design a quasi or a true experimental study, investigating the impact of the independent variable on the dependent variable.
vmklan
VideoGamesandAgression2.pdf
Violent Video Games and Physical Aggression: Evidence for a Selection Effect Among Adolescents
Johannes Breuer University of Münster
Jens Vogelgesang University of Erfurt
Thorsten Quandt University of Münster
Ruth Festl University of Münster and University of
Hohenheim
Longitudinal studies investigating the relationship of aggression and violent video games are still scarce. Most of the previous studies focused on children or younger adolescents and relied on convenience samples. This paper presents data from a 1-year longitudinal study of N � 276 video game players aged 14 to 21 drawn from a representative sample of German gamers. We tested both whether the use of violent games predicts physical aggression (i.e., the socialization hypothesis) and whether physical aggression predicts the subsequent use of violent games (i.e., the selection hypothesis). The results support the selection hypotheses for the group of adolescents aged 14 to 17. For the group of young adults (18 –21), we found no evidence for both the socialization and the selection hypothesis. Our findings suggest that the use of violent video games is not a substantial predictor of physical aggression, at least in the later phases of adolescence and early adulthood. The differences we found between the age groups show that age plays an important role in the relationship of aggression and violent video games and that research in this area can benefit from a more individu- alistic perspective that takes into account both intraindividual developmental change and interindividual differences between players.
Keywords: video games, violence, aggression, adolescents, young adults
From the earliest investigations into the rela- tionship of video game1 use and aggression in the 1980s (Cooper & Mackie, 1986; Dominick, 1984; Silvern & Williamson, 1987; Winkel, Novak, & Hopson, 1987) until today, hundreds
of experimental and correlational studies have been conducted. Despite the large number of studies, the debate about the link between video games and aggression is ongoing, not only in politics and the mass media, but also within academia (Bushman & Huesmann, 2014; Elson & Ferguson, 2014a, 2014b; Krahé, 2014; War- burton, 2014). While all of the available meta- analyses (Anderson et al., 2010; Ferguson, 2007; Ferguson & Kilburn, 2009; Sherry, 2001, 2007) found a relationship between aggression and the use of (violent) video games, the size and interpretation of this connection differ largely between these studies; as do the defini-
1 We use the term video games as an umbrella term that includes all types of digital games, whether they are played on a PC, home consoles, handhelds, or mobile devices. We decided to use “video game” because it is the most common term in the literature and it is easier to read than the composite “computer and video games” or the more aca- demic denomination “digital games.”
This article was published Online First February 16, 2015.
Johannes Breuer, Department of Communication, Uni- versity of Münster; Jens Vogelgesang, Department of Com- munication, University of Erfurt; Thorsten Quandt, Depart- ment of Communication, University of Münster; Ruth Festl, Department of Communication, University of Münster, and Department of Communication, University of Hohenheim.
The research leading to these results has received funding from the European Union’s Seventh Framework Pro- gramme (FP7/2007–2013) under grant agreement number 240864 (SOFOGA).
Correspondence concerning this article should be ad- dressed to Johannes Breuer, Department of Communication, University of Münster, Bispinghof 9-14, 48143 Münster, Germany. E-mail: [email protected]
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
Psychology of Popular Media Culture © 2015 American Psychological Association 2015, Vol. 4, No. 4, 305–328 2160-4134/15/$12.00 http://dx.doi.org/10.1037/ppm0000035
305
tions and measurement of violent content and aggression in the studies that were included in these meta-analyses. In addition, some meta- analyses only found a relationship for aggres- sive thoughts or feelings, but not for aggressive behavior. There is also a controversy about what exactly causes this link and, most impor- tantly, about the direction of the (potential) ef- fects.
Experimental research on video games and aggression has been criticized for a lack of ecological validity and the unstandardized use of measures of aggression that have not been properly validated (Ferguson & Rueda, 2009; Ferguson, Smith, Miller-Stratton, Fritz, & Hei- nrich, 2008; Ritter & Eslea, 2005; Tedeschi & Quigley, 1996). The issue of the real-world implications of findings from laboratory studies is further complicated by the fact that they can only investigate short-term effects that often only last for a few minutes (Barlett, Branch, Rodeheffer, & Harris, 2009). Cross-sectional correlational research, on the other hand, typi- cally has larger samples, but is unsuitable for making any claims about the direction of the effect. Longitudinal studies combine the advan- tages of cross-sectional and experimental stud- ies, as they use larger samples than most exper- imental studies and allow to sort out the temporal precedence between the variables of interest. Although it is still possible that addi- tional variables are responsible for the temporal order, given a sound control of potentially rel- evant third variables, panel studies allow to make claims about long-term effects that both cross-sectional and experimental research do not allow. Nonetheless, while panel data can help to determine direction and strengths of effects by testing for covariation and controlling for temporal order, only controlled experiments provide the means to actually prove causality (Finkel, 1995). Compared with the abundance of cross-sectional survey studies and experi- mental research, panel studies on video games and aggression are still scarce. The meta- analysis by Anderson et al. (2010), for example, included 34 effect sizes from longitudinal stud- ies2 and Ferguson and Kilburn (2009) used data from five longitudinal studies. While several longitudinal studies use a composite score for media violence that includes video games (e.g., Ferguson, Ivory, & Beaver, 2013; Gentile, Coyne, & Walsh, 2011; Krahé, Busching, &
Möller, 2012; Krahé & Möller, 2010; Ostrov, Gentile, & Crick, 2006), there are relatively few that look specifically at the effects of video games. Among those studies that explicitly in- vestigate video games, some only look at rela- tively brief periods of several months, and al- most all studies rely on convenience samples and focus on children or adolescents.
In longitudinal research on media violence and aggression, there are two seemingly com- peting hypotheses. The socialization hypothesis states that the repeated use of violent media leads to an increase of aggression over time, whereas the selection hypothesis is based on the idea of selective exposure (Zillmann & Bryant, 1985) and posits that individuals who are more aggressive will tend to choose (more) violent media content. The downward spiral model (Slater, Henry, Swaim, & Anderson, 2003) combines these hypotheses by proposing that individuals higher in trait aggression will choose more violent media content, which, in turn, increases their level of aggression. As with the experimental and cross-sectional studies, evidence from longitudinal studies on the rela- tionship between (violent) video games and ag- gression is mixed at best. Some studies found a media effect (Anderson et al., 2008; Hopf, Hu- ber, & Wei�, 2008; Möller & Krahé, 2009), while others report selection effects (von Salisch, Vogelgesang, Kristen, & Oppl, 2011), provide evidence for both (Slater et al., 2003), or found no effects (Ferguson, 2011; Ferguson, Garza, Jerabeck, Ramos, & Galindo, 2013; Fer- guson, San Miguel, Garza, & Jerabeck, 2012; Wallenius & Punamäki, 2008; Williams & Skoric, 2005).
A limitation of the previous longitudinal studies is that almost all of them rely on con- venience samples that are mostly composed of students from elementary schools, high schools, or colleges located in the areas where the re- spective researchers are based. Most studies also focus on specific grades, thereby reducing the age range of participants. In addition, even longitudinal studies often only test one direction of effects; mostly the socialization hypothesis.
2 Anderson et al. (2010) do not report the number of longitudinal studies in their paper. This number should be substantially lower than the number of effect sizes, as most longitudinal studies include cross-sectional and longitudinal effects (often also for different dependent variables).
306 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
The goal of the current study was to address some of these issues by testing both the social- ization and the selection hypothesis and com- paring these relationships for adolescents and young adults, as these groups differ with regard to their developmental stage as well as their access to (violent) video games.
Theories Explaining Long-Term Effects of Video Games on Aggression
In the field of media violence research, there are three comprehensive theoretical models that aim at explaining the relationship between vio- lent video games and aggression. The most pop- ular is the General Aggression Model (GAM; Anderson & Bushman, 2002). The GAM com- bines the assumptions of social learning (Ban- dura, 1977), excitation transfer (Zillmann, 1983), and cognitive neoassociation (Berkow- itz, 1990). Long-term effects of video game violence are explained mainly by mechanisms of social learning and cognitive neoassociation. Put briefly, the GAM posits that the repeated use of violent media causes a learning, re- hearsal, and reinforcement of aggressive be- liefs, attitudes, perceptual and expectation sche- mata, and behavioral scripts, as well as an emotional desensitization to violence. In their combination, all of these processes can lead to an increase in aggressive personality and, ulti- mately, affect the likelihood to (re-) act aggres- sively in social encounters in the real world.
Although the GAM allows to formulate spe- cific hypotheses about the effects of violent video games and has been widely used in pre- vious research, it has been criticized for its overreliance on social learning, the neglect of biological factors, the conceptualization of me- dia use(r)s as passive, and the insufficient dis- tinction between real and fictional violence (Ferguson & Dyck, 2012). An alternative theory that focuses more on genetic factors and attri- butes of the social environment is the Catalyst Model (Ferguson et al., 2008). In essence, the Catalyst Model suggests that the roots of (vio- lent) criminal and aggressive behavior are ge- netic and proximal social factors, such as family and peer influences, and their interaction, whereas distal social influences, such as media violence, only have a negligible effect (Fergu- son, Ivory, et al., 2013). In this model, violent media are considered as stylistic catalysts in-
stead of sources of aggression. This means that individuals with an increased tendency for ag- gressive behavior may model violent acts they have seen in the media, whereas the actual inclination to (re-) act aggressively is not influ- enced or caused by violent media. The main limitation of the Catalyst Model is that it is difficult to test, as the measurement of genetic and proximal social risk factors poses substan- tial challenges to the methods of social science research. To date only three studies have sys- tematically tested the Catalyst Model and found support for its main assumptions (Ferguson, Ivory, et al., 2013; Ferguson et al., 2008; Surette, 2013).
The Downward Spiral Model by Slater et al. (2003) is a theory that accounts for both the socialization and the selection hypothesis. The Downward Spiral Model has also been called the negative feedback loop model by its authors (Slater, 2003) and describes a reciprocal rein- forcement of aggressive personality and prefer- ence for violent media content. Basically, the model assumes a circular relationship between current and future aggressive tendencies and use of violent media. While the inclusion of both socialization and selection effects is a strength of this model, it does not make any detailed statements about the role of other variables, such as personal experiences with violence, that could potentially moderate the relationship be- tween media use and aggression. As the down- ward spiral can only be studied in longitudinal designs that ideally also include more than two waves, there have been few studies that actually tested this model (Ferguson, 2011; Möller & Krahé, 2009; Slater et al., 2003; von Salisch et al., 2011; Willoughby, Adachi, & Good, 2012) and only one of these studies provided some empirical support for it (Slater et al., 2003).
Longitudinal Studies on Video Games and Aggression
As mentioned before, the number of longitu- dinal studies on video games and aggression is still relatively small. As the present study was concerned with video games, the overview in this section will focus on studies that were pub- lished in peer-reviewed journals and explicitly looked at the relationship between aggression and video games, and not violent media content in general. One of the earliest studies focusing
307VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
on video games was the short-term longitudinal field study by Williams and Skoric (2005). This study investigated the effect of one particular massively multiplayer online role-playing game (MMORPG) on aggressive cognitions and be- haviors. Later studies looked at longer periods (typically between 1 and 2 years) and video games in general or at least specific genres or types of games (mostly “violent” games; with varying definitions of what “violent” means). In our review of the literature, we found 11 journal publications that present longitudinal data from studies dealing specifically with the relationship of aggression and video games. Table 1 sums up their methods (sample, design, and measures) and main findings. Overall, there are vast dif- ferences between these studies with regard to both the direction (socialization vs. selection) and the size of the effects they found. A big part of the inconsistencies in the results can be at- tributed to major methodological discrepancies between the individual studies. The longitudinal studies differ from one another in various re- spects, including size, origin, and composition of the sample; measures of aggression and ex- posure to violent video games; control vari- ables; and number of and time lag between waves (Table 1). While the differences in some crucial categories, such as the measures for ag- gression and exposure to violent content, are quite substantial, other features are much more homogeneous across studies. Although sample sizes vary between N � 143 (Ferguson, Garza, et al., 2013; Möller & Krahé, 2009) and N � 1,492 (Willoughby et al., 2012), almost all of them are convenience samples and the large majority include only children and/or adoles- cents (Table 1).
Summing up the comparisons in Table 1, it can be noted that both the methods and results of longitudinal studies on the link between ag- gression and video game use are very heteroge- neous. This heterogeneity of findings and mea- sures is somewhat contrasted by a relative homogeneity in the age and recruitment of the samples.
Aggression, Violent Video Games, and Age
Our review of previous longitudinal studies on video games and aggression revealed that the majority of them worked with convenience samples of children and teenagers, with the ex-
ception of the study by Williams and Skoric (2005) that used a self-selected online sample that also included adult players. Accordingly, the age range of the samples typically only spans a few years (M � 4.8 years for the nine studies in Table 1 that report the age range of their sample). Due to the limited age range of most studies, few of them have investigated the role of participant age in detail. While control- ling for participant sex is done in most studies, only a few control for age (Wallenius & Pu- namäki, 2008; Williams & Skoric, 2005) or specifically look at potential differences in the size and direction of effects between age groups (Anderson et al., 2008; Ferguson, Garza, et al., 2013; Willoughby et al., 2012).3 Most of the studies that did compare between age groups also found differences in terms of effect size. In the study by Willoughby et al. (2012), there were only small socialization effects from grades 9 to 10 (� � .06) and 11 to 12 (� � .08), but not from grades 10 to 11, when controlling for all of the measured third variables. Ander- son et al. (2008) found stronger socialization effects for the younger samples (� � .15) than for the older sample (� � .08). However, the study by Ferguson, Garza, et al. (2013) that found no effect of exposure to video game vi- olence on aggression, bullying, and delinquency also found no differences between the groups of late childhood (ages 10 –11), preadolescence (12–13), and adolescence (14 –17). With regard to age differences, von Salisch et al. (2011) suggest that the selection effect they found in their study with third and fourth graders may be replaced by socialization effects once media preferences have become more stable at an older age.
In a review of the literature on violent video games and aggression, Kirsh (2003) laments the absence of a developmental perspective. For the case of video game violence and aggression, this is especially problematic, as research has shown that video game preferences differ be- tween age groups and also change over time (Greenberg, Sherry, Lachlan, Luca, & Holm- strom, 2010). Genres that typically include
3 While Willoughby et al. (2012) compared the effect sizes across three waves for the same sample, Anderson et al. (2010) calculated a combined model that distinguished between younger and older participants with the data from the two Japanese studies and the one American study.
308 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
T ab
le 1
O ve
rv ie
w o f
L o n g it
u d in
a l
S tu
d ie
s o n
V id
eo G
a m
es a n d
A g g re
ss io
n
S tu
dy C
ou nt
ry S
am pl
e S
am pl
e ty
pe
M ea
su re
of vi
de o
ga m
e vi
ol en
ce M
ea su
re (s
) of
ag gr
es si
on C
on tr
ol va
ri ab
le s
W av
es
T im
e la
g be
tw ee
n w
av es
S oc
ia li
za ti
on ef
fe ct
S el
ec ti
on ef
fe ct
W il
li am
s &
S ko
ri c
(2 00
5)
U S
A N
� 21
3; A
ge 14
–6 8
(M �
27 .7
)
S el
f- se
le ct
ed S
el f-
re po
rt ed
ho ur
s of
pl ay
fo r
M M
O R
P G
A sh
er o n ’s
C a ll
2
N or
m at
iv e
B el
ie fs
in A
gg re
ss io
n ge
ne ra
l sc
al e
(H ue
sm an
n &
G ue
rr a,
19 97
); tw
o be
ha vi
or al
qu es
ti on
s on
ag gr
es si
ve so
ci al
in te
ra ct
io ns
S ex
, ag
e 2
1 m
on th
N or
m at
iv e
be li
ef s
ab ou
t ag
gr es
si on
: B
� .2
5, n .s
.; A
rg um
en ts
w it
h fr
ie nd
s: B
� �
1. 63
, n .s
.; A
rg um
en ts
w it
h pa
rt ne
r: B
� �
.0 4,
n .s
.
N ot
te st
ed (fi
el d
st ud
y)
W al
le ni
us &
P un
am äk
i (2
00 8)
F in
la nd
N �
31 6;
A ge
(T 2)
12 –1
5 (M
� 13
.8 )
C on
ve ni
en ce
S el
f- re
po rt
ed ra
ti ng
s of
vi ol
en ce
in ga
m es
pl ay
ed an
d fr
eq ue
nc y
of pl
ay in
g ac
ti on
, fi
gh ti
ng ,
an d
sh oo
ti ng
ga m
es
T en
it em
s fr
om th
e D
ir ec
t &
In di
re ct
A gg
re ss
io n
S ca
le (B
jö rk
qv is
t, L
ag er
sp et
z, &
Ö st
er m
an ,
19 98
)
S ex
, ag
e- gr
ou p,
pa re
nt –c
hi ld
co m
m un
ic at
io n
2 2
ye ar
s �
� .0
1, n .s
. N
ot te
st ed
(t a b le
co n ti
n u es
)
309VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
T ab
le 1
(c o n ti
n u ed
)
S tu
dy C
ou nt
ry S
am pl
e S
am pl
e ty
pe
M ea
su re
of vi
de o
ga m
e vi
ol en
ce M
ea su
re (s
) of
ag gr
es si
on C
on tr
ol va
ri ab
le s
W av
es
T im
e la
g be
tw ee
n w
av es
S oc
ia li
za ti
on ef
fe ct
S el
ec ti
on ef
fe ct
S hi
bu ya
et al
. (2
00 8)
Ja pa
n N
� 59
1; A
ge (T
1) 10
–1 1
(m ea
n ag
e no
t re
po rt
ed )
U nc
le ar
(m os
t li
ke ly
co nv
en ie
nc e)
D ic
ho to
m ou
s va
ri ab
le (v
io le
nt ye
s/ no
) fo
r th
re e
fa vo
ri te
vi de
o ga
m es
an d
21 co nt
ex tu
al va
ri ab
le s
ab ou
t th
e ty
pe of
vi ol
en t
co nt
en t
in ea
ch ga
m e
A gg
re ss
io n
S ca
le fo
r C
hi ld
re n
(B us
s &
P er
ry ,
19 92
; S
ak ai
et al
., 20
00 );
an ti
- vi
ol en
ce no
rm s;
re ce
nt ag
gr es
si ve
be ha
vi or
S ex
, ar
ea of
li vi
ng ,
w ee
kl y
vi de
o ga
m e
us e
2 1
ye ar
H os
ti li
ty :
� �
.1 3,
p �
.0 5
fo r
bo ys
an d
n .s
. fo
r gi
rl s;
P hy
si ca
l an
d ve
rb al
ag gr
es si
on ,
an ti
vi ol
en ce
no rm
s, an
d ag
gr es
si ve
be ha
vi or
: al
l n .s
. fo
r bo
th gi
rl s
an d
bo ys
(e ff
ec t
si ze
s no
t re
po rt
ed )
N ot
te st
ed
H op
f et
al .
(2 00
8) G
er m
an y
N �
31 4;
M ea
n ag
e (T
1) �
12
C on
ve ni
en ce
F re
qu en
cy of
pl ay
in g
vi ol
en t
ga m
es fr
om a
li st
of 19
po pu
la r
ti tl
es
It em
s on
vi ol
en ce
be li
ef s,
de li
nq ue
nc y,
ve rb
al ag
gr es
si on
, ph
ys ic
al ag
gr es
si on
, an
d de
vi an
ce in
sc ho
ol (T
il lm
an n,
H ol
le r-
N ov
it zk
i, H
ol ta
pp el
s, M
ei er
, &
P op
p, 19
99 )
S ch
oo l
an d
cl as
sr oo
m cl
im at
e, w
el l-
be in
g in
sc ho
ol ,
se lf
- re
gu la
ti on
, se
lf -
ef fi
ca cy
in sc
ho ol
, em
ot io
na l
re ac
ti on
s to
vi ol
en ce
, m
at er
ia li
st ic
va lu
e or
ie nt
at io
ns ,
m ed
ia ed
uc at
io n
by pa
re nt
s, po
ve rt
y, ag
gr es
si ve
ne ss
, pe
ac ea
bl en
es s
2 2
ye ar
s A
gg re
ss iv
e be
ha vi
or in
sc ho
ol :
� �
.1 8
(s ig
ni fi
ca nc
e le
ve l
no t
re po
rt ed
); D
el in
qu en
cy :
� �
.2 9
(s ig
ni fi
ca nc
e le
ve l
no t
re po
rt ed
)
N ot
te st
ed
310 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
T ab
le 1
(c o n ti
n u ed
)
S tu
dy C
ou nt
ry S
am pl
e S
am pl
e ty
pe
M ea
su re
of vi
de o
ga m
e vi
ol en
ce M
ea su
re (s
) of
ag gr
es si
on C
on tr
ol va
ri ab
le s
W av
es
T im
e la
g be
tw ee
n w
av es
S oc
ia li
za ti
on ef
fe ct
S el
ec ti
on ef
fe ct
A nd
er so
n et
al .
(2 00
8) U
S A
N �
36 4;
A ge
9– 12
(m ea
n ag
e no
t re
po rt
ed )
U nc
le ar
(m os
t li
ke ly
co nv
en ie
nc e)
S el
f- re
po rt
ed am
ou nt
of vi
ol en
t co
nt en
t �
fr eq
ue nc
y of
pl ay
fo r
th re
e fa
vo ri
te vi
de o
ga m
es
In de
x of
te ac
he r,
pe er
, an
d se
lf -
re po
rt s
of ph
ys ic
al ag
gr es
si on
S ex
, ph
ys ic
al ag
gr es
si on
at ti
m e
1
2 5
to 6
m on
th s
� �
.1 6
(9 5%
- C
I: .0
8, .2
3) N
ot te
st ed
Ja pa
n N
� 18
1; A
ge 12
–1 5
(m ea
n ag
e no
t re
po rt
ed )
U nc
le ar
(m os
t li
ke ly
co nv
en ie
nc e)
F re
qu en
cy of
pl ay
in g
fi ve
vi ol
en t
vi de
o ga
m e
ge nr
es :
fi gh
ti ng
ac ti
on ,
ac ti
on ,
ac ti
on ro
le -
pl ay
in g,
sh oo
ti ng
, ad
ve nt
ur e
S ix
-i te
m ve
rs io
n of
th e
ph ys
ic al
ag gr
es si
on sc
al e
by B
us s
& P
er ry
(1 99
2)
S ex
, ph
ys ic
al ag
gr es
si on
at ti
m e
1
2 4
m on
th s
� �
.1 4
(9 5%
- C
I: .0
3, .2
5) N
ot te
st ed
(t a b le
co n ti
n u es
)
311VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
T ab
le 1
(c o n ti
n u ed
)
S tu
dy C
ou nt
ry S
am pl
e S
am pl
e ty
pe
M ea
su re
of vi
de o
ga m
e vi
ol en
ce M
ea su
re (s
) of
ag gr
es si
on C
on tr
ol va
ri ab
le s
W av
es
T im
e la
g be
tw ee
n w
av es
S oc
ia li
za ti
on ef
fe ct
S el
ec ti
on ef
fe ct
Ja pa
n N
� 1,
05 0;
A ge
13 –1
8 (m
ea n
ag e
no t
re po
rt ed
)
U nc
le ar
(m os
t li
ke ly
co nv
en ie
nc e)
V id
eo ga
m e
pl ay
in hr
s pe
r w
ee k
� vi
ol en
ce ra
ti ng
s fo
r m
os t
fa vo
ri te
ge nr
e an
d th
re e
ad di
ti on
al fa
vo ri
te ge
nr es
as si
gn ed
by th
e au
th or
s
S in
gl e
it em
se lf
- re
po rt
on fr
eq ue
nc y
of ph
ys ic
al ag
gr es
si on
in th
e la
st m
on th
S ex
, ph
ys ic
al ag
gr es
si on
at ti
m e
1
2 3
to 4
m on
th s
� �
.0 8
(9 5%
- C
I: .0
2, .1
3) N
ot te
st ed
M öl
le r
& K
ra hé
(2 00
9)
G er
m an
y N
� 14
3; M
ea n
ag e
(T 1)
� 13
.3
C on
ve ni
en ce
F re
qu en
cy of
pl ay
� ex
pe rt
vi ol
en ce
ra ti
ng s
fo r
a li
st of
po pu
la r
ga m
es
S ev
en it
em s
fr om
th e
ph ys
ic al
ag gr
es si
on su
bs ca
le by
B us
s &
P er
ry (1
99 2)
� se
ve n
it em
s on
re la
ti on
al ag
gr es
si on
ba se
d on
th e
in di
re ct
ag gr
es si
on sc
al e
by B
us s
& W
ar re
n (2
00 0)
S ex
, no
rm at
iv e
be li
ef s
ab ou
t ag
gr es
si on
, ho
st il
e at
tr ib
ut io
n bi
as
2 30
m on
th s
P hy
si ca
l ag
gr es
si on
: �
� .2
7, p
� .0
01 ;
R el
at io
na l
ag gr
es si
on :
� �
.0 8,
n .s
.
P hy
si ca
l ag
gr es
si on
: �
� �
.0 2,
n .s
.; R
el at
io na
l ag
gr es
si on
: �
� �
.0 9,
n .s
.
312 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
T ab
le 1
(c o n ti
n u ed
)
S tu
dy C
ou nt
ry S
am pl
e S
am pl
e ty
pe
M ea
su re
of vi
de o
ga m
e vi
ol en
ce M
ea su
re (s
) of
ag gr
es si
on C
on tr
ol va
ri ab
le s
W av
es
T im
e la
g be
tw ee
n w
av es
S oc
ia li
za ti
on ef
fe ct
S el
ec ti
on ef
fe ct
F er
gu so
n (2
01 1)
U S
A N
� 30
2; A
ge (T
1) 10
–1 4
(M �
12 .3
)
C on
ve ni
en ce
(s no
w ba
ll sa
m pl
in g)
E S
R B
ra ti
ng s
� fr
eq ue
nc y
of pl
ay fo
r th
re e
fa vo
ri te
vi de
o ga
m es
C hi
ld B
eh av
io r
C he
ck li
st (A
ch en
ba ch
& R
es co
rl a,
20 01
) fi
ll ed
ou t
by th
e pa
rt ic
ip an
ts an
d th
ei r
pr im
ar y
ca re
gi ve
rs ;
O lw
eu s
B ul
ly in
g Q
ue st
io nn
ai re
(O lw
eu s,
19 96
); ge
ne ra
l de
li nq
ue nc
y su
bs ca
le of
th e
N eg
at iv
e L
if e
E ve
nt s
qu es
ti on
na ir
e (P
at er
no st
er &
M az
er ol
le ,
19 94
)
S ex
, an
ti so
ci al
pe rs
on al
it y,
ne ig
hb or
ho od
pr ob
le m
s, ne
ga ti
ve re
la ti
on s
w it
h ad
ul ts
, fa
m il
y at
ta ch
m en
t, de
li nq
ue nt
pe er
s, fa
m il
y en
vi ro
nm en
t, fa
m il
y vi
ol en
ce ,
de pr
es si
ve sy
m pt
om s
2 1
ye ar
S el
f- re
po rt
ed se
ri ou
s ag
gr es
si on
: �
� .�
03 ,
n .s
.; O
th er
-r ep
or te
d se
ri ou
s ag
gr es
si on
: �
� �
.0 1,
n .s
.; V
io le
nt cr
im e:
� �
.0 7,
n .s
.; B
ul ly
in g:
� �
.1 2,
n .s
.;
n .s
. (e
ff ec
t si
ze fo
r ag
gr es
si ve
be ha
vi or
no t
re po
rt ed
)
vo n
S al
is ch
et al
. (2
01 1)
G er
m an
y N
� 32
4; A
ge (T
1) 8–
12 (M
� 8.
9)
C on
ve ni
en ce
A ve
ra ge
of ex
pe rt
vi ol
en ce
ra ti
ng s
fo r
up to
si x
fa vo
ri te
co m
pu te
r or
vi de
o ga
m es
P ee
r an
d te
ac he
r no
m in
at io
ns fo
r ve
rb al
ly an
d ph
ys ic
al ly
ag gr
es si
ve be
ha vi
or
S ex
, ne
ig hb
or ho
od of
re si
de nc
e, pa
re nt
s’ m
ig ra
ti on
st at
us ,
pr es
en ce
of an
ol de
r br
ot he
r, sc
ho ol
ac hi
ev em
en t,
se lf
- pe
rc ei
ve d
co m
pe te
nc e
2 1
ye ar
� �
� .0
1, n .s
. �
� .2
6, p
� .0
1
(t a b le
co n ti
n u es
)
313VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
T ab
le 1
(c o n ti
n u ed
)
S tu
dy C
ou nt
ry S
am pl
e S
am pl
e ty
pe
M ea
su re
of vi
de o
ga m
e vi
ol en
ce M
ea su
re (s
) of
ag gr
es si
on C
on tr
ol va
ri ab
le s
W av
es
T im
e la
g be
tw ee
n w
av es
S oc
ia li
za ti
on ef
fe ct
S el
ec ti
on ef
fe ct
W il
lo ug
hb y
et al
. (2
01 2)
C an
ad a
N �
1, 49
2; A
ge no
t re
po rt
ed (T
1: C
an ad
ia n
ni nt
h- gr
ad er
s)
C om
pl et
e sa
m pl
e of
al l
hi gh
sc ho
ol s
in on
e sc
ho ol
di st
ri ct
in O
nt ar
io ,
C an
ad a
D ic
ho to
m ou
s va
ri ab
le s
(y es
/n o)
fo r
ac ti
on an
d fi
gh ti
ng vi
de o
ga m
es (s
us ta
in ed
pl ay
: su
m s
fo r
al l
w av
es )
& fr
eq ue
nc y
of pl
ay in
g ac
ti on
an d
fi gh
ti ng
ga m
es fo
r gr
ad es
11 an
d 12
O ve
rt ag
gr es
si on
as se
ss ed
by a
co m
po si
te of
tw o
sc al
es (L
it tl
e, Jo
ne s,
H en
ri ch
, &
H aw
le y,
20 03
; M
ar in
i, S
pe ar
, &
B om
ba y,
19 99
)
S ex
, no
nv io
le nt
vi de
o ga
m e
pl ay
, ac
ad em
ic m
ar ks
, de
pr es
si ve
sy m
pt om
s, de
la y
of gr
at ifi
ca ti
on ,
pe er
de vi
an ce
, sp
or ts
in vo
lv em
en t,
fr ie
nd sh
ip qu
al it
y, pa
re nt
–a do
le sc
en t
re la
ti on
sh ip
qu al
it y,
pa re
nt al
co nt
ro l,
sc ho
ol cu
lt ur
e
4 1
ye ar
G ra
de s
9– 10
: �
� .0
6, p
� .0
5; G
ra de
s 11
–1 2:
� �
.0 8,
p �
.0 1
� s
no t
re po
rt ed
, bu
t al
l n .s
.
F er
gu so
n et
al .
(2 01
2) U
S A
N �
16 5;
A ge
(T 1)
10 –1
4 (M
� 12
.3 )
C on
ve ni
en ce
E S
R B
ra ti
ng s
� fr
eq ue
nc y
of pl
ay fo
r th
re e
fa vo
ri te
vi de
o ga
m es
C hi
ld B
eh av
io r
C he
ck li
st (A
ch en
ba ch
& R
es co
rl a,
20 01
) fi
ll ed
ou t
by th
e pa
rt ic
ip an
ts an
d th
ei r
pr im
ar y
ca re
gi ve
rs
S ex
, an
ti so
ci al
pe rs
on al
it y
tr ai
ts ,
fa m
il y
at ta
ch m
en t,
de li
nq ue
nt pe
er s,
fa m
il y
vi ol
en ce
, de
pr es
si on
3 1
ye ar
an d
2 ye
ar s
S el
f- re
po rt
ed se
ri ou
s ag
gr es
si on
: �
� .0
3, n.
s. ;
O th
er -r
ep or
te d
se ri
ou s
ag gr
es si
on :
� �
� .0
3, n.
s. ;
D at
in g
vi ol
en ce
: �
� �
.0 5,
n. s.
;
N ot
te st
ed
314 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
T ab
le 1
(c o n ti
n u ed
)
S tu
dy C
ou nt
ry S
am pl
e S
am pl
e ty
pe
M ea
su re
of vi
de o
ga m
e vi
ol en
ce M
ea su
re (s
) of
ag gr
es si
on C
on tr
ol va
ri ab
le s
W av
es
T im
e la
g be
tw ee
n w
av es
S oc
ia li
za ti
on ef
fe ct
S el
ec ti
on ef
fe ct
F er
gu so
n, G
ar za
, et
al .
(2 01
3)
U S
A N
� 14
3; A
ge (T
1) 10
–1 7
(M �
12 .8
)
C on
ve ni
en ce
E S
R B
ra ti
ng s
� fr
eq ue
nc y
of pl
ay fo
r th
re e
fa vo
ri te
vi de
o ga
m es
C hi
ld B
eh av
io r
C he
ck li
st (A
ch en
ba ch
& R
es co
rl a,
20 01
) fi
ll ed
ou t
by th
e pa
rt ic
ip an
ts ’
pr im
ar y
ca re
gi ve
rs ;
O lw
eu s
B ul
ly in
g Q
ue st
io nn
ai re
(O lw
eu s,
19 96
); ge
ne ra
l de
li nq
ue nc
y su
bs ca
le of
th e
N eg
at iv
e L
if e
E ve
nt s
qu es
ti on
na ir
e (P
at er
no st
er &
M az
er ol
le ,
19 94
)
S ex
, de
pr es
si ve
sy m
pt om
s, an
ti so
ci al
pe rs
on al
it y,
fa m
il y
at ta
ch m
en t,
de li
nq ue
nt pe
er s,
pa re
nt al
su pe
rv is
io n,
pa re
nt al
de pr
es si
on
2 1
ye ar
A gg
re ss
io n:
� �
� .0
2, n .s
.; D
el in
qu en
cy :
� �
.0 2,
n .s
.; B
ul ly
in g:
� �
.0 5,
n .s
.
N ot
te st
ed
N o te
. E
S R
B �
E nt
er ta
in m
en t
S of
tw ar
e R
at in
g B
oa rd
.
315VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
large amounts of violence, such as action and first-person shooter games, are particularly pop- ular among younger players (Quandt, Breuer, Festl, & Scharkow, 2013). At the same time, the age of a player also affects her or his access to video games. Most games that feature very ex- plicit and graphical depictions of violence are rated 18� and should, hence, not be legally available to minors. Teenage players usually also have a very limited amount of personal income that they can spend on video games, and parents are more likely to monitor the media use of their children when they are younger (Wal- lenius & Punamäki, 2008). But, age not only determines the accessibility and use of violent video games, it is also related to (physical) aggression. Developmental researchers found a curvilinear relationship between aggression and age, with peaks in early adolescence (Linde- man, Harakka, & Keltikangas-Järvinen, 1997; Loeber & Stouthamer-Loeber, 1998). Wil- loughby et al. (2012) also suggest that “the long-term relation between violent video game play and aggression may be different for ado- lescents (e.g., 12 to 19 years) and adults (e.g., 25 years and older), due to changes in the brain during adolescence and young adulthood” (p. 12). Following this suggestion, the present study was carried out to investigate whether the size and maybe even the direction of effects differ for adolescents and young adults. Adoles- cents and young adults are an interesting target demographic for this line of research because they have been shown to be the heavy users of video games (Greenberg et al., 2010). A recent survey among adolescents aged 12 to 19 in Germany showed that 81% play video games and that 34% regularly play games with violent content (Medienpädagogischer Forschungsver- bund Südwest, 2012).
Method
Participants and Procedure
Our review of the existing literature showed that most studies rely on convenience samples (Table 1), typically drawn from local schools. Only the study by Willoughby et al. (2012) can be seen as potentially representative, at least for high school students in the province of Ontario, Canada. To arrive at more generalizable results, our study used data from a representative panel
study of German gamers aged 14 and older. Recruiting for this study was a two-step proce- dure. First, a representative sample of 50,012 persons aged 14 and older were asked about their use of video games in an omnibus tele- phone survey. This sample was recruited in accordance with the German Arbeitskreis Deutscher Markt- und Sozialforschungsinstitute (ADM) telephone sampling system (von der Heyde, 2013): First, private households with phones (mostly landline plus a small amount of mobile phone numbers) were selected ran- domly. Second, within the household, the indi- vidual whose last birthday was closest to the date of the call was selected for the telephone interview. Approximately 25% (N � 12,587) of the participants were identified as gamers (i.e., individuals who currently play video games at least occasionally). From this group, we re- cruited a stratified random sample of 4,500 gamers for the first wave of the main study. This sample was composed of 3,500 respondents who play digital games with others (colocated, online, or via local networks) and 1,000 gamers who only play solo. Due to this stratified sam- pling, the proportion of gamers who play with others was higher in the main study (77.8%) than in the omnibus survey (68.4%).
The computer-assisted telephone interviews were conducted by a professional German mar- ket research institute. At the end of the inter- view, respondents were asked, if they were will- ing to participate in the second wave of the study 1 year later. Because of financial con- straints and in anticipation of panel mortality, we recruited a random subset of about 50% of the respondents from wave 1 of the main study for the second wave. Thus, of the 4,500 gamers from wave 1, N � 2,199 were interviewed in wave 2. As we were only interested in the longitudinal relationship of violent video games and aggression among adolescents and young adults, we focused our analysis on those respon- dents who participated in both waves and were aged 14 to 21 when they were first interviewed. This subsample included n � 332 individuals. There was no difference in average age between respondents who took part in both waves and those who were interviewed only in the first wave (M2 � 17.5 years compared with M1 � 17.7, t(883) � 1.15, p � .25). The second wave sample contained slightly more females than the first wave sample (29% compared with 26%,
316 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
�2(1) � 0.74, p � .39). After listwise deletion, the final sample (see Data Analysis section) comprised n � 276 respondents (i.e., 83% of the subsample).4 Little’s (1988) likelihood ratio test showed (�2(18) � 23.32, p � .18) that the missing data of the variables of interest (phys- ical aggression and use of violent video games) are missing completely at random. Respondents of the final sample that was used for our anal- yses had an average age of 17.6 (SD � 1.9) and 19.2% (n � 53) of them were female.
Measures
Demographic factors. Participant sex, age, and education were all measured with single items. The education item asked respondents about their highest educational degree. The an- swering option reflected the German educa- tional system and ranged from 0 (no school leaving certificate) to 5 (university degree).
Physical aggression. We decided to focus on physical aggression, as this is the type of aggression most commonly featured in violent video games (Lachlan, Smith, & Tamborini, 2005; Smith, Lachlan, & Tamborini, 2003) and both socialization and selection effects are more likely to occur, if the behavior presented in the game and the one exhibited in real life are similar (Möller & Krahé, 2009). We used two items from the German translation (Herzberg, 2003) of the physical aggression subscale from the Aggression Questionnaire by Buss and Perry (1992). The two items were “There are people who pushed me so far that we came to blows” (phys aggr 1) and “Given enough prov- ocation, I may hit another person” (phys aggr 2). Participants indicated on a 5-point scale to what degree these statements apply to them (ranging from 1 � does not apply at all to 5 � fully applies). Cronbach’s alphas for physical aggression were satisfactory and stable across both waves for the subsample under investiga- tion (t1: � .75; t2: � .74).
Use of violent video games. Participants were asked to name their favorite game plus up to five additional games that they currently play. All games were then coded for the age rating assigned by the German age rating system Un- terhaltungssoftware Selbstkontrolle (USK) us- ing their online database (see www.usk.de/en). The coding scheme used the USK age rating system (0�, 6�, 12�, 16�, 18�) with the
additional category of “no clearance.” No clear- ance means that the game did not receive an official age rating from the USK because it is deemed harmful to minors. In such cases, the games are examined by the Federal Review Board for Media Harmful to Minors (BPjM: Bundesprüfstelle für jugendgefährdende Me- dien; see http://www.bundespruefstelle.de/bpjm/ information-in-english.html). If the BPjM ar- rives at the decision that a video game is potentially harmful to minors, the game is not allowed to be advertised in Germany and can only be sold “under the counter” in stores to which minors have access. Eventually, this means that the game is less publicly visible and much harder to (legally) acquire, but it might also increase its appeal as a “forbidden fruit” (Bijvank, Konijn, Bushman, & Roelofsma, 2009).
For each wave, we computed a mean age rating score for every participant who named at least one game. We used the USK rating as an indicator for violent content, as this character- istic is one of the main reasons for the assign- ment of age ratings in Germany (Hyman, 2005; MacMillan & Wedell, 2013). If games are not given an age rating, this is mostly due to ex- treme and explicit depictions of violence (see http://www.usk.de/fileadmin/documents/USK_ Broschuere_ENG.pdf). Previous content analy- ses have also shown that games with higher age ratings tend to include more frequent and more graphic portrayals of violence (Haninger & Thompson, 2004; Thompson, Tepichin, & Haninger, 2006). Age ratings have already been used as a proxy for violent content in several previous studies (Ferguson, 2011; Ferguson et al., 2012; Olson et al., 2009) and they were clearly correlated with ratings of violent content in the studies by Busching et al. (2013); Möller and Krahé (2009), and Ferguson (2011). While Busching et al. (2013) suggest that age ratings are valid and reliable measures of violent con- tent, they caution researchers that “they should
4 The relatively high number of excluded respondents is mostly due to missing values in the age ratings for the games they played (details see Measures section). In several cases, the games could not be clearly identified because of unintelligible answers by the respondents or typos by the interviewers or because there were no age ratings available for the game in the USK database (e.g., for games played over social networking sites).
317VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
only be used in the country in which they were developed” (p. 13) because of potential inter- cultural differences in the reasons for assigning age labels.
Overall video game use. Overall use of video games was measured in self-reported hours per day.
Data Analysis
For our main analysis, we performed param- eter estimation using the mean- and variance- adjusted maximum likelihood (MLMV) proce- dure in Mplus (Version 6.0; Muthén & Muthén, 1998 –2010). MLMV provides chi-square val- ues and estimates with standard errors that are robust to non-normality. Model fit is assessed using the probability of the mean- and variance- adjusted chi-square value (p � .05), root-mean square error of approximation (RMSEA � .06), the comparative fit index (CFI � .9), and weighted root mean square residual (WRMR � .9). Model comparison and selection was per- formed using MLMV difference testing (Asp- arouhov & Muthén, 2006). For the comparison of age groups, we distinguished between ado- lescents (aged 14 –17 at t1) and young adults (18 –21 at t1). The age of 18 was chosen as a cutoff because this is the age at which you can legally buy video games that are labeled 18�, which is the highest age rating assigned by the German USK (see previous section on Mea- sures). We opted for a group comparison in- stead of using age as a continuous control vari- able because we were interested more in the differences between the two populations of ad- olescents and young adults and less in the in- fluence of age on physical aggression and the use of (violent) video games.
Results
Preliminary Analyses
Table 2 shows the intercorrelations of the variables included in the structural equation model as well as their means, standard devia- tions, skewness, and kurtosis.
As the descriptive statistics for the two age groups differed, we examined mean differences in the measures of video game use and physical aggression. Although the mean differences were in the expected directions, with older respon-
dents (18 –21) playing more violent games (M � 2.85), while reporting fewer hours of overall video game play (M � 1.17) and lower levels of mean physical aggression (M � 1.77) than the respondents aged 14 to 17 (Ms � 2.65; 1.24; 1.97), separate t-tests revealed no signifi- cant differences between the groups at Time 1 (all p .1, r � .1).5 Although the differences between the groups were not significant, they mirror the descriptive data from the Jugend, Information, (Multi-) Media (JIM) study of ad- olescents and media use in Germany that found a decrease of overall gaming frequency, but an increase in the use of violent games with age (Medienpädagogischer Forschungsverbund Südwest, 2012). Looking at the cross-sectional association between the use of violent games and physical aggression, we found a significant correlation only for the younger group (r � .34, p � .001).6
Long-Term Relationships Between Use of Violent Video Games and Physical Aggression
Longitudinal research rests on the assump- tion that the meaning of the constructs involved does not change over time. To test this, the factor loadings of the measurement model were constrained to be time-invariant over the two waves. The overall model fit indicates that the validity of the physical aggression measurement model does not change over time (�2(6, N � 276) � 12.39, p � .05, CFI � .98, RMSEA � .06, WRMR � .62). In the next step, we further tested the assumption that the physical aggres- sion measurement model is group-invariant (i.e., the validity of physical aggression mea- surement model is the same for individuals aged 14 –17 years and 18 –21 years). The overall model fit indicates that this assumption is valid
5 We refrained from comparisons between female and male respondents due to their uneven distribution in our sample. Most of the previous studies, however, have found males to report higher levels of both aggression and use of violent video games (e.g., Anderson et al., 2008; Ferguson, Garza, et al., 2013; Möller & Krahé, 2009; Shibuya et al., 2008; von Salisch et al., 2011; Wallenius & Punamäki, 2008; Willoughby et al., 2012).
6 After controlling for measurement error in the cross- lagged structural equation model, the cross-sectional path turned out to be even stronger with r � .4 (see next section and Figure 1).
318 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
(�2(15, N14 –17 � 140, N18 –21 � 136) � 17.92, p � .27, CFI � .99, RMSEA � .04, WRMR � .48). In sum, the aforementioned tests show that physical aggression has been measured time- and group-invariant.
Figure 1 shows the results of the cross-lagged structural equation model. The upper values of the arrows in Figure 1 represent the parameter estimates for the younger age-group (14 –17), while the lower values show the parameter es- timates for the older age-group (18 –21). On the left side, the two-sided arrow shows the cross- sectional correlation between physical aggres- sion and use of violent games. The horizontal one-sided arrows between the same variables represent the stability estimates (autoregres- sion). The standardized autoregression coeffi- cient is a number between �1 and � 1. A high positive value indicates that interindividual dif- ferences over time do not change, which is
commonly referred to as covariance stability. The one-sided arrows between different vari- ables represent the cross-lagged effects. The two-sided arrow on the right side of Figure 1 shows the cross-sectional residual correlation of the dependent variables after controlling for au- toregressive and cross-lagged effects.
Parameter estimation suggests that physical aggression self-reports were highly stable over time. A �2-difference test indicated that the autoregressive effects of physical aggression are not statistically different between the two groups (��2(1, N14 –17 � 140, N18 –21 � 136) � 1.01, p � .32, one-tailed). It can therefore be concluded that physical aggression is highly time-invariant in both groups. By contrast, the two age groups differ with respect to the autore- gression of violent game use (��2(1, N14 –17 � 140, N18 –21 � 136) � 8.96, p � .01, one- tailed). The use of violent video games is far
Table 2 Intercorrelations Between Items for Participants Aged 14 to 17 Years and 18 to 21 Years
Item 1 2 3 4 5 6 7 8 9
Adolescents aged 14–17 years (n � 140)
1. Phys aggr 1 t1 — .56 .58 .52 .31 .29 �.22 �.15 .01 2. Phys aggr 2 t1 — .49 .55 .29 .37 �.25 �.09 .07 3. Phys aggr 1 t2 — .62 .13 .27 �.19 �.16 �.02 4. Phys aggr 2 t2 — .25 .28 �.27 �.23 �.08 5. Violent game use t1 — .46 �.33 �.01 .28 6. Violent game use t2 — �.34 �.06 .24 7. Participant sex t1
a — .03 �.17 8. Education t1 — �.13 9. Gaming frequency t1 — Mean 1.86 2.08 1.58 1.41 2.65 2.63 .22 2.85 1.24 SD 1.24 1.25 .98 .70 1.26 1.26 .42 1.12 1.29 Skewness 1.33 1.16 1.86 1.91 .22 .27 1.36 �.12 2.16 Kurtosis .62 .39 3.02 4.52 �1.14 �.98 �.16 �1.62 6.30
Young adults aged 18–21 years (n � 136)
1. Phys aggr 1 t1 — .64 .59 .54 .03 �.04 �.15 �.04 .08 2. Phys aggr 2 t1 — .64 .53 .02 �.01 �.21 �.08 .08 3. Phys aggr 1 t2 — .65 .08 .07 �.21 �.05 .09 4. Phys aggr 2 t2 — .10 .06 �.21 .01 .24 5. Violent game use t1 — .65 �.21 �.06 .17 6. Violent game use t2 — �.21 �.05 .25 7. Participant sex t1
a — .06 �.19 8. Education t1 — .05 9. Gaming frequency t1 — Mean 1.68 1.85 1.56 1.41 2.85 2.63 .16 3.41 1.17 SD 1.10 1.13 .97 .75 1.19 1.22 .37 .95 1.11 Skewness 1.77 1.36 1.97 2.19 �.04 .16 1.86 �1.15 1.25 Kurtosis 2.42 .99 3.53 5.30 �.91 �.97 1.47 �.08 .84
Note. a 0 � male, 1 � female.
319VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
more stable among respondents aged 18 to 21. The cross-sectional positive correlation be- tween physical aggression and violent video game use is statistically significant (r � .40, p � .01, one-tailed) for the younger group. However, this contemporary correlation only indicates covariation. To test the temporal or- der, cross-lagged parameters were estimated. Comparing all cross-lagged effects showed that only one parameter estimate between physical aggression self-reports at Time 1 and the use of violent games at Time 2 was statistically signif- icant. Participants aged 14 to 17 who are more physically aggressive at Time 1 nominated more violent games at Time 2 (� � .30, p � .01). By contrast, this relationship was not found for young adults (aged 18 –21). A �2- difference test proved that the effect size differ- ence between the two groups was statistically significant (��2(1, N14 –17 � 140, N18 –21 � 136) � 8.04, p � .01, one-tailed). Accordingly, our data suggest that physical aggression pre- dicts the use of violent video game among ad- olescents, while the reverse does not seem to be true.
The cross-lagged structural equation model depicted in Figure 1 is only testing the bivariate relationship between physical aggression and violent video game use. It is important, though, to control for spurious effects of third variables
on the bivariate relationship of interest (Slater, 2007). Following the procedure by von Salisch et al. (2011), we estimated three additional models. In each model, a third variable was introduced in the structural equations (Figure 2). The candidate set of third variables consisted of participant sex, level of education, and gam- ing frequency measured at Time 1.
As can be seen in Table 3, all three additional two-group models fitted the data excellent. All �2 tests were nonsignificant. When controlling for sex, level of education, and gaming fre- quency separately, physical aggression at Time 1 was still a significant predictor of violent video game use at Time 2 in the younger age- group. The selection effect varied between � � .26 (p � .01) and � � .34 (p � .01). The size of the cross-lagged socialization effects was again not statistically significant in any of the additional models. In sum, the longitudinal re- lations between physical aggression and violent video game use were not influenced by sex, education, or gaming frequency.
Discussion
The results of our study provide some ev- idence for a selection effect in the adolescent group aged 14 to 17. Essentially, this corrob- orates the findings from von Salisch et al.
Physical Aggression
Physical Aggression
.97 **
.88 **
.40 ** ns
.30 ** ns
ns ns
R² = .84 R² = .79
Use of Violent Games
Use of Violent Games
R² = .28 R² = .43
ns ns
.34 **
.65 **
2 emiT1 emiT
Figure 1. Cross-lagged structural equation model: Relationships between physical aggres- sion and use of violent games. Note. Upper row: standardized coefficients of adolescents aged 14 to 17 years, lower row: standardized coefficients of young adults aged 18 to 21 years. N � 276, MLMV estimation, �2(15, N14-17 � 140, N18-21 � 136) � 17.92, p � .27, CFI � .99, RMSEA � .04, WRMR � .48, � p � .05, �� p � .01.
320 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
(2011), who found a selection effect in their sample of children aged 8 to 12, for an older sample. For the group of young adults aged 18 to 21, however, we found no indication of either a socialization or a selection effect. These findings pertain, even when controlling for participant sex, education, and overall fre- quency of video game play. This is in line with several previous longitudinal studies (Ferguson, Garza, et al., 2013; Ferguson et al., 2012; von Salisch et al., 2011; Wallenius & Punamäki, 2008; Williams & Skoric, 2005), while it also contradicts others (An- derson et al., 2008; Möller & Krahé, 2009).
With regard to the theories that explain the relationship between violent video games and aggression, our results fit best with the Cata- lyst Model (Ferguson et al., 2008) that does
not predict a substantial influence of violent media on real-life aggression. The idea of violent media as a stylistic catalyst for indi- viduals with a tendency for aggression is compatible with the selection effect we found for adolescents aged 14 to 17. The absence of socialization effects in the present study con- tradicts the assumptions of the GAM (Ander- son & Bushman, 2002), according to which a repeated use of violent media leads to an increase in aggressive behavioral tendencies. While von Salisch et al. (2011) speculated that the selection effect they found for their sample of third and fourth graders might be the beginning of a downward spiral (Slater et al., 2003), our study found no such relation- ship for adolescents and young adults. As the sample in our study was limited to adoles-
Physical Aggression
Physical Aggression
Use of Violent Games
Use of Violent Games
2 emiT1 emiT
Third variable
Figure 2. Cross-lagged structural equation model with third variable control.
Table 3 Influence of Third Variables on the Cross-Lagged Effects
Third variable
Selection effect with third
variable control
Socialization effect with third variable control Model fit
14–17 18–21 14–17 18–21 �(df) p� � � �
Participant sex (n � 276) .26�� NS NS NS 20.69 .35 Education (n � 247) .34�� NS NS NS 18.54 .49 Gaming frequency (n � 273) .31�� NS NS NS 23.38 .22
Note. MLMV estimation. � p � .05. �� p � .01.
321VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
cents and young adults, however, it might be possible that socialization effects occur at a younger age when media preferences and es- pecially personality traits are more malleable.
As both physical aggression (Lindeman et al., 1997; Loeber & Stouthamer-Loeber, 1998) and the use of (violent) video games (Greenberg et al., 2010) change with age, it is not surprising that the same should be true for the relationship between these two variables. Both the peak in aggression and the height- ened interest in violent video games have been suggested to be part of normal (i.e., healthy) developmental phases, especially among boys (Ferguson, 2010; Lenhart et al., 2008; Olson, 2010). Accordingly, the selec- tion effect we found for adolescents could be interpreted as a sign of selective exposure to violent content in a phase of life that goes along with a general peak in aggressive be- havioral tendencies. It may well be that phys- ical aggression, the use of violent games, and the selective exposure effect for adolescents can be explained by another underlying fac- tor, such as sensation-seeking. Similar to the developmental change in aggression, a study by Steinberg et al. (2008) found a curvilinear relationship between age and sensation- seeking, with peaks between age 10 and 15. Previous studies have also linked sensation- seeking with both a preference for violent media (Slater, 2003) and aggression (Joire- man, Anderson, & Strathman, 2003).
As stated before, some of the differences in the findings can be attributed to differences in the methods used. Unlike other studies that mostly relied on convenience samples, we used data from a representative sample of German gamers aged 14 and older. We also compared the effects for adolescents (aged 14 –17) and young adults (18 –21) to take into account both developmental change and the access to video games. The differences we found between the age groups suggest that age is an important variable that needs to be considered when investigating the relation- ship between aggression and video game use. From our data it appears that the selection effect disappears once media preferences have solidified and appeal of the “forbidden fruit” is diminished. The higher autoregres- sion coefficient for the use of violent games among the older age-group (� � .65 vs. � �
.34) indicates that video game preferences stabilize at the beginning of adulthood. It seems that the phase of preference formation that von Salisch et al. (2011) report for their sample of 8- to 12-year-olds continues into adolescence and begins to stabilize once play- ers turn 18 and all types of games are legally available to them. In addition, parental con- trol of video game use tends to decrease with age (Wallenius & Punamäki, 2008). This not only enables players to more freely choose the games they play, but likely also reduces the “forbidden fruit effect” (Bijvank et al., 2009).7 Unfortunately, it is impossible to dis- entangle the effect of the solidification of media preferences and the forbidden fruit ef- fect in our current data. Hence, to arrive at a more detailed understanding of what causes the disappearance of the selection effect in early adulthood, more research into the con- tribution and relationship of the factors of legal availability and the solidification of video game preferences would be necessary. For now, we can only assume that both con- tribute to some extent to the change in the relationship between video game use and (physical) aggression.
Physical aggression was extremely stable across waves for both age groups (� � .97 vs. � � .88). This stability of trait aggression in the transition from adolescence to early adulthood might be part of the reason why we found no media effects. Put simply, the use of violent video games cannot explain a change in physi- cal aggression, if physical aggression does not change at all. Again, this is in line with the Catalyst Model (Ferguson et al., 2008), which proposes that the use of violent media is not a strong enough influence to alter fundamental personality traits. Genetic influences and prox- imal social factors, such as family violence (Ferguson, Ivory, et al., 2013; Ferguson et al., 2012), are likely to shape aggressive personality
7 Despite the relatively strict regulations in Germany, however, it is not uncommon for minors to play games that are not suitable for them according to the USK labels. In our wave 1 sample, 14% of gamers aged 14 and 15 played at least one game labeled 16� and 29% reported to currently play at least one game with an 18� USK rating. Of the respondents who were 16 or 17 years old in the first wave, 35% indicated that they play one or more games rated 18�.
322 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
traits already before the later phases of adoles- cence that were the focus of the current study.
Although we did cover a larger age range than most other longitudinal studies in this field and compared the relationship between violent video games and physical aggression for ado- lescents and young adults, our findings are not generalizable to other player populations, such as primary school students or older adults. Of course, our results do not mean that violent video games are completely harmless and do not have an effect on any player. Especially younger children may be negatively affected by these games, but then again, age rating systems and parental control should prevent access to violent games at a young age. Hence, if children play games that are not suitable for them, the undesired effects this may have are, ultimately, attributable to a lack of parent– child communi- cation or parental care. The results may also be different for other countries. Germany has some of the strictest laws with regard to the protection of minors from potentially harmful media con- tent. Some violent games are only available as localized low-violence versions that are typi- cally less explicit and graphic in their depiction of violent acts. A more important limitation of the present study, however, is the reliance on a very brief self-report measure of physical ag- gression. The inclusion of only two items on physical aggression was due to the design of the survey that featured questions on large variety of topics. And while the additional inclusion of peer, teacher, or parent reports of aggressive behavior is desirable (Ferguson, 2011; Fergu- son, Garza, et al., 2013; Ferguson et al., 2012; Gentile & Bushman, 2012; Krahé et al., 2012; von Salisch et al., 2011), this is not feasible for large-scale telephone surveys, especially if they also include adults. It is also possible that the effects we found are different for other types of aggression, such as verbal, relational, or indirect aggression (Möller & Krahé, 2009).
Another limitation of this study is that our use of age ratings as a proxy for violent content might be too crude. Even though violent content is one of the major criteria for the German USK age ratings (Hyman, 2005; MacMillan & Wedell, 2013), there are certainly others, such as sexual content or the complexity of the game mechanics (Busching et al., 2013). And while games with higher age ratings tend to feature more violent acts (Thompson et al., 2006),
many games for younger audiences also contain some forms of violence (Thompson & Haninger, 2001). These types of violence usu- ally differ from another on several dimensions, such as graphicness, realism, and justification (Tamborini, Weber, Bowman, Eden, & Skalski, 2013). The combination of a thorough content analysis and a longitudinal survey design by Shibuya, Sakamoto, Ihori, & Yukawa (2008) showed that the characteristics of video game violence, such as its justification, realism, graphicness, or punishment, seem to be more important than just the amount. However, most subjective ratings of violent content depend mostly or even exclusively on the graphicness of the portrayals (Gentile et al., 2011; Potter, 1999). Accordingly, self-reports of how violent a game is (Anderson et al., 2008; Gentile & Bushman, 2012) can be problematic, also be- cause there are interindividual differences in what is perceived as violent. Expert ratings, on the other hand, can be expected to be less bi- ased, but still bring about the difficulty of dif- ferences in expertise and, at the same time, strongly depend on the training of the coders and the stimulus material that is used, such as video recordings of a game or game reviews (Busching et al., 2013). To avoid the issue of interindividual differences in the evaluation of violent content, we opted for age ratings, but we acknowledge that there may be other measures of violent content that are more precise.
Games and genres that are violent, such as first-person shooters or fighting games, typi- cally also differ from others on more dimen- sions than just violent content, including competitiveness or pace of action (Adachi & Willoughby, 2011; Elson, Breuer, van Looy, Kneer, & Quandt, 2013). Apart from game characteristics, it might be that there are other variables affecting the relationship between aggression and the use of violent video games that we did not control for in this study, such as academic achievement (Krahé et al., 2012; von Salisch et al., 2011; Willoughby et al., 2012), relationship with parents (Ferguson, Garza, et al., 2013; Wallenius & Punamäki, 2008; Willoughby et al., 2012), family vio- lence (Ferguson et al., 2012; Ferguson, Garza, et al., 2013), or peer delinquency (Ferguson, Garza, et al., 2013; Ferguson et al., 2012; Willoughby et al., 2012). Finally, longitudinal studies remain correlational data, even though
323VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
they can identify the temporal precedence be- tween two or more variables. While we tried to control for potentially influential third vari- ables, such as respondent sex, education, and overall use of video games, there may be other variables that influenced the temporal relationship of physical aggression and use of violent games, such as those mentioned ear- lier.
Despite these limitations, we believe that our study shows that individual differences between video game players need to be taken into account when studying the relationship between aggression and video game use. One important variable in this context is age, as it is closely related to both developmental change and the access to violent games. Be- cause media preferences and personality traits tend to stabilize with age, both socialization and selection effects should be less likely for older players. Our replication of the findings by von Salisch et al. (2011) with data from an older and representative sample lends further support to the assumption of the Catalyst Model (Ferguson et al., 2008) that violent media do not have a substantial impact on aggressive personality or behavior, at least in the phases of late adolescence and early adult- hood that we focused on. To more fully in- vestigate the role of developmental change and age differences, future studies should in- clude more and potentially also more fine- grained age groups; consider additional mod- erator variables, such as family violence or sensation-seeking; and look at longer periods than just 1 year. To explain the relationship between video game use and aggression, it is necessary to abandon monocausal and unidi- rectional models and to understand that video games are more than just stimuli that affect everybody in the same way. Media users are more active and media effects are more indi- vidual than most theoretical models would suggest.
References
Achenbach, T. M., & Rescorla, L. A. (2001). Manual for ASEBA school-age forms & profiles. Burling- ton, VT: University of Vermont.
Adachi, P. J. C., & Willoughby, T. (2011). The effect of violent video games on aggression: Is it more than just the violence? Aggression and Violent
Behavior, 16, 55– 62. doi:10.1016/j.avb.2010.12 .002
Anderson, C. A., & Bushman, B. J. (2002). Human aggression. Annual Review of Psychology, 53, 27– 51. doi:10.1146/annurev.psych.53.100901.135231
Anderson, C. A., Sakamoto, A., Gentile, D. A., Ihori, N., Shibuya, A., Yukawa, S., . . . Kobayashi, K. (2008). Longitudinal effects of violent video games on aggression in Japan and the United States. Pediatrics, 122, e1067– e1072. doi: 10.1542/peds.2008-1425
Anderson, C. A., Shibuya, A., Ihori, N., Swing, E. L., Bushman, B. J., Sakamoto, A., . . . Saleem, M. (2010). Violent video game effects on aggression, empathy, and prosocial behavior in eastern and western countries: A meta-analytic review. Psy- chological Bulletin, 136, 151–73. doi:10.1037/ a0018251
Asparouhov, T., & Muthén, B. O. (2006). Robust chi square difference testing with mean and variance adjusted test statistics. Mplus Web Notes, 10, 1– 6.
Bandura, A. (1977). Social learning theory. New York, NY: Prentice Hall.
Barlett, C., Branch, O., Rodeheffer, C., & Harris, R. (2009). How long do the short-term violent video game effects last? Aggressive Behavior, 35, 225– 236. doi:10.1002/ab.20301
Berkowitz, L. (1990). On the formation and regula- tion of anger and aggression: A cognitive- neoassociationistic analysis. American Psycholo- gist, 45, 494 –503. doi:10.1037/0003-066X.45.4 .494
Bijvank, M. N., Konijn, E. A., Bushman, B. J., & Roelofsma, P. H. M. P. (2009). Age and violent content labels make video games forbidden fruits for youth. Pediatrics, 123, 870 – 6. doi:10.1542/ peds.2008-0601
Björkqvist, K., Lagerspetz, K., & Österman, K. (1998). Direct–Indirect Aggression Scales (DIAS). In K. Björkqvist & K. Österman (Eds.), Scales for research on interpersonal relations. Turku, Fin- land: Publishing House of Abo Akademi Univer- sity.
Busching, R., Gentile, D. A., Krahé, B., Möller, I., Khoo, A., Walsh, D. A., & Anderson, C. A. (2013), Testing the reliability and validity of dif- ferent measures of violent video game use in the United States, Singapore, and Germany. Psychol- ogy of Popular Media Culture. doi:10.1037/ ppm0000004
Bushman, B. J., & Huesmann, L. R. (2014). Twenty- five years of research on violence in digital games and aggression: A reply to Elson & Ferguson (2013). European Psychologist, 19, 47–55. doi: 10.1027/1016-9040/a000164
Buss, A. H., & Perry, M. (1992). The aggression questionnaire. Journal of Personality and Social
324 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
Psychology, 63, 452– 459. doi:10.1037/0022-3514 .63.3.452
Buss, A., & Warren, W. (2000). Aggression question- naire manual. Los Angeles, CA: Western Psycho- logical Services.
Cooper, J., & Mackie, D. (1986). Video games and aggression in children. Journal of Applied Social Psychology, 16, 726 –744. doi:10.1111/j.1559- 1816.1986.tb01755.x
Dominick, J. R. (1984). Videogames, television vio- lence, and aggression in teenagers. Journal of Communication, 34, 136 –147. doi:10.1111/j .1460-2466.1984.tb02165.x
Elson, M., Breuer, J., Van Looy, J., Kneer, J., & Quandt, T. (2013). Comparing apples and or- anges? Evidence for pace of action as a confound in research on digital games and aggression. Psy- chology of Popular Media Culture. Advance on- line publication. doi:10.1037/ppm0000010
Elson, M., & Ferguson, C. J. (2014a). Twenty-five years of research on violence in digital games and aggression: Empirical evidence, perspectives, and a debate gone astray. European Psychologist, 19(1), 33– 46. doi:10.1027/1016-9040/a000147
Elson, M., & Ferguson, C. J. (2014b). Does doing media violence research make one aggressive? The ideological rigidity of social cognitive theories of media violence and response to Bushman and Huesmann (2013), Krahé (2013), and Warburton (2013). European Psychologist, 19, 68 –75. doi: 10.1027/1016-9040/a000185
Ferguson, C. J. (2007). Evidence for publication bias in video game violence effects literature: A meta- analytic review. Aggression and Violent Behavior, 12, 470 – 482. doi:10.1016/j.avb.2007.01.001
Ferguson, C. J. (2010). Blazing angels or resident evil? Can violent video games be a force for good? Review of General Psychology, 14, 68 – 81. doi: 10.1037/a0018941
Ferguson, C. J. (2011). Video games and youth vio- lence: A prospective analysis in adolescents. Jour- nal of Youth and Adolescence, 40, 377–391. doi: 10.1007/s10964-010-9610-x
Ferguson, C. J., & Dyck, D. (2012). Paradigm change in aggression research: The time has come to retire the General Aggression Model. Aggression and Violent Behavior, 17, 220 –228. doi:10.1016/j.avb .2012.02.007
Ferguson, C. J., Garza, A., Jerabeck, J., Ramos, R., & Galindo, M. (2013). Not worth the fuss after all? Cross-sectional and prospective data on violent video game influences on aggression, visuospatial cognition and mathematics ability in a sample of youth. Journal of Youth and Adolescence, 42, 109 –122. doi:10.1007/s10964-012-9803-6
Ferguson, C. J., Ivory, J. D., & Beaver, K. M. (2013). Genetic, maternal, school, intelligence, and media use predictors of adult criminality: A longitudinal
test of the Catalyst Model in adolescence through early adulthood. Journal of Aggression, Maltreat- ment and Trauma, 22, 447– 460. doi:10.1080/ 10926771.2013.785457
Ferguson, C. J., & Kilburn, J. (2009). The public health risks of media violence: A meta-analytic review. The Journal of Pediatrics, 154, 759 –763. doi:10.1016/j.jpeds.2008.11.033
Ferguson, C. J., & Rueda, S. M. (2009). Examining the validity of the modified Taylor competitive reaction time test of aggression. Journal of Exper- imental Criminology, 5, 121–137. doi:10.1007/ s11292-009-9069-5
Ferguson, C. J., Rueda, S. M., Cruz, A. M., Ferguson, D. E., Fritz, S., & Smith, S. M. (2008). Violent video games and aggression: Causal relationship or byproduct of family violence and intrinsic vio- lence motivation? Criminal Justice and Behavior, 35, 311–332. doi:10.1177/0093854807311719
Ferguson, C. J., San Miguel, C., Garza, A., & Jera- beck, J. M. (2012). A longitudinal test of video game violence influences on dating and aggres- sion: A 3-year longitudinal study of adolescents. Journal of Psychiatric Research, 46, 141–146. doi: 10.1016/j.jpsychires.2011.10.014
Ferguson, C. J., Smith, S., Miller-Stratton, H., Fritz, S., & Heinrich, E. (2008). Aggression in the lab- oratory: Problems with the validity of the modified Taylor competitive reaction time test as a measure of aggression in media violence studies. Journal of Aggression, Maltreatment and Trauma, 17, 118 – 132. doi:10.1080/10926770802250678
Finkel, S. E. (1995). Causal analysis with panel data. Thousand Oaks, CA: Sage.
Gentile, D. A., & Bushman, B. J. (2012). Reassessing media violence effects using a risk and resilience approach to understanding aggression. Psychology of Popular Media Culture, 1, 138 –151. doi: 10.1037/a0028481
Gentile, D. A., Coyne, S., & Walsh, D. A. (2011). Media violence, physical aggression, and rela- tional aggression in school age children: A short- term longitudinal study. Aggressive Behavior, 37, 193–206. doi:10.1002/ab.20380
Greenberg, B. S., Sherry, J., Lachlan, K. A., Lucas, K., & Holmstrom, A. (2010). Orientations to video games among gender and age groups. Simulation and Gaming, 41, 238 –259. doi:10.1177/ 1046878108319930
Haninger, K., & Thompson, K. M. (2004). Content and ratings of teen-rated video games. Journal of the American Medical Association, 291, 856 – 865. doi:10.1001/jama.291.7.856
Herzberg, P. (2003). Faktorstruktur, Gütekriterien und Konstruktvalidität der deutschen Übersetzung des Aggressionsfragebogens von Buss und Perry [Factor structure, quality criteria, and construct validity of the German translation of the Aggres-
325VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
sion Questionnaire by Buss and Perry. Zeitschrift für Differentielle und Diagnostische Psychologie, 24, 311–323. doi:10.1024/0170-1789.24.4.311
Hopf, W. H., Huber, G. L., & Weiß, R. H. (2008). Media violence and youth violence. Journal of Media Psychology: Theories, Methods, and Appli- cations, 20, 79 –96. doi:10.1027/1864-1105.20 .3.79
Huesmann, L. R., & Guerra, N. G. (1997). Children’s normative beliefs about aggression and aggressive behavior. Journal of Personality and Social Psy- chology, 72, 408 – 419. doi:10.1037/0022-3514.72 .2.408
Hyman, P. (2005). Rated and willing: Where game rating boards differ. Game Developer Magazine. Retrieved from http://www.gamasutra.com/view/ feature/130896/rated_and_willing_where_game_ .php
Joireman, J., Anderson, J., & Strathman, A. (2003). The aggression paradox: Understanding links among aggression, sensation seeking, and the con- sideration of future consequences. Journal of Per- sonality and Social Psychology, 84, 1287–1302. doi:10.1037/0022-3514.84.6.1287
Kirsh, S. J. (2003). The effects of violent video games on adolescents. Aggression and Violent Behavior, 8, 377–389. doi:10.1016/S1359- 1789(02)00056-3
Krahé, B. (2014). Restoring the spirit of fair play in the debate about violent video games: A comment on Elson and Ferguson (2013). European Psychol- ogist, 19, 56 –59. doi:10.1027/1016-9040/a000165
Krahé, B., Busching, R., & Möller, I. (2012). Media violence use and aggression among German ado- lescents: Associations and trajectories of change in a three-wave longitudinal study. Psychology of Popular Media Culture, 1, 152–166. doi:10.1037/ a0028663
Krahé, B., & Möller, I. (2010). Longitudinal effects of media violence on aggression and empathy among German adolescents. Journal of Applied Developmental Psychology, 31, 401– 409. doi: 10.1016/j.appdev.2010.07.003
Lachlan, K. A., Smith, S. L., & Tamborini, R. (2005). Models for aggressive behavior: The attributes of violent characters in popular video games. Com- munication Studies, 56, 313–329. doi:10.1080/ 10510970500319377
Lenhart, A., Kahne, J., Middaugh, E., Rankin Macgill, A., Evans, C., & Vitak, J. (2008). Teens, video games, and civics. Washington, DC. Re- trieved from http://www.pewinternet.org/~/media/ Files/Reports/2008/PIP_Teens_G a m e s _ a n d _ Civics_Report_FINAL.pdf.pdf
Lindeman, M., Harakka, T., & Keltikangas-Järvinen, L. (1997). Age and gender differences in adoles- cents’ reactions to conflict situations: Aggression, prosociality, and withdrawal. Journal of Youth and
Adolescence, 26, 339 –351. doi:10.1007/s10964- 005-0006-2
Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing val- ues. Journal of the American Statistical Associa- tion, 83, 1198 –1202. doi:10.1080/01621459.1988 .10478722
Little, T. D., Jones, S. M., Henrich, C. C., & Hawley, P. H. (2003). Disentangling the “whys” from the “whats” of aggressive behaviour. International Journal of Behavioral Development, 27, 122–133. doi:10.1080/01650250244000128
Loeber, R., & Stouthamer-Loeber, M. (1998). Devel- opment of juvenile aggression and violence: Some common misconceptions and controversies. Amer- ican Psychologist, 53, 242–259. doi:10.1037/ 0003-066X.53.2.242
MacMillan, K., & Wedell, Z. (2013). Best practices for leveraging worldwide age ratings submissions and geopolitical content. Presentation at the Local- ization Summit of the 2013 Game Developers Conference.
Marini, Z., Spear, S., & Bombay, K. (1999). Peer victimization in middle childhood: Characteristics, causes, and consequences of school bullying. Brock Education, 9, 32– 47.
Medienpädagogischer Forschungsverbund Südwest. (2012). JIM-Studie 2012. Jugend, Information, (Multi-) Media. Retrieved from http://www.mpfs .de/fileadmin/JIM-pdf12/JIM2012_Endversion.pdf
Möller, I., & Krahé, B. (2009). Exposure to violent video games and aggression in German adoles- cents: A longitudinal analysis. Aggressive Behav- ior, 35, 75– 89. doi:10.1002/ab.20290
Muthén, L. K., & Muthén, B. O. (1998 –2010). Mplus user’s guide (6th ed.). Los Angeles, CA: Muthén & Muthén.
Olson, C. K. (2010). Children’s motivations for video game play in the context of normal development. Review of General Psychology, 14, 180 –187. doi: 10.1037/a0018984
Olson, C. K., Kutner, L. A., Baer, L., Beresin, E. V., Warner, D. E., & Nicholi, A. M. II. (2009). M- rated video games and aggressive or problem be- havior among young adolescents. Applied Devel- opmental Science, 13, 188 –198. doi:10.1080/ 10888690903288748
Olweus, D. (1996). The revised Olweus Bully/Victim Questionnaire. Bergen, Norway: University of Bergen.
Ostrov, J. M., Gentile, D. A., & Crick, N. R. (2006). Media exposure, aggression, and prosocial behav- ior during early childhood: A longitudinal study. Social Development, 15, 612– 627. doi:10.1111/j .1467-9507.2006.00360.x
Paternoster, R., & Mazerolle, P. (1994). General strain theory and delinquency: A replication and extension.
326 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
Journal of Research in Crime and Delinquency, 31, 235–263. doi:10.1177/0022427894031003001
Potter, W. J. (1999). On media violence. Thousand Oaks, CA: Sage. Blinded for review.
Quandt, T., Breuer, J., Festl, R., & Scharkow, M. (2013). Digitale Spiele: Stabile nutzung in einem dynamischen markt. [Digital games: Stable pat- terns of use in a dynamic market]. Media Perspek- tiven, 10, 483– 492.
Ritter, D., & Eslea, M. (2005). Hot Sauce, toy guns, and graffiti: A critical account of current labora- tory aggression paradigms. Aggressive Behavior, 31, 407– 419. doi:10.1002/ab.20066
Sakai, A., Yamasaki, K., Soga, S., Oashi, O., Shimai, S., & Otake, K. (2000). Shogakusei kougekisei shitsumonshi no sakusei to shinraisei, datousei no kentou [Development of an aggression question- naire for elementary school–aged children]. Gak- kou hoken kenkyu [Japanese Journal of School Health], 42, 423– 433.
Sherry, J. (2001). The effects of violent video games on aggression. Human Communication Research, 27, 409 – 431. doi:10.1111/j.1468-2958.2001 .tb00787.x
Sherry, J. (2007). Violent video games and aggres- sion: Why can’t we find effects? In R. Preiss, N. Gayle, M. Burrell, M. Allen, & J. Bryant (Eds.), Mass media effects research: Advances through meta-analyses (pp. 245–262). Mahwah, NJ: Erl- baum.
Shibuya, A., Sakamoto, A., Ihori, N., & Yukawa, S. (2008). The effects of the presence and contexts of video game violence on children: A longitudinal study in Japan. Simulation and Gaming, 39, 528 – 539. doi:10.1177/1046878107306670
Silvern, S. B., & Williamson, P. A. (1987). The effects of video game play on young children’s aggression, fantasy, and prosocial behavior. Jour- nal of Applied Developmental Psychology, 8, 453– 462. doi:10.1016/0193-3973(87)90033-5
Slater, M. D. (2003). Alienation, aggression, and sensation seeking as predictors of adolescent use of violent film, computer, and website content. Journal of Communication, 53, 105–121. doi: 10.1111/j.1460-2466.2003.tb03008.x
Slater, M. D. (2007). Reinforcing spirals: The mutual influence of media selectivity and media effects and their impact on individual behavior and social identity. Communication Theory, 17, 281–303. doi:10.1111/j.1468-2885.2007.00296.x
Slater, M. D., Henry, K. L., Swaim, R. C., & Ander- son, L. L. (2003). Violent media content and ag- gressiveness in adolescents: A downward spiral model. Communication Research, 30, 713–736. doi:10.1177/0093650203258281
Smith, S. L., Lachlan, K. A., & Tamborini, R. (2003). Popular video games: Quantifying the presentation of violence and its context. Journal of Broadcast-
ing and Electronic Media, 47, 58 –76. doi:10.1207/ s15506878jobem4701_4
Steinberg, L., Albert, D., Cauffman, E., Banich, M., Graham, S., & Woolard, J. (2008). Age differences in sensation seeking and impulsivity as indexed by behavior and self-report: Evidence for a dual sys- tems model. Developmental Psychology, 44, 1764 –1778. doi:10.1037/a0012955
Surette, R. (2013). Cause or catalyst: The interaction of real world and media crime models. American Journal of Criminal Justice, 38, 392– 409. doi: 10.1007/s12103-012-9177-z
Tamborini, R., Weber, R., Bowman, N. D., Eden, A., & Skalski, P. (2013). “Violence is a many- splintered thing”: The importance of realism, jus- tification, and graphicness in understanding per- ceptions of and preferences for violent films and video games. Projections, 7, 100 –118. doi: 10.3167/proj.2013.070108
Tedeschi, J. T., & Quigley, B. M. (1996). Limitations of laboratory paradigms for studying aggression. Aggression and Violent Behavior, 1, 163–177. doi: 10.1016/1359-1789(95)00014-3
Thompson, K. M., & Haninger, K. (2001). Violence in E-rated video games. Journal of the American Medical Association, 286, 591–598. doi:10.1001/ jama.286.5.591
Thompson, K. M., Tepichin, K., & Haninger, K. (2006). Content and ratings of mature-rated video games. Archives of Pediatrics and Adolescent Medicine, 160, 402– 410. doi:10.1001/archpedi .160.4.402
Tillmann, K.-J., Holler-Novitzki, B., Holtappels, H. G., Meier, U., & Popp, U. (1999). Schül- ergewalt als Schulproblem [Student violence as a school problem]. Munich, Germany: Juventa.
Von der Heyde, C. (2013). The ADM sampling sys- tem for telephone surveys. Retrieved from Arbe- itskreis Deutscher Markt- und Sozialforschungsin- stitute e. V. website: https://www.adm-ev.de/en/ navoben/adm-sampling/tel-description/
Von Salisch, M., Vogelgesang, J., Kristen, A., & Oppl, C. (2011). Preference for violent electronic games and aggressive behavior among children: The beginning of the downward spiral? Media Psychology, 14, 233–258. doi:10.1080/15213269 .2011.596468
Wallenius, M., & Punamäki, R.-L. (2008). Digital game violence and direct aggression in adoles- cence: A longitudinal study of the roles of sex, age, and parent– child communication. Journal of Ap- plied Developmental Psychology, 29, 286 –294. doi:10.1016/j.appdev.2008.04.010
Warburton, W. (2014). Apples, oranges and the bur- den of proof: Putting media violence findings in context. A comment on Elson and Ferguson (2013). European Psychologist, 19, 60 – 67. doi: 10.1027/1016-9040/a000166
327VIOLENT VIDEO GAMES AND PHYSICAL AGGRESSION
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
Williams, D., & Skoric, M. (2005). Internet fantasy violence: A test of aggression in an online game. Communication Monographs, 72, 217–233. doi: 10.1080/03637750500111781
Willoughby, T., Adachi, P. J. C., & Good, M. (2012). A longitudinal study of the association between violent video game play and aggression among adolescents. Developmental Psychology, 48, 1044 –1057. doi:10.1037/a0026046
Winkel, M., Novak, D. M., & Hopson, H. (1987). Personality factors, subject gender, and the effects of aggressive video games on aggression in ado-
lescents. Journal of Research in Personality, 21, 211–223. doi:10.1016/0092-6566(87)90008-0
Zillmann, D. (1983). Arousal and aggression. In R. G. Geen & E. Donnerstein (Eds.), Aggression: Theoretical and empirical reviews (pp. 75–102). New York, NY: Academic.
Zillmann, D., & Bryant, J. (1985). Selective exposure to communication. Hillsdale, NJ: Erlbaum.
Received November 20, 2013 Revision received February 27, 2014
Accepted March 4, 2014 �
Members of Underrepresented Groups: Reviewers for Journal Manuscripts Wanted
If you are interested in reviewing manuscripts for APA journals, the APA Publications and Communications Board would like to invite your participation. Manuscript reviewers are vital to the publications process. As a reviewer, you would gain valuable experience in publishing. The P&C Board is particularly interested in encouraging members of underrepresented groups to participate more in this process.
If you are interested in reviewing manuscripts, please write APA Journals at [email protected]. Please note the following important points:
• To be selected as a reviewer, you must have published articles in peer-reviewed journals. The experience of publishing provides a reviewer with the basis for preparing a thorough, objective review.
• To be selected, it is critical to be a regular reader of the five to six empirical journals that are most central to the area or journal for which you would like to review. Current knowledge of recently published research provides a reviewer with the knowledge base to evaluate a new submission within the context of existing research.
• To select the appropriate reviewers for each manuscript, the editor needs detailed information. Please include with your letter your vita. In the letter, please identify which APA journal(s) you are interested in, and describe your area of expertise. Be as specific as possible. For example, “social psychology” is not sufficient—you would need to specify “social cognition” or “attitude change” as well.
• Reviewing a manuscript takes time (1– 4 hours per manuscript reviewed). If you are selected to review a manuscript, be prepared to invest the necessary time to evaluate the manuscript thoroughly.
APA now has an online video course that provides guidance in reviewing manuscripts. To learn more about the course and to access the video, visit http://www.apa.org/pubs/ authors/review-manuscript-ce-video.aspx.
328 BREUER, VOGELGESANG, QUANDT, AND FESTL
T hi
s do
cu m
en t
is co
py ri
gh te
d by
th e
A m
er ic
an P
sy ch
ol og
ic al
A ss
oc ia
ti on
or on
e of
it s
al li
ed pu
bl is
he rs
. T
hi s
ar ti
cl e
is in
te nd
ed so
le ly
fo r
th e
pe rs
on al
us e
of th
e in
di vi
du al
us er
an d
is no
t to
be di
ss em
in at
ed br
oa dl
y.
- Violent Video Games and Physical Aggression: Evidence for a Selection Effect Among Adolescents
- Theories Explaining Long-Term Effects of Video Games on Aggression
- Longitudinal Studies on Video Games and Aggression
- Aggression, Violent Video Games, and Age
- Method
- Participants and Procedure
- Measures
- Demographic factors
- Physical aggression
- Use of violent video games
- Overall video game use
- Data Analysis
- Results
- Preliminary Analyses
- Long-Term Relationships Between Use of Violent Video Games and Physical Aggression
- Discussion
- References
