|Year : 2023 | Volume
| Issue : 1 | Page : 36-45
Internet Gaming Disorder: An Interplay of Cognitive Psychopathology
Filzah Kakul, Sarah Javed
Department of Psychology, Faculty of Social Sciences, Aligarh Muslim University, Aligarh, Uttar Pradesh, India
|Date of Submission||02-Nov-2022|
|Date of Decision||14-Jan-2023|
|Date of Acceptance||17-Jan-2023|
|Date of Web Publication||10-Feb-2023|
Department of Psychology, Faculty of Social Science, Aligarh Muslim University, Aligarh - 202 002, Uttar Pradesh
Source of Support: None, Conflict of Interest: None
Introduction: Internet addiction is currently considered a worldwide problem, with a possible impact on mental health. Young adults are recognized to be at high risk of developing Internet gaming disorder (IGD). According to a recent clinical model, young adults with IGD may endorse a distinct set of maladaptive beliefs that underlie persistent and excessive engagement in Internet gaming activities. The objective of this study was to examine the incidence of problematic gaming beliefs and psychological distress in a sample of “Indian Young Adults” with and without IGD. Methods: The research is descriptive in nature, conducted during the month of April 2022–May 2022 on a sample of 306 young adults (185 males and 121 females) recruited from multiple universities. A Google form survey that included validated measures of IGDs, Internet gaming cognition, and psychological distress were distributed on various online platforms for collecting the data. Results: According to the findings, young adults with IGD report significantly higher maladaptive gaming beliefs (t = 16.199, P < 0.001) and psychological distress (depression - t = 12.11. P = < 0.001 and anxiety/stress - t = 10.95, P = < 0.001) than young adults without IGD. The size of observed effects was large for cognition (Cohen's d = 2.14), depression (Cohen's d = 2.14), and anxiety/stress (Cohen's d = 1.96). The sample also reported strong correlation between IGD symptoms and gaming cognitions (P = <0.001). Further hierarchical regression analysis revealed depression variables as a significant predictors in the final model (β = 0.212, P = 0.002, confidence interval [CI] = 0.219–0.944) and overvaluation (β = 0.196, P = 0.020, CI = 0.048–0.545), maladaptive rules (β = 0.334, P = 0.003, CI = 0.117–0.551), and gaming social acceptance (β = 0.272, P = 0.001, CI = 0.190–0.693) as the three strongest cognition predictors of IGD symptoms. Conclusion: These findings indicate that young adults with IGD have distinct problematic thoughts about gaming and highlight the importance of addressing these cognitions in therapeutic interventions for the disorder.
Keywords: Anxiety, depression, gaming cognition model, internet gaming disorder, maladaptive beliefs, psychological distress, video gaming cognitions
|How to cite this article:|
Kakul F, Javed S. Internet Gaming Disorder: An Interplay of Cognitive Psychopathology. Asian J Soc Health Behav 2023;6:36-45
| Introduction|| |
Technology has been constantly evolving and creating novel inventions for decades, and the use of it, particularly the Internet, is expanding every year. Its influence may be observed in practically every aspect of our lives. With the shift of manual tasks into digitalized activities, whether it's education, socializing, gaming, entertainment, etc., everything is chosen to be done through this platform.
One of the major problem young adults is particularly vulnerable of developing is related to Internet video gaming. Internet video gaming is associated with psychological problems and is a big health concern worldwide.,,,, In 2021, there were an estimated 3.24 billion players worldwide, with nearly 1.48 billion gamers in Asia, making it the largest video gaming market in the world. The online gaming sector in India was valued at over 79 billion Indian rupees, increasing from approximately 65 billion rupees the previous year. This sector is projected to be valued more than 150 billion Indian rupees by 2024, with a compound annual growth rate of roughly 15%.
Over the last decade, research on mental health issues related to Internet gaming disorder (IGD) has increased. Moreover, with the increased recognition of IGD, the World Health Organization issued the 11th version of the International Classification of Diseases-11 in mid-2018, describing IGD, as follows:
“Persistent or recurrent gaming behavior characterized by an impaired control over gaming, increasing priority given to gaming over other activities to the extent that gaming takes precedence over other interests and daily activities and continuation of gaming despite the occurrence of negative consequences.“
IGD is also classified as a condition in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) in Section III. It includes nine main criteria, which include (1) obsession, (2) withdrawal, (3) tolerance building, (4) impaired control, (5) loss of interest in other activities and hobbies, (6) continued play, despite knowing the consequences of its impact on life, (7) a tendency to lie about the frequency of gaming, (8) a desire to escape from psychological problems, and (9) loss of opportunity in work or study or significant relationships. According to the suggested criteria, an individual is said to exhibit IGD if they have five or more of these symptoms in a year.
Individuals who engage in excessive Internet gaming but not at the level of IGD – specifically, they meet one to four of the nine DSM-5 criteria for IGD (i.e., at-risk groups) tend to have lower cognitive functions, especially in terms of verbal ability and working memory. However, individuals who meet the diagnostic criteria for IGD (i.e., clinical groups) are gamers who are unable to control their excessive behavior despite being conscious of the root of the problem, to the extent where they even ignore their basic needs (eating, sleeping, hygiene, etc.), resulting in a range of health problems such as weight gain or loss, dry or strained eyes, headaches, backaches, carpal tunnel syndrome, general fatigue, and/or exhaustion.,,,, In addition, depression, anxiety, obsessive-compulsive symptoms, hostility/aggression, and minor indications of attention deficit hyperactivity disorder have also been associated with IGD and psychopathology. These risk of psychopathology due to problematic gaming is observed at greater rates among young adults who already have symptoms of generalized anxiety disorder, panic disorder, depression, social phobia, or attention-deficit hyperactivity disorder.,, Problematic video gamers also face disruptions in schoolwork and housework, social functioning, leisure activities, and health and lifestyle behaviors.,, Moreover, they were found to be investing their time, effort, and money to compete with other players through electronic devices. Such activities exhibited in problematic video gaming or IGD populations were observed to be similar in nature to addictive disorders such as pathological gambling. Like gambling, video-gaming also involves repetitious behaviors and cognitions of reward seeking, preoccupation, loss of control over gaming, tolerance, and withdrawal.,,
There are major cognitive characteristics associated with IGD, a review study identified seven distinct cognitions related to IGD as follows: (i) preference for online social interaction, (ii) mood regulation, (iii) cognitive diversion, (iv) self-escapism,,,, (v) positive attitude toward in-game rewards, (vi) actual-ideal self-discrepancy, and (vii) intrinsic motivation to play. Attempts have been made to adapt these criteria to cognitive behavioral models. However, preoccupation (i.e., obsession with games) is identified as the most central or core criterion among the IGD cognitions.,,
Models of internet gaming cognitions
Several research studies have focused on and examined IGD. However, they lack a clear theoretical model. However, some theories/theoretical models may still be significant in understanding the clear hypothesis behind the clinical incidence of IGD. The basis of prevalent cognitive-behavioral models of problematic Internet gaming is the concept of preoccupation (i.e., obsessive thought patterns) as well as general maladaptive beliefs about oneself, others, and the world.,
The relationship between video-gaming cognitions and problematic behavior can partly be understood by the cognitive dissonance theory. If the individual spends a lot of time, money, and/or other resources on playing video games, or when their habits start to interfere with daily life, the person feels regret because they start feeling personally accountable for the negative results due to their playing activities. The majority of players may actively change their behavior to lessen this dissonance. Some gamers, on the other hand, affirm themselves by the benefits of videogame playing in an attempt to elucidate the negative outcomes. This helps the individual to lessen their dissonance while simultaneously persisting in harmful behaviors. According to these findings, it may be possible to distinguish between problematic and nonproblematic players based on how much a person feels personally accountable for the consequences of his or her behavior as well as their willingness to change their behaviors.
A cognitive-behavioral model by Davis, in relevance to IGD, proposes that pathological Internet usage is characterized by “problematic cognitions coupled with behaviors that either intensify or maintain the maladaptive response.” These cognition distortions are activated by Internet-related stimuli and establish and perpetuate excessive Internet-use behavioral habits. They include cognition thoughts about oneself and the world, such as “I am only good on the Internet,” “I am worthless offline, but I am someone online,” “The Internet is the only place I can feel safe,” and “Nobody loves me offline.” These cognitions were found to be analogous to Beck's Cognitive Theory of Depression. In short, they suggest that individuals use the Internet to look for validating social engagement and feedback from others because they have a low opinion of themselves.
Another model developed by Dong and Potenza suggests that IGD is characterized by a need for instant gratification despite recognizing the long-term harmful repercussions of it. This decision-making perspective is thought to interact with craving, meaning a desire to feel pleasure and to lessen unpleasant emotional experiences.
A recent model called the “Four Factor Model,” proposed by King and Delfabbro outlines four IGD-related cognition factors for understanding problematic gaming which corresponds to the IGD's definition by DSM-5, containing nine criteria in the following way: (1) Beliefs about the value and tangibility of game rewards (DSM-5 IGD criteria: obsession and loss of interest in other activities and hobbies). These suggest how an individual overvalue in-game rewards and how they get attached to an avatar or online identity as if it's an extension of themselves. (2) Inflexible and maladaptive gaming rules (DSM-5 IGD criteria: tolerance building, impaired control, and continued play despite knowing the consequences of its impact on life and a tendency to lie about the frequency of gaming). These include cognitive distortions in such a way that the individual despite being aware of psychological issues, people keep playing games excessively and fails in attempts to control their engagement. (3) Over-reliance on gaming to meet self-esteem needs: (DSM-5 IGD criteria: withdrawal and a desire to escape from psychological problems). These suggests how problematic users may have low self-esteem and come to redefine their self-worth in terms of their videogame playing abilities and their performance and gaming investment become the measure of building their self-esteem. (4) Gaming as a method of gaining social acceptance: (DSM-5 IGD criteria: loss of opportunity in work or study or significant relationships). This factor suggests that the social context of Internet gaming may enable the player to develop a network of online-based relationships whilst also disengaging from social contacts who are incompatible with the individual's gaming behavior. Online relationships may be facilitated by the interaction of in-game avatars, including cooperative and competitive gaming activities that provide many opportunities for social advancement via leaderboards and player ranking systems.,
Currently, there is a need to better comprehend the cognitive factors that underlie IGD in young adults. Based on our review of existing literature, we have found no studies the same on Indian young adults. Although previous internet gaming cognition models, have talked about maladaptive beliefs, they lack detailed exploration.
Based on these premises, we chose to quantitatively describe and analyze the presence of problematic gaming beliefs in a sample of young adults with and without IGD. The prediction was that IGD-affected young adults would report significantly more problematic Internet gaming cognitions than young adults without IGD. Particularly, IGD young adults were hypothesized to: (i) be more prone to overvalue gaming rewards, items, and identities, (ii) have more rigid rules and biases that foster gaming behaviors, and (iii) be more likely to rely on gaming for their self-esteem and social identity. In addition, the study sought to identify certain gaming cognitions that contributed to an elevated risk of IGD symptomatology.
| Methods|| |
The research is descriptive in nature, conducted during the month of April 2022–May 2022 on a sample of 306 young adults (185 males and 121 females) recruited from multiple universities. A survey was used to examine basic demographic data including age, gender, religion, region, education, family type and factors of video-gaming engagement questionnaire (such as ownership and accessibility, frequency of usage, and types of games played). The following standardized measures were included in the survey for assessing the variables.
Internet Gaming Disorder Scale 9-short-form
The Internet Gaming Disorder Scale 9 – Short-form (IGDS9-SF), a shortened version of the “Internet Gaming Disorder Scale (18 items),” has been intended to determine all nine diagnostic criteria of IGD in an individual which are described by DSM-5., The respondents were supposed to answer to all the nine-items on the 5-point Likert Scale having values as: 0 − never, 1 − rarely, 2 − sometimes, 3 – often, and 4 − very often. Scores are delineated into three categories on the basis of symptoms present: (1) Nonproblem (1–2 symptoms); (2) At-risk (3–4 IGD symptoms); and (3) highly at risk (5 or more IGD symptoms, as per DSM-5 guidelines). Good psychometric property of IGDS9-SF has been reported by previous studies.,, Furthermore, three additional questions were added to test the reliability of the responses: (1) do you personally believe that you have a video-gaming problem (yes/no), (2) whether others had stated that you have a gaming problem (yes/no), and finally (3) the duration of the symptoms, with response options of “0–3 months,” “3–6 months,” “6–12 months,” or “over 12 months.“
Internet Gaming Cognition Scale
King and Delfabbro designed the scale to examine cognitions associated with gaming. The scale comprises four sub-dimensions and 24 items: beliefs about game reward value and tangibility (4 items), maladaptive and inflexible rules about gaming behavior (8 items), over-reliance on gaming to meet self-esteem needs (7 items), and gaming as a method of gaining social acceptance (5 items). The scale has a 5-point Likert scale having values as: 0 − never, 1 − rarely, 2 − sometimes, 3 – often, and 4 − very often.
Depression Anxiety Stress Scale-10
The Depression Anxiety Stress Scale (DASS-10) is a 10-item version of the DASS-42. The DASS-10 may be used to evaluate overall distress among adolescents and adults. The items are framed on a 4-point Likert scale having values as: 0 − never, 1 − sometimes, 2 − often, and 3 − always. Devaluation of life, despair, self-deprecation, apathy, and severity of depression can all be evaluated on the depression scale. The Anxiety/Stress Scale measures situational anxiety and subjective feelings of anxious affect, nervous arousal, irritability, impatience, etc.
Initial descriptive analyses, independent-samples t-tests, and one-way analysis of variances (ANOVAs) were performed on the dataset to determine the differences in demographic, cognition, and distress scores according to IGD status. To evaluate the potential differences in cognitive profiles across IGD and gaming activity groups, ANOVA techniques were employed. A hierarchical regression was employed to examine the relationship between gaming cognition variables and IGD symptomatology.
This research was approved by the Research Committee affiliated with Department of Psychology, Faculty of Social Sciences, Aligarh Muslim University. All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study. The participants were explained about the voluntary nature of participation in this study and the possibility of withdrawal from the study at any time without being penalized.
| Results|| |
Internet gaming disorder symptoms: Prevalence, characteristics, and course
The prevalence of IGD in the sample was 14.2%. In our sample of highly at risk, the symptoms that were most frequently reported were escapism (100%) and losing interest in previous hobbies (100%), followed by preoccupation (97%) and tolerance (97%) and highly at risk predominantly played multiplayer online games (48%) followed by puzzles games (16%). The majority (97%) of highly at risk had a personal computer or gaming console. It was found that highly at risk reported, on average, at least 3.5 h/day playing video games.
Only 16 (36%) of the highly at risk responded “yes” when asked whether they believed that they had video gaming problem. Similar to this, 26 (59%) highly at risk indicated that others had stated that they have a video-gaming problem. The majority of highly at risk who had a gaming problem reported a symptom course that lasted longer than 12 months (n = 12, 75%).
Comparisons of study variables according to internet gaming disorder classification
A one-way ANOVA revealed significant between-group differences in total hours spent in video-gaming, with Games-Howell post-hoc suggesting an increased trend in gaming hours according to IGD classification. Highly at risk reported spending three times as many gaming hours per day than nonproblem comparison cases. Effect size using Eta square was reported to be small.
Significant between-group differences in gaming cognition scores was observed. Highly at risk scored significantly higher than at-risk cases on all cognition subscales who, in turn, scored significantly higher than comparison cases. Notably, nonproblem cases indicated agreement with, on average, no more than five items on the 24-item video-gaming cognition scale. Highly at risk, on the other hand, on an average endorsed 15 items on the cognition scale. This Eta Square effect size was reported to be moderate.
There were statistically significant between-group differences on DASS subscales, although the observed effect sizes were moderate and group mean scores tended to fall within the “mild” to “moderate” range for symptom severity, indicating relatively low clinical significance.
There were no statistically significant age differences in IGD classification. However, there was a small effect of gender on IGD classification, with a greater tendency toward males reporting IGD symptoms.
Assessment of cognitive profiles of highly at risk
To further examine between-group differences in cognition according to IGD classification, a separate analysis involved the identification of two subgroups of participants: (1) highly at risk (meeting 5 or more IGD criteria, as noted above) and (2) nonproblem cases (zero reported IGD symptoms). Groups did not differ significantly in gender (χ2 = 8.97, P = 0.62) or age (t = 0.75, P = 0.45). These selection criteria resulted in a nonclinical gaming group that could be directly compared to highly at risk along psychological variables [Table 1].
|Table 1: A comparison of video gamers with and without Internet gaming disorder on demographics, cognition, and psychological distress|
Click here to view
As indicated in [Table 1], independent samples t-tests indicated that highly at risk scored significantly higher than nonclinical cases (i.e., healthy controls) on all cognition-related measures and on DASS. The effect sizes for these differences ranged from large to very large. In particular, highly at risk scored over one standard deviation higher than controls on overvaluing and gaming self-esteem scales as well as total cognition scores. Comparisons of DASS scores across groups also identified large differences, but DASS symptom severity was relatively low in clinical terms across groups [Table 1].
Cognition's role in Internet gaming disorder
Further zero order correlation was conducted to determine the statistical utility of cognition variables in predicting IGD symptomatology. [Table 2] presents Pearson's correlations, which were used to assess bivariate associations between demographics, video-gaming activity, cognition variables, and DASS measures. Notably, this analysis identified significant and strong relations between cognition variables and IGD symptoms, as well as video-gaming activity and IGD symptoms [Table 2].
|Table 2: Zero order correlation between age, video gaming frequency, Internet gaming disorder symptomology and cognition variable, and Depression Anxiety Stress Scale measure|
Click here to view
Given that IGD scores were related to gaming frequency, psychological distress, as well as the cognition scores, it was important to examine the relationship between cognitions and IGD after controlling for these variables. In the first step (Model 1) of the hierarchical regression analysis, gaming frequency and DASS variables were entered, followed by cognitive variables in the second step (Model 2). As shown in [Table 3], Model 2 significantly predicted IGD symptomatology and explained 69% of the variation in IGD symptoms. Cognition variables accounted for 20% of the variance in the model based on differences in adjusted R2 values. The DASS-Depression variables were significant predictors in the final model. Gender and gaming frequency were not significant predictors in the final model. Overvaluation, maladaptive rules, and gaming social acceptance were the three strongest cognition predictors of IGD symptoms [Table 3].
|Table 3: Hierarchical multiple regression models of demographic, gaming, cognitive, and psychological distress factors predicting Internet gaming disorder symptoms|
Click here to view
| Discussion|| |
The objective of this study was to examine the incidence of problematic gaming beliefs and psychological distress in a sample of “Indian young adults” with and without IGD. Its secondary aim sought to identify certain gaming cognitions that contributed to an elevated risk of IGD symptomatology. Furthermore, we expected that young adults with IGD will have considerably more problematic internet gaming cognitions than non-IGD young adults.
Important trends were found in this research from the participants across our study, which included a higher proportion of (i) male respondents than female, (ii) urban respondents rather than rural, (iii) graduate students rather than PG, Ph.D. students, (iv) nuclear family than joint or extended family, (v) multiplayer gamers followed by puzzle gamers as compared to other types of gamers, and (vi) computer or gaming console owner than not owning it.
This research sheds insight on the significant prevalence of IGD in young adults. The prevalence of IGD in the sample was 14.2%. This was in line with a recent meta-review that indicated the prevalence of IGD ranged from 0.21% to 57.50% in general populations across 160 studies conducted internationally. Further, it was found that clinical groups (i.e., young adults with IGD) persisted specific maladaptive beliefs compared to the at-risk groups and other gaming populations. Gamers without IGD also exhibited similar cognitions, but to a lesser extent than IGD populations. The variations in general cognitive functioning were also examined, and the most common symptoms observed in young adults were their engagement in gaming activities as a form of escapism from the real world and its associated problems. This was in line with a review research that found escapism to be the most common cognition associated with IGD. Moreover, it was found that young adults with IGD lost interest in their hobbies as a result of their obsession with the gaming routine and style, which was followed by the need for longer gaming sessions, i.e., tolerance. Overall, as expected, maladaptive gaming cognitions were more strongly significant in clinical groups than in non-IGD groups. There was a large practical difference in cognition types and was greater than one standard deviation. It is noteworthy that these notions are central to the psychometric properties of the Internet gaming cognition scale, as well as to the cognitive behavioral models, specifically, “The Four-Factor Model” by King and Delfabbro.
The findings showed that the presence of maladaptive gaming cognitions and IGD symptoms were positively correlated linearly. Moreover, there were significant differences in cognition types of about one standard deviation between IGD groups and non-IGD groups. We can also infer from the results that participants in clinical groups were four times higher on depression and anxiety/stress (i.e., items of DASS). Therefore, we may conclude that young adults with IGD have more psychological distress. The observed effect magnitude, however, varied only moderately, not showing considerable severity in symptoms. There was no (very less) significant effect on age and gender. The total number of video gaming hours per day has a positive relationship with IGD symptomology. Although it is recognized that gaming time is not a direct indicator of harm, it was found that highly at risk reported, on average, at least 3.5 h/day playing video games. This amount exceeds the recommended screen time guidelines (i.e., <2 h/day) for adolescents set forth by multiple health guidelines internationally.
In addition, only a few (i.e., 36%) of the highly at risk accepted that they had video gaming problems. It is possible that the rest were in denial or in refusal to accept the nature and extent of their problems. They might have been too embarrassed or ashamed to accept they had a problem, or they may have rationalized that gaming is not detrimental because of its beneficial components, such as online socialization. Another major key point worth noting is that the players might lack insight about their problematic behaviors and cognitions, or specifically, we can say, they don't recognize the engagement in gaming as problematic, which further becomes an obstacle in seeking self-directed or professionally administered help in overcoming gaming problems. The development of insight into the negative effects of gaming and the identification of cognitive loopholes that result in denial should be one of the main objectives for helping problematic gamers. Working toward recognizing the root of the problem associated with denial and irrational beliefs impairing the adolescent's self-efficacy in the real world may provide pathways toward learning essential skills and exposure.,
The main finding of the study was the high correlation between IGD symptomatology and gaming cognitions. Notably, the observed difference in total cognitive scores had an effect size that was considerably large and was close to or over two standard deviations, which is normally a marker of a difference that is clinically significant. This idea is consistent with current knowledge of the cognitive mechanisms underlying psychopathologies in the both normal and clinical populations, such as cognitive bias in gambling, fear in phobias, delusions in schizophrenia, and body image issues in eating disorders.
Nonproblem and clinical IGD groups significantly differed on all four gaming cognition types. According to the regression analysis, three types of cognition were responsible for the majority of the variation in IGD symptomology. Maladaptive rules about gaming, overvaluation, and social acceptability of gaming were these three types. These gaming cognitions were specifically in line with the processes stated by Wright et al., including anticipation (i.e., game-related expectancies), relief (i.e., providing a sense of control), and facilitation (i.e., granting permission to continue gaming based on belief that one cannot cope with gaming). To fully understand these mechanisms of IGD and the related affective and arousal responses, more in-depth research is required.
Suggestions for future research
Individuals turn to playing online games, to cope with existential situations that make them experience emotional distress (such as anxiety, tension, and stress), social alienation or/and isolation, frustration, and life dissatisfaction, However, a person's mental health might be significantly impacted by prolonged and excessive online gaming, which can keep them to avoid interacting with others in real life.,,, Overall, the inferences will continue to alter in different settings in terms of the general video gaming cognitions and psychological distress. To date, only a small number of empirical studies have been conducted on this typology and thus we anticipate that the future research on similar frameworks will be aided by our work.
However, video gaming is not necessarily problematic. Previous studies have also reported that some video game genres may be even beneficial in terms of socialization and interaction. The therapeutic use of video games has not been based on strong scientific evidence besides the general notion that somehow some video games have some beneficial effects on cognition in some individuals. However, it is necessary to provide appropriate treatment interventions to help clients to abstain from gaming or to reduce gaming behavior. The cognitive behavioral models have provided some therapeutic interventions for problematic gaming. Furthermore, the most commonly identified intervention by several studies in this regard is cognitive behavioral therapy.,, Another study has shown that 84-h abstinence from gaming plays an important role in improving problematic gaming cognitions and behaviors. Apart from this, we recommend the support of preventative educational measures and systems, involvement of family members along with society's support in improving, and promoting a healthy lifestyle for those who are affected by this disorder.
The present study has several limitations which need to be addressed. The methodology of surveying exclusively on the online platform hindered reaching to all segments of the population (e.g., offline population groups). Further, the adoption of measuring instruments used to evaluate IGD had limited access over the Internet and was deployed only in a small number of studies. For example, the Internet Gaming Cognition Scale was identified in relatively few similar typologies. The scale's usage was mostly noticed in researches evaluating the scale's psychometric properties and the translation of the scale accordingly to the language of the particular regions for future studies.,, However, in our study, we employed these scales to gain insight about the individual's mental health and cognitive distortions. Although from the subject's responses, we inferred that there might be faking or false filling of responses for social desirability, i.e., in order to appear more favorable to society. In addition, one of the constraints found while performing this study was the restricted access to information and data as they were not open access. Our study was confined to evaluating these problems in a particular age group (i.e., young adults). Hence, there might have been selection bias. Since, nowadays, it is being noticed that the prevalence of IGD is increasing in other age groups as well. For example, IGD symptoms are likely to be observed in a variety of populations such as children's and adult's; hence, a more focused investigation on all groups is required to better understand the etiology, prevalence, and risk factors. In addition, the fact that our study could only be done in India limited the geographic scope of our research and perhaps to some extent constrained the generalizability of our findings. However, it has been shown that geographic locations have no discernible effect on observed cognitions. Further, we were not able to examine the several domains related to the dysfunctional cognitions in a subject, corresponding to different gaming genres and the effects on various health and life activities such as eating, sleeping, and daily work patterns, etc., in light of IGD within an individual. Hence, we would suggest a more detailed examination in future that overcomes all of these constraints to better comprehend and infer from the study.
| Conclusion|| |
This study indicates that internet gaming cognitions might be useful predictor of young adults with or without gaming disorder. The findings retrieved from the beliefs about Internet gaming can be valuable in clinical settings and research endeavors. The systematic difference shown on the IGD cognitive profile, however, is only the initial step in comprehending the internal mental processes of gaming disorder. In order to fully comprehend the etiology, prevalence, and related risk factors, additional research is required to further explore these observations, especially in varied gaming communities. Given the acknowledged challenges with participant insight into gaming problems, Internet gaming cognition may be a valuable auxiliary measure of outcomes in intervention research. The identification of IGD cognitions in individuals may assist healthcare professionals developing therapeutic models and intervention strategies that will benefit patients and their families. In the new and expanding field of study into the cognitive processes behind IGD, it is hoped that this basic work may serve as a starting point for numerous other investigations.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Schneider LA, King DL, Delfabbro PH. Maladaptive coping styles in adolescents with internet gaming disorder symptoms. Int J Ment Health Addict 2018;16:905-16.
Ferguson CJ, Coulson M, Barnett J. A meta-analysis of pathological gaming prevalence and comorbidity with mental health, academic and social problems. J Psychiatr Res 2011;45:1573-8.
King DL, Delfabbro PH. The cognitive psychopathology of internet gaming disorder in adolescence. J Abnorm Child Psychol 2016;44:1635-45.
Müller KW, Janikian M, Dreier M, Wölfling K, Beutel ME, Tzavara C, et al.
Regular gaming behavior and internet gaming disorder in European adolescents: Results from a cross-national representative survey of prevalence, predictors, and psychopathological correlates. Eur Child Adolesc Psychiatry 2015;24:565-74.
Rehbein F, Kliem S, Baier D, Mößle T, Petry NM. Prevalence of internet gaming disorder in German adolescents: Diagnostic contribution of the nine DSM-5 criteria in a state-wide representative sample. Addiction 2015;110:842-51.
Diagnostic and Statistical Manual of Mental Disorders – The DSM-5. 5th
ed. The DSM5. Washington, DC: American Psychiatric Association; 2013.
Jang JH, Chung SJ, Choi A, Lee JY, Kim B, Park M, et al.
Association of general cognitive functions with gaming use in young adults: A comparison among excessive gamers, regular gamers and non-gamers. J Clin Med 2021;10:2293.
Király O, Nagygyörgy K, Griffiths MD, Demetrovics Z. Problematic Online Gaming. Behavioral Addictions, Academia Press. 2014; 61-97.
Király O, Griffiths MD, Demetrovics Z. Internet gaming disorder and the DSM-5: Conceptualization, debates, and controversies. Curr Addict Rep 2015;2:254-62.
Alimoradi Z, Lin CY, Broström A, Bülow PH, Bajalan Z, Griffiths MD, et al.
Internet addiction and sleep problems: A systematic review and meta-analysis. Sleep Med Rev 2019;47:51-61.
Chen CY, Chen IH, Hou WL, Potenza MN, O'Brien KS, Lin CY, et al.
The relationship between children's problematic internet-related behaviors and psychological distress during the onset of the COVID-19 pandemic: A longitudinal study. J Addict Med 2022;16:e73-80.
Chen IH, Chen CY, Pakpour AH, Griffiths MD, Lin CY. Internet-related behaviors and psychological distress among schoolchildren during COVID-19 school suspension. J Am Acad Child Adolesc Psychiatry 2020;59:1099-102.e1.
Lim JA, Lee JY, Jung HY, Sohn BK, Choi SW, Kim YJ, et al.
Changes of quality of life and cognitive function in individuals with internet gaming disorder: A 6-month follow-up. Medicine (Baltimore) 2016;95:e5695.
King DL, Delfabbro PH, Griffiths MD, Gradisar M. Assessing clinical trials of internet addiction treatment: A systematic review and CONSORT evaluation. Clin Psychol Rev 2011;31:1110-6.
Kuss DJ, Griffiths MD. Internet gaming addiction: A systematic review of empirical research. Int J Ment Health Addict 2016;10:278-96.
Pies R. Should DSM-V designate “internet addiction” a mental disorder? Psychiatry (Edgmont) 2009;6:31-7.
Porter G, Starcevic V, Berle D, Fenech P. Recognizing problem video game use. Aust N Z J Psychiatry 2010;44:120-8.
Delfabbro P, King D. On finding the C in CBT: The challenges of applying gambling-related cognitive approaches to video-gaming. J Gambl Stud 2015;31:315-29.
King DL, Delfabbro PH. The cognitive psychology of internet gaming disorder. Clin Psychol Rev 2014;34:298-308.
Griffiths MD. Amusement machine playing in childhood and adolescence: A comparative analysis of video games and fruit machines. J Adolesc 1991;14:53-73.
Pontes HM, Griffiths MD. Internet gaming disorder and its associated cognitions and cognitive-related impairments: A systematic review using PRISMA guidelines. Rev Argent Cienc Comport 2015;7:102-18.
Haagsma MC, Caplan SE, Peters O, Pieterse ME. A cognitive-behavioral model of problematic online gaming in adolescents aged 12–22 years. Comput Human Behav 2013;29:202-9.
Snodgrass JG, Lacy MG, Dengah HJ, Eisenhauer S, Batchelder G, Cookson RJ. A vacation from your mind: Problematic online gaming is a stress response. Comput Human Behav 2014;38:248-60.
Zanetta Dauriat F, Zermatten A, Billieux J, Thorens G, Bondolfi G, Zullino D, et al.
Motivations to play specifically predict excessive involvement in massively multiplayer online role-playing games: Evidence from an online survey. Eur Addict Res 2011;17:185-9.
Hilgard J, Engelhardt CR, Bartholow BD. Individual differences in motives, preferences, and pathology in video games: The gaming attitudes, motives, and experiences scales (GAMES). Front Psychol 2013;4:608.
Li D, Liau A, Khoo A. Examining the influence of actual-ideal self-discrepancies, depression, and escapism, on pathological gaming among massively multiplayer online adolescent gamers. Cyberpsychol Behav Soc Netw 2011;14:535-9.
Yee N. Motivations for play in online games. Cyberpsychol Behav 2006;9:772-5.
Wan CS, Chiou WB. The motivations of adolescents who are addicted to online games: A cognitive perspective. Adolescence 2007;42:179-97.
King DL, Delfabbro PH. Is preoccupation an oversimplification? A call to examine cognitive factors underlying internet gaming disorder. Addiction 2014;109:1566-7.
Davis RA. A cognitive-behavioral model of pathological Internet use. Comput Human Behav 2001;17:187-95.
Young KS, Brand M. Merging theoretical models and therapy approaches in the context of internet gaming disorder: A personal perspective. Front Psychol 2017;8:1853.
Festinger L. A Theory of Cognitive Dissonance. Stanford University Press; California. 1962.
Chiou WB, Wan CS. Using cognitive dissonance to induce adolescents' escaping from the claw of online gaming: The roles of personal responsibility and justification of cost. Cyberpsychol Behav 2007;10:663-70.
Forrest CJ, King DL, Delfabbro PH. The measurement of maladaptive cognitions underlying problematic video-game playing among adults. Comput Human Behav 2016;55:399-405.
Beck AT. Thinking and depression. II. Theory and therapy. Arch Gen Psychiatry 1964;10:561-71.
Dong G, Potenza MN. A cognitive-behavioral model of internet gaming disorder: Theoretical underpinnings and clinical implications. J Psychiatr Res 2014;58:7-11.
Caplan SE. Theory and measurement of generalized problematic internet use: A two-step approach. Comput Human Behav 2010;26:1089-97.
Ali AM, Al-Amer R, Atout M, Ali TS, Mansour AM, Khatatbeh H, et al.
The nine-item internet gaming disorder scale (IGDS9-SF): Its psychometric properties among Sri Lankan students and measurement invariance across Sri Lanka, Turkey, Australia, and the USA. Healthcare (Basel) 2022;10:490.
Stavropoulos V, Beard C, Griffiths MD, Buleigh T, Gomez R, Pontes HM. Measurement invariance of the internet gaming disorder scale-short-form (IGDS9-SF) between Australia, the USA, and the UK. Int J Ment Health Addict 2018;16:377-92.
Poon LY, Tsang HW, Chan TY, Man SW, Ng LY, Wong YL, et al.
Psychometric properties of the internet gaming disorder scale-short-form (IGDS9-SF): Systematic review. J Med Internet Res 2021;23:e26821.
Chen IH, Ahorsu DK, Pakpour AH, Griffiths MD, Lin CY, Chen CY. Psychometric properties of three simplified Chinese online-related addictive behavior instruments among mainland Chinese primary school students. Front Psychiatry 2020;11:875.
Tung SE, Gan WY, Chen JS, Kamolthip R, Pramukti I, Nadhiroh SR, et al.
Internet-related instruments (Bergen social media addiction scale, smartphone application-based addiction scale, internet gaming disorder scale-short form, and nomophobia questionnaire) and their associations with distress among Malaysian university students. Healthcare (Basel) 2022;10:1448.
Cakiroglu S, Gormez V. Adaptation of internet gaming cognition scale to Turkish: Reliability and validity study. Psychiatry Clin Psychopharmacol 2020;30:159-64.
Christie B. Doctors revise declaration of Helsinki. BMJ 2000;321:913.
Darvesh N, Radhakrishnan A, Lachance CC, Nincic V, Sharpe JP, Ghassemi M, et al.
Exploring the prevalence of gaming disorder and Internet gaming disorder: A rapid scoping review. Syst Rev 2020;9:68.
Gentile DA, Choo H, Liau A, Sim T, Li D, Fung D, et al.
Pathological video game use among youths: A two-year longitudinal study. Pediatrics 2011;127:e319-29.
Jacobson NS, Truax P. Clinical significance: A statistical approach to defining meaningful change in psychotherapy research. J Consult Clin Psychol 1991;59:12-9.
Griffiths MD. The role of cognitive bias and skill in fruit machine gambling. Br J Psychol 1994;85:351-69.
Ollendick TH, Matson JL, Helsel WJ. Fears in children and adolescents: Normative data. Behav Res Ther 1985;23:465-7.
Peters ER, Joseph SA, Garety PA. Measurement of delusional ideation in the normal population: Introducing the PDI (Peters et al.
Delusions Inventory). Schizophr Bull 1999;25:553-76.
Steiger H, Goldstein C, Mongrain M, Van der Feen J. Description of eating-disordered, psychiatric, and normal women along cognitive and psychodynamic dimensions. Int J Eat Disord 1990;9:129-40.
Wright FD, Beck AT, Newman CF, Liese BS. Cognitive therapy of substance abuse: Theoretical rationale. NIDA Res Monogr 1993;137:123-46.
De Pasquale C, Dinaro C, Sciacca F. Relationship of internet gaming disorder with dissociative experience in Italian university students. Ann Gen Psychiatry 2018;17:28.
De Pasquale C, Sciacca F, Martinelli V, Chiappedi M, Dinaro C, Hichy Z. Relationship of internet gaming disorder with psychopathology and social adaptation in Italian young adults. Int J Environ Res Public Health 2020;17:8201.
Sung HT, Sigerson L, Cheng C. Social capital accumulation in location-based mobile game playing: A multiple-process approach. Cyberpsychol Behav Soc Netw 2017;20:486-93.
Kühn S, Gallinat J, Mascherek A. Effects of computer gaming on cognition, brain structure, and function: A critical reflection on existing literature. Dialogues Clin Neurosci 2019;21:319-30.
King DL, Kaptsis D, Delfabbro PH, Gradisar M. Effectiveness of brief abstinence for modifying problematic internet gaming cognitions and behaviors. J Clin Psychol 2017;73:1573-85.
Yu Y, Mo PK, Zhang J, Li J, Lau JT. Validation of the Chinese version of the revised internet gaming cognition scale among adolescents in china: Maladaptive cognitions as potential determinants of internet gaming disorder. Int J Environ Res Public Health 2019;17:290.
Ioannidis K, Hook R, Goudriaan AE, Vlies S, Fineberg NA, Grant JE, et al.
Cognitive deficits in problematic internet use: Meta-analysis of 40 studies. Br J Psychiatry 2019;215:639-46.
[Table 1], [Table 2], [Table 3]