloglossia increased from 204.4 in 2011 to 356.6 per 100,000 people in 2020, while the frenum surgery rate increased from 26.8 to 34.3 per 100,000 people. Males were more likely to receive frenum surgery than females. Surgeries were more likely to be done at a hospital instead of a clinic or a general hospital. In the age group of 0 - 4 years, the largest number of frenum surgeries were performed in pediatrics, and in the age group of 5 - 9 years, the largest number of surgeries were conducted in pediatric dentistry. In the older age groups, the largest proportion of frenum surgeries were performed in the departments of conservative dentistry and oral and maxillofacial surgery. The diagnosis of ankyloglossia and the operation of frenum surgery among South Korean children increased during the last decade. Since the function of the tongue can affect maxillofacial development in many aspects, pediatric dentists should pay more attention to the functional management of intraoral soft tissue in growing children.

• Culinary science and hospitality research
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• v.15 no.4
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• pp.286-298
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• 2009

The purpose of this study is to determine potential associations among consumer preference for American beef, consumers' involvement in selection of desired beef, and their intentions to purchase beef. In order to meet the above purpose, this study surveyed the visitors who shopped at 2 big discount stores selected in each of 3 metropolitan cities(Seoul, Daejeon and Daegu) from July 11 to 13, 2008. Total 278 sheets of the questionnaire were collected and used for final data analysis. As a result, it was found that the consumers responded most sensitively to the safety of food when buying beef but didn't care much about the amount of fat and beef brand. In terms of imported beef, it was found that Australian beef was considered reliable by consumers, and their preference for Korean beef was positively correlated with that for Australian beef. In addition, in regard to the attributes of beef selection, it was found that low involvement group had higher intentions to purchase American beef than high involvement group. In order to determine the potential effects of consumers' involvement in the attributes of beef selection on their intentions to purchase American beef, this study conducted data analysis in control of consumer preference for American beef. As a result, it was found that consumers' involvement in the attributes of beef selection had significant effects on their intentions to buy American beef. And sex was found to be one of the demographic characteristics associated with involvement in the attributes of beef selection, particularly associated with low involvement. Depending on sex, it was found that women had lower preference for American beef than men.

• Journal of the Economic Geographical Society of Korea
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• v.7 no.1
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• pp.97-115
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• 2004

The purpose of this study is to investigate the spatial pattern of retail services and the consumer behaviors. For the purpose we select Jeju Island as the study area, because it retains relatively little distorted retail service systems by it's locational isolation. The retail service systems comprise three types: large-scale modern marts, conventional markets, and periodic markets. This study attempts to examine the interrelationships between these three different types, of retail services, and to figure out the spatial characteristics of consumer behaviors for each of them. We performed questionnaire surveys for getting the data of consumer behaviors. We applied several statistical methods to analyze the survey data. Most of retail services are located in two urban centers, Jeju City and Seoguipo City. We found that the locations of retail services are determined strongly by population size. The selection of market type and the location to go for shopping are related strongly with the types of goods. However, there is a wide difference in the consumer behaviors according to the consumer's socio-economic characteristics. Young wives tend to go shopping to large-scale marts in Jeju City which is the higher level central place, while old wives go shopping to conventional markets and periodic markets. They also show different shopping behaviors according to the household income levels. Low income groups prefer to go conventional markets located near to their residence, middle income groups go to large-scale marts in Jeju, and high income group go out of the Jeju Island. However, the consumer behavior does not show big difference according to the size of family. There are also no difference in the selection for shopping location according to the consumer's resident locations.

• The Korean Journal of Franchise Management
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• v.10 no.1
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• pp.43-52
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• 2019

Purpose - Many companies use the Internet to conduct their business to maintain and acquire their customers. SNS is used as a site where users can create profiles, build personal networks, and then share and exchange information with others. Not only do people use SNS for their self-promotion, but they also promote their services by creating SNS pages. SNS is recognized as a medium for implementing effective advertising strategies and is being used as an important means of promoting the company. Therefore, in this study, we investigate the effect of SNS marketing characteristics of restaurant franchise firms on utilitarian value and hedonic value and examine their effects on purchase intention. Research design, data, and methodology - The data were collected from 20s-60s respondents who have used SNS for restaurant visit using Google survey. A total of 159 responses were collected and used for final analysis. Smart PLS 3.0 was used for the hypothesis test. Results - As a result of an analysis, it was shown that the influence of the playfulness and affordability of information on the utilitarian value had a significant positive effect. Interaction and up-to-date did not have a positive effect on utilitarian value. Interaction, affordability, and up-to-date have no significant positive effects on hedonic value. The playfulness of information has a positive effect on the hedonic value. Both utilitarian value and hedonic value had positive effects on purchase intention. Conclusions - The findings of this study suggest that the SNS marketers of restaurant franchisors should focus on the playfulness, affordability, and up-to-date rather than the interactivity of SNS. In marketing through SNS, the act of presenting the basis of information and enhancing the provision of information through objective criteria makes it possible to experience the practical value of information. It is necessary to develop differentiated contents which cause customers interest and fun and to induce many customers' purchase intent by providing objective and realistic information. In order to increase the customers' repurchase intentions toward the food service business, customers should maximize the hedonic value and practical value felt through information. It should also focus on providing information that customers are receptive to, rather than providing prompt information.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.157-171
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• 2021

The purpose of this study is to assess the smart city for major cities in Korea. The assessment indicators are based on the STIM structure (Service, Technology, Infrastructure, and Management Layer Architecture) of the Multi-Layered Smart City Model. Assessment indicators are established through smart city concepts, case analysis, big data analysis, as well as weighted through expert AHP survey. For the assessment, seven major metropolitan cities are selected, including Seoul, and their data such as KOSIS, KISDISTAT from 2017 to 2019 is utilized for the smart city level assessment. The smart city level results show that the service, technology, infrastructure, and management levels were relatively high in Seoul and Incheon, which are metropolitan areas. Whereas, Busan, Daegu, and Ulsan, the Gyeongsang provinces are relatively moderate, while Daejeon and Gwangju, the South Chungcheong region and the Jeolla provinces, were relatively low. The overall STIM ranking shows a similar pattern, as the Seoul metropolitan area smart city level outperforms the rest of the analyzed areas with a large difference. Accordingly, balanced development strategies are needed to reduce gaps in the level of smart cities in South Korea, and respective smart city plans are needed considering the characteristics of each region. This paper will follow the literature review, assessment index establishment, weight analysis of assessment index, major cities assessment and result in analysis, and conclusion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.