Predicción del Síndrome Informático Visual mediante la adicción a videojuegos en estudiantes chinos y españoles

  1. Lobato Rincón, Luis- Lucio 1
  2. Medina Sánchez, Maria Ángeles 1
  3. Huerta Zavala, Pilar 3
  4. Matos Cámara, Rafael Fabricio 2
  5. Bernárdez Vilaboa, Ricardo 1
  1. 1 Universidad Complutense de Madrid

    Universidad Complutense de Madrid

    Madrid, España

    ROR 02p0gd045

  2. 2 Universidad Pedagógica Nacional

    Universidad Pedagógica Nacional

    Ciudad de México, México


  3. 3 Universidad de Burgos

    Universidad de Burgos

    Burgos, España


Revista Habanera de Ciencias Médicas

ISSN: 1729-519X

Year of publication: 2023

Volume: 21

Issue: 5

Pages: e4853

Type: Article

More publications in: Revista Habanera de Ciencias Médicas


SCImago Journal Rank

(Indicator corresponding to the last year available on this portal, year 2022)
  • Year 2022
  • SJR Journal Impact: 0.145
  • Best Quartile: Q4
  • Area: Health Policy Quartile: Q4 Rank in area: 248/281
  • Area: Public Health, Environmental and Occupational Health Quartile: Q4 Rank in area: 545/612

Scopus CiteScore

(Indicator corresponding to the last year available on this portal, year 2022)
  • Year 2022
  • CiteScore of the Journal : 1.0
  • Area: Health Policy Percentile: 25
  • Area: Public Health, Environmental and Occupational Health Percentile: 22


Introduction: The use of video games, due to the extent that it has reached during the COVID-19 pandemic, is a relevant study variable especially because of its interactions with aspects of mental and visual health. Objective: to predict the occurrence of computer vision syndrome according to the level of addiction to video games in university undergraduates during a particular period of uncertainty due to health and mobility restrictions imposed by governments as a result of the COVID-19 pandemic. Material and Methods: To accomplish this objective, an online questionnaire was administered with three validated instruments: a questionnaire to assess playing video games (CHCVI), a questionnaire to evaluate video games addiction (CERV), and a questionnaire to detect computer vision syndrome (CSQ). The three questionnaires were applied to a sample of 253 students from both Chinese and Spanish universities. To establish the predictions, robust indexes were constructed based on the Factor Analysis of the instruments administered. Finally, logistic regression was applied to predict computer vision syndrome. Results: The results showed greater computer vision syndrome and appetite for video games in Spanish students, and lower computer vision syndrome scores but a greater alteration of daily life in chinese students due to this type of leisure. Moreover, it was found that students from the Chinese sample entailed a lower risk of suffering from computer vision syndrome, and that having higher levels of addiction involved 1,4 times more likelihood of suffering from such syndrome. Conclusions: The present findings demonstrate a previously unexplored relationship between video games addiction and visual symptoms related to screen exposure.