Computer Gaming and Physiological Changes in the Brain: An Insight from QEEG Complexity Analysis.

To compare the pattern of brain waves in video game addicts and normal individuals, a case-control study was carried out on both. Thirty participants were recruited from 14 to 20 years old males from two gaming centers. Twenty healthy participants were gathered from different schools in Tehran using the available sampling method. The QEEG data collection was performed in three states: closed-eye and open-eye states, and during a working memory task. As expected, the power ratios did not show a significant difference between the two groups. Regarding our interest in the complexity of signals, we used the Higuchi algorithm as the feature extractor to provide the input materials for the multilayer perceptron classifier. The results showed that the model had at least a 95% precision rate in classifying the addicts and healthy controls in all three types of tasks. Moreover, significant differences in the Higuchi Fractal Dimension of a few EEG channels have been observed. This study confirms the importance of brain wave complexity in QEEG data analysis and assesses the correlation between EEG-complexity and gaming disorder. Moreover, feature extraction by Higuchi algorithm can render support vector machine classification of the brain waves of addicts and healthy controls more accurate.

Psychometric Properties of the Persian Translation of Video Gaming Addiction Test.

INTRODUCTION: The current study aims to measure the validity, reliability, and psychometric properties of the Persian translation of the Video Gaming Addiction Test (VAT). METHODS: A total of 280 young men (14-20 years old) (Mean±SD age: 17.22±1.8 years), including excessive gamers and normal subjects, entered the study. They answered VAT, Visual Analog Scale (VAS), and Conner-Davidson Resilience Scale (CD-RISC). The VAT was translated and then back-translated. For testing reliability, we used the Cronbach alpha, split-half method, and Guttman method. Also, convergent and discriminant validity were tested to examine the construct validity of the translated version of VAT. RESULTS: The Cronbach alpha for the total scale was 0.81. Also, after splitting questions in half, the Cronbach alpha values for these halves were 0.71 and 0.69. Six Guttman lambdas were calculated with 0.75 minimum and 0.82 maximum, all showing good reliability of the test. Convergent validity was tested by testing the correlation between VAT and VAS. The Pearson correlation was fond 0.73, showing a strong relationship between the two factors (P<0.001). For testing discriminant validity, the association of VAT with CD-RISC was tested, showing no correlation between these scales (r=-0.157; P=0.09). CONCLUSION: The Persian translation of the VAT is valid and reliable, and it is appropriate for research and clinical use with acceptable properties, similar to the original version.