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Spanish Validation and Scoring of the Internet Gaming Disorder Scale - Short-Form (IGDS9-SF)

Published online by Cambridge University Press:  19 June 2020

Iván Sánchez-Iglesias*
Affiliation:
Universidad Complutense (Spain)
Mónica Bernaldo-de-Quirós
Affiliation:
Universidad Complutense (Spain)
Francisco J. Labrador
Affiliation:
Universidad Complutense (Spain)
Francisco J. Estupiñá Puig
Affiliation:
Universidad Complutense (Spain)
Marta Labrador
Affiliation:
Universidad Complutense (Spain)
Ignacio Fernández-Arias
Affiliation:
Universidad Complutense (Spain)
*
Correspondence concerning this article should be addressed to Iván Sánchez-Iglesias. Universidad Complutense. Facultad de Psicología. Departamento de Psicobiología y Metodología en Ciencias del Comportamiento. Carretera de Húmera, s/n, Campus de Somosaguas, Pozuelo de Alarcón. 28223 Madrid (Spain). E-mail: [email protected]

Abstract

Since the inclusion of the Internet Gaming Disorder (IGD) in the Diagnostic and statistical manual of mental disorders (5th ed.) (DSM-5), the Internet Gaming Disorder Scale-Short Form (IGDS9-SF), a short nine items test, has become one of the most used standardized instruments for its psychometric evaluation. This study presents a validation and psychometric evaluation of the Spanish version of the IGDS9-SF. A sample of 2173 videogame players between 12 and 22 years old, comprising both genders, was employed, achieved with a randomized selection process from educational institutions in the city of Madrid. Participants completed the adapted version of the IGDS9-SF, the General Health Questionnaire (GHQ-12) and a negative cognitions scale associated with videogame use, as well as sociodemographic data and frequency of videogame play. A unifactorial structure with sufficient reliability and internal consistency was found through exploratory and confirmatory analyses. In addition, the instrument was found to have good construct validity; the scoring of the IGDS9-SF were found to show a positive association with gaming frequency, with general health problems, and to a greater extent, with problematic cognitions with regard to videogames. Factorial invariance was found concerning the age of participants. However, even though the factorial structure was consistent across genders, neither metric nor scalar invariance were found; for this reason, we present a scale for the whole sample and a different one for gender. These results suggest that this Spanish version of the IGDS9-SF is a reliable and valid instrument, useful to evaluate the severity of IGD in Spanish students, and we provide a scoring scale for measurement purposes.

Type
Research Article
Copyright
© Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid 2020

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References

American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (DSM–5®) (5th Ed.). American Psychiatric Publishing. https://doi.org/10.1176/appi.books.9780890425596CrossRefGoogle Scholar
Beranuy, M., Machimbarrena, J. M., Vega-Osés, M. A., Carbonell, X., Griffiths, M. D., & González-Cabrera, J. (2020). Spanish validation of the Internet Gaming Disorder Scale–Short Form (IGDS9–SF): Prevalence and relationship with online gambling and quality of life. International Journal of Environmental Research and Public Health, 17(5), Article 1562. https://doi.org/10.3390/ijerph17051562CrossRefGoogle ScholarPubMed
Bernaldo-de-Quirós, M., Labrador-Méndez, M., Sánchez-Iglesias, I., & Labrador, F. (2019). Instrumentos de medida del trastorno de juego en internet en adolescentes y jóvenes según criterios DSM–5: Una revisión sistemática [Measurement instruments of Internet gaming disorder in adolescents and young people according to DSM–5 criteria: A systematic review]. Adicciones. Advance online publication. https://doi.org/10.20882/adicciones.1277CrossRefGoogle Scholar
Brown, T. A. (2015). Confirmatory factor analysis for applied research. Guilford Publications.Google Scholar
Chau, P. Y. (1997). Reexamining a model for evaluating information center success using a structural equation modeling approach. Decision Sciences, 28, 309334. https://doi.org/10.1111/j.1540-5915.1997.tb01313.xCrossRefGoogle Scholar
Chen, F. F. (2007). Sensitivity of Goodness of Fit Indexes to lack of Measurement Invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 464504. https://doi.org/10.1080/10705510701301834CrossRefGoogle Scholar
Comunidad Autónoma de Madrid (2017). Buscador de centros educativos [Educative centers search engine]. Retrieved April 1, 2017, from http://www.madrid.org/wpad_pub/run/j/MostrarConsultaGeneral.icmGoogle Scholar
DeCarlo, L. T. (1997). Mardia's multivariate skew (b1p) and multivariate kurtosis (b2p) [SPSS macro]. Retrieved December 10, 2019, from http://www.columbia.edu/~ld208/Google Scholar
Son, D. T., Yasuoka, J., K, C., Poudel, K. C., Otsuka, K., & Jimba, M. (2013). Massively multiplayer online role-playing games (MMORPG): Association between its addiction, self-control and mental disorders among young people in Vietnam. International Journal of Social Psychiatry, 59(6), 570577. https://doi.org/10.1177/0020764012445861CrossRefGoogle ScholarPubMed
Evren, C., Dalbudak, E., Topcu, M., Kutlu, N., Evren, B., & Pontes, H. M. (2018). Psychometric validation of the Turkish nine-item InternetGaming Disorder Scale –Short Form (IGDS9–SF). Psychiatry Research, 265, 349354. https://doi.org/10.1016/j.psychres.2018.05.002CrossRefGoogle Scholar
Feng, W., Ramo, D. E., Chan, S. R., & Bourgeois, J. A. (2017). Internet gaming disorder: Trends in prevalence 1998–2016. Addictive Behaviors, 75, 1724. https://doi.org/10.1016/j.addbeh.2017.06.010CrossRefGoogle ScholarPubMed
Fernández-Árias, I., Bernaldo-de-Quirós, M., Sánchez-Iglesias, I., Labrador-Méndez, M., Estupiñá, F., & González-Álvarez, M. (2019, July 21–24). Identificación de clusters de perfil en el uso y abuso de videojuegos en adolescentes y jóvenes [Cluster identification of profiles in use and abuse of videogames in adolescents and young adults]. In F. J. Labrador (Chair), Gamer test: Evaluación e identificación de problemas con los videojuegos [Gamer test: Evaluation and identification of videogame problems] [Symposium]. IV Congreso Nacional de Psicología e International Symposium on Psychological Prevention. Vitoria-Gasteiz, Álava, Spain.Google Scholar
Goldberg, D., & Williams, P. (1988). A user’s guide to the General Health Questionnaire. Windsor, UK: NFER-Nelson.Google Scholar
Griffiths, M. D. (2017). Behavioural addiction and substance addiction should be defined by their similarities not their dissimilarities. Addiction, 112(10), 17181720. https://doi.org/10.1111/add.13828CrossRefGoogle Scholar
Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179185. https://doi.org/10.1007/BF02289447CrossRefGoogle ScholarPubMed
Jorgensen, T. D., Pornprasertmanit, S., Schoemann, A. M., & Rosseel, Y. (2018). semTools: Useful tools for structural equation modeling. (Version 0.5–1) [Computer software]. R package. https://CRAN.R-project.org/package=semToolsGoogle Scholar
Kelley, K. (2018). MBESS: The MBESS R Package (Version 4.4.3) [Computer software]. R Package. https://CRAN.R-project.org/package=MBESSGoogle Scholar
King, D. L., & Delfabbro, P. H. (2016). The cognitive psychopathology of Internet Gaming Disorder in adolescence. Journal of Abnormal Child Psychology, 44(8), 16351645. https://doi.org/10.1007/s10802-016-0135-yCrossRefGoogle ScholarPubMed
King, D. L., Haagsma, M. C., Delfabbro, P. H., Gradisar, M., & Griffiths, M. D. (2013). Toward a consensus definition of pathological video-gaming: A systematic review of psychometric assessment tools. Clinical Psychology Review, 33, 331342. https://doi.org/10.1016/j.cpr.2013.01.002CrossRefGoogle Scholar
Király, O., Sleczka, P., Pontes, H. M., Urbán, R., Griffiths, M. D., & Demetrovics, Z. (2017). Validation of the Internet Gaming Disorder Test (IGDT–10) and evaluation of the nine DSM–5 Internet Gaming Disorder criteria. Addictive Behaviors, 64, 253260. https://doi.org/10.1016/j.addbeh.2015.11.005CrossRefGoogle ScholarPubMed
Kuss, D. J., & Griffiths, M. D. (2012). Internet gaming addiction: A systematic review of empirical research. International Journal of Mental Health Addiction, 10(2), 278296. https://doi.org/10.1007/s11469-011-9318-5CrossRefGoogle Scholar
Kuss, D. J., Griffiths, M. D., & Pontes, H. M. (2017). Chaos and confusion in DSM–5 diagnosis of Internet Gaming Disorder: Issues, concerns, and recommendations for clarity in the field. Journal of Behavioral Addictions, 6(2), 103–09. https://doi.org/10.1556/2006.5.2016.062CrossRefGoogle ScholarPubMed
Lam, L. T. (2014). Internet gaming addiction, problematic use of the internet, and sleep problems: A systematic review. Current Psychiatry Reports, 16(4), Article 444. https://doi.org/10.1007/s11920-014-0444-1CrossRefGoogle ScholarPubMed
Lemmens, J. S., Valkenburg, P. M., & Peter, J. (2009). Development and validation of a game addiction scale for adolescents. Media Psychology, 12(1), 7795. https://doi.org/10.1080/15213260802669458CrossRefGoogle Scholar
Lloret-Segura, S., Ferreres-Traver, A., Hernández-Baeza, A., & Tomás-Marco, I. (2014). El análisis factorial exploratorio de los ítems: Una guía práctica, revisada y actualizada[Exploratory item factor analysis: A practical guide revised and updated]. Anales de Psicología, 30(3), 11511169. http://doi.org/10.6018/analesps.30.3.199361CrossRefGoogle Scholar
Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519530. https://doi.org/10.1093/biomet/57.3.519CrossRefGoogle Scholar
McDonald, R. P. (1999). Test theory: A unified treatment. Lawrence Erlbaum Associates.Google Scholar
Monacis, L., de Palo, V., Griffiths, M. D., & Sinatra, M. (2017). Validation of the Internet Gaming Disorder Scale – Short-Form (IGDS9–SF) in an Italian-speaking sample. Journal of Behavioral Addictions, 5(4), 638690. https://doi.org/10.1556/2006.5.2016.083Google Scholar
Moudiab, S., & Spada, M. M. (2019). The relative contribution of motives and maladaptive cognitions to levels of Internet Gaming Disorder. Addictive Behaviors Reports, 9, 100160. https://doi.org/10.1016/j.abrep.2019.100160CrossRefGoogle ScholarPubMed
O’Connor, B. P. (2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, Instruments, & Computers, 32(3), 396402. https://doi.org/10.3758/BF03200807CrossRefGoogle ScholarPubMed
Pontes, H. M., & Griffiths, M. D. (2015). Measuring DSM–5 Internet gaming disorder: Development and validation of a short psychometric scale. Computers in Human Behavior, 45, 137143. https://doi.org/10.1016/j.chb.2014.12.006CrossRefGoogle Scholar
Pontes, H. M., & Griffiths, M. D. (2016). Portuguese validation of the Internet Gaming Disorder Scale–Short-Form. CyberPsychology, Behavior & Social Networking, 19(4), 288293. https://doi.org/10.1089/cyber.2015.0605CrossRefGoogle ScholarPubMed
Pontes, H. M., Király, O., Demetrovics, Z., & Griffitths, M. D. (2014). The conceptualization and measurement of DSM–5 Internet Gaming Disorder: The development of the IGD–20 Test. PLOS ONE, 9(10), e110137. https://doi.org/10.1371/journal.pone.0110137CrossRefGoogle Scholar
Pontes, H. M., Macur, M., & Griffiths, M. D. (2016). Internet Gaming Disorder among Slovenian primary schoolchildren: Findings from a nationally representative sample of adolescents. Journal of Behavioral Addictions, 5(2), 304310. https://doi.org/10.1556/2006.5.2016.042CrossRefGoogle ScholarPubMed
Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling and more. Version 0.5–12 (BETA). Journal of Statistical Software, 48(2), 136. https://doi.org/10.18637/jss.v048.i02CrossRefGoogle Scholar
Schivinski, B., Brzozowska-Woś, M., Buchanan, E. M., Griffiths, M. D., & Pontes, H. M. (2018). Psychometric assessment of the Internet Gaming Disorder diagnostic criteria: An Item Response Theory study. Addictive Behaviors Reports, 8, 176184. https://doi.org/10.1016/j.abrep.2018.06.004CrossRefGoogle ScholarPubMed
Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of Educational Research, 99, 323338. https://doi.org/10.3200/JOER.99.6.323-338CrossRefGoogle Scholar
Scott, J., & Porter-Armstrong, A. P. (2013). Impact of multiplayer online role-playing games upon the psychosocial well-being of adolescents and young adults: Reviewing the evidence. Psychiatry Journal, 2013, Article ID 464685. https://doi.org/10.1155/2013/464685CrossRefGoogle Scholar
van Rooij, A. J., & Kardefelt-Winther, D. (2017). Lost in the chaos: Flawed literature should not generate new disorders: Commentary on: Chaos and confusion in DSM–5 diagnosis of Internet Gaming Disorder: Issues, concerns, and recommendations for clarity in the field (Kuss et al.). Journal of Behavioral Addictions, 6(2), 128132. https://doi.org/10.1556/2006.6.2017.015CrossRefGoogle Scholar
Wu, T.-Y., Lin, C.-Y., Årestedt, K., Griffiths, M. D., Broström, A., & Pakpour, A. H. (2017). Psychometric validation of the Persian nine-item Internet Gaming Disorder Scale – Short Form: Does gender and hours spent online gaming affect the interpretations of item descriptions? Journal of Behavioral Addictions, 6(2), 256263. https://doi.org/10.1556/2006.6.2017.025CrossRefGoogle Scholar