Internet Gaming Disorder: Addiction Concentration

One of the leisure activities that individuals engage in is internet gaming. The number of persons participating in gaming activities has been on the rise. Despite the benefits obtained through internet gaming, uncontrolled use has indicated that excessive usage can result in a disorder. Despite not being classified as a psychiatric disorder by APA, the adverse effects of IGD are worrisome. In the modern society, internet gaming disorder is becoming increasingly common. Different researches have stated that males are more prone to internet gaming disorder than females. 

This study evaluated commonness of IGD among male and female university students. The DSM -5 diagnostic criteria and IGD9-SF were used to diagnose the disorder. The prevalence of IGD was found to be 10% to 15% for males and 3% to 5% in females. The study recommends further research into IGD to come up with a standard and clear diagnostic criterion. Research into the treatment methods of IGD is also necessary to help individuals already suffering from IGD. 

Internet Gaming Disorder: Addiction Concentration 

In the current times, it is hard to visualize a world without the internet. This technological innovation has taken over our lives. Hardly a day passes by without using internet services. Its use has been widespread. Some of the applications include communication, reading news, business, social interactions, and entertainment ( American Psychiatric Association, 2013) . The utilization of internet services for entertainment or leisure activities has been on the rise in the recent past. An excellent example of this utilization is online gaming. 

Internet gaming has been defined as the participation in games through online platforms. Internet games involving role playing have been found to be the most addictive since individuals tend to be too immersed in the gaming activity with the other characters involved. Internet gaming is described as advantageous to gamers by offering pleasurable moments, creates a sense of attainment and provides a socialization platform with other gamers (Ko, 2014). Several studies imply that when individuals have engaged internet games, particular pathways in the brain are stimulated in a way analogous to the effects of the consumption of certain drugs by addicts (Wang, Ren, Long and Liu, 2019). Engaging in online gameplay triggers neurological responses that induce a feeling of pleasure and reward ( American Psychiatric Association, 2013). Internet gaming is, therefore, useful for leisure and stress management. 

Excessive and out of control gaming has however been found to be addictive. Addictive gaming poses serious disbenefits to individuals (Wang et al., 2019). Persons addicted to internet gaming lose touch of the everyday life activities. Their disinterest in everyday life activities is in favor of gaming activities. IGD is also associated with health problems including hallucinations, , neck and elbow aches, excessive weight gain, and peripheral neuropathy, amongst other conditions ( Paulus, Von Gontard , and Popow, 2018). IGD has been found to contribute to low education achievement and financial problems (Paulus et al., 2018). IGD has also been found to contribute to the disturbance of sleep patterns and is associated with conditions such as insomnia (Paulus et al., 2018). In extreme cases, IGD has also been found to contribute to suicidal thoughts, and in rare scenarios, individuals have committed suicide due to internet gaming (Paulus et al., 2018). The incapacity to restrain one’s gaming patterns raised an alarm on internet gaming. Due to its addictive nature, psychologists termed excessive and uncontrolled online gaming a disorder. The disorder was christened as internet gaming disorder (IGD). 

The American Psychiatric Association in 2013 (American Psychiatric Association, 2013) cited absence of consensus on the pathological nature of IGD internet gaming disorder as the basis for not classifying it as a psychiatric disorder. The APA however incorporated online gaming disorder in part III of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) as a problem requiring deeper scholastic research prior to its classification as a psychiatric condition (Wang et al., 2019). Amongst other substance use disorders, nine-point criteria was provided to assist in diagnosis (Wang et al., 2019). The American Psychiatric Association called for comprehensive study into the problem to determine if the same patterns of excess gaming are prevalent. Consequently, several types of research have been undertaken concerning internet gaming disorder. The studies have touched on various topics such as symptoms, predisposing factors, prevalence depending on age and gender, diagnosis methods, and treatment options for the disorder. 

Research has found different factors to make individuals prone to getting online gaming disorder. Discontent in life along with a low self-esteem makes individuals withdrawn from real life activities. Such persons are likely to seek an escape route from everyday stressing activities through the use of gaming activities (Ko, 2014). Consequently, such individuals are susceptible to developing IGD. Dissatisfaction in life together with a broken self-esteem is common in children and adolescents, thus explaining why this group of persons are amongst those highly addicted to internet gaming. Different researches have focused on the different factors that make individuals vulnerable to develop unrestrained gaming habits. Persons who exhibit high impulsiveness have been found to be predisposed to online gaming disorder (Ko, 2014). Internet gaming acts as an escape route from stressing scenarios by offering relief and distraction. 

Internet gaming disorder presents itself through various symptoms. Disinterest in everyday life bustles and hobbies that previously made an individual happy is document as one of the indicators of IGD ( González-Bueso, et al., 2018) . Tolerance of long computer hours of gaming and becoming angry due to computer inaccessibility are also indicators of IGD ( González-Bueso et al., 2018). Becoming quarrelsome and dishonest has also be found to be indicative of IGD. King et al. (20113) described the symptoms of IGD to comprise of withdrawal, conflict and disinterest. The American Psychiatrists Association uses DSM-5 diagnosis criteria, which proposes nine symptoms. The symptoms comprise of preoccupation with gaming activities, gaming withdrawal effects, tolerance of extended gaming times, failure to restrain gaming, disinterest in other life undertakings, unrestrained gaming regardless of its detriments, deceit on durations spent gaming, utilization of gaming as an escape from distress and functional impairment in education, career, and relationships. 

Online gaming disorder is often attributed to males (Wang et. al, 2019). Incidences of IGD are more common in males than in females. The commonness ratio of online gaming disorder between males to females has been estimated at 3:1 (Wang et al., 2019). IGD is also common among children and adolescents. According to Hussain, Griffiths, and Baguley (2012), adolescents were engaged in gaming activities more frequently in a week than adults. Adults, on the other hand, played for long durations in a one gaming session. However, IGD is also prevalent among the aging persons too. The Entertainment Software Association estimates the mean age of online gamers to be 30 years (Chen, Oliffe and Kelly , 2018). According to Northrup and Shumway (2014), 68 percent of persons engaged in gaming activities are individuals older than 18 years. A study in China found out that 60.6 percent of persons using the internet were involved in internet games (China Internet Network Information Center, 2018). In China, the prevalence of gaming disorders has been estimated at 3.5%-17% (Wang et al., 2019). In the US, IGD prevalence is approximated at 0.3%-1.0%, while in Germany, the prevalence is at 1.16 percent (Wang et al., 2019). As evident from the different studies, IGD is not only prevalent in males but females too. 

The prevalence of IGD among children and teenagers has also been found to be quite high. The immaturity of children’s cognitive control is said to contribute to high prevalence rates of IGD in children ( Sugaya, Shirasaka, Takahashi and Kanda , 2019) . The presence of internet gaming disorder in children affects sleeping patterns, academic performance, and the quality of parent-child relationships. Sugaya et al. (2019), in a review study on the prevalence of IGD, indicated that most of studies using DSM-5 IGD diagnosis criteria had recorded IGD prevalence of between 1.2 to 5.9 percent amongst the teenagers. Also, more boys had IGD than girls. Studies carried out using the Young's Internet Assessment Test diagnostic questionnaire (YDQ) showed that the commonness of problematic game use in adolescents was at 3.6 percent. Another review of the prevalence of IGD in adolescents was carried out by Fam (2018). In the review, the prevalence of IGD is recorded at 4.6 percent. The prevalence was higher for male adolescents at 6.8 percent than female participants at 1.3 percent. The study also found out the prevalence rates were higher for studies carried out in Asian countries. 

Different studies have indicated the commonness of online gaming disorder to be greater in males than in females. The percentage of males engaged in gaming is also higher than that of females. Adolescent males utilize about of 1- 1.5 hours each day or about 13 hours per week engaged in gaming activities (Chen et al., 2018). Adult males, on the other hand, spend an average of 4.68 hours each day or 27.76 hours each week (Chen et al., 2018). Chen et al. (2018) cite the design of games by males and for males as the reason for the higher gaming rates in males. Consequently, more males are prone to internet gaming disorder. Lee and Kim (2017), in a study conducted in 5 Korean cities among students, found out that internet game addicts were 3 times more in males than in females. Li and wang (2013), in a study among Chinese teenagers, found similar results. The prevalence of gaming disorder has been estimated to be between 0.7 to 27.5 percent, and the phenomenon is mostly in young men. De Pasquale, Dinaro and Sciacca (2018) , in a study conducted in an Italian university among the students, found out the commonness of internet gaming disorder in males was at 35.5 percent while in females, the prevalence was 1.6 percent. Paulus et al. (2018), in a study review indicated the commonness of IGD in males might be as high as five times more than in females. A US research recorded the commonness of IGD among males to be 11.9 percent, while in females, the prevalence was 2.9 percent (Paulus et al., 2018). Thus, from several studies, it is right to state, males are more vulnerable to acquire online gaming disorder than females. 

According to Wang, Zheng, Yuan, Du and Dong (2019), females are more vulnerable to the adverse effects of internet gaming disorder. Wang et al. (2019) carried out the study on 62 internet gaming disorder subjects 29 males and 33 females using structural magnetic resonance imaging. The reasons cited for the difference in the vulnerabilities is the difference in brain cortical thickness and negative correlations of addiction severities. Females had thinner cortical thicknesses than males and thus were more prone to effects of internet gaming disorder. 

Besides, the DSM-5 diagnostic procedure for online gaming disorder, other instruments are used in the diagnosis of internet gaming disorder. World Health Organization in 2018 grouped IGD together with substance and behavioral dependency. The 11 th edition of International Classification of Diseases and Related Health Problems (ICD-11), provided the diagnostic procedure for gaming disorder comprising of three criteria (Montag et al., 2019) . The criteria involve uncontrollable gaming obsession for more than 12 months, reduced involvement in other daily activities in favor of gaming, and escalation of gaming behavior despite its detriments. Young’s Internet Addiction Test has previously been severally utilized in different researches to assess the presence of gaming problems ( Király, Griffiths and Demetrovics , 2015) . Other assessment tools that have been used in previous studies are, Problematic Internet Gaming Questionnaire,  and the Problematic Internet Gaming Questionnaire Short Form ( Király et al., 2015). 

Different researches have analyzed some of the treatment methods that are being used in online gaming disorder treatment. Wang et al. (2019) and Chen et al. (2018) note of absence of any specific recognized treatment measures for internet gaming. The absence is attributed to the unclarity of the pathogenesis of gaming disorder. The treatment measures already in use have been premised on the treatment of psychiatric disorders for example drug use disorder (Wang et al., 2019). The treatment measures involve a drug, psychobehavioural, and comprehensive treatment. Phycological treatment involving personal and team therapy is the mostly adopted procedure in internet gaming problem treatment. 

Phycological treatment involves different methods such as personal treatment, group therapy, family therapy, and school-dependent group therapy. Individual treatment focus on cognitive -behavioral therapy (CBT) to improve one's cognitions concerning a game. Group therapies involve groups of 6 to 10 people and use lectures and discussions. Group therapies are considered useful in helping reduce the dependence on gaming and helping increase human interactions (Wang et al., 2019). The family treatment utilizes the family structure in marriage and uses counseling and peer support groups. Psychiatrists have mainly advocated pharmacological therapies. They utilize drugs, especially antidepressants, to help reduce the game addiction symptoms (Wang et al., 2019). Comprehensive treatments use a combination of different methods to treat gaming disorders. Mostly it integrates other treatment methods into the cognitive -behavioral therapy (Chen et al., 2018). Examples of combinations that have been used are CBT combined with drug treatment and CBT, combined with motivation enhancement therapy (Wang et al., 2019). No single method is exclusively effective in internet gaming disorder treatment. There is a need for clinical research into the treatment methods to come up with an effective method that can be utilized in online gaming disorder. 

This research is intended to assess the commonness of IGD amongst the student population in Southern New Hampshire University. The hypothesis for the research is that the IGD is more common in male students than in female students. 

Methods 

The study was carried out within Southern New Hampshire University. The study involved students from the different departments within the university. The selection criterion was random, and no preference was given to any department. Students from the school of education, business, arts, and sciences were involved. It involved male and female students who on their volition presented themselves as subjects for the study. Consent to carry out the study was obtained from the concerned authorities within the university. After permission to carry out the study was granted, students were sensitized on the aim of the study. The existent students’ social media platforms within the campus were used to carry out sensitization and recruitment. Students presented themselves in the two categories for the study, active gamers and those who rarely participated in gaming. Students who agreed to present themselves as subjects of the study were debriefed of the information the survey would gather to ensure the final decision to take part in the survey was consensual and not coerced by any means. Participants were also informed that the study would ensure that confidentiality was maintained. The selection criteria for the study was carried out through random means. 

The study recruited 421 participants at Southern New Hampshire University. The 421 participants recruited were individuals who had reported having been actively engaged in internet gaming and thus were more likely to suffer from addiction. Male participants were 200, while female participants were 221. A 100 participants were used as a control sample for the study, 50 males, and 50. The control sample consisted of individuals who considered themselves non-gamers and those who were hardly engaged in any online gaming activities. The subjects’ age ranged from 18- 24 years. The study was carried out between September to November of 2019. 

An online web platform was prepared to be used for this study. The decision to use the online web platform to carry out the study was informed by the numerous advantages that such a platform would present towards the excellent execution of this research. An online web platform would offer convenience for the participants in the study. Using the link for the study, participants could log onto the platform from any place, including the comfort of their residences. The online platform also eliminates the face to face interface between humans. Questionnaires filled in a face to face interaction are prone to social desirability bias (Krumpal, 2013; Patten, 2016). Social desirability bias occurs when individuals feel inclined to give specific responses that are considered acceptable in society. For example, when carrying out research to determine the commonness of online gaming disorder using direct interviews, individuals will most probably be dishonest and give responses that depict them not suffering from the disorder. An online web platform, on the other hand, helps to increase the confidence level of the research, since participants are likely to give more honest answers. Their confidentiality is guaranteed through the online platform since they feel no eyes prowling the kind of responses they are providing to the questionnaires. Daily email reminders were disseminated to participants who had been recruited to take part in the study but were yet to give their responses. 

Already existent questionnaires on the diagnosis of online gaming disorder were used. The APA DSM-5 criteria and IGD9-SF questionnaires were used. An additional questionnaire was tailored for this study. The study aimed to determine the gaming patterns and the durations that they were engaged in gameplay. Upon clicking the survey link to participate in the study, participants were directed to the electronic questionnaire that collected data on the gaming patterns. However, a precondition for one to give consent to participate in the study was set. The questionnaires could only open after the participants had given their online consent. The anonymity of the participants when participating in the survey was guaranteed by blocking the IP addresses of all the participants. 

The American Psychiatric Association (2013) diagnosis criteria for IGD was one of the methods used in this study. The APA symptom checklist was administered in the form of a questions in which the subjects could either give a "yes/no" response. The checklist contains nine criteria useful in internet gaming disorder diagnosis through self-reporting. The checklist is used in line with the DSM-5 Manual. The presence of online gaming disorder is indicated by presence of 5 or more of the nine diagnosis symptoms. Higher scores in this checklist indicate the severity of the disorder, with such individuals spending excessively long hours on the computer and loss of interest in social activities. The disruption to normal activities can also be mild or moderate, depending on the score. 

The study also used the Online Gaming Disorder – Short Form version (IGD9-SF) which was prepared in line with DSM-5 9-point criteria (Montag et al., 2019; De Pasquale et al., 2018)). The IGD9-SF is a psychometric instrument (Montag et al., 2019). This instrument was also tailored in questionnaire format and the nine questions prepared out of DSM-5 allocated responses in a Likert scale comprising 5 points: "never" is assigned a value of 1, "rarely" a value of 2, "sometimes" a value of 3, “often” a value of 4 and “very often” a value of 5. IGD9- SF was quite useful in the determination of how severe the gaming disorder was. Through the summation of the answers of a participant, the severity of the gaming disorder was obtained. The severity score ranges from 9 to 45. Higher summations show greater extremity of gaming problem. Only participants scoring from 36 to 45 according to this instrument were categorized as having internet gaming disorder. Participants with a score of 9 to 35 were classified as not having the disorder. 

Details such as one's sex, time spent gaming, games played, and the reasons for engaging in internet gaming were collected. Participants were required to fill out all the questions on a page before proceeding to the next page. For items that the participants did not wish to respond to, the option of “Do not want to answer” was included. It was, however, compulsory that the participants fill out the information about their age, gender, and the time spent gaming. All the questionnaires having such responses were categorized as having missing data. Participants were questioned whether they had, at any point sought help for mental health treatment. The response to this question was left open, and participants could give the yes, no, or do not want to answer response. Other items that were also open included whether the participant spent adequate time with other persons, what are the reasons that make them engage in internet gaming, whether they felt lonely and whether they long for more human interaction. These questions sought to identify whether the participants were isolated. 

The data collected during the study was analyzed using the SPSS software version 24. The statistical association between the various data parameters was carried out. This included the correlation of gaming disorder with sex and the correlation of online gaming problem with sex. Descriptive statistics, namely mean and standard variation, were also used in data analysis. The answers of the DSM-5 Manual questionnaire were analyzed, and the means and the standard deviation calculated. 

Results 

91.4 percent of the participants representing 385 participants out of the 421 participants filled out the questionnaires completely. The percentage represented high response rates for the participants. The filled-out questionnaires were the ones used for the analysis. The rest of the responses were categorized as missing data and disregarded. The median age of the subjects in the study was 20 years. 

Out of the 385 filled out questionnaires, 200 questionnaires were filled out by female participants, while 185 males filled out the questionnaires completely. The 200 questionnaires among the female participants represented a 90.5 percent response rate, while male participants expressed a 92.5 percent response rate. Out of the analyzed data, among the male participants, 15.1 percent of the participants (representing 28 individuals) had five or more of their DSM -5 Manual questionnaire responses, indicating that they were suffering from internet gaming disorder. Among the female participants, 5 percent (representing 10 of the participants) had five or more of their DSM-5 Manual responses, indicating that they had internet gaming disorder. there was no association between subjects’ age and commonness of IGD for the analyzed data. The commonness of IGD was quite random and uneven across the different ages of the subjects involved in study. 

The results of IGD9-SF showed that 10 % of male subjects had severe online gaming problem and were considered disordered. Three percent of the female participants had severe IGD and considered disordered. The summation of the results of the responses of these individuals was greater than 36. 

Data analysis indicated that male participants in the study spent quite a lot of time in online gaming. The mean number of hours used by males on internet gaming was between 3 to 10 hours per day. Three individuals out of the analyzed males spent as high as 12 hours per day on online gaming. One individual indicated spending 20 hours per day on online gaming. The response was considered an outlier since it is highly impractical to utilize 20 hours each day on online gaming. The analyzed results among the females indicated that female participants spent about 3 to 5 hours per day on online gaming. Two female participants responded, having utilized about 7 hours each day on online gaming. 

An analysis of level of isolation among the participants was also undertaken. 25.4 percent of the male participants (representing 47 persons) indicated feeling lonely and longed for longer periods of human interaction. Fifty percent of the female participants (representing 100 persons) responded that they felt lonely and longed for more hours of social interactions. 

An analysis of the reasons that participants engaged in internet gaming indicated varied responses among males and females. 65.4 percent of the male participants (representing 121 persons) cited the search for a sense of achievement as the main reason that they engaged in internet gaming. On the other hand, 49 percent of the female participants indicated that they participated in online gaming in search of social interactions with other players. The other reasons for participation in internet gaming included escaping from stressful situations in life, boredom, and peer influence. These responses were, however, quite a few and random among the participants and accounted for the remaining percentages as to why individuals engaged in internet gaming. 

Responses pertaining to whether the participants had ever sought treatment for mental disorders were analyzed. The results showed that 5 percent of the female subjects had sought help for psychiatric disorders. The percentage of male participants who had looked for help for psychiatric health disorders was 2 percent. In one of the questions, the participants were asked whether they would be willing to seek help for treatment if they were diagnosed with internet gaming disorder. 90 (180 persons) percent of the female participants expressed that they would seek treatment compared to 70.3 (130 persons) percent of the male participants. For those not willing to seek help, reasons were asked as to why they would not seek treatment. The responses from such participants indicated that they did not recognize internet gaming as a disorder. To them, online gaming was quite beneficial, even when done for long hours. 

Discussion 

Results obtained validated the hypothesis of the research that online gaming disorder is quite common among male student population than in female student population. The DSM-5 diagnostic criteria expressed an IGD prevalence of 15 % and 3.0 % for males and females, respectively. The IGD9- SF indicated an IGD prevalence of 10 % and 3 % for males and females, respectively. The results of the study are no different from other results provided by previous studies on the commonness of IGD. The commonness of IGD in the US population as documented by a previous study puts the prevalence at 11.9 % for males and 2.9 % for females (Papulus et al., 2018). Other studies have also found the commonness of IGD to be greater in males than in females (Ko, 2014; Chen et al., 2018; Lee and Kim, 2017; Li and Wang, 2013; De Pasquale et al., 2018). 

The study found out that male participants spent more hours on internet gaming than female participants. Males utilized about 3 to 10 hours each day, while females spent about 3 to 5 hours each day on internet gaming. Chen et al. (2018) also expressed the high number of gaming hours in males. Other differences between males and females in internet gaming included the reasons for engaging in internet gaming and whether individuals would seek help. The differences in internet gaming addiction between the male and female are no different than what has been observed by other studies. Various reasons are cited as to why more males are prone to internet gaming addiction. Su, Han, Jin, Yan and Potenza (2019), in an analysis of internet addictions, states that there exists preferential use for internet applications, with males being more into gaming and pornography while females are more into social networking and shopping. 

No association between the age of the participants and the commonness of IGD was found out in this study. The absence of this correlation can be associated to the narrow age difference in the age of the participants. The use of a narrow age difference can be considered a shortcoming in this study. Other limitations in this study include the use of different scales in the diagnosis of IGD. Suggestions have been made for the development of a standard diagnostic scale for IGD (Wang et al., 2019; Montag et al., 2019). Another limitation was the failure to include cross-cultural considerations in formulating the study. Petry and O’Brien (2013) suggest the integration of cross-cultural factors such as gendered practices and cultural beliefs when determining the reasons and prevalence of IGD. The dependence on individual self-reports can also be considered as a limitation. Przybylski (2016) suggests that convergent information from different respondents, such as parents, friends, and romantic partners, can help improve the confidence level of data collected in IGD studies. 

Conclusion 

Online gaming disorder is a common problem in the modern society. The prevalence of the disorder amongst males is higher than females presenting a new health issue for men. Even if it has not yet been classified as a psychiatric disorder by the APA, its effects are disturbing such as the incidences of suicide. There is need for in depth research into this condition with the aim of obtaining standardized preventive and treatment methods. 

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