Video Game Use Among Children and Adolescents With Attention Deficit Hyperactivity Disorder

Electronic media use by children and adolescents is growing each year. From 2004 to 2009, electronic daily media exposure increased from six hours and twentyone minutes to seven hours and thirty-eight minutes. The ubiquity of electronic media among youth is apparent in our technology-driven culture; however, more research on video gaming patterns and characteristics of children and adolescents with developmental disabilities is warranted specifically, individuals with Attention Deficit Hyperactivity Disorder (ADHD). As of 2011, the number of children and adolescents with ADHD in schools represents 6.4 million in the USA. Given that ADHD is a prevalent disability in children and adolescents, there is a need to be able to effectively discern the most time and cost effective interventions for youth with ADHD, including those that are electronically mediated. Thus, this study examines parent-reported video game use among children and adolescents with ADHD collected from a clinical sample, and compares their rates of use with previously reported data from national samples. Parents completed the Children’s Use of Video Games and Digital Media, comprised of 13 questions that assessed ADHD type characteristics expressed during activities, duration spent across different activities, parent involvement, perceptions, and parent use of video games. The present study found that only weekend/vacation days video game play for youth with ADHD was reported by parents as more frequent than video game play among the national sample reported by Rideout and colleagues. Male youth statistically played more video games than female youth, and the only statistical age difference was found among 11-14 year-old children/adolescents and 5-7 year-old children, with older children/adolescents playing more video games. The majority of parents in the present sample endorsed that their children demonstrated fewer ADHD behaviors during video game play (i.e., less inattention, hyperactivity, and disorganization). In conclusion, the variability of video game and media use indicate potential areas to capitalize on teachable moments for ADHD youth while in the home. Findings from this study are expected to inform future research and practice with children with ADHD, particularly in the areas of effective parenting, intervention development, and the use of technology-based learning strategies.

Average weekday and weekend/vacation time spent in tech activities compared to a national sample (Rideout et al., 2010)

Statement of the Problem
Electronic media use by children and adolescents is growing each year. From 2004 to 2009, daily electronic media exposure increased from six hours and twentyone minutes to seven hours and thirty-eight minutes (Rideout, Foehr, & Roberts, 2010). The ubiquity of electronic media among youth is apparent in our technologydriven culture (Alvermann, 2013;Lim, Zhao, Tondeur, Chai, & Tsai, 2013;Pera, 2013). However, research is lacking on video gaming patterns and characteristics of children and adolescents with developmental disabilities -specifically, individuals with Attention Deficit Hyperactivity Disorder (ADHD). This area is important to study because technology mediated interventions, such as those possible with video games, hold promise for ADHD youth (Barkley, 2014;DuPaul & Stoner, 2014).

Play and video game use
Learning is a process of acquiring information through experience that results in behavior change (Domjan, 2014). Generally, children and adolescent learn via their academic experiences, social interactions, and explored interests (Anning & Edwards, 2006;Hansen, 2003). Primarily children learn through experiences such as social interactions, manipulation of objects, interactive instruction, and play-based learning (Bergen & Fromberg, 2009). As compared with childhood, adolescent learning is more self-directed and socially constructed (Hansen, 2003). Irrespective of developmental periods, play can nevertheless support learning across childhood and adolescence (Bodrova & Leong, 2003;Brotherson, 2009).
Play can be defined as a self-selected activity, engaged in independently or with others, that elicits gratification (Bergen & Fromberg, 2009;VanderVen, 2008).
Plato discussed play as a mechanism for learning rules and developing skills that would prove useful to later adult functioning (D'Angour, 2013). Contemporary research further suggests that learning through play promotes healthy cognitive, social, and emotional functioning from early childhood through adolescence (Bergen & Fromberg, 2009;Drew, Christie, Johnson, Meckley, & Nell, 2008;Ginsburg, 2007;Gronlund, 2006). While play can take on many different forms and expressions, play is often conceptualized as occurring in five stages: (a) onlooker, (b) solitary, (c) parallel, (d) associative, and (e) cooperative play (Brotherson, 2009). Onlooker play is defined as passive play and not engaging with others playing. Solitary play consists of independent play. Parallel play consists of playing alongside others but without active interactive engagement. Associative play consists of two or more individuals working toward independent goals but interacting and playing together. Cooperative play requires the players to work together to achieve a common goal (Brotherson, 2009).
Although the stages of play are conceptualized from a child perspective, these stages can be conceptualized in terms of adolescent play as well. For example, in considering team sports, such as, football, players work toward common goals (e.g., scoring a touchdown; preventing the other team from doing so). In contemporary society, the nature of play influencing children and adolescents' experiences is replete with the presence of electronic media and technology use (e.g., video games, smart phones, television). Thus, technology is a major influence on the lives of children and adolescents in play and other aspects of daily life.
The development of play-based technology has not only created a new medium for learning in all children through video games but also for their parents as well. As reported by the Entertainment Software Association (ESA), an estimated 59 percent of Americans play video games with approximately 30 percent who are 18 years and younger (ESA, 2014). The ESA further reports that within the 30 percent of youth who are playing video games, 42 percent of parents play video and computer games at least weekly. A majority of parents (75%) report they believe video game play with their children provides an opportunity to interact with them (ESA). As compared with study compiled by the ESA, Lenhart and colleagues (Lenhart et al., 2008) found a higher number of reported video game use. These researchers (Lenhart et al.) found that 97 percent of 1102 male and female adolescents played video games, with genre distributions relatively equal among males and females. However, 50 percent of the male participants preferred more extreme and violent games, compared to only 14 percent of females ( ESA, 2014).
In addition to the studies compiled by the ESA (2014) and Lenhart et al. (2008) a more general collection of video game and media use was conducted by the Kaiser Family Foundation (Rideout et al., 2010) using qualitative and quantitative methods.
Children were required to report their daily video game and media use, as well as, complete a journal entry describing their media usage. The findings from this study (Rideout et al.) demonstrated a significant media use from 2004 to 2009, with daily national video game rates at an average of 1 hour and 13 minutes. While it is clear that children and adolescents are widely engaged in technology-based play, there remain many questions about the potential benefits and drawbacks for cognition, behaviors, and interventions.

Potential benefits and drawbacks of video games
As video game research became a focus of scientific research, so did the potential benefits and drawbacks of such games. In a review of video games, (Granic, Lobel, & Engels, 2014)  This discrepancy in research foci may be due to the nature of recording and interpreting observable cognitive responses as easier relative to motivational, emotional, and social information. Therefore we are currently limited in describing the potential benefits and drawbacks of video games within psychological and social domains.
Given the literature regarding the potential benefits and drawbacks of video games has primarily focused on cognition, and within the area of cognition has concentrated on the domain of executive functions, this is explored further. Executive functioning skills, as defined as a person's ability to attend and process relevant environmental stimuli while inhibiting irrelevant stimuli to achieving a desired outcome (Carlson & Meltzoff, 2008;Carlson, Moses, & Breton, 2002;Zelazo & Frye, 1998), is critical not only for daily functioning but as well as video game play.
Executive functioning can be explained by the outcomes involved in particular situations. For example, when a child is asked to search for a toy, he or she has to attend to given instructions and then process a plan without interference -all while using working memory to hold this goal in mind (Zelazo & Frye, 1998). Specific executive functions that are often discussed in the literature are, for example, attention, inhibition, planning, and working memory.
Many video game studies have studied dimensions of executive functioning to understand the potential cognitive benefits of video game play. For example, studies on attention demonstrate that gamers outperformed non-gamers on tasks requiring attention to target stimuli, and inhibition of attention to irrelevant stimuli (Dye, Green, & Bavelier, 2009;Green & Bavelier, 2012). Similar to Dye et al. (2009), Boot, Kramer, Simons, Fabiani, andGratton (2008) found that expert gamers performed better at tracking objects, were more accurate in recalling visual items in short-term memory, better at switching between tasks, and mentally rotating objects more quickly and accurately than non-expert gamers. In addition, Karle, Watter, and Shedden (2010) found that gamers were better able to control attention at the initial stages of stimuli presentation, which facilitated quicker and more accurate task switching than non-gamers. Video game expertise thus appears to promote differences between gamers and non-gamers (Bavelier et al., 2011;Boot et al., 2008;Green & Bavelier, 2012 enumeration, (f) visual acuity, (g) mental rotation, (h) temporal judgment, search, and (i) resistance to masking. However, four studies did not find differences in visual searching (e.g., responding to a targets following alternating cues and delay), attention cuing, and visual attention (Boot et al.). Eight studies using randomized control designs found training benefits in mental rotation, enumeration (e.g., participants have to determine the number of squares presented briefly on a computer screen), object tracking, visual acuity, decision-making, contrast sensitivity, and resistance to masking (Boot et al., 2011). Only one study did not demonstrate significant training effects (Boot et al.). In addition to the existing evidence to support that playing video games may enhance cognition, there is some evidence to suggest that video games may serve to influence development in a detrimental way (e.g., addictive tendencies; attention).
Whereas there are cognitive benefits in video game play, there are potential drawbacks related to attention and problematic video game use. For instance, a potential drawback of video game play is the potential to either cause or exacerbate attention problems. For example, Swing, Gentile, Anderson, and Walsh (2010) assessed 1323 children (6-12 years-old) to examine exposure to both television and video games and its association to attention problems. Teachers reported on children's classroom behaviors, including ability to stay on task, pay attention, and not interrupt the classroom. Children who had exceeded the American Academy of Pediatrics' recommendation of no more than two hours of daily video game and television exposure were more likely to display above average teacher rated attention problems.
Specific to video game play, teachers rated children as displaying more attention problems in class when video games were played on average for one hour and thirtyfour minutes per day.
Similarly, Gentile, Swing, Lim, and Khoo (2012) reported comparable results regarding rates of attentional problems in relation to video game use. A total of 3,034 children and adolescents (8-17 years-old), from Singapore, were surveyed over a three-year period to assess daily and weekly video game use. After controlling for gender, age, race, and socio-economic status (SES) variables, Gentile et al. found that time spent playing video games was a robust predictor of attention problems. This study also addressed the directionality of the relationship between video games and attention problems to determine whether children with attention problems were more attracted to video games, or did video game play produce children with more attention problems? Support for a bidirectional relationship was found, such that children who played video games and had more attention problems presented with increased attention difficulties (Gentile et al.).

Parent perception
Another influence on youth's video game use is the perceptions of video games exhibited by parents. Across 536 parent-child dyads measured on video game use and parent perception, results found that on average parents monitored the types of video games played by children, restricted certain graphic video games, evaluated the games selected by their children, and parents played video games with their children (Nikken & Jansz, 2003). In addition, when parents perceived certain video games as potentially harmful, then parents were more apt to restrict video games. However, families from a low socio-economic status (SES) restricted video games more often and evaluated the negative and positive aspects of the video games. No difference between frequency of video game play for low SES and high SES parents was found.
Taken together, the research on the potential benefits and drawbacks of using video games, as well as parent perception, highlights the need to further explore how video games are used by Attention Deficit Hyperactivity Disorder (ADHD) youth.
Furthermore, this research aims to extend the current knowledge and literature regarding individuals with attention problems who play video games, and in turn, may hold promise for intervention development and implementation and effective parenting practices.

Children and adolescents with ADHD
In addition to exploring potential benefits and drawbacks of video game use among the general population recent research has explored potential benefits and drawbacks for children and adolescents with developmental disabilities, for example, youth with ADHD (e.g., Nikkelen, Valkenburg, Huizinga, & Bushman, 2014 Overall, an individual with ADHD is likely to experience difficulty with managing and switching between tasks, attention skills, and working memory (DuPaul & Weyandt, 2006).

ADHD video game use and concerns
It is well documented that there is a great deal of variability among children with ADHD, both in terms of presenting difficulties, and in terms of day-to-day behavior (DuPaul & Stoner, 2014). Children and adolescents without disabilities vary in their level of video game use; for instance between 42 percent (ESA, 2014) and 97 percent (Lenhart et al., 2008) of youth play video games. With respect to studies comparing video game play among youth with ADHD and typically developing (TD) controls, there are no significant differences reported (Bioulac, Arfi, & Bouvard, 2008;Durkin, 2010;Mazurek & Engelhardt, 2013). Children who are typically developing are defined as individuals without a clinically diagnosed developmental disability.
Thus, whereas video game use of ADHD youth is similar to TD youth, the breakdown of ADHD sub-type characteristics might suggest different levels and interests of video game use. For example, in a meta-analysis conducted by Nikkelen et al. (2014) positive correlations were reported for the studies that focused on inattention (r + = .32) and impulsivity (r + = .11) ADHD related behaviors with media use. Across 29 cross-sectional, 12 longitudinal, and four experimental studies a significant positive correlation (r + = .12) between general media use (i.e., television and video games) and a composite score (i.e., attention, impulsive, and hyperactive problems) was found. The largest effect size was found by studies that described inattention problems versus studies that reported composite ADHD scores. This distinction is in line with previous research (Milich, Balentine, & Lynam, 2001), Further, a longitudinal study conducted by Fischer and Barkley (2006) followed a group of adolescents with ADHD (N = 149) and TD controls (N = 76) until adulthood (19-25 years of age), and recorded weekly amount of time spent engaging in social, financial, and recreational activities. Results indicated no significant differences between the adolescents with ADHD and TD controls in time spent playing video games, although mean differences illustrated that self-reported weekly video game hours were higher for ADHD adolescents (ADHD adolescents M = 4.0; TD controls M = 1.9). Within this sample, television watching, talking on the telephone, and hobby engagement were reported as longer significant durations for the ADHD adolescents than for TD controls. Albeit not significant the two weekly activities with lowest means were reading for pleasure and working out. Across all leisure activities combined, ADHD adolescents (M = 145.7) displayed significantly longer hours per week than TD controls (M = 100.2).

ADHD and technology intervention
Whereas limited research has suggested that video game use and duration among youth with ADHD is similar to TD controls, there has been research on the positive effects of technology-mediated interventions for ADHD youth within behavioral and academic domains. In a review paper on video games for children and adolescents with developmental disabilities, Durkin, Boyle, Hunter, and Conti-Ramsden (2013) reported that technology interventions demonstrated efficacy in increasing working memory. For example,  conducted a study to determine the extent that training working memory would improve on-task behaviors in the classroom. Using a randomized double-blind placebo, control design, Green et al. found that for 26 children with ADHD (17 males, 9 females; Mean age = 9.7 years), training working memory significantly produced more on-task classroom behaviors. Similar to Green et al. findings, working memory research (Holmes, Gathercole, & Dunning, 2009;Klingberg, Forssberg, & Westerberg, 2002) reinforces the concept that improvement in cognitive control can lead to improved behavioral functioning.
Other research utilizing technology has assessed computerized intervention effects on academic functioning. For example, (Clarfield & Stoner, 2005) conducted a multiple-baseline study with three male students in special education with an ADHD diagnosis to compare the efficacy of a computerized reading instruction program to teacher-directed instruction at increasing oral reading fluency. Clarfield and Stoner reported that not only did the computerized reading instruction program produce more words read correctly by students but also regression estimates of weekly growth rates during the intervention phase for two participants were similar to those of general education students. Their findings (Clarfield & Stoner) illustrated that computerized instruction is effective and may serve to assist teachers with managing classrooms and individuals who present with attention difficulties.
In summary, as of 2011, there are 6.4 million in the USA children and adolescents with ADHD in schools (CDC/NCHS, 2013) and ADHD is estimated to have a monetary impact of 36 to 52 billion dollars in the US each year (Pelham, Foster, & Robb, 2007). Given the prevalence and financial societal burden of ADHD, there is a need to be able to effectively discern the most time and cost effective ADHD interventions -potentially including electronically mediated interventions. Thus, the general findings from this study are intended to inform future research and practice with children with ADHD, particularly in the areas of effective parenting, intervention development, and the use of technology based learning strategies.

Research questions and hypotheses
Question 1: To what extent is the amount of time spent playing video games and other types of activities (e.g., homework, watching TV) by children and adolescents with ADHD, as reported by parents, similar to or different from that of the general population of children and adolescents?
Hypothesis: Children and adolescents with ADHD will display similar video game and activity duration than that of the general population of children and adolescents.
Question 2: Are there gender differences in the amount of time spent playing video games by children and adolescents with ADHD in the study sample, as reported by parents?
Hypothesis: Males will demonstrate significantly higher rates of video game play than females.
Question 3: Are there differences in the amount of time spent playing video games between younger and older participants?
Hypothesis: Younger children will display significantly higher rates of video game use than older participants. Hypothesis: Children and adolescents with an ADHD-I subtype diagnosis will demonstrate significantly more technology and/or non-technology use than children and adolescents with an ADHD-C subtype diagnosis.

Study Procedure
For the purposes of the present study, information was gleaned from all participating parents and children, to include only those questionnaires completed by parents of children and adolescents whose evaluation resulted in a diagnosis of ADHD. Demographic information reported include: age, gender, and a proxy of Parents reported ADHD sub-type characteristics across different activities on a four-item scale (Never, Sometimes, Often, Always). For instance, parents were asked,

How often does your child lose focus, become inattentive, and easily distracted when:
(a) playing video games, (b) doing homework, (c) watching TV, or (d) playing with Legos or blocks. Parents then reported the minutes their child spent daily on various activities (e.g., watching TV, reading, playing outside, video games, texting, playing with toys) selecting between five different boxes (None, <30, 30-60, 60-120, >120).
Parents were further asked about limit settings surround video game use. Next, parents reported their concerns surrounding video game use on five-point scale (Not at all, Mildly, Somewhat, Concerned, Extremely). Then, parents were asked how much they believe video games can help their children in a various academic, cognitive, and behavioral areas on a five-point scale (Not at all, A little bit, Somewhat, Quite a bit, A great deal). Parents marked the amount of minutes (None to <30, 30-60, 60-120, >120) spent in various activities (e.g., watching TV, using the internet, playing video games, using cell phones). Parents were then asked to rank their interest and expertise with video games, apps, and other digital technologies (e.g., cell phones, IPods, Internet, etc.).

Data Analysis. Extant data was utilized to answer the proposed research
questions. To answer the first research questions descriptive statistics were reported that included the mean, median, and standard deviations. Next, an Analysis of Variance (ANOVA) assessed group mean video game use differences between male and female gamers. The independent variable (IV) was gender and dependent variable (DV) was amount of time spent playing video games. Next, a series of ANOVAs were used to assess group differences across age variables. The IV was age and the DV was amount of time spent playing video games and other activities.
Lastly, to test between group differences exist between ADHD combined-type and ADHD primarily inattentive-type children and adolescents, a series of ANOVAs were run. The IV was ADHD sub-type (ADHD combined vs. ADHD inattentive type) and DVs were activity types (e.g., technology, academic, non-academic, nontechnology). All data were checked for assumptions of normality before performing parametric statistical analyses (i.e., ANOVAs). A macro-level effect size value (e.g., Eta-squared) was used as an indication of the magnitude of the relationship between independent and dependent variables. The following effect size guidelines were used: small (η 2 = 0.02), medium (η 2 = 0.13), and large (η 2 = 0.26) (Miles & Shevlin, 2001).
Micro-level effect size values (e.g., Cohen's d) provided an indication of the magnitude of relationship between means. The following mean effect size guidelines were used: small (d = 0.2), medium (d = .0.5), and large (d = 0.8) (Cohen, 1988).

Chapter III: Results
A total of 102 children and adolescents with ADHD-C and 29 children and adolescents with ADHD-I were included in this study's sample. Within this sample of 131, there were 96 males and 35 females with a mean age of 9.36 (SD = 3.26). There were a total of 131 parents. Including 115 females and 16 males, with a mean age of 40.07 (SD = 8.59). As a proxy of social-economic status (due to limited information on parents) we are reporting whether parents were on state versus private health insurance. There were 64 (49%) parents on state funded health insurance plans and 61 (47%) parents on privately funded health insurance plans. Parent education level could not be obtained from the sample.

Research question 1
To what extent is the amount of time spent playing video games and other types of activities (e.g., homework, watching TV) by children and adolescents with ADHD, as reported by parents, similar to or different from that of the general population of children and adolescents?
Hypothesis: Children and adolescents with ADHD will display similar video game and activity duration than that of the general population of children and adolescents.

Tech Activities
The average weekday time spent playing videos games for children and adolescents with ADHD was between 30-60 minutes (n = 128, M = 2.32, SD = 1.09).
As reported by parents, 27 percent of the sample did not play video games, 30 percent played less than 30 minutes, 28 percent play between 30-60 minutes, and 13 percent played longer than 1 hour during each weekday. During the weekend days and vacation days, parental reports indicate video games were played, on average, between 60-120 minutes per day (n = 128, M = 3.34, SD = 1.28). As reported by parents, 9 percent of the sample did not play video games on the weekend days and vacation days, whereas 18 percent played less than 30 minutes, 25 percent played between 30-60 minutes, and 47 percent played longer than one hour. Time of video game play during the weekday and weekend was significantly correlated (r = .52, p < .000).
Therefore, it appears that those who played video games for longer periods of time during the weekdays also played more during the weekends. A previous national sample of self-reported activities ages 8-18 years-old (e.g., Rideout et al., 2010) reported average daily video game play as 1 hour and 13 minutes. Our sample during the weekdays played videogames for less time than the national daily average, however, participants in our sample played more than the national average on the weekend.
Average weekday Internet use was approximately 30 minutes (n = 127, M = 2.08, SD = 1.03). As reported by parents, 32 percent of the sample did not use the Internet, 37 percent used the Internet less than 30 minutes, 18 percent used the Internet between 30-60 minutes, and 9 percent used the Internet more than 1 hour during the weekday. During weekends and vacation days, the average Internet use was between 30-60 minutes (n = 127, M = 2.53, SD = 1.32). As reported by parents, 28 percent of the sample did not use the Internet, whereas 25 percent used the Internet less than 30 minutes, 21 percent used the Internet between 30-60 minutes, and 24 percent used the Internet more than one hour on weekend and vacation days. Compared to the previously reported youth national Internet use of 30 minutes a day (e.g., Rideout et al., 2010), the study's sample used the Internet at approximately the same rate during the week, but during weekend/vacation days Internet use was engaged in more frequently by this sample compared to the national sample.
The average weekday time completing schoolwork on a computer was approximately less than 30 minutes (n = 128, M = 1.68, SD = 0.80). As reported by parents, 47 percent of the sample did not use a computer to complete schoolwork, 35 percent completed schoolwork on a computer for less than 30 minutes, 12 percent completed schoolwork on a computer between 30-60 minutes, and 3 percent completed schoolwork on a computer for longer than 1 hour during the weekday.
During the weekend days and vacation days, the average time spent completing homework on a computer was approximately less than 30 minutes (n = 128, M = 1.41, SD = 0.69). As reported by parents, 66 percent of the sample used a computer to complete schoolwork, whereas 25 percent used a computer to complete schoolwork for less than 30 minutes, 5 percent used a computer to complete schoolwork between 30-60 minutes, and 2 percent used a computer to complete schoolwork for longer than one hour on weekend and vacation days. No national data (i.e., Rideout et al., 2010) was reported for completing schoolwork on a computer, thus, no qualitative comparison is applicable.
The average weekday time spent on a cell phone was approximately less than 30 minutes (n = 127, M = 1.48, SD = 0.95). As reported by parents, 70 percent of the sample did not use a cell phone, 16 percent used a cellphone for less than 30 minutes, 3 percent used a cell phone between 30-60 minutes, and 8 percent used a cell phone for longer than 1 hour during the weekday. During weekend and vacation days, the average time spent on a cell phone was approximately less than 30 minutes (n = 128, M = 1.64, SD = 1.18). As reported by parents, 66 percent of the sample did not use a cell phone, whereas 18 percent used a cellphone for less than 30 minutes, 3 percent used a cell phone between 30-60 minutes, and 11 percent used a cell phone for longer than one hour on the weekend and vacation days. Compared to a previous national sample of self-reported activities among children and adolescents ages 8-18 years-old (i.e., Rideout et al., 2010) cell phone use was on average 32 minutes. This sample used cell phones less than the national population on both weekdays and weekends/vacations.
The average weekday time spent listening to music was approximately 30 minutes (n = 127, M = 2.35, SD = 1.10). As reported by parents, 21 percent of the sample did not listen to music, 41 percent listened to music for less than 30 minutes, 24 percent listened to music between 30-60 minutes, and 12 percent listened to music for longer than 1 hour during the weekday. During weekend and vacation days, the average time spent listening to music was approximately less than 30 minutes (n = 128, M = 2.81, SD = 1.20). As reported by parents, 12 percent did not listen to music, whereas 34 percent listened to music for less than 30 minutes, 23 percent listened to music 30-60 minutes, and 29 percent listened to music for longer than one hour on the weekend and vacation days. Compared to a national sample (i.e., Rideout et al., 2010) that listened to music for 2 hours and 31 minutes on average per day, this sample listened to music less frequently during weekdays and weekends/vacations. to music, and TV) children and adolescents with ADHD engaged less during weekdays and weekends/vacation compared to a national sample (i.e., Rideout et al., 2010). Weekend/vacation video game play among youth with ADHD was more frequent than the national sample collected by Rideout and colleagues (see Table 1).

Research question 2
Are there gender differences in the amount of time spent playing video games and other types of activities by children and adolescents with ADHD in the study sample, as reported by parents?
Hypothesis: Male participants will demonstrate significantly higher rates of video game play than female participants.
The average frequency of weekday video game play for males with ADHD was between 30-60 minutes (n = 94, M= 2.46, SD = 1.09). As reported by parents, 22 percent did not play video games, 28 percent played less than 30 minutes, 34 percent played between 30-60 minutes, and 14 percent played longer than 1 hour during each weekday. During weekend days and vacation days, parents reported video games were played, on average, between 60-120 minutes (n = 94, M = 3.60, SD = 1.17). As reported by parents, 4 percent of the sample did not play video games on weekend days and vacation days, whereas 15 percent played less than 30 minutes, 25 percent played between 30-60 minutes, and 54 percent played longer than one hour. played longer than one hour (see Tables 5 & 6). In sum, there is statistical support for the second research hypothesis, such that male children and adolescents with ADHD engage in video game play significantly more than female children and adolescents with ADHD.

Research question 3
Are there differences in the amount of time spent playing video games, as reported by parents, between younger and older participants?
Hypothesis: Younger children will display significantly higher rates of video game use than older participants.
To examine whether there were differences in amounts of video game play across ages, first participants were divided into four age categories based on the distribution of scores and developmental age. The groups' years were 5-7, 8-10, 11-14, and 15-18.
Children between 5-7 years of age played video games during the weekday for approximately 30 minutes or less (n = 46, M = 2.09, SD = .812). As reported by parents, 26 percent did not play video games, 40 percent played less than 30 minutes, 30 percent played between 30-60 minutes, and 2 percent played longer than 1 hour during each weekday. During weekend days and vacation days, parents reported video games were played for approximately 30-60 minutes (n = 46, M = 2.93, SD = 1.12). As reported by parents, 6 percent of the sample did not play video games on weekend days and vacation days, whereas 34 percent played fewer than 30 minutes, 28 percent played between 30-60 minutes, and 30 percent played longer than one hour.
Children between 8-10 years of age played video games for approximately 30 minutes each day (n = 41, M = 2.46, SD = 1.08). As reported by parents, 21 percent did not play video games, 28 percent played fewer than 30 minutes, 30 percent played between 30-60 minutes, and 16 percent played more than 1 hour during each weekday.
During weekend days and vacation days, parents reported video games were played for approximately 60 minutes (n = 41, M = 3.59, SD = 1.22). As reported by parents, 9 percent of the sample did not play video games on weekend and vacation days, whereas 7 percent played less than 30 minutes, 21 percent played between 30-60 minutes, and 58 percent played longer than one hour. Overall the data did not support the third hypothesis. Older participants significantly played more video games than younger participants on weekend/vacation days but not during weekdays among this sample.

Research question 4
To what extent are there differences in the amount of time spent playing video games and other types of activities, as reported by parents, as a function of ADHD

diagnosis (ADHD combined-subtype [ADHD-C] compared with ADHD primarily inattentive-subtype [ADHD-I]).
Hypothesis: Children and adolescents with an ADHD-I subtype diagnosis will demonstrate significantly more technology and/or non-technology use than children and adolescents with an ADHD-C subtype diagnosis.
A series of independent ANOVAs were utilized to test group differences between ADHD subtype diagnosis (i.e., ADHD-C vs. ADHD-I) and technology and non-technology media use (i.e., video games, computers, Internet use, sports, homework, etc.). All variables met parametric assumptions for ANOVAs, except  Next, non-technology use across ADHD subtype diagnosis was examined via a series of independent ANOVAs among non-digital media use variables (e.g., homework, sports, playing with toys). All variables met parametric assumptions for completing ANOVAs, except for playing with toys on weekends and vacations.
Playing with toys was analyzed using a non-parametric test (e.g., Mann-Whitney).
Across . All other ANOVAs, and remaining nonparametric test, did not approach significance, F < 1 and p > .05, respectively.
In sum, the data do not support the research hypothesis, there was no statistical evidence to the support the notion that children and adolescents with an ADHD-I subtype diagnosis were significantly more engaged in more technology and nontechnology use than children and adolescents with an ADHD-C subtype diagnosis.  Parents' monitoring, limit setting, and engagement with digital media.
As a supplementary analysis, parent responses and perceptions to questions regarding parental engagement, monitoring, and limit setting of children with ADHD and digital media were analyzed. First, parents were asked to what extent they monitor the length of time their child plays video games and goes on the computer on a 4-point scale (i.e., Never, Sometimes, Often, Always). The modal response was "Always" (n = 61, 47%). Other responses showed that there were 35 (27%) parents who endorsed "Often", 30 (23%) who endorsed "Sometimes", and 5 (4%) parents who did not report monitoring video game and computer use (see Figure 1).
Next, parents were asked to report on their limit setting practices surrounding their children's digital media use. Approximately one-third of parents (37%, n = 49) said digital media is only allowed after homework is completed, 26 (20%) parents reported that there are no rules surrounding digital media, 10 (8%) parents reported children could play as long as they desired, and 25 (19%) parents restricted digital media use based on hours per day. Lastly, there were 17 (13%) parents who reported only allowing digital media on weekends and vacations and 4 (3%) parents who did not allow digital media use.
With respect to parental engagement, parents were asked to endorse how many times per week they spent together with their child playing video games, the amount of time parents watched their child play video games, and the amount of time spent going online with their child. First, there were 84 (64%) of parents who did not endorse playing video games with their child, however, there were 27 (21%) parents who endorsed once a week video game play with their child, and 19 (16%) parents who endorsed playing video games more than once a week. Second, there were a total of 47 (36%) who did not watch their child play video games, 29 (22%) parents who watched their child play video games at least once a week, and 54 (41%) parents who watched their child play video games more than once a week. Lastly, there were a total of 46 (35%) parents who reported not going online with their child, 32 (24%) parents who reported going online with their child at least once a week, and 53 (41%) parents who reported going online with their child more than once a week.

Perception of ADHD behaviors and level of concern regarding video game play
Parents were asked to report to what extent their child displayed inattention, hyperactivity, and disorganization while playing video games. Specifically, parents were asked to endorse the following questions as either "Never", "Sometimes", "Often", or "Always": How often does your child lose focus, become inattentive, and easily distracted when playing video games; How often does your child fidget, squirm, and appear restless when playing video games; and How often does your child appear disorganized, forgetful, and scattered when playing video games. First,70 (53%) parents who reported that their child does not display inattentive behaviors while playing video games, whereas 38 (29%) parents endorsed "Sometimes", 19 (15%) parents endorsed "Often", and 4 (3%) parents endorsed "Always" for inattentive behaviors during their child's video game play. Second, there were a total of 74 (57%) of parents who reported that their child does not appear hyperactive while playing video games, whereas 34 (26%) parents endorsed "Sometimes", 17 (13%) parents endorsed "Often", and 6 (5%) parents endorsed "Always" for child hyperactivity during video game play. Third, there were 91 (70%) parents who reported that there child does not appear disorganized while playing video games, whereas 25 (19%) parents endorsed "Sometimes", 9 (7%) parents endorsed "Often", and 2 (2%) parents endorsed "Always" for their child's disorganized behaviors during video game play.

Parents' beliefs about how much video games help their children
Parents were further asked to report their personal beliefs regarding whether video games can serve to help their children across a variety of activities. Items were rated on a 5-point scale (i.e., Not at all, A little bit, Somewhat, Quite a bit, A great deal). Below modal responses are reported for each response category (see Figure 2 for complete frequencies). Seven areas of functioning were queried (i.e., Adaptability/Compromise, Writing, Understanding Self and Others, Making Friends, Self-Control, Teamwork, Time Management) with the majority of parents reporting that video games did not serve to help their child. For example, 45 (34%) parents endorsed that video games did not help their child in adaptability and compromise; 81 (62%) parents endorsed that video games did not help their child's writing; 68 (52%) parents endorsed that video games did not help their child understand themselves or others; 68 (52%) parents endorsed that video games did not help their child make friends; 59 (45%) parents endorsed that video games did not help their child with selfcontrol; 40 (31%) parents endorsed that video games did not help their child with team work; and, 54 (41%) parents endorsed that video games do not help their child with time management.
Next, 68 parents endorsed that video games could help "A little bit" with reading (n = 34, 26%) and physical benefits (e.g., hand-eye coordination; n = 34, 26%). Lastly, there were a total of five areas that had a modal "Somewhat" response; specifically, 39 (30%) parents endorsed that video games could "Somewhat" help their child's problem solving, 41 (31%) parents endorsed that video games can "Somewhat" help their child's planning abilities; 40 (31%) parents endorsed that video games can "Somewhat" help their child's memory, 41 (31%) parents endorsed that video games can "Somewhat" help their child's focus, and 39 (30%) parents endorsed that video games can "Somewhat" help their child's math skills.

Chapter IV: Discussion
The primary purpose of this study was to examine video game use among children and adolescents with a clinical diagnosis of ADHD and to compare this study's data with that of a national youth media use survey (i.e., Rideout et al., 2010).
Along with video game activity, other technology and non-technology activities were compared to a national sample collected by Rideout and colleagues. A secondary aim of this study was to assess whether there were statistical differences between video game use across gender and age variables, as well as, determine technology and nontechnology differences as a function of an ADHD subtype diagnosis. Finally, information was gleaned from parent responses, regarding limit setting, monitoring, and beliefs about whether video games can augment children's academic, social, and behavioral skills in order to provide a better understanding of parental perception of video game use by their children.
With respect to the first research question, children and adolescents with ADHD, as compared with a national sample of children (i.e., Rideout et al., 2010), engaged in less frequent technology activity use, such as, video game play, Internet use, cell phone use, listening to music, and watching TV. However, video game play for youth with ADHD on weekend/vacation days was reported to be more frequent than video game play for the national sample reported by Rideout and colleagues.
This finding suggests that when youth with ADHD are not in school, and not bound to weekday constraints, then video game play exceeds national norms as reported by Rideout et al. Overall, children and adolescents with ADHD displayed less frequent technology use across media activities relative to the general population of children and adolescents. Aside from video game play on weekend/vacation days, there were no other notable differences.
The second research question examined gender differences across video game use. Both male and female youth with ADHD played video games at lower rates during weekdays compared to national samples, but during weekends/vacations both males and females displayed higher rates of video game play compared to the national average (Rideout et al., 2010). Moreover, statistical analyses between male and female children and adolescents with ADHD indicate males significantly engaged in more video game play compared to females across weekdays and weekend/vacation days. Effect sizes demonstrated a small to medium (η 2 = .04) effect during weekday video game play, and a large effect size gender was large (η 2 = .11) during weekend/vacation video game play. This finding indicates that gender plays a significant role in influencing video game use, whereby male children and adolescents with ADHD more often engage in video game play than female children and adolescents with ADHD.
The third research question addressed age differences in video game play by comparing younger and older participants with ADHD. Although video game play did not approach significance on weekdays, age differences were found between 5-7 and 11-14 year-olds during video game play on weekends/vacation days. The effect size of this statistically significant finding was small (d = -.26), with the older 11-14 year age group playing significantly more video games on weekends/vacations compared to the 5-7 year age group. Overall these findings indicate no age differences were found during weekday activities, and that small differences across age groups of children with ADHD were found for weekend/vacation days, with older children playing more.
Finally, the fourth research question sought to examine technology and nontechnology use across differing ADHD subtypes. Within the sample, there were children and adolescents with ADHD-C and ADHD-I subtypes. Contrary to the research hypothesis, there was no statistical evidence to the support the notion that children and adolescents with an ADHD-I subtype diagnosis significantly engaged in more technology and non-technology activities than children and adolescents with an ADHD-C subtype diagnosis. Across the technology variables there was a nonsignificant but small effect size (n 2 = .03) for video game play on weekdays, indicating that children with ADHD-C play slightly more video games than children with ADHD-I. Although, video game use across both groups was descriptively below the national average. As for schoolwork completed on weekend/vacation days and weekday cell phone use, these were engaged in more frequently by youth with ADHD-I compared to youth with ADHD-C. Additionally, children and adolescents with ADHD-C engaged in significantly more outdoor sport play compared to children and adolescents with ADHD-I.

How is data similar to and different to that of previous research?
In a similar study to the present one, Mazurek and Engelhardt (2013)  generalization to diverse populations is cautioned. In addition, the present study did not provide data on children and adolescents with ADHD-H subtype; therefore, generalizations to this ADHD subtype are not possible. Lastly, the type of survey utilized ranges as potential estimates, whereas previous research has asked parents to estimate the exact time or even ask the youth to report using a combination of quantitative and qualitative methods.

Summary and Conclusion
The current study provides a focus on video game use among youths with ADHD population, including both male and female participants and ADHD subtypes.
Both gender and subtype diagnosis have not been a prior focus in previous ADHD and video gaming research. Findings suggest that gender may play a significant role in influencing video game use among ADHD youth, with male youth playing more than female youth. As for age, there is some indication that older children and adolescents may play video games more often than their younger counterparts. Additionally, there is a need to further examine possible differences in subtype diagnoses.
In conclusion, the use of video games not only in the home but also in the classroom, will require further controlled studies to better understand this possible educational tool (Young et al., 2012). While the current education research on video gaming utility is ongoing, the results from the present study nevertheless demonstrate parents endorse their children as exhibiting fewer ADHD behaviors (i.e., inattention, hyperactivity, and disorganization) during video game play as compared to other times. The combination of understanding these motivating and engaging activities among ADHD populations can guide practitioners, teachers, and parents to make informed decisions about the integration of technology across interventions with classroom and home environments. The purpose of this survey is to learn more about how parents view their children's use of video games and other digital technologies. In addition to asking about your child's digital habits, we will also ask about your own technology use. Please complete this survey for only one child, since many of the questions may have age-specific responses. Thank you for taking the time to complete this survey.

Appendix A CHILDREN'S USE OF VIDEO GAMES AND DIGITAL MEDIA
Questions about YOUR CHILD'S use of video games and technology. I do not allow my child to play video games or use the Internet My child is allowed to play video games and use the Internet only on weekends and vacations. My child is allowed to play video games and use the Internet after their homework is completed. My child is allowed to play video games and use the Internet for ___ hours per day. My child is allowed to play video games and use the Internet whenever they want, as long as they are doing well in school. We do not have any specific rules about my child's use of video games and digital media.
9. How many times per week do you: 0 1 2-4 5-10 10+ Play video games with your child Ask your child to help you with digital devices Watch your child play video games Go online together with your child 10. If your child plays video games, describe the level of concern you have about the following issues: