The presentation refers to  the contradictory findings regarding the prevalence of internet addiction among Greek adolescent

Motti - Stefanidi, Frosso

Stavropoulos, Vassilis

Digital Repository of Hellenic Managing Authority of the Operational Programme &quot;Education and Lifelong Learning&quot; (EDULLL)

INTERNET ADDICTION AMONG GREEK  ADOLESCENTS. PREDICTION FROM FLOW OF INTERNET ACTIVITY AND IMPULSIVE COMPULSIVE   BEHAVIORVassilis Stavropoulos& Frosso Motti - StefanidiThis research has been co-financed by the European Union (EuropeanSocial Fund – ESF) and Greek national funds through the OperationalProgram "Education and Lifelong Learning" of the National StrategicReference Framework (NSRF) - Research Funding Program: Heracleitus II.Investing in knowledge society through the European Social Fund.Impetus for this research project• Contradictory findings regarding the prevalence of internet addiction among Greek adolescents6.1%(Siomos et al.)20081%(Tsitsika et al. 2009) 11%(Siomos et al2008)Impulsive- Compulsive Behaviors and Internet Addiction  Arousal which is reassured by the manifestation of a behavior-Internet Use (Treuer, Fabian &  Furedi, 2001)AddictionsInternet AddictionImpulsive Compulsive BehaviorsIC-ΙUDImpulsive-Compulsive Internet Usage Disorder (Dell' Ossο, Altamura, Hadley, Baker & Hollander, 2006)P.I.GPositive Immediate Gratification Phenomenon(Marlatt & Gordon, 1985)Internet Flow and Internet Addiction(Chen, 2006)• An individual who abuses the Internet must be absorbed by his Online Activity (Chen, 2006)• As Flow defines the level the user is absorbed in the online activity (Chen, 2006), achieved through a Positive Immediate Gratification  mechanism• The user must be in a state of Flow (Weibel et al, 2008)Model of Understanding Internet Addiction(Douglas et al, 2008)AbusesPush FactorsPull FactorsImpulsive Compulsive BehaviorsInternet FlowConsequently In the present study as Predictors of Internet Addiction were examined:• Impulsive Compulsive Behaviors • Internet FlowResearch Questions1. What is the prevalence of Internet Addiction among Greek high school students?2. Do Impulsive Compulsive behaviors and Internet  Flow predict Internet Addiction?3. Does impulsive compulsive behavior mediate the relationship between Flow of internet activity and levels of Internet Addiction ?Research Sample• N= 2090 Adolescents• Boys=1035 (49,7%)• Girls=1048 (50,3%)• Attica= 1919 (91,8%)• Korinthia= 171 (8,2%)• General High Schools= 1728 (82,7 %)• Technical High Schools=362 (17,3 %)• Mean Age= 16,16 Instruments• Internet use was assessed with:• The Internet Addiction Test (Young, 1998) Cronbach a= 0,91• The Young Diagnostic Questionnaire (Young,1998)• Internet Flow was assessed with:• Internet Flow Questionnaire (Chen, Wigand & Nilan, 1999) Cronbach a= 0,58• Impulsivity- Compulsivity was assessed with:• The Impulsive Compulsive scale of the Symptom Check List – 90 (Derogatis,1994) Cronbach a= 0,79Question 1What is the prevalence of Internet Addiction among Greek high school students?One sample, two different criteria37,10%51%11,60% 0,30%37,1 % Digitally Iliterate but mostly Rare Users51% Healthy Users11,6% High Risk Group For Internet Addiction-Abuse86,210,73,186,2 % Digitally Illiterate, Rare and Healthy Users10,7 % High Risk Group for Interent Addiction3,1% Internet Addiced UsersBut why does this difference exist?Possible Answer….• Crosscultural Differences in cut off point scores…• To examine this  hypothesis• We conducted ROC curve analysis to propose new cut of points… ΙΑΤ SCORE SENSITIVITY1 -SPECIFICITY50.50 .983 .082IAT=0IAT=100 Based on our results we estimate the Prevalence of IAD86,210,73,186,2 % Digitally Illiterate, Rare and Healthy Users10,7 % High Risk Group for Interent Addiction3,1% Internet Addiced UsersQuestion 2Do Impulsive Compulsive behaviors and Internet  Flow predict Internet Addiction?Results• In order to answer this question weperformed a multiple linear regressionanalysis (Stepwise Method)• All Collinearity Diagnostic Criteria werewithin permitable for the analysis limits(VIF < 2, Tolerance > 0,5, ConditionIndex < 15)ResultsInternet Addiction DisorderInternet FlowImpulsivity CompulsivityPredictors Β SE Beta pFlow5.01 0.30 0.39 0.000Impulsivity- Compulsivity6.05 5.90 0.24 0.000Results• The analysis findings supported our initial hypotheses.• Multiple Correlation Index was R = 0.52• Regression Coefficient was R2 = 0,27• Adjusted Regression Coefficient was R2 = 0,27• The slope of the regression line wassignificantly different from zero {F (1, 1442) =265.72, p = 0,0000.}Question 3Does Impulsive Compulsive behavior mediate the relationship between Flow of internet activity and levels of Internet Addiction ?Results• We examined Impulsivity and Compulsivity, as proposedmediator of the effect of Flow on Internet Addiction .• For this purpose we performed bootstrapping on theminimum recommended 1000 samples• we calculated the Sobel test for the total and specificindirect effects as well bias-corrected and acceleratedbootstrap confidence intervals for the indirect effects asproposed by Preacher and Hayes at 2008 *.Results seem to support our hypothesesTable 2Mediation of the Effect of Flow on Internet Addiction through Impulsivity Compulsivity  Product of Coefficients BootstrappingPoint Estimate SE Z PBCa 99% CILower UpperIndirect EffectsImpulseCompulse 0.90     0.12    7.71  .001 0.66 1.17Total 0.90     0.12    7.71  .001 0.66 1.17Note—BC, bias corrected; BCa, bias corrected and accelerated; 1,000 bootstrap samples.Results in PictureInternet Addiction DisorderInternet FlowImpulsivity CompulsivityDirect EffectsInidirect EffectsTake Home Message• A user who is in Flow when online• stimulates Positive Immediate Gratification tendencies• Which might progressively recycle and expand to other aspects of his life• Ending  either to strengthen Impulsive Compulsive manifestations that already exist, or initializing themTake Home Message  Internet AddictionImpulsive Compulsive BehaviorsFlowExperienceP.I.GThank you  Discussion: Question  1 Finding: • The significanlty lower than the U.S. Greek Cut off point in IAT Stresses:• The need for indigenous measures(emic approach)• The possible effect of the individualism – Collectivism Cultural Dimension • Countries with higher individualism show a higher rate of internet adoption, because as something new, it is considered less trheatening for the prevailing norm (Erumban & De Jong, 2006). • Higher collectivism gives more modest answers to likert sacles, due to less tolerance of  inequality (Triandis, 1996)• Matters of Scalar Equivalence: Collectivists direct their evaluation more toward interdependency with their in group and less to self-related issues (Triandis, 1996)• And Less than one fourth of IAT questions refers to consequences in relations with others.

Internet addiction among Greek adolescents: Prediction from flow of internet activity and impulsive compulsive behavior

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Internet addiction among Greek adolescents: Prediction from flow of internet activity and impulsive compulsive behavior

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Digital Repository of Hellenic Managing Authority of the Operational Programme "Education and Lifelong Learning" (EDULLL)

Internet addiction among Greek adolescents: Prediction from flow of internet activity and impulsive compulsive behavior

Abstract

Similar works

Full text

Available Versions

Digital Repository of Hellenic Managing Authority of the Operational Programme &quot;Education and Lifelong Learning&quot; (EDULLL)

Digital Repository of Hellenic Managing Authority of the Operational Programme "Education and Lifelong Learning" (EDULLL)