Abnormal psychological performance as potential marker for high risk of internet gaming disorder: An eye-tracking study and support vector machine analysis - Wang, Shuai; Li, Jialing; Wang, Siyu; Wang, Wei; Mi, Can; Xiong, Wenjing; Xu, Zhengjia; Tang, Longxing; Li, Yanzhang (Frontiers in Psychology, 2022)
Individuals with high risk of internet gaming disorder (HIGD) showed abnormal psychological performances in response inhibition, impulse control, and emotion regulation, and are considered the high-risk stage of internet gaming disorder (IGD). The identification of this population mainly relies on clinical scales, which are less accurate. This study aimed to explore whether these performances have highly accurate for discriminating HIGD from low-risk ones. Eye tracking based anti-saccade task, Barratt impulsiveness scale (BIS), and Wong and Law emotional intelligence scale (WLEIS) were used to evaluate psychological performances in 57 individuals with HIGD and 52 matched low risk of internet gaming disorder (LIGD). HIGD group showed significantly increased BIS total (t = -2.875, p = 0.005), attention (t = -2.139, p = 0.035), motor (t = -2.017, p = 0.046), and non-planning (t = -2.171, p = 0.032) scores, but significantly decreased WLEIS emotion regulation score (t = 2.636, p = 0.010) and correct rate of eye tracking anti-saccade task (t = 2.294, p = 0.024) compared with LIGD group. BIS total score was negatively correlated with the WLEIS total (r = -0.473, p < 0.001) and WLEIS emotion regulation (r = -0.366, p < 0.001) scores. A combination of the WLEIS emotion regulation score and the correct rate of anti-saccade task could discriminate HIGD from LIGD with 91.23% sensitivity, 82.69% specificity, and 87.16% accuracy. Participants with higher gaming hours daily were 40 times more likely to be high risk than their counterparts (p < 0.001). Hence, psychological performances were worse in HIGD. A combination of abnormal emotion regulation and response inhibition might be a potential marker to identify HIGD individuals.