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      대학생의 자기결정성, 우울, 자아존중감, 충동성이 스마트폰중독에 미치는 영향

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      https://www.riss.kr/link?id=T13853355

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      This study aimed to identify the influencing factors on smartphone addiction by examining the relationships between smartphone addiction, self-determination, depression, self-esteem, and impulsivity in college students, and ultimately to provide basic information for developing smartphone addiction prevention programs.
      As research subjects, this study conducted a survey of 263 college students from two universities. Data were collected from Sept. 22, 2014 to Sept. 30, 2014. For the data collected, SPSS/WIN 21.0 program was used for statistical analysis and real number and percentage, mean and standard deviation, t-test, ANOVA, Tukey post-hoc test, Pearson's correlation coefficients, and multiple regression analysis were also used.

      Our findings were summarized as follows:

      1. For general characteristics of college students and the patterns of their use of smartphone, ‘males’ was 50.95% and that of ‘females’ 49.05%. Their average age was 20.98 years old. As type of housing, most of them (142 subjects, 54.%) responded to ‘parent's house.’ As satisfaction with school life, they responded to ‘moderate’ (111 subjects, 42.2%) the most. As subjective economic condition, they responded to ‘moderate’ (178 subjects, 67.7%) the most. As function that they use with smartphone, they responsed to ‘chatting, messenger’ (141 subjects, 53.6%) the most, As average monthly fee, they responded to ‘more than 70 thousand won’ (119 subjects, 45.3%) the most. As hours that they use with smartphone, they responded to ‘3 to 6 hours’ (115 subjects, 43.7%) the most. They appeared to have used smartphone for 5 hours and 35 minutes on average. As percentage that they use smartphone in everyday life, they responded to ‘moderate’ (128 subjects, 48.7%) the most.
      2. The percentage of smartphone addition was 89.4% for general users, 7.2% for potential risk users, and 3.4% for high-risk users. In particular, 4.5% of male was smartphone addicted users and 17.1% for females, which suggested that the number of female students was three times higher than that of male students. Self-determination score was 3.70 on average and subfactors autonomy, competence, and relationship appeared at 3.64, 3.53, and 3.95 point, respectively. And depression score was 0.83 on average, self-esteem score 3.62, and ‘impulsivity’ score 2.19.
      3. To look at the difference in smartphone addiction depending on the general characteristics of college students and the patterns that they use with smartphone, there was no significant difference in age, housing type, subjective economic state, and average monthly fee, among the general characteristics and the patterns that they use with smartphone, and in satisfaction with school life, it appeared that ‘unsatisfied’ was at 33.31 point, ‘moderate’ at 31.48, and ‘satisfied’ at 29.01, which suggested that unsatisfied students with school life showed a higher score in smartphone addiction than moderate or satisfied students (F=7.23, p=.001). To look at the hours for which they use with smartphone, ‘6 hours or more’ was at 33.40 point, ‘3 to 6 hours’ at 31.92, and ‘3 hours or less’ at 28.08, which suggested that students who used smartphone for 3 hours or more showed a higher score in smartphone addiction than students who used smartphone for 3 hours or less (F=12.94, p<.001). To look at the percentage that they use with smartphone in every life, ‘important’ was at 35.92 point, ‘moderate’ at 29.26, and ‘unimportant’ at 24.95, which suggested that students who thought smartphone important showed a higher score in smartphone addiction than students who thought smartphone moderate and again students who thought smartphone moderate showed a higher score in smartphone addiction than students who thought smartphone important(F=60.47, p=.000).
      4. There was a negative correlation between smartphone addiction and autonomy (r=-.363), competence (r=-.289), relativity(r=-.179), and self-esteem (r=-.404). And, there was a positive correlation between smartphone addiction and depression (r=.383) and impulsivity (r=.360).
      5. As a result of multiple regression analysis for identifying the influential factors to the smartphone addiction in college students, it appeared that the influential factors to the smartphone addiction in college students were percentage of smartphone in everyday life (β=.503, p<.001), self-esteem (β=-.176, p=.020), and impulsivity (β=.179, p=.000). As a result of looking at the explanatory power by factor in stages, it appeared that the percentage of smartphone in everyday life was explanatory of smartphone addiction at 35.7%, the highest explanatory power, and self-esteem and impulsivity was 8.1%, 3.2%, respectively.

      In conclusion, given that the higher recognition of smartphone in everyday life, the lower the self-esteem, and the higher the impulsivity, the higher the smartphone addiction becomes, self-control programs to enhance self-esteem and adjust impulsivity and cognitive behavior adjustment to change the recognition of the percentage of smartphone in everyday life are required for reducing the smartphone addiction.
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      This study aimed to identify the influencing factors on smartphone addiction by examining the relationships between smartphone addiction, self-determination, depression, self-esteem, and impulsivity in college students, and ultimately to provide basi...

      This study aimed to identify the influencing factors on smartphone addiction by examining the relationships between smartphone addiction, self-determination, depression, self-esteem, and impulsivity in college students, and ultimately to provide basic information for developing smartphone addiction prevention programs.
      As research subjects, this study conducted a survey of 263 college students from two universities. Data were collected from Sept. 22, 2014 to Sept. 30, 2014. For the data collected, SPSS/WIN 21.0 program was used for statistical analysis and real number and percentage, mean and standard deviation, t-test, ANOVA, Tukey post-hoc test, Pearson's correlation coefficients, and multiple regression analysis were also used.

      Our findings were summarized as follows:

      1. For general characteristics of college students and the patterns of their use of smartphone, ‘males’ was 50.95% and that of ‘females’ 49.05%. Their average age was 20.98 years old. As type of housing, most of them (142 subjects, 54.%) responded to ‘parent's house.’ As satisfaction with school life, they responded to ‘moderate’ (111 subjects, 42.2%) the most. As subjective economic condition, they responded to ‘moderate’ (178 subjects, 67.7%) the most. As function that they use with smartphone, they responsed to ‘chatting, messenger’ (141 subjects, 53.6%) the most, As average monthly fee, they responded to ‘more than 70 thousand won’ (119 subjects, 45.3%) the most. As hours that they use with smartphone, they responded to ‘3 to 6 hours’ (115 subjects, 43.7%) the most. They appeared to have used smartphone for 5 hours and 35 minutes on average. As percentage that they use smartphone in everyday life, they responded to ‘moderate’ (128 subjects, 48.7%) the most.
      2. The percentage of smartphone addition was 89.4% for general users, 7.2% for potential risk users, and 3.4% for high-risk users. In particular, 4.5% of male was smartphone addicted users and 17.1% for females, which suggested that the number of female students was three times higher than that of male students. Self-determination score was 3.70 on average and subfactors autonomy, competence, and relationship appeared at 3.64, 3.53, and 3.95 point, respectively. And depression score was 0.83 on average, self-esteem score 3.62, and ‘impulsivity’ score 2.19.
      3. To look at the difference in smartphone addiction depending on the general characteristics of college students and the patterns that they use with smartphone, there was no significant difference in age, housing type, subjective economic state, and average monthly fee, among the general characteristics and the patterns that they use with smartphone, and in satisfaction with school life, it appeared that ‘unsatisfied’ was at 33.31 point, ‘moderate’ at 31.48, and ‘satisfied’ at 29.01, which suggested that unsatisfied students with school life showed a higher score in smartphone addiction than moderate or satisfied students (F=7.23, p=.001). To look at the hours for which they use with smartphone, ‘6 hours or more’ was at 33.40 point, ‘3 to 6 hours’ at 31.92, and ‘3 hours or less’ at 28.08, which suggested that students who used smartphone for 3 hours or more showed a higher score in smartphone addiction than students who used smartphone for 3 hours or less (F=12.94, p<.001). To look at the percentage that they use with smartphone in every life, ‘important’ was at 35.92 point, ‘moderate’ at 29.26, and ‘unimportant’ at 24.95, which suggested that students who thought smartphone important showed a higher score in smartphone addiction than students who thought smartphone moderate and again students who thought smartphone moderate showed a higher score in smartphone addiction than students who thought smartphone important(F=60.47, p=.000).
      4. There was a negative correlation between smartphone addiction and autonomy (r=-.363), competence (r=-.289), relativity(r=-.179), and self-esteem (r=-.404). And, there was a positive correlation between smartphone addiction and depression (r=.383) and impulsivity (r=.360).
      5. As a result of multiple regression analysis for identifying the influential factors to the smartphone addiction in college students, it appeared that the influential factors to the smartphone addiction in college students were percentage of smartphone in everyday life (β=.503, p<.001), self-esteem (β=-.176, p=.020), and impulsivity (β=.179, p=.000). As a result of looking at the explanatory power by factor in stages, it appeared that the percentage of smartphone in everyday life was explanatory of smartphone addiction at 35.7%, the highest explanatory power, and self-esteem and impulsivity was 8.1%, 3.2%, respectively.

      In conclusion, given that the higher recognition of smartphone in everyday life, the lower the self-esteem, and the higher the impulsivity, the higher the smartphone addiction becomes, self-control programs to enhance self-esteem and adjust impulsivity and cognitive behavior adjustment to change the recognition of the percentage of smartphone in everyday life are required for reducing the smartphone addiction.

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      목차 (Table of Contents)

      • I. 서론 1
      • 1. 연구의 필요성 1
      • 2. 연구목적 3
      • 3. 용어정의 4
      • II. 문헌고찰 6
      • I. 서론 1
      • 1. 연구의 필요성 1
      • 2. 연구목적 3
      • 3. 용어정의 4
      • II. 문헌고찰 6
      • 1. 스마트폰중독 6
      • 1) 스마트폰 이용 행태 6
      • 2) 스마트폰중독 7
      • 3) 스마트폰중독에 영향을 미치는 요인 9
      • 2. 자기결정성 11
      • 3. 우울 13
      • 4. 자아존중감 15
      • 5. 충동성 17
      • III. 연구방법 20
      • 1. 연구 설계 20
      • 2. 연구 대상 20
      • 3. 연구 도구 20
      • 4. 자료 수집방법 22
      • 5. 자료 분석방법 23
      • Ⅳ. 연구결과 25
      • 1. 대학생의 일반적 특성 및 스마트폰 이용 행태 25
      • 2. 대학생의 스마트폰중독, 자기결정성, 우울, 자아존중감, 충동성의 정도 28
      • 3. 대상자의 일반적 특성과 스마트폰 이용 행태에 따른 스마트폰중독의 차이 30
      • 4. 대상자의 자기결정성, 우울, 자아존중감, 충동성, 스마트폰중독의 상관관계 33
      • 5. 대상자의 스마트폰중독에 영향을 미치는 요인 35
      • Ⅴ. 논의 37
      • Ⅵ. 결론 및 제언 44
      • 1. 결론 44
      • 2. 제언 46
      • 참고문헌 47
      • 부록 56
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