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Subject

Classifying latent profiles in mobile phone usage and dependency of adolescents and testing the effects of determinants
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잠재프로파일 분석을 통한 청소년의 휴대전화 사용과 의존도 유형 분류 및 관련 변인들의 영향력 검증

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Type
Academic journal
Author
Lee, Jungmin (충남대학교) Chung, Hyewon (충남대학교)
Journal
National Youth Policy Institute Studies on Korean Youth Vol.27 No.2(Wn.81) KCI Accredited Journals
Published
2016.5
Pages
121 - 157 (37page)

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Classifying latent profiles in mobile phone usage and dependency of adolescents and testing the effects of determinants
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This study explored how students could be classified into latent groups in terms of mobile phone usage and dependency and what factors were related to each class. Latent profiles were conducted using the 5th wave of data from the KCYPS 2011. Based on the results of the latent profiles, the final model yielded four latent classes of mobile phone dependency: ‘high-level dependency’, ‘middle-level dependency’, low-level dependency’ and ‘low-dependency efficiency’. It was also found that high-level dependency was one of the highest in terms of proportion. Multinomial logistic regression analysis revealed that factors related differently to each latent class. Compared to the low-dependency efficiency class, the middle-level dependency class was significantly related to high levels of parental neglect and low learning activity. In particular, the high-level dependency class tended to use a mal-functional mobile phone due to excessively cohesive peer attachment. The results of latent profile analysis indicated that a program should be created not only for students but also for parents, schools and the local community to participate in. This study can be utilized to predict latent classes according to various background variables that are susceptible to mobile phone dependency, focusing on 2nd grade students in high school. Prevention and appropriate intervention methods for mobile phone dependency were also discussed.

Contents

초록
Ⅰ. 서론
Ⅱ. 이론적 배경
Ⅲ. 연구방법
Ⅳ. 결과 및 해석
Ⅴ. 논의 및 결론
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UCI(KEPA) : I410-ECN-0101-2017-334-000695578