A new study examining the relationships among personality, motivation, and internet gaming disorder (IGD) found that predictors of IGD include male gender, neurotic and introverted personality traits, and motivation related to achievement.
The Journal of Addictions & Offender Counseling study included 1,881 adults from various countries.
IGD is defined as “persistent and recurrent use of the Internet to engage in games, often with other players, leading to clinically significant impairment or distress” by the American Psychiatric Association.
The study’s authors noted that gamers’ social tendencies, as determined by personality traits, may play a role in developing problematic gaming habits and addiction.
When counselors understand the potential social context of clients’ situations, they have more information to develop prevention and treatment strategies that treat the whole person and not just a diagnosis.
More research is needed to understand the full interplay among personality, motivation, and IGD, along with demographic risk factors.
“I am excited to be publishing on the topic of IGD along with an elite group of researchers from a variety of fields, including psychology and information technology, to meet the need for research established by the American Psychiatric Association,” said lead author Kristy L. Carlisle, PhD, of Old Dominion University.
IGD is defined as “persistent and recurrent use of the Internet to engage in games, often with other players, leading to clinically significant impairment or distress” by the American Psychiatric Association.
“One of my goals is to produce culturally responsive research that highlights the need for context in the diagnostic criteria proposed for IGD, including the social nature of the games and the level of simulation possible in them because of technology.”‘
Behavioral addictions and substance use disorders share many clinical manifestations including comorbidities such as depression [1].
Internet addiction (IA) has been regarded as a putative behavioral addiction.
Internet gaming disorder (IGD), as a most prevalent form of IA, has been included in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) as a condition warranting further study [2].
Psychiatric illnesses have conventionally been considered as categorically distinct entities. However, in the initiative of Research Domain Criteria (RDoC), neurobiological markers of cognitive and emotional dysfunctions are considered to be of significant importance in diagnostic classification and may be shared between neuropsychiatric conditions [3].
In particular, brain imaging has provided an efficient tool in identifying these neural markers. Previous studies examined the neural bases of cognitive impairments such as deficient inhibitory control and maladaptive decision-making in IGD [4, 5].
However, emotional dysfunctions (e.g., depression) and the underlying neural mechanisms in this population remained largely unclear despite high comorbidity of IGD and depression.
Depression symptoms frequently occur in individuals with IA/IGD [6]. A meta-analysis reported a significantly higher proportion of patients with depression in individuals with IA (26.3%) than in healthy controls (11.7%) [7].
Studies in IGD also reported higher depressive tendencies in individuals at risk for or with IGD, as well as reduction in depression during remission from IGD [8–10]. However, these cross-sectional findings could not clarify the directionality between IA/IGD and depression [11, 12]. A prospective study would help further revealing the interrelationship between symptoms of IGD and depression.
Resting-state fMRI has emerged as a widely used tool to investigate intrinsic brain activity [13, 14] and cerebral dysfunction in many neuropsychiatric disorders, including IGD and major depressive disorder (MDD) [15, 16]. Importantly, IGD and MDD appear to share resting-state functional connectivity (rsFC) alterations in the emotional network, comprising the amygdala and subgenual anterior cingulate cortex (sgACC).
Specifically, the amygdala contributes to the detection and integration of interceptive and autonomic information and emotional stimuli, and to formation and storage of negative emotion memories [11, 15, 17–19].
The sgACC plays a critical role in regulating arousal in response to emotional and other salient stimuli [20, 21]. Previous studies reported maladaptive interactions of the amygdala with regions of the executive control network, including the lateral prefrontal cortex (PFC), in link with excessive responses to negative stimuli both in MDD [22–24] and IGD [25].
The sgACC is central to affective regulation [15, 22] and the pathogenesis of depression [15, 26].
Interconnected with the sgACC and amygdala, the PFC is part of the task control circuit that regulates emotion [27]. MDD patients showed elevated connectivity between the sgACC and dorsolateral/dorsomedial PFC, in association with excessive self-directed rumination [28, 29].
Increased sgACC-PFC connectivity has also been found in individuals with drug addiction [30, 31]. Thus, examining the functional connectivities between the amygdala, sgACC, and PFC, as well as their relationship with depression and addiction severity may reveal critical neural phenotypes of IGD.
Furthermore, previous studies showed that behavioral interventions are effective in ameliorating both addiction severity [32, 33] and depression symptoms in individuals with IGD or IA in general [34–36].
Examining how behavioral interventions influence emotional network connectivity and its associations with reduction in depression and addiction symptoms would provide additional evidence in support of shared neural substrates of IGD and depression.
In the current study, we presented findings from a 4-year longitudinal survey to explore the interrelationship between symptom severity of depression and addiction in IGD. Furthermore, to elucidate the neural networks underlying depression in individuals with IGD, we conducted a cross-sectional rsFC study focusing on the amygdala and sgACC.
Finally, we examined how behavioral treatment ameliorated depression and remediated circuit dysfunction in link with depression in individuals with IGD. Based on previous behavioral evidence [11, 12, 37], we hypothesized a bidirectional relationship between past and future severity of Internet addiction/depression symptoms. Further, based on previous neuropsychiatric studies [25, 38], we hypothesized that individuals with IGD would show depression symptoms and altered rsFC of amygdala and sgACC with regions of the executive control network, which could be alleviated by the behavioral intervention for IGD.
Results
Study 1: a longitudinal survey of depression and addiction severity in internet gamers
Bivariate correlations demonstrated moderate stability of the same variables across the four waves, significant concurrent correlations between variables within each wave, and significant longitudinal correlations across waves (see Table S1). Specifically, across the four waves, severity of Internet addiction earlier was associated with higher depression later (r’s ranging from 0.19 to 0.27, P < 0.01), and higher depression earlier was associated with greater addiction severity later (r’s ranging from 0.25 to 0.30, P < 0.01).
To test bidirectional relationships between addiction and depression severity, we first fit Model 1 without any covariates or constraints. The model fit for this basic model was good [χ2(210) = 441.049, P < 0.001, CFI = 0.972, RMSEA = 0.044, SRMR = 0.070]. Model 1 served as the base model for comparison with more constrained models, where each of the cross-lagged paths was constrained to be equal across measurements. Consistent with our hypotheses, Model 2 showed better fit than Model 1 with better RMSEA but no significant difference in χ2, CFI and TLI values [Δχ2(12) = 10.912, P > 0.05; ΔCFI < 0.01, ΔTLI < 0.01]. Thus, metric invariance of Internet addiction was supported, suggesting that addiction severity was understood and assessed by online gamers to be the same across the 4 years. Second, Model 3 was better compared to Model 2, with slightly better RMSEA but same CFI, TLI and χ2 value. That is, the cross-lagged effects of the two relations [depression/addiction severity (T) addiction/depression severity (T+1)] were identical across the 4 years. Next, Model 4 differed from Model 3 in χ2 but not other fit indices (ΔCFI < 0.01, ΔTLI < 0.01, ΔRMSEA < 0.01), suggesting that each autoregressive effect of the two variables was stable and identical across the 4 years. Model 4 was thus selected as a final model for this study.
Table Table22 lists the path coefficients of Model 1 and 4, and shows that the severity of Internet addiction and depression symptoms was positively correlated over time. Furthermore, the impact of depression on addiction severity (β = 0.118, 0.126, 0.127) was higher than the impact of addiction severity on depression (β = 0.070, 0.066, 0.070). Together, these results provide statistical measures of the temporal interrelationship between depression and addiction severity.
Study 2: neural correlates of depression in internet gaming disorders
Demographics and internet gaming characteristics of IGD and HC subjects
IGD and HC subjects did not differ in age, education, or alcohol use and cigarette smoking measures. As expected, IGD subjects reported higher BDI (8.78 ± 5.54 vs. 2.85 ± 3.64; t = 6.91, P < 0.001) and higher CIAS scores (78.46 ± 8.40 vs. 43.49 ± 9.64; t = 20.27, P < 0.001), in comparison to HC subjects (Table S3).
rsFC differences between IGD and HC subjects
Compared to HC, IGD subjects showed significantly higher rsFC between the left amygdala and right DLPFC (Figure (Figure22 and Table Table3).3). However, no significant between-group differences were observed for the right amygdala or bilateral sgACC seeds. By using a more liberal criterion (voxel level P < 0.005 and cluster-level P < 0.05), IGD subjects showed significantly higher rsFC between the left sgACC and right DLPFC (Figure S2 and Table S4).
Within the IGD group, depression score was negatively correlated with connectivity between the left amygdala and right DLPFC (MNI: 57, 9, 30; r = −0.35; Figure Figure2).2). There was no significant correlation between addiction severity and left amygdala—right DLPFC connectivity.
Study 3: the effects of behavioral intervention on depression and the neural bases of therapeutic efficacy
Demographics and internet gaming characteristics
ANOVA with repeated measures showed a group (CBI+ & CBI−) by session (first & second assessments) interaction for the severity of IGD [F(1, 59) = 22.62, P < 0.001] and BDI score [F(1, 59) = 7.89, P < 0.01] (Table (Table4).4). Compared to the control group, the intervention group showed significant reductions in both CIAS and depression scores after treatment.
Changes in rsFC in the CBI + and CBI− groups
Compared with the CBI− group, the CBI + group showed significantly reduced rsFC of the left amygdala with left precentral gyrus and DLPFC, following the intervention (Figure (Figure3A3A and Table Table5).5). However, no significant between-group differences were observed for the right amygdala or bilateral sgACC seeds. With a more liberal criterion (voxel level P < 0.005 and cluster-level P < 0.05), CBI+ subjects showed significantly decreased functional connectivity between the left sgACC and the left postcentral gyrus (Figure S3 and Table S5).
Brain-behavior relationships
Although no significant associations between changes of the rsFC and levels of depression or addiction severity were observed in the CBI+ group, the connectivity between left amygdala and right DLPFC at baseline was negatively associated with changed score of depression ([Post-Pre], MNI: 42, 15, 27, r = 0.63; SVC; Figures 3B,C) in the CBI+ group. However, the association was no more significant when controlled for the baseline depression severity.
Source:
Wiley
Media Contacts:
Penny Smith – Wiley
Image Source:
The image is in the public domain.
Original Research: Open access
“Personality, Motivation, and Internet Gaming Disorder: Conceptualizing the Gamer”. Kristy L. Carlisle, Edward Neukrug, Shana Pribesh, Jill Krahwinkel.
Journal of Addictions & Offender Counseling doi:10.1002/jaoc.12069
