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Contextualizing video game play: The moderating effects of cumulative risk and parenting styles on the relations among video game exposure and problem behaviors

Detailed Record

Title:

Contextualizing video game play: The moderating effects of cumulative risk and parenting styles on the relations among video game exposure and problem behaviors.

Authors:

Linebarger, Deborah L.. University of Iowa, Iowa City, IA, US, [email protected] 

Address:

Linebarger, Deborah L., College of Education, University of Iowa, N278 Lindquist Center, Iowa City, IA, US, 52242, [email protected] 

Source:

Psychology of Popular Media Culture, Vol 4(4), Oct, 2015. Special Issue: Video Games and Youth. pp. 375-396.

NLM Title Abbreviation:

Psychol Pop Media Cult

Publisher:

US : Educational Publishing Foundation

ISSN:

2160-4134 (Print) 2160-4142 (Electronic)

ISBN:

1-4338-2196-6 978-1-4338-2025-0

Language:

English

Keywords:

hyperactivity, video games, cumulative risk, parenting styles, attention problems

Abstract:

This study examined the direct and moderated relations associated with video game exposure and child behavior problems (i.e., hyperactivity, inattention). Research linking video game exposure to these problem behaviors is inconsistent likely because studies have used measures that combine elements of both problems in the same scale and because key contextual factors associated with video game play (i.e., cumulative family risk, parenting styles, video game content) are not included or have been covaried out. A nationally representative group of US parents/caregivers of 788 preschoolers (2–5 years) and 391 school-age children (6–8 years) were interviewed by phone and asked to report their child’s video game exposure via a 24-hr time diary, demographic information, their parenting styles, and their child’s hyperactivity levels and attention problems. Separate regressions by age were conducted. Video game exposure was directly associated only with increasing levels of hyperactivity in preschool children, an effect reduced to nonsignificance when parenting styles were covaried out. Adding cumulative risk and parenting styles as moderators increased the amount of variance accounted for across both the preschool and school-age samples. Responsive parenting moderated the effects of video game exposure for low-risk preschoolers’ and high-risk school-age children’s hyperactivity levels and high-risk preschoolers’ and low-risk school-age children’s attention problems. In the final set of models with video game exposure broken into violent and nonviolent content, different patterns of effects and larger effect sizes emerged across cumulative risk, responsiveness, and nonviolent video game exposure. Violent video game exposure was associated only with low-risk school-age children’s hyperactivity levels. (PsycINFO Database Record (c) 2018 APA, all rights reserved)

Document Type:

Journal Article

Subjects:

*Behavior Problems; *Computer Games; *Parenting Style; *Recreation; *Exposure; Attention; Hyperkinesis

PsycINFO Classification:

Childrearing & Child Care (2956)

Population:

Human Male Female

Location:

US

Age Group:

Childhood (birth-12 yrs) Preschool Age (2-5 yrs) School Age (6-12 yrs) Adulthood (18 yrs & older)

Tests & Measures:

MacArthur CDI III Short Form McCarthy Scales of Children’s Ability National Household Education Survey Assessment of Literacy and Language   DOI: 10.1037/t14964-000 Cumulative Risk Index   DOI: 10.1037/t65678-000 Peabody Picture Vocabulary Test Strengths and Difficulties Questionnaire   DOI: 10.1037/t00540-000

Grant Sponsorship:

Sponsor: U.S. Department of Education, Corporation for Public Broadcasting, Public Broadcasting System for the Ready to Learn initiative, US Grant Number: cooperative agreement U295A05003 Recipients: No recipient indicated

Methodology:

Empirical Study; Interview; Quantitative Study

Format Covered:

Electronic

Publication Type:

Journal; Peer Reviewed Journal

Publication History:

First Posted: Apr 6, 2015; Accepted: Dec 3, 2014; Revised: Nov 20, 2014; First Submitted: Mar 3, 2014

Release Date:

20150406

Correction Date:

20180412

Copyright:

American Psychological Association. 2015

Digital Object Identifier:

http://dx.doi.org.ezproxy.snhu.edu/10.1037/ppm0000069 

PsycARTICLES Identifier:

ppm-4-4-375

Accession Number:

2015-14739-001

Number of Citations in Source:

74

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Contextualizing Video Game Play: The Moderating Effects of Cumulative Risk and Parenting Styles on the Relations Among Video Game Exposure and Problem Behaviors

Contents

1. Video Game Research
2. Ecological Approach to Understanding Potential Effects of Video Game Exposure
3. Cumulative Risk
4. Parenting Styles
5. Moderating Effects of Different Contextual Factors
6. Age-Related Differences
7. Method
8. Participants
9. Design
10. Procedure
11. Demographic Measures
12. Cumulative Risk
13. Parenting Style
14. Child Ability Covariate
15. Video Game Exposure
16. Outcome Measures
17. Analytic Approach
18. Results
19. Model 1: Does Video Game Exposure Predict Child Behavior Problems and Do the Patterns Differ for Hyperactivity and Inattention?
20. Model 2: After Including Parenting Styles as Covariates, Does Video Game Exposure Predict Child Behavior Problems and Do the Patterns Differ for Hyperactivity and Inattention?
21. Model 3: Do Cumulative Risk and Parenting Styles Moderate the Relations Between Video Game Exposure and Child Behavior Problems?
22. Model 4: Do the Patterns Observed for Overall Video Game Exposure, Cumulative Risk, and Parenting Styles Vary When Video Game Exposure Is Divided Into Content Categories?
23. Discussion
24. Parenting Styles
25. Video Game Content Effects
26. Limitations
27. Conclusion
28. References

Full Text

Listen Pause Stop Select: American Accent Australian Accent British Accent Volume   Settings Download mp3 Close Player Speech-enabled by ReadSpeaker By: Deborah L. Linebarger University of Iowa;

Acknowledgement: This project was supported by a cooperative agreement between the U.S. Department of Education, the Corporation for Public Broadcasting, and the Public Broadcasting System for the Ready to Learn initiative, PR# U295A05003. However, these contents do not necessarily reflect the opinions or represent the policy of the Department of Education. You should not assume endorsement by the Federal Government as well.

Recent research linking video game exposure to child behavior problems including attention and hyperactivity problems are inconsistent (Ferguson, 2011; Parkes, Sweeting, Wight, & Henderson, 2013; Swing, Gentile, Anderson, & Walsh, 2010). Swing et al. (2010) found that 9-year-old US children’s attention problems in the classroom were positively associated with increasing time spent playing video games (i.e., exposure) although the magnitude of the effect was small (β = .10). The scale used to measure attention problems in this study consisted of three items that combined elements of both inattention and hyperactivity/impulsivity (e.g., difficulty staying on task, often interrupts other children’s work). Parkes et al. (2013) found no relation between U.K. 7-year-olds’ video game exposure and a combined screening measure of hyperactivity and attention problems (i.e., Strengths and Difficulties Questionnaire). Ferguson (2011) also found no relation between Hispanic 10- to 14-year-olds’ video game exposure and attention problems although the estimates used to calculate video game exposure were fairly imprecise both in total exposure and in the categorization of video game content. Children were asked to recall the total number of hours they spent playing video games during a week and whether the games they played were violent or not.

One explanation for the small effect found by Swing et al. (2010) and the null findings reported by Parke et al. (2013) is related to how outcomes were measured. In these two studies, items tapping both inattention and hyperactivity were included. Although there is likely overlap in these two behaviors, emerging evidence suggests differentiation in the neuropsychological mechanisms associated with each behavior problem (Martel & Nigg, 2006; Sonuga-Barke, 2003). Specifically, regulation problems and cognitive control deficits are hypothesized to lead to inattention whereas reactive or motivational control problems are hypothesized to lead to hyperactivity (Martel & Nigg, 2006). Each behavior problem is then differentially predictive of adolescent and adult outcomes including academic problems for those exhibiting greater inattention (Breslau, Lane, Sampson, & Kessler, 2008; Duncan et al., 2007) and substance abuse, juvenile delinquency, and other externalizing problems for those exhibiting greater hyperactivity (Elkins, McGue, & Iacono, 2007). The null findings reported by Ferguson (2011) could be a function of the data collection method. Asking for a global estimate of the hours of video games played assumes that respondents are able to accurately provide an estimate of use in a relatively short amount of time. In a series of time use studies, researchers have found that adults often overestimated their and their children’s time spent in socially desirable activities (e.g., reading to their children, working out, number of hours worked) and underestimated their time spent in socially undesirable activities (e.g., drinking, TV watching; Juster & Stafford, 1985; Robinson, 1985; Robinson & Godbey, 1997). Finally, other research indicates that older children have difficulty accurately estimating their own time use (Comstock & Scharrer, 1999). Increasing measurement error reduces the accuracy of the predictive models and likely underreports effects, an issue when most media exposure/outcomes studies find relatively small effects.

Video Game Research

Researchers have proposed different theories to explain the relations between video game exposure and behavior problems. Considering each theory in light of the neuropsychological mechanisms described above suggests that it might be possible to more clearly predict whether and how video games would be associated with specific behavior problems. The first theory relates to the fast pace of video games. It is argued that this fast pace increases arousal during and after exposure due to frequent shifts in attention and the continual renewal of the orienting response (Huizinga, Nikkelen, & Valkenburg, 2013). Over time, children habituate to these arousal levels leading to changes in the child’s baseline arousal level that require ever and greater stimulation. When such stimulation is absent, children will be more likely to exhibit inattention or hyperactivity when faced with less arousing situations (Lang, Zhou, Schwartz, Bolls, & Potter, 2000). Research investigating this hypothesis with TV indicates that fast pace is unrelated to attention problems specifically (Anderson, Huston, Schmitt, Linebarger, & Wright, 2001) although Lillard and Peterson (2011) have found that watching a 9-min clip from a fast-paced program (i.e., Sponge Bob Squarepants) caused short-term deficits in executive function, a set of skills that comprises both hyperactivity and attentional components, compared with children who either watched a more slowly paced educational program or drew a picture.

The second hypothesis proposes that frequent video game playing affects the way that a child’s attentional style develops such that the child scans and shifts attention to onscreen content more frequently rather than selecting and focusing attention for any period of time (Huizinga et al., 2013). Spending more time scanning and shifting attention and less time selecting and focusing attention may make it especially challenging to attend to tasks like reading or homework that require the selecting and focusing attentional style (Jensen, Martin, & Cantwell, 1997). Although it is unclear how each media effects hypothesis might differentially relate to hyperactivity and inattention, the differentiated neuropsychological mechanisms coupled with the different hypotheses does provide potential explanatory mechanisms for different patterns of effects. Therefore, one purpose of this study is to test the effects of video game exposure to evaluate similarities and differences across both hyperactivity and inattention problems.

In addition to these medium-specific based explanations, it is also likely that the specific content of a video game (e.g., violence, role-playing, first-person shooter, educational messages) would influence particular outcomes. Content-based theories of TV effects have typically provided better explanations of observed relations compared with medium-specific theories (Anderson & Bushman, 2001). Research investigating the relation between exposure to specific video game content and attention is mixed and typically conducted with children age seven years and older. Visual-perceptual attention skills are enhanced when children and adults play more action-based video games (i.e., 1st/3rd person point of view, heavy action, fast-paced typically featuring violent themes like Call of Duty or Halo; Dye & Bavelier, 2010; Oei & Patterson, 2013). Playing matching games, spatial memory games, and hidden object games are associated with stronger visual search skills and spatial memory (for the latter two game types; Oei & Patterson, 2013). In contrast, research that defines attention as the ability to concentrate and not become easily distracted has correlationally and longitudinally linked violent video game exposure to attention problems (Gentile, Swing, Lim, & Khoo, 2012) although the effect disappears when initial attention problems were controlled. Research examining hyperactivity and specific video game content has similarly linked action-based video game exposure to better inhibitory control in an adult sample (Oei & Patterson, 2013). In the present study, exposure was divided into nonviolent content and violent content using ratings provided by the Entertainment Software Rating Board (i.e., ESRB).

Ecological Approach to Understanding Potential Effects of Video Game Exposure

Also missing from studies examining exposure and behavior problems is an examination of the ecological contexts in which video game play is situated in young children’s lives and how these contexts might moderate the relationships observed between video game play and child behavior problems. A number of environmental factors reflecting broader ecological categories like settings, economic resources, parenting, parent education, and other cultural and linguistic factors surround where and how children experience media. Human development is always development in context (Bronfenbrenner & Morris, 2006; Ceci & Hembrooke, 1995; Luscher, 1995; Moen, Elder, & Luscher, 1995). Contexts can simultaneously limit and facilitate performance, depending upon the nature of the context. For instance, more educated parents, greater economic resources, or high-quality parenting might buffer any negative effects associated with video game exposure whereas poorly educated parents, fewer economic resources, or poor-quality parenting might exacerbate negative effects (Burchinal, Campbell, Bryant, Wasik, & Ramey, 1997; Sameroff, Seifer, Barocas, Zax, & Greenspan, 1987). A second purpose of this study was to test for the moderating roles of two ecological contexts: the home environment created by varying levels of cumulative sociodemographic risk (Sameroff & Feise, 2000) and the parent–child relationship characterized by different parenting styles (Baumrind, 1991; Maccoby & Martin, 1983).

Cumulative Risk

Research indicates that poor developmental outcomes including child behavior problems increase as the number of sociodemographic risk factors accumulate (Ackerman, Izard, Schoff, Youngstrom, & Kogos, 1999; Burchinal et al., 1997; Jones, Forehand, Brody, & Armistead, 2002; Sameroff, Bartko, Baldwin, Baldwin, & Seifer, 1998; Sameroff & Feise, 2000; Sameroff et al., 1987). Specifically, low maternal education, single-parent status, poverty, maternal age at birth, minority status, and number of children living in the house have been individually linked to poorer academic and social outcomes (Burchinal et al., 1997). The individual effects of any one sociodemographic risk are amplified as the presence of these risks accumulates leading to substantial disadvantage (Lima, Caughy, Nettles, & O’Campo, 2010; Sameroff et al., 1987). Children living in high-risk environments are more likely to exhibit behavior problems compared with children living in low-risk environments (Essex et al., 2006; Pingault et al., 2011). Much of the influence of these sociodemographic risks on child behavior problems is likely transmitted through parenting (Burchinal, Roberts, Zeisel, Hennon, & Hooper, 2006; Ceballo & Hurd, 2008). As risks accumulate, the ability of a parent to maintain a positive emotional climate in the home is markedly diminished (Arnold & Doctoroff, 2003; Conger et al., 1992; Conger, Ge, Elder, Lorenz, & Simmons, 1994; Trentacosta et al., 2008).

Parenting Styles

Broad patterns of parenting, referred to as parenting styles, are composed of a complex set of behaviors that function to create a particular emotional climate in a child’s home (Baumrind, 1991; Darling & Steinberg, 1993; Maccoby & Martin, 1983). Parenting styles have been conceptualized along two different continua: responsiveness/warmth and consistency/behavioral control. Children with parents who are appropriately responsive, sensitive to their children’s cues, and warm exhibit fewer attention problems and decreased levels of hyperactivity (Healey, Flory, Miller, & Halperin, 2011). In contrast, parents who exhibit disorganized and unpredictable parenting tend to create environments where discipline is inconsistently applied and rules may or may not be followed. Children in these families are more likely to exhibit higher levels of hyperactivity and more attention problems (Gardner, 1989; Nigg, Hinshaw, & Huang-Pollack, 2006; Stormshak, Bierman, McMahon, Lengua, & Conduct Problems Prevention Research Group, 2000).

Moderating Effects of Different Contextual Factors

Although cumulative risk and parenting styles are both hypothesized to moderate the relations between video game exposure and child behavior problems, it is unclear how each construct, individually or in combination, will exert influence. For instance, researchers using an approach similar to the one proposed here (i.e., cumulative risk and parenting quality as moderators) found significant and positive associations between educational TV viewing and executive function in a high-risk sample of elementary schoolchildren, especially when their parents exhibited higher levels of warmth and responsiveness (Linebarger, Barr, Lapierre, & Piotrowski, 2014). In contrast, the low-risk elementary schoolchildren in this sample exhibited poorer executive function when they were exposed to increasing levels of background TV and had parents who exhibited less consistency in their parenting. Collectively, the different neuropsychological pathways identified for hyperactivity and attention problems, combined with different associations linked to cumulative risk and exposure, highlight the importance of examining how exposure is situated in a child’s life and whether different contextual factors are associated with differing patterns of effects (Bronfenbrenner & Morris, 2006).

Age-Related Differences

One final complication involves examining the role that age-related differences might play in whether and how parenting and video game exposure are linked to hyperactivity and attention problems. In this sample, it was possible to test whether effects were the same or different for preschoolers (i.e., 2–5 years old) compared with school-age children (i.e., 6–8 years old). Several lines of research would suggest that this age split is important to consider. First, there is rapid developmental change between birth and age 5 across a variety of academic and social behaviors including impulse control and attention. By age 5, foundational capacities for directing attention and controlling impulses are in place. As children enter formal schooling, they are shifting from this rapid developmental phase to refining and learning to efficiently deploy attention and inhibit impulses (Hardy et al., 2007; Moriguchi & Hiraki, 2013). Although the rapid phase of development is diminishing, it is also possible that formal schooling, with its significant cognitive and social demands, could exacerbate behavior problems. Second, video game exposure varies between preschoolers and school-age children. These different play patterns are likely the result of the types of content typically available for or preferred by each age group as well as a better developed ability to navigate the complexities associated with playing video games (e.g., motor skills, ability to read, understanding of how video games work). Consequently, parenting styles, cumulative risk, and video game exposure that might have been harmful, helpful, or unrelated to behavior in preschoolers could manifest differential effects in a school-age population.

The purposes of this study are fourfold and will be examined separately for preschoolers and school-age children. First, the direct relations between exposure and child behavior problems will be tested independently for hyperactivity and attention problems. Next, parenting styles will be included as covariates in each model. Third, cumulative risk and parenting styles will be evaluated as moderators of any relations between total video game exposure and child behavior problems. Finally, differential patterns associated with violent and nonviolent video game content will be tested.

Method

Participants

Participants were 788 parents/primary caregivers of a child between 2 and 5 years old (preschoolers) and 391 parents/primary caregivers of a child between 6 and 8 years old (school-age). An additional 298 parents/primary caregivers were not included in the analysis because their child was under 2 years of age and the outcomes of interest could not be collected for that age-group. Table 1 reports demographic, cumulative risk, video game exposure, parenting styles, and outcomes descriptives for the full sample of preschoolers and school-agers as well as the age cohorts split by cumulative risk status. Descriptive Statistics for Full Sample and Split by Risk Status for Demographics, Cumulative Risk, Video Game Exposure, Parenting Styles, and Child Behavior Problems

Design

Institutional review board approval was obtained from the University of Pennsylvania prior to a private survey research firm administering a rolling cross-sectional survey using a disproportionate stratified random digit dialing procedure between January and March, 2009. The response rate of 39.1% was similar to other nationally representative surveys conducted with parents of young children (e.g., 40%; see Lapierre et al., 2012, for further details regarding survey implementation).

Procedure

The survey firm administered eligibility screening and informed consent prior to parents completing the 50-min survey. Questions ranged from household demographics, to a 24-hr time use diary, and an assessment of the child’s behavioral functioning. Parents were compensated US$25 when using a landline (∼96%) and US$50 when using a cellphone. No demographic differences were found between those contacted via landline and those contacted via cellphone.

Demographic Measures

Parents were asked a series of questions regarding child and family characteristics. See Table 1 for full descriptive statistics on all measures.

Cumulative Risk

A cumulative risk index modeled after Sameroff et al. (1998) was created using six demographic variables. Risks were dichotomized into 0 = no risk present and 1 = at risk. The following were included in the index:

Child’s racial/ethnic background

Children whose parents identified them as Latino/a, African American, Hispanic, American Indian, or other were coded as minority status and coded at risk.

Children in the household

Children living in families with four or more children in the home were considered at risk.

Maternal age

Children whose mothers were younger than 18 years at the time of their child’s birth were coded at risk.

Maternal education

Children whose mothers reported having less than a high school diploma were coded at risk.

Single parent status

Children who were living in families where there was only one adult caregiver in the home were considered at risk.

Socioeconomic status

An income-to-needs ratio was calculated based on 2009 federal poverty guidelines by asking parents their average household income and their family size (Federal Register, 23 January 2009). Children whose income-to-needs ratio was less than 2.0 were considered at risk.

Parenting Style

Based on Baumrind’s conceptualization of parenting styles (1991), two subscales of the original 62-item questionnaire (Robinson, Mandleco, Olsen, & Hart, 1995) were administered to all participants: degree of parenting responsiveness and degree of parenting inconsistency (lack of follow through). Each was measured via seven items using a 5-point Likert scale: 1 (never) to 5 (always; e.g., how often does parent find it difficult to discipline the child: α = .73, inconsistency; how often does parent praise the child: α = .83, responsiveness).

Child Ability Covariate

Based on prior research suggesting relations among parenting quality, early language and reading skills, and the outcomes examined here (Bernier, Carlson, & Whipple, 2010), vocabulary size (children between 2 and 3 years old), language skills (children between 3 and 6 years old), and early literacy skills (children between 6 and 8 years old) were included as covariates in all models.

Vocabulary skills

Vocabulary skills for preschool children between 2 and 3 years old were assessed via the MacArthur CDI III short form (MCDI), a 100-item vocabulary production checklist. Raw scores were converted to percentile ranks accounting for both sex and age differences. Validity estimates were calculated using the McCarthy Scales of Children’s Ability (.47–.56); the Peabody Picture Vocabulary Test (.41–.49); and conversational language samples (.26–.42; Feldman et al., 2005). Three- to 5-year-olds’ language skills were based on 10 questions adapted from the Assessment of Literacy and Language (ALL; Lombardino, Lieberman, & Brown, 2005). These items asked parents to report their child’s vocabulary knowledge, language complexity, and articulation ability. Exploratory factor analysis supported a one-factor model for these 10 items with adequate internal reliability (Cronbach’s alpha = .77).

Literacy skills

Literacy skills for children between 6 and 8 years old were based on a series of questions about the child’s phonological and phonemic awareness abilities and their early reading skills (e.g., does your child read simple stories? Chapter books?). Items were selected from the ALL (Lombardino et al., 2005) and the National Household Education survey (O’Donnell, 2008). A one-factor model was found through an exploratory factor analysis. The scale’s internal reliability estimate was adequate (Cronbach’s alpha = .91).

Video Game Exposure

A 24-hr time diary adapted from the Panel Study of Income Dynamics was administered to capture the duration of all of the child’s activities from the previous weekday or weekend day (or most recent typical day if previous day was atypical). Total video game exposure was operationalized as the total number of hours of video game play parents reported their child did during the previous 24 hr. In addition, when parents reported their children playing video games, interviewers asked them what the title of the video game was. Each title was then categorized as containing any violence or no violence using content codes supplied by the Entertainment Software Rating Board (ESRB, 2014).

Outcome Measures

Two subscales (i.e., hyperactivity, attention problems) were used from the widely used parent-report measure Behavior Assessment System for Children (BASC-2; Reynolds & Kamphaus, 2004). The BASC-2 has sound psychometric properties (internal consistency = .90 to .91; test–retest = .84) and is able to discriminate between groups of children with preexisting clinical diagnoses (Sullivan & Riccio, 2006). Convergent validity is reported with The Achenbach System of Empirically Based Assessment (.71–.83); the Conner’s Rating Scales (.51–.78); and the Behavior Rating Inventory of Executive Function (.83, global executive function composite). Questions were answered using a 4-point Likert scale (i.e., 1 (never) to 4 (almost always)). Two separate versions of the BASC-2 Scales were administered based on the child’s age: preschool (2–5 years old) and school-age (6–8 years old). Summed raw scores were converted to T scores (M = 50, SD = 10). Higher scores on each subscale were indicative of more behavior problems (i.e., greater levels of hyperactivity or more attention difficulties). Specifically, scores ranging from 60 to 69 were considered at risk for maladjustment while scores 70 or higher were considered clinically significant for behavior problems.

Analytic Approach

Multiple linear regression models were computed within the survey module of STATA 12.0 to include the survey weight correction thereby eliminating problems arising from incorrect standard error estimates (see Lapierre et al., 2012, for details). Weights were included to adjust for differing probabilities in the likelihood of selection for all survey respondents as well as to account for coverage gaps and nonresponse biases in the survey frame. Weights were poststratified along several dimensions using estimates from the 2009 Census American Community Survey.

To address the research questions, four sets of regression models were computed separately by age (i.e., preschool, 2–5 years old; school-age, 6–8 years old), each building upon the last. First, the direct associations between video game exposure and hyperactivity and inattention were computed with demographic covariates included (Models 1a/b). Next, parenting styles (i.e., responsive, inconsistent) were included as individual covariates to determine whether removing the variance associated with parenting changed any relations between exposure and outcomes (Models 2a/b). The third set of models involved first splitting the sample into low-risk and high-risk groups based on previous research indicating significant differences in relations across low- and high-risk (Linebarger et al., 2014; Sameroff et al., 1998). Then, each model included interaction terms between both parenting styles and total video game exposure to test the moderating effects of parenting styles (Models 3a–d). Interaction terms were created by first centering the independent variable and the two moderators. Table 2 provides information about exposure and both behavior problems by a median split for responsiveness and consistency (i.e., high/low) for age-groups. The fourth set of models were constructed the same way as Models 3a–d; however, video game exposure was split into violent content and nonviolent content and interaction terms were created for both parenting styles and both exposure categories (Models 4a–d). When significant interactions between parenting style and video game exposure were found, simple effects slopes were calculated for the mean and ±1 standard deviation for responsiveness. Graphs were created using these responsiveness values and three levels of video game exposure: none, 30 min, and 60 min. Means for Video Game Exposure, Hyperactivity, and Attention Problem Split by Age and Parenting Style

High risk was operationalized as 2 or more cumulative risk factors (Sameroff et al., 1998). Although Models 3 and 4 involved splitting children into low- and high-risk samples, when each regression was computed, the original continuous risk variable was used; therefore, in the low-risk regressions, risk was either 0 or 1 whereas in the high-risk regressions, risk ranged from 2–6 risks. Tables 3–8 provide detailed regression results. Regression Results Predicting Preschool Behavior Problems From Video Game Exposure Without (Model 1) and With (Model 2) Parenting Style Included as a Covariate Regression Results Predicting School-Age Behavior Problems From Video Game Exposure Without (Model 1) and With (Model 2) Parenting Style Included as a Covariate Regression Results Predicting Preschool Behavior Problems From Video Game Exposure With Cumulative Risk and Parenting Style Included as Moderators (Model 3) Regression Results Predicting School-Age Behavior Problems From Video Game Exposure With Cumulative Risk and Parenting Style Included as Moderators (Model 3) Regression Results Predicting Preschool Behavior Problems From Video Game Exposure Split by Content With Cumulative Risk and Parenting Style Included as Moderators (Model 4) Regression Results Predicting School-Age Behavior Problems From Video Game Exposure Split by Content With Cumulative Risk and Parenting Style Included as Moderators (Model 4) Regression Results Predicting Preschool Behavior Problems From Video Game Exposure Without (Model 1) and With (Model 2) Parenting Style Included as a Covariate Regression Results Predicting School-Age Behavior Problems From Video Game Exposure Without (Model 1) and With (Model 2) Parenting Style Included as a Covariate Regression Results Predicting Preschool Behavior Problems From Video Game Exposure With Cumulative Risk and Parenting Style Included as Moderators (Model 3) Regression Results Predicting School-Age Behavior Problems From Video Game Exposure With Cumulative Risk and Parenting Style Included as Moderators (Model 3) Regression Results Predicting Preschool Behavior Problems From Video Game Exposure Split by Content With Cumulative Risk and Parenting Style Included as Moderators (Model 4) Regression Results Predicting School-Age Behavior Problems From Video Game Exposure Split by Content With Cumulative Risk and Parenting Style Included as Moderators (Model 4) Figure 1. Low-risk preschoolers’ hyperactivity levels by parental responsiveness and nonviolent video game exposure. Figure 2. High-risk preschoolers’ attention problems by parental responsiveness and nonviolent video game exposure. Figure 3. Low-risk school-age children’s attention problems by parental responsiveness and nonviolent video game exposure. Figure 4. High-risk school-age children’s hyperactivity levels by parental responsiveness and nonviolent video game exposure.

Results

Model 1: Does Video Game Exposure Predict Child Behavior Problems and Do the Patterns Differ for Hyperactivity and Inattention?

Hyperactivity

Each hour of video game exposure was associated with a 2.36-point increase in hyperactivity scores in preschoolers with the model, accounting for 8.6% of the variance in the outcome (Table 3). Video game exposure was unrelated to hyperactivity in school-age children although the overall model accounted for 16.2% of the variance (Table 4). Regression Results Predicting Preschool Behavior Problems From Video Game Exposure Without (Model 1) and With (Model 2) Parenting Style Included as a Covariate Regression Results Predicting School-Age Behavior Problems From Video Game Exposure Without (Model 1) and With (Model 2) Parenting Style Included as a Covariate

Attention problems

Video game exposure was unrelated to attention problems in both preschoolers (Table 3) and school-age children (Table 4), with the models accounting for 10.1% and 16.0% of the variance, respectively.

Model 2: After Including Parenting Styles as Covariates, Does Video Game Exposure Predict Child Behavior Problems and Do the Patterns Differ for Hyperactivity and Inattention?

Hyperactivity

Once parenting styles were included as covariates, video game exposure was no longer associated with hyperactivity scores in preschoolers (Table 3). The association between exposure and hyperactivity was also not significant for school-age children (Table 4). The inclusion of both parenting styles to the models explained an additional 13.8% of the variance in preschoolers’ hyperactivity scores and 11.3% in school-agers’ scores.

Attention problems

Video game exposure was unrelated to attention problems in both preschoolers (Table 3) and school-age children (Table 4). The inclusion of both parenting styles to the models explained an additional 8.9% of the variance in preschoolers’ attention scores and 4.0% in school-agers’ scores.

Model 3: Do Cumulative Risk and Parenting Styles Moderate the Relations Between Video Game Exposure and Child Behavior Problems?

Low-risk preschoolers

Responsive parenting moderated the relation between exposure and hyperactivity levels, increasing the amount of variance accounted for by 4.2% (Tables 5). Parenting did not moderate the relation between exposure and attention problems. Parental consistency also did not moderate the exposure/hyperactivity relationship. Regression Results Predicting Preschool Behavior Problems From Video Game Exposure With Cumulative Risk and Parenting Style Included as Moderators (Model 3)

At low and mean levels of video game exposure, children whose parents were more responsive exhibited lower levels of hyperactivity compared with children whose parents were average in responsiveness or low in responsiveness. Further, increasing levels of exposure were associated with concomitant increases in hyperactivity levels. For children whose exposure levels were 1 standard deviation above the mean, there were no differences associated with responsiveness; that is, all children exhibited significantly higher levels of hyperactivity.

High-risk preschoolers

Responsive parenting moderated the relation between exposure and attention problems, increasing the amount of variance accounted for by 3.3% but was unrelated to hyperactivity levels in high-risk preschoolers (Tables 5). Consistency did not moderate the exposure/behavior problems relationship.

In general, children with low levels of exposure to video games exhibited more attention problems. As exposure increased, attention problems decreased. When video game exposure was high, children with more responsive parents exhibited better attention. Conversely, when video game exposure was low, children with less responsive parents exhibited better attention. There were no differences in attention problems associated with responsiveness for children whose video game exposure was average.

Low-risk school-agers

Responsive parenting moderated the relation between exposure and attention problems increasing the amount of variance accounted for by 1.0% but was unrelated to hyperactivity levels in low-risk school-agers (Tables 6). Consistency did not moderate the exposure/behavior problems relationship. Regression Results Predicting School-Age Behavior Problems From Video Game Exposure With Cumulative Risk and Parenting Style Included as Moderators (Model 3)

In general, children with low levels of exposure to video games exhibited more attention problems. As exposure increased, attention problems decreased. When video game exposure was average or high, children with more responsive parents exhibited better attention. There were no differences in attention problems associated with responsiveness for children whose video game exposure was low.

High-risk school-agers

Responsive parenting moderated the relation between exposure and hyperactivity levels, increasing the amount of variance accounted for by 2.7% but was unrelated to hyperactivity levels in high-risk school-agers (Tables 6). Parental consistency was unrelated to the exposure/behavior problems relations. Although parenting styles did not moderate the relation between exposure and attention problems for high-risk school-age children, there was a direct effect of exposure on attention problems. As exposure increased, attention problems increased by 2.40 points per hour.

In general, children with low levels of exposure to video games exhibited higher levels of hyperactivity. As exposure increased, hyperactivity decreased. When video game exposure was low or average, children with more responsive parents exhibited higher hyperactivity levels. There were no differences in hyperactivity associated with responsiveness for children whose video game exposure was high.

Model 4: Do the Patterns Observed for Overall Video Game Exposure, Cumulative Risk, and Parenting Styles Vary When Video Game Exposure Is Divided Into Content Categories?

Low-risk preschoolers

Responsive parenting moderated the relation between video game exposure and both hyperactivity and attention problems in low-risk preschoolers, increasing the variance in each model by 4.6% and 0.2%, respectively (Tables 7). Consistency did not moderate the exposure/behavior problems relationship. Because the increase in variance accounted for in the attention model was quite small and nonsignificant, the interactions model will not be discussed further. Regression Results Predicting Preschool Behavior Problems From Video Game Exposure Split by Content With Cumulative Risk and Parenting Style Included as Moderators (Model 4)

As nonviolent video game exposure increased, all children’s hyperactivity levels were higher (Figure 1). At no and 30-min exposure, children’s hyperactivity scores fell within the normal range. Children with no exposure whose parents were more responsive exhibited the lowest levels of hyperactivity, 4 points lower than their peers whose parents were the least responsive (just under half a standard deviation). Hyperactivity scores for children with at least 1 hr of exposure to nonviolent video games the previous day were considered in the clinically significant range for all children regardless of responsiveness; that is, all low-risk preschoolers who played at least 1 hr of nonviolent video games the previous day were reported to exhibit hyperactivity behaviors that put them at risk for maladjustment problems related to hyperactivity. Children whose parents were highly responsive obtained scores that were 2.5 points worse than their peers whose parents were the least responsive (i.e., about ¼ standard deviation difference). Figure 1. Low-risk preschoolers’ hyperactivity levels by parental responsiveness and nonviolent video game exposure.

High-risk preschoolers

Responsive parenting moderated the relation between video game exposure and both hyperactivity and attention problems in high-risk preschoolers, increasing the variance in each model by 1.2% and 4.4%, respectively (Tables 7). Consistency did not moderate the exposure/behavior problems relationship. Because the increase in variance accounted for in the hyperactivity model was small and nonsignificant, this interactions model will not be discussed further.

As nonviolent video game exposure increased, all children’s attention problems were lower (Figure 2). Children with no exposure had attention problem scores in the clinically significant range for maladjustment problems. In contrast, high-risk preschoolers with 30 min or more of nonviolent video game exposure during the previous day obtained attention problem scores in the normal range. At 30 min of exposure, children with highly responsive parents obtained scores 4 points better than their peers with the least responsive parents (i.e., nearly ½ standard deviation better) whereas at 60 min of exposure, children with highly responsive parents obtained scores 8 points better than their peers with the least responsive parents (i.e., nearly 1 standard deviation better). Figure 2. High-risk preschoolers’ attention problems by parental responsiveness and nonviolent video game exposure.

Low-risk school-agers

Responsive parenting moderated the relation between video game exposure and attention problems only in low-risk school-agers increasing the variance by 11.2% (Tables 8). Consistency did not moderate the exposure/behavior problems relations. Although parenting did not moderate the relation between exposure and hyperactivity problems for low-risk school-age children, there was a direct effect of exposure on hyperactivity levels. As violent video game exposure increased, hyperactivity levels increased by 2.31 points per hour. Regression Results Predicting School-Age Behavior Problems From Video Game Exposure Split by Content With Cumulative Risk and Parenting Style Included as Moderators (Model 4)

Attention problem scores were within the normal range for all low-risk school-age children regardless of responsiveness and nonviolent video game exposure although children who had no exposure had higher attention problem scores compared with their peers with 30 or more min of exposure (Figure 3). In addition, children whose parents were highly responsive obtained attention problem scores that were between 4 and 6.5 points better than their peers whose parents were the least responsive. Figure 3. Low-risk school-age children’s attention problems by parental responsiveness and nonviolent video game exposure.

High-risk school-agers

Responsive parenting moderated the relation between video game exposure and hyperactivity levels only in high-risk school-agers, increasing the variance by 3.1% (Tables 8). Consistency did not moderate the exposure/behavior problems relations. Although parenting did not moderate the relation between exposure and attention problems for high-risk school-age children, there was a direct effect of exposure on attention problems. As nonviolent video game exposure increased, attention problems increased by 2.80 points per hour.

In general, children with low levels of exposure to nonviolent video games exhibited higher hyperactivity levels (Figure 4). As exposure increased, hyperactivity levels decreased. For high-risk school-age children with 30 min or no exposure, hyperactivity scores were in the at risk and clinically significant range, respectively. Only children with 60 min or more of nonviolent video game exposure obtained hyperactivity scores within the normal range. Children with no exposure whose parents were also highly responsive obtained hyperactivity scores that were nearly 4 points worse when compared with their peers whose parents were the least responsive (i.e., nearly ½ standard deviation). There were no differences in hyperactivity scores associated with responsiveness for children who were exposed to 60 min or more of nonviolent video games. Figure 4. High-risk school-age children’s hyperactivity levels by parental responsiveness and nonviolent video game exposure.

Discussion

Video game exposure was directly associated only with increasing levels of hyperactivity in preschool children, an effect reduced to nonsignificance when parenting styles were covaried out of the model, a finding consistent with previous research (Parkes et al., 2013). No direct relations without or with parenting styles included as covariates were observed between preschoolers’ exposure and attention problems or school-agers’ exposure and both hyperactivity and attention problems. Adding cumulative risk and parenting styles as moderators did increase the amount of variance accounted for across both the preschool and school-age samples. Responsive parenting moderated the effects of video game exposure for low-risk preschoolers’ and high-risk school-age children’s hyperactivity levels and high-risk preschoolers’ and low-risk school-age children’s attention problems. In the final set of models with video game exposure broken into violent and nonviolent content, different patterns of effects and larger effect sizes emerged across cumulative risk, responsiveness, and nonviolent video game exposure. Violent video game exposure was associated only with low-risk school-age children’s increasing hyperactivity levels. These results indicate that an ecological approach which considers multiple and interacting child and family factors be used while investigating media effects (see Barr & Linebarger, 2010; Jordan, 2004; Linebarger et al., 2014; Linebarger & Vaala, 2010).

Parenting Styles

Parenting plays a central role in the development and consolidation of the regulatory functions of attention and hyperactivity (Nigg et al., 2006). These skills are rapidly developing during early childhood. Parenting consistency functioned as a main effect in the majority of models tested, predicting lower levels of hyperactivity and fewer attention problems. When parents were more inconsistent and unpredictable, children’s behavior problems increased similarly without any additional buffering or exacerbation linked to video game exposure.

On the other hand, moderating effects were observed with responsiveness. Research involving children with clinical diagnoses of ADHD documents that responsive parenting is particularly relevant to externalizing problems including hyperactivity and impulsivity (Johnston, Murray, Hinshaw, Pelham, & Hoza, 2002; Rothbaum & Weisz, 1994). The ability to monitor and sensitively respond to challenging behavior is more difficult when a child displays impulsive, disorganized, and poorly regulated behavior (Johnston et al., 2002). In responsive households, parents are more sensitive to their child’s cues thereby contributing to a child’s sense of trust in and understanding that his or her needs will be met. This trust, in turn, facilitates the development of a child’s appropriate behavioral responses and effective coping styles leading to competence in self-regulating (Landry, Smith, & Swank, 2003).

Responsiveness moderated the video game exposure/behavioral problems relations differently depending on cumulative risk and only for nonviolent video game exposure. As nonviolent video game exposure increased, low-risk preschoolers’ hyperactivity levels increased. Preschoolers whose parents were highly responsive had the lowest levels of hyperactivity when they also had no exposure to nonviolent video games when compared with preschoolers whose parents were the least responsive. The reverse was true for these low-risk preschoolers at 60 min of nonviolent video game exposure; that is, preschoolers with highly responsive parents had the highest levels of hyperactivity compared with their peers with the least responsive parents. One explanation for these differences may be that low-risk preschoolers, particularly those with highly responsive parents, who spend a lot of time playing nonviolent video games are spending less time with their parents or less time engaged in cognitively stimulating activities that have been traditionally associated with positive developmental outcomes (e.g., more book reading). In this study, low-risk preschoolers who played video games the previous day spent 18 min reading versus 25 min spent reading by low-risk preschoolers who did not play any video games the previous day. These low-risk preschool video game players were also exposed to 3.41 hr of background TV the previous day compared with 2.71 hr of background TV for those who did not play. Previous research indicates that higher levels of exposure to background TV for preschoolers is associated with worsening executive function skills (Linebarger et al., 2014). It is important to note that the time diary used in this study only measured exposure during the prior 24 hr and, as such, it is difficult to know whether those who played video games did so on a more regular basis and for longer than their peers who did not play during the prior 24 hr. Additional detailed and extensive diary studies are needed to investigate this more carefully.

High-risk preschoolers’ attention problem scores decreased as their exposure to nonviolent video games increased. No exposure was associated with behavior problem scores indicative of attention maladjustment regardless of parenting responsiveness. In contrast, attention problems scores were within the normal range for high-risk preschoolers when they were exposed to 30 or more minutes of nonviolent video games during the prior 24 hr. Further, high-risk preschoolers whose parents were also highly responsive had the fewest attention problems, between 4 and 8 points (about ½ to ¾ of a standard deviation) better than their peers whose parents exhibited average or low levels of responsiveness. Children who are high-risk due to sociodemographic characteristics such as living in poverty with less educated parents and often in single-parent homes tended to exhibit more behavior problem symptomology compared with their low-risk peers (Galéra et al., 2011). Although the direction of the effects between nonviolent video game exposure and attention problems is unclear, these results provide intriguing evidence that nonviolent video game exposure plays some role in the development of attentional skills in these high-risk preschoolers’ lives. For instance, video games might provide some type of structure and environmental input that may be lacking in high-risk homes where material and educational resources are limited and parenting, while warm and responsive, was also more likely to be inconsistent. Video games are structured so that players are constantly operating at the outer edge of their competence, with continual challenges (Gee, 2007). The key is that these challenges are difficult but not undoable. In addition, video games offer immediate feedback and potential rewards that likely encourage the child to continue playing, improving task performance that, in turn, contributes to greater advancements within the game. With appropriate scaffolding, video game content can provide a bridge between what a child can do currently and new competencies. Similarly, appropriate parental scaffolding, a skill more often found with responsive parents (Landry, Miller-Loncar, Smith, & Swank, 2002), has been linked to stronger executive function skills (to which impulse control contributes) in preschoolers (Landry et al., 2002).

Both high- and low-risk school-age children’s behavior problems scores were lower as nonviolent video game exposure increased. Specifically, hyperactivity levels were lower and in the normal range for high-risk school-age children when their exposure levels topped 60 min whereas all low-risk school-age children’s attention problems scores were within the normal range regardless of exposure although children with no exposure obtained the poorest attention scores.

Video Game Content Effects

Not all relations between video game exposure and behavior problems were moderated by responsiveness. Two models evidenced only main effects of video game exposure although cumulative risk differentiated the results. Low-risk school-age children’s hyperactivity scores were 2.31 points higher (∼¼ standard deviation; β = .15) for every hour of violent video games played whereas high-risk school-age children’s attention problems scores were 2.80 points higher (∼¼ standard deviation; β = .28) for every hour of nonviolent video games played. The research investigating the relations between violent video game exposure and behavior problems are mixed (see recent meta-analyses by Anderson & Bushman, 2001; Ferguson & Kilburn, 2009) likely due to a combination of poor measurement of behavior problems (e.g., combining attention and hyperactivity items in the same scale; Swing et al., 2010) and lack of precision in the exposure estimates (specifically for correlational studies). In addition, the size of the observed effects tends to be small, accounting for less than 10% of the variance and usually less than 5%. More time spent playing violent video games likely displaced low-risk school-age children’s time spent with parents and in activities that have been traditionally and positively associated with low-risk children’s development (e.g., reading, cognitively stimulating materials and experiences; Bradley, Corwyn, Burchinal, McAdoo, & Garcia Coll, 2001; Bradley, Corwyn, McAdoo, & Coll, 2001). Other research has found similar results for school-age children (Wright et al., 2001).

Most of the significant effects found in this study were associated with nonviolent video game exposure especially in combination with responsiveness likely because all children in this study who played video games were more likely to play nonviolent ones (3 min to every 1 min of violent content in preschool; 1.67 min to every 1 min of violent content in school-age). As described above, exposure to violent video games was associated only with low-risk school-age children’s hyperactivity scores. Video games coded as violent consisted of titles mainly in the ESRB category E (generally suitable for everyone) and E10 (suitable for children 10 years and older). Violent content descriptors for these games included “minimal cartoon, fantasy, or mild violence” (ESRB, webpage http://www.esrb.org/ratings/ratings_guide.jsp; Lego Batman or Lego Star Wars, various Super Mario Cart/Party games, and a variety of Wii Sports contact games such as Wii Play and Tony Hawk).

Limitations

There are several limitations to the presented findings. First, this study is a cross-sectional correlational study that relies on parental report. In no way is it possible to determine the direction of the effects. Although exposure may cause behavior problems, it is equally likely that behavior problems existed and exposure followed. Or, the relationship could be reciprocal. Research indicates that problematic video game use is higher among children with clinical ADD/ADHD diagnoses although time spent playing does not differ (Mazurek & Engelhardt, 2013). Perhaps video games engage these children in different ways. In addition, parents of children with higher levels of hyperactivity and more attention challenges may allow their children to use video games as a way to manage difficult behavior (Gadow & Sprafkin, 1993). Second, the exposure measure used (a time diary recording all activities during the previous 24 hr including duration and title of any media activities) was only able to provide estimates of the previous day’s use. Consequently, just 17.5% of the sample reported any video game use the prior day, a percentage consistent with recent estimates of daily use (i.e., 17%; Commonsense Media, 2011). These data underestimate all children’s use of video games and likely underestimate the associations reported here.

Conclusion

Collectively, the results highlight the multiple and interdependent contextual factors that are associated with child behavior problems including the home environment, the quality of the parent–child relationship, and exposure to different genres of video games. Total video game exposure did directly predict higher levels of hyperactivity in the preschool sample, just one of four direct associations tested. Covarying out parenting variables reduced this direct relation to nonsignificance. More importantly, dividing exposure into nonviolent and violent content and including parenting styles and cumulative risk as moderators offered a clearer picture of the results; accounted for a greater percentage of the variance in child behavior problems; and helped to uncover effects absent or minimal in other studies when such variables were not included (Swing et al., 2010), were covaried out (Parkes et al., 2013), or were collected with a great deal of imprecision (Ferguson, 2011). Future research would benefit from methods that measure exposure and outcomes with greater precision, designs and analyses that include multiple contextual factors like those tested here (i.e., cumulative risk, parenting styles, different video game content), and analyses that allow these factors to vary and interact (Bronfenbrenner & Morris, 2006).

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Submitted: March 3, 2014 Revised: November 20, 2014 Accepted: December 3, 2014

This publication is protected by US and international copyright laws and its content may not be copied without the copyright holders express written permission except for the print or download capabilities of the retrieval software used for access. This content is intended solely for the use of the individual user. Source: Psychology of Popular Media Culture. Vol. 4. (4), Oct, 2015 pp. 375-396) Accession Number: 2015-14739-001 Digital Object Identifier: 10.1037/ppm0000069

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