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Copyright restrictions may apply Predictive Values of Psychiatric Symptoms for Internet Addiction in Adolescents: A 2-Year Prospective Study Ko C-H, Yen.

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Presentation on theme: "Copyright restrictions may apply Predictive Values of Psychiatric Symptoms for Internet Addiction in Adolescents: A 2-Year Prospective Study Ko C-H, Yen."— Presentation transcript:

1 Copyright restrictions may apply Predictive Values of Psychiatric Symptoms for Internet Addiction in Adolescents: A 2-Year Prospective Study Ko C-H, Yen J-Y, Chen C-S, Yeh Y-C, Yen C-F. Predictive values of psychiatric symptoms for Internet addiction in adolescents: a 2-year prospective study. Arch Pediatr Adolesc Med. 2009;163(10):937-943.

2 Copyright restrictions may apply Ko et al – October 2009 Introduction Previous reports found that up to 18% of adolescents have Internet addiction in Western and Eastern societies. Identification of the risk factors for Internet addiction is therefore of clinical significance for the prevention of, and early intervention into, Internet addiction in adolescents. Study Aims –To evaluate the predictive values of psychiatric symptoms for the occurrence of Internet addiction. –To identify any sex differences in the predictive value of psychiatric symptoms for the occurrence of Internet addiction in adolescents.

3 Copyright restrictions may apply Ko et al – October 2009 Methods Study Design –Baseline: Self-administered questionnaire regarding Internet addiction, depression, attention-deficit/hyperactivity disorder (ADHD), social phobia, and hostility. –Follow-up: Self-administered questionnaire regarding Internet addiction for participants at 6, 12, and 24 months after baseline. Sample –N = 2162 adolescents from 10 junior high schools (mean age 12.36 years at baseline) in southern Taiwan. –n = 1848 adolescents (882 male, 966 female) had no Internet addiction at baseline and completed at least 1 follow-up assessment.

4 Copyright restrictions may apply Ko et al – October 2009 Methods Data Analysis –Predictive values of psychiatric symptoms for the occurrence of Internet addiction, using Cox proportional hazard regression analysis for all participants and for separate groups of male and female participants. Limitations –The classification of Internet addiction was based only on the results of a self-reported questionnaire. –ADHD symptoms were determined solely by self-reported data. –2 schools and 1 school did not participate in the second and fourth investigations, respectively.

5 Copyright restrictions may apply Ko et al – October 2009 Results Depression, ADHD, social phobia, and hostility were found to predict the occurrence of Internet addiction among all participants and female participants. –Among male participants, only ADHD and hostility were identified as risk factors for Internet addiction. In multivariate analyses: –ADHD and hostility remained significant predictors of Internet addiction among all participants after controlling for sex and age. –Hostility and ADHD remained significant predictors of the occurrence of Internet addiction among male and female participants, respectively.

6 Copyright restrictions may apply Predictive Value of Age and Psychiatric Symptoms for Internet Addiction: Univariate Cox Proportional Hazard Regression Variable (No. Missing Data) Event, No. (%)Censored, No. Wald χ 2 Hazard Ratio95% CI Age 01.000.78-1.28 Depression a (85) Yes36 (20.5)140 6.10 b 1.561.10-2.22 No217 (13.7)1370 1[Reference] ADHD c (96) Yes50 (24.9)151 19.97 d 2.021.49-2.76 No206 (13.3)1345 1[Reference] Social phobia e (66) Yes54 (18.5)238 3.93 b 1.351.004-1.82 No212 (14.2)1278 1[Reference] Hostility f (109) Yes51 (23.4)167 14.86 d 1.831.34-2.48 No206 (13.5)1315 1[Reference] Abbreviations: ADHD, attention-deficit/hyperactivity disorder; CI, confidence interval. a Depression was assessed by the Center for Epidemiological Studies Depression Scale. b P <.05. c ADHD was assessed by the Attention-Deficit/Hyperactivity Disorder Self-rated Scale. d P <.001. e Social phobia was assessed by the Brief Version of the Fear of Negative Evaluation Scale. f Hostility was assessed by the Buss-Durkee Hostility Inventory–Chinese Version–Short Form.

7 Copyright restrictions may apply Predictive Value of Age and Psychiatric Symptoms for Internet Addiction: Multivariate Cox Proportional Hazard Regression a Variable (No. Missing Data) Wald χ 2 Hazard Ratio95% CI All participants (287) Age0.030.98 0.74-1.29 Male23.68 b 1.97 1.50-2.59 ADHD9.34 c 1.72 1.21-2.43 Hostility7.97 c 1.67 1.17-2.38 Male (158) Age 0.031.030.73-1.46 Hostility 6.35 d 1.821.14-2.89 Female (129) Age 0.100.930.59-1.47 ADHD 16.00 b 2.831.70-4.72 Abbreviations: ADHD, attention-deficit/hyperactivity disorder; CI, confidence interval. a Forward regression. b P <.001. c P <.01 d P <.05.

8 Copyright restrictions may apply Ko et al – October 2009 Discussion Implications for Future Clinical Work –As ADHD, hostility, depression, and social phobia are predictors of the emergence of Internet addiction, albeit to different degrees in different sexes, effective screening and intervention for these psychiatric symptoms are necessary to prevent Internet addiction among adolescents. ADHD and hostility persisted as predictors in multivariate models of Internet addiction, while depression and hostility did not. –As a strategy of integrated therapy for Internet addiction and psychiatric disorders, dual diagnosis could provide more consistent treatment effects for adolescents with Internet addiction than separate therapeutic approaches. –Sex differences in psychiatric comorbidity should be considered when developing prevention and intervention strategies for Internet addiction.

9 Copyright restrictions may apply Ko et al – October 2009 Discussion Implications for Future Research –Why and how Internet addiction was associated with preceding psychiatric symptoms should be explored. Implications for Health Policy –ADHD, hostility, depression, and social phobia should be screened for and addressed early by clinicians to prevent the occurrence of Internet addiction in adolescents.

10 Copyright restrictions may apply Ko et al – October 2009 Contact Information If you have questions, you may contact the corresponding author, Chen-Fang Yen, MD, PhD: –E-mail: chfaye@cc.kmu.edu.twchfaye@cc.kmu.edu.tw


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