Subtyping treatment-seeking gaming disorder patients

BACKGROUND AND AIMS

Gaming Disorder (GD) is characterized by a pattern of persistent and uncontrolled gaming behavior that causes a marked impairment in important areas of functioning. The evolution of the worldwide incidence of this disorder warrants further studies focused on examining the existence of different subtypes within clinical samples, in order to tailor treatment. This study explored the existence of different profiles of patients seeking treatment for GD through a data-driven approach.

METHODS

The sample included n = 107 patients receiving treatment for GD (92% men and 8% women) ranging between 14 and 60 years old (mean age = 24.1, SD = 10). A two-step clustering analysis approach explored the existence of different underlying GD profiles based on a broad set of indicators, including sociodemographic features, clinical course of the condition (e.g., onset or evolution), psychopathological symptoms, and personality traits.

RESULTS

Two GD profiles emerged. The first cluster grouped together patients who presented with a lower psychological impact (n = 72, 66.1%), whereas the second cluster comprised patients with a higher psychological impact (n = 35, 32.7%). Cluster comparisons revealed that those patients presenting the higher impact were older, with a later onset of pathological gaming patterns, and more pronounced psychopathological symptoms and dysfunctional personality profiles.

CONCLUSIONS

GD severity is influenced by specific demographic, clinical, and psychopathological factors. The identification of two separate profiles provides empirical evidence that contributes to the conceptualization of this disorder, as well as to the development of reliable and valid screening tools and effective intervention plans focused on the precise characteristics of the treatment-seeking patients.

Disturbed craving regulation to gaming cues in internet gaming disorder: Implications for uncontrolled gaming behaviors

BACKGROUND

The ability to control craving for games is very important to abstain from Internet gaming disorder (IGD) and abundant clinical evidence has suggested that craving dysregulation is the essential pathogenesis for IGD. However, the neural mechanism underlying this feature remains unclear.

METHODS

Subjective evaluation and fMRI data from 44 participants (IGD participants: 21; recreational Internet game users (RGUs): 23) were collected while they were performing a regulation of craving task. We analyzed and compared their brain features while they regulated cravings to gaming stimuli.

RESULTS

Compared to RGUs, IGD participants showed enhanced brain activation in the right anterior cingulate cortex, posterior cingulate cortex (PCC), orbitofrontal cortex and middle temporal gyrus and in the left dorsolateral prefrontal cortex and thalamus during the regulation of craving task. Generalized psychophysiological interaction (gPPI) analysis revealed that IGD participants showed decreased functional connectivity between the right PCC and right inferior parietal lobule compared to that in RGU participants.

CONCLUSIONS

The results suggested that deficits of craving regulation in IGD participant were associated with the imbalanced coordination between the reward network and the executive network. Enhanced game-seeking motivation and disturbed executive control are responsible for craving dysregulation in IGD participants. These findings suggest a biological mechanism for IGD that may help in finding potential interventions.

Males are more sensitive to reward and less sensitive to loss than females among people with internet gaming disorder: fMRI evidence from a card-guessing task

BACKGROUND

Many studies have found an interesting issue in the Internet gaming disorder (IGD): males are always observed to be the majority. However, there are little research to exploring the differences in the neural mechanisms between males and females in decision-making process among people with IGD. Therefore, explore the reward/loss processing between different gender with IGD could help in understanding the underlying neural mechanism of IGD.

METHODS

Data from functional magnetic resonance imaging (fMRI) were collected from 111 subjects (IGD: 29 males, 25 females; recreational internet game user (RGU): 36 males, 21 females) while they were performing a card-guessing task. We collected and compared their brain features when facing the win and loss conditions in different groups.

RESULTS

For winning conditions, IGD group showed hypoactivity in the lingual gyrus than RGU group, male players showed hyperactivity in the left caudate nucleus, bilateral cingulate gyrus, right middle frontal gyrus (MFG), right precuneus and inferior parietal lobule relative to the females. And significant sex-by-group interactions results showed higher brain activities in the thalamus, parahippocampal gyrus and lower brain activities in Inferior frontal gyrus (IFG) were observed in males with IGD than females. For losing conditions, IGD group showed hypoactivity in the left lingual gyrus, parahippocampal gyrus and right anterior cingulate cortex (ACC) compared to the RGU group, male players showed hyperactive left caudate nucleus and hypoactive right middle occipital gyrus relative to females. And significant sex-by-group interactions results showed that compared to females with IGD, males with IGD showed decreased brain activities in the IFG and lingual gyrus.

CONCLUSIONS

First, there appeared to be no difference in reward processing between the IGD and RGU group, but IGD showed less sensitivity to loss. Secondly, male players showed more sensitivity to rewards and less sensitivity to losses. Last but not least, males and females showed opposite activation patterns in IGD degree and rewards/losses processing. And male IGD subjects are more sensitive to reward and less sensitive to loss than females, which might be the reason for the gender different rates on IGD.

Spanish Validation of the Internet Gaming Disorder Scale-Short Form (IGDS9-SF): Prevalence and Relationship with Online Gambling and Quality of Life

Online gaming is a very common form of leisure among adolescents and young people, although its excessive and/or compulsive use is associated with psychological impairments in a minority of gamers. The latest (fifth) edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5, Section III) tentatively introduced Internet Gaming Disorder (IGD). Since then, a number of evaluation tools using the DSM-5 criteria have been developed, including the Internet Gaming Disorder Scale-Short Form (IGDS9-SF). The main objective of this study was to translate and adapt the IGDS9-SF into Spanish, as well as to obtain indicators relating to its validity and reliability. The Spanish version of four scales were administered: IGDS9-SF, Mobile Phone-Related Experiences Questionnaire (CERM), Online Gambling Disorder Questionnaire (OGD-Q), and KIDSCREEN-27. The sample comprised 535 Vocational Training students (mean age 18.35 years; SD±2.13; 78.5% males) who reported playing video games in the past 12 months. Confirmatory factor analysis yielded a one-dimensional model with a good fit while the reliability indicators were satisfactory. Findings indicated that 1.9% of gamers were classified with IGD (meeting five or more criteria for more than 12 months). Additionally, another 1.9% were considered gamers 'at-risk' because they endorsed four criteria. Positive and significant relationships were found between the IGDS9-SF, the CERM, and the OGD-Q. Participants classified with IGD had poorer health-related quality of life. In conclusion, the Spanish IGDS9-SF is a valid and reliable instrument to assess IGD according to the DSM-5.

Personality Factors Predicting Smartphone Addiction Predisposition: Behavioral Inhibition and Activation Systems, Impulsivity, and Self-Control

The purpose of this study was to identify personality factor-associated predictors of smartphone addiction predisposition (SAP). Participants were 2,573 men and 2,281 women (n = 4,854) aged 20–49 years (Mean ± SD: 33.47 ± 7.52); participants completed the following questionnaires: the Korean Smartphone Addiction Proneness Scale (K-SAPS) for adults, the Behavioral Inhibition System/Behavioral Activation System questionnaire (BIS/BAS), the Dickman Dysfunctional Impulsivity Instrument (DDII), and the Brief Self-Control Scale (BSCS). In addition, participants reported their demographic information and smartphone usage pattern (weekday or weekend average usage hours and main use). We analyzed the data in three steps: (1) identifying predictors with logistic regression, (2) deriving causal relationships between SAP and its predictors using a Bayesian belief network (BN), and (3) computing optimal cut-off points for the identified predictors using the Youden index. Identified predictors of SAP were as follows: gender (female), weekend average usage hours, and scores on BAS-Drive, BAS-Reward Responsiveness, DDII, and BSCS. Female gender and scores on BAS-Drive and BSCS directly increased SAP. BAS-Reward Responsiveness and DDII indirectly increased SAP. We found that SAP was defined with maximal sensitivity as follows: weekend average usage hours > 4.45, BAS-Drive > 10.0, BAS-Reward Responsiveness > 13.8, DDII > 4.5, and BSCS > 37.4. This study raises the possibility that personality factors contribute to SAP. And, we calculated cut-off points for key predictors. These findings may assist clinicians screening for SAP using cut-off points, and further the understanding of SA risk factors.