Validation of Theoretical and Measurement Model of the Generalized Problematic Internet Use Scale 2 in a Polish Sample

Keywords: Generalized Problematic Internet Use (GPIU), the cognitive-behavioral model of GPIU, Caplan GPIUS2, measurement invariance

Abstract

The Generalized Problematic Internet Use Scale (GPIUS2) was developed to operationalize the theoretical cognitive-behavioral model of GPIU.  The aims of the study were to examine the theoretical model of GPIU, analyze the psychometric properties of the GPIUS2 among Polish adolescents, study measurement invariance across gender and method of data collection (offline vs. online). The sample comprised of 1,621 participants (52% men, Mage = 20.3). Some participants completed an online version of the GPIUS2 (n = 707, 73% men, M = 17.9), and others filled in a pencil and paper version (n = 914, 35% men, M = 22.1). Reliability was assessed (Cronbach’s α; McDonald’s ω). The factor structure and nomological, convergent, and discriminant validity were tested. The findings of this study supported the reliability and the factor structure of the GPIUS2. The factor similarity in Polish sample and the original US sample was high (Tucker’s congruence coefficients were range: .99–1.00). The structural relationships between the constructs of the model, convergent and discriminant validity were confirmed. The strong measurement invariance of the model across gender and method of data collection was confirmed. The Polish version of the GPIUS2 is a reliable and valid instrument that can be used for Polish adolescent samples. The scale showed measurement invariance across gender and method of data collection. Furthermore, the results support the cognitive-behavioral model of problematic Internet use in adolescents.

References

Aboujaoude, E. (2010). Problematic Internet use: An overview. World Psychiatry, 9(2), 85–90. https://doi.org/10.1002/j.2051-5545.2010.tb00278.x

Andreou, E., & Svoli, H. (2013). The association between Internet user characteristics and dimensions of Internet addiction among Greek adolescents. International Journal of Mental Health and Addiction, 11, 139–148. https://doi.org/10.1007/s11469-012-9404-3

Assunçao, R., & Matos, P. (2017). The generalized problematic Internet use scale 2: Validation and test of the model to Facebook use. Journal of Adolescence, 54(1), 51–59. https://doi.org/10.1016/j.adolescence.2016.11.007

Barke, A., Nyenhuis, N., & Kroner-Herwig, B. (2014). The German version of the Generalized Pathological Internet Use Scale 2: A validation study. Cyberpsychology, Behavior, and Social Networking, 17(7), 474–482. https://doi.org/10.1089/cyber.2013.0706

Bauer, D. (2017). A more general model for testing measurement invariance and differential item functioning. Psychological Methods, 22(3), 507–526. https://doi.org/10.1037/met0000077

Breslau, J., Aharoni, E., Pedersen, E., & Miller, L. (2015). A review of research on problematic Internet use and well-being. With recommendations for the U.S. Air Force. RAND Corporation.

Brown, T. (2015). Confirmatory factor analysis for applied research (2nd ed.). Guilford Press.

Caplan, S. (2002). Problematic Internet use and psychosocial well-being: Development of a theory-based cognitive-behavioral measure. Computers in Human Behavior, 18(5), 533–575. https://doi.org/10.1016/s0747-5632(02)00004-3

Caplan, S. (2003). Preference for online social interaction: A theory of problematic Internet use and psychosocial well-being. Communication Research, 30(6), 625–648. https://doi.org/10.1177/0093650203257842

Caplan, S. (2007). Relations among loneliness, social anxiety, and problematic Internet use. CyberPsychology & Behavior, 10(2), 234–241. https://doi.org/10.1089/cpb.2006.9963

Caplan, S. (2010). Theory and measurement of generalized problematic Internet use: A two-step approach. Computers in Human Behavior, 26(5), 1089–1097. https://doi.org/10.1016/j.chb.2010.03.012

Chen, F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464–504. https://doi.org/10.1080/10705510701301834

Chun, J. (2016). Effects of psychological problems, emotional dysregulation, and self-esteem on problematic Internet use among Korean adolescents. Children and Youth Services Review, 68, 187–192. https://doi.org/10.1016/j.childyouth.2016.07.005

Ciżkowicz, B. (2017). Walidacja polskiej wersji Skali Uogólnionego Problematycznego Używania Internetu (GPIUS2). Przegląd Psychologiczny, 60(3), 363–379.

Dalal, P., & Basu, D. (2016). Twenty years of Internet addiction … Quo Vadis? Indian Journal of Psychiatry, 58(1), 6–11. https://doi.org/10.4103/0019-5545.174354

Davis, R. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17(2), 187–195. https://doi.org/10.1016/s0747-5632(00)00041-8

Deng, L., & Chan, W. (2017). Testing the difference between reliability coefficients alpha and omega. Educational and Psychological Measurement, 77(2), 185–203. https://doi.org/10.1177/0013164416658325

Derbyshire, K., Lust, K., Schreiber, L., Odlaug, B., Christenson, G., Golden, D., & Grant, J. (2013). Problematic Internet use and associated risks in a college sample. Comprehensive Psychiatry, 54(5), 415–422. https://doi.org/10.1016/j.comppsych.2012.11.003

Fioravanti, G., Primi, C., & Casale, S. (2013). Psychometric evaluation of the Generalized Problematic Internet Use Scale 2 in an Italian sample. Cyberpsychology, Behavior, & Social Networking, 16(10), 761-7676. https://doi.org/10.1089/cyber.2012.0429

Fioravanti, G., & Casale, S. (2015). Evaluation of the Psychometric Properties of the Italian Internet Addiction Test. Cyberpsychology, Behavior, & Social Networking, 18(2), 120¬–128. https://doi.org/10.1089/cyber.2014.0493

Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobserved variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Gámez-Guadix, M., Villa-George, & F., Calvete, E. (2012). Measurement and analysis of the cognitive-behavioral model of generalized problematic Internet use among Mexican adolescents. Journal of Adolescence, 35(6), 1581–1591. https://doi.org/10.1016/j.adolescence.2012.06.005

Gámez-Guadix, M., Orue, I., & Calvete, E. (2013). Evaluation of the cognitive-behavioral model of generalized and problematic Internet use in Spanish adolescents. Psicothema, 25(3), 299–306. https://doi.org/10.7334/psicothema2012.274

Guitton, M. (2014). The importance of studying the dark side of social networks. Computers in Human Behavior, 31, 335. https://doi.org/10.1016/j.chb.2013.10.055

Główny Urząd Statystyczny (2020). Społeczeństwo informacyjne w Polsce w 2020 r. https://stat.gov.pl/wyszukiwarka/szukaj.html

Hair, J., Hult, G., Ringle, C., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE Publications.

Hermida, R. (2015). The problem of allowing correlated errors in structural equation modeling: Concerns and considerations. Computational Methods in Social Sciences, 3(1), 1–17.

Hu, L., & Bentler, P. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

Jarczyńska, J. (2015). Problematyczne używanie Internetu przez młodzież i młodych dorosłych – przegląd narzędzi do przesiewowej oceny tego zjawiska. Przegląd Pedagogiczny, 1, 119–136.

Johnson, J. (2021). Worldwide digital population as of January 2021. https://www.statista.com/statistics/617136/digital-population-worldwide

Kemp, S. (2021a). Digital in 2021: Global overview. https://datareportal.com/reports/digital-2021-global-overview-report

Kemp, S. (2021b). Digital 2021: Poland. https://datareportal.com/reports/digital-2021-poland

Kerkhof, P., Finkenauer, C., & Muusses, L. (2011). Relational consequences of compulsive Internet use: A longitudinal study among newlyweds. Human Communication Research, 37(2), 147–173. https://doi.org/10.1111/j.1468-2958.2010.01397.x

Kim, H., Devis, K. (2009). Toward a comprehensive theory of problematic Internet use: Evaluating the role of self-esteem, anxiety, flow, and the self-rated importance of Internet activities. Computers in Human Behavior, 25(2), 490–500. https://doi.org/10.1016/j.chb.2008.11.001

Kim, B., Chang, S., Park, J., Seong, S., Won, S., & Cho, M. (2016). Prevalence, correlates, psychiatric comorbidities, and suicidality in a community population with problematic Internet use. Psychiatry Research, 244, 249–256. https://doi.org/10.1016/j.psychres.2016.07.009

Kline, R. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Press.

Kuss, D., Griffith, M., Karila, L., & Billieux, J. (2014). Internet addiction: A systematic review of epidemiological research for the last decade. Current Pharmaceutical Design, 20(25), 1–26. https://doi.org/10.2174/13816128113199990617

Kuss, D., & Lopez-Fernandez, O. (2016). Internet addiction and problematic Internet use: A systematic review of clinical research. World Journal of Psychiatry, 6(1), 143–176. https://doi.org/10.5498/wjp.v6.i1.143

Lam, L. (2014). Internet gaming addiction, problematic use of the Internet, and sleep problems: A systematic review. Current Psychiatry Reviews, 16, 444. https://doi.org/10.1007/s11920-014-0444-1

Leo, J., & Wulfert, E. (2013). Problematic Internet use and other risky behaviors in college students: An application of problem-behavior theory. Psychology of Addictive Behaviors, 27(1), 133–141. https://doi.org/10.1037/a0030823

Lorenzo-Seva, U., & ten Berge, J. M. (2006). Tucker’s congruence coefficient as a meaningful index of factor similarity. Methodology, 2(2), 57–64. https://doi.org/10.1027/1614-2241.2.2.57

McDonald, R. (1999). Test theory: A unified treatment. Erlbaum.

Moon, S., Hwang, J., Kim, J., Shin, A., Bae, S., & Kim, J. (2018). Psychometric properties of the Internet Addiction Test: A systematic review and meta-analysis. Cyberpsychology, Behavior, and Social Networking, 21(8), 473–484. https://doi.org/10.1089/cyber.2018.0154

Park, S., Hong, K., Park, E., Ha, K., & Yoo, H. (2013). The association between problematic Internet use and depression, suicidal ideation and bipolar disorder symptoms in Korean adolescents. Australian & New Zealand Journal of Psychiatry, 47(2), 153–159. https://doi.org/10.1177/0004867412463613

Prasad, K., Hamza, A., Shrinivasa, B., Sharma, M., & Reddy, S. (2017). Etiological factors related to problematic Internet use. Indian Journal of Health and Wellbeing, 8(7), 602–604.

Pontes, H., Caplan, S., & Griffiths, M. (2016). Psychometric validation of the Generalized Problematic Internet Use Scale 2 in a Portuguese sample. Computers in Human Behavior, 63, 823–833. https://doi.org/10.1016/j.chb.2016.06.015

Reise, S., Bonifay, W., & Haviland, M. (2013a). Scoring and modeling psychological measures in the presence of multidimensionality. Journal of Personality Assessment, 95(2), 129–140. https://doi.org/10.1080/00223891.2012.725437

Reise, S., Scheines, S., Widaman, K., & Haviland, M, (2013b). Multidimensionality and structural coefficient bias in structural equation modeling: A bifactor perspective. Educational and Psychological Measurement, 73(1), 5–26. https://doi.org/10.1177/0013164412449831

Revelle, W. (2019). psych: Procedures for personality and psychological research (Version 1.9.12).

Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02

Thatcher, A., & Goolam, S. (2005). Development and psychometric properties of the Problematic Internet Use Questionnaire. South African Journal of Psychology, 35(4), 793–809. https://doi.org/10.1177/008124630503500410

Throuvala, M., Griffiths, M., Rennoldson, M., & Kuss, D (2019). School-based prevention for adolescent Internet addiction: Prevention is the key. A systematic literature review. Current Neuropharmacology, 17(6), 507–525. https://doi.org/10.2174/1570159x16666180813153806

Tokunaga, R., & Rains S. (2010). An evaluation of two characterizations of the relationships between problematic Internet use, time spent using the Internet, and psychosocial problems. Human Communication Research, 36(4), 512–545. https://doi.org/10.1111/j.1468-2958.2010.01386.x

Vondrácková, G., & Gabrhelík, R. (2016). Prevention of Internet addiction: A systematic review. Journal of Behavioral Addictions, 5(4), 568–579. https://doi.org/10.1556/2006.5.2016.085

Young, K. (1998). Internet addiction: The emergence of a new clinical disorder. CyberPsychology & Behavior, 1(3), 237–244. https://doi.org/10.1089/cpb.1998.1.237

Young, K., Pistner, M., O’Mara, J., & Buchanan, J. (1999). Cyber disorders: The mental health concern for the new millennium. CyberPsychology & Behavior, 2(5), 475– 479. https://doi.org/10.1089/cpb.1999.2.475

Zajac, K., Ginley, M., Chang, R., & Petry, N. (2017). Treatments for Internet gaming disorder and Internet addiction: A systematic review. Psychology of Addictive Behaviors, 31(8), 979–994. http://doi.org/10.1037/adb0000315

Published
2022-04-26
Section
Articles