|Year : 2018 | Volume
| Issue : 3 | Page : 208-212
Video game use among schoolchildren and its impact on the study habits
Janardhana Navaneetham1, Juna Chandran2
1 Department of Psychiatric Social Work, NIMHANS, Bengaluru, Karnataka, India
2 Department of Social Work, Amrita School of Social Work, Cochin, Kerala, India
|Date of Web Publication||27-Sep-2018|
Dr. Janardhana Navaneetham
Department of Psychiatric Social Work, NIMHANS, Bengaluru, Karnataka
Source of Support: None, Conflict of Interest: None
Background: Children usually play video games for entertainment, excitement, challenge seeking, emotional coping, and escaping from reality to virtuality to fulfill their unsatisfied needs or motivations. Video game is a ‘medium’ through which young children can make sense of, and feel at home in the present modern generation where in parents are too busy with their own career choices. Methods: The present study aims at understanding prevalence and how it impacts on the academics among the school children and to understand about mental health problems among the pathological user. The present study likes to explore the addiction of video and internet games among students and establish fact about its effects. Students were selected from two schools with state syllabus. Video game addiction scale and study checklist was used for the present study. 200 students in the classes of 8th and 9thgrades and those who can read and write English were invited to participate in the survey. Results: Almost half of the children reported that they did not play Video Game, 18% of students are using video game with control, 20% students are excessively using video games and 17.5% of the students fall under addiction category. The study indicated that 19% of the children were spending more than 3 hours for game. Conclusion: In conclusion, playing video and internet games is a widespread activity among young children, and a substantial proportion of their time is spent on this activity, affecting their relationship and the time spent on learning.
Keywords: Students, study habits, video game addiction, video game addiction impact, video game use
|How to cite this article:|
Navaneetham J, Chandran J. Video game use among schoolchildren and its impact on the study habits. Indian J Soc Psychiatry 2018;34:208-12
|How to cite this URL:|
Navaneetham J, Chandran J. Video game use among schoolchildren and its impact on the study habits. Indian J Soc Psychiatry [serial online] 2018 [cited 2021 Nov 30];34:208-12. Available from: https://www.indjsp.org/text.asp?2018/34/3/208/242353
| Introduction|| |
Play is an important and essential element in the life of children. Providing “time and space” for the children is not only essential for their healthy development but also the “right of every child.” Video game is a “medium” through which young children can make sense of and feel at home in the present modern generation wherein parents are too busy with their own career choices., Over the past few decades, the predominant site of children's play has moved from public space on the street, to a public space in the playgrounds, schoolyards, this indeed over last two decades has changed to indoor games, particularly in their own bedrooms where indoor play technologies such as television, video, DVDs, game consoles, and computer games have proliferated.
Video game addiction is the extreme use of computer and video games that interfere with the daily life of the children. Children usually play video games for entertainment, excitement, challenge seeking, emotional coping, and escaping from reality to virtuality to fulfill their unsatisfied needs or motivations. Parents report that their children do spend excessive amount of time in playing video games and on internet affecting their study time and habits, sometimes they need to play compulsively while eating, and it isolates them from the family, friends, and from social contacts. The children almost entirely focus on game achievements rather than other life events such as their educational attainment and exhibit lack of imagination and mood swings when they are stopped or restricted from doing the activity.,, There is no formal diagnosis of video game addiction in the current medical or psychological literature; however, recent studies related to addiction medicine do report about the behavior addictions among children, adolescents, and young adults.,
Many studies have examined the prevalence of video gaming addiction,,, which varies across countries and culture. Studies have shown a prevalence of 8.7% among Singaporean youth; 9.9% among Spanish adolescents; American youth aged 8–18 years indicated a prevalence of 8.0%; adolescents prevalence rate 1.7% for Germany; and 3.3% prevalence among adolescents and young adults in the Netherlands. These inconsistent findings may be explained by several factors, especially sociocultural and criteria differences.
The primary motivation for playing video games is for coping with the daily stressors., Escapism appeared to be the most important factor predicting internet gaming addiction and pathological gaming, followed by perceived parent hostility, real-ideal self-discrepancy, and lack of parental supervision and actually ideal self-discrepancy and depression. Pathological gamers more likely to have video game systems in their bedrooms, reported having more trouble paying attention at school, receive poorer grades in school, have more health problems, and were more likely to feel “addicted.” Studies have found that while the physical manifestations are minimal or difficult to identify, the psychological and social impact can be significant.
Given the increasing prevalence in children and its influence on their development, need for good understanding of video gaming use is necessitated for the mental health professionals to develop a prevention programs for promoting their coping and thereby mental health of the children. Thus, the first objective of this study was to examine the sociodemographic profiles and the pattern of video gaming behaviors in schoolgoing children. The second objective was to estimate the prevalence of video game addiction and its impact on the study habits of the children.
| Methodology|| |
The present study aims at understanding prevalence and how it relates to the study habits among the school children and to understand about mental health problems among the pathological user. High schools in the city of South Calicut were considered as the universe for the study. Calicut city has 88 aided and nonaided schools. Students were selected from two aided nonboarding schools following state syllabus, selected conveniently for the research. The schools were following English medium of instruction. All students in the classes of 8th (n = 110) and 9th grades (n = 100) of these school were selected for the study. Those who can read and write English were invited to participate in the survey. Each student completed an anonymous questionnaire, which explores information about personal details, family details, leisure time activities, study habits, and video game use. Ethical approval was obtained from the Department of Psychiatric Social Work, NIMHANS. Letter of permission for conducting the study was sent to both the schools. Parents were informed about the study and its implication and the consent form was sent to their home. The headmasters of the schools received the consent from the parents. In the first session, researcher interacted with the students in the classroom; after building rapport, they were explained about the purpose and outcome of the study and obtained their assent for participation in the research. With the support of teachers, students were divided into small groups and given questionnaire for filling. Out of 210 questionnaires returned, 10 were incomplete. Therefore, 200 questionnaires were utilized for the analysis.
Video game addiction Scale, it has ten questions to assess the duration of engagement with the video game play, frequency of video game use, leisure time activities, nature and attitude toward video game which were assessed on four-point scale. Response A – gets a score of 2, response B – gets a score of 5, response C – gets a score of 10, and response D – gets a score of 0. To establish cultural sensitivity, face validation was done by the faculty of the departments of child and adolescent psychiatry, nursing, clinical psychology, and psychiatric social work. The scores on the scale indicate 0–19 as nonusers, score of 20–39 as user with control, score of 40–69 shows that students are spending excessive time with video game, and score of 70–100 indicates that they are dependent.
Study habits checklist which has been adopted from the “Student Enrichment Programme” My Work Book. This checklist used to assess the study habits among the students. The checklist consists of 20 items, each followed by two responses, yes and no. In the current study, the “yes” response was coded as 1 and “no” was coded as 0. The checklist was divided into seven domains based on the similar themes. They are time management (2 items), note-taking items, reading and home assignment (4 items), memory (2 items), group study (5 items), classroom activities (3 items), and leisure time activities (2 items). Lower score indicates more problems with the study habits.
Descriptive analyses were used to describe the students' social and demographic information, gaming behaviors, and the prevalence of probable gaming addiction as measured by the video game addiction scale.
| Results|| |
The age of the respondents varies from 13 years to 16 years [Table 1]. About 57% of the adolescents are 13 years old, 38.5% of the children are 14 years old, 4% of them are 15 years old, and 0.5% was 16 years old. Nearly, one-fifth, 21% respondents were single child and 79% of them had either elder or younger sibling in their family. Birth order of the respondents shows that majorities (47%) of the respondents were first born, 11% were middle born, and 29% were last child.
As per the child report, 52% of their family had an income of Rs 10,000 and 48% of the family were in the income group of 10,001–30,000. Majority (86%) of the respondents hail from the nuclear family, whereas 12% of the respondents belong to joint families. Remaining 2% of them had single-parent families. Majority (88%) of respondents' family size was <5 members and 12% of the respondents' family size was between 5 and 12 family members.
Nearly one half (46.5%) of the fathers belonged to the age group of 35–45, 46% of the fathers belonged to the age category of 46–55. Only 2% of the respondents' fathers are educated up to primary school, 36.5% of the fathers are educated up to 10th standard, 27% of them hold Preuniversity College, and 29.5% of them have completed degree, and 10% of them have studied up to postgraduation and professional course. About 25% of the fathers were government employees and another 7% of them were working in private firms, only 5% of them were agriculturalist, 19.5% of the fathers were daily wage earner, and 42.5% fathers had their own business.
Less than 4% of the mothers belonged to the age group of <30, majority of the mothers (80%) belonged to the age category of (35–40). About 14.5% mothers are in the age category of (45–50), 1.5% of the respondent's mothers were in the age group of 56- 60 years. 39.5% of the mothers have attended college education; 53% of the mothers had secondary and higher secondary education. Majority (65.5%) of the mothers were homemakers; 6.5% and 5.5% of the mothers were in government and private jobs, respectively, others were involved in agricultural and daily wages-related activities.
[Table 2] indicates that 44.5% of the students are not using video games, 18% of the students are using video games for entertainment (mild category), and 20% of the students are excessively playing video games. About 17.5% of the students fall under addiction (video game addiction) category.
Around 19.5% and 23.5% of the students reported they were frequently and very frequently involved in downloading video games, respectively. [Table 3] provides details about the downloading and the time spent in playing video games. Majority of the (52.5%) students are not downloading video games from any sites or buying games, whereas 4.5% of the students are occasionally download games from the internet. The results on the time spent for video game indicate that 19% children were playing video games >3 h; followed by 31% of the students are playing 1–2 h; 23.5% students playing for 30 min regularly.
|Table 3: Number (percentage) of the study participants downloading and playing video games (n=200)|
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The F value of 23.355 (P <0.001) reveals significant difference between different type of video game users on their study habits [Table 4]. The scores on study habit checklist differ between different levels of video game use. Students using video games excessively had a mean score of 11.15, children dependent on video games had a means score of 9.14. Whereas children using video game with control had a means score of 14.81 and non users had a mean score of 15.19. The mean scores of students in excessive use and addicted use were lower compared to other two groups. This indicates that they had more problems related to study habits. The t-test reveals that there is no difference in the study habits between boys and girls (t-test 0.617 and P = 0.197) and also between the age group of 13 years and <13 years and children who are 14 years and >14 years (t value of 0.267 and P = 0.790).
| Discussion|| |
The present study is probably one of the studies which examined the pattern of video gaming use among 8th and 9th standard studying in the state syllabus of Calicut city. Almost half of the children reported that they did not play video game (44.5%), 18% of students are using video game with control (mild category), and 20% students are excessively using video games. About 17.5% of the students fall under addiction (video game addiction) category. For many families, playing video games appeared to be a harmless leisure activity and feel that the attention and the academic intelligence will improve using video games. In the study conducted by Hauge to understand the problems of video game addiction among 8th- and 9th-grade students, they also found that 18% of children mostly boys (80%) were classified as addicted to video games. In the study conducted by Gentle (2009) published first national American study on pathological video game addiction have found the prevalence of video game usage in Asia and Europe, and concluded that the US and Asia students were showing that around 20%–25% of gamers seem to be having real problems to the point that they were considered pathological gamers, Gentile who published the first national American study on pathological video game addiction among youths. In the study conducted in Singapore found that 22% of the students said they become restless or irritable when they attempt to reduce their play. The other problematic symptoms were endorsed by far fewer young gamers, with the least likely symptom being stealing video games or money to buy games.
The present study indicated that 19% of the children were spending >3 h for games, most of their productive time. In the study conducted by Turner et al. found that most of the students (85%) reported of playing video games in the past year and 18.3% reported playing video games daily. The study conducted by Gentile shows that 10% to be pathological players according to the standards established for pathological gambling, leading damages in the spheres of family, social, and school. Another study done on the problems of addiction among 8th- and 9th-grade students found that 18% were classified as addicted. Majority of the addicted students, approximately 80% were male. Less than 30% of nonaddicted student reported having been in a fight in the past year, while almost 50% of addicted students reported the same.
The present study has found that girls and boys had similar study habits. Many studies like Panda found that boys had significantly better study habits than girls. Researches also have found that boys were poorer in study habits than girls. Higbee and Manalo found few relationships of memory skills with gender, grades, or year in a school. Hence, it may be derived that rather than gender having a direct impact on study skills and academic performance, it is the perception and attitude toward academic tasks and goal importance which becomes the causal agent in directing all elements necessary to achieve high levels of study behavior given the theoretical framework of planned behavior.
Our research has some limitations. First, the focus of the present study was on video and internet gaming in general rather than internet gaming in particular. A focus on video gaming, in general, makes our results comparable to the reports of previous studies. Second, the present study was not based on structured psychiatric interview and diagnostic criteria for internet gaming disorder. Third, the standardized scales with good psychometric properties would have been used. Fourth, as the data were not skewed, some of the parametric tests such as post hoc test, goodness of fit test, Scheffe multiple range test was not conducted, is one of the limitations of the study. Fifth, cross-sectional studies have some limitation of not having data to understand the time spent on video games previously, how it got affected their outdoor games over a period of time. Thus long-term studies would help us to know the trend of video game use over the years, which would give more information to arrive at generalizations of time spent on video games over years and its impact on time spent for outdoor games. Sixthly results cannot be generalized to other population as the study is cross-sectional done in one center.
| Conclusion|| |
Playing video and internet games is a widespread activity among young children, and a substantial proportion of their learning time is spent on this activity, affecting their learning and also affecting their relationship not only in the family but also in their schools. There is a need for paying special attention for those children who are particularly vulnerable to video and internet gaming addiction. The prevalence identified in the present study may demand the need for professional interventions for the children in the form of preventive and promotive mental health activities at the school level and family interventions in the form of quality time, disciplining and enhancing and empowering families to deal with the problems. Further research is needed to understand the underlying mechanisms of video and internet gaming addiction and to explore effective preventative or interventional strategies for these children.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Juul J. Half-real: Video games between real rules and fictional worlds. Cambridge: Massachusetts Institute of Technology Press; 2011.
Sutton-Smith B. The ambiguity of play. Cambridge: Harvard University Press; 2009.
Buckingham D. The Making of Citizens: Young People, News, and Politics. US: Taylor & Francis; 2000.
Hauge MR, Gentile DA. Video Game Addiction Among Adolescents: Associations with Academic Performance and Aggression. Paper Presented at Society for Research in Child Development Conference, Tampa; April, 2003.
Wan CS, Chiou WB. Why are adolescents addicted to online gaming? An interview study in Taiwan. Cyberpsychol Behav 2006;9:762-6.
Willoughby T. A short-term longitudinal study of internet and computer game use by adolescent boys and girls: Prevalence, frequency of use, and psychosocial predictors. Dev Psychol 2008;44:195-204.
O'Keeffe GS, Clarke-Pearson K; Council on Communications and Media. The impact of social media on children, adolescents, and families. Pediatrics 2011;127:800-4.
Shek DT, Yu L. Internet addiction in Hong Kong adolescents: Profiles and psychosocial correlates. Int J Disabil Human Dev 2012;11:133-42.
Lo SK, Wang CC, Fang W. Physical interpersonal relationships and social anxiety among online game players. Cyberpsychol Behav 2005;8:15-20.
Yu L, Shek DT. Internet addiction in Hong Kong adolescents: A three-year longitudinal study. J Pediatr Adolesc Gynecol 2013;26:S10-7.
Petry NM, O'Brien CP. Internet gaming disorder and the DSM-5. Addiction 2013;108:1186-7.
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.
Choo H, Gentile DA, Sim T, Li D, Khoo A, Liau AK, et al.
Pathological video-gaming among Singaporean youth. Ann Acad Med Singapore 2010;39:822-9.
Tejeiro Salguero RA, Morán RM. Measuring problem video game playing in adolescents. Addiction 2002;97:1601-6.
Gentile D. Pathological video-game use among youth ages 8 to 18: A national study. Psychol Sci 2009;20:594-602.
Haagsma MC, Pieterse ME, Peters O. The prevalence of problematic video gamers in the Netherlands. Cyberpsychol Behav Soc Netw 2012;15:162-8.
Desai RA, Krishnan-Sarin S, Cavallo D, Potenza MN. Video-gaming among high school students: Health correlates, gender differences, and problematic gaming. Pediatrics 2010;126:e1414-24.
Tao R, Huang X, Wang J, Zhang H, Zhang Y, Li M, et al.
Proposed diagnostic criteria for internet addiction. Addiction 2010;105:556-64.
Grüsser SM, Thalemann R, Albrecht U, Thalemann CN. Excessive computer usage in adolescents – Results of a psychometric evaluation. Wien Klin Wochenschr 2005;117:188-95.
Batthyány D, Müller KW, Benker F, Wölfling K. Computer game playing: Clinical characteristics of dependence and abuse among adolescents. Wien Klin Wochenschr 2009;121:502-9.
Kwon JH, Chung CS, Lee J. The effects of escape from self and interpersonal relationship on the pathological use of internet games. Community Ment Health J 2011;47:113-21.
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.
Rhys M. Discover the real world. Com-video game addiction test. Discover the Real World. 2006.
Sekar K, Parthsarathy R, Arvind Raj E, Manoj K, Roncalli A, Kumar S, et al
. Student Enrichment Programme, My Work Book. Department of Psychiatric Social work, NIMHANS, Bangalore, Publication; 2010.
Tao R, Huang X, Wang J, Zhang H, Zhang Y, Li M. Proposed diagnostic criteria for internet addiction. Addiction 2010;105:556-64.
Hauge MR, Gentile DA. Video Game Addiction among Adolescents: Associations with Academic Performance and Aggression. In: Society for Research in Child Development Conference; April, 2003.
Turner NE, Paglia-Boak A, Ballon B, Cheung JT, Adlaf EM, Henderson J, et al
. Prevalence of problematic video gaming among Ontario adolescents. Int J Ment Health Addiction 2012;10:877-89.
Panda BN. Study-habits of disadvantaged and non-disadvantaged adolescents in relation to sex and academic performance. Indian Journal of Psychometry & Education 1992;23:91-6.
Grabill KM, Lasane TP, Povitsky WT, Saxe P, Munro GD, Phelps LM, et al
. Gender and study behavior: How social perception, social norm adherence, and structured academic behavior are predicted by gender. North Am J Psychol 2005;7:7-24
Higbee KL, Manalo E. What memory skills are most important to university students in the United States and New Zealand? Psychologia 2006;49:66-73.
Sideridis GD, Kaissidis-Rodafinos A. Goal importance within planned behaviour theory as ‘the’ predictor of study behaviour in college. Br J Educ Psychol 2001;71:595-618.
[Table 1], [Table 2], [Table 3], [Table 4]