2012. Vol.3, No.4, 310-314
Published Online April 2012 in SciRes (
Copyright © 2012 SciRes.
Risk Factors Associated with the Abuse of Video Games
in Adolescents
Ricardo A. Tejeiro1, Jorge L. Gómez-Vallecillo1, Manuel Pelegrina2,
Agustín Wallace2, Enrique Emberley3
1Departamento de Psicología, Facultad de Ciencias de la Educación, Universidad de Cádiz,
Campus Río San Pedro, Cádiz, Spain
2Departamento de Metodología, Facultad de Psicología, Universidad de Málaga, M álaga, Spain
3Centro de Profesorado del Campo de Gibraltar, La Lín ea d e l a Co ncep ción , Spain
Email: {ricardo.tejeiro, jorge.gomez}, {pelegrina, awallace},
Received January 4th, 2012; revised February 10th, 2012; accepted March 16th, 2012
Several studies have revealed the existence of a maladaptive pattern of video game use whose symptoms
are quite similar to those of the disorder referred to as “abuse” in the DSM-IV-TR (APA, 2000). The aim
of this paper is to examine the psychosocial characteristics of the adolescent video game abusers and to
compare them with the risk factors that the literature associates with substance dependence. For this pur-
pose, two groups (“problem” and “social” players) were formed with 236 Spanish adolescents aged be-
tween 12 and 17 years, by means of the Problem Video Game Playing questionnaire (PVP; Tejeiro &
Bersabe, 2002), and their psychosocial characteristics were then analyzed by means of a wide battery of
tests. Only 37.3% of the problem players showed a psychosocial pattern similar to the risk factors for de-
pendence; an integral model of maladaptive behavior is discussed as explanation for these persons’ video
game abuse. The other 69.6% of “problem players” only differed from the “social players” in their over-
use of video games (but not in other psychosocial factors); the social learning approach is suggested for
these adolescents’ behavior.
Keywords: Video Games; Adolescence; Dependence; Abuse; Risk Factors
Over the last 30 years, addiction has been one of the prob-
lems most commonly associated with the use of video games
(Tejeiro, Pelegrina, & Gómez-Vallecillo, 2009). As with the
presumed behavioral addictions to Internet (Ferraro, Caci,
D’Amico, & Di Blasi, 2007), cell phone (Beranuy, Chamarro,
Graner, & Carbonell, 2009), sex (Goodman, 1989) and others,
the adaptation of the diagnostic criteria for substance depend-
ence or pathological gambling from the American Psychiatric
Association’s Diagnostic and Statistical Manual of Mental Dis-
orders (DSM) has been the methodological choice of a majority
of diagnostic or screening studies on video game “addiction”.
Results range from 6 to 19 percent of apparently “addicted”
video game players, as shown in Table 1.
One of the scales developed from this perspective is the PVP
(Problem Video Game Playing Questionnaire; Tejeiro & Ber-
sabe, 2002). Its 9 items are based on the DSM-IV (APA, 1994)
criteria for substance dependence and for pathological gam-
bling, as well as the literature on addictions. Psychometric ana-
lyses show that the PVP is one-dimensional and has acceptable
internal consistency (Cronbach’s alpha) at .69. The pattern of
associations between the scale scores and alternative measures
of problem play supports its construct validity (higher total
scores in the scale were associated with higher frequency of
play, mean and longest times per session, self and parents per-
ception of playing to excess, and scores in the Severity of De-
pendence Scale).
However, while it is true that the PVP and other DSM adap-
tations make it possible to detect and to assess the presence of
an apparently addictive disorder, it remains unclear if this dis-
order can be referred to as an “addiction”. The PVP authors
presented their instrument as a quantitative measure, not as a
tool for the diagnosis of addiction, and different studies in the
Table 1.
“Addiction” to video games: prevalence studies.
Study Country Percentage of “addicted”
Fisher (1994, 1995) UK 6%
Griffiths & Dancaster (1995)UK 8%
Phillis, Rolls , Rouse,
& Griffiths (1995) UK 7.5%
Haugue & Ge n til e
(2003) USA 15%
Arab et al. (2006 ) Chile 10% - 15%
Rau, Peng, & Yang (2006) China 19%
Grusser, Thalemann,
& Griffiths (2007) Germany 11.9%
Ko et al. (2007) Taiwan 7.5%
Moussa (2008) France 8%
Gentile (2009) USA 8.5%
Peng & Li (20 09) China 10.3%
Porter, Starcevic,
Berle, & Fenech (2010) Australia 8%
Gentile et al. (2011) Singapore 9.9%
United States of America (Lyles, 2007; Langley, 2010; Elliott,
Golub, Ream, & Dunlap, 2011; Ream, Elliott, & Dunlap, 2011a,
2011b; Tolchinsky & Jefferson, 2011), France (Bioulac, Arfi,
& Bouvard, 2008, 2010), United Kingdom (Collins, Freeman,
& Chamarro-Premuzic, 2012), Ca nada (Adlaf, Paglia-Boak, Be i-
tchman, & Wolfe, 2008; Parker et al., 2008; Taylor, 2008; La-
frenière, Vallerand, Donahu e, & L a v i g ne, 2009), Ice l a n d (Hró a -
rsson, 2004; Einarsdóttir, 2008; Skarphédinsson, Pálsdóttir, &
Ólason, 2008), China (De-Lin Sun et al., 2008), Australia (Lo-
ton, 2007), Brazil (Icassati-Suzuki, Vieira, Araujo, & Magallaes,
2009), Thailand (Supaket, Munsawaengsub, Nanthamongkol-
chai, & Apinuntavetch, 2008) an d Peru (Vallejos & Capa, 2010)
have followed this suggestion in using the PVP as a quantita-
tive approach. Contrariwise, Arab et al. (2006, 2007) in Chile
used the instrument to diagnose “video game addiction” when
respondents answered affirmatively 2 or more items.
Tejeiro (2002) suggested that the pattern of problems associ-
ated with high PVP scores can be best referred to as “abuse”,
since it is quite similar to the DSM-IV-TR (APA, 2000) criteria
for substance abuse: a maladaptive pattern (of use) leading to
clinically significant impairment or distress as manifested by a
failure to fulfill major role obligations at school or home, or
continued use despite having persistent or recurrent social or
interpersonal problems caused or exacerbated by the behavior
(arguments, physical fights). Similarly, Sánchez-Carbonell, Ber-
anuy, Castellana, Chamarro, & Oberst (2008) concluded that
the presumed mobile phone addiction should be better concep-
tualized as an example of abuse.
Another problem with this approach is that all the studies
that have used DSM based instruments have considered the
“addicted” video game players as a homogeneous group, but in
no case this homogeneity has been tested. For example, Haughe
and Gentile stated that “the addicted group revealed more re-
ports of involvement in physical fights in the last year, more
arguments with friends and teachers, higher hostile attribution
scores, and lower grades” (Haughe & Gentile, 2003), but they
didn’t specify if all the “addicted” did equally share this prob-
lem profile.
The current study utilizes one of these instruments, the PVP,
to analyze the psychosocial characteristics of those adolescents
who are video games abusers. Our hypothesis is that these risk
factors are similar to those of substance abusers. For this pur-
pose, an integral approach to the addictions will be assumed in
which this condition is associated with numerous risk and pro-
tection factors, both individual and social (Calafat, Armengual,
Farres, Mejias, & Borras, 1992).
Seven hundred and thirty seven secondary school students
participated in the study. Students were recruited from ten ur-
ban public schools in the Spanish cities of La Linea, Algeciras
and Puerto Real. The mean age of respondents was 14 years
(SD = 1.12). Forty-eight percent of respondents were female.
Participants were treated in accordance with the “Ethical Prin-
ciples of Psychologists and Code of Conduct” (American Psy-
chological Association, 1992).
Data were collected by means of a questionnaire designed for
the present study and several self-report instruments. Our ques-
tionnaire was divided into two parts. The first part was to be
fulfilled by the student and contained 12 questions regarding
his or her video game beliefs and behaviors; it also included a
classical sociometric procedure to measure popularity and
status in the class-group. The second part, to be fulfilled by his
or her teacher, included 6 questions regarding the students’
behavior and achievement. The other instruments were the PVP
(Tejeiro & Bersabe, 2002), Eysenck Personality Questionnaire-
Junior (EPQ-J; Eysenck & Eysenck, 1975), third self-adminis-
tered version of the Socialization Battery (Batería de Sociali-
zación BAS-3; Silva & Martorell, 1984), Self-concept Ques-
tionnaire, form A (Cuestionario de Autoconcepto AFA; Musitu,
García & Gutiérrez, 1991), Impulsiveness, Venturesomeness
and Empathy Scale (IVE-J; Eysenck, Easting, & Pearson, 1984),
A-D Anti-social Illegal Behaviors Questionnaire (Cuestionario
A-D de Conductas Anti-sociales-Ilegales; Seisdedos, 1988),
General Intelligence Test Domino series Form 2 (Test General
de Inteligencia TIG-2; TEA, 1990) and Situation-1 Spatial-
perceptive Test (Test Espacial-Perceptivo Situation-1; Seisde-
dos, 1990). Analyses were conducted using the SPSS version
15.0 (SPSS, Chicago, IL, USA).
Interested teachers volunteered their classrooms for inclusion
in the study and helped obtaining parental consent, with consent
levels greater than 95% for all classrooms. Each participant
then completed the nine PVP items in a form administered by
the researchers during regular classroom hours. Since our pur-
pose was to compare “addicted” versus “non addicted” players,
all the 118 participants who scored 4 or more in the PVP
(16.01% of respondents) were further considered as “problem
This cut-off point of 4 follows the suggestions of Griffiths
(1991) and Fisher (1994, 1995), but it must be noted that in
posterior analysis it was found that a variation to 5 or 3 would
not significantly affect the results. Their PVP scores ranged
from 4 to 7 (M = 5.40; SD = .92). A second group of 118 “so-
cial players” was then formed, matched in gender and age with
the previous group, among those who had played video games
during the previous year but scored less than 4 in the PVP.
“Problem” and “social players” continued in the study and
completed the rest of the aforementioned questionnaires.
A cluster analysis was performed on the data from EPQ-J,
BAS-3, AFA, A-D, TIG-2, Situation-1 and IVE-J, which iden-
tified two groups of 44 and 192 persons. All the players in the
first group were problem players, whereas the second group
included problem and social players. Three groups should
therefore be distinguished: C1, formed by the 44 participants
from the first original cluster, this is, 37.3% of the problem
players; C2, formed by the 74 problem players not included in
C1; and C3, formed by the 118 social players.
The male-female ratio is higher in C1 (6:1) than in C2
(1.46:1) and C3 (2.07:1), but differences are not significant
²(2) = 3.08; p = .215). The years of experience with the video
games in C1 (M = 8.00, SD = 1.30) are similar to those in C2
(M = 7.91; SD = 1.15) and both higher than in C3 (M = 4.70;
SD = 2.52) (F = 5.91; p = .004). Differences between groups
Copyright © 2012 SciRes. 311
were evaluated by one-factor ANOVAS with post hoc Tam-
hane’s T2, Pearson’s chi-square and Student’s t tests. C1 and
C3 members were significantly different in most of the vari-
ables, whereas C2 were similar to C1 in all the variables di-
rectly related to the use of video games, but similar to C3 in the
other variables. Results are resumed in Table 2.
C1 members are different to the others in the following vari-
ables: they score higher in introversion, hardness and tendency
to anti-social and illegal behaviors, and they score lower in
sincerity, empathy, consideration for the others and self-con-
cept. Their teachers tend to consider them as conflictive and
maladapted. These players think that their video game play is a
normal behavior, but they believe that video games may lead to
addiction, displacement of educational and social activities,
aggressiveness and poor school performance. They perceive a
low parental knowledge and control of their use of video games,
as well as low control of their general behavior. Poor commu-
nication and affective relationships are also found in these
Table 2.
Mean scores and statistical significance.
Cluster 1 Cluster 2 Cluster 3 F p
PVP 5.29 5.16
1.22 235.2 .000
Neuroticism 16.07 13.66 13.07 4.91.009
Extraversion 8.93 13.31 12.72 28.75.000
Hardmess 3.64 1.66 1.83 20.46.000
Sincerity 5.93 9.78 9.59 26.52.000
Antisocial behavior 22.79 17.34 17.24 13.45.000
Consideration 10.07 12.03 12.04 22.26.000
Self-control 6.57 8.03 8.67 7.94.001
Retreat 4.57 2.56 2.48 9.64.000
Social anxiety 4.43 3.66 4.13 1.47.236
Leadership 8.43 7.25 7.07 4.22.018
Sincerity 5.86 5.81 5.70 .13 .880
Academic self-c. 17.86 22.91 23.02 79.83.000
Social self-concept 5.36 8.50 8.41 25.48.000
Emotional self-c. 14.64 20.38 20.52 63.89.000
Family self-conc ept 6.36 9.75 9.83 37.67.000
Total self-concept 44.21 61.53 61.83 79.13.000
Impulsiveness 13.29 12.88 12.46 1.09.340
Desire for a dventure 16.50 18.69 17.91 5.73.005
Empathy 13.71 16.88 16.63 22.37.000
Antisocial behavior 12.29 8.75 8.35 24.28.000
Criminal b ehavior 3.43 .94 .93 46.81.000
TIG-2 24.14 23.38 23.46 .42 .660
Situation-1 38.29 36.94 37.22 .38 .685
families. C1 members report low shared play with their parents,
few conversations with them about this topic, lower family
satisfaction, less positive family context and less perceived
proximity to their parents. They also report higher gambling,
tobacco and alcohol use among their friends. Finally, these
players show higher absenteeism, lower satisfaction with their
school and teachers, worse relationships with their teachers, and
lower satisfaction with their city and neighborhood.
C1 and C2 members, but not C3 members, share the follow-
ing characteristics: they play video games frequently (“daily” or
“almost daily”) and in long sessions (1.5 to 2 hours). They tend
to have friends who also play video games, they like to talk to
them about this activity and they prefer and practice shared play.
TV console and computer are their preferred systems, while
sports, platforms and adventures are their favorite types of play.
C1 and C2 member s own more games and more game systems,
and they tend to play at home or in the homes of friends.
No inter-cluster differences were found in the following
variables: intelligence, perceptive and spatial skills, entertain-
ment as first reason for playing, family structure and composi-
tion, socio-economic status, frequency and satisfaction with
peer relations, and school grades.
All those who scored 4 or more in the PVP seem to present a
problem of video game abuse, although only one third of them
(included in C1) revealed a pattern of psychosocial characteris-
tics similar to the pattern of risk factors consistently associated
with addictions in the literature. The other problem players
simply have a high involvement with video games and show a
number of problem behaviors associated with this activity.
Therefore, our hypothesis was only confirmed for C1 members.
The integrated models of maladaptive behavior can account
for the abuse of video games in C1. Research has consistently
demonstrated the importance of the family with regards to the
development of behavioral problems in children and adoles-
cents (Dekovic, Janssens, & Va n As, 2003). Characteristics s uch
as conflict, lack of warmth and communication, and negligent
discipline have been identified as leading factors in adolescents
developing behavior problems that include maladaptation (less
satisfaction, poor personal well-being and worse relationships
with the figures of authority), low self-esteem and the use of
drugs as alternative gratification source (e.g., Brook, Brook,
Gordon, Whiteman, & Cohen, 1990). These children tend to
seek peer support and guide (López, 1986). If their personality
is as found in C1 (low consideration, low empathy, high neu-
roticism, high hardness, tendency to anti-social and illegal be-
haviors), their odds of joining maladapted groups increase. The
model offered by these groups includes substance abuse, gam-
bling and anti-social behaviors. Some characteristics of the
video games are particularly relevant to this pattern of relation-
ships. Video games represent a world that is seldom or never
visited by adults. Parents hardly know about the games or con-
trol their children’s use of games (Colwell & Pain, 2000).
Video games are also a challenging experience (Lepper &
Malone, 1987), a chance for these adolescents to test their skills
and thus to perceive a feeling of control and competence that
helps overcoming their low self-esteem. Video games help the
teenagers to identify themselves with the group and to find a
place in its hierarchy (Suess et al., 1998). Finally, they provide
a chance to put into practice the adolescent’s fantasies of de-
Copyright © 2012 SciRes.
struction and aggression with a high degree of realism but
without possibility of harm (Turkle, 1984). Therefore, mal-
adapted adolescents, as compared with other groups, will tend
to play more with the video games and to show higher levels of
problem behaviors (absenteeism, lies, fights, etc.) not only as-
sociated with the games but also with other realms of their
As for C2 members, the social learning approach seems to
provide the best explanation for their abuse of video games.
Higher involvement in this activity (and higher exposure to its
effects) can be seen as a consequence of the vicinity of peers
who play. C2 members were found to own more video games
and more game systems, as compared with the “non abuse”
group; it is difficult to state whether higher ownership is the
cause or a consequence of a higher involvement, but probably
the effects are bidirectional. Finally, higher involvement is
probably associated with lower parental control.
It can be concluded that adolescents tend to practice pleasant
activities without moderation, and that they find higher attrac-
tiveness in the video games than in most alternative activities.
A poor parent involvement in video game habits is expected to
facilitate the onset of problems, especially among problem
adolescents. Their condition can then be considered a form of
A number of caveats need to be noted regarding the present
study. First, it included a small sample of a specific age group
from a determined geographical area. This study is also based
on the PVP and therefore might be affected by any mistake in
this instrument’s design or validation. Finally, the strict obser-
vance of research ethics excluded the analysis of some poten-
tially relevant variables, such as aggressive behaviors in par-
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