• The Journal of Korean Society for School & Community Health Education
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• v.16 no.1
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• pp.65-81
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• 2015

Objectives: This descriptive study was aimed to investigate the related factors of smartphone addiction among preschool children. Methods: The subject of study was 186 smartphone using mothers with children between 3 to 6 years old in Busan. Data were collected with self-administered questionnaires from July to November, 2013 at nurseries, preschools, and cultural center. Data were analyzed using descriptive statistics, t test, ANOVA, and stepwise multiple regression. Results: 79.6% of children have ever used smartphone and mean smartphone addiction of them were 26.77 based on 60 points. The related factors of smartphone addiction among children were the children's smartphone usage time per day (less than 0.5 hours vs 0.5-0.9 hours (p=0.004), less than 0.5 hours vs more than 1.0 hours (p<0.001), mother's smartphone addiction (p<0.001), and perceived mother's permission level compared to other children's mothers (p=0.004), which 3 factors explained 39% of variance of smartphone addiction of children. Conclusions: Considering the related factors of smartphone addiction among preschool children, mothers should recognize the importance of the their use smartphone and attitude toward smartphone use of children, and take measure to limit children's excessive use of smartphone.

• Journal of IKEEE
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• v.19 no.2
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• pp.237-243
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• 2015

Recently, eight out of ten people have smartphone in Korea. Also, many applications of smartphone have increased. So, smartphone addiction has become a social issue. Especially, many people in smartphone addiction can't control themselves. Sometimes they don't realize that they are smartphone addiction. Many studies, mostly surveys, have been conducted to diagnose smartphone addiction, e.g. S-measure. In this paper, we suggest how to detect smartphone addiction based on ECG and Eye Gaze. We measure the signals of ECG from the Shimmer and the signals of Eye Gaze from the smart eye when the subjects see the emotional video. In addition, we extract features from the S-transform of ECG. Using Eye Gaze signals(pupil diameter, Gaze distance, Eye blinking), we extract 12 features. The classifier is trained using Random Forest. The classifiers detect the smartphone addiction using the ECG and Eye Gaze signals. We compared the detection results with S-measure results that surveyed before test. It showed 87.89% accuracy in ECG and 60.25% accuracy in Eye Gaze.

• 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 Society of School Health
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• v.33 no.1
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• pp.48-57
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• 2020

Purpose: The purpose of this study is to identify the relationship between perceived smartphone addiction and physical and mental health among female college students. Methods: Data were collected using a questionnaire to measure perceived smartphone addiction and physical and mental health of 314 female students attending a college located in D city from April 9 to May, 31, 2019. The collected data were analyzed using descriptive statistics, 𝑥² test, t-test and stepwise multiple regression with SPSS 18. Results: The respondents were classified into two groups, the perceived smartphone addiction group (29.3%) and the perceived smartphone non-addiction group (70.7%). Perceived smartphone addiction was significantly different according to daily smartphone usage time (p<.001), smartphone usage fee (p=.005), most satisfying thing about using smartphones (p=.006) and importance of smartphones in daily life (p<.001). The perceived smartphone addiction group had more physical health problems (p=.001) and more mental health problems (p<.001). The factors affecting physical health were perceived smartphone addiction and importance of smartphones in daily life, with 62% of explanatory power (F=10.15, p<.001). As for mental health, the affecting factors were also perceived smartphone addiction and importance of smartphones in daily life, with 87% of explanatory power (F=14.52, p<.001). Conclusion: It is important to raise awareness of smartphone addiction including its negative impact on physical and mental health, reduce smartphone usage time, and build offline social relationships.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.88-99
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• 2017

This study investigated the clinical characteristics of the Internet addiction risk group using MMPI-2 and discussed whether the MMPI-2 can be used for diagnosis, evaluation and intervention of the Internet addiction risk group. We verified the difference in the MMPI-2 scales between the addiction-risk group and the general user group, and verified whether the substance-related scales MAC-R, AAP, and AAS scales can distinguish between Internet addiction risk group and general users. The results of the analysis of the MMPI-2 characteristics of 39 Internet addiction risk group and 21 general user group who visited internet addiction counseling center showed significant difference in the D, Pa, Pt, Sc, and Si scales on the clinical scale. There was no difference in the MAC-R, AAS, and APS scales between the Internet addiction group and the general user group. This suggests, that it is not possible to screen the Internet addiction risk group with the supplementary measure, and it is necessary to develop a new scale to diagnose internet addiction.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.21-37
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• 2021

This study investigated the intellectual structure of the latest trends in Korean addiction research in the social sciences. A network analysis of keywords with co-word occurrence was performed on 172 papers from the KCI database based on the data from the year of 2019, and a total of 432 keywords were extracted. The network analysis was performed using several programs: Bibexcel, COOC, WNET, and NodeXL. As a result of the study, keywords related to addiction type, study subjects, research methods, and research variables were found, and a total of 20 clusters were identified. Furthermore, to identify and measure weighted networks, the relationships between each keyword were explored and discussed in detail through a network analysis of global centralities, local centralities, and betweenness centralities. The study indicated that the latest issues were focused on smartphone addiction and provided implications for the future research and practice that fields and topics of relationship addiction, food addiction, and work addiction should be more considered. Further, the study discussed the relationship between drug addiction-crime, alcohol addiction-family, and gambling addiction-motivation and the necessity of qualitative study.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.77-86
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• 2012

The significances of this study are that it offers the possibility of empirical measure, and analysis of the relevance among the temperament according to the degree of Internet addiction, parental rearing behaviors, and committing school violence and that, based on this, were drawn policy suggestions to prevent school violence according to the degree of Internet addiction. According to the results of this study it was revealed that there are differences in Internet addiction depending on the demographical and sociological characteristics. The result of investigating the impact of Internet addiction's degree on the actions of committing school violence shows that the level of general activities is high in the group of young people of Internet addiction and addiction risk, their low access/withdrawal temperament and mood temperament affect significantly the actions of committing school violence, and in parenting behavior mother's high expectations and low supervision affect youth Internet addiction and school violence. Thus, policy suggestions to prevent school violence according to Internet addiction were presented y dividing the role of government and schools, and homes.

• Research in Community and Public Health Nursing
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• v.28 no.3
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• pp.280-290
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• 2017

Purpose: The aim of this research is to examine the moderating effects of self-esteem and resilience in the relationship between smartphone addiction and depression among middle school students. Methods: Data were collected from 324 middle school students in D City during the period of July 1st-17th, 2015. Multiple regression analysis, the Baron & Kenny's mediation verification, and Sobel test were conducted to measure the mediating effects of self-esteem and resilience on depression. Results: There were significant correlations among the variables; smartphone addiction, self-esteem, resilience, and depression. Self-esteem had a complete mediating effect (${\beta}=-.40$, p<.001) in the relationship between smartphone addiction and depression (Sobel test: Z=4.68, p<.001). Resilience had a partial mediating effect (${\beta}=-.15$, p<.001) in the relationship between smartphone addiction and depression (Sobel test: Z=2.40, p<.001). Conclusion: This study suggests to apply self-esteem and resilience in developing nursing intervention programs for adolescent depression caused by smartphone addiction.

• The Journal of Korean Association of Computer Education
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• v.17 no.6
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• pp.1-8
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• 2014

Recently, use of smartphones has increased so sharply at all ages that addiction problems have emerged. This study analysed factors, focusing on demographic variables, that impact on smartphone addiction of elementary students. First, differences between distributions of addicted groups and those between distributions of most frequently used smartphone functions per variable are analyzed. As a result, grade and academic achievements yield the biggest differences between distributions of addicted groups and gender, grade, and academic achievements yield differences between distributions of most frequently used smartphone functions. Also, differences between distributions of most frequently used smartphone functions per addicted user group are regarded significant. Furthermore, factors affecting smartphone addiction are analysed through the logistic regression analysis and decision trees, where grade, academic achievements, dual-income parents, and residential areas are found affecting in that order.

• Korean Journal of Child Studies
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• v.26 no.1
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• pp.31-46
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• 2005

This study examined internet game addiction and college adaptation(academic, social, personal-emotional, institutional attachment) by Internet game motivation types. The 475 subjects (235 male and 240 female college students) responded to the newly developed self-report measure, Internet Game Motivation Scale (IGMS). Cluster analyses of IGMS data identified 5 types of Internet game motivation: Active I, Active II, Moderate I, Moderate II, Passive. Active (I, II) types had the highest scores in Internet game addiction while the Passive type yielded the lowest. Except for academic adaptation, all aspects of college adaptation varied as a function of Internet game motivation types. Overall, Moderate II showed highest whereas Active I showed lowest academic adaptation scores.