The Impact of Gender and Age on Game Addiction

Yuanzhi Chen

School of Culture and Creativity, Beijing Normal-Hong Kong Baptist University, Zhuhai, Guangdong, 519087, China

Keywords: Game Addiction, Gender, Age.

Abstract: Game addiction has rose a public concern in recent days. Current studies have revealed the impact of gender

and age on game addiction from multiple aspects, encompassing variations in national contexts, cultural

backgrounds, sample sizes, and methodologies. In addition, this literature review essay summarized the

research process, methodologies, and results of 8 related researches in order to discuss the correlation between

gender, age and game addiction. In conclusion, present studies indicate that male gender and young age are

risk factors linked to game addiction. Males and young people are easier to be affected by game addiction.

This results might suggest that the prevention of game addiction should focus more on young male population.

Further, future longitudinal research is needed to reveal the causality effects of age- and gender- related

variables on game addiction.

1 INTRODUCTION

Video games have become an important part of

billions of people’s lives nowadays. They have

become a new media that influenced multiple fields,

such as entertainment, socializing, or even education.

But the addiction problem of this new media has

emerged with its development. The World Health

Organization (2020) has argued that severe addiction

to video games is a mental disease and has been

defined as Gaming Disordered (GD) in the

11th version of the International Classification of

Disease (ICD-11). Although GD is not widespread,

the WHO still alerts individuals who participate in

games to pay attention to the length of time they

devote to gaming. Besides, according to a report from

the WHO (2024), 12% of the adolescents are at risk

of game addiction. This suggests the importance of

the understanding of video game addiction. Current

studies show that there are differences in the degree

of gaming addiction among different genders and age

groups. Therefore, understanding how these two

elements affect game addiction is important for

preventing game addiction and, furthermore, Gaming

Disordered. In this essay, the differences in game

addiction between different genders and age groups

will be discussed.

2 INTRODUCTION TO STUDY

SUBJECT

In this essay, the impacts of two elements, gender and

age, on video game addiction will be introduced.

Except for that, several psychological behaviour

dimension will be mentioned. They are trouble

caused by game using, time that spent on game,

gratification caused by game using, and economical

profits which comes from game using.

2.1 Definition of Game Addiction

Generally, video game addiction is a subtype of

internet addiction. Since internet addiction came to be

acknowledged as a clinical disorder, the researchers

studied game addiction as a subspecies of it. Except

for that, such a kind of addiction was always

attributed to the Massive Multi-user Online Role Play

Game (MMORPG) (Graham & Joseph, 2014).

Some researchers (Lee, Zach, et al.,

2015) claimed that the behavior and feature of

MMOG addiction were concluded into these seven

dimensions: Salience (e. g., game as the most

important activity in gamers’ lives), Mood

Modification (e. g., the game could modify the

gamers’ mood), Tolerance (e. g., more and more

amounts of time or resources used in the game),

Withdrawal (e. g., feels unpleasant when

discontinuing the game), Conflicts (e. g., problems

456

Chen, Y.

The Impact of Gender and Age on Game Addiction.

DOI: 10.5220/0013993200004916

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Public Relations and Media Communication (PRMC 2025), pages 456-460

ISBN: 978-989-758-778-8

caused by excessive playing of the game), Recurrent

(e. g., a propensity to return to previous excessive

game play pattern), and Uncontrollable (e. g., can not

control the resources spent on games).

Such kinds of behaviors and features could lead to

multiple negative influences on people’s lives. For

example, research points out that game addiction has

a significant correlation with sleeping problems

(Alghamdi, 2024). Djannah (2021) states that game

addiction is able to cause health problems by making

the problematic gamers delay eating and sleeping.

Graham & Joseph (2014) also mentioned that game

addiction may lead to poor academic performance

and escapism. In some serious cases, it may even lead

to seizures and death.

2.2 Game Addiction Scale (GAS)

GAS is a common method that has been widely used

in game addiction research. Early research has

developed a lot of kinds of scales (Wong & Hodgins,

2014). Although there might be differences in

advantages and disadvantages between each kind of

them, they generally built a conceptual approach to

video game addiction from different aspects.

Moreover, they also provided a lot of data for

understanding video game addiction through

application in previous research.

3 THE IMPACT OF GENDER ON

VIDEO GAME ADDICTION

In this section, the previous research result of how

gender affects video game addiction will be shown.

Gender was confirmed to have a correlation with

game addiction in several previous studies. For

example, Abolfotouh & Barnawi (2024) collected

data from 737 adolescents through an online survey

by using the GASA (Game Addiction Scale for

Adolescents). The male-to-female ratio in the sample

is 40. 8% : 59. 2%. Within the sample, 8. 3% were

addicted gamers while 33. 4% were problem gamers.

Further logistic regression analysis points out that

male gender is significantly (OR=1. 36, p=0. 038)

associated with game addiction.

Emre Müezzin (2015) did further research discuss

the gender’s effects on game addiction by collecting

samples from 131 North Cyprus high school students.

The sample of the research contains 61. 8% (n=81)

female students and 38. 2%% (n=50) male students.

Data collection for the survey was carried out using

the Online Game Addiction Scale, which is composed

of three sub-components: troubles, success, and

economic profit. They correspond to the level of

trouble that is is caused by habits of playing online

games, the level of relying on online games to satisfy

one’s sense of achievement, and the level of

economic gain through playing online games and

their impacts. All of the subscales follow the principle

of “the higher score, the higher level.” SPSS for

Windows was used to analyze data. The analysis

shows that in all three subscales, male

students’ average score is statistically significantly

(p=. 000) higher than female students. In conclusion,

male students have a higher score in the online game

addiction index. The research points out that male

high school students have a significantly greater

probability of being affected by online game

addiction, especially in the aspects of satisfying

achievement, getting profits from online games, and

getting in trouble because of playing online games.

All in all, the research reveals that online game

addiction is more likely to affect male high school

students. Despite valuable results and data provided

by this research, some limitations should be noticed.

First, the research only covered the online game

category, so other game types, such as single-player

games, are not included in this research. Second, the

samples come from high school, so other age groups

are not included in this research.

Research that contains a much larger scale of

samples has been conducted by Rehbein & Mößle

(2013). 4436 7th to 10th grade students from ten

schools in Hanover, Germany were surveyed. There

are 48. 4% male samples included within the total

sample. Both the Video Game Addiction Scale and

the Compulsive Internet Use Scale were used in this

research. With sufficient sample size, the research

argued that most video game addicts are male, and the

number of video game-addicted girls is extremely

small (n=9). This result could support the idea that

males are the main body of video game addiction.

Another research study (Mentzoni et al., 2011) on

video game addiction among the Norwegian

population clearly defines the relationship between

gender and video games. The sample consisted of

2,500 individuals between the ages of 15 and 40 who

were sourced from the Norwegian National Registry.

To show the situation of video game addiction, the

seven-item version of the GASA was utilized. The

scale contains seven items for all essential factors of

the seven dimensions of game addiction. If the

respondents endorse all of the items, they will be

identified as game addicts. or those respondents who

endorsed at least four items, they are classified as

problem gamers. In order to explore the connection

The Impact of Gender and Age on Game Addiction

457

between gender and video game addiction, the

researchers use problem video game use and gender

as an independent variable to conduct a crude and

adjusted logistic regression analysis. Except for that,

players were grouped in quartiles according to the

time they spent on games per week from low to high

to investigate the predictors of MMORPG preference.

As a result, a significant gender difference in game

use pattern. The majority of male respondents had a

regular game playing habit, while the majority of

female respondents did not. The investigation on

MMORPG preference predictors shows that gender is

a significant predictor. Male responders whose

gaming frequency placed them in the highest quartile

were the most likely to have a preference for

MMORPGs. As for the result of game addiction

prevalence, male gender is an important predictor.

Within all respondents, there were only 4 individuals

who were classified as game addicts, and all of them

were male. Inclusion: game addiction was especially

prevalent within the male gender. But because of the

low number of addicts, researchers did not do further

research on this group of people.

A research study study from Greece

(Tsitsika, 2009) has suggested the same opinion from

a different aspect. The research included 953 grades

9 and 10 high school students from the urban district

of Attica, Greece. The sample consists of of 438 boys

and 499 girls. They were asked to report their time

spent on the internet per week. Then, the participants

were divided into 5 groups according to the time

period they devoted to internet use. The groups are

The groups are non - users who spend 0 to 1 hour per

week, low internet users who spend 1 to 3 hours per

week, medium users who spend 4 to 10 hours per

week, high internet users who spend 11 to 20 hours

every week, and problem users who spend more than

20 hours every week. Except for that, the researchers

also collected the the data about what they usually use

the internet for, including gaming. The stepwise

forward multivariate logistic regression analysis

method has been used for the data analysis. The result

shows that the absolute majority (98. 5%) of

excessive male internet users use the internet for

gaming, while females do not. This might suggest that

male internet users were easier to fall into game

addiction.

In conclusion, current studies state gender has a

significant impact on game addiction prevalence.

Game addiction is more likely to happen in males.

Besides this valuable opinion provided by the studies,

a common limit of them should be noticed. Generally,

the studies use gender as a cross-sectional variable, so

the longitudinal variables that relate to gender have

not been covered by the research. For example,

Mentzoni’s research (2011) only covered how gender

affects MMORPG addiction; other types of games are

not included.

4 THE IMPACT OF AGE ON

GAME ADDICTION

Age differences are also claimed to be connected with

game addiction prevalent in the previous research.

For example, the study of Rehbein & Mößle

(2013) argued that younger students in 7th and 8th

grade are more likely to be affected by game

addiction than students in later school years. This

result has already shown the trend of negative

correlation between age and video game addiction

prevalent.

To be more specific, Festl et al. (2012) did

research in the same country with Rehbein & Mößle,

in German. The research also contains a sufficient

sample size of 50,000 individuals aged 14 and over.

The data was collected by German standard

computer-assisted telephone interviewing, and the

Game Addiction Scale (GAS) was used in data

collection. The researchers also estimated a multi-

group structural equation model to test the latent

variable of how personality traits correlated to age.

The personality traits included three different aspects;

they are social competence, self-efficacy, and anger

aggression. Preliminary analysis confirmed the

correlation between age and game addiction. Then,

the researchers divided the respondents into three

groups. They are teenagers whose ages fall between

14 and 18, younger adults whose ages fall between 19

and 39, and older adults aged more than 40. Although

this result may be caused by the different preferences

between younger adults and older adults, the research

claims that adolescents easier to be affected by game

addiction than the older adults (p<0. 05). In the aspect

of age and personality traits, problematic game use

has a significant correlation with low levels of

sociability and a sense of insufficient social support

in adolescents than adult gamers (p<0. 05).

To sum up, the research verified that age and

game addiction are negatively correlated. However,

to draw a causal conclusion, more longitudinal data

and analysis are needed.

Another study done by Vollmer et al.

(2014) reveals a stronger correlation between age and

game addiction. 741 teenagers aged 11 to 16 from

different schools in Istanbul participated in the study.

Computer Game Addiction Scale (CGA scale) was

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used to test the level of CGA symptoms of

individuals. The result of the bi-variate Pearson’s

correlation analysis shows that age has a strong

negative (p=-0. 022) correlation with game addiction;

this leads to the conclusion that younger adolescents

report higher CGA.

A research study from Norway supported this

opinion. 24,000 people, randomly chosen from the

Norway's official national population register

(NPRN), constitute the sample. The ages of

participants are 16-74 (Wittek et al., 2016). The

GASA was used in the questionnaire to test the level

of game addiction. Pearson product – moment

correlation analysis was used for data analysis. The

participants have been divided into 3 age groups of 16

to 30, 31 to 50, and 51 to 74. Compared to the people

whose age is in group 16 to 30, being in the other two

groups shows a significant negative correlation with

game addiction in crude and adjusted analysis. The

researchers claim that The youngest age group had a

higher likelihood of belonging to the addicted group

compared to the other two groups. To be specific, 2.

9 times more than the middle age group and 4 times

more than the oldest group. In summary, being young

in age is an essential factor for game addiction. But

the researchers warned that the game, as a new

phenomenon, may have an influence on this

conclusion.

In summary, age was shown to be negatively

correlated with game addiction in current studies.

This suggests younger individuals may be easier to

fall into game addiction. Lots of research mentioned

the need for longitudinal data analysis, and this

suggests age can not simply be a reason for game

addiction. More research on other factors related to

age, which might influence game addiction, is

needed. For example, game preferences, cultural

background, and social needs differ between different

age groups.

5 DISCUSSION AND

SUGGESTION

All in all, current studies have covered different

cultures or country backgrounds, sample populations,

and study methodologies. They generally indicate a

correlation between gender, age, and game addiction.

Male gender was suggested to be a strong factor in

game addiction, while young age is another strong

factor. This correlation may be influenced by multiple

factors. For example, Festl et al. (2012) point out that

the high percentage of game addiction among young

people may be caused by the greater amount of leisure

time and a lesser burden of work or family

obligations. According to another investigation

carried out by Jahantigh & Nourimoghadam (2023),

a correlation was found between the problematic

game use in adolescents and the cognitive-avoidance

behavior of their mothers. The Pearson’s correlation

analysis in this study shows that there is a significant

(p<0. 001) correlation between mother’s cognitive

avoidance and adolescents’ anxiety. The researchers

claim that this result has led to a significant indirect

effect on game addiction (β=0. 04~0. 06).

The general result and conclusion of current

studies may suggest that the prevention of game

addiction should focus more on the young population

of the male gender. The result of the research on the

correlation between age and game addiction shows

that the adolescents and younger adults aged 11 to 39

are much easier to fall into game addiction than the

other age groups. Among adolescents and young

adults, an inverse relationship between age and game

addiction still holds. This suggests being in a school

age is an important factor for game addiction.

In addition, the prevention from schools and

parents is essential for people of this age. A study on

cyber violence and bullying recommended that

educators and families build a common prevention on

adolescent problematic gaming (Hidayat et al., 2022).

Another research study (Greenfield, 2022) shares the

same opinion as this study. The researcher states that

in those cases where patients are children,

adolescents, or young adults, the treatment must be

made based on the motivation and resources of the

patient and family. The research focus on college

school students also suggests that by enhancing self-

control capabilities and family functionality,

symptoms of game addiction can be mitigated. (Zhou

& Xing, 2021). Besides, some researchers claim that

it is necessary to differentiate the prevention of game

addiction based on gender since males are more likely

to be influenced by game addiction than females

(Durakhatice et al., 2022).

Besides, researchers also claim that gender and

age, as a cross-sectional variable, can not be

considered as causally related to game addiction.

There are plenty of longitudinal variables related to

gender and age that might influence game addiction

causally, for instance, cohort effects, personality

(Wittek et al., 2016), gaming preferences

(Mentzoni et al., 2011), and so on. In addition, there

is a need for research in those fields. So, future

research may focus on how those cross-

sectional factors within gender and age affect game

addiction. Except for that, a larger sample population

The Impact of Gender and Age on Game Addiction

459

can be expanded, for example, from a gender and age

perspective on game addiction prevalence in Asia,

South America, or other different cultural groups.

6 CONCLUSION

To sum up, existing research has identified a

correlation among age, gender, and game addiction.

Regarding gender, the prevalence of game addiction

is greater in males compared to females. In terms of

age, young individuals are more likely to be addicted

to games than the elderly.

This result suggests the prevention of the game

addiction should be more focused on male teenagers

and young adults. Due to the relatively high

prevalence of game addiction among school-aged

students, schools and parents play an important role

in the prevention.

For the future research, the relationships between

longitudinal variables, which are related to gender

and age, and game addiction are needed. Except for

that, research on the prevalence of more uncovered

countries, regions, minority populations, and cultures

is also needed.

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