|Year : 2022 | Volume
| Issue : 4 | Page : 112-116
Prevalence of Internet gaming disorder among engineering students aged 18–25 years: A cross-sectional study from Ernakulam district
Nevin J Palal, Sreelakshmi Mohandas, Minu Maria Mathew, Aravind S Raj, Aravind V Mohan, Abdul Bari, Amrithachandra K P, Aravindh Krishna R
Department of Community Medicine, Amrita School of Medicine, Amrita Institute of Medical Sciences (AIMS), Kochi, Kerala, India
|Date of Submission||21-Oct-2022|
|Date of Acceptance||30-Dec-2022|
|Date of Web Publication||20-Feb-2023|
Dr. Sreelakshmi Mohandas
Department of Community Medicine, Amrita Institute of Medical Sciences (AIMS), Ponekkara, Kochi 682041, Kerala
Source of Support: None, Conflict of Interest: None
Introduction: The number of mobile game users has increased globally over the last few years. Gaming has been reported as a new way of satisfying basic human needs within the constraints of the current modern society. This research aimed to determine the prevalence of Internet gaming disorder (IGD) among engineering students aged 18–25 years in the Ernakulam district of Kerala and the associated risk factors. Materials and Methods: This was an online-based cross-sectional study among engineering colleges in Ernakulam district of Kerala selected by simple random sampling. Students with psychiatric ailments were excluded from the study. On the basis of the prevalence of IGD, reported by Mihara and Higuchi in 2017, the minimum calculated sample size for this study using the formula, n = (4*pq)/d2 was 291. The study tool was a semi-structured questionnaire with three segments: socio-demographic profile, IGD, and Internet gaming behavior pattern. As data were collected using Google Forms, data were downloaded from Google Sheet and exported to and analyzed using SPSS software program, version 20.0. Results: The study had 271 participants and most of them were males. The mean age group of the study population was 22.77 years. The prevalence of IGD was found to be 2.2%. In the associated risk factors, people living alone were found to have a significant association with IGD. Conclusion: Although the prevalence observed in our research is low, more attention needs to be given to keeping the prevalence low, as the number of gamers in India has been constantly increasing.
Keywords: Diagnostic and Statistical Manual of Mental Disorders-5, Internet gaming disorder, mobile gaming
|How to cite this article:|
Palal NJ, Mohandas S, Mathew MM, Raj AS, Mohan AV, Bari A, K P A, Krishna R A. Prevalence of Internet gaming disorder among engineering students aged 18–25 years: A cross-sectional study from Ernakulam district. Amrita J Med 2022;18:112-6
|How to cite this URL:|
Palal NJ, Mohandas S, Mathew MM, Raj AS, Mohan AV, Bari A, K P A, Krishna R A. Prevalence of Internet gaming disorder among engineering students aged 18–25 years: A cross-sectional study from Ernakulam district. Amrita J Med [serial online] 2022 [cited 2023 Mar 24];18:112-6. Available from: https://ajmonline.org.in/text.asp?2022/18/4/112/370005
| Introduction|| |
Gaming disorder has been explained in the 11th Revision of the International Classification of Diseases (ICD-11) as a pattern of gaming behavior (“digital-gaming” or “video-gaming”) characterized by damaged control over gaming, with increasing priority given to gaming over other activities. In Internet gaming disorder (IGD), gaming takes precedence over daily activities, and there is a continuation of gaming despite the occurrence of negative consequences. The inclusion of gaming disorder in ICD-11 follows the evolution of treatment programs for people with health conditions similar to those characteristics of gaming disorder, in many parts of the world.
The worldwide prevalence of gaming disorder was 3.05% when considering only studies that met more stringent sampling criteria. The pooled prevalence rate in South-East Asia stands at 10.1% for gaming disorders.
Many terms have been used to describe IGD. A few of them are Internet gaming addiction, online gaming addiction, computer game addiction, and pathological gaming. For gaming disorder to be diagnosed, the behavior pattern must be of adequate severity to result in significant impairment in personal, family, social, educational, occupational, or other important areas of functioning and would normally have been evident for at least 12 months. IGD shares many similarities in physical and psychosocial manifestations with substance use disorder, including cerebral changes on functional magnetic resonance imaging (fMRI).
Several conceptualizations of these addictions have emerged, each with its assessment tools. These conditions include problematic Internet use (PIU), IGD, and social media addiction (SMA). These conditions have been associated with health outcomes such as problematic alcohol use, sleep disorders, and mental illness. These maladaptive technology conditions have most commonly been studied in isolation from each other.
The proposed symptoms of IGD include Preoccupation with gaming, Withdrawal symptoms when gaming is taken away or not possible (sadness, anxiety, and irritability), tolerance, the need to spend more time gaming to satisfy the urge, inability to reduce playing, unsuccessful attempts to quit gaming and continuing to game despite problems.
Among the studies that have looked for the motives behind gaming, coping, escape, socialization, and personal satisfaction were identified as important motives for gaming behavior., The escape and achievement motives have also been consistently found to be connected with problematic gaming., Within the limitations of the current modern society, gaming has been described as a new way of fulfilling basic human needs.
Currently, according to the American Pediatric Association, both genders are equally vulnerable to IGD; however, the majority of research and documented cases of IGD involve male adolescents and young adults. There are emerging concerns about the addiction liability of Internet gaming with studies consistently showing the increasing prevalence of anxiety, depression, lower positive affect, and psychological well-being among game addicts.
The prevalence of IGD can be assessed using several scales. The different gaming disorder tools include AIC-S gaming, GAS-7, Internet gaming disorder test (IGDT-0), Internet Gaming Disorder Scale Short Form (IGDS9-SF), and Lemmens IGD-9 scale. No single tool has been reported to be superior to the others. This study was undertaken in the wake of coronavirus disease-2019 (COVID-19) when the screen time of all students has increased. Hence, the objectives of this research were to estimate the prevalence of IGDs among engineering students aged 18–25 years age group in Ernakulam district Kerala and to understand their pattern of use.
| Materials and Methods|| |
Study participants and selection
An online cross-sectional survey was conducted using Google forms among engineering college students aged 18–25 years in the Ernakulam district of Kerala between September and October 2021. Students with any previous diagnosis of mental health ailments were excluded from the study. Using a simple random technique, a total of six colleges were selected from a list of 18 engineering colleges in the district. The Google form was forwarded to student representatives of the selected colleges, which was then disseminated among their peers (snowball sampling). Informed consent was taken via Google Forms.
On the basis of the prevalence of IGD as reported by Mihara and Higuchi, the minimum calculated sample size for this study was calculated using the formula, n = (4*pq)/d2, where p is the prevalence from existing literature (27.5%), q is 100-p and d is the allowable error, set at 20% of 27.5%. With 95% confidence, the minimum calculated sample size was 264.
The study tool was a semi-structured questionnaire with three segments;
- Socio-Demographic profile: Information concerning the following was collected: age in completed years, gender, marital status, college, the branch of Engineering, living arrangement, place of stay, number of siblings, maternal and paternal education, and occupation and type of family.
- Internet Gaming Disorder Scale-SF 9: The responses to the nine items were self-rated by the participants on a 5-point Likert scale as follows: 1 = “Never,” 2 = “Rarely,” 3 = “Sometimes,” 4 = “Often,” and 5 = “Very Often.” The total score was tallied by adding the scores obtained on all nine items. It ranged from 9 to 45, with higher scores indicating greater severity of IGD. The questionnaire may be used to distinguish disordered gamers and non-disordered gamers by accounting for IGD in all those participants who had marked 5 for at least five or more items on the scale. Most mathematical models suggest a cut-off point of 32 to classify IGD. The cut-off score of 32 has been used in this research to estimate the prevalence of IGD.
- Internet Gaming Behavior: Questions related to Internet Gaming Behavior were included to understand the pattern of Internet Gaming. The questions were adapted from published literature.
The data collected using Google Forms was downloaded from Google Sheets and exported to and analyzed using SPSS software version 20.0.
The prevalence of IGD has been expressed in percentage. Descriptive statistics using mean, standard deviation, median, range, frequency, and percentage were used to indicate the sample characteristics. A chi-square test of significance was done to look for the risk factors associated with IGD. The level of statistical significance was set at P < 0.05 for all the tests.
| Results|| |
A total of 270 students responded to the survey and the mean age of the study population was 20.77 + 1.51 years. Two-thirds of the study participants were of age less than 21 years and a majority (76%) of them were males. Approximately three-fourths of the study participants belonged to nuclear families while 3% of them had only a single parent. About 67% of the study population was from an urban locality and 43% from a rural neighborhood.
A majority, 67% of the study participants lived with their family and a minority (1.1%) stayed alone or with friends, while the others stayed in the hostel. Most of the mothers had a professional or postgraduate education (40%) while most fathers had graduate-level education (41%). A higher proportion of the fathers were employed in professional work (55%) while most mothers were unemployed/ housewives. A small segment of the participants were married, 2.2%.
On the basis of the cut-off value of 32, the prevalence of IGD in our study was 2.2%. The mean score observed was 15.65 + 6.65. Among the risk factors analyzed for IGD, although IGD was more prevalent among participants aged less than 21 years, among male students, unmarried participants, participants hailing from rural backgrounds and those coming from nuclear families; no statistically significant association was found. However, IGD was found to be significantly higher among participants living alone (15.398; P = 0.009).
The mean scores for the 9 questions are depicted in [Table 1]. The closer the score to 5 the higher the severity of IGD. In our research, the highest mean score was observed for component number 8 viz. “Do you play in order to temporarily escape or relieve a negative mood (e.g., helplessness, guilt, and anxiety)?” indicating that most students relied on Internet gaming to overcome negative moods which they encountered during their day.
The distribution of study participants based on Internet gaming behavior is described in [Table 2]. Approximately, 43% of the participants spent 5–10 h online per day, 16.3% spent 10–20 h and 1.5% of the participants spent more than 20 h online per day. Around 9% of the participants spent 5–10 h gaming per day, and 4.1% of participants spent 10–20 h gaming per day. A total of 13.3% of study participants had initiated gaming below 5 years of age, while 5.9% of the study participants had initiated Internet use below 5 years of age. A majority, (46.7%) of the study participants preferred multiplayer online game mode and 35.2% preferred the genre shooting and action.
|Table 2: Distribution of study respondents based on Internet gaming behavior (n = 270)|
Click here to view
| Discussion|| |
Of the 270 students who participated, the prevalence of IGD was found to be 2.2% among engineering college students. Majority of the students in our study were males and most of them were between 18 and 21 years of age. The observed prevalence of 2.2% was lower than the prevalence of IGD reported among medical students in India (3.6%) and 9.1% among engineering students in Karnataka. The lower prevalence may be because of the online data collection methods or due to volunteer-induced bias.
The mean score observed was 15.65 + 6.65 for the IGDS9-SF questionnaire. This is lower than the mean score reported among medical students in New Delhi. The only identified significant risk factor for IGD in our study was living alone on univariate analysis which is similar to the findings from New Delhi. Multiplayer online mode for gaming was the most preferred genre among students in our study and this is similar to medical students. The plausible reason for the preferred genre and living alone as a risk factor for IGD may be the need for companionship during a negative mood. This is evident from the high mean score observed for component number 8 in the IGDS9-SF, in our study.
The amount of time spent gaming per day for most of our participants was less than 5 h and this is similar to the findings reported by Khan et al. in Belgavi. Although a smaller proportion; 6%–14% of our study participants had started using the Internet and online gaming at less than 5 years of age, respectively. This is higher than the findings of Reshma. among Higher Secondary School students in Kerala. The decreasing age profile for initiation of Internet use and online gaming indicates the lack of knowledge among family members about the consequences of addiction and its forerunners.
However, our findings of IGD prevalence are in line with the evidence generated by Mihara and Higuchi in their systematic literature review. The paucity of literature with adequate external validity, differences in the study tool used coupled with differences in methodologies, especially the statistical analysis makes it difficult to compare the findings at a higher level and to devise strategies to better cope with the probable negative effects of IGDs.
| Conclusion|| |
Although the observed prevalence of IGD among engineering students in our study is lower than the findings reported from other studies in India, we are at crossroads with the advancing era of technology which has the potential to increase the prevalence in the coming years. The limitations of this research were the lack of access to colleges due to the COVID-19-induced restrictions. There are no similar research works undertaken in Kerala that could reveal the prevalence of IGD among different age groups and diverse professional groups. A multicentric interventional study with validated tools to identify the prevalence and to better educate about the ill effects of gaming addiction are of unrelenting priority.
The authors thank participants and teachers from the various engineering colleges in Ernakulam district.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2]