Sexual Differences in Internet Gaming Disorder (IGD): From Psychological Features to Neuroanatomical Networks

Abstract

Internet gaming disorder (IGD) has been included in the 2013 Diagnostic and Statistical Manual of Mental Disorders (DSM-5) as a condition in need of further study, and gaming disorder was recognized by the World Health Organization as a mental disorder in the International Classification of Disease (ICD-11) of 2018. IGD has different characteristics in the two sexes and is more prevalent in males than females. However, even if the female gamer population is constantly growing, the majority of available studies analyzed only males, or the data were not analyzed by sex. To better elucidate sex differences in IGD, we selectively reviewed research publications that evaluated IGD separately for males and females collected in approximately one hundred publications over the past 20 years. The available data in this narrative review indicate that IGD is strongly dimorphic by sex for both its psychological features and the involvement of different brain areas. Impulsivity, low self-control, anxiety, emotion dysregulation, and depression are some of the psychological features associated with IGD that show a sex dimorphism. At the same time, IGD and its psychological alterations are strongly correlated to dimorphic functional characteristics in relevant brain areas, as evidenced by fMRI. More research is needed to better understand sex differences in IGD. Animal models could help to elucidate the neurological basis of this disorder.

Neuroimaging Correlates of Internet Gaming Disorder: Can We Achieve the Promise of Translating Understanding of Brain Functioning Into Clinical Advances?

“…35,36 Moreover, abnormal frontoparietal/cingulo-opercular network connections have been described in males with IGD, suggesting another possible mechanism for male vulnerability to develop IGD. 37 Marraudino et al, 38 in their review, also examined sex/gender differences identified at the neurobiological level in individuals with IGD. Regarding the prefrontal region, a lower activation of the left dlPFC has been identified, especially in the case of women.…”

Internet gaming disorder and tobacco use disorder share neural connectivity patterns between the subcortical and the motor network

“…It mediates the salience and control of goal‐directed behavior in inhibitory processes (de Bourbon‐Teles et al, 2014 ; Phillips et al, 2016 ; Saalmann, 2014 ). Higher fractional anisotropy in the thalamus and lower functional connectivity between the thalamus and dorsal striatum have been found in IGD (Jin et al, 2016 ; Marraudino et al, 2022 ). Additionally, Greater brain activation and perfusion of the thalamus have been observed in TUD (Derogatis & Melisaratos, 1983 ; Due et al, 2002 ; Franklin et al, 2007 ; Kang et al, 2012 ; McClernon et al, 2009 ).…”

“…It mediates the salience and control of goal-directed behavior in inhibitory processes (de Bourbon-Teles et al, 2014;Phillips et al, 2016;Saalmann, 2014). Higher fractional anisotropy in the thalamus and lower functional connectivity between the thalamus and dorsal striatum have been found in IGD (Jin et al, 2016;Marraudino et al, 2022).…”

Development and Internal Validation of a Model for Predicting Internet Gaming Disorder Risk in Adolescents and Children

“…A longitudinal study conducted by Wartberg et al ( 8 ) found that male sex, severe self-esteem problems, and severe hyperactivity symptoms are predictors of problematic online gaming behavior. In addition to the above, several other studies focusing on risk factors for IGD support that many variables are significantly associated with the development of IGD, including video game cost ( 9 , 10 ), gaming time ( 11 , 12 ), difficulty in emotion regulation ( 13 ), higher impulsivity ( 11 , 14 , 15 ), hyperactivity symptoms ( 16 – 19 ), self-esteem problems ( 19 – 21 ), playing multiplayer games ( 22 , 23 ), emotional symptoms ( 24 , 25 ), peer relationship problems ( 26 – 28 ), family relationship problems ( 29 , 30 ), and male sex ( 2 , 12 , 31 – 33 ), among others. Therefore, we collected information on these variables, with age and lifestyle factors (which we believe may be related to family support) as candidate predictors.…”