- Email: [email protected]
Video game use and problem behaviors in boys with autism spectrum disorders
Research in Autism Spectrum Disorders 7 (2013) 316–324
Contents lists available at SciVerse ScienceDirect
Research in Autism Spectrum Disorders Journal homepage: http://ees.elsevier.com/RASD/default.asp
Video game use and problem behaviors in boys with autism spectrum disorders Micah O. Mazurek a,b,*, Christopher R. Engelhardt c a
University of Missouri, Department of Health Psychology, United States Thompson Center for Autism and Neurodevelopmental Disorders, 205 Portland Street, Columbia, MO 65211, United States c University of Missouri, Department of Psychological Sciences, 210 McAlester Hall, Columbia, MO 65211-2500, United States b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 8 August 2012 Received in revised form 20 September 2012 Accepted 21 September 2012
Children with autism spectrum disorders (ASD) have strong preferences for screen-based media, particularly video games. Although problematic video game use has been associated with behavior problems among typically developing children, the relationship between these variables has not been previously examined among children with ASD. The current study examined the relationships between aspects of video game use and problem behaviors among a sample of 169 boys (ages 8–18) with ASD. Parents reported on their children’s behavioral functioning and video game habits and preferences, including the average number of hours spent playing video games per day, preferred game types (genres), and problematic (i.e., addictive) video game play patterns. The results revealed that problematic video game use was significantly correlated with inattention and oppositional behavior. Boys who played Role-Playing games had higher levels of both problematic game use and oppositional behavior. Finally, problematic game use and RolePlaying game genre were significant predictors of oppositional behavior, even when controlling for age and amount of time spent playing video games. The results highlight the clinical importance of examining video game use patterns among children with ASD, and indicate a need for future experimental and longitudinal research in this area. ß 2012 Elsevier Ltd. All rights reserved.
Keywords: Autism spectrum disorder Video games Problem behaviors Oppositional behavior
1. Introduction Children with autism spectrum disorders (ASD) are at an increased risk for difficulties regulating their behavior and attention. These symptoms are not considered to be primary diagnostic features of ASD, but they commonly occur alongside core impairments in communication and social skills and repetitive behavior (American Psychiatric Association, 2000). Specifically, children with ASD demonstrate high rates of oppositional behavior (Gadow, Devincent, Pomeroy, & Azizian, 2005; Mayes, Calhoun, Aggarwal, et al., 2012), inattention, hyperactivity (Frazier et al., 2001; Gadow et al., 2005; Mayes, Calhoun, Mayes, & Molitoris, 2012), and aggression (Kanne & Mazurek, 2011). These co-occurring difficulties can have significant effects on daily functioning for children with ASD and their families. Thus, the identification of factors that may be strongly associated with these behaviors would provide important information for both clinicians and families. Among potentially relevant factors, video game use has been anecdotally associated with problem behaviors by many parents of children with ASD. As will be discussed, there is ample evidence of an association between video game play and behavior problems among typically developing children. However, previous studies have not examined the association
* Corresponding author at: Thompson Center for Autism and Neurodevelopmental Disorders, University of Missouri, 205 Portland Street, Columbia, MO 65211, United States. Tel.: +1 573 884 8502; fax: +1 573 884 6421. E-mail addresses: [email protected] (M.O. Mazurek), [email protected] (C.R. Engelhardt). 1750-9467/$ – see front matter ß 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.rasd.2012.09.008
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
317
between these variables in children with ASD. The current study not only fills this important gap in the literature, but it also examines the extent to which preferences for particular video game genres are associated with behavior problems among individuals with ASD. Emerging research has shown that children with ASD spend the majority of their discretionary time using electronic media, including video games (Orsmond & Kuo, 2011; Shane & Albert, 2008). Adolescents with ASD are also more likely than those with other types of disabilities to spend most of their free time playing video games (Mazurek, Shattuck, Wagner, & Cooper, 2012). In addition, a recent study found that children with ASD spent significantly more hours per day playing video games and demonstrated significantly higher scores on a measure of problematic video game use than their typically developing siblings (Mazurek & Wenstrup, 2012). Thus, it appears that children with ASD are at an increased risk for problematic patterns of video game play. However, studies have not yet examined whether video game use relates to behavior problems in children with ASD. Therefore, the current study focuses on: the amount of time spent playing video games, problematic game play patterns, and video game genre, each of which has been associated with negative outcomes in previous studies in the general population. 1.1. Amount of video game play and behavior Studies of video game use have examined a variety of aspects of game play that appear to have distinct contributions to an individual’s out-of-game (i.e., real world) behavior. At the most basic level of measurement, the amount of time an individual spends playing video games has been extensively studied in previous research. For example, Chan and Rabinowitz (2006) found that adolescents who spent more than 1 h per day playing video games had significantly greater symptoms of inattention and hyperactivity, and greater symptoms of behavioral addiction. Core elements of behavioral addiction include salience (e.g., cravings or preoccupation), tolerance, withdrawal, relapse, mood modification, and conflict (see Gentile, 2009). Swing, Gentile, Anderson, and Walsh (2010) also found that time spent playing video games was significantly associated with subsequent attention problems across a 13-month period in adolescence, even after controlling for earlier attention problems. More recently, Gentile, Swing, Lim, and Khoo (2012) examined the longitudinal relations among video game use, attention problems and impulsivity in a large sample of children and adolescents. Over a 3-year period, the results indicated that time spent playing video games was significantly related to subsequent attention problems and impulsivity even after controlling for initial levels of attention/impulsivity and demographic variables. Furthermore, although video game violence was associated with attention problems and impulsivity, total video game exposure emerged as the most robust predictor of such problems. 1.2. Video game content, problematic game use, and behavior A large body of research has also demonstrated a clear effect of both video game content and genre on behavior problems among typically developing children and adolescents. The vast majority of this research over the past several decades has focused on the correlates and consequences of violent video game use. Numerous studies have shown a clear causal relationship between short- and long-term exposure to violent video games, particularly First-Person Shooter games, and increases in aggressive thinking, aggressive affect, and aggressive behavior (for a review see Anderson, 2004; Anderson et al., 2010). More recently, video game researchers have also begun to investigate pathological or problematic video game use, which has been conceptualized as a form of behavioral addiction (Gentile, 2009; Tejeiro Salguero & Mora´n, 2002). Studies examining the measurement of this construct have found support for construct validity and reliability, indicating that problematic video game play is a distinct construct that can be reliably assessed (Gentile, 2009; King, Delfabbro, & Zajac, 2011). Cross-sectional studies have demonstrated significant associations between problematic video game use and problem behaviors. For example, in a large sample of 804 adolescents, participants who were classified as pathological gamers were more likely to demonstrate aggressive behavior than those who did not demonstrate pathological gaming patterns (Gru¨sser, Thalemann, & Griffiths, 2007). Similar associations between online gaming addiction and aggression have also been found in a large sample of young adults (Kim, Namkoong, Ku, & Kim, 2008). Anecdotal reports from families are consistent, suggesting that disruption of game play is often an antecedent for aggressive outbursts among adolescents who demonstrate pathological patterns of play (Young, 2009). Recently, Lemmens, Valkenburg, and Peter (2011) also found that problematic video game use, regardless of violent content, predicted longitudinal increases in physical aggression among a large sample of adolescent boys. Problematic video game and internet use have also been associated with inattention and impulsivity among both adolescents (Rehbein, Kleimann, & Mo¨ssle, 2010) and adults (Meerkerk, van den Eijnden, Franken, & Garretsen, 2010; Yen, Yen, Chen, Tang, & Ko, 2009). Similarly, in a sample of children with ADHD, children with higher scores on a measure of problematic video game play demonstrated significantly greater problems with hyperactivity, aggression, and externalizing behaviors (Bioulac, Arfi, & Bouvard, 2008). In addition to the previously reported negative consequences associated with violent games (Anderson et al., 2010), studies have also found that other video game genres, particularly Role-Playing games, are related to the potential for problematic video game use and negative consequences. Role-Playing games contain particular game design features that
318
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
may make them especially prone to addictive patterns of use (King, Delfabbro, & Griffiths, 2011). For example, these games have high reward schedules, including both virtual rewards (such as scores, achievements, and in-game items) and social rewards (including peer attention and approval in online multi-player games). In addition, because players must create, maintain, and advance characters over time and have the option to explore open-ended virtual worlds, Role-Playing games have the potential to be more time-consuming than other genres, possibly increasing the likelihood of problematic use patterns. Given these features, it is not surprising that Role-Playing games have been highly associated with the development of problematic game play patterns. In a large sample of Korean adolescents, Role-Playing game users had significantly greater internet addiction scores as compared to other game genres, and Role-Playing games were more likely to be the preferred game genre among individuals classified as high-risk for internet addiction (Lee et al., 2007). In a randomized longitudinal study, Smyth (2007) assigned young adults into gaming genre groups (arcade, console, solo computer, or Role-Playing) for 1 month. The results indicated that the Role-Playing group differed significantly from the other genre groups, with reduced sleep quality, reduced overall health, and increased interference of game play with socialization. In a large population-based study of German adolescents, both online Role-Playing and First-Person Shooter game genre players were significantly more likely than players of other game types to demonstrate video game dependence, and multivariate analyses revealed that Role-Playing game use remained a significant predictor even after accounting for a number of additional psychological and demographic predictors (Rehbein et al., 2010). 1.3. Current study In summary, previous findings from the general population indicate that particular aspects of video game play are strongly associated with externalizing behavior problems. Given that children with ASD are at increased risk for these behavior problems, and that they spend a significant amount of time playing video games, this topic is highly relevant and clinically important. Surprisingly, previous research has not yet explored the relations among these variables in children with ASD. Thus, the purpose of the current study was to examine the associations between video game use and behavior problems in a sample of children with ASD. Our primary hypotheses were: (1) the amount of time spent playing video games would be positively associated with problem behaviors, (2) problematic video game use would be positively associated with problem behaviors, and (3) game genre, particularly First-Person Shooter and Role-Playing games, would be associated with problem behaviors. A secondary aim of the study was to examine the relative contributions of our hypothesized game genres to problem behaviors when considered jointly within multivariate models. Previous studies have revealed significant gender differences in both patterns and consequences of video game play. Studies have consistently shown that males spend greater amounts of time playing video games (Gentile, 2009; Marshall, Gorely, & Biddle, 2006), are at greater risk for pathological game play (Gentile, 2009; Gentile et al., 2011; Lemmens et al., 2011), and express different, more reward-focused reasons for game play than females (Ko, Yen, Chen, Chen, & Yen, 2005). Given these findings, the current study examined game-play patterns among boys only. 2. Methods 2.1. Participants The sample for the current study included parents of 169 boys with ASD ranging in age from 8 to 18 years (M = 12.1; SD = 2.8) who were recruited with the assistance of a national open enrollment ASD registry, the Interactive Autism Network (IAN) Research Database at Kennedy Krieger Institute Baltimore, Maryland, sponsored by the Autism Speaks Foundation. Enrollment into IAN involves the completion of a battery of questionnaires regarding the child’s ASD diagnosis, primary and associated symptoms, and other aspects of child and family functioning. Recent studies examining the validity of parent-reported ASD diagnosis among the IAN sample have reported a high degree of concordance with both external clinical documentation and with gold-standard diagnostic tools (Daniels et al., 2012; Lee et al., 2010). A complete list of IAN survey questions and instruments may be found at: http://www.iancommunity.org/cs/ian_research_questions/ ian_research_questions. Participants for the current study were recruited by email, and parents completed all measures online using a web-based format. Eligibility requirements included age range (8–18) and a parent-reported professional diagnosis of ASD, including Autism or Autistic Disorder (52.7%), Asperger’s Disorder (28.4%), or Pervasive Developmental Disorder, NOS (18.9%). The majority of the sample was Caucasian (89.3%). Regarding parent-reported intellectual functioning, 8.9% of the sample was reported to have a previously assessed IQ of 70 or below. Analyses of variance (ANOVA) indicated that the group with IQ below 70 did not differ from those above 70 with regard to any study-related variables. 2.2. Measures Parents completed a series of questions developed for the current study including demographic information, diagnostic and functional information, and specific information about activity and screen-based media use, as described below.
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
319
2.2.1. Video game use Parents reported the average number of hours per day their children spent ‘‘playing video or computer games.’’ Parents provided separate estimates for a ‘‘typical weekday’’ and ‘‘typical weekend day.’’ An average daily use variable was created, consistent with previous studies (Orsmond & Kuo, 2011; Zimmerman & Christakis, 2005), by multiplying the weekday response by 5, multiplying the weekend response by 2, and dividing the sum of these by 7. 2.2.2. Video game genre Parents also listed the three most common video games their children had played in the past month. Games were coded into mutually exclusive categories primarily using descriptions found on the Entertainment Software Rating Board website (http://www.esrb.org/index-js.jsp). These genre descriptions were also cross-referenced with popular gaming websites, specifically Gamespot (http://www.gamespot.com/) and IGN (http://www.ign.com/). The resulting genre categories included: (1) Action and Action-Adventure, (2) Adventure, (3) Role-Playing, (4) Strategy, (5) Puzzle and Mini-game, (6) Educational, (7) Fighting, (8) First-Person Shooter, (9) Music, (10) Platform, (11) Racing, (12) Simulation, and (13) Sports Simulation. 2.2.3. Problematic video game use Problematic patterns of video game play were assessed using a modified version of the Problem Video Game Playing Test (PVGT) (King, Delfabbro, & Zajac, 2011). The original 20-item PVGT was developed as a self-report measure for adolescents and adults, which assesses problematic aspects of game-playing based on the behavioral addiction model (Griffiths, 2005), including salience, mood modification, withdrawal, tolerance, relapse, and conflict. Items are rated on a 5-point Likert-type scale ranging from Never to Always. Modifications for the current study included wording adjustments to increase relevance for younger participants, and modification from first- to parent-report format. One of the original items (item 20, focusing on mood modification) was dropped from the scale for the purpose of the current study based on parent-reported difficulty in responding accurately to the item during pilot testing of the modified instrument. Specifically, the item assesses whether an individual plays games as a means of changing his or her mood, and parents indicated difficulty in determining this. As a result, 19 items were retained in the final modified version. Cronbach’s alpha coefficients were examined to assess internal consistency of the modified scale. The results indicated strong internal consistency, with alpha of .94. Item-total correlations ranged from 0.46 to 0.81. A total PVGT score, calculated as the sum of all item scores, was used in subsequent analyses. 2.2.4. Attention problems, impulsivity, and oppositional behavior The Vanderbilt Attention Deficity/Hyperactivity Disorder Parent Rating Scale (VADPRS) (Wolraich, Hannah, Baumgaertel, & Feurer, 1998) was used to assess symptoms of inattention, hyperactivity/impulsivity, and oppositional defiant behaviors. The VADPRS is a widely used parent-report rating scale used to assess symptoms of ADHD, ODD, and other clinically relevant symptoms. For the purposes of the current study, items from the Inattention (9 items), Hyperactivity/Impulsivity (9 items), and Oppositional Defiant (8 items) subscales were administered. Items are rated on a 4-point Likert-type scale ranging from 0 (Never) to 3 (Very Often). The VADPRS has been previously found to have good internal consistency, validity, and reliability (Wolraich et al., 2003). In the current sample, Cronbach’s alpha coefficients were .88 for the Inattention subscale, .87 for the Hyperactivity/Impulsivity subscale, and .88 for the Oppositional Defiant subscale, indicating good internal consistency for all subscales in the current population. 2.3. Data analyses Bivariate relationships between continuous variables were examined using Pearson’s correlations. Preference for game genre was examined using percentages across the sample of those who had played video games within the past month. Percentages were calculated for each game genre type, including percentage reporting each type as their #1 most frequently played game, and percentage who reported each type within the top three most frequently played games. Given that previous research has revealed genre-specific effects on behavioral functioning (i.e., Role-Playing and Shooter style games), we focused on these specific game types in subsequent analyses. Two dichotomous variables were created to indicate whether or not this type of game genre (Role-Playing and Shooter, respectively) was reported as one of the top three most frequently played games. Group comparisons between those who did and did not report playing each of these game genre types (among their top three games) were conducted using ANOVA for continuous variables. Cohen’s d is reported as a measure of effect size. Levene’s statistic was significant in some cases, indicating that the assumption of homogeneity of variances for ANOVA was not met. Welch adjusted F statistics are reported in these cases. Next, linear regression analyses were conducted to examine the relative contributions of video game play variables to the cross-sectional prediction of behavior problems. Separate regression models were computed for each dependent variable of interest (including inattention, hyperactivity, and oppositional/defiant symptoms), controlling for age. Additional independent variables included daily hours of video game play, PVGT score, Shooter game play (dichotomous), and Role-Playing game play (dichotomous).
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
320 Table 1 Video game genre preference. Game genre
Percenta reporting genre as #1 game
Percent reporting genre as one of the top 3
Most frequent game title by genre
Action Platform Shooter Puzzle/Mini-Game Role-Playing Sports Simulation Racing Educational Simulation Adventure Strategy Fighting Music
15.7 14.3 12.9 10.7 9.3 8.6 6.4 6.4 5.7 3.6 3.6 2.1 0.7
30.7 25.0 20.7 16.4 20.0 12.9 17.9 8.6 13.6 7.1 6.4 6.4 1.4
Star Wars series Super Mario Bros. series Call of Duty series Angry Birds Pokemon series Madden NFL series Mario Kart series PBS Kids Online Games The Sims Legend of Zelda series Plants vs. Zombies Super Smash Bros. Brawl Guitar Hero
a
Percentage of sample of children who have played video games within past month, n = 140.
3. Results 3.1. Video game use patterns Results indicated that children in current sample spent an average of 2.4 h per day playing video games (M = 2.4, SD = 1.7), and that daily video game use was positively correlated with age (r = .23, p = .003). Table 1 shows information regarding video game genre preferences. An examination of the most frequently reported game genre indicates that the Action category was the most frequently reported first choice, followed by Platform and Shooter, and these categories were also the most frequently reported among the top three game categories. As shown in Table 2, video game play variables were also moderately related with one another, with significant positive correlations between daily hours of video game play and PVGT scores (r = .314, p < .001). Also, as shown in Table 3, boys who were reported to play Shooter
Table 2 Means, standard deviations and correlation coefficients (n = 169). Variable
M
SD
Range
Age Video game hours/day PVGT score Inattention Hyperactivity Oppositional defiant
12.1 2.4 39.9 17.0 12.0 8.1
2.8 1.7 11.6 6.1 6.7 5.5
8–18 0–7.4 19–74 1–27 0–27 0–24
1
2 .23** .12 .04 .16* .11
.31*** .03 .15 .07
3
4
5
.41*** .07 .34***
.41*** .32***
.39***
* p < .05. ** p < .01. *** p < .001. Table 3 Group comparisons by game genre. Variable
Age Video game hours/day PVGT score Inattention Hyperactivity Oppositional defiant Age Video game hours/day PVGT Score Inattention Hyperactivity Oppositional defiant
Yes M (SD) Shooter 14.2 (2.5) 3.0 (1.5) 45.0 (12.3) 16.8 (5.5) 11.1 (6.6) 9.7 (4.9) Role-Playing 13.0 (2.4) 3.3 (1.9) 45.4 (11.9) 17.7 (5.3) 10.6 (5.4) 10.7 (6.7)
No M (SD)
F
p
Cohen’s d
11.6 2.3 38.7 17.1 12.2 7.8
(2.7) (1.7) (11.2) (6.2) (6.7) (5.5)
23.0 4.9 7.1 0.04 0.6 3.1
<.001 .03 .008 .83 .44 .08
1.00 0.47 0.53 0.47 0.16 0.37
11.9 2.2 38.7 16.9 12.3 7.6
(2.9) (1.6) (11.3) (6.3) (6.9) (5.0)
3.6 7.2a 7.9 0.4 2.1a 5.4a
.06 .01 .005 .51 .16 .03
0.41 0.60 0.58 0.14 0.27 0.52
Note: Group comparisons on continuous variables conducted with ANOVA. Cohen’s d is reported for all effect sizes, with positive values indicating higher scores in the group playing the specific game. a The adjusted Welch F-ratio is reported due to unequal variance.
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
321
Table 4 Relations among video game variables and behavior: linear regression analyses. Independent variables Inattention Equation Age Daily hours of video game play PVGT score Shooter genre Role-Playing genre Oppositional defiant Equation Age Daily hours of video game play PVGT score Shooter genre Role-Playing genre
R2
F
.19
7.22***
.15
B
SE B
b
0.06 0.43 0.24 1.34 0.32
0.17 0.28 0.04 1.22 1.19
.03 .12 .47*** .09 .02
0.09 0.30 0.15 1.03 2.32
0.16 0.26 0.04 1.14 1.12
.05 .09 .31*** .07 .16*
5.4***
* p < .05. *** p < .001.
games spent significantly more hours per day playing video games (p = .03) and demonstrated significantly higher PVGT scores (p = .008) than boys whose parents did not list Shooter games among their top three most frequently played games. Similarly, boys who played Role-Playing games also spent significantly more hours per day playing video games (p = .01) and demonstrated higher PVGT scores (p = .005) than those who did not play Role-Playing games. 3.2. Video game use and problem behaviors Bivariate analyses were conducted to examine the primary study hypotheses. Contrary to our first prediction, no significant correlations were found between daily hours of video game play and inattention, hyperactivity, or oppositional defiant behavior (see Table 2). However, we found partial support for our second prediction. Specifically, PVGT score was significantly positively correlated with inattentive symptoms (r = .406, p < .001), and oppositional/defiant symptoms (r = .340, p < .001), but not with hyperactivity. Consistent with our third prediction, boys who were reported to play Role-Playing games had significantly greater oppositional behaviors (p = .03), as shown in Table 3. Similarly, boys who played Shooter games also had greater oppositional behaviors; however, this difference did not reach statistical significance (p = .08). However, neither Role-Playing nor Shooter game genres were associated with higher scores on the inattention or hyperactivity scale. 3.3. Multivariate analyses To examine the relative contributions of each video game variable when considered jointly within multivariate models, separate linear regression models were conducted for each problem behavior variable (inattention, hyperactivity, and oppositional symptoms), while controlling for age. Additional independent variables included average daily hours of video game play, PVGT score, Shooter game play, and Role-Playing game play. The regression model for hyperactivity symptoms was not statistically significant, indicating that the model was not a good fit for the data. However, as shown in Table 4, the models for inattention and oppositional defiant symptoms were both significant. In the model predicting inattention, the results indicated that a significant main effect was observed for PVGT score (p < .001), but not for age, video game hours, or either video game genre. For the model predicting oppositional behavior, the results showed significant main effects of both PVGT score (p < .001) and Role-Playing genre (p = .039), but no effects were observed for age, video game hours, or Shooter genre. To show that our predicted game genre effects are unique to First-Person Shooter games and Role-Playing games, we also conducted similar regression models for game genres that, in theory, should not be related to behavior problems. Consistent with this hypothesis, these models revealed that none of the remaining game genres predicted greater behavior problems (ps > .05). In fact, even after controlling for all other variables in the model, Educational and Sports games predicted less oppositional defiant symptoms (p < .05), and Sports games predicted less hyperactivity (p < .05). 4. Discussion The current study is the first to describe the relationships between aspects of video game play and problem behaviors among children with ASD. In a sample of 169 boys with ASD, the results indicated that amount of game play alone was not associated with problem behaviors. Rather, the most reliable predictors of problem behaviors were shown to be video game genre and problematic, or addictive, qualities of play. Specifically, significant positive relationships were found between problematic video game use and both inattention and oppositional symptoms. Furthermore, boys with ASD who primarily played Role-Playing games had significantly greater oppositional behaviors
322
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
than those who did not play such games. Interestingly, the results from multivariate models added further support to our prediction that Role-Playing games would be uniquely associated with problem behaviors. Even when controlling for other variables (i.e., age, amount of time spent playing games, and problematic video game patterns), Role-Playing game genre remained a significant cross-sectional predictor of oppositional behavior. Furthermore, the results of subsequent analyses indicated that children who played game genres that should be theoretically unrelated to poor behavioral control (i.e., Sports and Educational games), demonstrated fewer oppositional behaviors and less hyperactivity than those who primarily played other game genres. The results of this study are consistent, in part, with findings from the general population. For example, the significant associations between problematic video game play, inattention, and oppositional behavior in the current sample are similar to those reported in adolescents and adults without ASD (Bioulac et al., 2008; Rehbein et al., 2010; Yen et al., 2009). Interestingly, however, hyperactivity was not significantly associated with either problematic video game use or video game genre. This is in contrast to previously reported associations between problematic game and internet use and hyperactivity/ impulsivity (Bioulac et al., 2008; Meerkerk et al., 2010; Yen et al., 2009). Future studies of video game use in children with ASD would benefit from the inclusion of comparison groups, including both typically developing children and those with ADHD. This would help to further delineate potentially distinct profiles of video game use and behavior among different diagnostic groups. Our finding that Role-Playing games were highly associated with problematic video game play was also consistent with previous research. Specifically, others have also found that Role-Playing games are associated with problematic game use among individuals without ASD (Smyth, 2007). Given their tendency to engage in restricted and repetitive patterns of activity (American Psychiatric Association, 2000), children with ASD may be at particular risk for developing problematic, or addictive, game play patterns. In fact, in a previous study, we found that children with ASD demonstrated significantly greater levels of problematic video game play than typically developing children (Mazurek & Wenstrup, 2012). With this in mind, Role-Playing games may contribute to an even greater potential for problematic game use patterns among children with ASD, given their particular game-design features. Furthermore, preoccupation with video games and trouble disengaging from them may serve as antecedents for disruptive behavior, as has been anecdotally reported among other children (Young, 2009). Overall, it appears that for children with ASD, the potential for preoccupation represents a key game play quality that relates closely with the occurrence of problem behaviors. Interestingly, violent video game use did not emerge as a significant predictor of either oppositional behavior or inattention in either bivariate or multivariate models. Consistent with Rehbein et al. (2010), we found that First-Person Shooter games were significantly associated with problematic game play patterns; however, they did not relate specifically to behavior problems. The reasons for this are not clear. One potential explanation is that the problem behaviors we targeted did not include measures of physical aggression. Although oppositional symptoms include affective anger and defiance, no overt behavioral symptoms of aggression were examined. Future studies among children with ASD should include measures of aggression, specifically, in order to determine if associations between video game violence and aggressive thoughts and behavior are similar or different from those in the general population (Anderson et al., 2010). Theoretical models proposed to account for these previously documented associations between video game violence exposure and aggression often include social learning (Bandura, 1978) and social-cognitive components (Anderson & Bushman, 2002). It is possible that these models require further study among children with ASD, particularly given their deficits in social learning (Vivanti & Rogers, 2011). Experimental paradigms would be most helpful in order to determine if violent video game exposure results in changes in aggressive thoughts or behavior among children with ASD. 4.1. Limitations and future directions It should be noted that the current study relied on parent-report for all measures. In future studies, a more thorough characterization of the sample would be ideal, including measures of core ASD symptoms, cognitive functioning, and language. Although parent-report is often considered to be more valid than self-report in assessment of symptoms and behavior among children with ASD (Lopata et al., 2010; Mazefsky, Kao, & Oswald, 2011), studies examining the relative concordance between parent- and self-report on measures of video game use would be very informative, especially if considered in multi-trait, multi-method models. Finally, the use of alternative measures of video game use, including time use diaries, direct observation, and electronic monitoring techniques would be helpful (Vandewater & Lee, 2009). Finally, it is important to note that the current study was cross-sectional in design; therefore, causality cannot be determined. It is possible that children with pre-existing behavior problems are more inclined to play video games for longer periods of time and in a more intense manner. Alternatively, particular patterns of video game play may directly contribute to the development of behavior problems. It is also possible that these problems have bi-directional relationships. Longitudinal prospective studies and experimental paradigms are needed to more carefully evaluate these issues. Future research in this area is critical in order to inform video game use recommendations for both parents and clinicians. As emerging research investigates the effectiveness of video-game based interventions for improving functional outcomes, it will be equally important to understand the mechanisms and nature of problematic aspects of game play among children with ASD.
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
323
4.2. Conclusions The results of this study provide important new information about the relationships between video game use and behavior problems in children with ASD. Although anecdotal concerns about problematic video game use have been reported by clinicians and parents, this is the first empirical study on the topic. Our findings revealed that problematic video game use is highly associated with behavior problems among boys with ASD, and that boys who play Role-Playing games are especially likely to demonstrate co-occurring oppositional behavior. These results highlight the clinical importance of examining video game use patterns among children with ASD and indicate a need for future experimental and longitudinal research in this area. References American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders – Fourth edition, text revision. Washington, DC: American Psychiatric Association. Anderson, C. A. (2004). An update on the effects of playing violent video games. Journal of Adolescence, 27, 113–122. Anderson, C. A., & Bushman, B. J. (2002). Human aggression. Annual Review of Psychology, 53, 27–51. Anderson, C. A., Shibuya, A., Ihori, N., Swing, E. L., Bushman, B. J., Sakamoto, A., et al. (2010). Violent video game effects on aggression, empathy, and prosocial behavior in Eastern and Western countries: A meta-analytic review. Psychological Bulletin, 136, 151–173. Bandura, A. (1978). Social learning theory of aggression. Journal of Communication, 28, 12–29. Bioulac, S., Arfi, L., & Bouvard, M. P. (2008). Attention deficit/hyperactivity disorder and video games: A comparative study of hyperactive and control children. European Psychiatry, 23, 134–141. Chan, P. A., & Rabinowitz, T. (2006). A cross-sectional analysis of video games and attention deficit hyperactivity disorder symptoms in adolescents. Annals of General Psychiatry, 5, 16. Daniels, A., Rosenberg, R., Anderson, C., Law, J., Marvin, A., & Law, P. (2012). Verification of parent-report of child autism spectrum disorder diagnosis to a webbased autism registry. Journal of Autism and Developmental Disorders, 42, 257–265. Frazier, J. A., Biederman, J., Bellordre, C. A., Garfield, S. B., Geller, D. A., Coffey, B. J., et al. (2001). Should the diagnosis of Attention-Deficit/Hyperactivity disorder be considered in children with Pervasive Developmental Disorder? Journal of Attention Disorders, 4, 203–211. Gadow, K. D., Devincent, C. J., Pomeroy, J., & Azizian, A. (2005). Comparison of DSM-IV symptoms in elementary school-age children with PDD versus clinic and community samples. Autism, 9, 392–415. Gentile, D. A. (2009). Pathological video-game use among youth ages 8 to 18: A national study. Psychological Science, 20, 594–602. Gentile, D. A., Choo, H., Liau, A., Sim, T., Li, D., Fung, D., et al. (2011). Pathological video game use among youths: A two-year longitudinal study. Pediatrics, 127, e319–e329. Gentile, D. A., Swing, E. L., Lim, C. G., & Khoo, A. (2012). Video game playing, attention problems, and impulsiveness: Evidence of bidirectional causality. Psychology of Popular Media Culture, 1, 62–70. Griffiths, M. D. (2005). A components model of addiction within a biopsychosocial framework. Journal of Substance Use, 10, 191–197. Gru¨sser, S. M., Thalemann, R., & Griffiths, M. D. (2007). Excessive computer game playing: Evidence for addiction and aggression? CyberPsychology & Behavior, 10, 290–292. Kanne, S., & Mazurek, M. (2011). Aggression in children and adolescents with ASD: Prevalence and risk factors. Journal of Autism and Developmental Disorders, 41, 926–937. Kim, E. J., Namkoong, K., Ku, T., & Kim, S. J. (2008). The relationship between online game addiction and aggression, self-control and narcissistic personality traits. European Psychiatry, 23, 212–218. King, D., Delfabbro, P., & Griffiths, M. (2011). The role of structural characteristics in problematic video game play: An empirical study. International Journal of Mental Health and Addiction, 9, 320–333. King, D., Delfabbro, P., & Zajac, I. (2011). Preliminary validation of a new clinical tool for identifying problem video game playing. International Journal of Mental Health and Addiction, 9, 72–87. Ko, C.-H., Yen, J.-Y., Chen, C.-C., Chen, S.-H., & Yen, C.-F. (2005). Gender differences and related factors affecting online gaming addiction among Taiwanese adolescents. Journal of Nervous and Mental Disease, 193, 273–277. Lee, H., Marvin, A. R., Watson, T., Piggot, J., Law, J. K., Law, P. A., et al. (2010). Accuracy of phenotyping of autistic children based on internet implemented parent report. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 153B, 1119–1126. Lee, M.-S., Ko, Y.-H., Song, H.-S., Kwon, K.-H., Lee, H.-S., Nam, M., et al. (2007). Characteristics of internet use in relation to game genre in Korean adolescents. CyberPsychology & Behavior, 10, 278–285. Lemmens, J., Valkenburg, P., & Peter, J. (2011). The effects of pathological gaming on aggressive behavior. Journal of Youth and Adolescence, 40, 38–47. Lopata, C., Toomey, J., Fox, J., Volker, M., Chow, S., Thomeer, M., et al. (2010). Anxiety and depression in children with HFASDs: Symptom levels and source differences. Journal of Abnormal Child Psychology, 38, 765–776. Marshall, S. J., Gorely, T., & Biddle, S. J. H. (2006). A descriptive epidemiology of screen-based media use in youth: A review and critique. Journal of Adolescence, 29, 333–349. Mayes, S. D., Calhoun, S. L., Aggarwal, R., Baker, C., Mathapati, S., Anderson, R., et al. (2012). Explosive, oppositional, and aggressive behavior in children with autism compared to other clinical disorders and typical children. Research in Autism Spectrum Disorders, 6, 1–10. Mayes, S. D., Calhoun, S. L., Mayes, R. D., & Molitoris, S. (2012). Autism and ADHD: Overlapping and discriminating symptoms. Research in Autism Spectrum Disorders, 6, 277–285. Mazefsky, C. A., Kao, J., & Oswald, D. P. (2011). Preliminary evidence suggesting caution in the use of psychiatric self-report measures with adolescents with highfunctioning autism spectrum disorders. Research in Autism Spectrum Disorders, 5, 164–174. Mazurek, M. O., Shattuck, P. T., Wagner, M., & Cooper, B. (2012). Prevalence and correlates of screen-based media use among youths with autism spectrum disorders. Journal of Autism and Developmental Disorders, 42, 1757–1767. Mazurek, M. O., & Wenstrup, C. (2012). Television, video game and social media use among children with ASD and typically developing siblings. Journal of Autism and Developmental Disorders, http://dx.doi.org/10.1007/s10803-012-1659-9. Meerkerk, G. J., van den Eijnden, R. J. J. M. , Franken, I. H. A., & Garretsen, H. F. L. (2010). Is compulsive internet use related to sensitivity to reward and punishment, and impulsivity? Computers in Human Behavior, 26, 729–735. Orsmond, G. I., & Kuo, H.-Y. (2011). The daily lives of adolescents with an autism spectrum disorder. Autism, 15, 579–599. Rehbein, F., Kleimann, M., & Mo¨ssle, T. (2010). Prevalence and risk factors of video game dependency in adolescence: Results of a German nationwide survey. CyberPsychology, Behavior & Social Networking, 13, 269–277. Shane, H., & Albert, P. (2008). Electronic screen media for persons with autism spectrum disorders: Results of a survey. Journal of Autism and Developmental Disorders, 38, 1499–1508. Smyth, J. M. (2007). Beyond self-selection in video game play: An experimental examination of the consequences of Massively Multiplayer Online Role-Playing game play. CyberPsychology & Behavior, 10, 717–721.
324
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
Swing, E. L., Gentile, D. A., Anderson, C. A., & Walsh, D. A. (2010). Television and video game exposure and the development of attention problems. Pediatrics, 126, 214–221. Tejeiro Salguero, R. A., & Mora´n, R. M. B. (2002). Measuring problem video game playing in adolescents. Addiction, 97, 1601–1606. Vandewater, E. A., & Lee, S.-J. (2009). Measuring children’s media use in the digital age: Issues and challenges. American Behavioral Scientist, 52, 1152–1176. Vivanti, G., & Rogers, S. J. (2011). Action understanding and social learning in autism: A developmental perspective. Life Span and Disability, 14, 7–29. Wolraich, M. L., Hannah, J. N., Baumgaertel, A., & Feurer, I. D. (1998). Examination of DSM-IV criteria for attention deficit/hyperactivity disorder in a county-wide sample. Journal of Developmental and Behavioral Pediatrics, 19, 162–168. Wolraich, M. L., Lambert, W., Doffing, M. A., Bickman, L., Simmons, T., & Worley, K. (2003). Psychometric properties of the Vanderbilt ADHD Diagnostic Parent Rating Scale in a referred population. Journal of Pediatric Psychology, 28, 559–568. Yen, J.-Y., Yen, C.-F., Chen, C.-S., Tang, T.-C., & Ko, C.-H. (2009). The association between adult ADHD symptoms and internet addiction among college students: The gender difference. CyberPsychology & Behavior, 12, 187–191. Young, K. (2009). Understanding online gaming addiction and treatment issues for adolescents. American Journal of Family Therapy, 37, 355–372. Zimmerman, F. J., & Christakis, D. A. (2005). Children’s television viewing and cognitive outcomes: A longitudinal analysis of national data. Archives of Pediatric and Adolescent Medicine, 159, 619–625.
Contents lists available at SciVerse ScienceDirect
Research in Autism Spectrum Disorders Journal homepage: http://ees.elsevier.com/RASD/default.asp
Video game use and problem behaviors in boys with autism spectrum disorders Micah O. Mazurek a,b,*, Christopher R. Engelhardt c a
University of Missouri, Department of Health Psychology, United States Thompson Center for Autism and Neurodevelopmental Disorders, 205 Portland Street, Columbia, MO 65211, United States c University of Missouri, Department of Psychological Sciences, 210 McAlester Hall, Columbia, MO 65211-2500, United States b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 8 August 2012 Received in revised form 20 September 2012 Accepted 21 September 2012
Children with autism spectrum disorders (ASD) have strong preferences for screen-based media, particularly video games. Although problematic video game use has been associated with behavior problems among typically developing children, the relationship between these variables has not been previously examined among children with ASD. The current study examined the relationships between aspects of video game use and problem behaviors among a sample of 169 boys (ages 8–18) with ASD. Parents reported on their children’s behavioral functioning and video game habits and preferences, including the average number of hours spent playing video games per day, preferred game types (genres), and problematic (i.e., addictive) video game play patterns. The results revealed that problematic video game use was significantly correlated with inattention and oppositional behavior. Boys who played Role-Playing games had higher levels of both problematic game use and oppositional behavior. Finally, problematic game use and RolePlaying game genre were significant predictors of oppositional behavior, even when controlling for age and amount of time spent playing video games. The results highlight the clinical importance of examining video game use patterns among children with ASD, and indicate a need for future experimental and longitudinal research in this area. ß 2012 Elsevier Ltd. All rights reserved.
Keywords: Autism spectrum disorder Video games Problem behaviors Oppositional behavior
1. Introduction Children with autism spectrum disorders (ASD) are at an increased risk for difficulties regulating their behavior and attention. These symptoms are not considered to be primary diagnostic features of ASD, but they commonly occur alongside core impairments in communication and social skills and repetitive behavior (American Psychiatric Association, 2000). Specifically, children with ASD demonstrate high rates of oppositional behavior (Gadow, Devincent, Pomeroy, & Azizian, 2005; Mayes, Calhoun, Aggarwal, et al., 2012), inattention, hyperactivity (Frazier et al., 2001; Gadow et al., 2005; Mayes, Calhoun, Mayes, & Molitoris, 2012), and aggression (Kanne & Mazurek, 2011). These co-occurring difficulties can have significant effects on daily functioning for children with ASD and their families. Thus, the identification of factors that may be strongly associated with these behaviors would provide important information for both clinicians and families. Among potentially relevant factors, video game use has been anecdotally associated with problem behaviors by many parents of children with ASD. As will be discussed, there is ample evidence of an association between video game play and behavior problems among typically developing children. However, previous studies have not examined the association
* Corresponding author at: Thompson Center for Autism and Neurodevelopmental Disorders, University of Missouri, 205 Portland Street, Columbia, MO 65211, United States. Tel.: +1 573 884 8502; fax: +1 573 884 6421. E-mail addresses: [email protected] (M.O. Mazurek), [email protected] (C.R. Engelhardt). 1750-9467/$ – see front matter ß 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.rasd.2012.09.008
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
317
between these variables in children with ASD. The current study not only fills this important gap in the literature, but it also examines the extent to which preferences for particular video game genres are associated with behavior problems among individuals with ASD. Emerging research has shown that children with ASD spend the majority of their discretionary time using electronic media, including video games (Orsmond & Kuo, 2011; Shane & Albert, 2008). Adolescents with ASD are also more likely than those with other types of disabilities to spend most of their free time playing video games (Mazurek, Shattuck, Wagner, & Cooper, 2012). In addition, a recent study found that children with ASD spent significantly more hours per day playing video games and demonstrated significantly higher scores on a measure of problematic video game use than their typically developing siblings (Mazurek & Wenstrup, 2012). Thus, it appears that children with ASD are at an increased risk for problematic patterns of video game play. However, studies have not yet examined whether video game use relates to behavior problems in children with ASD. Therefore, the current study focuses on: the amount of time spent playing video games, problematic game play patterns, and video game genre, each of which has been associated with negative outcomes in previous studies in the general population. 1.1. Amount of video game play and behavior Studies of video game use have examined a variety of aspects of game play that appear to have distinct contributions to an individual’s out-of-game (i.e., real world) behavior. At the most basic level of measurement, the amount of time an individual spends playing video games has been extensively studied in previous research. For example, Chan and Rabinowitz (2006) found that adolescents who spent more than 1 h per day playing video games had significantly greater symptoms of inattention and hyperactivity, and greater symptoms of behavioral addiction. Core elements of behavioral addiction include salience (e.g., cravings or preoccupation), tolerance, withdrawal, relapse, mood modification, and conflict (see Gentile, 2009). Swing, Gentile, Anderson, and Walsh (2010) also found that time spent playing video games was significantly associated with subsequent attention problems across a 13-month period in adolescence, even after controlling for earlier attention problems. More recently, Gentile, Swing, Lim, and Khoo (2012) examined the longitudinal relations among video game use, attention problems and impulsivity in a large sample of children and adolescents. Over a 3-year period, the results indicated that time spent playing video games was significantly related to subsequent attention problems and impulsivity even after controlling for initial levels of attention/impulsivity and demographic variables. Furthermore, although video game violence was associated with attention problems and impulsivity, total video game exposure emerged as the most robust predictor of such problems. 1.2. Video game content, problematic game use, and behavior A large body of research has also demonstrated a clear effect of both video game content and genre on behavior problems among typically developing children and adolescents. The vast majority of this research over the past several decades has focused on the correlates and consequences of violent video game use. Numerous studies have shown a clear causal relationship between short- and long-term exposure to violent video games, particularly First-Person Shooter games, and increases in aggressive thinking, aggressive affect, and aggressive behavior (for a review see Anderson, 2004; Anderson et al., 2010). More recently, video game researchers have also begun to investigate pathological or problematic video game use, which has been conceptualized as a form of behavioral addiction (Gentile, 2009; Tejeiro Salguero & Mora´n, 2002). Studies examining the measurement of this construct have found support for construct validity and reliability, indicating that problematic video game play is a distinct construct that can be reliably assessed (Gentile, 2009; King, Delfabbro, & Zajac, 2011). Cross-sectional studies have demonstrated significant associations between problematic video game use and problem behaviors. For example, in a large sample of 804 adolescents, participants who were classified as pathological gamers were more likely to demonstrate aggressive behavior than those who did not demonstrate pathological gaming patterns (Gru¨sser, Thalemann, & Griffiths, 2007). Similar associations between online gaming addiction and aggression have also been found in a large sample of young adults (Kim, Namkoong, Ku, & Kim, 2008). Anecdotal reports from families are consistent, suggesting that disruption of game play is often an antecedent for aggressive outbursts among adolescents who demonstrate pathological patterns of play (Young, 2009). Recently, Lemmens, Valkenburg, and Peter (2011) also found that problematic video game use, regardless of violent content, predicted longitudinal increases in physical aggression among a large sample of adolescent boys. Problematic video game and internet use have also been associated with inattention and impulsivity among both adolescents (Rehbein, Kleimann, & Mo¨ssle, 2010) and adults (Meerkerk, van den Eijnden, Franken, & Garretsen, 2010; Yen, Yen, Chen, Tang, & Ko, 2009). Similarly, in a sample of children with ADHD, children with higher scores on a measure of problematic video game play demonstrated significantly greater problems with hyperactivity, aggression, and externalizing behaviors (Bioulac, Arfi, & Bouvard, 2008). In addition to the previously reported negative consequences associated with violent games (Anderson et al., 2010), studies have also found that other video game genres, particularly Role-Playing games, are related to the potential for problematic video game use and negative consequences. Role-Playing games contain particular game design features that
318
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
may make them especially prone to addictive patterns of use (King, Delfabbro, & Griffiths, 2011). For example, these games have high reward schedules, including both virtual rewards (such as scores, achievements, and in-game items) and social rewards (including peer attention and approval in online multi-player games). In addition, because players must create, maintain, and advance characters over time and have the option to explore open-ended virtual worlds, Role-Playing games have the potential to be more time-consuming than other genres, possibly increasing the likelihood of problematic use patterns. Given these features, it is not surprising that Role-Playing games have been highly associated with the development of problematic game play patterns. In a large sample of Korean adolescents, Role-Playing game users had significantly greater internet addiction scores as compared to other game genres, and Role-Playing games were more likely to be the preferred game genre among individuals classified as high-risk for internet addiction (Lee et al., 2007). In a randomized longitudinal study, Smyth (2007) assigned young adults into gaming genre groups (arcade, console, solo computer, or Role-Playing) for 1 month. The results indicated that the Role-Playing group differed significantly from the other genre groups, with reduced sleep quality, reduced overall health, and increased interference of game play with socialization. In a large population-based study of German adolescents, both online Role-Playing and First-Person Shooter game genre players were significantly more likely than players of other game types to demonstrate video game dependence, and multivariate analyses revealed that Role-Playing game use remained a significant predictor even after accounting for a number of additional psychological and demographic predictors (Rehbein et al., 2010). 1.3. Current study In summary, previous findings from the general population indicate that particular aspects of video game play are strongly associated with externalizing behavior problems. Given that children with ASD are at increased risk for these behavior problems, and that they spend a significant amount of time playing video games, this topic is highly relevant and clinically important. Surprisingly, previous research has not yet explored the relations among these variables in children with ASD. Thus, the purpose of the current study was to examine the associations between video game use and behavior problems in a sample of children with ASD. Our primary hypotheses were: (1) the amount of time spent playing video games would be positively associated with problem behaviors, (2) problematic video game use would be positively associated with problem behaviors, and (3) game genre, particularly First-Person Shooter and Role-Playing games, would be associated with problem behaviors. A secondary aim of the study was to examine the relative contributions of our hypothesized game genres to problem behaviors when considered jointly within multivariate models. Previous studies have revealed significant gender differences in both patterns and consequences of video game play. Studies have consistently shown that males spend greater amounts of time playing video games (Gentile, 2009; Marshall, Gorely, & Biddle, 2006), are at greater risk for pathological game play (Gentile, 2009; Gentile et al., 2011; Lemmens et al., 2011), and express different, more reward-focused reasons for game play than females (Ko, Yen, Chen, Chen, & Yen, 2005). Given these findings, the current study examined game-play patterns among boys only. 2. Methods 2.1. Participants The sample for the current study included parents of 169 boys with ASD ranging in age from 8 to 18 years (M = 12.1; SD = 2.8) who were recruited with the assistance of a national open enrollment ASD registry, the Interactive Autism Network (IAN) Research Database at Kennedy Krieger Institute Baltimore, Maryland, sponsored by the Autism Speaks Foundation. Enrollment into IAN involves the completion of a battery of questionnaires regarding the child’s ASD diagnosis, primary and associated symptoms, and other aspects of child and family functioning. Recent studies examining the validity of parent-reported ASD diagnosis among the IAN sample have reported a high degree of concordance with both external clinical documentation and with gold-standard diagnostic tools (Daniels et al., 2012; Lee et al., 2010). A complete list of IAN survey questions and instruments may be found at: http://www.iancommunity.org/cs/ian_research_questions/ ian_research_questions. Participants for the current study were recruited by email, and parents completed all measures online using a web-based format. Eligibility requirements included age range (8–18) and a parent-reported professional diagnosis of ASD, including Autism or Autistic Disorder (52.7%), Asperger’s Disorder (28.4%), or Pervasive Developmental Disorder, NOS (18.9%). The majority of the sample was Caucasian (89.3%). Regarding parent-reported intellectual functioning, 8.9% of the sample was reported to have a previously assessed IQ of 70 or below. Analyses of variance (ANOVA) indicated that the group with IQ below 70 did not differ from those above 70 with regard to any study-related variables. 2.2. Measures Parents completed a series of questions developed for the current study including demographic information, diagnostic and functional information, and specific information about activity and screen-based media use, as described below.
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
319
2.2.1. Video game use Parents reported the average number of hours per day their children spent ‘‘playing video or computer games.’’ Parents provided separate estimates for a ‘‘typical weekday’’ and ‘‘typical weekend day.’’ An average daily use variable was created, consistent with previous studies (Orsmond & Kuo, 2011; Zimmerman & Christakis, 2005), by multiplying the weekday response by 5, multiplying the weekend response by 2, and dividing the sum of these by 7. 2.2.2. Video game genre Parents also listed the three most common video games their children had played in the past month. Games were coded into mutually exclusive categories primarily using descriptions found on the Entertainment Software Rating Board website (http://www.esrb.org/index-js.jsp). These genre descriptions were also cross-referenced with popular gaming websites, specifically Gamespot (http://www.gamespot.com/) and IGN (http://www.ign.com/). The resulting genre categories included: (1) Action and Action-Adventure, (2) Adventure, (3) Role-Playing, (4) Strategy, (5) Puzzle and Mini-game, (6) Educational, (7) Fighting, (8) First-Person Shooter, (9) Music, (10) Platform, (11) Racing, (12) Simulation, and (13) Sports Simulation. 2.2.3. Problematic video game use Problematic patterns of video game play were assessed using a modified version of the Problem Video Game Playing Test (PVGT) (King, Delfabbro, & Zajac, 2011). The original 20-item PVGT was developed as a self-report measure for adolescents and adults, which assesses problematic aspects of game-playing based on the behavioral addiction model (Griffiths, 2005), including salience, mood modification, withdrawal, tolerance, relapse, and conflict. Items are rated on a 5-point Likert-type scale ranging from Never to Always. Modifications for the current study included wording adjustments to increase relevance for younger participants, and modification from first- to parent-report format. One of the original items (item 20, focusing on mood modification) was dropped from the scale for the purpose of the current study based on parent-reported difficulty in responding accurately to the item during pilot testing of the modified instrument. Specifically, the item assesses whether an individual plays games as a means of changing his or her mood, and parents indicated difficulty in determining this. As a result, 19 items were retained in the final modified version. Cronbach’s alpha coefficients were examined to assess internal consistency of the modified scale. The results indicated strong internal consistency, with alpha of .94. Item-total correlations ranged from 0.46 to 0.81. A total PVGT score, calculated as the sum of all item scores, was used in subsequent analyses. 2.2.4. Attention problems, impulsivity, and oppositional behavior The Vanderbilt Attention Deficity/Hyperactivity Disorder Parent Rating Scale (VADPRS) (Wolraich, Hannah, Baumgaertel, & Feurer, 1998) was used to assess symptoms of inattention, hyperactivity/impulsivity, and oppositional defiant behaviors. The VADPRS is a widely used parent-report rating scale used to assess symptoms of ADHD, ODD, and other clinically relevant symptoms. For the purposes of the current study, items from the Inattention (9 items), Hyperactivity/Impulsivity (9 items), and Oppositional Defiant (8 items) subscales were administered. Items are rated on a 4-point Likert-type scale ranging from 0 (Never) to 3 (Very Often). The VADPRS has been previously found to have good internal consistency, validity, and reliability (Wolraich et al., 2003). In the current sample, Cronbach’s alpha coefficients were .88 for the Inattention subscale, .87 for the Hyperactivity/Impulsivity subscale, and .88 for the Oppositional Defiant subscale, indicating good internal consistency for all subscales in the current population. 2.3. Data analyses Bivariate relationships between continuous variables were examined using Pearson’s correlations. Preference for game genre was examined using percentages across the sample of those who had played video games within the past month. Percentages were calculated for each game genre type, including percentage reporting each type as their #1 most frequently played game, and percentage who reported each type within the top three most frequently played games. Given that previous research has revealed genre-specific effects on behavioral functioning (i.e., Role-Playing and Shooter style games), we focused on these specific game types in subsequent analyses. Two dichotomous variables were created to indicate whether or not this type of game genre (Role-Playing and Shooter, respectively) was reported as one of the top three most frequently played games. Group comparisons between those who did and did not report playing each of these game genre types (among their top three games) were conducted using ANOVA for continuous variables. Cohen’s d is reported as a measure of effect size. Levene’s statistic was significant in some cases, indicating that the assumption of homogeneity of variances for ANOVA was not met. Welch adjusted F statistics are reported in these cases. Next, linear regression analyses were conducted to examine the relative contributions of video game play variables to the cross-sectional prediction of behavior problems. Separate regression models were computed for each dependent variable of interest (including inattention, hyperactivity, and oppositional/defiant symptoms), controlling for age. Additional independent variables included daily hours of video game play, PVGT score, Shooter game play (dichotomous), and Role-Playing game play (dichotomous).
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
320 Table 1 Video game genre preference. Game genre
Percenta reporting genre as #1 game
Percent reporting genre as one of the top 3
Most frequent game title by genre
Action Platform Shooter Puzzle/Mini-Game Role-Playing Sports Simulation Racing Educational Simulation Adventure Strategy Fighting Music
15.7 14.3 12.9 10.7 9.3 8.6 6.4 6.4 5.7 3.6 3.6 2.1 0.7
30.7 25.0 20.7 16.4 20.0 12.9 17.9 8.6 13.6 7.1 6.4 6.4 1.4
Star Wars series Super Mario Bros. series Call of Duty series Angry Birds Pokemon series Madden NFL series Mario Kart series PBS Kids Online Games The Sims Legend of Zelda series Plants vs. Zombies Super Smash Bros. Brawl Guitar Hero
a
Percentage of sample of children who have played video games within past month, n = 140.
3. Results 3.1. Video game use patterns Results indicated that children in current sample spent an average of 2.4 h per day playing video games (M = 2.4, SD = 1.7), and that daily video game use was positively correlated with age (r = .23, p = .003). Table 1 shows information regarding video game genre preferences. An examination of the most frequently reported game genre indicates that the Action category was the most frequently reported first choice, followed by Platform and Shooter, and these categories were also the most frequently reported among the top three game categories. As shown in Table 2, video game play variables were also moderately related with one another, with significant positive correlations between daily hours of video game play and PVGT scores (r = .314, p < .001). Also, as shown in Table 3, boys who were reported to play Shooter
Table 2 Means, standard deviations and correlation coefficients (n = 169). Variable
M
SD
Range
Age Video game hours/day PVGT score Inattention Hyperactivity Oppositional defiant
12.1 2.4 39.9 17.0 12.0 8.1
2.8 1.7 11.6 6.1 6.7 5.5
8–18 0–7.4 19–74 1–27 0–27 0–24
1
2 .23** .12 .04 .16* .11
.31*** .03 .15 .07
3
4
5
.41*** .07 .34***
.41*** .32***
.39***
* p < .05. ** p < .01. *** p < .001. Table 3 Group comparisons by game genre. Variable
Age Video game hours/day PVGT score Inattention Hyperactivity Oppositional defiant Age Video game hours/day PVGT Score Inattention Hyperactivity Oppositional defiant
Yes M (SD) Shooter 14.2 (2.5) 3.0 (1.5) 45.0 (12.3) 16.8 (5.5) 11.1 (6.6) 9.7 (4.9) Role-Playing 13.0 (2.4) 3.3 (1.9) 45.4 (11.9) 17.7 (5.3) 10.6 (5.4) 10.7 (6.7)
No M (SD)
F
p
Cohen’s d
11.6 2.3 38.7 17.1 12.2 7.8
(2.7) (1.7) (11.2) (6.2) (6.7) (5.5)
23.0 4.9 7.1 0.04 0.6 3.1
<.001 .03 .008 .83 .44 .08
1.00 0.47 0.53 0.47 0.16 0.37
11.9 2.2 38.7 16.9 12.3 7.6
(2.9) (1.6) (11.3) (6.3) (6.9) (5.0)
3.6 7.2a 7.9 0.4 2.1a 5.4a
.06 .01 .005 .51 .16 .03
0.41 0.60 0.58 0.14 0.27 0.52
Note: Group comparisons on continuous variables conducted with ANOVA. Cohen’s d is reported for all effect sizes, with positive values indicating higher scores in the group playing the specific game. a The adjusted Welch F-ratio is reported due to unequal variance.
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
321
Table 4 Relations among video game variables and behavior: linear regression analyses. Independent variables Inattention Equation Age Daily hours of video game play PVGT score Shooter genre Role-Playing genre Oppositional defiant Equation Age Daily hours of video game play PVGT score Shooter genre Role-Playing genre
R2
F
.19
7.22***
.15
B
SE B
b
0.06 0.43 0.24 1.34 0.32
0.17 0.28 0.04 1.22 1.19
.03 .12 .47*** .09 .02
0.09 0.30 0.15 1.03 2.32
0.16 0.26 0.04 1.14 1.12
.05 .09 .31*** .07 .16*
5.4***
* p < .05. *** p < .001.
games spent significantly more hours per day playing video games (p = .03) and demonstrated significantly higher PVGT scores (p = .008) than boys whose parents did not list Shooter games among their top three most frequently played games. Similarly, boys who played Role-Playing games also spent significantly more hours per day playing video games (p = .01) and demonstrated higher PVGT scores (p = .005) than those who did not play Role-Playing games. 3.2. Video game use and problem behaviors Bivariate analyses were conducted to examine the primary study hypotheses. Contrary to our first prediction, no significant correlations were found between daily hours of video game play and inattention, hyperactivity, or oppositional defiant behavior (see Table 2). However, we found partial support for our second prediction. Specifically, PVGT score was significantly positively correlated with inattentive symptoms (r = .406, p < .001), and oppositional/defiant symptoms (r = .340, p < .001), but not with hyperactivity. Consistent with our third prediction, boys who were reported to play Role-Playing games had significantly greater oppositional behaviors (p = .03), as shown in Table 3. Similarly, boys who played Shooter games also had greater oppositional behaviors; however, this difference did not reach statistical significance (p = .08). However, neither Role-Playing nor Shooter game genres were associated with higher scores on the inattention or hyperactivity scale. 3.3. Multivariate analyses To examine the relative contributions of each video game variable when considered jointly within multivariate models, separate linear regression models were conducted for each problem behavior variable (inattention, hyperactivity, and oppositional symptoms), while controlling for age. Additional independent variables included average daily hours of video game play, PVGT score, Shooter game play, and Role-Playing game play. The regression model for hyperactivity symptoms was not statistically significant, indicating that the model was not a good fit for the data. However, as shown in Table 4, the models for inattention and oppositional defiant symptoms were both significant. In the model predicting inattention, the results indicated that a significant main effect was observed for PVGT score (p < .001), but not for age, video game hours, or either video game genre. For the model predicting oppositional behavior, the results showed significant main effects of both PVGT score (p < .001) and Role-Playing genre (p = .039), but no effects were observed for age, video game hours, or Shooter genre. To show that our predicted game genre effects are unique to First-Person Shooter games and Role-Playing games, we also conducted similar regression models for game genres that, in theory, should not be related to behavior problems. Consistent with this hypothesis, these models revealed that none of the remaining game genres predicted greater behavior problems (ps > .05). In fact, even after controlling for all other variables in the model, Educational and Sports games predicted less oppositional defiant symptoms (p < .05), and Sports games predicted less hyperactivity (p < .05). 4. Discussion The current study is the first to describe the relationships between aspects of video game play and problem behaviors among children with ASD. In a sample of 169 boys with ASD, the results indicated that amount of game play alone was not associated with problem behaviors. Rather, the most reliable predictors of problem behaviors were shown to be video game genre and problematic, or addictive, qualities of play. Specifically, significant positive relationships were found between problematic video game use and both inattention and oppositional symptoms. Furthermore, boys with ASD who primarily played Role-Playing games had significantly greater oppositional behaviors
322
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
than those who did not play such games. Interestingly, the results from multivariate models added further support to our prediction that Role-Playing games would be uniquely associated with problem behaviors. Even when controlling for other variables (i.e., age, amount of time spent playing games, and problematic video game patterns), Role-Playing game genre remained a significant cross-sectional predictor of oppositional behavior. Furthermore, the results of subsequent analyses indicated that children who played game genres that should be theoretically unrelated to poor behavioral control (i.e., Sports and Educational games), demonstrated fewer oppositional behaviors and less hyperactivity than those who primarily played other game genres. The results of this study are consistent, in part, with findings from the general population. For example, the significant associations between problematic video game play, inattention, and oppositional behavior in the current sample are similar to those reported in adolescents and adults without ASD (Bioulac et al., 2008; Rehbein et al., 2010; Yen et al., 2009). Interestingly, however, hyperactivity was not significantly associated with either problematic video game use or video game genre. This is in contrast to previously reported associations between problematic game and internet use and hyperactivity/ impulsivity (Bioulac et al., 2008; Meerkerk et al., 2010; Yen et al., 2009). Future studies of video game use in children with ASD would benefit from the inclusion of comparison groups, including both typically developing children and those with ADHD. This would help to further delineate potentially distinct profiles of video game use and behavior among different diagnostic groups. Our finding that Role-Playing games were highly associated with problematic video game play was also consistent with previous research. Specifically, others have also found that Role-Playing games are associated with problematic game use among individuals without ASD (Smyth, 2007). Given their tendency to engage in restricted and repetitive patterns of activity (American Psychiatric Association, 2000), children with ASD may be at particular risk for developing problematic, or addictive, game play patterns. In fact, in a previous study, we found that children with ASD demonstrated significantly greater levels of problematic video game play than typically developing children (Mazurek & Wenstrup, 2012). With this in mind, Role-Playing games may contribute to an even greater potential for problematic game use patterns among children with ASD, given their particular game-design features. Furthermore, preoccupation with video games and trouble disengaging from them may serve as antecedents for disruptive behavior, as has been anecdotally reported among other children (Young, 2009). Overall, it appears that for children with ASD, the potential for preoccupation represents a key game play quality that relates closely with the occurrence of problem behaviors. Interestingly, violent video game use did not emerge as a significant predictor of either oppositional behavior or inattention in either bivariate or multivariate models. Consistent with Rehbein et al. (2010), we found that First-Person Shooter games were significantly associated with problematic game play patterns; however, they did not relate specifically to behavior problems. The reasons for this are not clear. One potential explanation is that the problem behaviors we targeted did not include measures of physical aggression. Although oppositional symptoms include affective anger and defiance, no overt behavioral symptoms of aggression were examined. Future studies among children with ASD should include measures of aggression, specifically, in order to determine if associations between video game violence and aggressive thoughts and behavior are similar or different from those in the general population (Anderson et al., 2010). Theoretical models proposed to account for these previously documented associations between video game violence exposure and aggression often include social learning (Bandura, 1978) and social-cognitive components (Anderson & Bushman, 2002). It is possible that these models require further study among children with ASD, particularly given their deficits in social learning (Vivanti & Rogers, 2011). Experimental paradigms would be most helpful in order to determine if violent video game exposure results in changes in aggressive thoughts or behavior among children with ASD. 4.1. Limitations and future directions It should be noted that the current study relied on parent-report for all measures. In future studies, a more thorough characterization of the sample would be ideal, including measures of core ASD symptoms, cognitive functioning, and language. Although parent-report is often considered to be more valid than self-report in assessment of symptoms and behavior among children with ASD (Lopata et al., 2010; Mazefsky, Kao, & Oswald, 2011), studies examining the relative concordance between parent- and self-report on measures of video game use would be very informative, especially if considered in multi-trait, multi-method models. Finally, the use of alternative measures of video game use, including time use diaries, direct observation, and electronic monitoring techniques would be helpful (Vandewater & Lee, 2009). Finally, it is important to note that the current study was cross-sectional in design; therefore, causality cannot be determined. It is possible that children with pre-existing behavior problems are more inclined to play video games for longer periods of time and in a more intense manner. Alternatively, particular patterns of video game play may directly contribute to the development of behavior problems. It is also possible that these problems have bi-directional relationships. Longitudinal prospective studies and experimental paradigms are needed to more carefully evaluate these issues. Future research in this area is critical in order to inform video game use recommendations for both parents and clinicians. As emerging research investigates the effectiveness of video-game based interventions for improving functional outcomes, it will be equally important to understand the mechanisms and nature of problematic aspects of game play among children with ASD.
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
323
4.2. Conclusions The results of this study provide important new information about the relationships between video game use and behavior problems in children with ASD. Although anecdotal concerns about problematic video game use have been reported by clinicians and parents, this is the first empirical study on the topic. Our findings revealed that problematic video game use is highly associated with behavior problems among boys with ASD, and that boys who play Role-Playing games are especially likely to demonstrate co-occurring oppositional behavior. These results highlight the clinical importance of examining video game use patterns among children with ASD and indicate a need for future experimental and longitudinal research in this area. References American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders – Fourth edition, text revision. Washington, DC: American Psychiatric Association. Anderson, C. A. (2004). An update on the effects of playing violent video games. Journal of Adolescence, 27, 113–122. Anderson, C. A., & Bushman, B. J. (2002). Human aggression. Annual Review of Psychology, 53, 27–51. Anderson, C. A., Shibuya, A., Ihori, N., Swing, E. L., Bushman, B. J., Sakamoto, A., et al. (2010). Violent video game effects on aggression, empathy, and prosocial behavior in Eastern and Western countries: A meta-analytic review. Psychological Bulletin, 136, 151–173. Bandura, A. (1978). Social learning theory of aggression. Journal of Communication, 28, 12–29. Bioulac, S., Arfi, L., & Bouvard, M. P. (2008). Attention deficit/hyperactivity disorder and video games: A comparative study of hyperactive and control children. European Psychiatry, 23, 134–141. Chan, P. A., & Rabinowitz, T. (2006). A cross-sectional analysis of video games and attention deficit hyperactivity disorder symptoms in adolescents. Annals of General Psychiatry, 5, 16. Daniels, A., Rosenberg, R., Anderson, C., Law, J., Marvin, A., & Law, P. (2012). Verification of parent-report of child autism spectrum disorder diagnosis to a webbased autism registry. Journal of Autism and Developmental Disorders, 42, 257–265. Frazier, J. A., Biederman, J., Bellordre, C. A., Garfield, S. B., Geller, D. A., Coffey, B. J., et al. (2001). Should the diagnosis of Attention-Deficit/Hyperactivity disorder be considered in children with Pervasive Developmental Disorder? Journal of Attention Disorders, 4, 203–211. Gadow, K. D., Devincent, C. J., Pomeroy, J., & Azizian, A. (2005). Comparison of DSM-IV symptoms in elementary school-age children with PDD versus clinic and community samples. Autism, 9, 392–415. Gentile, D. A. (2009). Pathological video-game use among youth ages 8 to 18: A national study. Psychological Science, 20, 594–602. Gentile, D. A., Choo, H., Liau, A., Sim, T., Li, D., Fung, D., et al. (2011). Pathological video game use among youths: A two-year longitudinal study. Pediatrics, 127, e319–e329. Gentile, D. A., Swing, E. L., Lim, C. G., & Khoo, A. (2012). Video game playing, attention problems, and impulsiveness: Evidence of bidirectional causality. Psychology of Popular Media Culture, 1, 62–70. Griffiths, M. D. (2005). A components model of addiction within a biopsychosocial framework. Journal of Substance Use, 10, 191–197. Gru¨sser, S. M., Thalemann, R., & Griffiths, M. D. (2007). Excessive computer game playing: Evidence for addiction and aggression? CyberPsychology & Behavior, 10, 290–292. Kanne, S., & Mazurek, M. (2011). Aggression in children and adolescents with ASD: Prevalence and risk factors. Journal of Autism and Developmental Disorders, 41, 926–937. Kim, E. J., Namkoong, K., Ku, T., & Kim, S. J. (2008). The relationship between online game addiction and aggression, self-control and narcissistic personality traits. European Psychiatry, 23, 212–218. King, D., Delfabbro, P., & Griffiths, M. (2011). The role of structural characteristics in problematic video game play: An empirical study. International Journal of Mental Health and Addiction, 9, 320–333. King, D., Delfabbro, P., & Zajac, I. (2011). Preliminary validation of a new clinical tool for identifying problem video game playing. International Journal of Mental Health and Addiction, 9, 72–87. Ko, C.-H., Yen, J.-Y., Chen, C.-C., Chen, S.-H., & Yen, C.-F. (2005). Gender differences and related factors affecting online gaming addiction among Taiwanese adolescents. Journal of Nervous and Mental Disease, 193, 273–277. Lee, H., Marvin, A. R., Watson, T., Piggot, J., Law, J. K., Law, P. A., et al. (2010). Accuracy of phenotyping of autistic children based on internet implemented parent report. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 153B, 1119–1126. Lee, M.-S., Ko, Y.-H., Song, H.-S., Kwon, K.-H., Lee, H.-S., Nam, M., et al. (2007). Characteristics of internet use in relation to game genre in Korean adolescents. CyberPsychology & Behavior, 10, 278–285. Lemmens, J., Valkenburg, P., & Peter, J. (2011). The effects of pathological gaming on aggressive behavior. Journal of Youth and Adolescence, 40, 38–47. Lopata, C., Toomey, J., Fox, J., Volker, M., Chow, S., Thomeer, M., et al. (2010). Anxiety and depression in children with HFASDs: Symptom levels and source differences. Journal of Abnormal Child Psychology, 38, 765–776. Marshall, S. J., Gorely, T., & Biddle, S. J. H. (2006). A descriptive epidemiology of screen-based media use in youth: A review and critique. Journal of Adolescence, 29, 333–349. Mayes, S. D., Calhoun, S. L., Aggarwal, R., Baker, C., Mathapati, S., Anderson, R., et al. (2012). Explosive, oppositional, and aggressive behavior in children with autism compared to other clinical disorders and typical children. Research in Autism Spectrum Disorders, 6, 1–10. Mayes, S. D., Calhoun, S. L., Mayes, R. D., & Molitoris, S. (2012). Autism and ADHD: Overlapping and discriminating symptoms. Research in Autism Spectrum Disorders, 6, 277–285. Mazefsky, C. A., Kao, J., & Oswald, D. P. (2011). Preliminary evidence suggesting caution in the use of psychiatric self-report measures with adolescents with highfunctioning autism spectrum disorders. Research in Autism Spectrum Disorders, 5, 164–174. Mazurek, M. O., Shattuck, P. T., Wagner, M., & Cooper, B. (2012). Prevalence and correlates of screen-based media use among youths with autism spectrum disorders. Journal of Autism and Developmental Disorders, 42, 1757–1767. Mazurek, M. O., & Wenstrup, C. (2012). Television, video game and social media use among children with ASD and typically developing siblings. Journal of Autism and Developmental Disorders, http://dx.doi.org/10.1007/s10803-012-1659-9. Meerkerk, G. J., van den Eijnden, R. J. J. M. , Franken, I. H. A., & Garretsen, H. F. L. (2010). Is compulsive internet use related to sensitivity to reward and punishment, and impulsivity? Computers in Human Behavior, 26, 729–735. Orsmond, G. I., & Kuo, H.-Y. (2011). The daily lives of adolescents with an autism spectrum disorder. Autism, 15, 579–599. Rehbein, F., Kleimann, M., & Mo¨ssle, T. (2010). Prevalence and risk factors of video game dependency in adolescence: Results of a German nationwide survey. CyberPsychology, Behavior & Social Networking, 13, 269–277. Shane, H., & Albert, P. (2008). Electronic screen media for persons with autism spectrum disorders: Results of a survey. Journal of Autism and Developmental Disorders, 38, 1499–1508. Smyth, J. M. (2007). Beyond self-selection in video game play: An experimental examination of the consequences of Massively Multiplayer Online Role-Playing game play. CyberPsychology & Behavior, 10, 717–721.
324
M.O. Mazurek, C.R. Engelhardt / Research in Autism Spectrum Disorders 7 (2013) 316–324
Swing, E. L., Gentile, D. A., Anderson, C. A., & Walsh, D. A. (2010). Television and video game exposure and the development of attention problems. Pediatrics, 126, 214–221. Tejeiro Salguero, R. A., & Mora´n, R. M. B. (2002). Measuring problem video game playing in adolescents. Addiction, 97, 1601–1606. Vandewater, E. A., & Lee, S.-J. (2009). Measuring children’s media use in the digital age: Issues and challenges. American Behavioral Scientist, 52, 1152–1176. Vivanti, G., & Rogers, S. J. (2011). Action understanding and social learning in autism: A developmental perspective. Life Span and Disability, 14, 7–29. Wolraich, M. L., Hannah, J. N., Baumgaertel, A., & Feurer, I. D. (1998). Examination of DSM-IV criteria for attention deficit/hyperactivity disorder in a county-wide sample. Journal of Developmental and Behavioral Pediatrics, 19, 162–168. Wolraich, M. L., Lambert, W., Doffing, M. A., Bickman, L., Simmons, T., & Worley, K. (2003). Psychometric properties of the Vanderbilt ADHD Diagnostic Parent Rating Scale in a referred population. Journal of Pediatric Psychology, 28, 559–568. Yen, J.-Y., Yen, C.-F., Chen, C.-S., Tang, T.-C., & Ko, C.-H. (2009). The association between adult ADHD symptoms and internet addiction among college students: The gender difference. CyberPsychology & Behavior, 12, 187–191. Young, K. (2009). Understanding online gaming addiction and treatment issues for adolescents. American Journal of Family Therapy, 37, 355–372. Zimmerman, F. J., & Christakis, D. A. (2005). Children’s television viewing and cognitive outcomes: A longitudinal analysis of national data. Archives of Pediatric and Adolescent Medicine, 159, 619–625.