Factor structure of the compulsive internet use scale

Cyberpsychology, Behavior, and Social Networking

Volumn 17, Issue 1, 2014, Pages 46-51

  Guertler, Diana ^a   Broda, Anja ^b   Bischof, Anja ^c   Kastirke, Nadin ^a   Meerkerk, Gert Jan ^d   John, Ulrich ^a   Meyer, Christian ^a   Rumpf, Hans Juergen ^c  

^a UNIVERSITY MEDICINE GREIFSWALD   (Germany)

^b UNIVERSITY OF LEIPZIG   (Germany)

^c UNIVERSITY OF LÜBECK   (Germany)

^d Addiction Research Institute Rotterdam   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

ADDICTION; ADOLESCENT; ADULT; ARTICLE; FACTORIAL ANALYSIS; FEMALE; GERMANY; HUMAN; INTERNET; MALE; MIDDLE AGED; PSYCHOMETRY; QUESTIONNAIRE; TIME; UTILIZATION REVIEW; YOUNG ADULT;

ADOLESCENT; ADULT; BEHAVIOR, ADDICTIVE; FACTOR ANALYSIS, STATISTICAL; FEMALE; GERMANY; HUMANS; INTERNET; MALE; MIDDLE AGED; PSYCHOMETRICS; QUESTIONNAIRES; TIME FACTORS; YOUNG ADULT;

EID: 84892692225     PISSN: 21522715     EISSN: 21522723     Source Type: Journal    
DOI: 10.1089/cyber.2013.0076     Document Type: Article

References (33)

1. Shaw M, Black DW. Internet addiction: definition, assessment, epidemiology and clinical management. CNS Drugs 2008; 22:353-365.
2. Beard KW. Internet addiction: a review of current assessment techniques and potential assessment questions. CyberPsychology & Behavior 2005; 8:7-14.
3. Chou C, Condron L, Belland JC. A review of the research on Internet addiction. Educational Psychology Review 2005; 17:363-388.
4. American Psychiatric Association. (2000) Diagnostic and statistical manual of mental disorders. Washington DC: American Psychiatric Association.
5. Meerkerk GJ, Van Den Eijnden RJJM, Vermulst AA, et al. The Compulsive Internet Use Scale (CIUS): some psychometric properties. CyberPsychology & Behavior 2009; 12:1-6.
6. Griffiths M. Internet addiction: fact or fiction? Psychologist 1999; 12:246-250.
7. Dimitrov DM. Testing for factorial invariance in the context of construct validation. Measurement & Evaluation in Counseling & Development 2010; 43:121-149.
8. Peukert P, Steffen S, ElKasmi J, et al. Faktorielle Struktur der deutschen Version der Compulsive Internet Use Scale (CIUS) nach konfirmatorischer Faktorenanalyse [Factorial structure of the German version of the Compulsive Internet Use Scale (CIUS) after confirmatory factor analysis]. Zeitschrift fü r Klinische Psychologie und Psychotherapie 2012; 41:101-108.
9. Meyer C, Bischof A, Westram A, et al. The project "Pathological Gambling and Epidemiology" (PAGE): study design and results of fieldwork. International Journal of Methods in Psychiatric Research 2013; (in press).
10. Levy P, Lemeshow S. (2008) Sampling of populations. Methods and applications. Hoboken, New Jersey: Wiley.
11. Khazaal Y, Chatton A, Atwi K, et al. Arabic validation of the Compulsive Internet Use Scale (CIUS). Substance Abuse Treatment, Prevention & Policy 2011; 6:32.
12. Khazaal Y, Chatton A, Horn A, et al. (2012) French validation of the Compulsive Internet Use Scale (CIUS). www.springerlink.com/content/ 602021835723070g/full text.pdf (accessed Dec. 14, 2012).
13. Alavi SS, Jannatifard F, Eslami M, et al. Validity, reliability and factor analysis of Compulsive Internet Use Scale in students internet users of Isfahan's universities [Abstract] 2011. http://him.mui.ac.ir/index.php/him/ article/view/204 (accessed Nov. 1, 2012).
14. Muthén LK, Muthén BO. (1998-2000) Mplus user's guide.6th ed. Los Angeles, CA: Muthén & Muthén.
15. Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychological Methods 2002; 7:147-177.
16. Azur MJ, Stuart EA, Frangakis C, et al. Multiple imputation by chained equations: what is it and how does it work? International Journal of Methods in Psychiatric Research 2011; 20:40-49.
17. Raghunathan TE, Lepkowski JM, Hoewyk JV, et al. A multivariate technique for multiply imputing missing values using a sequence of regression models. Survey Methodology 2001; 27:85-95.
18. van Buuren S. Multiple imputation of discrete and continuous data by fully conditional specification. Statistical Methods in Medical Research 2007; 16:219-242.
19. Muthén BO, Kaplan D. A comparison of some methodologies for the factor analysis of non-normal Likert variables. British Journal of Mathematical & Statistical Psychology of Addictive Behaviors 1985; 38:171-189.
20. Hooper D, Coughlan J, Mullen M. Structural equation modelling: guidelines for determining model fit. Electronic Journal of Business Research Methods 2008; 6:53-60.
21. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling-A Multidisciplinary Journal 1999; 6:1-55.
22. Bryant F, Satorra A. Principles and practice of scaled difference chi-square testing. Structural Equation Modeling 2012; 19:372-398.
23. Whittaker TA. Using the modification index and standardized expected parameter change for model modification. Journal of Experimental Education 2012; 80:26-44.
24. Milfont TL, Fischer R. Testing measurement invariance across groups: applications in cross-cultural research. International Journal of Psychological Research 2010; 3:111-121.
25. Raju NS, Laffitte LJ, Byrne BM. Measurement equivalence: a comparison of methods based on confirmatory factor analysis and item response theory. Journal of Applied Psychology 2002; 87:517-529.
26. Cheung GW, Rensvold RB. Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal 2002; 9:233-255.
27. Cartierre N, Coulon N, Demerval R. Validation d'une version courte en langue française pour adolescents de la Compulsive Internet Use Scale [Validation of a short French version for adolescents of the Compulsive Internet Use Scale]. Neuropsychiatrie de l'enfance et de l'adolescence 2011; 59:415-419.
28. MacKenzie S, Podsakoff P, Jarvis C. The problem of measurement model misspecification in behavioral and organizational research and some recommended solutions. Journal of Applied Psychology 2005; 90:710-730.
29. Frazier TW, Youngstrom EA. Historical increase in the number of factors measured by commercial tests of cognitive ability: are we overfactoring? Intelligence 2007; 35:169-182.
30. Horn JL. A rationale and test for the number of factors in factor analysis. Psychometrika 1965; 30:179-185.
31. Velicer W. Determining the number of components from the matrix of partial correlations. Psychometrika 1976; 41:321-327.
32. Podsakoff P, MacKenzie S, Lee J, et al. Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology 2003; 88:879-903.
33. Brown TA. (2006) Confirmatory factor analysis for applied research. New York: Guilford Press.