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Maladaptive Cognitions in Adolescents and Young Adults When They Play: The Dysfunctional Cognitions in Gaming Scale (DCG)

Author

Listed:
  • Iván Sánchez-Iglesias

    (Department of Psychobiology & Behavioral Sciences Methods, Complutense University of Madrid, 28223 Madrid, Spain)

  • Mónica Bernaldo-de-Quirós

    (Department of Personality, Assessment and Clinical Psychology, Complutense University of Madrid, 28223 Madrid, Spain)

  • Francisco J. Estupiñá

    (Department of Personality, Assessment and Clinical Psychology, Complutense University of Madrid, 28223 Madrid, Spain)

  • Ignacio Fernández-Arias

    (Department of Personality, Assessment and Clinical Psychology, Complutense University of Madrid, 28223 Madrid, Spain)

  • Marta Labrador

    (Department of Personality, Assessment and Clinical Psychology, Complutense University of Madrid, 28223 Madrid, Spain)

  • Marina Vallejo-Achón

    (Department of Personality, Assessment and Clinical Psychology, Complutense University of Madrid, 28223 Madrid, Spain)

  • Jesús Saiz

    (Department of Social, Work and Differential Psychology, Complutense University of Madrid, 28223 Madrid, Spain)

  • Francisco J. Labrador

    (Department of Personality, Assessment and Clinical Psychology, Complutense University of Madrid, 28223 Madrid, Spain)

Abstract

Gaming is increasingly prevalent among young people, and Gaming Disorders are a growing concern. Maladaptive cognitions related to gaming may affect the psychological development of young people. We examined psychometric properties of the Dysfunctional Cognitions Gaming (DCG) Scale in Spanish adolescents and young adults. We applied 16 items of the DCG Scale in a sample of 2173 video gamers (age from 12 to 22; 28.8% female), extracted from random sampling in educational institutions. Three factors emerged from exploratory analysis (EFA): Preoccupation, Self-esteem, and Compulsion, accounting for 51.92% of the scale’s total variance. Confirmatory analysis (CFA) yielded a good fit, RMSEA = 0.040, 90% CI [0.034, 0.046]. However, several results (factor cross-loadings in EFA, a high eigenvalue for the first factor in parallel analysis, high correlation between latent factors in CFA, and high hierarchical omega and explained common variance—ECV—in a bifactor model) suggested the convenience of using the total score for evaluation and other applied purposes. The scale showed adequate reliability, ω = 0.908, 95% CI [0.900, 0.914], R xx = 0.91. No gender or age invariance was found. The scale converged with the severity of internet gaming disorder scores, r = 0.697, p < 0.05; higher frequency of video gaming, F(1, 2165) = 474.9, p < 0.001, η 2 = 0.176; poorer mental health, r = 0.20, p < 0.05. We provided percentile ranks separated by gender and age. The DCG Scale seems to be a reliable and valid instrument to identify maladaptive cognitions about gaming in Spanish youth. These cognitions are a health-related problem; identifying and addressing them would be desirable to promote positive youth development.

Suggested Citation

  • Iván Sánchez-Iglesias & Mónica Bernaldo-de-Quirós & Francisco J. Estupiñá & Ignacio Fernández-Arias & Marta Labrador & Marina Vallejo-Achón & Jesús Saiz & Francisco J. Labrador, 2022. "Maladaptive Cognitions in Adolescents and Young Adults When They Play: The Dysfunctional Cognitions in Gaming Scale (DCG)," Sustainability, MDPI, vol. 14(23), pages 1-15, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:16109-:d:991464
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    References listed on IDEAS

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    1. Yanqiu Yu & Phoenix Kit-han Mo & Jianxin Zhang & Jibin Li & Joseph Tak-fai Lau, 2019. "Validation of the Chinese Version of the Revised Internet Gaming Cognition Scale among Adolescents in China: Maladaptive Cognitions as Potential Determinants of Internet Gaming Disorder," IJERPH, MDPI, vol. 17(1), pages 1-12, December.
    2. John Horn, 1965. "A rationale and test for the number of factors in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 30(2), pages 179-185, June.
    3. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
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