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The effectiveness of a parental guide for prevention of problematic video gaming
in children: A public health randomized controlled intervention study
ELFRID KROSSBAKKEN
1
*, TORBJØRN TORSHEIM
1
, RUNE AUNE MENTZONI
1,2
, DANIEL LUKE KING
3
,
BJØRN BJORVATN
4,5
, INGJERD MEEN LORVIK
6
and STÅLE PALLESEN
1,5
1
Department of Psychosocial Science, University of Bergen, Bergen, Norway
2
KoRus-Øst, Innlandet Hospital Trust, Ottestad, Norway
3
School of Psychology, The University of Adelaide, Adelaide, Australia
4
Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
5
Norwegian Competence Center for Sleep Disorders, Haukeland University Hospital, Bergen, Norway
6
Treatment Center for Addictive Disorder, The Borgestad Clinic, Skien, Norway
(Received: June 23, 2017; revised manuscript received: September 30, 2017; second revised manuscript received: November 30, 2017;
accepted: December 3, 2017)
Background and aims: Excessive use of video games among children and adolescents is a growing concern. The aim
of this study was to investigate the effectiveness of a brief parental guide with advices and strategies for regulating
video gaming in children. Methods: A random sample of guardians of children between the age of 8–12 years old
(N=5,864) was drawn from the Norwegian Population Registry and equally randomized into an intervention and a
control condition. A parental guide based on clinical and research literature was distributed by postal mail to those in
the intervention condition. A 4-month follow-up survey comprising questions about problematic video gaming,
gaming behavior, sleep activity, and parental video game regulation behavior was administered. Results: Independent
t-tests revealed no significant differences between the two conditions (N=1,657, response rate 30.1%) on any
outcome measure. An ANOVA with planned comparisons showed that respondents who reported that they had read
and followed the parental guide reported more video game problems and used more parental mediation strategies than
those who did not read and follow the guide. Conclusions: We found no evidence for the effectiveness of the
psychoeducational parental guide on preventing problematic video gaming in children. However, the guide was read
and positively assessed by a significant proportion of guardians. Differences between those who studied the guide and
those who did not may indicate that parental guides are better aimed at providing important information to those who
already have problems rather than as a mean of primary prevention.
Keywords: problematic video gaming, parental guide, video game addiction
INTRODUCTION
Video gaming is a very prevalent pastime among children
and adolescents in the developed world. Studies suggest that
88% of all American youths between the age of 8–18 years
play video games at least occasionally (Gentile, 2009),
whereas 68.6% of male and 43.4% of female Norwegians
play video games on a weekly basis (Mentzoni et al., 2011).
In a representative German study of adolescents, it was
found that mean daily time spent gaming was 141 min
(Rehbein, Kleimann, & Mößle, 2010). However, far from all
individuals spending much time playing video games seem
to have problems because of this (Brunborg, Mentzoni, &
Frøyland, 2014). Such gamers are often denoted as highly
engaged (Charlton & Danforth, 2007) or enthusiastic
gamers (Griffiths & Meredith, 2009). Still, studies have
shown that some young people lose control over their game
playing behavior to such extent that it is associated with
significant problems, such as loneliness and social isolation,
lower academic achievement, depression, anxiety, and sleep
problems (Brunborg et al., 2014;Lemmens, Valkenburg, &
Peter, 2011;Mentzoni et al., 2011;Wenzel, Bakken,
Johansson, Götestam, & Øren, 2009). Problematic video
gaming is also recognized as a potential behavioral disorder,
similar to gambling disorder, which is often referred to as
video game addiction (Griffiths & Meredith, 2009;Hellman,
Schoenmakers, Nordstrom, & van Holst, 2013). This is also
reflected in the fifth and most recent version of the Diag-
nostic and Statistical Manual of Mental Disorders (DSM-5)
(2013) where “Internet gaming disorder”(IGD) was includ-
ed as a condition for further studies. Thus, despite the
ongoing discussion on how to conceptualize and assess the
phenomena (Griffiths et al., 2016;Kuss, Griffiths, & Pontes,
2017), there seems to be consensus about the need for
generating more knowledge about gaming disorder.
* Corresponding author: Elfrid Krossbakken; Department of Psy-
chosocial Science, University of Bergen, PO Box 7807, Bergen
5020, Norway; Phone: +47 55 58 86 48; Fax: +47 55 58 98 79;
E-mail: elfrid.krossbakken@uib.no
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use,
distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited.
© 2017 The Author(s)
FULL-LENGTH REPORT Journal of Behavioral Addictions
DOI: 10.1556/2006.6.2017.087
A recent Norwegian representative study of gamers (aged
16–74 years) found the prevalence of video game addiction
to be 1.4%, and of problematic gaming to be 7.3%. Addic-
tion and problems were inversely related to age (Wittek
et al., 2016). Another Norwegian study of eight graders
found the prevalence of video game addiction to be 4.2%
(Brunborg et al., 2013). A meta-analysis consisting of
studies published between 2001 and 2011 reported an
overall prevalence rate of 3.1% of video game addiction
among youths and young adults (Ferguson, Coulson, &
Barnett, 2011), suggesting that problematic video gaming
among young people represents a serious public health
concern that warrants intervention.
To date, several psychological (Li & Wang, 2013;
Pallesen, Lorvik, Bu, & Molde, 2015) and pharmacological
(Han, Hwang, & Renshaw, 2010;Han et al., 2009) treatment
studies have been conducted, with varying degrees of
success (Winkler, Dörsing, Rief, Shen, & Glombiewski,
2013). However, the prevention of problematic video game
playing has received much less attention in many countries,
despite many benefits that this approach may offer to
individuals at risk (King et al., 2017). Proposed primary
prevention strategies include: attention-switching (directing
youth to other extracurricular activities such as sports),
rationalization/education about the risks of online gaming
addiction, parental monitoring, restriction of game-related
resources (e.g., limiting access to games), and increased cost
of playing (Xu, Turel, & Yuan, 2012). For example, parental
monitoring has been found to have a positive effect on
children’s media use, sleep, academic and social behaviors
(Gentile, Reimer, Nathanson, Walsh, & Eisenmann, 2014),
and setting rules restricting screen time, and encouraging
physical activity have demonstrated efficacy in reducing
screen time in children (Carlson et al., 2010).
Problematic use of video games in early childhood has
been found to be a predictor for addictive behavior in
adolescence (Rehbein & Baier, 2013). However, there are
also studies indicating that the temporal stability of excessive
gaming may be low and resolve spontaneously (Rothmund,
Klimmt, & Gollwitzer, in press;Scharkow, Festl, & Quandt,
2014). Nevertheless, a logical target for prevention of pro-
blems related to video gaming would be parents of preteen
youth, given preteens’commonly premorbid status and their
greater receptivity, compared with teenage adolescents, to
parental involvement (Lwin, Stanaland, & Miyazaki, 2008;
Pasquier, 2001). One cost-efficientpreventionstrategywith
the possibility to reach a broad scope of parents of young
children might be distributing leaflets with psychoeducative
advice and recommendations intended to incorporate healthy
parental strategies. To the best of our knowledge, there have
not been previous studies investigating the effect of parental
guides on behavioral change, without any other reinforcers.
However, a recent review concerned with prevention of
Internet addiction called for more studies with interventions
aimed at parents and significant others of young children
(Vondráčková & Gabrhelík, 2016). Previous studies have also
shown that interventions, which focus on parental involve-
ment can yield behavioral change in children (Petrie, Bunn, &
Byrne, 2006). One study showed that a simple psychoedu-
cative intervention provided to parents had a positive effects
on family communication and awareness of adolescent
substance behavior (Spirito, Hernandez, Cancilliere, Graves,
& Barnett, 2015). Furthermore, parent–child communication
is, in addition to parental monitoring, regarded as one central
parental skill to focus on prevention of Internet addiction
(Vondráčková & Gabrhelík, 2016). In line with this, the
purpose of this study was to examine the effectiveness of
a parental guide for parents of children aged 8–12 years
constructed with the aim of preventing the onset or develop-
ment of problematic video gaming. Based on past research,
we predicted that equipping parents with prevention strategies
would have a beneficial effect on their children’svideo
gaming behavior, thereby reducing the risk of problematic
video gaming and strengthening positive outcomes in general
functioning.
METHODS
Participants and procedure
A random sample of 6,000 guardians of children between
the ages of 8–12 years old was drawn from the Norwegian
Population Registry (Figure 1). In all, 136 guardians were
drawn twice on the basis of having several children in our
desired age range (8–12 years), reducing our gross sample to
5,864. All guardians were then randomly assigned (using
www.randomizer.org) to either the intervention condition or
the control condition.
A brief parental guide on “how to regulate video game
behavior in children”was developed based on specific
clinical recommendations (Griffiths & Meredith, 2009;
King, Delfabbro, & Griffiths, 2010,2012;King, Delfabbro,
Griffiths, & Gradisar, 2012;Young, 2009), a treatment
manual for video game addiction (Pallesen et al., 2015),
factors identified as useful for preventing video game
problems (Xu et al., 2012), and clinical experience and
feedback from a reference group consisting of parents of
children in the age range of 8–12 years old. The guide is
presented in Appendix. Participants in the intervention
condition received the guide via postal mail in January
2015, along with an explanatory letter informing them that
they had been randomly selected to receive the guide. Four
months later, guardians in both conditions received a ques-
tionnaire along with an invitation to participate in the study
and a description of the formalities concerning confidenti-
ality and a statement that the data would be used exclusively
for research purposes. If the guardians had several children
between the ages of 8–12 years of age, they were instructed
to base their answers on the youngest child. The invitation
described the aim of the study as mapping out how parents
regulate gaming in children, and that they only had to return
one questionnaire to participate (single time point). Those
who did not respond received a reminder with a new
questionnaire approximately 2 months after the first survey.
In total, 1,762 guardians completed and returned the ques-
tionnaire (i.e., a response rate of 30.1%). In all, 11 cases
were duplicates and were excluded. We included cases
where the child had already turned 13 years old (N=86),
but excluded 82 cases that fell outside our desired age range.
A total of 12 cases were excluded because information
about the age of the child was missing. The final sample
Journal of Behavioral Addictions
Krossbakken et al.
(N=1,657) consisted of 831 in the intervention condition
and 826 in the control condition. Surveys were received
from 583 fathers and 1,022 mothers, 32 “others”
(e.g., grandparents, foster parents, etc.) concerning 759 girls
and 876 boys. The mean age of the children was 10.1 years.
After completing the questionnaire, the participants were
enrolled in a raffle, with the possibility of winning 50 gift
certificates (at 500 NOK apiece) and two iPad’s.
Measures
The survey comprised questions about demographics (the
child’s age and gender, whom they live with, and parents’
education level). Two items assessing time spent gaming
each day on weekdays and weekends were also included.
One item assessed whether guardians applied rules
constraining time spent playing video games (“completely
disagree,”“partially disagree/agree,”and “completely
agree”)(Carlson et al., 2010).
Video game problems. To measure video game pro-
blems, a Norwegian translation of the nine criteria pro-
posed for IGD found in DSM-5 (American Psychiatric
Association [APA], 2013) was administered. To detect
changes occurring within the study period, the time frame
was set to the past 3 months. To be able to detect nuances
in terms of gaming problems, the response alternatives
were aligned along a 5-point Likert scale ranging from
“completely disagree”(1) to “completely agree”(5). If
guardians agreed (“agree”or “completely agree”)onat
least five of the nine items (APA, 2013), the child was
categorized with “IGD.”Cronbach’sαfor this scale
was .90.
Guardians randomly drawn from the Norwegian
Population registry.
N= 6000
Guardians randomized to
the intervention group.
N= 3000
Received the
guide in themail
Received the
questionnaire
and a reminder
Returned the
questionnaire.
N=869
Final sample.
N= 831
Excluded
duplicates.
N= 1
Excluded due to
missing age.
N= 2
Excluded due to
wrong age.
N= 35
Guardians drawn
twice.
N= 33
Guardians randomized to
the intervention group.
N= 3000
No intervention
Received the
questionnaire
and a reminder
Returned the
questionnaire.
N=893
Final Sample.
N= 826
Excluded due to
wrong age.
N= 47
Excluded
duplicates.
N= 10
Excluded due to
missing age.
N= 10
Guardians drawn
twice.
N= 103
Figure 1. Flow chart depicting the procedure of the randomized controlled trial investigating a parental guide aimed at guardians of children
in the age of 8–12 years old
Journal of Behavioral Addictions
Effect of guide to prevent problematic gaming
Sleep problems and bedtime resistance. Sleep problems
and bedtime resistance were addressed using the “bedtime
resistance”subscale of the Child Sleep Habits Questionnaire
(CSHQ; six items) (Owens, Spirito, & McGuinn, 2000).
CSHQ is a screening instrument instructing guardians to
indicate on a 3-point scale how many days during the past
week, or during a “typical”week, certain sleep habits occur
(“usually”5–7 days, “sometimes”2–4 days, and “rarely”
0–1 day). We also asked respondents to indicate whether or
not the behavior was problematic (“yes”or “no”). Cron-
bach’sαfor bedtime resistance was .67.
Parental mediation. Parental mediation can be defined as
the various strategies parents use to control, supervise, and
interpret content (Warren, 2001) of video games to guide
and regulate gaming (Nikken & Jansz, 2006). To measure
parental mediation, we used a parental mediation scale
(Nikken & Jansz, 2006) that contained 13 items addressing
how often guardians apply certain parental strategies
regarding gaming. All items are answered on a 3-point
scale (“rarely or never,”“now and then,”and “often”). The
scale has three subdimensions: restrictive mediation (five
items, e.g., “monitoring gaming behavior”), co-playing
(three items, e.g., “playing together”), and active mediation
(five items, e.g., “telling games are just fantasy”). Cron-
bach’sαfor restrictive mediation, co-playing, and active
mediation were .78, .79, and .79, respectively.
Parental limit setting efficacy. Parental efficacy in terms
of perceived ability to set limits for the child’s screen time,
game time, and promote physical activities (Jago, Sebire,
Edwards, & Thompson, 2013) was assessed by three items.
The guardians were asked to indicate how certain they were
about managing limit setting in the aforementioned circum-
stances (e.g., “to limit time used by my child to play video
games”). The response alternatives range from 0 (complete-
ly certain to fail) to 100 (completely certain to manage) on
an 11-point scale.
Assessing general satisfaction with guide. For guardians
in the intervention condition, the questionnaire contained
one item that asked if they were aware of having received
the guide (“yes”or “no”). If they confirmed having received
it, they were asked to state if they: (a) studied the content of
the guide carefully, (b) tried to follow the recommendations,
and (c) thought the recommendations had been positive for
their child. These three items were answered along a 5-point
Likert scale ranging from strongly disagree (1) to strongly
agree (5).
Statistics
Analysis was conducted using SPSS, version 22. To
compare the two conditions, data were analyzed using
either χ
2
analyses (for nominal variables) or t-tests for
independent samples (for interval or ratio variables). Scale
mean scores were calculated if at least 75% of the items
were answered. An a priori power analysis setting the
effect size to small (d=0.20), αset to .05 (two-tailed),
power set to .80 showed that 788 subjects would be needed
to detect real group differences (Faul, Erdfelder, Lang, &
Buchner, 2007).
To further investigate contrasts between groups who had
dealt with the guide in different ways, a one-way ANOVA
with planned contrasts was conducted. Post hoc analysis
was carried out with Hochberg gt-2 corrections to account
for unequal sample sizes. Items asking if the guardians had
read the guide carefully and followed the recommendations
were used to group the guardians. Answering 1 or 2
(strongly disagree or disagree) at the 5-point Likert scale
was defined as denying to have read or followed the guide,
whereas answering 3–5(“neither agree nor disagree”to
“strongly agree”) was coded as complying to have read or
followed the guidelines. Four unique groups were created:
“not read, not followed”(a), “read, not followed”(b), “read,
followed”(c), and “remaining of the intervention group,”
which comprise guardians who denied having read the
guide, but complied to have followed the instructions, and
the one who did not notice the guide in the mail (d). These
were all compared with the control group, which had not
received the guide (e). The following planned contrasts were
conducted against the control group: “intervention group”
(a, b, c, d, vs. e), “received”(a, b, c, vs. e), “read”(b, c vs. e),
and “read and followed”(c vs. e).
Ethics
Returning the survey in a prepaid envelope was regarded as
consent. The guardians were informed that participation was
voluntary and that they could contact the researchers if they
wanted to withdraw from the study after returning the
questionnaire. It was also stated that to participate one just
had to return the completed questionnaire. The project was
approved by the Norwegian Center for Research Data
(project no. 41016).
RESULTS
χ
2
analyses revealed no significant difference between the
two conditions regarding age of child χ
2
(5, n=1,657) =
1.76, p=.88, sex χ
2
(1, n=1,635) =0.31, p=.58, type of
guardian (“mother,”“father,”and “other”) answering the
questionnaire χ
2
(2, n=1,637) =0.04, p=.35, whom the
child lived with χ
2
(5, n=1,657) =3.64, p=.60, the edu-
cation level of the father χ
2
(7, n=1,657) =9.64, p=.21, or
education level of the mother χ
2
(7, n=1,657) =8.60,
p=.28. The answers of 77 guardians (4.8%, 95%
CI =3.7%–5.8%) equally distributed between the two con-
ditions χ
2
(1, n=1,613) =0.03, p=.87 suggested that their
child could be categorized with IGD.
In terms of potential effects of the guide, no significant
difference was observed between the conditions on any of
the outcome measures (Table 1).
Of the guardians who received the guide, 73.4%
(n=604) reported that they were aware of having received
it. Furthermore, 63.4% (n=388) agreed to have read and
studied the content carefully and 49.4% (n=298) agreed
that they tried to follow the recommendations in the guide.
Furthermore, 32.6% (n=197) of the guardians agreed that
the guidelines had had a positive impact on their child
(Table 2).
Comparing the different groups of participant (see
Table 3for distribution) against the control group
revealed significant differences regarding video game
Journal of Behavioral Addictions
Krossbakken et al.
problems, restrictive and active mediation, and parental
efficacy concerning screen time and physical activity
(Table 4). The post hoc analysis showed that the signifi-
cant differences mostly occurred between different sub-
groups within the intervention group where those who
read and followed the guide reported more gaming pro-
blems (p<.05) and used more restrictive (p<.01) and
active mediation strategies(p<.05) than the other sub-
groups compared with the control group. Those who
chose not to read or followed the guide reported less-
restrictive mediation strategies than the control group
(p<.01). Furthermore, 29 of the 37 guardians in the
intervention group who suggested that their child could
be categorized with IGD was located in the subgroup
“read and followed,”one was located in the subgroup
“read, not followed,”seven in the subgroup “remaining of
intervention group,”andzerointhe“did not read, did
not follow.”There were no significant age differences
between the subgroups of participants.
DISCUSSION
The aim of this study was to investigate the effectiveness of
a parental guide for gaming activity in a randomized sample
of guardians of children between the ages of 8–12 years.
Receiving the guide did not produce any behavioral effect
either in guardian or child on any of the outcome measures.
The lack of effects occurred despite the fact that a significant
proportion of guardians in the intervention condition tried to
follow the guidelines and assessed them as having a positive
impact on their child. Further investigation revealed that the
guardians who read and followed the guide reported more
video game problems in their children, and used more
restrictive and active mediation strategies than those who
did not read the guide. The latter group also used less-
restrictive mediation strategies compared with the control
group.
The lack of effect of the guide might be due to several
reasons. One possible explanation might be that the time
Table 1. Results of t-test and descriptive statistics for the outcome measures by the two conditions of guardians of children between the
age of 8–13
Condition
95% CI for mean
difference
Intervention Control
Outcome measures MSDnMSDn t dfpd
Video game problems 1.95 0.75 800 1.90 0.77 813 −0.12, 0.03 −1.16 1611 .25 −0.06
Child sleep problems 1.96 0.12 677 1.96 0.11 675 −0.01, 0.01 0.19 1350 .85 0.01
Bedtime resistance 1.11 0.23 767 1.11 0.24 728 −0.02, 0.03 0.14 1493 .89 0.08
Game time weekdays 79.55 72.60 784 78.42 76.63 787 −8.52, 6.25 −0.30 1569 .76 −0.02
Game time weekends 138.79 101.26 788 139.07 106 791 −9.96, 10.51 0.05 1574.23 .96 0.00
Time restriction 2.47 0.62 803 2.44 0.64 812 −0.09, 0.03 −0.95 1613 .34 −0.05
Restrictive mediation 2.08 0.51 795 2.10 0.51 807 −0.03, 0.07 0.66 1600 .51 0.03
Co-playing mediation 1.58 0.48 783 1.62 0.50 802 −0.02, 0.08 1.30 1583 .20 0.07
Active mediation 1.85 0.49 794 1.83 0.51 808 −0.07, 0.03 −0.91 1600 .37 −0.05
Parental efficacy
screen time
90.70 2.07 827 91.46 20.75 818 −1.24, 2.77 0.75 1643 .45 0.04
Parental efficacy
gaming
93.88 18.26 801 93.78 19.79 806 −1.96, 1.76 −0.10 1605 .91 0.00
Parental efficacy
activity
96.08 18.87 826 95.98 19.36 811 −1.96, 1.74 −0.12 1635 .91 −0.01
Note. Video game problems range from 1 (“completely disagree”)to5(“completely agree”). Child sleep problems range from 1 (“yes”)to2
(“no”). Bedtime resistance ranges from 1 (“rarely”)to3(“usually”). Time restriction ranges from 1 (“completely disagree”)to3(“completely
agree”). Restrictive, co-playing, and active mediation range from 1 (“rarely or never”)to3(“often”). Parental efficacy ranges from 0
(“completely certain to fail”) to 100 (“completely certain to manage”). Game time is reported in minutes per day. M=mean; SD =standard
deviation; CI: confidence interval.
Table 2. Assessment of a parental guide on video game usage by guardians in the intervention condition
Question
Disagree Neither agree nor disagree Agree
n%n%n%
“I have read and studied the content of the guide thoroughly”89 14.5 135 22.1 388 63.4
“I have tried to follow the advice/recommendation from the guide”68 11.3 237 39.3 298 49.4
“I think the advice from the guide has had an positive impact on my child”42 7.0 364 60.4 197 32.6
Note: Categories have been merged. Disagree: “completely disagree”and “disagree;”Neither agree nor disagree: “neither agree nor
disagree;”Agree: “completely agree”and “agree.”
Journal of Behavioral Addictions
Effect of guide to prevent problematic gaming
Table 3. Distribution of the different subgroups of guardians and the control group
“Not read, not followed”(a) “Read, not followed”(b) “Read, followed”(c) “Remaining of the intervention group”(d) Control group (e)
Outcome measures nMean SD n Mean SD n Mean SD n Mean SD n Mean SD
Video game problems 41 1.64 0.60 22 2.24 0.76 480 2.00 0.78 250 1.87 0.69 813 1.90 0.77
Child sleep problems 38 1.99 0.03 20 1.95 0.13 404 1.96 0.13 205 1.96 0.10 675 1.96 0.11
Bedtime resistance 41 1.10 0.21 22 1.14 0.25 454 1.10 0.22 238 1.11 0.23 728 1.11 0.24
Game time weekdays 40 70.50 46.83 22 103.18 95.25 473 78.28 73.83 243 82.02 71.60 787 78.42 76.63
Game time weekends 40 121.10 105.96 22 149.32 112.68 475 141.42 101.04 245 137.02 100.31 791 139.07 106.00
Time restriction 41 2.44 0.74 21 2.14 0.655 481 2.49 0.59 251 2.45 0.66 812 2.44 0.64
Restrictive mediation 41 1.75 0.46 22 1.90 0.56 477 2.14 0.48 249 2.03 0.53 807 2.09 0.51
Co-playing mediation 40 1.45 0.49 22 1.65 0.56 472 1.58 0.47 243 1.60 0.49 802 1.62 0.50
Active mediation 41 1.64 0.50 22 1.68 0.45 477 1.90 0.47 248 1.81 0.51 808 1.83 0.51
PE screen time 43 95.81 18.28 22 81.82 23.43 490 90.75 20.57 259 90.35 21.01 818 91.47 20.75
PE gaming 41 97.32 16.58 22 87.73 21.14 480 93.56 18.30 250 94.28 18.27 806 93.78 19.79
PE physical activity 43 98.37 21.37 22 86.82 21.46 488 96.23 18.85 260 96.02 18.33 811 96.02 19.14
Note. Video game problems range from 1 (“completely disagree”)to5(“completely agree”). Child sleep problems range from 1 (“yes”)to2(“no”). Bedtime resistance ranges from 1 (“rarely”)to3
(“usually”). Time restriction ranges from 1 (“completely disagree”)to3(“completely agree”). Restrictive, co-playing, and active mediation range from 1 (“rarely or never”)to3(“often”). Parental
efficacy ranges from 0 (“completely certain to fail”) to 100 (“completely certain to manage”). Game time is reported in minutes per day. M: mean; SD: standard deviation.
Table 4. Result of a one-way ANOVA with planed contrast and ad hoc test with Hochberg gt-2 corrections showing comparisons with the control group
“Intervention group”“Received”“Read”“Read and followed”
Outcome measures Fdfp Fdf p FdfpF df p Post hoc
Video game problems 0.40 1601 .53 0.68 1601 .41 6.46 1601 .01* 5.03 1601 .03* a <b*, a <c*
Child sleep problems 0.31 41.07 .58 0.21 30.70 .65 0.24 24.17 .63 0.48 751.43 .49
Bedtime resistance 0.07 1478 .79 0.05 1478 .83 0.23 1478 .63 0.51 1478 .48
Game time weekdays 0.76 1560 .38 0.60 1560 .44 2.06 1560 .15 0.00 1560 .98
Game time weekends 0.05 1568 .82 0.03 1568 .86 0.28 1568 .60 0.15 1568 .70
Time restriction 1.26 77.51 .27 1.60 60.32 .21 2.66 25.70 .12 2.03 1080.58 .15
Restrictive mediation 13.12 1591 .00** 11.88 1591 .001** 1.73 1591 .19 2.27 1591 .13 a <c**, a <d**, a <e**
Co-playing mediation 1.47 1574 .23 1.41 1574 .24 0.00 1574 .99 1.76 1574 .19
Active mediation 3.66 1591 .06 3.55 1591 .06 0.49 1591 .49 5.61 1591 .02* a <c*
PE screen time 1.26 1627 .26 1.03 1627 .31 4.77 1627 .03* 0.36 1627 .55 ns
PE gaming 0.15 1594 .70 0.25 1594 .62 2.06 1594 .15 0.04 1594 .84
PE physical activity 1.18 1619 .28 1.42 1619 .23 4.14 1619 .04* 0.05 1619 .82 ns
Note. Video game problems range from 1 (“completely disagree”)to5(“completely agree”). Child sleep problems range from 1 (“yes”)to2(“no”). Bedtime resistance ranges from 1 (“rarely”)to3
(“usually”). Time restriction ranges from 1 (“completely disagree”)to3(“completely agree”). Restrictive, Co-playing and Active mediation range from 1 (“rarely or never”)to3(“often”). Parental
efficacy ranges from 0 (“completely certain to fail”) to 100 (“completely certain to manage”). Game time is reported in minutes per day. Ad hoc test results refer to the following subgroups a =did not
read, not follow, b =read, did not follow, c =read and follow, d =remaining of intervention, and e =control. ANOVA: analysis of variance; M: mean; SD: standard deviation; ns: not siginficant.
*p<.05. **p<.01.
Journal of Behavioral Addictions
Krossbakken et al.
span of 4 months between the intervention and the survey is
too short to generate any change in guardian or child
behavior as the guide consisted of several specific pieces
of advice regarding behavioral change. According to the
stages of change model, both contemplation and prepara-
tion, which alone typically may take 3–6 months, are stages
that have to be passed before reaching the action stage
(Prochaska, DiClemente, & Norcross, 1992). Conversely,
another explanation for the lack of effects may be that the
time span of 4 months between the intervention and out-
come assessment is too long to produce any change without
any reminder of the information in between. In our sample,
most of the parents who read the guide reported to have
followed the guidelines. However, we do not have any
information describing what kind of specific advice they
followed and for how long period of time they followed the
advice. Accordingly, some guardians might have tried the
strategies briefly, and given up after a short period of time.
Another possible reason for lack of effects is that the guide
failed to be relevant for the guardians who received it. In our
sample, the average levels of perceived video game problems
and sleep problems in both conditions were overall very low.
In addition, guardians in both conditions reported high scores
on parental efficacy, and guardians in both conditions reported
having enforced time restrictions regarding gaming. Hence, a
ceiling effect might have been in play (Cozby & Bates, 2013),
which may indicate that most guardians already were setting
sensible limits concerning their children’s gaming. Still, many
of the parents read the guide and the overall evaluation was
positive. However, this might suggest that there is a demand
for education materials concerning children’s use of video
games and that further investigation is needed to examine in
detail what information is useful. A third possibility for lack of
effects is that the outcome measures lacked sensitivity or
relevance to measure effects of this intervention. However,
care was taken to select outcome measures deemed relevant
for the issue at stake. Still, specific questions related to
compliance with each specific piece of advice in the guide
might have had higher sensitivity in terms of potential effects
(Kazdin & Nock, 2003).
Even though the parents on average reported few pro-
blems related to video games, 4.8% reported that their child
fulfilled at least five of the nine criteria for problematic video
gaming from the DSM-5 (APA, 2013). This is in line with
previous research that has shown that most gamers do not
have any problems related to video games (Brunborg et al.,
2013,2014). As noted earlier, there was no significant
difference between the conditions on any outcome measure.
However, within the intervention condition, the majority of
parents with children who could be categorized with IGD
reported to have read and followed the guidelines. Further-
more, there was a significant difference between guardians
who read and studied the guide compared with those who
did not, in terms of video game problems and parental
mediation. In line with previous research, the increased use
of restrictive and active parental mediation strategies might
indicate that these kind of mediations are instituted more
frequently after the problem occurs (Nikken & Jansz, 2006;
Xu et al., 2012). This difference might indicate a selection
bias where those who already experience some problems
regarding gaming behavior in their children were compelled
to study the information more thoroughly. Thus, such kinds
of interventions might be effective in spreading information
to families who already have challenges with gaming.
Parents of children with or without challenges with gaming
might possibly require different information packages to
meet their interests and level of needs. A recent review of
prevention of Internet addiction (Vondráčková & Gabrhelík,
2016) concluded with the need for targeting at-risk popula-
tions and their network of support (e.g., guardians and
teachers). Our findings seem to support this statement,
indicating that guardians with concerns regarding their
children’s gaming will be more attentive to relevant infor-
mation. Comparing our findings with previous studies of
psychoeducative interventions, we find that other interven-
tions seem to offer other supportive factors as well as written
materials (e.g., personal contact with health professionals,
group activities, etc.) (Bai, Wang, Yang, & Niu, 2015;
Hemdi & Daley, 2017). The lack of supplementary sup-
portive elements may explain why this study had such small
impact. Further studies might investigate the possible effect
of written advice to guardians whose children already are
experiencing problems with video games, and also investi-
gate other means (e.g., school-based interventions) to pre-
vent problematic gaming from occurring in children and
adolescents.
One limitation of this study is the lack of a pretest, which
precluded us from investigating preintervention differences
between the conditions, and changes occurring from before
to after the introduction of the written material. Random
assignment and a large sample size, however, will increase
the likelihood of equivalence between the conditions in a
post-test only design (Kazdin, 2010), making the conditions
eligible for comparison, especially in the case of similar
response rates. Furthermore, our preliminary analysis
showed the conditions to be homogeneous on all measures,
making it fair to assume that the results presented in this
article could be attributed to the efficacy of the guide. It
should also be mentioned that the number of participants in
the different groups in the planned contrast varied, causing
variations in the statistical power of these analyses.
CONCLUSIONS
This is the first study to investigate the effects of written
preventive material regarding video game problems in a
large general population sample. Lack of effects may be
attributed to a short time span to outcome assessment, no
repetition/reminder of the information between intervention
and survey, ceiling effects, and lack of specificity between
the advice given and the outcome measures. Those who read
and followed the guide reported more problems with video
games in their children than those who did not study the
guide, which might suggest that such interventions might be
more beneficial for those in specific need of help regarding
this issue.
Funding sources: This project was funded by the Norwe-
gian Research Council.
Journal of Behavioral Addictions
Effect of guide to prevent problematic gaming
Authors’contribution: SP, IML, RAM, and DLK stood for
the conception and design of the work. All authors contrib-
uted to the acquisition, analysis, and interpretation of data.
EK drafted the work. All authors revised the work critically
in terms of important intellectual content. They also
approved the final version and are accountable for all
aspects of the work in terms of ensuring that questions
related to the accuracy or integrity of any part of the work
were appropriately investigated and resolved.
Conflict of interest: No competing financial interests exist.
REFERENCES
American Psychiatric Association [APA]. (2013). Diagnostic and
statistical manual of mental disorders (DSM-5
®
). Washington,
DC: American Psychiatric Association.
Bai, G.-N., Wang, Y.-f., Yang, L., & Niu, W.-Y. (2015). Effec-
tiveness of a focused, brief psychoeducation program for
parents of ADHD children: Improvement of medication adher-
ence and symptoms. Neuropsychiatric Disease and Treatment,
11, 2721. doi:10.2147/NDT.S88625
Brunborg, G. S., Mentzoni, R. A., & Frøyland, L. R. (2014). Is
video gaming, or video game addiction, associated with de-
pression, academic achievement, heavy episodic drinking, or
conduct problems? Journal of Behavioral Addictions, 3(1), 27–
32. doi:10.1556/JBA.3.2014.002
Brunborg, G. S., Mentzoni, R. A., Melkevik, O. R., Torsheim, T.,
Samdal, O., Hetland, J., Andreassen, C. S., & Palleson, S.
(2013). Gaming addiction, gaming engagement, and psycho-
logical health complaints among Norwegian adolescents.
Media Psychology, 16(1), 115–128. doi:10.1080/15213269.
2012.756374
Carlson, S. A., Fulton, J. E., Lee, S. M., Foley, J. T., Heitzler, C., &
Huhman, M. (2010). Influence of limit-setting and participation
in physical activity on youth screen time. Pediatrics, 126(1),
e89–e96. doi:10.1542/peds.2009-3374
Charlton, J. P., & Danforth, I. D. (2007). Distinguishing addiction
and high engagement in the context of online game playing.
Computers in Human Behavior, 23(3), 1531–1548. doi:10.
1016/j.chb.2005.07.002
Cozby, P. C., & Bates, S. C. (2013). Methods in behavioral
research (11th ed.). New York, NY: McGrawHill.
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*
Power 3: A flexible statistical power analysis program for
the social, behavioral, and biomedical sciences. Behavior
Research Methods, 39(2), 175–191. doi:10.3758/BF03193146
Ferguson, C. J., Coulson, M., & Barnett, J. (2011). A meta-analysis
of pathological gaming prevalence and comorbidity with men-
tal health, academic and social problems. Journal of Psychiat-
ric Research, 45(12), 1573–1578. doi:10.1016/j.jpsychires.
2011.09.005
Gentile, D. (2009). Pathological video-game use among youth ages
8 to 18: A national study. Psychological Science, 20(5), 594–
602. doi:10.1111/j.1467-9280.2009.02340.x
Gentile, D., Reimer, R. A., Nathanson, A. I., Walsh, D. A., &
Eisenmann, J. C. (2014). Protective effects of parental moni-
toring of children’s media use: A prospective study. JAMA
Pediatrics, 168(5), 479–484. doi:10.1001/jamapediatrics.
2014.146
Griffiths, M. D., & Meredith, A. (2009). Videogame addiction and
its treatment. Journal of Contemporary Psychotherapy, 39(4),
247–253. doi:10.1007/s10879-009-9118-4
Griffiths, M. D., Van Rooij, A. J., Kardefelt-Winther, D., Starcevic,
V., Király, O., Pallesen, S., Müller, K., Dreier, M., Carras, M.,
Prause, N., King, D. L., Aboujaoude, E., Kuss, D. J., Pontes,
H. M., Lopez Fernandez, O., Nagygyorgy, K., Achab, S.,
Billieux, J., Quandt, T., Carbonell, X., Ferguson, C. J., Hoff,
R. A., Derevensky, J., Haagsma, M. C., Delfabbro, P.,
Coulson, M., Hussain, Z., & Demetrovics, Z. (2016). Working
towards an international consensus on criteria for assessing
Internet gaming disorder: A critical commentary on Petry et al.
(2014). Addiction, 111(1), 167–175. doi:10.1111/add.13057
Han, D. H., Hwang, J. W., & Renshaw, P. F. (2010). Bupropion
sustained release treatment decreases craving for video games
and cue-induced brain activity in patients with Internet video
game addiction. Experimental and Clinical Psychopharmacol-
ogy, 18(4), 297–304. doi:10.1037/a0020023
Han, D. H., Lee, Y. S., Na, C., Ahn, J. Y., Chung, U. S., Daniels,
M. A., Haws, C. A., & Renshaw, P. F. (2009). The effect of
methylphenidate on Internet video game play in children
with attention-deficit/hyperactivity disorder. Comprehensive
Psychiatry, 50(3), 251–256. doi:10.1016/j.comppsych.2008.
08.011
Hellman, M., Schoenmakers, T. M., Nordstrom, B. R., & van
Holst, R. J. (2013). Is there such a thing as online video game
addiction? A cross-disciplinary review. Addiction Research &
Theory, 21(2), 102–112. doi:10.3109/16066359.2012.693222
Hemdi, A., & Daley, D. (2017). The effectiveness of a psychoe-
ducation intervention delivered via WhatsApp for mothers of
children with Autism Spectrum Disorder (ASD) in the King-
dom of Saudi Arabia: A randomized controlled trial. Child:
Care, Health and Development, 43(6), 933–941. doi:10.1111/
cch.12520
Jago, R., Sebire, S. J., Edwards, M. J., & Thompson, J. L. (2013).
Parental TV viewing, parental self-efficacy, media equipment
and TV viewing among preschool children. European Journal
of Pediatrics, 172(11), 1543–1545. doi:10.1007/s00431-013-
2077-5
Kazdin, A. E. (2010). Research design in clinical psychology (4th
ed.). Boston, MA: Pearson Education Company.
Kazdin, A. E., & Nock, M. K. (2003). Delineating mechanisms of
change in child and adolescent therapy: Methodological issues
and research recommendations. Journal of Child Psychology
and Psychiatry, 44(8), 1116–1129. doi:10.1111/1469-7610.
00195
King,D.L.,Delfabbro,P.H.,Doh,Y.Y.,Wu,A.M.,Kuss,D.J.,
Pallesen, S., Mentzoni, R., Carragher, N., & Sakuma, H. (2017).
Policy and prevention approaches for disordered and hazardous
gaming and Internet use: An international perspective. Preven-
tion Science, 1–17. doi:10.1007/s11121-017-0813-1
King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2010). Cognitive
behavioral therapy for problematic video game players: Con-
ceptual considerations and practice issues. Journal of
CyberTherapy and Rehabilitation, 3(3), 261–273. Retrieved
from http://journalofcybertherapy.webs.com/332010.htm
King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2012). Clinical
interventions for technology-based problems: Excessive
Journal of Behavioral Addictions
Krossbakken et al.
Internet and video game use. Journal of Cognitive Psychother-
apy, 26(1), 43–56. doi:10.1891/0889-8391.26.1.43
King, D. L., Delfabbro, P. H., Griffiths, M. D., & Gradisar, M.
(2012). Cognitive-behavioral approaches to outpatient treat-
ment of Internet addiction in children and adolescents. Journal
of Clinical Psychology, 68(11), 1185–1195. doi:10.1002/
jclp.21918
Kuss, D. J., Griffiths, M. D., & Pontes, H. M. (2017). Chaos and
confusion in DSM-5 diagnosis of Internet gaming disorder:
Issues, concerns, and recommendations for clarity in the field.
Journal of Behavioral Addictions, 6(2), 103–109. doi:10.1556/
2006.5.2016.062
Lemmens, J. S., Valkenburg, P. M., & Peter, J. (2011). Psychoso-
cial causes and consequences of pathological gaming. Com-
puters in Human Behavior, 27(1), 144–152. doi:10.1016/j.
chb.2010.07.015
Li, H., & Wang, S. (2013). The role of cognitive distortion in
online game addiction among Chinese adolescents. Children
and Youth Services Review, 35(9), 1468–1475. doi:10.1016/j.
childyouth.2013.05.021
Lwin, M. O., Stanaland, A. J., & Miyazaki, A. D. (2008).
Protecting children’s privacy online: How parental media-
tion strategies affect website safeguard effectiveness. Jour-
nal of Retailing, 84(2), 205–217. doi:10.1016/j.jretai.2008.
04.004
Mentzoni, R. A., Brunborg, G. S., Molde, H., Myrseth, H.,
Skouverøe, K. J. M., Hetland, J., & Pallesen, S. (2011).
Problematic video game use: Estimated prevalence and asso-
ciations with mental and physical health. Cyberpsychology,
Behavior, and Social Networking, 14(10), 591–596. doi:10.
1089/cyber.2010.0260
Nikken, P., & Jansz, J. (2006). Parental mediation of children’s
videogame playing: A comparison of the reports by parents and
children. Learning, Media and Technology, 31(2), 181–202.
doi:10.1080/17439880600756803
Owens, J. A., Spirito, A., & McGuinn, M. (2000). The Children’s
Sleep Habits Questionnaire (CSHQ): Psychometric properties
of a survey instrument for school-aged children. Sleep, 23(8),
1–9. doi:10.1093/sleep/23.8.1d
Pallesen, S., Lorvik, I. M., Bu, E. H., & Molde, H. (2015). An
exploratory study investigating the effects of a treatment
manual for video game addiction. Psychological Reports,
117(2), 490–495. doi:10.2466/02.PR0.117c14z9
Pasquier, D. (2001). Media at home: Domestic interactions and
regulation. In S. Livingstone & M. Bovill (Eds.), Children and
their changing media environment: A European comparative
study (pp. 161–177). Mahwah, NJ: Lawrence Erlbaum
Associates.
Petrie, J., Bunn, F., & Byrne, G. (2006). Parenting programmes for
preventing tobacco, alcohol or drugs misuse in children <18: A
systematic review. Health Education Research, 22(2), 177–
191. doi:10.1093/her/cyl061
Prochaska, J. O., DiClemente, C. C., & Norcross, J. C. (1992). In
search of the structure of change. In Y. Klar, J. D. Fisher, J. M.
Chinsky, & A. Nadler (Eds.), Self change (pp. 87–114).
New York, NY: Springer. doi:10.1007/978-1-4612-2922-3_5
Rehbein, F., & Baier, D. (2013). Family-, media-, and school-
related risk factors of video game addiction. A 5 year longitu-
dinal study. Journal of Media Psychology, 25(3), 118–128.
doi:10.1027/1864-1105/a000093
Rehbein, F., Kleimann, M., & Mößle, T. (2010). Prevalence and
risk factors of video game dependency in adolescence:
Results of a German nationwide survey. Cyberpsychology,
Behavior, and Social Networking, 13(3), 269–277. doi:10.
1089/cyber.2009.0227
Rothmund, T., Klimmt, C., & Gollwitzer, M. (in press). Low
temporal stability of excessive video game use in German
adolescents. Journal of Media Psychology. doi:10.1027/1864-
1105/a000177
Scharkow, M., Festl, R., & Quandt, T. (2014). Longitudinal
patterns of problematic computer game use among adolescents
and adults—A 2-year panel study. Addiction, 109(11), 1910–
1917. doi:10.1111/add.12662
Spirito, A., Hernandez, L., Cancilliere, M. K., Graves, H., &
Barnett, N. (2015). Improving parenting and parent-adolescent
communication to delay or prevent the onset of alcohol and
drug use in young adolescents with emotional/behavioral dis-
orders: A pilot trial. Journal of Child & Adolescent Substance
Abuse, 24(5), 308–322. doi:10.1080/1067828X.2013.829013
Vondráčková, P., & Gabrhelík, R. (2016). Prevention of Internet
addiction: A systematic review. Journal of Behavioral Addic-
tions, 5(4), 568–579. doi:10.1556/2006.5.2016.085
Warren, R. (2001). In words and deeds: Parental involvement and
mediation of children’s television viewing. The Journal of
Family Communication, 1(4), 211–231. doi:10.1207/S1532
7698JFC0104_01
Wenzel, H., Bakken, I., Johansson, A., Götestam, K., & Øren, A.
(2009). Excessive computer game playing among Norwegian
adults: Self-reported consequences of playing and association
with mental health problems. Psychological Reports, 105(3),
1237–1247. doi:10.2466/PR0.105.F.1237-1247
Winkler, A., Dörsing, B., Rief, W., Shen, Y., & Glombiewski, J. A.
(2013). Treatment of Internet addiction: A meta-analysis.
Clinical Psychology Review, 33(2), 317–329. doi:10.1016/j.
cpr.2012.12.005
Wittek, C. T., Finserås, T. R., Pallesen, S., Mentzoni, R. A., Hanss,
D., Griffiths, M. D., & Molde, H. (2016). Prevalence and
predictors of video game addiction: A study based on a national
representative sample of gamers. International Journal of
Mental Health and Addiction, 14(5), 672–686. doi:10.1007/
s11469-015-9592-8
Xu, Z., Turel, O., & Yuan, Y. (2012). Online game addiction
among adolescents: Motivation and prevention factors. Euro-
pean Journal of Information Systems, 21(3), 321–340.
doi:10.1057/ejis.2011.56
Young, K. (2009). Understanding online gaming addiction and
treatment issues for adolescents. The American Journal of Family
Therapy, 37(5), 355–372. doi:10.1080/01926180902942191
Journal of Behavioral Addictions
Effect of guide to prevent problematic gaming
APPENDIX: TRANSLATION OF THE GUIDELINES
•Gaming devices and computers should be located in
common rooms such as the living room.
•The bedroom of the child should be free of electronic
media devices, such as PC, TV, video games, tablets,
and cell phones.
•Avoid letting the child play video games during the last
hour before bedtime.
•Support and encourage the child to engage in physical
activity. For instance, you can take the child hiking;
enroll the child in a sports club or the like.
•Stimulate your child to spend time on other hobbies
and interests other than video games.
•Have rules that prohibit the child from prioritizing
video games over homework and family meals.
•Do not let the child play during meals.
•Do something pleasurable together with the child at
least one or two times per week, for instance cooking,
go to the cinema or visit a water park.
•Assess whether the game content is appropriate for the
age of your child. Be aware of the fact that some online
games can put your child in contact with others,
including adults, who might have a negative influence
on your child.
•Gather information about the games your child plays.
You might also play together with the child. Explain
the difference between fantasy and reality in the games.
•You might choose games that foster knowledge and
skills for your child.
•To promote a beneficial dialogue with your child about
video games, allow your child to tell you about a
favorite game and explain to you why this game, in
particular, is his/her favorite.
•Apply limits to regulate how much your child is
allowed to play, for instance, 1 hr/day for children,
and 2 hr/day for teenagers. During weekends or holi-
days, game time can be increased to 1–3 hr/day.
•Communicate openly with your child if you think that
he/she plays to avoid difficult thoughts or feelings.
•Create opportunities for the child to spend time with
others. Let your child invite friends over to play video
games, or do other activities together.
•Praise your child for doing homework and other duties
before playing video games.
•Supervise how much money the child spends on
equipment, breaking obstacles, leveling up or the like
in games.
•You might discuss with other parents and compose
common rules for video games.
•If your child spends a great deal of time home alone,
you might consider carefully whether you need to
restrict your child’s access to the Internet, e.g., by
applying router access restrictions.
•Have 1 or 2 days per week without video games.
•Be conscious of yourself as a role model for your child.
For instance, you might avoid sending text messages or
be online during meals, and do not play video games in
the timeframe when the child is prohibited from
playing.
•Inform your child clearly about the rules you will put
into practice regarding video games. If possible, in-
clude the child in a discussion about how the rules
should be.
•Be prepared to confiscate video games and/or gaming
consoles for a day or a weekend if the child violates the
rules repeatedly.
•Pay attention to how much your child plays and ensure
you have access to passwords used by the child to play
games online.
Journal of Behavioral Addictions
Krossbakken et al.
