Video Gaming and Children’s Psychosocial Wellbeing: A Longitudinal Study
J Youth Adolescence
Video Gaming and Children's Psychosocial Wellbeing: A Longitudinal Study
Adam Lobel 0 1 2 3
● Rutger C. M. E. Engels 0 1 2 3
● Lisanne L. Stone 0 1 2 3
● William J. Burk 0 1 2 3
● Isabela Granic 0 1 2 3
Adam Lobel 0 1 2 3
0 Overwaal, Centre for Anxiety Disorders , Pro Persona Tarweweg, Nijmegen 6534AM , Netherlands
1 Trimbos Institute , Da Costakade 45, Utrecht 3521VS , Netherlands
2 Swiss Center for Affective Sciences, University of Geneva , Chemin des Mines 9, Geneva 1202 , Switzerland
3 Behavioural Science Institute, Radboud University , Montessorilaan, Nijmegen 6525HR , Netherlands
The effects of video games on children's psychosocial development remain the focus of debate. At two timepoints, 1 year apart, 194 children (7.27-11.43 years old; male = 98) reported their gaming frequency, and their tendencies to play violent video games, and to game (a) cooperatively and (b) competitively; likewise, parents reported their children's psychosocial health. Gaming at time one was associated with increases in emotion problems. Violent gaming was not associated with psychosocial changes. Cooperative gaming was not associated with changes in prosocial behavior. Finally, competitive gaming was associated with decreases in prosocial behavior, but only among children who played video games with high frequency. Thus, gaming frequency was related to increases in internalizing but not externalizing, attention, or peer problems, violent gaming was not associated with increases in externalizing problems, and for children playing approximately 8 h or more per week, frequent competitive gaming may be a risk factor for decreasing prosocial behavior. We argue that replication is needed and that future research should better distinguish between different forms of gaming for more nuanced and generalizable insight.
Psychosocial development ● Video games ●; Prosocial behavior ● Longitudinal
Video games have rapidly become a universal aspect of
(Lenhart et al. 2008)
, and their quick rise
to prominence has stimulated scientific inquiry and public
. With researchers stressing that
children may be particularly susceptible to the influence of
video game playing
(Bushman and Huesmann 2006; Lobel
et al. 2014a)
, the effects of video games on children’s
psychosocial development remains highly debated. Video
games have thus been widely studied as a potential cause
for aggressive cognitions and behavior
(Anderson et al.
2010; Carnagey and Anderson 2004)
, emotional problems
such as depression (Tortolero et al. 2014), and hyperactivity
(Gentile et al. 2012)
. In these lines of
research, video games are seen as a compelling
entertainment medium whose clever use of feedback loops and
positive reinforcement schedules train unhealthy habits of
(Gentile and Gentile 2008a, b)
Conversely, researchers have recently begun to look at
video games as a domain for training healthy habits of mind
(Adachi and Willoughby 2012; Granic et al. 2014)
this perspective, many video games reward communication
and cooperation as well as resolving negative emotions such
as frustration. Moreover, video games seem to provide a
context for the fulfillment of self-deterministic needs,
thereby positively contributing to psychological well-being
(Ryan et al. 2006). The current paper adds to the discussion
on gaming’s positive and negative consequences with data
from a longitudinal study that could address the relations
between different forms of video game playing and the
psychosocial development of children. Here, psychosocial
development refers broadly to the psychological and social
changes children undergo during development, including
changes in patterns of internalizing and externalizing
problems, attention, and how children relate to peers.
Psychosocial Development and Gaming
In a recent review we argued for the potential of video
gaming to afford psychosocial benefits
(Granic et al. 2014)
This perspective focuses on gaming as a modern and
meaningful form of play, and therefore as a context where
children’s developmental needs can be met
Verenikina et al. 2003)
. Just as traditional forms of play
provide positive contexts for children’s psychosocial
(Erikson 1977; Piaget 1962; Vygotsky 1978)
, so too
video games seem to afford promise
Willoughby 2012; Granic et al. 2014)
. This promise is in part
due to the ubiquity of gaming; with between 90 and 97% of
children playing video games
(Lenhart et al. 2008)
, it seems
that social development has partly migrated from physical
playgrounds to digital ones. Moreover, video games have
become—particularly in the past decade—a more social and
emotionally rich entertainment medium. Thus, modern video
games may provide a context for children to bond with others
and learn the benefits of cooperation.
Yet despite the potential benefits of gaming for children’s
psychosocial development, scant empirical work has
explored these options
(Hromek and Roffey 2009;
Przybylski and Wang 2016)
. Instead, there has been a
predominant focus on the potential psychosocial dangers of
gaming. A recent meta-analysis identified 101 studies that
investigated the effects of playing (violent) video games on
children’s and adolescents’ psychosocial health. Of these
studies, nearly 70 of them assessed whether (violent) video
games were related to externalizing problems (such as
aggression). In contrast, prosocial behavior
et al. 2009)
and internalizing problems (such as depression)
were each assessed in about 20 studies
(e.g. Parkes et al.
. Just 9 studies assessed the relation between gaming
and attention problems
(e.g. Bioulac et al. 2008)
fewer investigated the relation between gaming and
children’s peer relationships
(e.g. Przybylski 2014)
Several methodological shortcomings are also important
to highlight. First, gaming research among children has
predominantly been cross-sectional in nature—64 of the
101 studies identified in
The major limitation of these studies is that they do not allow
inferences about order. Moreover, many of these studies have
not controlled for relevant background variables such as
socio-economic status (SES) and gender. On the other hand,
while experimental studies allow researchers to draw causal
inferences, the real-world generalizability of such gaming
studies remain debated. Regarding studies on externalizing
problems in particular, researchers have questioned the
ecological validity of the outcome measures used
and Bushman 1997; Ritter and Eslea 2005)
and the extent to
which these studies used well-matched control conditions
(see Przybylski et al. 2014)
. Beyond these issues, as most of
these experimental studies were run in a single lab session,
these experiments do not give enough insight into the
longterm consequences of playing video games.
Regarding internalizing problems, studies that examine
the link between gaming and emotional problems have
predominantly focused on “problematic gamers.” These are
individuals who habitually play for very many hours and
show other signs of dependency, such as avoiding social
interactions or obligations in favor of gaming
et al. 2011)
. Among adolescents, such gamers seem to have
elevated depression symptoms compared to their peers
(Messias et al. 2011)
. A recent, large scale, cross-sectional
study among Canadian adolescents also indicated that video
game play was positively associated with symptoms of
depression and anxiety
(Maras et al. 2015)
. These findings
are consistent with the conclusions made in a review by
Kuss and Griffiths (2012)
. These problems seem to emerge
as a result of escapism; that is that problematic gamers seem
drawn to gaming as an escape from real world problems. As
a means of escape, gaming may offer temporary distraction,
but without alleviating real world distress, excessive
gaming may only exacerbate said problems. Still, the
crosssectional nature of past studies leaves open whether
individuals with internalizing problems retreat to video games
as an escape, or whether gaming acts as a precursor to these
issues. Moreover, little is known about the relationship
between gaming and internalizing problems in children due
to the scarcity of research among this cohort.
Finally, hyperactivity and inattention has been
investigated as a detrimental psychosocial outcome of gaming.
This research is premised on the perception that video
games are fast-paced and offer frequent rewards, thus
potentially habituating children to a steady stream of novel,
pleasurable stimuli. On the one hand, children with
Attentional Deficit Hyperactivity Disorder have been shown to
play more video games than their peers
and Gentile and colleagues (2012) argue
that there may be a bidirectional effect between attentional
problems and gaming. On the other hand, studies among
adults show that action video games may confer cognitive
benefits, including improvements in executive functioning
(Green and Bavelier 2012)
. Due to these conflicting
findings, and a lack of longitudinal research among children, the
extent to which gaming may influence children’s attention
remains largely unknown.
Prosocial Behavior and Cooperative and Competitive
The potential influence of video games on social behavior
seems particularly relevant. This is because, compared to the
video games of just two decades ago, contemporary video
games have become increasingly social in nature
. Researchers such as Greitemeyer and Ewoldsen have
noted that just as some games predicate in-game progress on
violence, other games predicate progress on prosocial
(Ewoldsen et al. 2012; Greitemeyer and Osswald
. For instance, many games designed for multiple
players feature cooperative game modes where players are
encouraged to work together with others. A number of
studies support the hypothesis that cooperative gaming may
promote prosocial behavior
(Dolgov et al. 2014; Ewoldsen
et al. 2012)
and may curb aggressive behaviors
Ferguson 2013; Velez et al. 2014)
(although many of these
studies feature the sorts of methodological shortcomings
mentioned above). In contrast to cooperative gaming,
researchers have also investigated whether competitive
gaming promotes aggression and discourages prosocial
. For instance, Adachi and colleagues
performed a series of studies to test the relative extent to
which violent content and competitive play each promote
. Using experimental and
longitudinal designs, these studies indicated that in both the
shortand long-term, competitive gaming may be a greater
predictor of aggressive outcomes than violence alone. However,
cooperative and competitive gaming have yet to be
researched in the way these forms of play most commonly occur in
the real world—in tandem. Thus, while researchers have tried
to individually assess the effects of these forms of play, they
often co-occur in the real-world of gaming most children
participate. This is because many competitive video games
not only allow cooperative modes, but the competition in
these games is often team-based. However, no longitudinal
studies to date have simultaneously investigated the influence
of both cooperative and competitive video game playing; this
is important as many video games designed for competitive
play are also team-based, and therefore allow for cooperative
play as well.
Design and Hypotheses
The present longitudinal study was designed to address the
gaps in the literature described above. First, we focused on
the potential psychosocial benefits that playing video games
may have for children. Thus, in addition to assessing
negative outcomes such as externalizing problems,
internalizing problems, and hyperactivity and inattention, we
also focused on peer relations, and prosocial behavior.
Second, this study targeted an under-studied population,
namely children between the ages of seven and eleven.
Indeed, despite claims that children are especially vulnerable
to the effects of video game playing
, scant longitudinal research has targeted
children. Children seem particularly susceptible to being
influenced by video games because, unlike adults, they are
still in the process of forming patterns for how they deal with
social and emotional challenges. The behaviors and patterns
of mind that are therefore promoted during video game may
have a greater impact on them than on adults. Moreover, as
children near adolescence, their peer network and
relationships become increasingly important
. As a
result, the social interactions they enact and rehearse during
video game play may be of greater relevance for how they
interact with their peers in the real world. Finally, our
longitudinal design allowed us to simultaneously test for both
gaming and selection effects; in the former, video game
playing may precipitate psychosocial changes, whereas in the
latter, children who already show psychosocial deficits may
select video games as an outlet. Thus, our longitudinal design
also allowed us to investigate the tandem development of
video game playing and psychosocial health.
Five domains of children’s psychosocial health were
assessed at two timepoints—externalizing problems,
internalizing problems, hyperactivity and inattention, peer
problems, and prosocial behavior. Given the psychosocial
benefits of play, we expected video game playing at the first
time point to predict decreases in children’s (H1)
externalizing problems, (H2) internalizing problems, (H3) peer
problems, and (H4) overall psychosocial problems by the
second time point. Given the lack of consensus in the
research, no predictions were made for the influence of
gaming on hyperactivity and inattention, or on prosocial
behavior, although exploratory analyses were conducted.
We also explored the potential relationships between violent
video game content and both externalizing problems and
prosocial behavior. Finally, we also hypothesized that (H5a)
cooperative gaming at the first time point would be
associated with increases in prosocial behavior, whereas (H5b)
competitive gaming at the first time point would be
associated with decreases in prosocial behavior.
Data were collected during home visits 1 year apart (T1 and
T2; days between visits: range 265–510, M = 392.22, SD
= 59.05). Participants were recruited from a pool of 298
participants already participating in research which tracked
children’s psycho-social health
(Stone et al. 2010)
were contacted via letters sent to their homes and follow-up
phone invitations. At T1, the children’s gender was evenly
split (boys n = 98); 86.6% of parent reporters were female
(n = 168); with the exception of three adopted mothers and
one adopted father, all parents were the child’s biological
parent; finally, 96.9% of parents were Dutch (n = 188), with
the others coming from Suriname (n = 1) or nearby
European countries (n = 5). The study’s procedures were
approved by the Behavioural Science Institute’s Ethical
Review Board under the Radboud University, and informed
consent forms were obtained from parents at both
timepoints. Descriptive statistics for the sample at T1 and T2 are
reported in Table 1. Ten participants from T1 declined to
participate at T2. Additionally, data from ten parent reports
were missing at T2 because their data was not properly
saved by the recording software. With the exception of five
parents, all parent reports were provided by the same parent
at T1 and T2. Among parents, education level was low for
6.7%, medium for 30.4%, and high for 60.3%1.
Children provided self-reports during a face-to-face
interview with an experimenter. Parents provided their survey
responses via an online questionnaire. Families were
rewarded a 20 and 30 Euro voucher check (per child) for
their participation at T1 and T2 respectively.
1 Secondary and higher education in the Netherlands is stratified.
Here, low refers to individuals who completed the lowest level of
secondary school, a vocational school track until the age of 16;
medium refers to individuals who completed a more advanced
vocational track until the age of 17; and high refers to individuals
with a university-level education, having attained a Bachelor’s degree
Psychosocial health was measured by parent’s reports on the
Dutch version of the Strengths and Difficulties
; Dutch version
Widenfelt et al. 2003)
). The SDQ uses a 3-point Likert
scale (0–2 Not true to Very true) and is comprised of five
sub-scales: (a) internalizing problems, (b) externalizing
problems, (c) hyperactivity/inattention, (d) peer relationship
problems, and (e) prosocial behavior. Consistent with Stone
and colleagues (2010) reliability was calculated using ω;
this reliability index has repeatedly been shown to yield
more accurate estimates than α, particularly so when data
are skewed, as is the case with SDQ
(Stone et al. 2015;
Zinbarg et al. 2005)
. All sub-scales showed acceptable to
good reliability at T1 and T2: (a) internalizing problems
(sample: Many worries, often seems worried; ωT1 = .83;
ωT2 = .81); (b) externalizing problems (sample: Often fights
with other children or bullies them; ωT1 = .75; ωT2 = .89);
(c) hyperactivity/inattention (sample: Restless, overactive,
cannot stay still for long; ωT1 = .88; ωT2 = .89); (d)
peer problems (sample: Rather solitary, tends to play alone;
ωT1 = .83; ωT2 = .68); and (e) prosocial behavior (sample:
Shares readily with other children; ωT1 = .84; ωT2 = .78).
All sub-scales consist of five items with sum scores being
calculated for each sub-scale. The SDQ also includes
a total difficulties score, calculated as the sum scores of all
scales except for prosocial behavior (ωT1 = .95; ωT2 = .95);
this reflects children’s general psychosocial health.
Descriptive statistics for the SDQ measures are presented in
Children’s frequency of video game playing was assessed
by: (1) Parental reports for the number of hours their child
plays on average per week; (2) child reports for the number
of hours they had played video games during the past week;
(3) children’s ability to recall their gaming hours across a
whole week was scaffolded by an additional measure of
gaming frequency: in interviews, children looked over a
calendar with the experimenter and indicated for each day
over the past full week whether or not they had played a
video game in the morning, afternoon, and evening. “Video
games” were explicitly described to parents and children as
any game that can be played on an electronic device, and
several example games were listed.
Descriptive statistics for the frequency measures are
presented in Table 3. Both parent’s and children’s reported
hours of gaming were Windorized with a cut-off at 3 SD
above the mean (T1: parent reports: M = 5.76, SD = 3.87,
outliers n = 4; child reports: M = 4.86, SD = 4.25, outliers
n = 6. T2: parent reports M = 6.83, SD = 5, outliers n = 2;
child reports: M = 5.92, SD = 5.9, outliers n = 2). Children
reported an average of 7.88 discrete play sessions per week
(SD = 4.15) at T1 and 8.11 (SD = 4.78) at T2.
Moderate correlations were observed across the three
frequency measures at each time point (T1: r ≥ .47, p
< .001; T2: r ≥ .41, p < .001). Moderate correlations were
also observed within reporters across T1 and T2 (parental
report: r = .566, p < .001; child report: hours r = .367, p
< .001, calendar r = .485, p < .001). Game frequency was
operationalized as child reports of hours gaming2. As
psychosocial health was reported by parents, this means that
our analyses were performed across reporters. This is
preferred to analyses using only a single reporter as such
analyses introduce a potential single source bias
Laursen 2010; Lobel et al. 2014a)
2 Analyses using parent reported hours yielded the same pattern of
Similar to the methods in
Anderson and Dill (2000)
Prot et al. (2014)
, children were asked to report their
favorite video game(s) from the past several weeks. At T1,
Minecraft, Super Mario Bros., and Subway Surfer were the
most popularly listed games/franchises, each being reported
by 13 children. At T2, the most popular titles were more
diverse with 46 children listing Minecraft, 21 listing a title
from the Fifa franchise, and 18 listing Mario Party and Hay
Day each. Violent gaming was computed as a dichotomous
variable; children who listed a violent video game among
their favorite games were assigned a 1, and those who did
not were assigned a 0. Video games were classified as being
violent when gameplay required players to harm other
Cooperative and competitive gaming
Whereas third-party review boards provide information about
whether a game contains violent content, the extent to which
games are played cooperatively or competitively is not.
Violent content is therefore objectively observable based on a
game’s content and design, whereas competitive and
cooperative play is more difficult to observe. Following
Przybylski and Mishkin (2016)
, cooperative and competitive
gaming were therefore individually assessed by children with
a single item using a Likert scale (5-point scale: Never to
Every time or almost every time). Experimenters clearly
informed children what was meant by “cooperative” and
“competitive” gaming: Children were asked to think about the
times that they play video games, and to rate the frequency
with which, when playing, they play a game where they have
to “work together with others; that the game is cooperative”
and “play against others; that the game is competitive”.
All analyses were performed in R
(R Core Team 2013)
preliminary analyses, paired-sample t-tests were used to
determine whether children’s psychosocial health and
gaming frequency changed from T1 to T2, independent
ttests were used to determine whether there were gender
differences on all variables at both timepoints, and
correlations were calculated. To investigate our hypotheses, three
sets of structural path models were estimated with the
. In all models, full
information maximum likelihood was used to account for
missing values and the Hubert-White covariance adjustment
(MLR in lavaan) was applied to standard errors in order to
deal with the lack of normally distributed variables.
In the first models, cross-lagged panel models were
estimated to test H1-H4; that is, whether gaming at T1
would be associated with changes from T1 to T2 on (H1)
externalizing problems, (H2) internalizing problems, (H3)
peer problems, and (H4) overall psychosocial health.
Figure 1 presents a template model. These models allowed
us to simultaneously test the effects of gaming on
psychosocial health, and for the reverse, a selection effect of
psychosocial health at T1 influencing gaming frequency.
These same models were used to explore the relationship
between gaming and changes in attention problems and in
prosocial behavior. Our second and third models targeted
those children who regularly played video games, defined
as children who played for more than 1 h per week (95.9%
of children, n = 186)3. We chose to segment out non-gamer
children because our hypotheses specifically concern
differences in gaming behavior; that is we intended to
determine whether one pattern of gaming behavior could be
beneficial or detrimental compared to other patterns of
gaming behaviors. Therefore, for these children we
explored (1) whether violent gaming was associated with
changes in conduct problems and in prosocial behavior
(Fig. 2), and we tested (2) whether: (H5a) playing
cooperatively was associated with increases in prosocial
behavior; and (H5b) playing competitively was associated with
decreases in prosocial behavior (Fig. 3). All models were
saturated (and therefore had zero degrees of freedom).
Table 2 reports the means and standard deviations for the
SDQ at T1 and T2. Peer problems and total difficulties
decreased from T1 to T2 (peer: MT1 = 1.14 SDT1 = 1.63 vs.
MT2 = 0.97 SD T2 = 1.27, t(173) = 2.09, p = .038; total
difficulties: MT1 = 7.15 SDT1 = 5.33 vs. MT2 = 6.47
3 The observed pattern of results remained the same when only
including children who played for more than two (86.08%, n = 167) or
more than 3 h (75.77%, n = 147) per week.
Fig. 1 Cross-lagged panel model testing the bidirectional associations
between gaming frequency and psycho-social health. SDQ Strengths
and Difficulties Questionnaire, Gaming gaming frequency in hours
reported by children. Highlighted path reflects hypothesized path. Not
depicted: Gender, child’s age, and parental level of education were
included as control variables; correlations among predictor and among
outcomes are included in the model
Fig. 2 Model testing the associations between gaming frequency,
violent gaming, and psychosocial health. SDQ Strengths and
Difficulties Questionnaire, Gaming gaming frequency in hours reported by
children. Highlighted path reflects hypothesized path. Not depicted:
Gender, child’s age, and parental level of education were included as
control variables; correlations among predictor and among outcomes
are included in the model. This model was run twice, each using a
different SDQ subscale, once with the conduct problems subscale and
once with the prosocial behavior subscale
SDT2 = 4.99, t(173) = 2.29, p = .023). Regarding gaming
frequency, while children did not report an increase in the
number of discrete sessions per week that they played video
games (MT1 = 7.88 SDT1 = 4.15 vs. MT2 = 8.11 SD T2 =
4.78, t(182) = −1.18, p = 0.238), children’s hours gaming
per week increased according to both parents (MT1 = 5.7
SDT1 = 3.63 vs. M T2 = 6.8 SDT2 = 4.9, t(173) = −4.15, p
< .001) and children (MT1 = 4.9 SDT1 = 4.07 vs. MT2 =
5.82 SD T2 = 5.48, t(182) = −2.61, p = .01). Table 4
reports the correlations between all predictor and predicted
variables used for hypothesis testing, and Table 5 reports
the correlations between the control variables used in these
models (child’s age, gender (1 = Male, 2= Female), and
parent’s education level (1 = low, 2 = medium, 3 = high).
Gender differences were observed at both time points for
both the SDQ and gaming frequency (Table 6). Regarding
the SDQ, parents reported boys, compared to girls, at T1
and T2 as having more hyperactivity problems, less
prosocial behavior, and more overall difficulties. Parents also
reported boys as having more conduct problems at T2 than
girls, but this was not observed at T1. According to parents
and children, boys played video games more frequently
than girls at both T1 and T2. Finally, the popularity of
violent video games increased from T1 (n = 47) to T2 (n=
64), t(177) = −2.69, p = .008.
Gaming and Psychosocial Health
Figure 1 illustrates the cross-lagged panel models used to
test whether gaming at T1 was associated with changes in
psychosocial health. Contrary to our expectations, (H2)
gaming frequency predicted an increase in internalizing
problems from T1 to T2 (β4 = .137, p = .024). Also
contrary to our expectations, gaming was unrelated to (H1)
externalizing problems—β4 = .092, p = .125; (H3) peer
problems—β4 = .040, p = .516; and (H4) total difficulties—
β4 = .039, p = .413. Regarding hyperactivity/inattention
and regarding prosocial behavior, gaming frequency was
not associated with changes in these variables;—β4=
−.053, p = .255, and β4 = −.022, p = .727 respectively.
None of the psychosocial health measures at T1 were
associated with changes in gaming from T1 to T2 (β3 range:
0–0.69, p .299–.944) thus no selection effects were
observed. Stability paths for these models ranged from 0.54
to .79 with p ≤ .001 for β1 (SDQ across timepoints), and
from 0.3 to .31 with p ≤ .001 for β2 (gaming frequency
across timepoints), indicating that the SDQ and gaming
frequency were relatively stable across time points, with
gaming however showing more variability from T1 to T2.
Violent Gaming, Conduct Problems, and Prosocial
We next explored whether changes in conduct problems and
in prosocial behavior would be associated with violent
gaming among those children who played games at T1 (see
Fig. 2). Violent gaming was therefore added as a direct
effect—β3—as was the interaction between gaming
frequency (child report)4 and violent gaming—β4. In both the
conduct problems and the prosocial behavior models, no
associations were observed for either violent gaming
(conduct: β3 = 0.017, p = .788; prosocial: β3 = 0.091, p = .176)
or the interaction term (conduct: β4 = −0.122, p = .098;
prosocial: β4 = −0.081, p = .301)5.
Cooperative Gaming, Competitive Gaming, and
Finally, we simultaneously investigated whether changes in
prosocial behavior would be (H5a) positively associated with
cooperative gaming and (H5b) negatively associated with
competitive gaming among those children who played games
at T1 (see Fig. 3). Cooperative and competitive gaming were
added as direct effects—β5 and β7 respectively—and two
interaction terms were added representing the interaction
between gaming frequency (child report)5 and (1) cooperative
gaming and (2) competitive gaming—β6 and β8 respectively.
Neither cooperative nor competitive gaming at T1 was
associated with changes in prosocial behavior (cooperative: β3
= .07, p = 0.402; competitive: β5 = .021, p = 0.813);
moreover no significant interaction was observed between
cooperative gaming and gaming frequency on prosocial behavior
(β4 = .075, p = 0.362). Yet, a significant interaction was
observed between competitive gaming and hours gaming (β6
= −.181, p = 0.044). To interpret this interaction, simple
slopes analyses were conducted, and the regions of
significance were identified using the Johnson-Neyman
(Johnson and Fay 1950; Bauer and Curran 2005)
4 The pattern of results remained the same when the interaction term
was determined by parental reports of children’s gaming.
5 In coding games as being violent or not, violent games included
titles ranging from mild cartoon violence such as Super Mario Bros.—
and titles with more graphic violence—such as games from the Halo,
Call of Duty, and Grand Theft Auto franchises. There was some
discussion regarding Minecraft (frequency: T1 = 16; T2 = 45). In the
reported analyses, Minecraft was not classified as a violent video game
(despite the game allowing players to fend off “zombies”). We also
reran the analyses with Minecraft coded as a violent video games: The
pattern of results remained the same in the externalizing problems
model, and in the prosocial behavior model a main effect of violent
gaming was observed, such that violent gaming at T1 was associated
with an increase in prosocial behavior.
6 The Johnson-Neyman Technique was performed using resources
provided by Preacher, Curran, & Bauer (http://quantpsy.org/interact/
Fig. 4 Interaction between competitive gaming and gaming frequency
predicting changes in prosocial behavior. Values to the right of the
vertical line represent cases where prosocial behavior differs across
groups, and the vertical line marks children who reported playing 8.64
h per week. On the x-axis, −0.5 represents children who reported
playing 2.87 h per week, 0 represents children who reported playing
the mean number of hours per week (4.9)
Specifically, slopes for three levels of competitive gaming
(−1, 0, and +1 SD; per Bauer and Curran 2005) were plotted
—see Fig. 4. The slopes for the lines reflecting low and mean
levels of competitive gaming were not significant; low t =
0.93, p = .352, mean t = −.079, p = .433. The high
competitive slope was significant, t = −2.01, p = .047. As marked
by the vertical line in the figure, competitive gaming was
therefore seen to negatively predict prosocial behavior at T2
only for those who played video games 0.92 standard
deviation hours above the mean (M = 4.9, SD = 4.07; thus, 8.82 h
per week). Thus, hours gaming at T1 predicted less prosocial
behavior at T2 only for those who both gamed more on
average than their peers and who tended to play video games
The goal of the present study was to provide insight into the
potential influences of playing video games on children’s
psychosocial development. Despite the importance of this
topic, few longitudinal studies have been conducted in this
field. Moreover, the little research among pre-adolescent
children has predominantly focused on gaming and
children’s externalizing problems. Moreover, while cooperative
and competitive gaming have become a recent focus of
attention, no studies have yet examined their potential
influences while taking into consideration the naturalistic
way they occur, that is, often in tandem. Thus, in contrast to
past work, this study employed a longitudinal design,
recruited pre-adolescent children, examined children’s
psychosocial across multiple domains, and simultaneously
explored both cooperative and competitive gaming.
Contrary to our expectations that gaming would predict
improvements in children’s externalizing, internalizing,
peer, and overall psychosocial problems, gaming frequency
was associated with increases in children’s internalizing
problems, and was not associated with other changes. We
also explored the potential relationship between gaming and
changes in hyperactivity and inattention, and in prosocial
behavior; no relationships were observed. Importantly, no
selection effects were observed as well; that is, psychosocial
health at the study’s first time point was not associated with
changes in gaming frequency. Likewise, children’s
preference for violent video games was neither associated with
changes in externalizing problems nor in prosocial
behavior. Finally, while neither cooperative nor competitive
gaming were associated with changes in prosocial behavior,
frequent competitive gaming among children who played
video games for approximately eight and a half hours or
more per week was associated with declines in prosocial
For video games, their potential negative influence on
children’s conduct is perhaps the chief concern among the
public and within the scientific community. Violent video
games in particular are widely seen as having a deleterious
influence on children’s conduct, giving rise to aggressive
behavior and discouraging prosocial behavior
et al. 2010)
. In this study, however, gaming as a general
activity, and violent video gaming more specifically, were
neither associated with a rise in children’s externalizing
problems nor with a decrease in prosocial behavior. Thus,
violent gaming had no influence in this study. This outcome
aligns this study with a minority of published work showing
no effect of violent gaming on anti- or pro-social behavior.
One potential reason for this may have to do with the
study’s sample; scant longitudinal studies have tested the
influence of violent video games among pre-adolescent
This outcome may have also been influenced by our
operationalizing violent gaming as a dichotomous variable.
This method lumped together games that were low and high
in violent content. Our procedure was motivated by the
young age of our sample; we expected children to have
difficulties rating the intensity and realism of gaming
violence. Indeed, such ratings would likely have been either
uninformative or a source of bias in our sample. This is
because, of the 138 games listed by children in our sample,
just seven titles were rated by the Pan European Game
Information board as being unsuitable for children below
the age of 16. The low prevalence of highly violent gaming
in our sample may have therefore made it more difficult to
observe an association between violent gaming and
antisocial outcomes. On the other hand, the observed outcome
may offer encouragement given that children who played
games with age-appropriate levels of violence did not
develop anti-social tendencies when compared to their peers
who played non-violent games.
It is important to consider that there was a dramatic
change in the prevalence of violent video game play at this
study’s second wave. By this study’s second wave, the
number of highly violent games listed by children tripled to
22, and the number of children listing a preference for
violent video games increased by nearly 50%. One
possibility for this shift is that violent content becomes
increasingly of interest to children as they develop. Violent content
could be an avenue for developing children to explore
mature themes such as life-and-death. Another possibility is
that because highly violent games are restricted to older
audiences, these games may also be designed as more
challenging and complex than many non-violent games.
Violent games may therefore be attractive for child gamers
looking for greater challenges to meet their growing
abilities. Finally, children’s interest in violent games may
remain constant across development, however their access
to violent games may change over the course of
development. A crucial factor to consider is therefore parental
(Nikken and Jansz 2006)
. As children get older
and gain more autonomy, parental involvement in what
their children play may wane. Thus, contrary to our
findings, violent gaming may be detrimental to children—
however, the younger children in our sample may have also
been protected from this risk by virtue of their lack of
interest in, skill with, or access to violent games. These are
important considerations for future research. Thus, the
development of children’s motives to play violent video
games, the role of these motives, and the role of parental
mediation are likely important mediating factors to consider
when investigating the effects of violent gaming in children
(Sweetser and Wyeth 2005)
Against our expectations, gaming frequency was
associated with an increase in internalizing problems, such as
anxiety and depressive symptoms. Notably, however, no
selection effect was observed in our study, thus it was not
the case that children experiencing heightened internalizing
problems were more likely to play video games the
following year. Internalizing problems seem like an important
domain for future research particularly considering how
gaming research has mostly focused on externalizing
problems such as aggression. Importantly, this significant
finding should also be interpreted with caution due to the
small size of the observed relationship. Still, our finding is
consistent with reports that excessive gaming relates to
heightened levels of depressive symptoms among
(Maras et al. 2015)
. Anxious and depressive
symptoms emerge in children who feel a lack of control over
. One possibility is that
frequent gaming at a young age trains children against
dealing with real world adversity. Because game worlds
provide clear rules and the ability to retry challenges the
moment they seem too daunting, real world challenges may
seem overwhelming to frequent child gamers. Several other
processes may also be at work here, however. Video games
are known to evoke negative emotions, and frustration in
(Lobel et al. 2014b)
; negative arousal and feelings
of incompetence experienced while gaming may transfer to
afterwards. Second, for children, the quality of positive
emotion experiences afforded by video games may be
inferior to the positive emotion experiences afforded by
other more traditional activities. Finally, playing video
games may have been associated with other negative
outcomes which themselves led to emotion problems. For
instance, heightened video game play may lead to poor
(Hastings et al. 2009)
(van den Eijnden et al. 2008)
. The observed
association between gaming and internalizing problems
may therefore be an indirect consequence of gaming being
associated with other maladaptive behaviors. Future studies
should therefore examine gaming’s relation to how children
perceive real world adversity; a more holistic approach that
examines the interplay between frequent gaming and other
socio-developmental processes also seems warranted.
Gaming was not associated with changes in hyperactivity
and inattention. To our knowledge, this is just the second
study to examine this hypothesis with a longitudinal design
(see Gentile et al. 2012)
. With regards to attentional skills, it
is possible that video games as a whole was too broad a
predictor. Indeed, video games offer a wide variety of
interactions and operate under a variety of reward
schedules. Regarding hyperactivity and inattention, it seems
relevant to distinguish video games based on the duration of
play per session intended by the designer, and perhaps the
speed and intensity of visual and auditory stimulation.
Indeed, while some games are designed to be played in
short bursts, others are designed for extensive sessions; and
while some games bombard the player’s senses and require
rapid inputs, others take a slower pace and allow players to
be idle for long periods (Fullerton 2014). Our study did not
distinguish between different types of video games, largely
because at the young age that we assessed children, there
was very little variability in the types of games children
played. But it may be that some game types may be
detrimental (such as games which constantly offer short-term
rewards), whereas others may be beneficial (such as action
video games that vary these reward schedules), and that
these effects may have cancelled each other out, even in our
limited sample. Coding games based on their cognitive load
and reward schedules poses several large challenges, for
example: specific titles may be highly variable in their
complexity because this may increase with player progress.
We therefore recommend future research to conceptualize
video games based on their attentional demands and their
reward schedules and to draw new hypotheses based on
these factors. Experimental designs seem particularly
suitable; this is because researchers can work with designers to
finely and objectively manipulate the specific features of
game titles that may give rise to attentional deficits or
(e.g. Anguera et al. 2013)
Finally, habitually playing competitive video games was
only associated with a decline in prosocial behavior among
children who played video games competitively for about 8
or more hours per week. This was found when controlling for
cooperative gaming, which often co-occurs with competitive
gaming, and which has been found to promote prosocial
(Gentile et al. 2009)
. This pattern may be due to the
fact that in multiplayer games competitive goals often seem
to take precedence over cooperative goals. In these games
cooperation is often merely a means to better compete against
an opposing team; thus, the overarching goal of play in these
games remains competition. Here again we stress the
importance of replication and of developing and using
measures that are sensitive to the variety of social dynamics
across different games. Given that many existing multiplayer
games allow players to choose roles with either greater focus
on cooperation or competition (e.g. that of a medic or a
striker), experimental studies could be of particular benefit.
This study’s limitations are important to consider. First, as
already discussed, this study examined the potential influence
of video games in a broad sense. Modern video games
encompass a highly diverse set of interactions
(Granic et al.
, and even games within the same genre may engage
players in diverse ways. We therefore stress the importance
of more granular tests of specific forms of gaming. Second,
to partly address this issue, this study also examined gaming
more specifically in terms of social dynamics. To do so, we
used unstandardized assessments, given there were no
validated options. That is, our cooperative, and competitive
gaming measures utilized single-item questions for their
evaluation. While this is in line with other recent studies in
(e.g. Przybylski and Mishkin 2016)
measures are preferred. This limitation is noteworthy
despite the fact that these questions were answered during an
interview session with trained experimenters. Third, we
collected data just 1 year apart from each other; this is a
relatively short term for child development. Finally, a total of
six models were run for relating gaming to the Strengths
and Difficulties Questionnaire, a further two models were run
to examine violent gaming, and another model was run to
examine changes in prosocial behavior. Given this multiple
testing, and the relatively small size of the betas that were of
significance, the findings in this study should be taken with
some caution and should be replicated before strong
conclusion can be made.
Video games did not seem to pose harm for most domains
of children’s psychosocial development. Parents should be
particularly attentive to potential increases in children’s
internalizing problems as a result of video game playing.
The deleterious effects of violent video game play remains a
highly debated topic, with this study not lending support for
the influence of violent gaming on externalizing problems
or on prosocial behavior. While cooperative gaming seems
unrelated to prosocial behavior in our sample, frequent
gamers who also tend to play competitively may be at risk
for behaving less prosocially. Finally, this field would
benefit greatly from validated measures that quantify or
categorize the types of social and emotional processes being
activated by different games and game types, and that
accurately measure the social environment of video game
Acknowledgements This study was funded by the Behavioural
Science Institute, Radboud University Nijmegen.
Authors’ Contributions A. L. was the lead author, and therefore
wrote and revised the manuscript. A. L. oversaw and performed data
collection; this means that A. L. managed the researchers who
collected data, and that he also collected data from participants. A. L.
performed all the analyses described in the manuscript; this means that
A. L. managed the data in this study, and authored and ran all scripts
used to analyze the data. R. E. and I. G. conceived of the study; this
means that they initiated this longitudinal research project. R. E. and I.
G. participated in the study’s design and coordination; this means that,
together with A. L., R. E. and I. G. were involved in the selection of
measures used in this study and in devising the data collection
procedure. R. E. and I. G. gave instrumental feedback on the manuscript;
as the thesis supervisors to A. L., R. E. and I. G. commented on and
provided edits to this manuscript at multiple stages. L. S. was
instrumental in the study’s recruitment and design; this study was a direct
follow-up to a previous study conducted by L. S., who was responsible
for recruiting and retaining the participants of this study, which
allowed for them to be recruited for this study. L. S. therefore also
helped design this study, having laid the groundwork for some of the
measures used here. L. S. was also actively involved in the writing of
this manuscript, providing important feedback on the manuscript. W.
B. provided expertise for data analysis and the interpretation of results.
W. B. was A. L.’s direct contact for statistical support on this project.
W. B. walked A. L. through the statistical background for the models
used in this study, provided A. L. with the necessary information for
installing and properly employing the R packages used for the
analyses, double-checked the outcomes of the study’s findings based on
the models used, and provided input for the proper interpretation of the
findings. All authors read and approved the final manuscript.
Compliance with Ethical Standards The experimenters complied
with the ethical standards for attaining and managing data from adult
and minor participants as are monitored by the Behavioural Science
Institute’s Ethical Review Board. Participants were informed as to their
rights as volunteer participants and were informed regarding who they
could contact if they felt their rights had been breached. No complaints
Conflict of Interest
The authors declare that they have no
comEthical Approval The study’s procedures were approved by the
Behavioural Science Institute’s Ethical Review Board under the
Radboud University. Protocol number: ECG 26062012.
Informed Consent Informed consent forms were attained from all
participants at both of this study’s time points. Parents provided
consent for the collection and use of both their own data and that of their
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted
use, distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
Adam Lobel is a Postdoctoral Fellow at the University of Geneva’s
Swiss Center for Affective Sciences. He attained his PhD at the
Behavioural Science Institute, where he was affiliated when the
research presented here was conducted. Adam’s research interests are
primarily focused on the effects of gaming on mental health and
emotion regulation skills.
Professor Rutger C. M. E. Engels is the president of the Trimbos
Institute, and Professor at the Behavioural Science Institute. His
research interests include developmental psychopathology, and in
particular, smoking and drinking habits and addiction in adolescent
Lisanne Stone is a clinical psychologist at Pro Persona, and a former
PhD at the Radboud University’s Behavioural Science Institute. Her
research interests include anxiety and depression in children, and the
psychometric quality of measurements used to assess these
William J. Burk is an Assistant Professor at the Developmental
Psychology at the Radboud University’s Behavioural Science Institute.
His research interests include the role of peers in alcohol use among
adolescents, statistical modeling, and psychometrics.
Professor Isabela Granic is the Chair of the Developmental
Psychopathology Department at the Radboud University’s Behavioural
Science Institute and the head of that department’s Games for
Emotional and Mental Health Lab. He research interests include
dynamic systems, and the effects of gaming on mental health.
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