ORIGINAL ARTICLE Child Health Nurs Res, Vol.23, No.4, October 2017: ISSN(Print) ISSN(Onli

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1 ORIGINAL ARTICLE ISSN(Print) ISSN(Online) 이은지 1, 김윤경 2, 임수진 3 1 연세대학교대학원간호학과, 2 마산대학교간호학과, 3 인천가톨릭대학교간호대학 Factors Influencing Smartphone Addiction in Adolescents Eun Jee Lee 1, Yune Kyong Kim 2, Su-Jin Lim 3 1 Department of Nursing, The Graduate School, Yonsei University ; 2 Department of Nursing, Masan University, Changwon; 3 College of Nursing, Incheon Catholic University, Incheon, Korea Purpose: The purpose of this study was to verify the relationship among depression, school adjustment, parent-child bonding, parental control and smartphone addiction, and to identify factors which influence smartphone addiction in adolescents. Methods: A cross-sectional design was used, with a convenience sample of 183 middle school students from 3 middle schools. Data collection was conducted through self-report questionnaires from April to May, Data were analyzed using χ 2 test, Fisher s exact test, t-test, one-way ANOVA, correlation coefficient analysis, and binary logistic regression with SPSS Ver Results: The mean score for smartphone addiction was Of the adolescents, 21.3% were in the smartphone addiction risk group. Logistic regression analysis showed that gender (OR=7.09, 95% Cl: 2.57~19.52), school life (OR=0.86, 95% Cl: 0.79~0.93), smartphone usage time (OR=1.32, 95% Cl: 1.04~1.66), and parental control (OR=4.70, 95% Cl: 1.04~21.29) were effect factors for the smartphone addiction risk group. Conclusion: Findings indicate that school satisfaction was an important factor in adolescents smartphone addiction. Control oriented parent management of adolescents smartphone use did not reduce the risk of smartphone addiction and may have worsen the addiction. Future research is needed to improve understanding of how teachers and parents will manage their adolescents use of smartphones. Key words: Smartphone, Addictive behavior, Adolescents, Parents, Schools Corresponding author Yune Kyong Kim Department of Nursing, Masan University, 2640 Hammadaero, Naeseo-eup, Masanhoiwon-gu, Changwon 51217, Korea TEL yunekim27@gmail.com *.. * This manuscript has been submitted solely to this journal and is not published, in press, or submitted elsewhere. This research meets the ethical guidelines, including adherence to the legal requirements of Korea. Key words,,,, Received 1 September 2017 Received in revised form 2 October 2017 Accepted 18 October 2017 서 론 연구의필요성,. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non- Commercial License ( which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited %[1], % [2] % 7.7% 1.5 [3], % [4].. 25 [5], [6]. [7], [6]. DSM-5 (behavioral addiction), [8],,,,,. DSM-5 [8]. Copyright 2017 Korean Academy of Child Health Nursing 525

2 smartphone addiction, mobile phone dependence, nomophobia, problematic mobile phone use [9].,, [3].,,.,,,,, [10]. [5].., -. - [11].,. 40..,.,,,. [12], [13,14].,, [12,15] [14]., [11,16].,..,. ( ), ( - ), ( ). 연구목적.,.,,,, -,.,. 연구방법 연구설계. 연구대상 [17]., 13, 3,,. Binary logistic regression G- power program (Odds ratio), [18] 0.608, p1 = 0.384, α.05, %[2], 80%

3 , %. 연구도구스마트폰중독, [3]. [3]. 4 (1 : 5, 2 : 2, 3 : 4, 4 : 4 ) 15, 4. 8, 10, 13, , , 3 13, 4 14, 42~ , 3 12, 4 13, , 3 11, Cronbach s α.89, 우울,,,, [19], Kovacs Children s Depression Inventory (CDI)[20] Cho Lee [21]. 27, 0~2,. Cho Lee[21] Cronbach s α.82, 어머니-자녀애착 [22], [16] -. Parker - (Parental Bonding Inventory, PBI)[22] Song [23].. 12,, 13, ( ), 1 ( ), 2 ( ), 3 ( ) 4, 3, 4, 7, 8, 15, 16, 21, 22, 25, 4 3. Song[23] Cronbach s α 0.87, 0.94, 0.73 Song[23]. 25 Cronbach s α 학교적응,,, [15], Lee[15]. (8 ), (10 ), (10 ), (10 ) 4 38,,,,. 1 ( ), 2 ( ), 3 ( ), 4 ( ) 4. Lee[15] Cronbach s α.93, ~0.93 Cronbach s α.97. 일반적특성및스마트폰관련특성 11 5, 6.,,,,,,,,,,. 이은지, 김윤경, 임수진 527

4 자료수집방법및윤리적고려 (# P ) ,.,,,.,.,,,...,. 자료분석방법 SPSS Ver. 21.,,,. Kolmogorov-Smirnov test χ 2 test, Fisher s exact test, t-test one-way ANOVA., -, Correlation coefficient analysis. Binary logistic regression, Hosmer-Lemeshow. 연구결과 대상자의스마트폰중독정도 (21.3%), 144 (78.7%) ± 8.09, ± 4.44, ± 6.45 (Table 2). 대상자의인구사회학적특성에따른스마트폰정상사용자군과위험사용자군간의차이 37.1%, 6.4% (p<.001). Table 1. Comparison of General Characteristics between Normal User Group and Smartphone Addiction Risk Group (N=183) Variables Gender Categories Male Female Total (N=183, 100%) Normal user group (n=144, 78.7%) n (%) n (%) n (%) 94 (51.4) 89 (48.6) 88 (93.6) 56 (62.9) SA risk group (n=39, 21.3%) χ 2 p 6 (6.4) 33 (37.1) School year 1st grade 2nd grade 3rd grade 45 (24.6) 71 (38.8) 67 (36.6) 37 (82.2) 53 (74.6) 54 (80.6) 8 (17.8) 18 (25.4) 13 (19.4) Economic status High Average Low 44 (24.2) 131 (72.0) 7 (3.8) 36 (81.8) 101 (77.1) 6 (85.7) 8 (18.2) 30 (22.9) 1 (14.3) Academic performance High Average Low 41 (22.4) 112 (61.2) 30 (16.4) 39 (95.1) 84 (75.0) 21 (70.0) 2 (4.9) 28 (25.0) 9 (30.0) Family structure Intact family Single parent Extended family 156 (85.2) 18 (9.8) 9 (4.9) 122 (78.2) 14 (77.8) 8 (88.9) 34 (21.8) 4 (22.2) 1 (11.1) * SA=Smartphone addiction; *Fisher s exact test

5 Table 2. Difference in Study Variables according to Smartphone Addiction (N=183) Variables Smartphone addiction Categories Total Disturbance of adaptive functions Virtual life orientation Withdrawal Tolerance Total (N=183) Normal user group (n=144) n (%) or M±SD n (%) or M±SD n (%) or M±SD 29.40± ± ± ± ± ± ± ± ± ±2.33 SA risk group (n=39) χ 2 or t p 39.67± ± ± ± ± Period of smartphone ownership 3.10 ± ± ± Time on smartphone (hr/day) 3.21 ± ± ± Purpose of smartphone use SNS Entertainment Others 70 (38.7) 63 (34.8) 48 (2.5) 52 (74.3) 50 (79.4) 40 (83.3) 18 (25.7) 13 (20.6) 8 (16.7) Depression 7.26 ± ± ± Parental bonding Care Overprotection 28.82± ± ± ± ± ± Perceived parental control Frequently Occasionally Hardly ever 46 (25.1) 107 (58.5) 30 (16.4) 31 (67.4) 87 (81.3) 26 (86.7) 15 (32.6) 20 (18.7) 4 (13.3) Parental-control software Yes No 57 (31.1) 126 (68.9) 47 (82.5) 97 (77.0) 10 (17.5) 29 (23.0) School adjustment Total Schoolwork School friends School teacher School life ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± SA=Smartphone addiction. (p=.012).,, (Table 1). 대상자의스마트폰관련특성따른스마트폰정상사용자군과위험사용자군간의차이 (p). - (p), - (p<.001). (p). (p=.008).,, (p =.079) (Table 2) 스마트폰중독과연구변수와의상관관계 (p<.001) (Table 3). -,, -, (,,, ). 스마트폰중독영향요인, (, 이은지, 김윤경, 임수진 529

6 , ), ( -, ), (, ), Binary logistic regression (Table 4). (χ 2 = 53.30, p<.001), Nagelkerke 39.4%. 78.5%, Hosmer-Lemeshow (χ 2 = 6.09, p =.637),.,,, (CI: 2.57~19.52), (CI: 1.04~1.66). 4.7 (CI: 1.04~21.29), (CI: 0.79~0.93). 논의, -,,,. 21.3%., 37.1% 6.4%, 7.09, [14]. (Social Network Service, SNS) [2]. Table 3. Relationship among Smartphone Addiction, Parental Bonding, Depression and School Adjustment (N=183) Variables Parental bonding: Care SA Parental bonding Care Over-protection Depression r (p) r (p) r (p) r (p) -.48 () Parental bonding: Overprotection.41 () -.67 () Depression.45 () -.49 ().36 () School adjustment: Schoolwork -.55 ().60 () -.49 () -.60 () School adjustment: Friends -.42 ().54 () -.39 () -.51 () School adjustment: Teacher -.52 ().49 () -.41 () -.52 () School adjustment: School life -.56 ().51 () -.46 () -.48 () SA=Smartphone addiction. Table 4. Predictors of Smartphone Addiction Variables Categories B SE p OR 95% CI Gender Male (ref.) Female ~19.52 School adjustment: School life ~0.93 Time on smartphone (hr/day) ~1.66 Parental control Hardly ever (ref.) Occasionally Frequently ~ ~21.29 SE=Standard error; OR=Odds ratio; CI=Confidence interval

7 [13]., SNS [24]., [14]. SNS, SNS.,,,., , [14,16].,.,, [15]., [12,25].,. [26,27],., , [16].,,,., 4.7.,. [26]. TV,, [28]. [27], - [26]. - [27]. [29].. 10, [29]., -, -.. ( ), ( ),. [5,14,30],, [30]. [16]., - 이은지, 김윤경, 임수진 531

8 ..,,.,. 결론,,.,,, -.,.,.. Conflict of Interest No potential or any existing conflict of interest relevant to this article was reported. References 1. Gallup Korea. Survey about usage of smartphone and smartwatch in [Internet]. Seoul: Gallup Korea; 2016 [cited 2017 April 28]. Available from: 2. Korea Information Society Development Institute. The analysis of smartphone held and use behavior in children and adolescents. KIS- DI STAT Report. Seoul: Korea Information Society Development Institute; 2015 December. Report No.: National Information Society Agency. Development of Korean smartphone addiction proneness scale for youth and adults. R&D Report. Seoul: National Information Society Agency; 2011 November. Report No.: NIA IV-RER Ministry of Gender Equality and Family. The result from the 2016 national survey of the diagnosis on internet and smartphone usage habits [Internet]. Seoul: Ministry of Gender Equality and Family; 2016 [cited 2017 April 30]. Available from: _ &menuCd=DOM_ Kim BN, Ko EJ, Choi HI. A study on factors affecting smart-phone addiction in university students: A focus on differences in classifying risk groups. Studies on Korean Youth. 2013;24(3): Kwon M, Lee JY, Won WY, Park JW, Min JA, Hahn CT, et al. Development and validation of a smartphone addiction scale (SAS). PloS one. 2013;8(2):e Korean Institute of Criminology. Study on the public awareness of pornography using children and youth and effective regulation. Research Series. Seoul: Korean Institute of Criminology; 2016 December. Report No.: 16-AA American Psychiatric Association. Diagnostic and statistical manual of mental disorders. (DSM-5). 5th ed. Arlington, VA: American Psychiatric Publishing; p Billieux J, Maurage P, Lopez-Fernandez O, Kuss DJ, Griffiths MD. Can disordered mobile phone use be considered a behavioral addiction? An update on current evidence and a comprehensive model for future research. Current Addiction Reports. 2015;2(2): Kim JH, Seo MH, David P. Alleviating depression only to become problematic mobile phone users: Can face-to-face communication be the antidote? Computers in Human Behavior. 2015;51: Ko JS. Mediating effect of adolescents smart-phone addiction in the relationship between family function and school adjustment resilience. Journal of the Korea Contents Association. 2014;14(6): Choi JO. The impacts of smartphone addiction on academic grade of elementary school students. Journal of Korea Institute of Youth Facility & Environment. 2015;13(2): Cha DS. Effects of negative smartphone usage of elementary school 532

9 students on health with a special emphasis on moderating effects of parenting attitudes. Journal of School Social Work. 2017;38: Hwang KH, Yoo YS, Cho OH. Smartphone overuse and upper extremity pain, anxiety, depression, and interpersonal relationships among college students. The Journal of the Korea Contents Association. 2012;12(10): Lee KM. A study of middle-school students school adjustment constructs. The Korean Journal of Counseling and Psychotherapy. 2005;17(2): Ju SJ, Cho SS. A study on the discriminating factors of youth s smartphone addiction: Focusing on daily average smartphone usage time, impulsivity, peer relationships, mother s authoritarianism-rearing attitudes. Journal of Youth Welfare. 2015;17(1): Ministry of Gender Equality and Family. Actual condition survey of smartphone addiction in adolescents. Research Report. Seoul: Ministry of Gender Equality and Family; 2013 November. Report No.: Wu XS, Zhang ZH, Zhao F, Wang WJ, Li YF, Bi L, et al. Prevalence of internet addiction and its association with social support and other related factors among adolescents in China. Journal of Adolescence. 2016;52: World Health Organization. Depression [Internet] [cited 2016 September 28]. Available from: Kovacs M. The children s depression inventory (CDI). Psychopharmacology Bulletin. 1985;21(4): Cho SC, Lee YS. Development of the Korean form of the Kovacs Children s Depression Inventory. Journal of Korean Neuropsychiatric Association. 1990;29(4): Parker G, Tupling H, Brown LB. A parental bonding instrument. British Journal of Medical Psychology. 1979;52(1): Song JY. The development of the Parental Bonding Instrument - Korean version: Evaluation of the test reliability and validity. Journal of Korean Neuropsychiatric Association. 1992;31(5): Roberts JA, Yaya LHP, Manolis C. The invisible addiction: Cell-phone activities and addiction among male and female college students. Journal of Behavioral Addictions. 2014;3(4): Nam IS. A rising addiction among youths: Smartphones [Internet]. New York: Dow Jones & Company; 2013 [cited 2017 August 31]. Available from: Park NS, Oh HY. Impact of adolescent life stress and smartphone use on academic impairment: Focusing on the effect of parent involvement on adolescents smartphone use. The Journal of the Korea Contents Association. 2016;16(9): Stattin H, Kerr M. Parental monitoring: A reinterpretation. Child Development. 2000;71(4): American Academy of Pediatrics. Children, adolescents, and the media. Pediatrics. 2013;132(5): Livingstone S, Haddon L. EU Kids Online: Final report. London: London School of Economics and Political Science; p Yoo TJ, Kim SS. Impact of perceived parenting styles on depression and smartphone addition in college students. Journal of Korean Academy of Psychiatric and Mental Health Nursing. 2015;24(2): 이은지, 김윤경, 임수진 533

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