• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1203-1209
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• 2010

Internet addiction is a serious social problem in information society. The purpose of this study is to develope a small diagnostic scale in order to detect internet addiction easily. The reliability and validity of K-scale and Kimberly Young-scale is investigated. Five small diagnostic scale is suggested by factor analysis and regression. The comparision of these small scale is established by correlation coefficient, chi-square test, gamma value of concordance in contingency table. In view of reliability and validity, we suggest a small diagnostic scale. The results of this study may be useful to detect internet addiction by oneself.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.224-225
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• 2012

본 연구에서는 기존의 한국정보화진흥원의 인터넷 중독진단 척도인 K-척도와 2012년 새롭게 발표된 성인 인터넷 중독 자가진단 간략형 척도인 KS-A를 비교함으로써 성인 인터넷 중독진단의 현황과 문제점을 확인한다.

• The Journal of Korean Association of Computer Education
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• v.17 no.3
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• pp.1-10
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• 2014

Smartphone addiction and internet addiction cause a serious negative social problem due to the spread of the new media which is combined with the ubiquitous function. To evaluate the degree of Internet addiction and smartphone addiction of college students in the nearby areas, K-scale of internet addiction self-diagnosis scale and S-scale of smartphone addiction self-diagnosis scale for Korean adults were applied. This study aims to develop the survey questions, which get the basic internet patterns and access the web site, and to find the hidden addicts that is not found by general K-scale and S-scale using computers and smartphones. The result shows that a method of addiction diagnosis using the tolerance degree which is calculated by smart phone's internet main activities and using time(anticipated and real time) apart from K-scale and S-scale. So hidden internet and smartphone addicts could be found through the SPSS statistical analysis program.

• The Journal of Korean Association of Computer Education
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• v.16 no.5
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• pp.39-47
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• 2013

In the case of a weak self-control youth, young students easily tend to fall into addiction by using the Internet as a sensation seeking and an alternative to escape the reality. Until now, internet addiction self-diagnosis techniques such as Internet addiction scale have been developed and used to solve this kind of internet addiction issue. However, traditional methods do not assess the correlation of addiction and the effects of the environment systematically because they are simply composed of redundant addiction scale criteria and questionnaire forms of the diagnostic methods. Thus, in this paper, we propose a new internet addiction self-diagnosis technique based on Formal Concept Analysis (FCA) and implement a self-diagnosis system in order to make a systematic internet addiction self-diagnosis system. In addition, we analyze the correlation of the measured data based on different perspectives such as home environment, family relationships, peer relationships, school life, and so on.

• Journal of Family Resource Management and Policy Review
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• v.11 no.4
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• pp.55-71
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• 2007

The purpose of this study was to explore a self-diagnostic indicator for measuring a healthy family by adopting the theme of "happiness", which has surfaced as the most interesting in many academic fields recently. Though the basic concept of a healthy family may be shared by everyone, the criterion of happiness varies from one family to another. Therefore, it is desirable that the tool be made in such a way that every member of the family can check their health from a holistic perspective, rather than diagnosing health and happiness from the perspective of professionals. So, this study was aimed at diagnosing a family by using a tool named GAMMA model, so each family member can recognize problems and find the best options to solve it. This study. has a significant meaning in that it has tried to diagnose families by introducing the GAMMA model into domestic science for the first time.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.13-22
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• 2013

Smartphone addiction has become more serious than internet addiction since people can download and run numerous applications with smartphones even without internet connection. However, smartphone addiction is not sufficiently dealt with in current studies. The S-scale method developed by Korea National Information Society Agency involves so many questions that respondents are likely to avoid the diagnosis itself. Moreover, since S-scale is determined by the total score of responded items without taking into account of demographic variables, it is difficult to get an accurate result. Therefore, in this paper, we have extracted important factors from all data, which affect smartphone addiction, including demographic variables. Then we classified the selected items with a neural network. The result of a comparative analysis with backpropagation learning algorithm and multiclass support vector machine shows that learning rate is slightly higher in multiclass SVM. Since multiclass SVM suggested in this paper is highly adaptable to rapid changes of data, we expect that it will lead to a more accurate self-diagnosis of smartphone addiction.

• The Journal of Korean Association of Computer Education
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• v.15 no.2
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• pp.47-55
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• 2012

We discovered the fact that the most important factor for judging adults' internet addiction in the K-scale method which was developed by Korea National Information Society Agency (NIA), has composed of 4 categories including 20 items, is tolerance and preoccupation factor from the experiments by using data mining techniques. In this research, we propose a new internet addiction diagnostic method based on the degree of tolerance considering users' non-duty internet activities. From some questionnaire participants, their feedbacks for the K-scale and the proposed diagnostic method were collected, and then we confirmed that the proposed user-centered diagnostic method is effective to find undiscovered addicts due to individuals's intention in the K-scale.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.317-322
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• 2011

Korean adults' internet addiction diagnosis measure, K-scale developed by Korea National Information Society Agency (NIA), has composed of 4 categories including 20 items. This scale can diagnose user's internet addiction with individual's questionnaire items. Most of previous research works were tried to know reasons of internet addiction and to judge whether adolescents are addicted or not with their samples. In this research, it is the goal to find the key component to judge individual's internet addiction by using a decision tree in the data mining field and a principal component analysis in statistics. From the experimental results, we would discover that tolerance and preoccupation factor is the most important one to affect adult's internet addiction.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.7 no.2
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• pp.153-160
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• 1996

The purpose of this study is to find out the factors that affect the prognosis of conduct disorder in the adolescents. According to the nature or behavioral problems during 6 months after discharge, the good prognosis group(N=37) and the poor prognosis group(N= 36) were selected and scores of Youth Self Report(YSR), MMPI, KWIS were compared between both groups. The following results were obtained. 1) In family environmental factors, no significant difference was found between both groups. 2) In YSL total problem score, score of externalizing syndrome and score of delinquent behavior were significantly higher in the poor prognosis group. 3) In MMPI, no significant difference was found between both groups. 4) In KWIS, total 1.0. did not show significant differences between both groups. Our hypothesis that the prognosis of conduct disorder in adolescent is poorer in cases with higher quantities of problematic behaviors is certified.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.3
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• pp.35-45
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• 2011

Due to people's internet use growth and proliferation of ubiquitous technology, the internet addiction is becoming a social issue. However, the current adults' self-diagnosis measure about internet addiction, the K-scale, is a normal diagnostic method, which it does not consider user characteristics. In this research, we will propose a new internet addiction diagnostic method based on users' non-duty internet activities by using some questionnaire items to collect users' basic internet patterns used on duty related or non-duty related web sites. Since we simply ask for the basic internet usage pattern to each user who does not like to check frankly questionnaire items in the K-scale, the proposed method can find some hidden internet addicts compared to the K-scale with the SPSS statistical analysis tool.