MASARYK UNIVERSITY

Faculty of Social Studies

Department of Psychology

Lukas Blinka

Online gaming addiction: The role of avatars and sociability of gamers

Dissertation

Supervisor: Prof. David Šmahel, M.Sc. et Ph.D.

Brno 2015
I declare that I have written the thesis independently and all cited resources have been

listed in the references.

Brno, November 20, 2015 Lukas Blinka

2
 Table of Contents

Table of Contents ............................................................................................................................. 3

Acknowledgment.............................................................................................................................. 4
List of original publications ............................................................................................................. 6
Introduction ...................................................................................................................................... 8
Setting the Problem ........................................................................................................................ 11
A Brief Introduction to Online Games ....................................................................................... 12
MMO Games and Addiction ...................................................................................................... 14
Risk Factors of Addiction on the Side of the Player .................................................................. 21
Risk Factors of Addiction on the Side of the Game ................................................................... 22
Research Questions .................................................................................................................... 25
Methodology .................................................................................................................................. 27
Study I and II .............................................................................................................................. 27
Study III...................................................................................................................................... 29
Study IV ..................................................................................................................................... 30
Study V ....................................................................................................................................... 31
Results ............................................................................................................................................ 34
Research question one ................................................................................................................ 34
Research question two ................................................................................................................ 35
Research question three .............................................................................................................. 36
Discussion ...................................................................................................................................... 38
Avatar’s role in online gaming ................................................................................................... 38
Social factors of gaming addiction ............................................................................................. 39
Addiction and engagement – distinct or continuum? ................................................................. 41
Limitations and future directions................................................................................................ 42
Literature ........................................................................................................................................ 44
Study I ............................................................................................................................................ 53
Study II ........................................................................................................................................... 60
Study III.......................................................................................................................................... 65
Study IV ......................................................................................................................................... 84
Study V ........................................................................................................................................... 95

3
 Acknowledgment

This thesis and my work on it had a complicated history. I started the process of preparing

materials for the thesis in 2008 and was originally very enthusiastic. But enthusiasm burned

out quickly and I interrupted the process and turned to other research topics. I returned back

to study excessive computer gaming in 2012 with a new project, new thoughts, a new

colleague, and new hopes. This thesis represents a summary of the previous steps and the first

one after my return to this topic. As the process was complicated, there are several people I

would like to thank.

First, it is my supervisor, David Šmahel. Without him I would have never started research on

this topic (or maybe even any research in general). Our collaboration was intuitive and very

fruitful. We also had a bit of newbie’s luck (as gamers often say), as our common papers got a

surprisingly good reception in the scientific community. What a start it was!

Then I would like to thank my new colleague without whom I would certainly have never

finished the thesis. Kača Škařupová, with whom I spent endless time discussing science over

countless cups of tea. She revived my research enthusiasm. I really hope this is just the first

step in our cooperation and even more discussion, falsified hypotheses and discovered

theories are to come!

My greatest gratitude going beyond this expression goes to Anna Ševčíková, who is my

closest one in both life and science and who taught me to love and to think. Thank you for

being by my side! And thank you that we can carry BB together!

Certainly, there are many more people who shaped and influenced my work in the last years

and who made my life worth living, those who are both excellent friends and colleagues (and

sincere apology to those I am not mentioning here). Thank you, Andra Siibak, Filip Havlíček,

Kjartan Ólafsson!

4
I would also like to thank Jakub Mikuška who co-authored one of the papers and to Robert

Ganian, who proofread this thesis and most of my articles.

Last but not least I would like to acknowledge the projects which financially supported my

research: project MSM0021622406 of the Czech Ministry of Education, Youth and Sports,

and projects P407/12/1831 and GA15-19221S of the Czech Science Foundation.

5
 List of original publications

This dissertation is based on the following original publications which are enlisted in

a chronological order and will be referred to in the dissertation with respective Roman

numerals.

Blinka, L. (2008). The relationship of players to their avatars in MMORPGs:

differences between adolescents, emerging adults and adults. Cyberpsychology:

Journal of Psychosocial Research on Cyberspace, 2(1), article 5.

Smahel, D., Blinka, L., & Ledabyl, O. (2008). Playing MMORPGs: Connections

between addiction and identifying with a character. CyberPsychology & Behavior,

11(6), 715-718.

Blinka, L., Smahel, D. (2012). Addiction to online role-playing games. In Young,

K.S. de Abreu, C.N. (eds.) Internet addiction: A handbook and guide to evaluation

and treatment, pp 93-110. Wiley: Hoboken

Blinka, L., & Mikuška, J. (2014). The role of social motivation and sociability of

gamers in online game addiction. Cyberpsychology: Journal of Psychosocial

Research on Cyberspace, 8(2).

Skařupová, K., Blinka, L. (in press) Interpersonal dependency and online gaming

addiction. Journal of Behavior Addictions

6
Author’s contribution

Study I: the author was the sole contributor.

Study II: the author was responsible for the part concerning identifying with the

game character and also for writing the theoretical and discussion parts of the article.

Study III: The author was dominantly responsible for all parts of the article.

Study IV: The author was dominantly responsible for writing the paper in all its

aspects. Lower role was in the data collection and data analysis.

Study V: Both authors were equally responsible for writing the paper. However, the

author of this dissertation was dominantly responsible for the conceptualisation of the

article and less for the data analysis.

7
 Introduction1

Addiction to the internet or specific online applications is a hot topic whenever a new

extreme case of such an addict surfaces. The assumption that one day everyone will

stop meeting in person and that all communication will take place through digital

media has become a part of general discourse since the internet became an integral

part of our lives. The first pioneer studies which explicitly discussed the addictive

potential of computer games date back to the 1980s (Soper & Miller, 1983). While

this direction was further developed in the early 1990s (Shotton, 1991), its boom only

began with the publications of Mark Griffiths (1996) and Kimberly Young (1998)

from the second half of the nineties. Dozens of empirical as well as theoretical studies

in this area have appeared since then. This expansion has for instance led to the

inclusion of the Internet Gaming Disorder in the appendix of DSM-5 (APA, 2013)

and to further consideration of the conceptualization of this phenomenon also in the

11th revision of the International Classification of Diseases (Grant et al., 2014) –

while in both cases it was found that a full acknowledgment of this diagnosis is still

premature, the significance of online addiction as an emergent phenomenon of the 21st

century has been clearly established.

Based on one point of view, addiction to computer gaming is only a hypothetical

consequence of the use of this medium. After all, previous studies of certain media

effects have also showed that these do not represent major problems, and society has

always been able to adapt to the new situation. For instance, the panic surrounding

intensive reading of comic books in the fifties of the 20th century (Rodman & Fry,

2009) is now considered a humorous example of this. It would thus be reasonable to

1
Text of the Introduction and Setting the problem of the cover article is partially taken and translated
from Blinka, 2015 a, b

8
assume that interest in the negative effects of computer games will also subside over

time.

However, based on a second point of view the effects of these new forms of media are

actually clear – they have a large impact on the psychological, physical and social

well-being of individuals. This view goes hand-in-hand with a certain degree of moral

panic, which is generated or utilized by standard communication media. This line of

thought often includes a certain assumption on technological determinism, i.e., the

assumption that there exists a direct and causal relationship between use of the

medium and the considered effects.

This dissertation rejects both of these viewpoints and considers a third viewpoint, the

so-called Differential Susceptibility to Media Effects Model (Valkenburg & Peter,

2013). This model assumes that, depending on the context, certain people may

experience greater media effects than others, and that the use of a single medium can

lead to several simultaneous effects which can be both positive and negative. The

factors of susceptibility can be summarized as developmental (each developmental

stage represents specific goals, challenges and motivations), personal (ranging from

the structure of one’s persona to the presence of pathologies) and social (family

influence, close social surroundings, and societal conditions) (Valkenburg & Peter,

2013). Last but not least, these can include certain characteristics of the medium, i.e.,

computer games, which influence the individual’s behaviour (Blinka, 2013;

Valkenburg, Peter & Walther 2015).

This work focuses on the factors of susceptibility to pathological online gaming. The

dissertation consists of five articles, four of which are empirical and one of which is

theoretical. Study I and II focus on the relationship of players and their avatars and

the role of this relationship in the development of pathological gaming. Avatars are a

9
very important feature of online computer games. Study IV and V focus on the social

skills of players and how these skills can increase or decrease the susceptibility to

addiction. Playing of computer games is generally a very time-demanding hobby;

however, playing does not necessarily represent pathology on its own. That is why

studies IV and V also provide a comparison of intensive gaming both with and

without pathological traits; this is an important factor for further research as well as

for therapeutic practice.

These five articles are summarized by a cover article with the standard structure. In

the Setting the Problem section I will introduce the current state of the art in the area

of excessive gaming. I will explain online games and their significance. I will

introduce the addiction components model (Griffiths, 2005) and differentiate

pathological and non-pathological excessive gaming. I will also describe the

predictors of addiction on the side of the player as well as the influence of certain

characteristics of the online games themselves. This section ends with three research

questions formulated based on a review of literature. In the Methods section, I will

describe data collection, characteristics of the research samples, types of used

variables and analyses from individual empirical studies. In the Findings section, I

will attempt to answer individual research questions based on the results obtained in

individual empirical studies. Finally, in the Discussion section I will confront the

results with existing findings of other authors and I will introduce these in a wider

context. I will also propose directions for future research.

10
 Setting the Problem

Online gaming addiction2 is the second most prominent type of behavioural addiction,

both with respect to the interests of the public and experts, only surpassed by

gambling. Even though this disorder is not officially listed in the International

Classification of Diseases, in 2013 it was added to the appendix of DSM-5 (APA,

2013) under the name Internet Gaming Disorder. The manual explicitly mentions this

disorder as an experimental diagnosis, the status of which needs to be verified by

further research, since we still lack strong epidemiological data or data monitoring the

clinical course of the disease. In spite of this, the notion of addiction to online gaming

has been targeted by hundreds of studies, and a number of these have discovered a

range of similarities with traditional addictions. That is one of the reasons why this

subject has become a frequently discussed topic in the media, even though this degree

of medicalization is not very useful and in many cases leads to stereotypization and

the spread of false myths. Typically, media depict isolated and very rare cases, often

from South-eastern Asia, where excessive gaming has been known to even lead to

death. Even though one could think that online gaming is a phenomenon localized

predominantly in Southeast Asia, certain data indicate that this activity is also very

prevalent in the Czech Republic. The research of the World Internet Project in 2008

for instance discovered that 38 percent of adolescents in the Czech Republic played

online games on a daily basis, which is comparable for instance with the values of

Singapore (35%) and the U.S. (34%) and significantly more than values for Hungary

2
Due to the ongoing debate of whether this truly represents an addiction in the strictest meaning of the
word, a number of experts prefer other terms such as, e.g., problematic online gaming, obsessive
gaming (see for instance Wood, 2008; Király et al. 2014). I will use the term “addiction”
predominantly. This is consistent with the terminology used in the DSM, which on one hand uses the
term “Internet Gaming Disorder”, but categorizes this disorder in the group of “substance-related and
addiction disorders”. The term “addiction” is used in this section only in the strictest meaning of the
word, i.e., it refers exclusively to cases where players actually exhibit the symptoms of addiction. For
these cases, I also use the term “pathological gaming”.

11
(23%). Similarly, the results of the EU Kids Online II project have shown that Czech

children and adolescents are typically more interested in online gaming than in most

other European countries (Helsper et al., 2013).

A Brief Introduction to Online Games

In this dissertation I will not be speaking about all computer games, but rather only

about their online variants; specifically, the results are concerned with specific online

game worlds referred to as MMOs games (Massively Multiplayer Online games).

MMOs are characterized by the simultaneous presence of many (thousands) of

players in the game world at the same time, whereas all of these players can interact

with each other. There are several genres of such virtual worlds. The original and

until recently most popular type of such games were MMORPGs (where RPG stands

for role playing games), often set in science-fiction or fantasy worlds. In these games,

a player controls his/her character (the so-called avatar) who fulfils various tasks,

battles monsters and avatars of other players, but can also for instance become

craftsmen and create items for other players or simply go explore the expansive

virtual world. A typical representative of this genre is World of Warcraft (abbreviated

as WoW). MOBA (multiplayer online battle arena) games represent another

prominent genre, where players repeat shorter battle sequences against each other,

typically lasting between several minutes and an hour. This is currently the most

popular genre, with specific representatives including games such as League of

Legends or World of Tanks. Pure virtual worlds such as Second Life and sandbox

games are relatively less popular than the first two genres. Games played directly in

the browser (which do not require an installation) are then a completely separate

group – one prominent feature of such games is that they can be played using less

12
powerful devices. They may have various genres, but are generally simpler than

classical computer games and may be more attractive, e.g., for children.

Compared to classical offline computer games, MMOs have a range of special traits

which influence the intensity of play and the potential creation of addiction (Király et

al., 2014). In fact, intensity is one of the features that clearly differentiates these

games from other genres. 25 hours of play per week is considered the average, which

is several times the weekly value for classical computer games. Long uninterrupted

gaming sessions are also frequent – over one half of players have played over 10

hours in a single session, and over 80 percent of players have experienced sessions

over 8 hours long (Williams, Yee & Caplan, 2008; Yee, 2006). This approximately

matches the time players spend in school or at work. MMO games thus represent a

very significant free-time activity, and in the case of younger players also a very

prominent socialization environment.

The social aspect is one of the greatest allurements of MMO games (Cole & Griffiths,

2007). Contrary to the typical stereotypes, playing MMO games is not an asocial

activity – success in such games very strongly depends on communication and

cooperation with other players. Players typically form long-term groups (so-called

clans, guilds, etc.), and spend more of their game time with other players from their

group. For a large number of players, the game itself is only viewed as an

accompanying element for their interactions with the community surrounding the

game. Contrary to popular opinion, such social relationships are often supported by

real life – a significant number of players typically play with people they know from

real life (such as, e.g., schoolmates) or organize real-life meetings with people they

have met in the game.

13
Another specific trait of MMO games is the gradual development of one’s avatar or

gaming account. A (typically highly sophisticated) rewards system awards players

with points based on their fulfillment of in-game tasks, and these allow players to

access more advanced content of the game; the player’s avatar becomes more

powerful, better equipped and has a greater prestige in the eyes of other players

(Király et al., 2014).

Last but not least, MMOs are characteristic for being unlimited. Unlike standard

computer games, they do not have a strict end – they cannot be “completed”. This is

due to two factors: the game developer regularly adds new content to the game, and a

significant portion of the game is formed by the actions of other players. The gaming

world is also persistent – it exists and continues to develop even when a player is not

playing (Study III).

MMO Games and Addiction

One case study of addiction to online gaming is provided by Griffiths (2010) on the

subject of Jeremy, a 38-year-old male accountant, who has been married for 13 years

and has two children. His gaming habits took about 3-5 hours of his time each

evening, during which he played a MMORPG to relax after a stressful day. Over time,

he spent more and more time playing the game every day, and played for up to 14

hours per day before seeking out help. He tried to limit his gaming habits several

times, but never managed to sustain this for more than a few days. When he couldn’t

play, he had a strong feeling of anxiety and was irritable. The extreme amount of time

spent in the game has gradually led to conflicts in his life – he lost his job due to not

performing his work duties, and in the end his wife also abandoned him. All of his

problems led to him spending even more time in the game, because it provided him

14
with a sense of escape – leading to a vicious cycle, which he could not break alone. In

the end, he sought out psychological help on his own. (Griffiths, 2010).

The components model of addiction of the British psychologist Mark Griffiths is the

leading framework used in the research of addition to online games. This framework

(Griffiths, 2005) is based on an adaptation of Brown’s theoretical components of

addiction (1993). The above-specified case study illustrates the presence of all factors

of addiction. And to actually be able to speak of a factual addiction, all of the

following factors should be present (summarized as per Study III and Király et al.,

2014):

1) Salience – gaming over time becomes the most important activity in

the player’s life. Most of the player’s thoughts deal with the game (for

instance planning of future gaming sessions, memories of past gaming

sessions), and the same is also true for the player’s cravings and behaviour

(for instance, other activities are postponed due to gaming, including basic

hygienic and nutritional needs).

2) Euphoria – this generally represents positive mood swings caused by

the given activity, i.e., gaming. So-called mood management, the ability to

reduce stress, is one of the most important motivational factors for media in

general. It can thus be assumed that the strongest urge to play occurs during

times of increased stress, for instance in the test period in school.

3) Tolerance – gaming is progressive, over time it takes more and more

time, while the originally positive feelings from the game become harder to

reproduce. It can thus be assumed that those who are actually addicted are

rather averting the negative feelings of not playing than positively enjoying

the activity of playing.

15
 4) Withdrawal symptoms – the need to end a gaming sessions or inability

to play at a given time is often accompanied by negative feelings, mostly a

feeling of nervousness, bursts of anger, anxiety and depression.

5) Conflict – loss of control over playing and excessive time spent in the

game gradually leads to interpersonal conflicts with the player’s social

surroundings and a deterioration of performance in school or at work.

Intrapersonal conflicts are also frequent, for instance in the form of shame and

guilt.

6) Relapse – in spite of knowing that gaming leads to serious problems in

the player’s life and even after periods of relative control, the player has a

tendency to return to gaming. He/she is not capable of effectively dealing with

the situation without outside help.

Addiction to online gaming could then be conceptualized as follows: an activity,

which over time becomes a fundamental part of the player’s life, and over which the

player gradually loses control. Gaming is accompanied by mood swings, which

however turn to negative feelings if the individual cannot play. The intensity of

gaming over time leads to psychological, social and/or physical problems and

conflicts. The player has a tendency to return to gaming in spite of known negative

consequences and even if the player was able to manage his/her gaming habits for a

certain amount of time.

If we compare the above-mentioned components of addiction with the criteria of

addiction to online gaming as specified in DSM-5, we will see that DSM-5 has one

item for each component. An exception to this is the component of conflict, which has

four items. Hence excessive gaming is differentiated from pathology, i.e., addiction,

based on negative consequences. This corresponds to previous studies, which have

16
shown that not all components of addiction have the same weight for determining

pathology. Charlton and Danforth (2007) differentiate between central and peripheral

criteria of addiction on computer games. In their framework, central criteria included

conflict, withdrawal symptoms, relapse and behavioural salience. Peripheral criteria

then included cognitive salience, tolerance and euphoria. This division has significant

implications for diagnostics. If an individual only exhibits peripheral criteria of

addiction, then he or she is not suffering from a pathology – they are merely strongly

engaged in the game. Hence merely using the number of present factors can be

problematic, and may lead to misunderstandings and an incorrect assessment of

addiction.

Griffiths (2010) shows an example of excessive but non-pathological gaming on the

case study of 21-years-old Dave, who had just finished his Bachelor’s studies.

Similarly to the case of Jeremy described above, Dave also played 14 hours a day.

However, he did not see himself as addicted. He said that his social circle had

become significantly smaller since he finished his studies, since most of his friends

were no longer at the university and found jobs. He himself did not find a job right

away, and the game thus offered him both an opportunity to socialize and also

represented a sort of daily routine, since nothing very important was happening in his

life outside of the game. After some time, he did find a job and he also found a

girlfriend in the game. Over time, he limited the amount of time spent in the game due

to a lack of time. However, with his girlfriend kept playing from time to time – it was

an activity which was simply a part of their life style. (Griffiths, 2010)

This example also shows that, contrary to popular belief, time spent in the game is not

a suitable criterion of addiction. Just the sheer amount of time spent playing such

games can sometimes make his/her close ones worried about the player’s health;

17
however, such fears are not always appropriate or relevant. Many players can spend

an above-average amount of time in the online world and still not exhibit the

symptoms of addiction, or only exhibit them for a very short time period. Hence

addiction is also defined based on the “quality” of the gameplay, not just its

“quantity”.

In general, it is difficult to establish a clear causal relationship between excessive

gaming and specific follow-up psychosocial difficulties. Reduced performance in

school or work, interpersonal conflicts in the form of deterioration of close relations,

low self-esteem, feelings of anxiety and depression – all of these can represent not

only a consequence, but also a cause of excessive gaming. Games represent a

potential escape from and a means of relaxing during difficult times. Excessive

fixation on the virtual world can however have a further negative influence on these

factors. The emergence of an addiction can be understood as a symptom of an

unsuitable coping strategy.

On the other hand, a direct causal relationship can be established for the physical

health of players (even though this area in somewhat less studied than the

psychosocial effects of addiction). On the physical level, we see two complexes of

problems (Kalmus, Siibak & Blinka, 2014). The first consists of various minor

injuries of the musculoskeletal system due to long-term and long-lasting fixation in

unsuitable positions (as was already mentioned, players have a tendency to spend

dozens of hours per week in the game) – carpal tunnel syndrome, back pains,

headaches, etc. The second problem is then a lack of quantity and quality of sleep.

Players have a tendency of playing at night, when more people tend to be online. Due

to the fact that playing is usually a very cognitively demanding activity, it is often

18
accompanied by energy and caffeine-based drinks3. This then leads to the inferior

quality of sleep. Long-term low quality of sleep can then lead to less attentiveness,

greater susceptibility to diseases and a higher injury rate (Koulouglioti, Cole &

Kitzman, 2008).

It should also be mentioned that financial costs are not a criterion for addiction to

online gaming. Compared to gambling, online games are a rather “cheap” form of

entertainment; publishers usually aim for lower but more regular income from a large

amount of people4. However, one also needs to assess this critically. Publishers have

lately started to prefer the so-called free-to-play model, when the game is basically

available for free, but one can access advanced content for a fee. Hence when some

players lose control, they can in principle spend amounts on the game which they

would not be willing to pay in advance. This can lead to problems especially for

income-less players, for instance long-term unemployed or younger students (research

has identified a relationship between excessive internet use and problematic

behaviour such as, e.g., lying and minor theft, see for instance Šmahel and Blinka,

2012). Financial losses can also be created by games indirectly, i.e., by players

spending time in the game rather than at work; this can in some cases lead to

problematic players losing their jobs.

3
The relationship between addiction to online games and problematic use of caffeine is also mentioned
in DSM-5. It is possible to consider the potential susceptibility of certain players to other stimulants,
ranging from nicotine and even methamphetamine to overcome fatigue and improve concentration to
the use of sleep pills or cannabis-based drugs after gaming sessions to be able to sleep at all.
4
Not all online games require regular monthly payments. And yet, this area of entertainment is far
from insignificant from the financial perspective – on the contrary. The Entertainment Software
Association (ESA, 2013) estimated that only in the U.S. the computer games segment produced an
income of 14 billion USD in 2012 – and most of this was made in the area of online games. For
instance, WoW celebrated its 10th anniversary in 2014. At its peak, it had 12 million regular paying
players, and currently this number is still at around 10 million. The primary income of WoW is based
on regular monthly fees (about 15 USD per account per month), but also generates income from the
sale of add-ons (so-called expansions) for the game. During its existence, it generated hundreds of
billions of Czech Crowns in earnings for its developer Blizzard. League of Legends and World of
Tanks are examples of the most successful online games today; both of these games had 80 million
registered (but not necessarily paying) users in 2014 (source: Wikipedia).

19
Neurobiology of Addiction to Online Games

From the neurobiological viewpoint, addiction to online games occurs when, to

simplify the matter a bit, repetition of activities leads to a breakdown of the

mesolimbic dopamine system in brain – these are the areas responsible for

conditioning or general learning. It is assumed that associated playing with in-game

rewards (resulting in positive feelings from the game) and release of dopamine over

time lead to gradual intensification of such behaviour (Dreier et al., 2013). An EEG

study showed that pathological gamers had a stronger emotional reaction to

stimulating pictures depicting the game than non-pathological ones (Thalemann,

Wölfling & Grüsser, 2007), and in fact had similar characteristic reactions as those of

alcoholics when they are shown stimuli linked to drinking (Kuss & Griffiths, 2012).

When confronted with in-game stimuli, addicted players had a tendency to use similar

areas of the brain as cocaine users (Ko et al., 2009). Aside from functional changes,

structural changes of the brain were also reported (even though the direction of

association is not clear in this case) – reduced density of grey matter in the left

anterior and posterior cingulate cortex (Zhou et al., 2011) and amygdala (Ko et al.,

2014). A reduction in the amount of grey matter in the same areas is also typical for

individuals with attention disorders. As summarized by Kuss and Griffiths (2012a),

there is some evidence that from a neurobiological standpoint there is no symptomatic

difference between addicted gamers and other addicts. Because the number of studies

in this area is still relatively small, it can be expected that, aside from longitudinal and

epidemiological studies, also neurobiological investigations will play a fundamental

role in the understanding of excessive online gaming.

20
Risk Factors of Addiction on the Side of the Player

There are two dominant etiological models mentioned in the literature which form the

basis for addiction to online games. These models were identified also for general

excessive internet use (Blinka, 2014). The first is a complex of psychosocial and

emotional problems. The second complex then includes attention disorders and the

inability to resist impulses.

Psychosocial and emotional problems

A significant number of studies points towards a relationship between addiction to

online gaming and increased occurrence of depression, anxiety, social anxiety,

feelings of loneliness and neuroticism (Mehroof & Griffiths, 2010) along with lower

self-esteem, low self-efficacy and less comfort in social situations (Chak & Leung,

2004). It seems that studies more or less confirm the usual stereotype of an excessive

gamer being a younger male with an introvert or even schizoid personality, who is

socially shy (Kuss & Grifiths, 2012b). The risk of the occurrence of a pathology then

increases due to situational factors which increase stress in the individual’s life,

increase the feelings of isolation and negatively impact his/her emotional well-being.

Computer games, among others thanks to their system of rewards and wide range of

communication options, serve as a tool for regulating moods and stress (Hussain &

Griffiths, 2009), which allow a player to quickly get rid of feelings of loneliness and

low self-esteem. For most players, this represents a functional coping strategy.

However, some players get caught in a vicious cycle – while playing does represent a

short-term improvement of the individual’s well-being, in the long term it actually

makes the problems that brought the player into the game worse. Longitudinal studies

have notably discovered a deterioration of symptoms of depression and anxiety

(Gentile et al., 2011) or feelings of loneliness (Leemens, Valkenburg & Peter, 2011).

21
Attention disorders and increased impulsiveness

The second complex of predictors of addiction to online gaming is a lowered ability

to concentrate, increased impulsivity and tendency to get bored. Online games are a

multimodal environment; individuals can play, speak with others, watch videos with

guides for the game and switch between all of these on a need-to-need basis. Such an

environment is very well received especially by individuals who have a greater need

to be distracted. At the same time, these individuals are more susceptible to classical

conditioning (more susceptible to positive rewards but resistant to punishment, Ko et

al., 2012), which is an area games excel at (see below). It should be said that this

complex of predictors is significant especially for children and adolescents. Their

higher impulsivity leads to another symptom of addiction – problematic behaviour

such as for instance the tendency to lie and higher aggressiveness (Gentile et al.,

2011). The synergic effect of emotional problems, lower self-control and preference

of online games has been shown to a factor which may predicts the emergence of

internet addiction especially in adolescents (Blinka et al., 2015). However, the effect

of psychosocial and emotional problems seems to be dominant – Müller et al. (2012)

claims that a comparison of young online gamblers and gamers has shown that

pathological gamers had the lower self-esteem of the two groups. On the other hand,

gamblers typically exhibited a more aggressive, impulsive behaviour. However, most

characteristics were shared among both groups, which once again points at the

similarities between behavioural addiction disorders.

Risk Factors of Addiction on the Side of the Game

Even though psychosocial factors may to some extent explain why some people

exhibit the characteristic traits of addiction, they cannot fully explain why certain

objects of addiction are more frequent than others. MMO games clearly differentiate

22
themselves among other internet applications with respect to the amount of game time

and the potential of the occurrence of a pathology. It can thus be assumed that there

exist certain characteristics of online games which attract the at-risk group of players

and which support the creation of a pathology. The potential power of this effect is so

great that it even led to the comparison of MMO games to a virtual Skinner Box (e.g.,

Yee, 2002). Even though I rejected technological determinism in the introduction,

based on certain studies it is necessary to attribute a certain amount of influence also

to the games themselves.

The structural characteristics of online games are a wide phenomenon, consisting of

potentially dozens of distinct attributes. An in-depth taxonomy of so-called structural

characteristics of online games which support excessive gaming was created by King,

Delfabro and Griffiths (2010). These characteristics were divided into the following

categories: a) social environment – the presence of other players and the possibility of

communication with them; b) controls – for instance the quality of gameplay of the

game itself, optimum difficulty of the game etc.; c) the aspect of identity and story –

for instance the creation of an in-game avatar and identification with the avatar; d)

positive and negative rewards – for instance the awarding of points for the completion

of tasks, “levelling up”, gradual unlocking of content; e) appearance –graphics, sound

and so forth. Based on a comparison of the preferences among the groups of

pathological and non-pathological gamers carried out by King, Delfabbro and

Griffiths (2011), addiction was most closely tied to factors related to rewards –

obtaining points and higher levels of a player’s avatar or gaming account (so-called

leveling), meta-gaming points (for instance rankings of players, obtaining titled for

fulfilling a series of complicated tasks) and enjoying “100 percent of the game”

(discovering all locations, completion of all tasks regardless of their entertainment

23
etc.). It is interesting that these characteristics of games are also those which are most

time-demanding. Pathological gamers are hence willing to spend a significant amount

of time in-game, fulfil repetitive and monotonous tasks, and yet receive positive

feelings from playing the game. In this respect, a comparison of online games to a

Skinner Box seems to be relatively fitting.

Some research explained the tendency to remain in the game for a long time with the

so-called flow phenomenon (Chou and Ting, 2003). This occurs when the game is of

optimal difficulty – it is not too hard or too easy. The player is so focused on his or

her activity that he/she loses touch with time – even several hours spent in the game

could subjectively be experienced as a much shorter gaming session. The flow effect

can even lead to players suppressing certain physiological states such as fatigue,

hunger, thirst, the need to go to the toilet or even pain (StudyIII).

King and colleagues (2011) also identified other characteristics of games which on

their own did not have an effect on addiction but jointly, and especially in

combination with the rewards factor, had a synergic effect. These were social and

identity factors. The presence of thousands of other players is what differentiates

MMO games from classical offline computer games (which are usually played alone).

Other players are not only teammates with whom it is possible to communicate, make

alliances and cooperate; they’re not just adversaries who one needs to beat or compete

with. They’re also witnesses of actions – without them, everything performed in the

virtual world would only remain in the head of the player. Social sharing thus gives a

very real nature to virtual behaviour.

24
Research Questions

An important feature of computer games is an avatar or character5, (typically) a visual

representation of the gamer in a virtual environment. Online games added a level of

identity to the rather technical aspect of avatars (Trepte & Reinecke, 2010) – avatars

become the player’s representation in the gaming community and in-game

advancement is often connected to progressive improvement of avatar’s skills and

abilities. Thus, it affects player’s success in the game. Success should not be merely

understood on an intrapsychic level of game enjoyment (Trepte & Reinecke, 2010); it

is also related to feelings of competence and self-esteem (Bessiere, Seay & Kiesler,

2007) and thanks to its social basis it may lead to interactive aspects such as the

player’s recognition. Thus, player’s attitudes towards his or her own in-game avatar

may influence the player’s gaming habits, including pathological gaming. The first

research question is:

RQ 1: What are the patterns of player-avatar relationship and what role do

these patterns play in online gaming addiction?

As has been stated earlier, online games are essentially a social space. The social

aspect of online gaming is one of the key difference to offline gaming. At the same

time, gaming addiction is discussed only with respect to online gaming. That may

lead to thinking of social skills and orientation of gamers as a source of pathological

gaming. Some studies already suggested that introvert or lonely gamers are more

susceptible to pathological gaming (Caplan, Williams & Yee, 2009; Kuss & Griffiths,

2012b). However, it is not clear whether the susceptibility is caused by situational

factors (e.g., momentary loneliness which gamers tend to overcome by

communication and participation in gaming community) or trait factors (e.g., feelings

5
The terms avatar and character are used interchangeably in the thesis.

25
of lower confidence in social situations and thus preference of online communication

for its lower commitment). Thus, the second research question is:

RQ 2: What is the role of the player’s social skills, feelings of security in social

situations and social motivation for gaming in online gaming addiction?

Online gaming is an exceptionally popular activity with millions of people engaging

in it every day. Yet, gaming addiction does not seem to be epidemic – for most

gamers the game is just a voluntary free time activity or time-killer. However, as

stated by Charlton and Danforth (2007; 2010), these groups – recreational and

addicted gamers – are not the only ones. There is also a group of highly engaged

gamers, who enjoy the gaming activity a lot. This group may seem as problematic to

an external observer, but the core components of addiction are not present and thus

this group should not be considered as pathological. However, it is not yet clear

whether addicted and engaged groups are distinct or whether they differ just on the

level of pathology; whether, e.g., the protective and risk factors are the same (and

they differ in their severity) or are really distinct. Thus, the final research question is:

RQ 3: What are the differences between highly engaged and addicted gamers in

the social predictors of excessive gaming?

26
 Methodology

The quantitative approach was predominantly used to answer the posed research

questions. Web-based survey studies were employed in these cases (Studies I, II, IV,

V). Study III is a theoretical work based on literature, although it is not a systematic

review article. More detailed information concerning data collection, measures and

analysis may be found in the respective articles.

Study I and II

Study I and II shared the same data source. The data was collected via an online

questionnaire. Players of MMORPGs were asked to complete it using advertisements

distributed on several highly popular discussion forums dedicated to World of

Warcraft and Everquest (a MMORPG with similar features as World of Warcraft).

Both the advertisement and questionnaire were in English. Data collection was carried

out for several weeks, during which the advertisement was regularly updated.

The final sample consisted of 532 completed questionnaires in case of Study I and

548 completed questionnaires in case of Study II. The difference was caused by the

diverse distribution of missing data – only those questionnaires where the key items

were filled in were included in the following analysis. The average age of participants

was 25 years. In both studies the analysis from developmental perspective was

important, hence the sample was divided based on age – adolescents 12 to 19 years

old (26%), emerging adults 20 to 26 years old (36%), adults 27 years old and older

(36%). The gender distribution was unequal, but similar to what has been usually

reported by other studies – only 17.6% (15.4% respectively) were women. About two

thirds were from Europe and one third from North America. Almost half of the

27
sample played World of Warcraft (46.2%) followed by Everquest I and II (33%). The

gamers spent on average of 27 hours a week playing.

The key scale of the Study I consisted of 12 items describing the relationship of a

player to his or her avatar. These 12 items were created based on the results of a

qualitative study by Blinka and Šmahel (2007). Various items were based on a scale

asking about positive or negative feelings towards one’s avatar (pride, shame, and

inferiority), perceptible blending or separation of the player and his or her avatar, and

the discrepancy between perceptive skills of a gamer and his or her avatar. The

respondents were asked to answer the questions using a 5-point scale varying from 1

– strongly disagree to 5 – strongly agree. The scale was subjected to a principal

component analysis with varimax rotation. Three factors with an eigenvalue greater

than 1 were obtained. Combined, the components accounted for 54.3% of the total

variance. The identified factors were: 1) identification (Cronbach alpha = .80;

accounted for 30.6% of variance) with the highest loading item I possess the same

skills and abilities as my character does (.83); 2) immersion (Cronbach alpha = .68;

accounted for 14.1 of variance) with the highest loading item Sometimes I think just

about my character while not gaming (.83); 3) compensation (Cronbach alpha = .66;

accounted for 9.6% of variance) with the highest loading item I would rather be like

my character (.71). Further, a series of Bonferonni post hoc tests was conducted

comparing the means of the factors in three age categories, between sexes, and types

of relationships the players lived in (single, engaged, married).

Separate items measuring players’ relationships to their avatars were then used in

Study II and further analysed in relation to a MMO addiction scale. The MMO

addiction scale consisted of 14 items taken from other scales measuring gaming or

technology addictions (Young; 1998; Griffiths, 2000; Beard & Wolf, 2001; Grohol,

28
2005). The scale covered themes such as cognitive and behavioural salience,

tolerance, withdrawal symptoms, interpersonal conflicts, intrapersonal conflicts, and

loss of control. The 6-point response scale ranged from 1 – rarely to 6 – always. The

scale was subjected to a principle component analysis with varimax rotation. Three

factors with eigenvalue greater than 1 were obtained, however with a somewhat

weaker third factor. Combined, the components accounted for 55.2% of the total

variance. The identified factors were: 1) salience, euphoria, and withdrawal

(Cronbach alpha = .77; accounted for 20.4% of variance) with highest loading item

Playing the game may become the most meaningful activity in my life (.73); 2) conflict

(Cronbach alpha = .76; accounted for 39.3% of the variance) with the highest loading

item How often do you neglect household chores to spend more time in-game? (.77);

3) loss of control (Cronbach alpha = .73; accounted for 16% of the variance) with the

highest loading item, How often do you try to cut down the amount of time you spend

in-game and fail? (.80). We also calculated the overall addiction score value as a

mean of scores (2.49, SD = .85). The overall Cronbach alpha of the scale was .88.

A series of Pearson’s correlations and LSD post hoc test were conducted to assess the

relationship between factors of addiction and factors of player-avatar relationship.

Study III

This book chapter provides a comprehensive overview of the state of the art (prior to

the year of publication of Study III) of knowledge of certain aspects of the Internet

Gaming Disorder. An important part of Study III is the design of a questionnaire of

addiction on online gaming. The scale partially utilized experience received from

Study II, but mostly from publications by Mark Griffiths which described a six

component model of addiction (Griffiths, 2000; Griffiths, 2005). The criteria and

distribution of items was as follows – salience (one item for behavioral and one for

29
cognitive salience), withdrawal symptoms (one item), euphoria (one item), tolerance

(two items), conflict (two items). The four-point response scale ranged from 1 – never

to 4 –very often. The scale was further used by Study IV.

Study IV

This research sampled Czech and Slovak online gamers. Participants were recruited

through discussion forums and in-game promotions with the help of server

administrators. The final sample consisted of 667 MMO gamers. The mean age was

22.7 years (SD 6.6), 84% were males. There was no significant difference in hours

spent in game between males (M = 21.7, SD = 17.4) and females (M = 23.1, SD =

18.8). The most popular game was World of Warcraft (45%).

Online gaming addiction was measured by a scale developed by Blinka and Šmahel as

described above (Study III). The online gaming addiction index was created as a

mean value of those 10 items. Cronbach’s alpha was sufficient (.76). Based on the

work of Charlton and Danforth (2007, 2010), we employed differentiation of

pathological addicted gaming and non-pathological high engagement. Both categories

may look similarly passionate and thus not differentiable at first glance, but they

differ in the amount of pathology involved which has important implications for both

research and therapy. Thus, the study viewed addiction not only as a continuum, but

also employed a categorical approach. The group of Addicted (or at-risk of addiction)

included those participants who answered often or very often in conflict criterion and

at least three other criteria of addiction (12.1% of the sample). Highly engaged

consisted of those who, unlike the first group, did not meet the criteria of addiction

but reported above average gaming time (29.5% of the sample). Finally, the category

of casual gamers was created for those who did not meet the criteria for addiction and

played below average time (58.3% of the sample).

30
The study focus was the evaluation of the role of social factors in online gaming

addiction. To access those social factors, several scales were employed. The

Perceived Social Self-Efficacy scale developed by Smith and Betz (2000) was used to

measure gamers’ confidence in social situations (Cronbach’s alpha = .94.). The Social

motivation scale consisted of 9 items measuring preference and enjoyment of in-game

socialization and inclusion, feelings of support from the community, and teamwork.

The scale was adopted from other similar constructs by Yee (2006), Hsu, Wen and

Wu, (2009), Koo, (2009). The final alpha was .78. In-game friendship quality (peer

attachment) was measured using an adapted peer section of the Parent and Peer

Attachment Scale by Armsden and Greenberg (1987). Final alpha was .90.

Pearson’s correlations were evaluated between constructs. Furthermore, a two-step

hierarchical linear regression was used to determine associations between game

addiction as a dependent variable and social self-efficacy, social motivation, and

quality of in-game friendship, and control demographic variables and play time. To

analyze differences between the groups of addicted, highly engaged and casual

gamers, a series of ANOVAs was conducted.

Study V

This study sampled Czech (and probably some Slovak) online gamers. They were

recruited via advertisements published in online and offline game journals, online

game forums and community web-sites. Gamers were asked to fill in an online

questionnaire. A total sample of 6,730 gamers was obtained. However, for the

purpose of this study a subsample of those who play MMORPGs and MOBAs was

used (e.g., those dominantly playing first-person-shooting games were excluded). The

final number of respondents used for the analysis was 4,074. The mean age was 20.8

years (SD = 5.9), 93.5 % of which were males. The most popular games were League

31
of Legends (MOBA genre, 35.2%) and World of Warcraft (MMORPG genre, 19.7%).

Female gamers spent significantly less time gaming compared to males – females M =

27.9, SD = 15.8; males M= 33.2, SD = 16.7; p < .001.

Online gaming addiction was measured by the Addiction-Engagement Scale

developed by Charlton and Danforth (2007, 2010). The reason for using a different

scale to previous study was better suitability for differentiation of pathological and

non-pathological excessive gamers. The scale consists of 24 items, 12 for high

engagement and 12 for addiction. The scale ranged from 1 to 4. The addiction

subscale includes core criteria of addiction IV – conflict, behavioural salience,

withdrawal. The engagement subscale includes peripheral criteria of addiction such as

cognitive salience, tolerance and euphoria. Internal consistency was sufficient for

both subscales – addiction Cronbach’s α = .79, high engagement Cronbach’s α = .72.

Mean scores for both addiction and high engagement were created – addiction M =

1.82, SD = .49; high engagement M = 2.50, SD = .26.

Similarly to Study IV, the focus was to study the role of social motivation and

sociability of gamers in the development of pathological and non-pathological

excessive online gaming. To measure the social motivation, the same scale as in

Study IV was used. However, exploratory analysis identified two factors – team play

(five items, Cronbach’s α = .75) and social support (three items, Cronbach’s α =

0.70). We used these factors and created two variables based on the mean scores of

the respective items. To measure players’ social attitude and orientation, the

Relationship Profile Test by Bornstein at al. (2002) was employed. The scale has 30

items and is constructed to distinguish between healthy dependency (positive social

functioning, Cronbach’s α = .67, M = 3.63, SD = .56) and two subscales representing

negative social functioning – dysfunctional detachment (Cronbach’s α = .81, M =

32
3.22, SD = .60) and destructive overdependence (Cronbach’s α = .63, M = 2.95, SD =

.75).

Pearson’s correlations were determined between constructs. Two separate regression

models were constructed using a three-step hierarchical linear regression to determine

the association between 1) online gaming addiction and 2) high engagement and

interpersonal dependency traits, social motivation, control demographics and play

styles (intensity of gaming and preferred genre).

33
 Results

The empirical findings are introduced in three sections corresponding with the research

questions. More detailed results and statistics may be found in original articles.

Research question one

As described in the measures section of the cover article, using a factor analysis Study I

examined the potential components of the player – avatar relationship. Three factors emerged.

The dominant was identification – thinking about one-self and the avatar as having similar

characteristics or even not being separate entities. This factor accounted for about 30% of the

variance of the scale. Adult gamers scored significantly less in this factor compared to

adolescent or emerging adult gamers. The score was highest in case of adolescents. Similarly,

married gamers scored significantly lower compared to single or just engaged gamers. Other

two factors, immersion (relationship with the avatar being more emotional and also making

distinction between oneself and avatar) and compensation (thinking about the avatar as being

superior and ideal) were less prevalent – they accounted for about 14 and 9 per cent of the

variance. Also, there were no age differences in the score. It is worth noting that male and

married gamers scored significantly higher in immersion.

Study II found a significant, although rather weak, relationship between the identification

factor and gaming addiction (r = .22). However, this relationship may be moderated by age.

As the study showed, it is the group of younger gamers that recorded the highest (on average)

addiction score, and this group also scored highest in the identification factor.

No relationship between the addiction score and immersion or compensation factors were

found. However, two items from the immersion factors which measured feelings (positive –

proud and negative – shame) of a player to his or her avatar showed some relationship with

the addiction score. Generally players tend to feel proud of what their avatar did in game

more often (65.8% agreed, 19.3% disagreed) than they feel shame (13% agreed, 73.4%

34
disagreed). But shame had a moderate correlation with addiction (r = .30) while pride had a

somewhat weaker one (r = .24).

In summary, player’s intensive identification with his or her gaming avatar is, to a lower

extent, associated with gaming addiction.

Research question two

Although it was not their main focus, Studies II, IV and V examined the basic demographics

and intensity of gaming in relation to gaming addiction. Study I identified younger gamers as

scoring highest in addiction generally and in the factor of salience in particular. Study IV and

V assessed the Pearson’s correlation between age and gaming addiction to -.09 or -.23

respectively. Gender played no significant or a highly negligible role in all three studies. Not

surprisingly, the single strongest significant relationship was found in gaming frequency –

Pearson’s correlation was .43 in case of Study I, .24 in Study IV, and .34 in Study V. On the

other hand, in the linear regression model age and frequency of gaming lost some of their

strength, although they remained significant. They explained about 6% of the variance of

gaming addiction in Study IV and 14% in Study V.

Study IV examined the relationship of social motivation, social self-efficacy and in-game

peer attachment to internet gaming addiction. Correlation between those social constructs was

rather high, but they differ in their relationship to gaming addiction. Whereas no significant

correlation was found in case of in-game friendship, there was a positive correlation between

addiction and social motivation (r = .27), and negative between addiction and social self-

efficacy (r = -.16). When these three variables entered linear regression as independent

variables and when controlled for demographics and intensity of gaming, they kept their

predictive value of addiction. Higher score in social motivation for gaming predicted higher

addiction score (beta = .17). Lower score in social self-efficacy and in in-game peer

attachment predicted higher addiction score (beta in both cases = -.14). It may be concluded

that higher confidence in social situations and higher interpersonal trust are protective factors

35
of gaming addiction. Although social variables accounted for a mere 5% of variance of

addiction, this is similar to the effect of demographics and frequency of gaming.

Study V also examined the relationship of social motivation (or its two factors, team play and

social support), the concept of interpersonal dependency (dysfunctional detachment,

overdependence, and healthy dependency) and gaming addiction. Both factors of social

motivation were positively related to addiction (Pearson’s correlations r = .10 for team play

and r = .13 for social support). Dysfunctional detachment and destructive overdependence

were both positively correlated with addiction (r = .29 and r = .22 respectively), while healthy

dependency was negatively correlated (r = -.18). This pattern retained its significance also in

linear regression with addiction as a dependent variable. While destructive overdependence

and dysfunctional detachment both were risk factor of addiction (in both cases the beta was

.17), healthy dependency is a protective factor (beta -.13). Interpersonal dependency

constructs accounted for about 10% of variance of addiction. Interestingly, social motivation

factors accounted only for about 1% of variance and thus their role was negligible.

In summary, it seems that personality factors associated with healthy social functioning are

protective factors of online gaming addiction, while the characteristics associated with lower

social functioning are the risk factor of addiction.

Research question three

Study IV employed a series of ANOVAs to assess differences between casual, highly

engaged and addicted gamers. Engaged and addicted gamers did not differ in social

motivation for gaming. However, the highest score in social motivation was in the group of

highly engaged gamers and they significantly differed from the group of casual gamers.

Regarding in-game peer attachment (quality of in-game friendship), the highest score was

once again recorded in the group of highly engaged gamers and they significantly differed

from both casual and addicted gamers. In case of social self-efficacy, the lowest score was in

36
the group of addicted gamers, although they significantly differed only from the casual

gamers who scored the highest.

Study V employed a different approach to study engaged and addicted gamers. Instead of

comparison of mean differences, two separate linear regressions were conducted – one for

addiction as a dependent variable (see results section for RQ2) and one for engagement as a

dependent variable. In general, in case of high engagement, the three-step linear regression

had a much lower fit compared to regression with addiction; it accounted for only 8% of

variance (compared to 25% of regression with addiction). While 4% of variance was

explained by demographics and frequency of gaming, another 4% of variance was explained

by interpersonal dependency factors. Although all three factors of interpersonal dependency

were significant predictors, actual betas were rather low. Interestingly, social motivation for

gaming accounted for less than one percentage point of variance of engagement. High

engagement was also less correlated with gaming frequency, although the correlation was

significant (r = .11 compared to r = .34 in case of addiction).

To summarize, highly engaged gamers seem to be better socially adapted compared to

addicted gamers. But the regression models worked poorly for engagement compared to

addiction. This is suggesting that there may be more factors at work in case of engagement

which this dissertation did not identify.

37
 Discussion

This thesis explored two factors associated with excessive or even addictive computer

gaming. The first falls into the rank of media features, or, in this case specifically the avatar

which is a very important and common characteristic of MMOs. The second are

characteristics on the gamers’ side which may be predictors of problematic gaming. In this

case, it was a group of variables associated with gamers’ social functioning – social

motivation for gaming, confidence in social situations, interpersonal trust and interpersonal

dependency as a general characteristic of social orientation. Moreover, this thesis compared

these social characteristics between groups of potentially pathological and non-pathological

yet excessive gamers. Although some of the results provided clear patterns, actual effect sizes

tend to be rather mediocre. Neither identification with avatar nor sociability of gamers

seemed to be decisive in the development of addictive gaming. The crucial factors may be

rather connected to gaming performance and success and thus to the rewards system (King,

Delfabro & Griffiths, 2010; Kirby, Jones & Copello, 2014). This suggests validity of

the behavioural addiction concept, often explained through the brain dopamine system

responsible for learning and reward anticipation (Potenza, 2008; Brewer & Potenza,

2008). However, obtained results in this thesis bring context and understanding of

which factors are either increasing or decreasing the chance of pathology to emerge.

Avatar’s role in online gaming

The results of Study I and II showed that there is a mild connection between high player

identification with his or her avatar and high addiction score. This aspect of identification

included thinking about the avatar as possessing similar characteristics as are the gamer’s.

Surprisingly, the immersion factor was not associated with addiction. Immersion included

salience, i.e. frequent thinking about the game and the avatar when not gaming. Salience is

considered as one of the addiction factor (Griffiths, 2005), although, according to Charlton

38
and Danforth (2007, 2010) cognitive salience represents a peripheral rather than a core

criterion.

One of the potential explanations why addiction is related to avatar identification rather than

to immersion with the avatar may be the gamers’ motives behind the latter case. Levelling, or

the progressive gaining of power of the avatar, is a common feature of MMOs. As such, it is

rather connected to a gamer’s feelings of success and achievement (Yee, 2006). Indeed, the

achievement factor has been found to be more related to gaming addiction than the immersion

factor (King, Delfabro, Griffiths, 2011) and also more typical for younger gamers (Yee,

2006). In this respect, the results of this thesis are consistent with literature. On the other

hand, some studies suggest that dissimilar avatars and feelings of discrepancy between

oneself and the avatar are more typical for those gamers who show lower life satisfaction or

even depression (Trepte & Reinecke, 2010), both also being predictors of gaming addiction

(Mehroof & Griffiths, 2010; Gentile et al., 2011). There may be some moderating effects

of hidden variables which this thesis and its studies did not identify. Nevertheless, it may be

concluded that avatars as a game feature and the player’s relationship to an avatar do not have

a strong potential to explain gaming addiction. But as Study I suggests, the relationship may

be perceived by gamers as very important. An avatar may even represents some of gamer’s

complexes (Blinka & Šmahel, 2007) and it may be used in therapy, especially in

psychodynamic therapy, as a way to get to deeper feelings and facilitate the therapeutic

process.

Social factors of gaming addiction

Gaming addiction is typically associated with online games, not offline ones. There are two

main differences between offline and online games. First, offline games are usually played

significantly less intensively than online games (Király et al., 2014) and online games are a

social place while offline are not (Cole & Griffiths, 2007). Studies II, IV, V showed a

moderate correlation of addiction and intensity of gaming. However, such correlations may be

surprisingly low, as addiction and large amounts of played time are commonly or popularly

39
understood of as being basically the same thing. The results suggest a relationship but not

unity between these two notions, and thus intensity of gaming should not be considered as

factor of addiction per se.

The tendency to spend larger amounts of time in game increases with in-game social

activity and number of in-game friends (Cole & Griffiths, 2007), which may in turn

increase problematic behaviour. As Peters and Malesky (2008) report – a higher

amount of time spent in-game predicts a higher tendency of gaming addiction.

The relationship between social factors and gaming addiction is slightly more problematic.

Theoretically, there may be several hypotheses how social functioning may influence

excessive online gaming. It may be a form of compensation for insufficient social

opportunities in the gamer’s close environment (see case of Jeremy in the introduction,

Griffiths, 2010) or it may be a form of escapism in case of socially anxious individuals (Lo,

Wang, Fang, 2005).

However, social motivation for gaming, i.e. seeking of social support, was not or only very

poorly associated with addiction (Study IV and V). This finding is supported by some other

quantitative studies (Caplan et al., 2009, Kardefelt-Winther, 2014) but disproved by some

qualitative studies. Karlsen (2011) or Haagsma with colleagues (2013) found that, in gamers’

own words, it is the other fellow gamers who keep them playing. Thus, it may be the feeling

of social obligation that plays an important role here. Social motivation for gaming, as

measured in Study IV and V (and also, e.g. Yee, 2006 and most other studies on motivation

for online gaming), represents a conscious choice and preference rather than an inner and

deep drive and thus its explanatory value is limited. When we look at the gamers’ social

abilities and basic social orientation, the picture we get is more clear. Socially skilled,

confident and generally well socially adapted individuals are less inclined to pathological

gaming. At the same time socially less adapted individuals are more susceptible to

pathological gaming (Study IV and V). Problematic patterns of interpersonal dependency

40
have been shown to be risk factors of psychological distress including loneliness, lower self-

esteem, all being risk factors of online gaming addiction as well (Kuss & Griffiths, 2012b).

Addiction and engagement – distinct or continuum?

Generally, highly engaged but non-pathological gamers tend to show healthier signs of social

functioning. They tent to show higher levels of trust in their virtual in-game friends (Study

IV). Although having a high number of virtual friends may be considered by popular media

as a proof of unnatural and unhealthy social relationship, it was the group of addicted gamers

who showed the lowest trust or attachment in their in-game peers. Similarly, studies by Trepte

and Reinecke (2012) and Šmahel and his colleagues (2012) claim that closer or more frequent

relationships with those online is actually a sign of healthier psychosocial functioning. The

sociability of gamers functions rather similarly to real-life sociability and thus is independent

of the environment – it does not matter whether one is communicating offline or online.

This fact suggests that engagement and addiction are not just different stages of one

continuum. Rather, they tend to be distinct. Groups of highly engaged and addicted gamers

tend to have different characteristics to some extent. Study IV and V support the original

claims of Charlton and Danforth (2007, 2010) about this distinction. However, the model

employed by Study V had a very low explanatory value for engagement itself. The model

consisted of demographics and variables measuring social functioning and worked

significantly better in the case of addiction. That means that we do not know very well what

non-pathological yet highly engaged gaming is and what kind of gamers tend to play a lot in

this way and whether such gaming puts individuals into some other type of psychosocial risks

or whether it is just entertainment without any negative outcomes worth studying. Potentially,

with proliferation of gaming into society (e.g., prominent games are becoming highly-popular

“e-sports”), we can expect not only risks but also some opportunities emerging in the close

future.

41
Limitations and future directions

The biggest and most important limitation of the thesis comes from the fact that all four

empirical studies were designed and conducted in a similar way. All data come from a self-

selected non representative sample of MMO gamers recruited via online advertisements. This

probably limited variance of the sample and thus the obtained answers. A nation-wide

representative sample would provide more accurate data. But with the exception of

representative adolescent samples (recruited in schools), I am not aware of any other study

that would study gaming addiction on a representative sample of adult population. This

problem should be addressed in future research.

Another limitation of the thesis comes from the cross-sectional design of all empirical studies.

Thus, although I use terms like predictors of addiction for simplification, one cannot be sure

of the actual direction of the relationships. Longitudinal studies would be much better in

assessing the direction of casual links. Although some longitudinal studies have been

conducted in the field (e.g. Gentile et al., 2011; Leemens et al., 2011), the

overwhelming majority of research is cross-sectional.

The last main limitation comes from the way the key construct, gaming addiction, was

measured. Three studies used three different scales. Although their logic was similar,

there may be differences decreasing comparability. Also, none of the studies had a

clear cut-off point which would say what score in the scale is pathological. Again for

simplification, I used terms like “addicted gamers”, even though “at risk of addiction”

would be more precise. For future research, it is essential to test and assess the

addiction scale on a clinical population of those who showed signs of problematic

gaming. Quantitative, qualitative, and case studies on clinical population are very rare

and this should be one of the closest goals of research in this field. There is a body of

evidence suggesting that internet gaming addiction does exist, but we still do not

42
know for certain whether we are instead merely over-pathologizing the phenomenon

of MMO gaming.

43
 Literature

American Psychiatric Association. (2013). Diagnostic and Statistical Manual of

Mental Disorders: DSM 5. Books4US.

Armsden, G. C., & Greenberg, M. T. (1987). The Inventory of Parent and Peer

Attachment: Relationships to well-being in adolescence. Journal of Youth and

Adolescence, 16(5), 427-454.

Beard, K. W., & Wolf, E. M. (2001). Modification in the proposed diagnostic criteria

for Internet addiction. CyberPsychology & Behavior, 4(3), 377-383.

Bessière, K., Seay, A. F., & Kiesler, S. (2007). The ideal elf: Identity exploration in

World of Warcraft. CyberPsychology & Behavior, 10(4), 530-535.

Blinka, L., & Smahel, D. (2007). Role-playing" hry v kontextu analytické

psychologie [Role-playing games in the context of analytical psychology].

Československa psychologie, 51(2), 169.

Blinka, L. (2013) The good and the bad of the Internet. Studying subjective well-being

as an outcome of young people‘s online practices. Tartu: University of Tartu

Press.

Blinka, L. (2014). Nadměrné užívání a závislost na internetu [Excessive and addictive

internet use]. In Ševčíková, A. (Ed.), Děti online aneb vybraná rizika

používání internetu [Children online: Selected risks of internet use]. Praha:

Grada Publishing.

Blinka, L., Škařupová, K., Ševčíková, A., Wölfling, K., Müller, K. W., & Dreier, M.

(2015). Excessive internet use in European adolescents: what determines

44
 differences in severity? International Journal of Public Health, 60(2), 249-

256.

Blinka, L. (2015a). Úvod do studia závislostí na internetu [Introduction to study of

online addictions]. In Blinka, L. (ed) Online závislosti [Online addictions], pp

11-20. Praha: Grada Publishing.

Blinka, L. (2015b). Závislosti na online počítačovém hraní [Addiction to online

gaming]. In Blinka, L. (ed) Online závislosti [Online addictions], pp 111-130.

Praha: Grada Publishing.

Bornstein, R. F., Geiselman, K. J., Eisenhart, E. A., & Languirand, M. A. (2002).

Construct Validity of the Relationship Profile Test Links With Attachment,

Identity, Relatedness, and Affect. Assessment, 9(4), 373-381.

Brewer, J. A., & Potenza, M. N. (2008). The neurobiology and genetics of impulse

control disorders: Relationships to drug addictions. Biochemical

Pharmacology, 75(1), 63-75.

Caplan, S., Williams, D., & Yee, N. (2009). Problematic Internet use and

psychosocial well-being among MMO players. Computers in Human

Behavior, 25, 1312-1319.

Chak, K., & Leung, L. (2004). Shyness and locus of control as predictors of internet

addiction and internet use. CyberPsychology & Behavior, 7(5), 559-570.

Charlton, J. P., & Danforth, I. D. (2007). Distinguishing addiction and high

engagement in the context of online game playing. Computers in Human

Behavior, 23, 1531-1548.

45
Charlton, J. P., & Danforth, I. D. (2010). Validating the distinction between computer

addiction and engagement: online game playing and personality. Behaviour &

Information Technology, 29, 601-613.

Chou, T. J., & Ting, C. C. (2003). The role of flow experience in cyber-game

addiction. CyberPsychology & Behavior, 6(6), 663-675.

Cole, H., & Griffiths, M. D. (2007). Social interactions in massively multiplayer

online role-playing gamers. CyberPsychology & Behavior, 10(4), 575-583.

Dreier M., Wölfling K., Beutel M. E. (2014). Internetsucht bei Jugendlichen [Internet

addiction in youth]. Monatsschr Kinderheilkd, 162, 496–602.

Entertainment Software Association (2013). Essential Facts about the computer and

video game industry. http://www.theesa.com/facts/pdfs/esa_ef_2013.pdf

Gentile, D. A., Choo, H., Liau, A., Sim, T., Li, D., Fung, D., & Khoo, A. (2011).

Pathological video game use among youths: a two-year longitudinal study.

Pediatrics, 127(2), 319-329.

Grant, J., Atmaca, M., Fineberg, N. A., Fontenelle, L. F., Matsunaga, H., Veale, D., ...

& Stein, D. (2014). Impulse control disorders and “behavioural addictions” in

the ICD-11. World Psychiatry 13(2), 125-127.

Griffiths, M. (1996). Internet" addiction": an issue for clinical psychology? In

Clinical Psychology Forum (pp. 32-36).

Griffiths, M. (2000). Does Internet and computer "addiction" exist? Some case study

evidence. CyberPsychology & Behavior, 3(2), 211-218.

Griffiths, M.D. (2005). A 'components' model of addiction within a biopsychosocial

framework. Journal of Substance Use, 10, 191-197.

46
Griffiths, M. D. (2010). The role of context in online gaming excess and addiction:

Some case study evidence. International Journal of Mental Health and

Addiction, 8(1), 119-125.

Grohol JM. (2005). Internet addiction guide. www.psychcentral.com/netaddiction

Haagsma, M. C., Pieterse, M. E., Peters, O., & King, D. L. (2013). How gaming may

become a problem: A qualitative analysis of the role of gaming related

experiences and cognitions in the development of problematic game behavior.

International Journal of Mental Health and Addiction, 11(4), 441-452.

Helsper, E., Kalmus, V., Hasebrink, U., Sagvari, B. & de Haan, J. (2013) Country

classification: Opportunities, risks, harm and parental mediation

http://eprints.lse.ac.uk/52023/

Hsu, S. H., Wen, M. H., & Wu, M. C. (2009). Exploring user experiences as

predictors of MMORPG addiction. Computers & Education, 53, 990-999.

Hussain, Z., & Griffiths, M. D. (2009). Excessive use of massively multi-player

online role-playing Games: A pilot study. International Journal of Mental

Health and Addiction, 7(4), 563-571.

Kalmus, V., Sibak, A., Blinka, L. (2013). Internet and Child Well-Being. In A. Ben-

Arieh, F. Casas, I. Frønes, J.E. Korbin (Eds.), Handbook of Child Well-Being,

pp 2093-2133. Dordrech: Springer.

Kardefelt-Winther, D. (2014). Problematizing excessive online gaming and its

psychological predictors. Computers in Human Behavior, 31, 118-122.

Karlsen, F. (2011). Entrapment and near miss: A comparative analysis of psycho-

structural elements in gambling games and massively multiplayer online role-

47
 playing games. International Journal of Mental Health and Addiction, 9(2),

193-207.

Király,O., Nagyhyörgy, K., Griffiths, M.D., Demetrovics, Z. (2014). Problematic

online gaming. In Kenneth Paul Rosenberg and Laura Curtiss Feder (eds)

Behavioral addictions: Criteria, Evidence, and Treatment. Academic Press.

Kirby, A., Jones, C., & Copello, A. (2014). The impact of massively multiplayer

online role playing games (MMORPGs) on psychological wellbeing and the

role of play motivations and problematic use. International Journal of Mental

Health and Addiction, 12(1), 36-51.

King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2010). The role of structural

characteristics in problematic video game play: A review. Cyberpsychology:

Journal of Psychosocial Research on Cyberspace, 4(1), article 6.

King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2011). The role of structural

characteristics in problematic video game play: An empirical study.

International Journal of Mental Health and Addiction, 9(3), 320-333.

Ko, C. H., Liu, G. C., Hsiao, S., Yen, J. Y., Yang, M. J., Lin, W. C., Chen, C. S.

(2009). Brain activities associated with gaming urge of online gaming

addiction. Journal of psychiatric research, 43(7), 739–747.

Ko, C. H., Yen, J. Y., Yen, C. F., Chen, C. S., Chen, C. C. (2012). The association

between Internet addiction and psychiatric disorder: A review of the literature.

European Psychiatry, 27(1), 1-8.

48
Koo, D. (2009). The moderating role of locus of control on the links between

experiential motives and intention to play online games. Computers in Human

Behavior, 25, 466-474.

Koulouglioti, C., Cole, R., & Kitzman, H. (2008). Inadequate sleep and unintentional

injuries in young children. Public Health Nursing, 25(2), 106-114.

Kuss, D. J., & Griffiths, M. D. (2012a). Internet and gaming addiction: a systematic

literature review of neuroimaging studies. Brain Sciences, 2(3), 347-374.

Kuss, D. J., & Griffiths, M. D. (2012b). Internet gaming addiction: A systematic

review of empirical research. International Journal of Mental Health and

Addiction, 10, 278-296.

Lemmens, J. S., Valkenburg, P. M., & Peter, J. (2011). Psychosocial causes and

consequences of pathological gaming. Computers in Human Behavior, 27,

144-152.

Lo, S. K., Wang, C. C., & Fang, W. (2005). Physical interpersonal relationships and

social anxiety among online game players. CyberPsychology & Behavior,

8(1), 15-20.

Mehroof, M., & Griffiths, M. D. (2010). Online gaming addiction: The role of

sensation seeking, self-control, neuroticism, aggression, state anxiety, and trait

anxiety. Cyberpsychology, Behavior, and Social Networking, 13(3), 313-316.

Müller, K. W., Duven, E., Giralt, S., Beutel, M. E., Dreier, M., & Wölfling, K.

(2012). To game or to gamble? Empirical comparison of predictors of

computer game addiction and pathological gambling among adolescents.

European Psychiatry, 27, 1.

49
Peters, C. S., & Malesky Jr, L. A. (2008). Problematic usage among highly-engaged

players of massively multiplayer online role playing games. CyberPsychology

& Behavior, 11(4), 481-484.

Potenza, M. N. (2008). The neurobiology of pathological gambling and drug

addiction: an overview and new findings. Philosophical Transactions of the

Royal Society B: Biological Sciences, 363, 3181-3189.

Rodman, G., & Fry, K.G. (2009). Communication technology and psychological

wellbeing: Yin, Yang, and the golden mean of media effects. In Y. Amichai-

Hamburger (Eds.), Technology and Psychological Well-being, pp. 9–33.

Cambridge: Cambridge University Press.

Shotton, M. A. (1991). The costs and benefits of ‘computer addiction’. Behaviour &

Information Technology, 10(3), 219-230.

Šmahel, D., & Blinka, L. (2012). Excessive internet use among European children. In

Livingstone, S., Haddon, L., Görzig, A. (eds). Children, risk and safety on the

internet: Research and policy challenges in comparative perspective, pp 191-

204. Policy Press.

Smahel, D., Brown, B. B., & Blinka, L. (2012). Associations between online

friendship and Internet addiction among adolescents and emerging adults.

Developmental psychology, 48(2), 381.

Smith, H. M., & Betz, N. E. (2000). Development and validation of a scale of

perceived social self-efficacy. Journal of Career Assessment, 8, 283-301.

Soper, W. B., & Miller, M. J. (1983). Junk-time junkies: An emerging addiction

among students. School Counselor, 31(1), 40-43.

50
Thalemann, R., Wölfling, K., & Grüsser, S. M. (2007). Specific cue reactivity on

computer game-related cues in excessive gamers. Behavioral Neuroscience,

121(3), 614.

Trepte, S., & Reinecke, L. (2015). Avatar creation and video game enjoyment.

Journal of Media Psychology, 22(4), 171-184.

Valkenburg, P. M., & Peter, J. (2013). The differential susceptibility to media effects

model. Journal of Communication, 63(2), 221-243.

Valkenburg, P. M., Peter, J., & Walther, J. B. (in press). Media effects: Theory and

Research. Annual Review of Psychology, 67 (2016).

Williams, D., Yee, N., & Caplan, S. E. (2008). Who plays, how much, and why?

Debunking the stereotypical gamer profile. Journal of Computer‐Mediated

Communication, 13, 993-1018.

Wood, R. T. (2008). Problems with the concept of video game “addiction”: Some

case study examples. International Journal of Mental Health and Addiction,

6(2), 169-178.

Yee, N. (2006). The demographics, motivations, and derived experiences of users of

massively multi-user online graphical environments. Presence: Teleoperators

and Virtual Environments, 15, 309-329.

Young, K. S. (1998). Caught in the net: How to recognize the signs of internet

addiction--and a winning strategy for recovery. John Wiley & Sons.

Yee, N. (2002). Ariadne. Understanding MMORPG Addiction.

http://www.nickyee.com/hub/addiction/addiction.pdf.

51
Zhou, Y., Lin, F. C., Du, Y. S., Qin, L. D., Zhao, Z. M., Xu, J. R., & Lei, H. (2011).

Gray matter abnormalities in Internet addiction: A voxel-based morphometry

study. European Journal of Radiology, 79(1), 92-95.

52
 Study I

Blinka, L. (2008). The relationship of players to their avatars in MMORPGs:

differences between adolescents, emerging adults and adults.

Cyberpsychology: Journal of psychosocial research on cyberspace, 2 (1).

53
54
55
56
57
58
59
 Study II

Šmahel, D. Blinka, L., & Ledabyl, O. (2008). Playing MMORPGs:

Connections between Addiction and Identifying with a Character.

CyberPsychology & Behavior, 11, (6), 715-718.

60
61
62
63
64
 Study III

Blinka, L., & Šmahel, D. (2011). Addiction to online role-playing games. In:

Young, K.S. & de Abreu, C.N. (Eds.) Internet Addiction: A Handbook and

Guide to Evaluation and Treatment (74-90). Hoboken: John Wiley & Sons

65
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

CHAPTER 5

Addiction to Online
Role-Playing Games
LUKAS BLINKA and DAVID SMAHEL

M
ASSIVE MULTIPLAYER online role-playing games (MMORPGs) are one
example of Internet applications that have become increasingly pop-
ular. These games are played in online worlds, where an individual
acts through a created virtual personality, a so-called avatar. The popularity
of these games can be seen from data on the most popular MMORPG, World
of Warcraft, which has over 11.5 million official subscribers. Based on data
from the Entertainment Software Association (2007), the number of online
gamers doubled between 2006 and 2007. MMORPGs are a type of so-called
massively multiplayer online (MMO) game; MMOs include, for example, the
well-known game Second Life. MMOs are not always games in the strict sense
of the word; for example, users of Second Life often claim that “Second Life
is not a game but a second life.” According to some statistics, MMO games
were played by 48 million players in April 2008 (Voig, Inc., 2008).
The forerunners of MMORPG games were so-called multiuser dungeons
(MUDs), which have inspired many books about virtual worlds as well as
researchers (Kendall, 2002; Suler, 2008; Turkle, 1997, 2005). The main difference
is that MUDs ran in text form while current MMORPG games are worlds
running in high graphic resolution. It is not clear what the differences between
text MUDs and the current graphic MMORPG games are concerning the
impact on players, but what we know for sure is that MMORPGs are played
by a much larger number of players today than MUDs ever were.
In this chapter we primarily deal with MMORPG games that have proven
to be a very significant free-time activity of some of today’s adolescents,

The authors acknowledge the support of the Faculty of Social Studies, Masaryk University.

73

66
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

74 INTERNET ADDICTION

younger adults, and adults (e.g., Ng & Wiemer-Hastings, 2005; Smahel, Blinka,
& Ledabyl, 2008). At the same time, MMORPGs are often presented as being
potentially dangerous due to possible addiction (Rau, Peng, & Yang, 2006;
Wan & Chiou, 2006a, 2006b), and as such they attract a lot of attention of the
scientific community, the general public, and media.
In other parts of the chapter, we will also list examples from 16 interviews
with MMORPG players that we carried out in May 2009. The semistructured
interviews with 12 men (aged 15 to 28) and four women (aged 15 to 19) was
carried out face-to-face in seven cases and online through Skype or ICQ in nine
cases. The interviews were analyzed with use of grounded theory. Samples
from these interviews have been included in the discussion to complement
the obtained results.
In this chapter we first deal with a description of the virtual worlds in
MMORPGs, so that the reader can get a better idea of what these worlds look
like. We then follow with showing who the players of these games are and
their motivations for playing. Afterward we present the concept of addiction
in the context of MMORPGs and factors facilitating addiction both on the
side of individual players and on the side of the game. We also present a short
questionnaire that can be used for basic diagnostics of online games addiction
symptoms and its following evaluation based on interviews with players. In
the last section we discuss the phenomenon of self-perceived addiction (i.e.,
a MMORPG player’s perception of potential addiction).

W H AT A R E M M O R P G s?
MMORPGs are usually fantasy role-playing games played on the Internet,
where several thousand various players from all around the world are present
at the same time. A player controls his or her character, which can fulfill vari-
ous tasks, advance its capabilities, and interact with other players’ characters.
A player can perform a wide range of activities, from building his or her
avatar’s character to interacting with other players in both positive ways
(conversation) and negative ways (aggression). The motivation for playing
MMORPGs also varies (as described further), as well as manners of playing
these games (e.g., Yee 2006b). A player can explore a vast world, which is per-
sistent in its character—it remains in existence even when the player logs off.
This world is consistently in development, disregarding the presence of the
player, which in a certain sense pressures the player to stay in touch with the
virtual world. If players are absent for a longer period of time, they become
out of touch with the virtual world and lose their influence and power to
affect the world. The player also loses power compared to fellow players who
are playing more often and advancing faster. In the words of an 18-year-old
male player: “ ThemoreI want toimprove, themoretimeI should invest in thegame.
That’s how the game works, unfortunately, and I always keep thinking that I could,
that I should spend even moretime online and do things now that I would otherwise

67
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

Addiction to Online Role-Playing Games 75

do tomorrow.” Success in the game is often closely tied with long-term and
everyday presence in the game.
It is the unbounded scope of the world, the practical impossibility of finish-
ing the game, and the emphasis on communication and cooperation with other
players that make MMORPGs different from traditional computer games, and
it is also the reason for considering it a whole new environment and subject.
The biggest difference between MMORPGs and other computer games is no-
table in the intensity of play: MMORPGs are played 25 hours per week on
average, whereas other computer games and video games are played over
20 hours per week by only 6% of players, and 84% of players spend less than
six hours per week playing (Ng & Wiemer-Hastings, 2005). The high intensity
of play is apparently the main factor for considering gaming problematic and
potentially addictive. It remains an open question, however: What actually
keeps players in the game for such long periods of time? Are they necessarily
addicted due to their long stay in the game, or could there be some other
explanation? Now we will have a closer look at who plays MMORPGs and
how much time they spend in the virtual world.

W H O P L AY S A N D H O W M U C H ?
There exists a generally established image of a typical gamer as a young
or adolescent man. Some findings (e.g., Griffiths, Davies, & Chappell, 2003;
Smahel, Blinka & Ledabyl, 2008; Yee, 2006b), however, disprove this archetype:
The average age of MMORPG players is generally around 25 years, and
there are more adult than adolescent players. Most often the gamers are
men—their representation exceeds 90%, especially for younger players. The
representation of women increases with age, and it reaches approximately 20%
among adult gamers (Griffiths, Davis, & Chappell, 2003). One notable fact is
that the average age of female gamers (approximately 32 years) is significantly
higher than the average age of male gamers. It seems that female players
usually become involved in the game through their partners (Yee, 2006a).
Female gamers of adolescent age are very rare. The increase in their numbers
during emerging adulthood and young adulthood suggests that they were
introduced to the game by their social surroundings (usually male partners).
At a first glance, the numbers on intensity of play are quite interesting.
As has been noted, the average intensity of play per week is approximately
25 hours (Griffiths, Davies, & Chappell, 2004; Smahel, Blinka, & Ledabyl,
2008); 11% of players, however, spend over 40 hours per week in the game
world, which corresponds to a full-time job or high school attendance (Ng &
Wiemer-Hastings, 2005); 80% of gamers play over eight hours in one session
at least from time to time (Ng & Wiemer-Hastings, 2005); and 60% play over
10 hours in one session (Yee, 2006a). One of the gamers in our interviews noted
that he has played 30 hours in one session. It can thus be said that MMORPGs
present, at least from a time perspective, a very significant part of the lives
of their players—since the intensity of play limits available time for other

68
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

76 INTERNET ADDICTION

activities. Furthermore, this is apparently not just a short episode in the lives
of the players. Griffiths, Davies, & Chappell (2004) found out that the average
time of play is approximately two years for adolescent players (aged up to 20)
and 27 months for older players. As for intensity of play, adolescents tend to
play more than their adult counterparts (26 hours per week for those under
20 compared to 22 hours for those over 26). However, the group of players
aged 20 to 22 spends the most time playing online games, with an average
of almost 30 hours per week. Based on Cole & Griffiths (2007), women play
significantly less, namely up to 10 hours per week less than men.
A very low representation of women among MMORPG players is unusual
compared to other online games. Based on data from the Entertainment Soft-
ware Association (2008), women form 44% of all online players (i.e., almost
half). Women, however, prefer puzzle and card games online, which represent
half of all online games. The data suggest that online role-playing games such
as World of Warcraft are played by approximately 11% of online players. This
group of players, however, plays very intensively, which is why this small
group is so significant. Games with low intensity of play are usually con-
sidered only a type of relaxation, whereas MMORPGs generally have more
complex motivations for play. Let’s have a closer look at them now.

M O T I VA T I O N F O R P L AY I N G M M O R P G s
MMORPGs are relatively complex virtual worlds, which offer wide and vary-
ing possibilities for entertainment. Yee (2006b) summarized the significant
components of play into three main categories: achievement, social, and im-
mersion, with a range of possible dimensions. The first component, achieve-
ment, includes management of game mechanisms. MMORPGs are relatively
complicated, and it usually takes a period of time for players to become fa-
miliar with the game mechanisms. Optimization of these game mechanisms
is then often the topic of discussion forums on the Internet, where play-
ers also tend to spend a lot of time. Achievement includes the notion of
advancement—the progression of a player’s avatar, both in experience lev-
els (leading to new abilities) and by obtaining better equipment. Overall this
gives more power to the player and a higher status in the game world. The last
part of the achievement component is competition—the process of competing
with other players.
The second MMORPG component comprises the social dimension of vir-
tual worlds. Online gaming is social in principle; solo play is allowed but
not encouraged: “ M M ORPGs are mainly about people—when I started playing,
it was absolutely fantastic.” Players gather into larger groups, usually called
“guilds,” although the terminology is different in certain online games. Play-
ing together with others then leads to a certain social commitment. Seay
et al. (2003) showed that players in guilds play four hours per week more
than unguilded players, on average. The game itself also serves as a chat;
players communicate not only about the game but about all sorts of other

69
 Addiction to Online Role-Playing Games 77

topics as well, via both text messages and voice chat. The Internet also sup-
ports self-disclosure of players. Yee (2006b) notes that 23% of male and 32% of
female players at some time disclosed personal and intimate information in
the game. This openness, however, varies with age. Whereas older individu-
als are mostly careful, over one-half of adolescents speak about their personal
real-life experiences in the game. Meeting with a fellow player in real life is
then more common for women (almost 16%) than for men (5%). A higher
tendency to meet in real life is found in older players. Another thing to note
is that, especially for adolescents, intensive playing can have a negative ef-
fect on offline social life—younger players have a higher tendency to immure
themselves in the game.
The third motivation component is immersion. A shared element of all
MMORPGs is a complex and vast world; a wide range of players thus focuses
on exploring this world (mostly based on the fantasy genre). Immersion also
occurs when identifying with one’s avatar—adjusting his or her appearance,
expanding his or her equipment, role-playing, and so on.
All of these components are in some way present in every MMORPG, and
various players prefer each component in varying degrees. Griffiths et al.
(2004), for example, claimed that violence in games is preferred by adolescent
players. The preference of violence, aggression, and competition in games de-
creases with age, and women also have a lower preference for these notions.
The social component of the game is preferred more by adult players. Some
players with a high potential for addictive behavior can then consider the
game their “second life,” citing an 18-year-old player who spends 70 hours
per week in the game: “ The game in itself comprises all sorts of interests, as if
it almost was a second life. You can do anything you could imagine there, perhaps
everything except for sex. I can even fish there.” For these types of players, all the
aforementioned motivations combine together. A less frequent but perhaps
even more interesting motivation is the targeted damaging of other players’
avatars, as described by a 19-year-old man playing 65 hours per week: “ I usu-
ally play to causeharm = I liketomurder, steal, and doanything immoral in thegame
(it helps merelax at theend of theday).” This player does not communicate with
others, but the game rather functions as a manner of relaxation for him, and as
he himself states: “ I can’t imaginebeing mean in real life. I’d say that in thisrespect,
the game allows me to try unexplored possibilities.” In this context we can then
consider internal psychological motivations for playing MMORPGs, includ-
ing psychological identification with one’s avatar and the virtual representa-
tion of a player. The deep psychological motivations for a player who uses
MMORPGs for stress relief are more likely a question for clinical interviews.
The avatar itself is an important game element; players, however, have var-
ious approaches to their avatars. Adolescents have the Largent tendency not
to distinguish between themselves and their avatars (Blinka, 2008). Thus they
pay less attention to differences between themselves and their game avatars,
and consider success in the game (e.g., in confrontation with other avatars)
their personal success. This apparently could be related to the origination

70
71
72
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

80 INTERNET ADDICTION

FA C T O R S O F A D D I C T I O N I N T H E G A M E
It remains an open question whether any Internet application can be consid-
ered a source of problematic behavior, in this case addiction to the Internet.
Nevertheless, the number of players and the intensity of play of MMORPGs
do invite such suspicions. Several studies have pinpointed the main factor of
this as the flow phenomenon, which explains the intensity of play and following
addiction (Chou & Ting, 2003; Rau, Peng, & Yang, 2006; Wan & Chiou, 2006a).
Flow is usually described as a difficult activity requiring a certain level of skill
and effort, usually related to some form of competition with others. Although
it is a subjective phenomenon, its creation is related to characteristic traits of
MMORPGs—online social communication and a permanent system of tasks,
rewards, and feedback (the role-playing factor). The carried-out activity also
blends with one’s consciousness—the player fully focuses only on the game
and does not pay attention to anything else, and the game then feels “smooth.”
During flow, other sensations are usually suppressed or completely ignored;
these include pain, tiredness, hunger, thirst, and excretion (players often play
over eight hours continuously). A typical indicator is an altered perception of
time; the activity feels like a several-minutes-long episode, whereas in reality
it could have been several hours long. Interruption while playing in such a
state is considered very unfavorable and often is the source of conflicts be-
tween players and their social surroundings. Concentration on playing the
game, together with the altered perception of time and curiosity, leads to ex-
cessive play (Chou & Ting, 2003). Time is not one of the factors of addiction;
however, there exists a moderate association between time spent in the game
and addictive behavior (Smahel et al., 2008). The amount of time spent in
the game is thus related to potential addiction; excessive time spent playing,
however, does not mean that a player is addicted.
Rau, Peng, and Yang (2006), for example, claim that experienced as well
as inexperienced players have difficulties leaving the game due to the flow
effect and the related alteration of time perception—they are not aware of the
length of their play, because they are consumed by the game. The results also
indicate that inexperienced players can enter flow faster (already in the first
hour of play), whereas more experienced players need more time. A similarity
arises with one of the factors of addiction—increasing tolerance, meaning the
player needs an ever increasing amount of time in the game to achieve the
sought sensations. As noted by Wan and Chiou (2006a), the relationship of
the flow phenomenon to addiction to online games might not be direct and
definite. It even seems that sometimes it could be reversed: The authors state
that the players with symptoms of addiction experience flow less often. The
flow state is strongest and most frequent when a player begins playing. The
more intensively and longer one plays, the lower is the frequency of flow.
It can even be assumed that truly addicted players sometimes do not have
positive sensations from the game, as stated by a 25-year-old man in our
research: “ You’reso bored that you’renot interested in doing anything, but you still

73
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

Addiction to Online Role-Playing Games 81

keep playing. When you play World of Warcraft a lot, it becomes your second life.
So whether you decideto bebored outsideor in WoW, it basically changes nothing.”
In this sense, the game is the place where a player may be, after all, less
bored than in real life. The game is empty, but real life is even emptier. We
can conjecture that these sensations could be related to depressions. Flow
is probably a significant factor for the initial engagement of players rather
than for addiction. The development of pathological play requires suitable
conditions on the player’s side.
It can also be said that the extent of MMORPG play is partially caused
by the social dimension of these games, which break the stereotype of an
addicted player as a lonely, unsociable individual or a nerd (e.g., Kendall,
2002). On the contrary, studies have shown that potential addiction positively
correlates with the social aspect of online games. Based on Cole and Griffiths
(2007), approximately 80% of players play with their real-life friends. About
75% have found good friends in the online game, and 43% have met them
face-to-face. As confirmed by an 18-year-old male player: “ The community of
players is important; it allows us to create our reputations as players over time and
reminds us what wehaveachieved over thepast years.”
We have demonstrated a moderate correlation (r = 0.44) in our research be-
tween addiction and the preference of the MMORPG social group—the more
players claimed they felt “more important and more respected in the virtual
group,” the more factors of addiction they displayed (Smahel, 2008). In total,
31% of all players agree that they feel more important in the MMORPG social
group than in real-life social groups. This number is higher for adolescents
aged 12 to 19, where a whole 50% agree compared to 35% of young adults
(aged 20 to 26) and 16% of adults (above 27). Adolescents thus have a higher
tendency to prefer the virtual group, which is also related to their higher
tendency for addictive behavior.
MMORPGs seem to be a considerably social activity. On one hand it is
positive that the game does not lead players into social isolation (it does the
opposite, actually), but on the other hand the social network keeps players
playing for a much longer time. A certain role is also played by the dissocia-
tion of social ties (Smahel et al., 2008)—the tendency toward addiction grows
with the tendency of dividing friendships originating in the virtual world
from those originating in real life. It can be said that the more players divide
their virtual life from their real one, the greater is their tendency toward ad-
diction. The most endangered group is the age group of adolescents, which
also displays the greatest tendency toward dividing real life from the virtual
world. It remains an open question whether we are not witnessing various ap-
proaches to reality for which we now have only a pathological interpretation.
Is it correct to consider someone’s preference for a virtual life pathological if
the person at the same time lives a normally functioning life in the real world?
That is, unless these two facts are mutually exclusive.
A certain role is also played by the infinity of MMORPG games—it is
basically impossible to finish these games, since they are continuously under

74
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

82 INTERNET ADDICTION

development. Since the game incorporates players’ characters so strongly into

its mechanics, it keeps changing and developing constantly. An example is the
virtual free-market economics in the game worlds—the prices of various items
and services follow complex rules and are affected by many real-life factors
(whether it is a holiday, time of the day, etc.), as well as game factors. The
software company developing the game also continuously performs various
upgrades, usually new features, items, locations, challenges, and so on. The
player is thus de facto forced to keep gathering new items (which are better
than the old ones) and search new locations to keep his or her social standing in
the game. This causes the equipment of players to gradually become obsolete
unless an upgrade is found; for example, year-old equipment is almost useless
due to the ease of obtaining better items in new locations. This endless and
continuing development forces players in the game to continuously remain
active; they usually have invested large amounts of time and energy (and
sometimes money), and to stop playing would mean throwing all that away,
including social contacts (other players are often at least virtually the best
friends of addicted players), prestige, and status, which players often lack
in the real world. In the words of one player who spends 80 hours weekly
playing: “ M y classmates and peers actually run into pubs and I run into that game
instead, and thereI can do as I please—it could bethesame kind of thing.”

FA C T O R S O F A D D I C T I O N O N T H E P L AY E R ’ S S I D E
Another direction in studying MMORPG addiction is an emphasis not on the
properties of games and virtual reality itself, but rather on players. Studies
point mainly to two psychological factors—lower self-esteem and self-efficacy.
At the same time we can say that obtaining positive self-esteem and self-
efficacy is one of the developmental goals of adolescence, which is probably
related to the fact that young players consider the game community more
important than older ones do (Smahel, 2008).
The factor of lower self-esteem seems to be crucial in the creation of ad-
diction; this has been shown in many studies, however mostly indirectly. For
example, Bessière, Seay, and Kiesler (2007) compared differences in players’
perceptions of their current self, ideal self, and game character. The results
have then shown that their current self was perceived worse than the game
character, and the game character was perceived worse than their ideal self.
The differences increased based on the level of depressiveness and the level
of self-esteem in particular. Respondents with high self-esteem had notably
lower discrepancies between their views of themselves and their game char-
acters, while there were higher discrepancies for respondents with lower self-
esteem. The ideal self then was about the same distance away for both groups.
This could mean that more depressive players and players with lower self-
esteem idealize their game characters and perhaps have a tendency to solve
their own perceived weaknesses through the game and thus a tendency to

75
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

Addiction to Online Role-Playing Games 83

become stuck in the game. Wan and Chiou (2006b) also consider self-efficacy
a very significant factor, especially for adolescent players.
The virtual environment of online games allows a lower emphasis on
self-control, permitting the subconsciousness of players to express itself
more—supported not only by the anonymity but also by the aforementioned
flow states. Players of role-playing games often daydream about the game,
their characters, and various situations. These fantasies are then considered
by players to be one of the most beneficial and strongest moments the game
has brought them and the reason they look forward to playing. Players them-
selves claim they are motivated by fun, experimenting, and so on, but as for
subconscious motivations, players with addictive symptoms are motivated
by self-expression of a full and efficient self, something they lack in real life
(Wan & Chiou, 2006b). These authors explain addiction in the game via a
mechanism that is principally close to the feeling of bliss obtained through
psychoanalysis. A similar mechanism is described by Allison et al. (2006),
where in the case of an 18-year-old hospitalized player the researchers show
that his excessive play sessions lasting up to 18 hours per day were mostly
a solution to his problems with self-esteem and social drawbacks. His char-
acter, a “shaman capable of reviving the dead and calling lightning,” then
represented a compensation for his deficits, allowing the player to create a
full-fledged self in the game. Although he had social phobias, he successfully
socialized in the game. Unfortunately, this player was not able to transfer such
a full self and the obtained self-efficacy into real life.
The authors, in accordance with Sherry Turkle (1997), thus liken the relation-
ship of the player to his character to a transfer as defined by deep psychology. A
transfer is a sort of space between an individual (his inner world) and the outer
reality, meaning the transfer does not fully belong to either of these places. The
game character is on one hand controlled by the player, but on the other hand it
is not part of the player, and this could explain why some players are not capa-
ble of fully controlling their play. The relationships between players and their
game characters can, however, have various forms, and the developmental
aspect also plays a certain role here (Blinka, 2008). Especially younger players
use their game characters as tools for gaining prestige in the game world and
are thus more susceptible to becoming stuck in the game. The relationships
between players and their characters can even have therapeutic potential
from a certain point of view. Players in the game unknowingly compensate
for certain aspects that they lack in themselves; if therapy could identify these
aspects, reflect them, and then transfer them into real life, the game could be
used to treat their problems, which could paradoxically lead to less time spent
in the game. Turkle showed a similar use of the therapeutic potential of games
on MUDs, the aforementioned predecessors of MMORPGs (Turkle, 1997).
Wolvendale (2006) spoke directly of the attachment of players to their game
characters. This is a very similar relationship to the one we have to absent
individuals—they are not in reality present, but by keeping them in our
minds, they are real in consequences. The game character is similarly absent or

76
77
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

Addiction to Online Role-Playing Games 85

dimension “often” or “very often.” The player is considered as having all

symptoms of addictive behavior if all five dimensions are present. The player
is considered “endangered by addictive behavior” if three dimensions plus
conflict are present. This questionnaire can be easily used as a simple test for
symptoms of addictive behavior in online gaming but it can never replace
clinical interview. There are also players who score low in the questionnaire
because they unconsciously (and sometimes also consciously because of social
pressure) underestimate their results.

SELF-PERCEPTION OF ADDICTION
Addiction to MMORPGs is not just a theoretical, abstract notion. The no-
tion of addiction in relation to MMORPGs has entered general awareness.
For example, Google found 4.5 million results when searching for “addiction
WoW” at the end of May 2009. There are hundreds of videos on YouTube
about this phrase. Yee (2006b) has stated that approximately half of players
consider themselves addicted. The older gamers had a lower tendency for
doing so: 67% of adolescent girl gamers, 47% of adolescent boy gamers, and
40% of adult gamers have labeled themselves addicted to the game. From
qualitative interviews with excessive players (Blinka, 2007), the tendency to
do so also seemed apparent; however, this has not yet been quantitatively
confirmed. Basically, younger players more often label themselves addicted,
but they do not consider this significant and reject possible negative impacts
of such addiction. Older players are more often aware of possible negative
aspects of addiction, but more often deny being actually addicted to the
game. The term addiction usually comprises three factors for players: The
first is excessive play compared to the referential group of players, which
is tricky due to the fact that the referential group of players can sometimes
play more than 10 hours a day. As stated by one of the players in our in-
terviews: “ I went to bed at night and the other players went to bed the other day
in themorning.” Another factor constitutes conflicts with one’s surroundings,
and the third is cognitive salience, meaning that a player constantly thinks,
dreams, or daydreams about the game. In the words of one of the players,
“ When I was addicted, I didn’t think about anything else and I played whenever
I could.”
One can also ask to what extent somebody labeling himself or herself
addicted could actually be related to addictive behavior. In our quantitative
study (Smahel, Blinka, & Ledabyl, 2007), we found agreement between self-
definition as an addicted individual and addictive behavior in about 21% of
players; such is thus the ratio of players who both have symptoms of addiction
and consider themselves addicted. Almost a quarter of players then claim to
be addicted but do not show symptoms of addiction—probably due to the
popular overuse of the word addiction. Many players base their judgment of
whether they are addicted solely on the amount of time spent playing. From
a therapeutic standpoint, 6% of players do not consider themselves addicted

78
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

86 INTERNET ADDICTION

but display symptoms of addiction. This group does not acknowledge their
addictive behavior, and that fact should be elaborated on therapeutically.
The remaining 49% of players do not consider themselves addicted and do
not display symptoms of addiction. A total of 27% of MMORPG players
in our study indicated all five factors of addiction—a relatively high share
considering the fact that, for example, World of Warcraft is played by over
11 million players.

C O N C L U S I O N : W H AT C A N T H E R A P I S T S D O ?
In this chapter we have dealt with playing MMORPGs in the context of
addiction to the game. Now let’s look at possible implications for therapists
as well as clinical or social workers who could come into contact with excessive
players of MMORPGs. Empirical data on therapeutic work with MMORPG
players is still rare, so we will now draw mostly from our experience with
and knowledge of MMORPGs and their context.
We have shown that MMORPGs are played primarily by men in young
adulthood and that time spent in the game often reaches 30 and more hours
per week. Motivations for playing MMORPGs are various, ranging from com-
petition in the context of creation of powerful characters and exploring the
online world to recognition in the virtual social group of players, often within
so-called guilds. The player’s virtual character, or avatar, becomes a part of
the player and the player communicates in the game through it. The virtual
character in a sense incorporates into the real personality of the player, based
on the current state of the player’s development and identity. Players then
feel a wide range of emotions toward their avatars. Since players spend a
lot of time in the game, they often label themselves addicted. About half of
players think that they are addicted to the game (Yee, 2006a). Usually this is
only a trendy and excessive use of the word addiction, since a large share of
these players do not display symptoms of addiction to the game. Symptoms
of addiction to the game are, however, displayed by approximately a quarter
of MMORPG players (Smahel, 2008; Smahel et al., 2008).
We have also presented a simple questionnaire for determining these symp-
toms, which can be used for basic orientation. However, for determining
whether someone is truly suffering from addiction, the best option is to par-
ticipate in a clinical interview. Many players undervalue or overvalue answers
in questionnaires, and playing in the context of the whole of the player’s life
must be taken into account. Therapists should ask questions regarding the
function of playing in the player’s life and the hidden motives for playing. It
seems that for many players with developed addictions to MMORPGs that
this addiction only hides other problems of the player in real life. This hy-
pothesis has, however, not yet been empirically verified, although it does
come from informative interviews with therapists. One of the therapists, for
example, stated that he had an adult client asking about his depressions. Only
after half a year of treatment did it become apparent that this client played

79
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

Addiction to Online Role-Playing Games 87

MMORPGs every day, morning to evening. He was at the same time very
ashamed of this and did not want to talk about it. Playing MMORPGs could
be not only the client’s main problem, but also a symptom hidden behind
another problem (e.g., depressions, anxiety). Playing online games is actually
a relatively safe symptom, since although physical needs sometimes do get
neglected to a certain degree, no physical harm is caused directly—as is the
case in overuse of drugs or alcohol.
Therapists also have a new option of working with the player’s relationship
to the avatar and also the context of social links in the game. Understanding
the function of the virtual social space of the player is apparently crucial:
Is it a compensation for relationships in the real world? Or is it a way of
supporting the player’s self-esteem and self-efficacy? The therapists should
ask themselves what the online world brings the player and how can the
player use this in real life. Potential addiction usually has a certain function
for players, in some manner that fits in their real lives—similarly to other
addictions or psychological problems. Addiction to MMORPGs is specific
due to the virtual presence of the player in a community and also due to
the relationship to the online character, but apparently is not special as far as
therapeutic principles and procedures are concerned. Our recommendation
to therapists of potential MMORPG addicts thus leads to using their proven
procedures for other types of addictions or problems and possibly combining
them with the options provided by the virtual world. Meeting the client in the
virtual world could lead to a better understanding of the player’s problems
and have certain therapeutic potential, as shown by Turkle in the example of
text online worlds (Turkle, 1997).
The future remains a big question as far as the development of addiction to
online games goes. If we look back, 10 years ago MMORPGs were practically
nonexistent and playing within complex online worlds was relatively rare,
mostly in the context of the aforementioned MUDs. We can thus ask: What will
happen in the next 5 to 20 or more years? The development of technologies
and online worlds is so fast that it is hard to guess what the future may
bring. It is practically certain, though, that online addiction has been on the
rise in recent years. We expect that the virtual reality as a form of escape
from the real world will become more and more common, and MMORPGs
will be no exception. If the borders between reality and virtual reality keep
blurring, be it by improving the graphics of games or quality of monitors or
by the development of new technological tools altogether such as monitors
in glasses, sensor gloves, or other examples, we can expect further significant
development and deepening of these phenomena. Players will find it even
more difficult to distinguish between the real world and the virtual one,
and their immersion in the game will be even greater. The importance of
exploring MMORPGs in the context of addiction will thus rise greatly. This
chapter can thus be seen as a prompt to people who come into contact with the
phenomenon of MMORPGs, whether in clinical practice or in their research,
not to underestimate virtual worlds and not to demonize them. Virtual worlds

80
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

88 INTERNET ADDICTION

are, first and foremost, simply another place for people to find fulfillment, be
it for better or worse.
The authors acknowledge the support of the Czech Ministry of Education,
Youth and Sports (MSM0021622406).

REFEREN CES
Allison, S. E., Walde, L. V., Shockley, T., & O’Gabard, G. (2006). The development of
self in the era of the Internet and role-playing games. American Journal of Psychiatry,
163, 381–385.
Beard, K. W., & Wolf, E. M. (2001). Modification in the proposed diagnostic criteria
for Internet addiction. CyberPsychology & Behavior, 4(3), 377–383.
Bessière, K., Seay, F. A., & Kiesler, S. (2007). The ideal elf: Identity exploration in
World of Warcraft. CyberPsychology & Behavior, 10(4), 530–535.
Blinka, L. (2007). I’m not an addicted nerd! Or am I? A narrative study on self-
perceiving addiction of MMORPGs players. Paper presented at the Cyberspace
2007. Retrieved from http:/ / ivdmr.fss.muni.cz/ info/ storage/ blinka-mmorpg.
ppt
Blinka, L. (2008). The relationship of players to their avatars in MMORPGs: Dif-
ferences between adolescents, emerging adults and adults [Electronic Version].
CyberPsychology: Journal of Psychosocial Research on Cyberspace, 2. Retrieved from
http:/ / cyberpsychology.eu/ view.php?cisloclanku= 2008060901&article= 5
Charlton, J. P., & Danforth, I. D. W. (2004). Differentiating computer-related addic-
tions and high engagement. In J. Morgan, C. A. Brebbia, J. Sanchez, & A. Voisk-
ounsky (Eds.), Human perspectives in the Internet society: Culture, psychology, gender
(pp. 59–68). Southampton, UK: WIT Press.
Charlton, J. P., & Danforth, I. D. W. (2007). Distinguishing addiction and high engage-
ment in the context of online game playing. Computers in Human Behavior, 23(3),
1531–1548.
Chou, T., & Ting, C. (2003). The role of flow experience in cyber-game addiction.
CyberPsychology & Behavior, 6(6), 663–675.
Cole, H., & Griffiths, M. D. (2007). Social interactions in massively multiplayer online
role-playing gamers. CyberPsychology & Behavior, 10(4), 575–583.
Entertainment Software Association. (2007). Essential facts about the computer and
video game industry [Electronic version]. Retrieved from http:/ / www.theesa.
com/ facts/ pdfs/ ESA EF 2007.pdf
Entertainment Software Association. (2008). Essential facts about the computer and
video game industry [Electronic version]. Retrieved from http:/ / www.theesa.
com/ facts/ pdfs/ ESA EF 2008.pdf
Griffiths, M. (2000a). Does Internet and computer “addiction” exist? Some case study
evidence. CyberPsychology & Behavior, 3(2), 211–218.
Griffiths, M. (2000b). Excessive Internet use: Implications for sexual behavior.
CyberPsychology & Behavior, 3(4), 537–552.
Griffiths, M. (2000c). Internet addiction—Time to be taken seriously? Addiction
Research, 8(5), 413–418.

81
82
P1: TIX/ OSW P2: TIX
JWBT338-c05 JWBT338-Young August 12, 2010 13:14 Printer Name: Hamilton, Castleton, New York

90 INTERNET ADDICTION

Turkle, S. (2005). Thesecond self: Computers and thehuman spirit (20th anniversary ed.).
Cambridge, MA: MIT Press.
Voig, Inc. (2008). MMOGData: Charts [Electronic version]. Retrieved October 16, 2008,
from http:/ / mmogdata.voig.com/
Wan, C.-S., & Chiou, W.-B. (2006a). Psychological motives and online games addiction:
A test of flow theory and humanistic needs theory for Taiwanese adolescents.
CyberPsychology & Behavior, 9(3), 317–324.
Wan, C.-S., & Chiou, W.-B. (2006b). Why are adolescents addicted to online gaming?
An interview study in Taiwan. CyberPsychology & Behavior, 9(6), 762–766.
Widyanto, L., & Griffiths, M. (2007). Internet addiction: Does it really exist? (Revisited).
In J. Gackenbach (Ed.), Psychology and the Internet: Intrapersonal, interpersonal, and
transpersonal implications (2nd ed.). (pp. 141–163). San Diego, CA: Academic Press.
Wolvendale, J. (2006). My avatar, my self: Virtual harm and attachment. Paper pre-
sented at the Cyberspace 2005, Brno, Moravia.
Yee, N. (2006a). The demographics, motivations and derived experiences of users
of massively-multiuser online graphical environments. Presence: Teleoperators and
Virtual Environments, 15, 309–329.
Yee, N. (2006b). The psychology of massively multi-user online role-playing games:
Motivations, emotional investment, relationships and problematic usage. In R.
Schroeder & A. Axelsson (Eds.), Avatarsat work and play: Collaboration and interaction
in shared virtual environments. Dordrecht, Netherlands: Springer.

83
 Study IV

Blinka, L. &Mikuška, J. (2014). The role of social motivation and sociability

of gamers in online game addiction. Cyberpsychology: Journal of

Psychosocial Research on Cyberspace, 8(2).

84
 Blinka, L., & Mikuška, J. (2014). The role of social motivation and sociability of gamers in online game
addiction. Cyberpsychology: Journal of Psychosocial Resear ch on Cyberspace, 8(2), article 6. doi:
10.5817/CP2014-2-6

Th e r ole of socia l m ot iva t ion an d socia bilit y of ga m e r s in onlin e

ga m e a ddict ion
Lukas Blinka1, Jakub Mikuška2

1
Faculty of Social Studies, Masaryk University, Brno, Czech Republic
2
School of Human Environmental Sciences, University of Kentucky, Lexington, KY, USA

Abst r a ct

Massiv ely m ult iplayer online ( MMO) gam es repr esent a long - st anding, int ensive and w ide spr ead t ype of
online applicat ions w hose popularit y cont inues t o grow . Alt hough j ust a m ere ent ert ainm ent and leisur e
act ivit y for m ost gam ers, it s pot ent ially negat ive and addict ive out com es w er e int ensively st udied and
recent ly also acknow ledged by t he Am erican Psychiat ric Associat ion ( 2013) . MMOs are essent ially a social
act ivit y, but em pirical st udies are equivocal in ident ifying w het her and t o w hat ext ent t he social fact ors
help dev elop t he addict ive gam ing habit s associat ed w it h t hese applicat ions. The pr esent st udy seek s t o
direct ly ident ify t he r ole of social fact or s in online addict iv e gam ing. Survey dat a from 667 MMO gam er s
wer e analysed. Toget her wit h an online gam e addict ion scale, t he invest igat ed psychological fact or s
included social m ot ivat ion for gam ing, online peer at t achm ent and social self - efficacy. The result s
rev ealed t hat alt hough social m ot ivat ion w as a predict or of addict ive gam ing, high social m ot iv at ion w as
t ypical for int ensiv e gam ers regardless of t heir lev el of addict ion. Howev er, gam er s at - risk of addict ion
scored low er in t heir social self- efficacy and int erpersonal t rust m easur ed by peer at t achm ent . This
support s t he poor - get - poorer hypot hesis, t hat generally less socially skilled gam ers face fur t her problem s
online. How ever, social fact ors w er e only m odest ly associat ed t o online addict ive gam ing w hich indicat es
higher r elevance of ot her fact ors ident ified by lit erat ure, e.g. im m er sion and in - gam e r ewards syst em s.

Keywords: online game addiction; social motivation; sociability; social self-efficacy; peer-attachment

I n t r odu ct ion

The Internet as an entertainment medium has proliferated through contemporary society along with the
multitude of its online applications. Online computer games in general and the MMO genre (massively
multiplayer online games) in particular are one of the online applications which became immensely
successful and changed the way many people spend their free time. For instance, World of Warcraft, one
of the most popular MMORPGs (role playing games), boasted 12 million subscribers in 2010 (Blizzard,
2010). With the spread of free-to-play games, it seems that the number of MMO players has been on a
constant rise. According to the Entertainment Software Association (ESA, 2013), in 2012 the computer
games market reached about 14 billion dollars in the U.S. alone and an overwhelming majority of this
profit was generated by online games. Many of the MMOs, including e.g. World of Warcraft, became so
widespread that they can be easily recognized as pop-cultural symbols.

What attracts the attention of both the public and academics is the intensity with which MMOs are played.
Most of the existing data claim that the average amount a player spends in MMOs is about 25 hours a
week (Griffiths, Davies, & Chappell, 2004; Smahel, Blinka, & Ledabyl, 2008; Williams, Yee, & Caplan,
2008), but many gamers play significantly more than that – about 11% of players spend 40 hours a week
in-game. Additionally, the majority of gamers have indulged in very long gaming sessions. As reported by

85
Yee (2006), 60% of MMO players have spent 10 continuous hours in-game without a break. Such loyalty
and compulsiveness of many players has been studied for a decade and half now and has generated a
relatively extensive body of existing literature on this topic. More often than not, the psychological
paradigm of so called Internet gaming addiction has been applied to approach this intensity of time
investment. Researchers have agreed that many heavy gamers actually develop symptoms similar to the
symptoms of other behavioural addictions – these include jeopardization of interpersonal and social
relationships, obsession by the game, persistence in gaming patterns despite being aware of their
negative consequences, experiencing of withdrawal symptoms while not able to be online, and relapsing
back into heavy gaming after periods of relative control (for an overview see e.g. Blinka & Smahel,
2011a; Kuss & Griffiths, 2012). Recently, the online games disorder was added as an experimental
diagnosis in the 5th revision of the Diagnostic and Statistical Manual of Mental Disorders (APA, 2013).

Some research suggested a more distinct typology rather than just the distinction of problematic and non-
problematic internet users and online gamers. For example, Dreier and colleagues (2014) identified four
different types of excessive internet users who differed in their level of controlling the behaviour and thus
only some of these could be considered to be at-risk of addiction. Similarly, in case of online gamers,
Charlton and Danforth (2007; 2010) described a third group in addition to the addicted and non-
problematic groups, which is characterized by high engagement – and despite being highly involved in the
activity and even showing some signs of peripheral addiction factors, this group should not be labelled as
pathologically addicted. In the present study we adopt this notion and we investigate not only addictive
gaming as a continuum but also three distinct types of users in relation to their level of addictive gaming
– i.e. casual (non-problematic) gamers, highly engaged (non-pathologic) gamers, and gamers at-risk of
addiction.

The literature has identified several personality factors associated with the tendency to use online games
excessively or even pathologically. For example, Mehroof and Griffiths (2010) found that online game
addiction is associated with neuroticism, sensation seeking, aggression and state and trait anxiety of the
gamers, while Caplan, Williams and Yee (2009) found a similar tendency with loneliness as the single
strongest predictor, followed by introversion and depression of the gamers. Kuss and Griffiths (2012)
summarized the factors associated with riskier gaming patterns as introversion, neuroticism and
impulsivity. This seems to be in line with results of studies examining the main gameplay motivations of
problematic gamers. Along with achievements – earning points, progressing, and levelling (King,
Delfabbro, & Griffiths, 2011), the major reasons for playing MMOs were namely immersion and escapism
(Yee, 2006; Caplan et al., 2009; King et al., 2011), e.g. using the game as a mood management tool to
cope with negative emotions (Hussain & Griffiths, 2009).

However, online games are also inherently a social activity, played with or against others, and offering
opportunities to make new friends online. Players often attribute the appeal of online games to the
community formed by other gamers. This is clearly visible on the positive relationship of the number of in-
game friends and the amount of time players invest into the games (Cole & Griffiths, 2007). Emotional
and behavioural investment seems to go hand in hand, and not only in terms of quantity of friends.
Caplan and colleagues (2009) found that one of the strongest predictors of pathological gaming was the
use of voice technology – this is usually used in a very social style of game play and the players using this
technology interact with others in the game more intensively. On the other hand, however, the same
study found no significant relationship between social motivation and pathological gaming (Caplan et al.,
2009) - a finding also supported by Kardefelt-Winther (2014). Despite the link between social factors and
development of excessive and pathological gaming has been consistently described by qualitative studies
(e.g. Haagsma, Pieterse, Peters, & King, 2013; Karlsen, 2011), the state of quantitative research seems
to be rather equivocal in assessing the role of social factors in problematic game play.

Based on the reviewed literature on personality factors and gaming addiction, one of the explanations of
what leads to problematic game play seems to be the so-called social compensation hypothesis. According
to Lo, Wang and Fang (2005) many players use the MMO environment to overcome their feelings of
isolation and social anxiety by immersing themselves into intensive online gaming and into building social
relationships within these games, which temporarily brings a sense of relief. Some studies indicated
positive outcomes of social online game play – for example in expanding social capital (Zhong, 2011) and
transferring the social connections formed in the game to the offline environment (Trepte, Reinecke, &
Juechens, 2012). However, many studies have shown that the social capital acquired in online games is a
bridging social capit al – loose relationships, characterized by their width – rather than bonding social
capit al – close relationships characterized by emotional support (Huvila, Holmberg, Ek, & Widen-Wulff,
2010; Williams, 2007). Thus online relationships may suffer from their superficiality and the fact that
some of the gamers may be caught in a vicious cycle, where the game and social interaction leads to
further isolation (Lo et al., 2005).

86
However, some researchers describe the actual situation as being more complex. Trepte and her
colleagues (2012) found that the players in closer physical and social proximity to other players (e.g.
those more involved in organisation of the gaming clans and guilds, those more in touch with other
players) yield more positive outcomes from the game. These players create not only the bridging but also
the bonding social capital which positively affects the social support they receive. Similarly, Smahel,
Brown, and Blinka (2012) found that the best adapted individuals (who report highest number of friends
and close friends) are those who report a balanced number of online and offline friends – they are able to
use both the online and offline environment to their benefit. Recently, it was for example Collins and
Freeman (2013) who found that problematic gamers report higher online social capital and lower offline
social capital, while in the case of the non-pathological gamers the negative effect of lowering offline
social capital was not reported and only the positive remained. Based on this we propose the following
hypotheses below.

Th e Pr e sen t St ud y

The purpose of this study is to examine whether the social factors – measured by social motivation for
gaming – and sociability – measured by social self-efficacy and peer attachment – are related to online
game addiction. Based on the reviewed literature, we hypothesize that:

H 1 : Social m ot ivat ion for gam ing is posit iv ely r elat ed t o online gam ing addict ion.

Some studies showed social aspects of online gaming as a motivational factor for gaming itself, both
pathological and non-pathological. Still, literature has shown that overcoming social isolation via social
game play is an important empowerment factor of pathological gaming. Thus we hypothesize that:

H 2 : Gam er s at - r isk of addict ion, highly engaged non - pat hological and casual gam ers ar e
different in respect t o t heir social m ot ivat ion for gam ing.

The potential that lower sociability of gamers is a predictor of addictive gaming has been stated in
research. Also, pathological gamers were identified to possess personality traits that are associated with
lower social involvement and lower feelings of security in social situations. Thus we hypothesize that:

H 3 : Social self- efficacy is negat iv ely associat ed w it h addict ive gam ing.

H 4 : Gam er s at - r isk of addict ion, highly engaged non - pat hological and casual gam ers ar e
different wit h respect t o t heir self- efficacy.

H 5 : Per ceived online peer at t achm ent is negat ively associat ed wit h addict ive gam ing.

H 6 : Gam er s at - r isk of addict ion, highly engaged non - pat hological and casual gam ers ar e
different wit h respect t o t heir per ceived online peer at t achm ent .

M e t h ods
Pa r t icip a n t s

The sample used in this study consisted of 667 MMORPG players (ages 11-54, M = 22.71, SD = 6.66;
84% male), predominantly from the Czech Republic and Slovakia. Players were recruited during Spring
2011 through discussion forum posts or by server-wide in-game promotions after contacting several
server administrators. In several cases, participation was incentivized by in-game rewards which may
have led several people to "click through" the survey, therefore everyone who completed the survey in
less than 4 minutes was omitted from the final sample, as well as everyone who consistently selected the
same response or did not respond to more than 50% of the relevant items.

On average, players in our sample spent 22 hours in MMORPGs every week (SD = 17.62), and played
mostly World of Warcraft (45%). There were no differences between males and females in terms of age
(Males: M = 22.69, SD = 6.47, Females: M = 22.88, SD = 7.67, t [649] = 0.74, p = .459), and hours
played per week (Males: M = 21.72, SD = 17.42, Females: M = 23.12, SD = 18.79, t [649] = 0.25, p =
.800).

87
M e a sur e s

On lin e g a m e a ddict ion . To assess the level of online game addiction, ten Likert-type questions on a 4-
point scale ranging from ‘never’ to ‘very often’ were used. This scale was designed and developed by
Blinka and Smahel (2011a) based on six criteria of addictive behaviour as proposed by Griffiths (e.g.
Griffiths, 2000; 2005) – salience (two items, divided into cognitive and behavioural salience), withdrawal
symptoms (one item), euphoria (one item), tolerance (two items); conflicts (two items); relapse and
reinstatement (two items). Sample items included “have you been unsuccessful in trying to limit time
spent online” (relapse and reinstatement) or “do your family, friends, job, and/or hobbies suffer because
of the time you spend with online gaming” (conflict). We created an online game addiction index as a
mean value of the 10 items (Cronbach’s alpha = .76).

Following and expanding Charlton and Danforth's (2007; 2010) notion of distinction between addicted and
highly-engaged players, we chose to define and compare three groups of players, based on their level of
addiction and intensity of game play. The authors argue that there is a difference between intensive
players who are simply passionate about the games, yet do not experience negative consequences
associated with their gaming patterns, and those who do. We chose to compare these highly engaged
players to those at risk of addiction, and to further provide contrast by including a group of casual or
recreational players. Thus we divided players into the following three groups: the "addiction at-risk" group
(12.1%, n = 81) consisted of players reported "often" or "very often" in at least three criteria on the
addiction scale, as well as the conflict criterion; the "highly engaged" group (29.5%, n = 197) contained
players who did not meet the criteria of the first group, but reported playing more than average time (22
hours) weekly; finally, "casual gamers" (58.3%, n = 389) were those that did not report the necessary
criteria for addiction and also reported playing below average time per week. The gender distribution
across the three groups was found to be equal (χ2 [2] = 2.80, p = .246). Comparing the groups on their
addiction scale scores shows that the groups are distinct in the severity of reported issues (F[2,664] =
223.54, p < .001, casual: M = 1.77, highly engaged: M = 1.94, at-risk: M = 2.65, all statistically
significant from each other at the p < .001 level).

Socia l m ot iv a t ion . To measure the players' enjoyment of the social aspects and their motivation to play
MMOs for these reasons, we utilized a number of items from the most common questionnaires measuring
this construct (Hsu, Wen, & Wu, 2009; Koo, 2009; Yee, 2006). Selected items focused on the individual's
attitudes instead of frequencies (such as those with response scales ranging from never to very often) and
loaded strongly on their respective factors in the original studies. Nine items in total were chosen to
create a three-component measure (socialization & community inclusion, relationships & support, and
teamwork). Sample items included “I like being a member of the gaming community”, and the 4-point
response scale ranged from "completely disagree" (1) to "completely agree" (4). After testing for internal
consistency, one item was omitted due to its low contribution to Cronbach's alpha of the scale. After the
exclusion the scale alpha was α = .78.

Pe r ce iv e d Socia l Se lf- Effica cy . Smith and Betz (2000) Perceived Social Self-Efficacy Scale was used to
measure the extent to which respondents viewed themselves as confident in performing various social
interactions. Sample items included "make friends in a group where everyone else knows each other" and
"put yourself in a new and different social situation". Response categories ranged from "no confidence at
all" (1) to "complete confidence" (5) and α = .94.

I n - Ga m e Fr ie n d sh ip Qu a lit y ( p e e r a t t a ch m e n t ) . To assess the perceived quality of friendships formed

with other players within the MMOs, we used the peer section of Armsden and Greenberg's (1987)
Inventory of Parent and Peer Attachment with modified instructions asking respondents to think of their
online friends as the reference category for the items. Sample items included "I trust my friends" and "I
feel my friends are good friends". Response categories ranged from "completely disagree" (1) to
"completely agree" (5). Due to data entry errors two of the twenty-five items were omitted. Despite this
issue, the scale reliability was more than adequate (α = .90).

Re su lt s

Pearson’s correlations revealed that online game addiction is positively related to in-game time and social
motivation for gaming, while being negatively related to social self-efficacy of gamers. Interestingly,
although social motivation and social self-efficacy are positively related, their relation to addiction is
opposite. Social motivation is positively related to in-game addiction while social self-efficacy is negatively
related to in-game addiction. Table 1 summarizes the results of correlational analysis.

88
 Table 1. Cor relat ions of m ain st udy variables.

(1) (2) (3) (4) (5) (6)

Addiction (1) - -.08 .13** -.16*** -.09* .24***
In-Game Friendship (2) - .42*** .39*** -.07 .14***
Social Motivation (3) - .27*** -.06 .16***
Social Self-Efficacy (4) - .07 .00
Age (5) - .01
Play time (6) -
Note: * p < .05, ** p < .01, *** p < .001

A two-step hierarchical linear regression was used to determine associations between online game
addiction and social self-efficacy, social motivation for gaming and quality of in-game friendships, and
after controlling for demographic variables and intensity of gaming. Model 1 includes only control
variables (age, gender and play time), and variables measuring social attitudes and skills are added in
Model 2 (see Table 2).

Table 2. Linear r egr ession: Social and cont rol fact or s associat ed w it h online
gam e addict ion.

Model 1 Model 2
B SE β B SE β
(Constant) 1.90*** 0.97 2.17*** 0.17
Age -0.01* 0.00 -.09 -0.01* 0.00 -.08
Gender 0.04 0.05 .03 0.03 0.05 .03
Play time 0.01*** 0.00 .23 0.01*** 0.00 .23
Social Motivation 0.17*** 0.04 .17
Social Self-Efficacy -0.09** 0.03 -.14
In-Game Friendship -0.13** 0.04 -.14
R2 .062 .113
F 13.797*** 13.073***
Δ R2 .050***
Note: * p < .05; ** p < .01; *** p < .001

In the first step of the regression, as expected, time spent in-game was a positive predictor of addiction.
While age was a negative predictor, i.e. younger gamers were more prone to addictive gaming, there was
no effect of gender. These control variables accounted for 6% of the variance in the addiction scores.
Social motivation for gaming was positively associated with gaming addiction even after controlling for
demographic variables – supporting hypothesis H1. The quality of in-game friendships and social self-
efficacy were both negatively related to gaming addiction, providing support for hypotheses H3 and H5.
Social variables accounted for about 5% of the variance in the addiction score over and above age,
gender, and play time.

To analyse inter-group differences, a series of ANOVAs was conducted. Table 3 displays that in social
motivation the groups of highly engaged and at-risk of addiction did not differ significantly. The two
groups did however differ significantly from the third one – the casual players, both reporting higher mean
score of social motivation and offering support to H2. Concerning social self-efficacy, the at-risk of

89
addiction group reported the lowest mean score. However they differed significantly only from the casual
group, again supporting our H4. In terms of the perceived in-game quality of friendships, it was again the
highly engaged gamers who scored highest and in that respect they differed from both the casual and at-
risk group (who reported the lowest score). Hence H6 was also supported.

Table 3. Differ ences by int ensit y and pat hology of gam ing in social and cont r ol variables.

Highly engaged At-risk of

Casual (389)
(197) addiction (81)
M SD M SD M SD F df(1;2) η2
Social Self Efficacy 3.23a 0.68 3.20ab 0.65 3.01b 0.71 3.32* 2;664 .01
In-Game Friendship 3.68a 0.47 3.81b 0.49 3.57a 0.50 7.83*** 2;664 .02
Social Motivation 2.80a 0.43 2.97b 0.42 2.91ab 0.49 10.14*** 2;664 .03
Age 22.56a 6.60 23.29a 6.88 22.03a 6.35 1.22 2;637 .00
Note: Groups with different superscripts are statistically significantly different from each other based on Scheffe's post-
hoc tests, * p < .05; ** p < .01; *** p < 001

D iscu ssion

The aim of this investigation was to examine the role of social motivation, sociability – self-confidence in
social situations, and perceived quality of online peer relationships in problematic online game play or
online game addiction. Each of the three social variables included in our model do have a unique,
statistically significant relationship with online game addiction, even after controlling for age, gender, and
play time.

Social motivation appeared to be positively associated with online game addiction, which suggests that
higher levels of social motivation for gameplay are likely to be accompanied by problematic game play, at
least to a certain degree. When comparing the groups of casual, highly engaged and at-risk players this
pattern becomes even easier to identify. The motivation to play with other players, team up, and share
the game with others is on average higher among highly engaged and pathological gamers than among
casual gamers. Social motivation for playing online games has been acknowledged as an important factor
in gaming behaviour (Yee, 2006) and especially in excessive gaming. For example, Seay, Jerome, Lee and
Kraut (2004) reported a higher amount of time spent in-game by players who were engaged in
community-based play compared to solo-players. Also, Hsu et al. (2009), Caplan et al. (2009), and
Haagsma et al. (2013) found that the role of belonging to an online community and the associated feeling
of obligation were very important predictors of online game addiction. It seems that the breadth of social
interaction opportunities offered by online games are alluring to gamers and may eventually lead to the
negative consequences of online gaming.

Social self-efficacy, the belief of one's competence in establishing and maintaining relationships with
others and/or confidence in group activities, is negatively associated with gaming addiction. Longitudinal
data would be necessary to even begin to disentangle the directionality of this effect, yet it seems that
gamers reporting higher negative consequences of their gameplay trust their social skills less. This was
again supported by the group comparisons. Pathological gamers – those at-risk of addiction – tend to
score lower in their social self-efficacy than casual gamers. The role of highly engaged gamers seems to
be equivocal in this regards, showing no significant difference from either of the groups, potentially
suggesting a transitional role of this gaming pattern.

Perceived quality of in-game friendships, the need for social contact, and the level of perceived trust and
understanding towards their online friends is inversely related to gaming addiction. Here the group
difference pattern is slightly clearer, with the highly engaged group reporting closer relationships than the
other two groups.

According to the social compensation hypothesis, lonely and socially anxious individuals are especially
inclined towards online gaming as it may help, temporarily, to overcome the feelings of isolation from
their offline lives which may consequently lead to gaming addiction (Lo et al., 2005). However, even
90
though Caplan with colleagues (2009) found that loneliness predicts problematic game play, they did not
find a similar association between problematic gameplay and social motivation. This slightly contradicts
the social compensation hypothesis. Our study found that social motivation plays a role in increasing the
gaming addiction score. A direct comparison between groups showed that the highly engaged and at-risk
gamers both score higher than casual gamers. Additionally, the highly engaged group also showed higher
satisfaction with their online companions. Moreover, highly engaged gamers did not differ from the casual
gamers in their social skills and feelings of security in social situations. Thus, the highly engaged but non-
pathological gamers are those for whom the social style of gaming is more typical. This suggests that
social motivation is an important and attractive feature of the game which can explain why people tend to
play online games in such large numbers and why they devote so much time to playing. However, it
cannot explain why some of the gamers develop addictive usage.

This explanation may lay elsewhere. As our study suggests, gamers at-risk of addiction scored the lowest
in both perceived quality of peer relationships (along with casual players) and social self-efficacy (along
with highly engaged players). Thus it may be the player’s social skills that make the difference. The
socially skilled do not face problems related to online gaming as often as those who are less skilled. Thus
it seems that the valid explanation could be what Kraut and colleagues (2002) called the rich-get-richer
and poor-get-poorer hypothesis – socially well adapted individuals are able to use the online environment
to gain even higher social benefits, while those socially handicapped face further deterioration of their
psychosocial well-being online.

However, it must be noted that the currently observed associations were rather modest – e.g. social
variables explained only one twentieth of the variance of the online game addiction score. The mean
differences in sociability between groups, although significant, were very small. On the other hand, some
differences, although ostentatiously significant, were not, potentially due to low statistical power resulting
from a small sample size (especially in the case of the at-risk group). The estimated power for a small
effect (Cohen's d = 0.25) to be found between the highly engaged and at-risk group is .30 as obtained
from the Bonferronni correction (alpha level of .0167), which is inadequate to conclude that the
differences between groups do not exist.

The small effects of the social variables hint at increased relevance of other studies which found that the
most significant roles in developing problematic gameplay are played especially by the factors of
immersion and escapism, the system of in-game rewards and achievements (e.g. Hsu et al., 2009, King,
Delfabro & Griffiths, 2010; Kirby, Jones & Copello, 2014). However the lower role of social factors in
problematic gameplay contradicts the results found by qualitative studies (e.g. Beranuy, Cardonell, &
Griffiths, 2013; Haagsma et al., 2013; Karlsen, 2011). These report, in the players’ own words, that it is
the social aspect of game what leads to over-engagement in the game and later to the pathology. Future
studies, both qualitative and quantitative, should address the issue of these rather incompatible and
inconsistent results. Furthermore, longitudinal studies on this topic would be beneficial to examine the
directionality of these effects and look at whether it is lower confidence in one's social skills that leads a
player to become addicted, or the amount of time spent in-game and the resulting negative consequences
that lead players to lose their confidence.

Our study unfortunately faces several limitations, similarly to many other studies on this topic.
Convenience sampling and self-selection may lead to biased results due to potential constraints of the
variance. The second problem, usually accompanying the first one, is that samples with mixed cultural
backgrounds are used. Large cross-cultural differences in predictors of excessive internet use in European
youth have been reported (Blinka & Smahel, 2011b) and we could expect similar differences also in
specific online applications like online games and in the adult population. Both issues could be addressed
by using nation-wide representative samples, which are still more common in studies of children and
adolescents (e.g. van Rooij et al., 2010). Despite these limitations, our study expands the literature by
examining the roles of social self-efficacy, motivation for social play, and quality of in-game relationships
in problematic game play, and provides a unique contrast of three groups of players divided by their
gaming patterns.

Ack n ow le dgm e n t

The article was supported by grant from Czech Science Foundation (P407/12/1831). The authors would
also like to thank Kristýna Tlustáková and Jan Gabriel for significant help with data collection.

91
 Refe r e n ces

American Psychiatric Association. (2013). Diagnost ic and st at ist ical m anual of m ent al disorders (5th ed.).
Arlington, VA: American Psychiatric Publishing.

Armsden, G. C., & Greenberg, M. T. (1987). The Inventory of Parent and Peer Attachment: Relationships
to well-being in adolescence. Journal of Yout h and Adolescence, 16 , 427-454.
http://dx.doi.org/10.1007/BF02202939

Beranuy, M., Carbonell, X., & Griffiths, M. D. (2013). A qualitative analysis of online gaming addicts in
treatment. I nt ernat ional Journal of Ment al Healt h and Addict ion, 11 , 149-161.
http://dx.doi.org/10.1007/s11469-012-9405-2

Blinka, L., & Smahel, D. (2011a). Addiction to online role-playing games. In K. S. Young, & C. N. de Abreu
(Eds.). I nt ernet addict ion: A handbook and guide t o evaluat ion and t r eat m ent (pp. 73-90). Hoboken:
Blackwell-Wiley.

Blinka, L., & Smahel, D. (2011b). Predictors of adolescents’ excessive internet use: A comparison across
European countries. Proceedings to 15t h European Confer ence on Developm ent al Psychology (pp. 337-
341). Bologna, Italy: Medimond.

Blizzard (2010). WORLD OF WARCRAFT® SUBSCRIBER BASE REACHES 12 MILLION WORLDWIDE

Retrieved from http://us.blizzard.com/en-us/company/press/pressreleases.html?id=2847881

Caplan, S., Williams, D., & Yee, N. (2009). Problematic Internet use and psychosocial well-being among
MMO players. Com put ers in Hum an Behavior, 25 , 1312-1319.
http://dx.doi.org/10.1016/j.chb.2009.06.006

Charlton, J. P., & Danforth, I. D. (2007). Distinguishing addiction and high engagement in the context of
online game playing. Com put ers in Hum an Behavior , 23 , 1531-1548.
http://dx.doi.org/10.1016/j.chb.2005.07.002

Charlton, J. P., & Danforth, I. D. (2010). Validating the distinction between computer addiction and
engagement: online game playing and personality. Behaviour & I nfor m at ion Technology , 29 , 601-613.
http://dx.doi.org/10.1080/01449290903401978

Cole, H., & Griffiths, M. D. (2007). Social interactions in massively multiplayer online role-playing gamers.
CyberPsychology & Behavior , 10 , 575-583. http://dx.doi.org/10.1089/cpb.2007.9988

Collins, E., & Freeman, J. (2013). Do problematic and non-problematic video game players differ in
extraversion, trait empathy, social capital and prosocial tendencies? Com put ers in Hum an Behavior , 29 ,
1933-1940. http://dx.doi.org/10.1016/j.chb.2013.03.002

Dreier, M., Tzavela, E., Wölfling, K., Mavromati, F., Duven, E., Karakitsou, . . . Tsitsika, A. (2013). The
development of adaptive and maladaptive patterns of Internet use among European adolescents at risk
for Internet Addictive Behaviours: A Grounded Theory inquiry. National and Kapodistrian University of
Athens (N.K.U.A.), Athens: EU NET ADB. Available at www.eunetadb.eu

Entertainment Software Association (2013). Essent ial Fact s about t he com put er and video gam e indust ry .
Retrieved from http://www.theesa.com/facts/pdfs/esa_ef_2013.pdf

Griffiths, M. (2000). Does Internet and computer "addiction" exist? Some case study evidence.
CyberPsychology & Behavior , 3, 211-218. http://dx.doi.org/10.1089/109493100316067

Griffiths, M. (2005). A 'components' model of addiction within a biopsychosocial framework. Journal of

Subst ance Use, 10, 191-197. http://dx.doi.org/10.1080/14659890500114359

92
Griffiths, M. D., Davies, M. N., & Chappell, D. (2004). Online computer gaming: A comparison of
adolescent and adult gamers. Journal of Adolescence, 27 , 87-96.
http://dx.doi.org/10.1016/j.adolescence.2003.10.007

Haagsma, M. C., Pieterse, M. E., Peters, O., & King, D. L. (2013). How gaming may become a problem: A
qualitative analysis of the role of gaming related experiences and cognitions in the development of
problematic game behavior. I nt ernat ional Journal of Ment al Healt h and Addict ion, 11 , 441-452.
http://dx.doi.org/10.1007/s11469-013-9427-4

Hsu, S. H., Wen, M. H., & Wu, M. C. (2009). Exploring user experiences as predictors of MMORPG
addiction. Com put er s & Educat ion, 53 , 990-999. http://dx.doi.org/10.1016/j.compedu.2009.05.016

Huvila, I., Holmberg, K., Ek, S., & Widén-Wulff, G. (2010). Social capital in Second Life. Online
I nform at ion Review , 34, 295-316. http://dx.doi.org/10.1108/14684521011037007

Hussain, Z., & Griffiths, M. D. (2009). Excessive use of massively multi-player online role-playing Games:
A pilot study. I nt ernat ional Journal of Ment al Healt h and Addict ion, 7 , 563-571.
http://dx.doi.org/10.1007/s11469-009-9202-8

Kardefelt-Winther, D. (2014). Problematizing excessive online gaming and its psychological predictors.
Com put ers in Hum an Behavior, 31 , 118-122. http://dx.doi.org/10.1016/j.chb.2013.10.017

Karlsen, F. (2011). Entrapment and near miss: A comparative analysis of psycho-structural elements in
gambling games and massively multiplayer online role-playing games. I nt ernat ional Journal of Ment al
Healt h and Addict ion, 9, 193-207. http://dx.doi.org/10.1007/s11469-010-9275-4

King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2010). The role of structural characteristics in problematic
video game play: A review. Cyberpsychology: Journal of Psychosocial Resear ch on Cyberspace, 4 (1),
article 6. Retrieved from: http://www.cyberpsychology.eu/view.php?cisloclanku=2010041401&article=6

King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2011). The role of structural characteristics in problematic
video game play: An empirical study. I nt ernat ional Journal of Ment al Healt h and Addict ion, 9 , 320-333.
http://dx.doi.org/10.1007/s11469-010-9289-y

Kirby, A., Jones, C., & Copello, A. (2014). The impact of massively multiplayer online role playing games
(MMORPGs) on psychological wellbeing and the role of play motivations and problematic use. I nt ernat ional
Journal of Ment al Healt h and Addict ion, 12, 36-51. http://dx.doi.org/10.1007/s11469-013-9467-9

Koo, D. (2009). The moderating role of locus of control on the links between experiential motives and
intention to play online games. Com put er s in Hum an Behavior, 25 , 466-474.
http://dx.doi.org/10.1016/j.chb.2008.10.010

Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V., & Crawford, A. (2002). Internet paradox
revisited. Journal of Social I ssues, 58 , 49-74. http://dx.doi.org/10.1111/1540-4560.00248

Kuss, D. J., & Griffiths, M. D. (2012). Internet gaming addiction: A systematic review of empirical
research. I nt er nat ional Journal of Ment al Healt h and Addict ion, 10 , 278-296.
http://dx.doi.org/10.1007/s11469-011-9318-5

Lo, S. K., Wang, C. C., & Fang, W. (2005). Physical interpersonal relationships and social anxiety among
online game players. CyberPsychology & Behavior, 8 , 15-20. http://dx.doi.org/10.1089/cpb.2005.8.15

Mehroof, M., & Griffiths, M. D. (2010). Online gaming addiction: The role of sensation seeking, self-
control, neuroticism, aggression, state anxiety, and trait anxiety. Cyberpsychology, Behavior, and Social
Net w orking, 13, 313-316. http://dx.doi.org/10.1089/cyber.2009.0229

Seay, A. F., Jerome, W. J., Lee, K. S., & Kraut, R. E. (2004, April). Project massive: a study of online
gaming communities. In CHI '04 ext ended abst r act s on Hum an fact ors in com put ing syst em s (pp. 1421-
1424). ACM.

93
94
 Study V

Škařupová, K. & Blinka, L. (in press) Interpersonal dependency and internet

gaming addiction. Journal of Behavioural Addictions

95
Interpersonal Dependency and Online Gaming Addiction

Abstract

Background and aims

The present study explores the relationship between social motivations and addiction

to online gaming and if that possible connection can be explained by the personality

traits responsible for social functioning.

Methods

We employ Bernstein’s concept of interpersonal dependency to distinguish healthy

dependency, dysfunctional detachment, and destructive overdependence, and

Charlton and Danforth’s conceptualisation of online gaming addiction and high

engagement. An online questionnaire was administered to a self-nominated sample of

4,074 online gamers. Two regression models were constructed to separately explain

gaming addiction and high engagement using social motivations to play, while

controlling for age, gender, and time spent online.

Results

High scores on subscales measuring dysfunctional detachment and destructive

overdependence were positively associated with online gaming addiction, while

healthy dependency was negatively correlated with addiction scores. In contrast, the

overall role of social motivation was negligible.

Discussion

People with healthy relationship profiles are less likely to develop problematic

patterns of online gaming. High in-game engagement, although sharing some factors

96
with addiction, was only poorly explained by the study variables, suggesting the

mutual exclusiveness of addiction and engagement.

Keywords: Online Gaming Addiction; High Engagement; Interpersonal Dependency;

Motivations to Play

97
Introduction

During the last decade and a half, Massive Multiplayer Online Games (MMOGs)

have become a significant entertainment medium to which millions of young people

devote a large portion of their leisure time (Williams, Yee, & Caplan, 2008).

Although mere entertainment and leisure activity for most gamers, a certain

proportion report that online gaming took over their lives and caused serious

problems in their social or occupational functioning (Haagsma, Pieterse, Peters, &

King, 2013). Health-related negative consequences are also among the symptoms of

excessive patterns of online gaming and include low quality and quantity of sleep,

neglecting meals or poor and unhealthy diet, repetitive strain injuries, etc. (c.f.

Kalmus, Siibak, & Blinka, 2014 for an overview). The most excessive players may

spend 40 hours or more per week online, which equals or exceeds the amount of time

spent in a regular full-time job (Dauriat et al., 2011). Online gaming has been shown

to be the riskiest online activity in terms of the development of Internet addiction and

related problems (Blinka et al., 2015).

The American Psychiatric Association included Internet Gaming Disorder in Section

3 of its revised diagnostic manual, DSM-5, as a potential future diagnosis that

requires further investigation (APA, 2013). However, whether problematic patterns of

online gaming represent a distinct psychiatric condition that belongs among

behavioural addictions is not yet a matter of consensus within the scientific

community (Griffiths, King, & Demetrovics, 2014). Although Griffiths’ criteria

(2005) of behavioural addiction were generally accepted in the research of online

gameing addiction, not all criteria were identified as similarly contributing to the

increase of pathology. Peripheral criteria (euphoria, cognitive salience, and tolerance),

especially when dominantly present without core criteria (behavioural salience,

98
withdrawal symptoms, relapse, and conflict), seem to be signs of non-pathological

gaming (Charlton & Danforth, 2004). Such high engagement in online gaming,

although extensive at first glance but non-problematic at the second, is not connected

to those personality traits which are associated with pathological gaming (Charlton &

Danforth, 2007, 2010). This suggests that high engagement and addiction, although

overlapping in some symptoms, are rather distinct categories and thus points toward

the usefulness of differentiating approaches in measuring Internet gaming addiction.

The addictive potential of online games is usually associated with the reward aspects

of gaming (King, Delfabbro, & Griffiths, 2011). However, MMOGs are inherently

social environments and thus the social aspects of games, the social motivations of

gamers, and their sociability may play an important role. As shown by Ng and

Wiemer-Hastings (2005), MMOGs are played much more intensively compared to

non-MMOGs. The difference is the community – while offline video games are

solitary or a small-group activity; thousands of people are online in MMOGs at the

same time. MMOGs represent a rich and valued source of social contacts for gamers

through in-game interactions, discussion forums, and also communication beyond the

gaming tasks (Yee, 2006; Cole & Griffiths, 2007). It has also been reported that

collective gaming, necessary for reaching advanced in-game content, leads to more

time spent online and may contribute to the development of patterns of compulsive

gaming (Haagsma, Pieterse, Peters, & King, 2013). According to the Social

Compensation Hypothesis (Caplan, 2003; Davis, 2001), lonely individuals are

especially prone to compulsive Internet use as they seek social support, which they

lack in their natural offline environment. Such gamers may then be caught in a vicious

circle - with increasing time spent online for in-game social interactions and in-game

group commitments, there may follow a negative effect on daily functioning and face-

99
to-face interactions, and the sense of loneliness may worsen (Davis, 2001; Shen &

Williams, 2011). From this point of view, the social motivation for gaming (i.e. the

seeking of in-game social support) can be expected to contribute to increased

addictive gaming. Nevertheless, such a direct relationship has not yet been confirmed.

Several studies indicate that this relationship is rather negligible (Blinka & Mikuška,

2014; S. Caplan, Williams, & Yee, 2009; Dauriat et al., 2011; Kardefelt-Winther,

2014; Király et al., 2015). According to Blinka and Mikuska (2014), a gamer’s social

skills and personality traits, such as lower interpersonal trust and lower social self-

efficacy, contribute to the development of pathological gaming more than the actual

social motivation for gaming. Gamers with schizoid personality traits and higher

introversion are reported to be more at risk of problematic online gaming (Kuss &

Griffiths, 2012). This finding indicates that the underlying psychological dispositions

of individuals may be the key to the relationship between social motivations and

online gaming addiction, and to the development of online gaming addiction.

Interpersonal dependency represents a useful concept to study the social traits of

gamers in relation to potential pathological game play. The concept itself describes

how people rely on others – how their cognition, motivation, affective responses, and

actual behavioural patterns are affected by relationships to others (Bornstein,

Porcerelli, Huprich, & Markova, 2009). The concept is, to some extent, similar to the

concept of attachment; for instance, high levels of interpersonal dependency share

some similarities with insecure attachment (Pincus & Wilson, 2001).

Bornstein divided the idea of interpersonal dependency into a three-dimensional

concept (Bornstein et al., 2003). The three dimensions of interpersonal dependency

are healthy dependency (confidence and autonomy, desire for closeness, and

situation-appropriate help seeking) representing healthy functioning; and two

100
representing dysfunctional functioning - destructive overdependence (characterised by

weak self, fear of negative evaluation, and reassurance seeking) and dysfunctional

detachment (fear of being hurt, fear of being overwhelmed by others, and consequent

need for control over social situations) (Bornstein et al., 2003). Individuals with

unhealthy interpersonal dependency traits tend to be more sensitive to peer pressure,

less stable in their attitudes and beliefs, and have a more pronounced need for

acceptance by others (Bornstein, 2009). These characteristics may be associated with

negative consequences and feelings in some social contexts and situations, but may be

effective and useful in others.

Destructive overdependence and dysfunctional detachment may underlie the affect of

dysregulation in individuals that may, subsequently and reportedly, put individuals at

risk of psychological and physiological disease (Fiori, Consedine, & Magai, 2008).

Individuals scoring high in interpersonal dependence face more psychological

impairment through decreased lower self-esteem and increased depression, loneliness,

and overall emotional dysregulation (Overholser, 1992). When observed, the

association between interpersonal dependency traits and substance use disorders (e.g.

smoking and alcoholism) was generally linked to orally dependent personality

features (Greenberg & Bornstein, 1988). The link between dependency traits and the

tendency to addictive behavioural patterns might, therefore, lead to the compensation

of unsatisfying or imperilling social contacts in real life. Thus, as online games are

inherently social environments, we assume that interpersonal dependency and the

conceptualizing social orientation of the individual might be a significant factor

explaining why some gamers tend to pathological gaming while others do not.

101
Research focus and hypotheses

In the present study we examine social motivations as conscious preferences and

personal traits represented by the three dimensions of interpersonal dependency in

relationship to highly engaged and addictive gaming.

Based on a literature review we expect the following:

H1: Social motivations do not play an important role in online gaming addiction, and

online gaming addiction is predicted by personality traits related to social

functioning. Social situation was expected to contribute to problematic gaming by

some researchers (Lemmens, Valkenburg, & Peter, 2011). However, the relationship

between online gaming addiction and social motivations, which may be a conscious

reflection of the lack of social contact, is not supported in literature.

H1a: Destructive overdependence is positively associated with online gaming

addiction. We expect that personal traits associated with orientation towards social

commitment and the need for positive feedback from the community may be an

important factor that contributes to higher addictive potential in these gamers.

H1b: Dysfunctional detachment is positively associated with online gaming addiction.

We expect that the MMOG environments, where it is easy to control social

interactions and there is a lack of face-to-face interactions, attract gamers who score

high in dysfunctional detachment.

H1c: Healthy dependency is negatively associated with online gaming addiction. We

expect that the healthy dependency personality trait, usually associated with healthy

social functioning, is negatively associated with online gaming addiction.

102
H2: High engagement in online gaming is not, in contrast to online gaming addiction,

significantly associated with the social motives and psychological traits significant

for social functioning. A large number of motives for online gaming has been

identified (Yee, 2006; Koo, 2009; King et al., 2011). We assume that intensive yet

non-pathological gamers enjoy the game for these various reasons and thus they are

not a group with any unified gaming pattern nor psychological trait or distress.

Methods

Participants

The data come from the first wave of a three-wave longitudinal online survey of

Internet gaming addiction. A total sample of 6,730 Czech and Slovak online gamers

was recruited through advertisement in online gaming magazines, on gaming

discussion forums, and on guild websites. The ads targeted the core of the Czech and

Slovak gaming community, with heavy players expected to be the highest proportion.

Incentives in the form of lottery prizes were used to solicit higher participation. The

questionnaire was published in Czech on the Lime Survey platform in Spring 2013. A

subsample of 4,074 players (ages 10-68; M = 20.81, SD = 5.95; 93.50% male) of

MMORPG and MOBA games was selected for the analysis, and measurement tools

were developed specifically for these types of games. Participants spent between two

and 92 hours per week playing online games (M = 32.85, SD = 16.72); League of

Legends (MOBA, 35.22%) and World of Warcraft (MMORPG, 19.69%) were the

most played games in the sample. Female players were significantly older compared

to males (Females: M = 21.79, SD = 6.80; Males: M = 20.75, SD = 5.88; p < 0.05);

103
and spent significantly less hours gaming per week (Females: M = 27.85, SD = 15.84;

Males: M = 33.20, SD = 16.73; p < 0.001).

Measures

Online gaming addiction was measured using the Addiction-Engagement

Questionnaire (AEQ), a 24-item tool with response options on a four-point scale (1-

strongly disagree; 4-strongly agree). The tool distinguishes between online gaming

addiction (12 items) and high engagement in online games (12 items). The addiction

subscale focuses on core addiction criteria, such as conflict, behavioural salience, and

withdrawal, while the engagement subscale measures peripheral addiction criteria,

such as cognitive salience, euphoria, and tolerance (Charlton & Danforth, 2007,

2010). Since the scale was not validated for discriminatory purposes, it is used as a

continuum. Both subscales had sufficient internal consistency (Cronbach’s α = 0.79

for addiction and Cronbach’s α = 0.72 for high engagement). We created two new

combined variables for addiction and engagement as mean scores of the respective

subscales ranging from 1 to 4 (MADD = 1.82, SDADD = 0.49; MENG = 2.50, SDENG =

0.26).

The frequency of online gaming, expressed in weekly playing hours, was constructed

as a combined measure using two open-ended questions: “In the last 3 months, how

much time (in hours) did you usually spend gaming on a normal working day?” and

“In the last 3 months, how much time (in hours) do you usually spend gaming on a

day off?” Respondents who did not play in the last three months (i.e. obtained zero in

the combined frequency variable) were excluded from the analysis.

To obtain information about game genre, respondents were asked to name a game

they played most often in the last three months. Only players of MMORPG and

104
MOBA games were included in the analysis, as the AEQ scale contained some items

relevant only to these types of games (i.e. questions on virtual character, levelling,

collecting armour, etc.).

Interpersonal dependency was measured using 30 items of the Relationship Profile

Test (RPT) (Bornstein, Geiselman, Eisenhart, & Languirand, 2002). The scale

distinguishes between destructive overdependence (Cronbach’s α = 0.81), healthy

dependence (Cronbach’s α = 0.63), and dysfunctional detachment (Cronbach’s α =

0.67), with 10 items providing answer options ranging from “very true” to “not at all

true” and representing each subscale. The three new variables, created as mean scores

of each sub-scale, ranged between 1 and 5 (MDO = 2.95, SDDO = 0.75; MHD = 3.63,

SDHD = 0.56; MDD = 3.22, SDDD = 0.60).

Social motivations for online gaming were measured using two subscales based on

eight items selected from the pool of the most commonly used questionnaires on

player’s motivations (Hsu, Wen, & Wu, 2009; Koo, 2009; Yee, 2006). Examples of

the items are: “I like talking to other players”; “I enjoy being part of the gaming

community”; “I sometimes share worries with other players”; and “I appreciate when

fellow players offer support in my real-life situations.” The four-point response scale

(strongly disagree – strongly agree) focused on respondents’ attitudes rather than

actual behaviour. The exploratory factor analysis showed two factors – team play

(five items) and social support (three items). Both scales had sufficient internal

consistency (Cronbach’s α = 0.75 for team play and Cronbach’s α = 0.70 for social

support). The final variables were created as mean scores of the respective items and

ranged between 1 and 4.

105
Data analysis

Pearson’s correlation coefficients were calculated for addiction, engagement, and all

predictors. Two separate regression models were constructed using a stepwise

hierarchical linear regression to determine the association between online gaming

addiction / engagement and social motivations / interpersonal dependency traits, while

controlling for age, gender, frequency of online gaming, and game genre.

Ethics

The study did not require approval of the ethics committee. In line with the university

ethical guidelines (CTT, 2015), details about the study aims, procedures, and the data

collected were provided on the first page of the questionnaire. As the participation

was solicited via online advertisement and parents of the underage children could not

be addressed directly, minors were requested to confirm that they would participate in

the survey with parental approval.

Results

Pearson’s correlation coefficients indicate a statistically significant relationship

between addiction and all predictors; addiction is negatively correlated with the

healthy-dependency-personality trait (r = -0.18, p < 0.01 ) and age (r = -0.23, p <

0.01). There is no relationship between the motivations for in-game social support and

high engagement (r = -0.03, p = 0.07). Time spent online is associated to both

addiction (r = -0.34, p < 0.01) and engagement (r = -0.11, p < 0.01), although the

effect is stronger for addiction. The association with the negative aspects of

interpersonal dependency -- destructive overdependence and dysfunctional

detachment -- is stronger for addiction than for engagement in online gaming. The

two negative aspects correlate positively, while there is a negative association with

106
healthy dependency. Healthy dependency is negatively correlated with addiction and

positively with both types of social motivations, while there is either no or negligible

association between social motivations and negative dependency traits. Team play is

negatively associated with both addiction and engagement. The correlation between

social support and healthy dependency indicates that these two concepts may be

related. The need for in-game social support also increases with age. Table 1

summarizes the results of the correlational analysis.

[INSERT TABLE 1 HERE]

Table 2 shows three linear regression models explaining online gaming addiction by

using the main interpersonal dependency subscales and social motivations. It confirms

that the negative aspects of interpersonal dependency are positive predictors for

online gaming addiction (hypotheses H1a and H1b), while there is a significant

negative association with healthy dependency (hypothesis H1c). The main effect of

social motivation is small and has only a limited impact on the relationship between

addiction and interpersonal dependency. Adding interpersonal dependency variables

into the model reduces the effect of social motivations; team play, particularly,

becomes non-significant in the third regression step. Overall, the final model explains

25% of the variance of online gaming addiction. Thus, we consider the whole

hypothesis H1 as confirmed.

[INSERT TABLES 2 & 3HERE]

Table 3 shows similar models for engagement to online games as a dependent

variable; the effect of the predictors is less pronounced and the final model explains

only 8% of the variance of online gaming engagement. Contrary to online gaming

addiction, adding dependency traits into the model slightly increased the effect of

107
social motivations in the final model. The need for social support is a positive

predictor for online gaming addiction patterns, but it is negatively associated with

high engagement and this effect, although small, remains significant despite the

interpersonal dependency traits in the final model. Thus, we cannot fully support

hypothesis H2 – the associations are opposite in comparison to addiction; however,

small but significant association with social motivation and interpersonal dependency

traits still exist.

Discussion

The present study confirmed that interpersonal dependency traits are crucial in

developing addictive behaviours discounting from the social motivation factors. Both,

dysfunctional detachment and destructive overdependence increase the online gaming

addiction score, while healthy dependency is associated with lower addiction scores.

The relationship between various addictions and overdependence has been reported in

literature (Loas et al., 2005) and our study extends the evidence of its relationship to

online gaming addiction. It must be noted that dysfunctional detachment and

destructive overdependence are not mutually distinct categories. On the contrary, they

are often found together (Bornstein et al., 2003; Bornstein et al., 2009) and they were

also mildly correlated in our research. In the case of online gaming, that means that

some of the pathological gamers may use MMOGs as an escape to a more secure and

controlled social environment and, at the same time, seek the social support and

recognition of fellow gamers. A concept very closely related to healthy dependency is

connectedness (Bornstein, 2009). Decreased connectedness has been reported to be

associated with increased general problematic Internet use (McIntyre, Wiener, &

Saliba, 2015). Our final model explaining the 25% variance of online gaming

addiction is completed with demographic- and gaming-style variables – gender does

108
not play a role, while younger gamers (those preferring the MOBA genre to

MMORPG and those spending more time in the game) seem to be more susceptible.

While the facts that younger gamers are more at risk of gaming addiction and that the

gender effect is rather negligible have been shown in literature (Caplan, Williams,

Yee, 2009), the change in the effect of the game genre is new information.

Traditionally, MMORPGs like World of Warcraft were shown to be the environment

which tended to attract or produce problematic gaming patterns. The fact that the

newly emerging MOBA genre even surpasses the MMORPGs should be further

investigated together with other possible emerging trends in the gaming industry.

High involvement in online gaming, on the other hand, is less connected to the

psychological underpinning of impairments in interpersonal relationships and can be

seen more as controlled, although time-consuming, behaviour. This suggests that

highly engaged and addicted gamers are a qualitatively distinct category and that they

differ not only in the mere quantity of the activity. Such a result is in line with the

previous findings of Charlton and Danforth (2010) and gives support to the approach

of measuring Internet gaming addiction that distinguishes types of involvement. Our

model combines demographic variables, personality traits, and social motivation for

gaming, and explained only 8% of the variance of engagement points to online

gaming as an entertaining activity, which is not necessary to problematize. Similar

results have been reported elsewhere, though different methods were used (e.g. Király

et al., 2015; Griffiths, 2010).

Healthy dependency is positively associated with both types of social motivation,

while there is a negligible relationship between social motives and destructive

overdependence, and a negative relationship between social motives and

dysfunctional detachment. Social motives, therefore, prevail in people who show a

109
healthy need for social contact, and online games are efficient sources for social

interaction. For some authors, motivations to play represent conscious choices that are

key to understanding the etiology of excessive patterns of online gaming (Kardelfelt-

Winther, 2014). In this view, the problematic patterns of online gaming are not

understood as addiction but rather as maladaptive coping strategies. This approach,

however, does not explain why only a few of those who report similar motivations to

online gaming find themselves hooked on the game, and why some develop extreme

symptoms of addiction that lead to neglecting basic drives. Our analysis indicates that

this view may be correct in terms of high involvement in online gaming, but when it

comes to loss of control, psychological factors play a role in the subsequent

development of the pathology. Billieux et al. (2015) report similar results when

demonstrating that social motivations are more typical for regulated role-play gamers

than for hard-core and unregulated players. Indeed, online gaming addiction has been

repeatedly shown to be associated with motives for immersion and escapism and with

achieving better in-game content and rewards (e.g. King et al., 2011; Király et al.,

2015; Kirby, Jones, & Copello, 2014).

A stronger relationship also exists between the time spent playing and online gaming

addiction than with time spent playing and high engagement. This finding suggests

that highly engaged gamers may have a sense for balance and can effectively control

the impact of gaming on their real-life affairs. Psychological dispositions, then, are

the underlying cause for reduced self-control and, subsequently, of disproportionate

time spent online. This would be in line with research showing that disinhibition may

manifest itself only in certain contexts, while in other situations individuals may

perform normally and show sufficient levels of self-control (Hofmann, Friese, &

Strack, 2009). The lack of self-control in online gaming might piggyback on unrelated

110
psychological discomfort, in this case as unsatisfying social contacts as a result of

unhealthy interpersonal dependency traits.

The limitations of this study are associated with the fact that, unlike interpersonal

dependency traits, motivations to play and the level of involvement in online gaming

may vary over time. The cross-sectional nature of the present study, therefore, cannot

capture the whole complexity of the relationships delineated earlier in this text. It

should also be acknowledged that our data come from a non-representative, self-

selected sample of Czech and Slovak online gamers. However, this fact should not

compromise the correlational analysis (Gosling, Vazire, Srivastava, & John, 2004).

Online gaming addiction, distinguished here from high engagement in online gaming,

is not a medical diagnosis and should be interpreted with regard to the respective

measurement instrument. The addiction subscale of the AEQ stresses those symptoms

of addictive behaviours that either represent various types of present conflict or

factors that may directly lead to one (i.e. behavioural salience, relapse, and

reinstatement) (Charlton & Danforth, 2007). We, therefore, cannot claim that negative

interpersonal dependency traits are predictors of addiction, but they certainly are

associated with such patterns of online gaming that put an individual at risk of

adverse consequences in many areas of life. People with healthy relationship profiles

are less likely to develop these problematic patterns of online gaming.

References

APA. (2013). Diagnostic and Statistical Manual of Mental Disorders: DSM-5:

Books4US.

Billieux, J., Thorens, G., Khazaal, Y., Zullino, D., Achab, S., & Van der Linden, M.
(2015). Problematic involvement in online games: A cluster analytic approach.
Computers in Human Behavior, 43(0), 242-250. doi:
http://dx.doi.org/10.1016/j.chb.2014.10.055

111
Blinka, L., & Mikuška, J. (2014). The role of social motivation and sociability of
gamers in online game addiction. Cyberpsychology, 8(2).

Blinka, L., Škařupová, K., Ševčíková, A., Wölfling, K., Müller, K. W., & Dreier, M.
(2015). Excessive internet use in European adolescents: what determines differences
in severity? International Journal of Public Health, 1-8.

Bornstein, R. F., Geiselman, K. J., Eisenhart, E. A., & Languirand, M. A. (2002).

Construct Validity of the Relationship Profile Test Links With Attachment, Identity,
Relatedness, and Affect. Assessment, 9(4), 373-381.

Bornstein, R. F., Languirand, M. A., Geiselman, K. J., Creighton, J. A., West, M. A.,
Gallagher, H. A., & Eisenhart, E. A. (2003). Construct validity of the Relationship
Profile Test: A self-report measure of dependency-detachment. Journal of personality
assessment, 80(1), 64-74.

Bornstein, R. F. (2009). Interpersonal dependency. In Leary, M. R., & Hoyle, R. H.

(Eds.). (2009). Handbook of individual differences in social behavior. Guilford Press.

Caplan, S., Williams, D., & Yee, N. (2009). Problematic Internet use and
psychosocial well-being among MMO players. Computers in Human Behavior, 25(6),
1312-1319.

Caplan, S. E. (2003). Preference for Online Social Interaction A Theory of

Problematic Internet Use and Psychosocial Well-Being. Communication Research,
30(6), 625-648.

Charlton, J. P., & Danforth, I. D. (2004). Differentiating computer-related addictions

and high engagement. Human perspectives in the internet society: culture, psychology
and gender, 4, 59-68.

Charlton, J. P., & Danforth, I. D. (2007). Distinguishing addiction and high

engagement in the context of online game playing. Computers in Human Behavior,
23(3), 1531-1548.

Charlton, J. P., & Danforth, I. D. (2010). Validating the distinction between computer
addiction and engagement: online game playing and personality. Behaviour &
Information Technology, 29(6), 601-613.

Cole, H., & Griffiths, M. D. (2007). Social interactions in massively multiplayer

online role-playing gamers. CyberPsychology & Behavior, 10(4), 575-583.

CTT. (2015). Nakládání s výzkumnými daty na Masarykově univerzitě: Centrum pro

transfer technologií, Masarykova univerzita.

Dauriat, F. Z., Zermatten, A., Billieux, J., Thorens, G., Bondolfi, G., Zullino, D., &
Khazaal, Y. (2011). Motivations to play specifically predict excessive involvement in
massively multiplayer online role-playing games: evidence from an online survey.
European Addiction Research, 17(4), 185-189.

Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use.

Computers in Human Behavior, 17(2), 187-195.

112
Fiori, K., Consedine, N., & Magai, C. (2008). The adaptive and maladaptive faces of
dependency in later life: Links to physical and psychological health outcomes. Aging
and Mental Health, 12(6), 700-712.

Gosling, S. D., Vazire, S., Srivastava, S., & John, O. P. (2004). Should we trust web-
based studies? A comparative analysis of six preconceptions about internet
questionnaires. American Psychologist, 59(2), 93.

Greenberg, R. P., & Bornstein, R. F. (1988). The dependent personality: II. Risk for
psychological disorders. Journal of Personality disorders, 2(2), 136-143.

Griffiths, M. (2005). A ‘components’ model of addiction within a biopsychosocial

framework. Journal of Substance Use, 10(4), 191-197. doi:
10.1080/14659890500114359

Griffiths, M. D. (2010). The role of context in online gaming excess and addiction:
Some case study evidence. International Journal of Mental Health and Addiction,
8(1), 119-125.

Griffiths, M. D., King, D. L., & Demetrovics, Z. (2014). DSM-5 internet gaming
disorder needs a unified approach to assessment. Neuropsychiatry, 4(1), 01-04.
doi:http://dx.doi.org/10.2217/npy.13.82

Haagsma, M. C., Pieterse, M. E., Peters, O., & King, D. L. (2013). How gaming may
become a problem: A qualitative analysis of the role of gaming related experiences
and cognitions in the development of problematic game behavior. International
Journal of Mental Health and Addiction, 11(4), 441-452.

Hofmann, W., Friese, M., & Strack, F. (2009). Impulse and self-control from a dual-
systems perspective. Perspectives on Psychological Science, 4(2), 162-176.

Hsu, S. H., Wen, M.-H., & Wu, M.-C. (2009). Exploring user experiences as
predictors of MMORPG addiction. Computers & Education, 53(3), 990-999.

Kalmus, V., Siibak, A., Blinka, L. (2014) Internet and child well-being. In Ben-Arieh,
A.; Frønes, I.; Casas, F.; Korbin, J.E. (Eds.) Handbook of Child Well-Being (pp. 2093-
2133). Dordrech: Springer

Kardefelt-Winther, D. (2014). A conceptual and methodological critique of internet

addiction research: Towards a model of compensatory internet use. Computers in
Human Behavior, 31, 351-354.

King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2011). The role of structural
characteristics in problematic video game play: An empirical study. International
Journal of Mental Health and Addiction, 9(3), 320-333.

Király, O., Urbán, R., Griffiths, M. D., Ágoston, C., Nagygyörgy, K., Kökönyei, G.,
& Demetrovics, Z. (2015). The Mediating Effect of Gaming Motivation Between
Psychiatric Symptoms and Problematic Online Gaming: An Online Survey. Journal
of medical Internet research, 17(4), e88.

113
Kirby, A., Jones, C., & Copello, A. (2014). The impact of massively multiplayer
online role playing games (MMORPGs) on psychological wellbeing and the role of
play motivations and problematic use. International Journal of Mental Health and
Addiction, 12(1), 36-51.

Koo, D.-M. (2009). The moderating role of locus of control on the links between
experiential motives and intention to play online games. Computers in Human
Behavior, 25(2), 466-474.

Kuss, D., & Griffiths, M. (2012). Internet Gaming Addiction: A Systematic Review
of Empirical Research. International Journal of Mental Health & Addiction, 10(2),
278-296. doi: 10.1007/s11469-011-9318-5

Lemmens, J. S., Valkenburg, P. M., & Peter, J. (2011). Psychosocial causes and
consequences of pathological gaming. Computers in Human Behavior, 27(1), 144-
152.

Loas, G., Guilbaud, O., Perez-Diaz, F., Verrier, A., Stephan, P., Lang, F., . . .
Flament, M. F. (2005). Dependency and suicidality in addictive disorders. Psychiatry
research, 137(1), 103-111.

McIntyre, E., Wiener, K. K., & Saliba, A. J. (2015). Compulsive Internet use and
relations between social connectedness, and introversion. Computers in Human
Behavior, 48, 569-574.

Ng, B. D., & Wiemer-Hastings, P. (2005). Addiction to the internet and online
gaming. CyberPsychology & Behavior, 8(2), 110-113.

Overholser, J. C. (1992). Interpersonal dependency and social loss. Personality and

Individual Differences, 13(1), 17-23.

Pincus, A. L., & Wilson, K. R. (2001). Interpersonal variability in dependent

personality. Journal of Personality, 69(2), 223-251.

Shen, C., & Williams, D. (2011). Unpacking time online: Connecting internet and
massively multiplayer online game use with psychosocial well-being. Communication
Research, 38(1), 123-149.

Williams, D., Yee, N., & Caplan, S. E. (2008). Who plays, how much, and why?
Debunking the stereotypical gamer profile. Journal of Computer‐Mediated
Communication, 13(4), 993-1018.

Yee, N. (2006). Motivations for play in online games. CyberPsychology & Behavior,
9(6), 772-775.

114
Table 1: Correlations of main study variables.
(1) (2) (3) (4) (5) (6) (7) (8) (9)
Addiction (1) - .25** .29** .22** -.18** .10** .13** -.23** .34**
Engagement (2) - .12** .15** .07** .12** .03 -.19** .11**
Destructive overdependence (3) - .28** -.20** .03 .07** -.18** .07**
Dysfunctional detachment (4) - -.18** -.19** -.08** .02 -.01
Healthy dependency (5) - .27** .19** .00 -.03
Team play (6) - .49** -.23** .19**
Social support (7) - -.06** .15**
Age (8) - .21**
Frequency of gaming (9) -
Note: ** p < .01

115
Table 2: Linear regression models for online gaming addiction (method: stepwise).
Model 1 Model 2 Model 3

b β Sig. b β Sig. b β Sig.

Constant 1.81 <.01 1.81 <.01 1.14 <.01
Gender (Female=1, Male=2) -0.04 -0.02 0.17 -0.03 -0.02 0.28 -0.01 0.00 0.79
Age -0.01 -0.14 <.01 -0.01 -0.15 <.01 -0.01 -0.10 <.01
Frequency of gaming 0.01 0.30 <.01 0.01 0.29 <.01 0.01 0.27 <.01
Genre (MMORPG=0, MOBA=1) 0.08 0.08 <.01 0.08 0.08 <.01 0.08 0.09 <.01
Team Play (TP) -0.05 -0.06 <.01 0.02 0.02 0.26
Social Support (SS) 0.06 0.10 <.01 0.06 0.09 <.01
Destructive overdependence (DO) 0.11 0.17 <.01
Dysfunctional detachment (DD) 0.14 0.17 <.01
Healthy dependence (HD) -0.11 -0.13 <.01

F 146.75 104.12 131.50

P <.001 <.001 <.001
R Square 0.14 0.15 0.25

Table 3: Linear regression models for high engagement in online gaming (method: stepwise).
Model 1 Model 2 Model 3

b β Sig. b β Sig. b β Sig.

Constant 2.59 <.01 2.50 <.01 2.01 <.01
Gender (Female=1, Male=2) 0.00 0.00 0.87 0.00 0.00 0.80 0.00 0.00 0.89
Age -0.01 -0.16 <.01 -0.01 -0.14 <.01 -0.01 -0.13 <.01
Frequency of gaming 0.00 0.09 <.01 0.00 0.08 <.01 0.00 0.08 <.01
Genre (MMORPG=0, MOBA=1) 0.01 0.03 0.14 0.01 0.02 0.25 0.02 0.03 0.09
Team Play (TP) 0.04 0.09 <.01 0.04 0.10 <.01
Social Support (SS) -0.01 -0.04 0.03 -0.02 -0.06 <.01
Destructive overdependence (DO) 0.02 0.07 <.01
Dysfunctional detachment (DD) 0.07 0.17 <.01
Healthy dependence (HD) 0.04 0.10 <.01

F 37.07 28.01 36.38

P <0.001 <0.001 <0.001
R Square 0.04 0.04 0.08

116