Journal of Youth and Adolescence

, Volume 39, Issue 2, pp 103–113 | Cite as

More Than a Just a Game: Video Game and Internet Use During Emerging Adulthood

  • Laura M. Padilla-Walker
  • Larry J. Nelson
  • Jason S. Carroll
  • Alexander C. Jensen
Empirical Research

Abstract

The purpose of this study was to gain a clearer understanding of the pattern of video game and internet use among college students and to examine how electronic leisure was related to risk behaviors (i.e., drinking, drug use, sex), perceptions of the self (i.e., self worth and social acceptance), and relationships with others (i.e., relationship quality with parents and friends). Participants included 813 undergraduate students (500 young women, 313 young men, M age = 20, SD = 1.87) who were mainly European American (79%), unmarried (100%) and living outside their parents’ home (90%). Results suggested that (a) video game use was linked to negative outcomes for men and women, (b) different patterns of video game and internet use existed for men and women and (c) there were different relations to risk behaviors, feelings about the self, and relationship quality based on the type of internet use, and based on gender. The discussion focuses on the implications of electronic leisure on the overall health and development of young people as they transition to adulthood.

Keywords

Video games Internet use Emerging adults 

Introduction

The leisure activities of emerging adults (individuals approximately ages 18–25) have dramatically changed during the last 10–15 years, with video game and internet use dominating free time that is occupied increasingly by electronic leisure. Longitudinal research suggests that only 24.5% of students used the internet in 1996 compared to 79.5% in 2001 (Hendel and Harrold 2004), while other sources suggest that as many as 95% of college students use the internet (Odell et al. 2000). Other sources report that the internet is used at least 30 min a day by 80% of 18–29 year olds and that 85% of college students own their own computer (America’s online pursuits 2003; The internet goes to college 2002). Taken together, it is clear that the use of electronic media has become a prominent aspect of the lives of college-aged individuals. Thus, in the current study we sought to gain a clearer understanding of the pattern of both video game and internet use among emerging adults, and how electronic leisure activity might be related to outcomes such as risk behaviors (i.e., drinking, drug use, sex), perceptions of the self (i.e., self worth and social acceptance), and relationships with others (i.e., relationship quality with parents and friends). The current study also examined gender differences in both the frequency of use and the patterns of relationships between use and outcomes.

Theoretical Approach

Brown (2006) has proposed the media practice model as a way that emerging adults select the types of media they interact with, and how these media choices further influence their identity. According to this model, who one is and the way one interacts with the world will influence what media an individual chooses. In turn, the way that individuals interact with and make sense of media will impact how they incorporate it into their daily lives, and will influence their behaviors and views of the world. For example, if emerging adults see themselves as victims, then they will be more likely to interact with media that portrays people as victims. The media they interact with will then have an influence on how they further develop their identity in this regard. If this media commonly shows victims acting out against others in aggressive ways, then individuals may integrate that concept into their own identity, becoming more socialized into aggressive and externalizing behaviors.

The media practice model also aligns with the work of Arnett (1995), suggesting that adolescents and emerging adults use media as a form of self-socialization. These theoretical approaches are similar in that both highlight the fact that the individual’s activities are self-chosen and actively sought out in an attempt at socialization. Arnett points out that, aside from peers, media is one of the most influential socialization agents that individuals choose for themselves (i.e., other socializing agents such as family, societal laws, community members and cultural beliefs are not chosen by the individual). Taken together with the media practice model (Brown 2006), who the individual is will inherently influence what media is chosen as a source of socialization, which in turn will influence the person’s identity formation. Given that emerging adulthood is a developmental period characterized by exploration and experimentation with various potentially risky behaviors (Schulenberg and Zarrett 2006), a time of identity formation when perceptions of self are especially salient (Arnett 2000), and a period during which individuals are renegotiating relationships with both parents, friends, and romantic partners (see Collins and Madsen 2006), it follows that emerging adults would seek out media that socializes them in this regard. Given this assumption, the current study examined how electronic media use was related to risk behaviors, perceptions of self, and relationships.

Video Game Use

Compared to the video games that were predominant 20 years ago, current video games are more sophisticated, more violent, and frequently include multiplayer online games (Anand 2007). While Olson et al. (2007) and others have studied the effects of video game use on adolescents, the majority of video game players are actually over the age of 18 (Anand 2007), most likely because these individuals have somewhat flexible schedules and a lack of supervision, which results in an increase in electronic leisure activity such as video game use (Olson et al. 2007). To date there are relatively few studies examining frequencies of video game use among emerging adults, or examining how use might be related to outcomes. The research that has been conducted suggests a negative correlation between time spent playing video games and academic performance (Anand 2007; Anderson and Dill 2000), and a positive relationship between violent video game use and aggression (Anderson and Dill 2000). However, our review of the recent literature has failed to reveal any research regarding video game use and correlations between other relevant items such as risk behaviors, self-perceptions, and relationship quality. Current research also suggests that video game use is primarily a male dominated leisure activity (Anand 2007; Olson et al. 2007), but little or no research has highlighted the impact that video game playing may have on the emerging adult women who do play.

Internet Use

Research on internet use among emerging adults has been more extensive than the research on video game use, with many of the existing studies focusing on frequency and amount of use. However, there are a few studies that have gone beyond frequency of use and examined the correlates of internet use. For example, Kraut et al. (2002) examined personality factors related to internet use and found that as extroverts used the internet more, they were more likely to be involved in the community, to have higher levels of self esteem, and to be less lonely. However, others have found that frequent internet users have lower self esteem than those who do not use the internet frequently (Landers and Lounsbury 2006; Niemz et al. 2005). Taken together, these studies suggest an association between internet use and self-perceptions, but conflicting findings necessitate further research that examines not only frequency of internet use, but type of internet use as well. In addition, we are aware of no research that examines the relationships between internet use and risk behaviors or relationship quality.

Although many studies examine the frequency of internet use, others suggest that it is more important to study the type of internet use (Gordon et al. 2007; Niemz et al. 2005). This debate is similar to the medium (any medium is negative because it takes you away from other things) versus content (the impact of media depends on the content) debate that exists in regard to television use (Anderson et al. 2001). Although there is evidence for both of these theoretical approaches, content theory has received more support (Gordon et al. 2007), suggesting that what one watches may be more important than the sheer number of hours watching television. Based on these theoretical approaches, the current study will examine overall internet use (medium approach), but will also examine how the association between internet use and outcomes may differ depending on the content of internet use.

Most researchers have found gender differences in the type of internet use, with males spending more time on the internet overall (Gordon et al. 2007; Sherman et al. 2000) as well as using it more for sex sites, research, news, games, and downloading music (Gordon et al. 2007; Odell et al. 2000), while females spend more time using the internet for e-mail. Although findings generally support gender differences in use, there is a need to explore how the type of internet use might be differentially related to outcomes for males and females.

Hypotheses

As a result of the dearth of research on electronic media use during emerging adulthood, a foundation for specific hypotheses was sometimes difficult to provide. However, based on theoretical models of media as a socialization agent (Arnett 1995; Brown 2006), we expected that the use of video games and violent video games would be positively related to risk behaviors, and negatively related to self-perceptions and relationship quality. Following the work of Anand (2007) and Olson et al. (2007), we anticipated finding gender differences in the frequency of video game use, and we also expected gender differences in how video game use was related to outcomes (although it was difficult to speculate specific differences in this regard). In the case of internet use, we also expected to find gender differences in the frequency and type of use (Gordon et al. 2007; Odell et al. 2000; Sherman et al. 2000), and explored whether the types of internet use were differentially associated with outcomes as a function of gender (Gordon et al. 2007; Niemz et al. 2005).

Method

Participants

Participants for this study were drawn from an ongoing study of emerging adults and their parents entitled “Project READY” (Researching Emerging Adults’ Developmental Years). The sample used in the current study consisted of 813 undergraduate students (500 young women, 313 young men) recruited from six college sites across the United States. For the purpose of current analyses, university site was collapsed into four sites that were meaningfully different from one another. Site 1 (n = 261) is a medium sized private religious university on the east coast, site 2 (n = 307) consists of two large public universities in the Midwest, site 3 (n = 106) consists of two small Liberal Arts colleges on the East coast, and site 4 (n = 129) is a large public university on the West Coast.

The mean age of the sample was 20.00 years (SD = 1.82) for women and 20.04 years (SD = 1.87) for men (age ranged from 18 to 26). Seventy-nine percent of the participants were European American, 4% were African American, 9% were Asian American, and 6% indicated that they were “mixed/biracial” or of another ethnicity. All of the participants were unmarried and 90% reported living outside their parents’ home in an apartment, house, or dormitory.

Procedure

Participants completed the Project READY questionnaire via the Internet (see http://www.projectready.net). Participants were recruited through faculty’s announcement of the study in undergraduate and graduate courses. Informed consent was obtained online, and only after consent was given could the participants begin the questionnaires. Each participant was asked to complete a survey battery of 448 items. Most participants were offered course credit or extra credit for their participation. Response rate varied by site (ranging from 50 to 75%), with an overall response rate of ~63%.

Measures

Video game use

To assess video game and violent video game use, participants answered two questions on a 6-point Likert scale ranging from 0 (none) to 5 (every day or almost every day). The questions asked, “During the past 12 months, on how many days did you play video games” and “During the past 12 months, on how many days did you play violent video games”.

Internet use

To assess the frequency of internet use, participants were asked an open-ended question, “On average, how many hours a day do you spend on the internet?” To assess the type of internet use, participants were asked seven questions on a 5-point Likert scale ranging from 1 (never) to 5 (very often), assessing how often they used the internet for the following purposes: entertainment (e.g., games, music, movies), headline news (e.g., national events, politics, international affairs), pornography, e-mail/instant messaging (IM), chat rooms, shopping, and school/work activities.

Risk behaviors

Risk behaviors were assessed using six items from the Add Health Questionnaire (www.cpc.unc.edu/addhealth/). For drinking, participants were asked to report on how many days during the last 12 months they drank alcohol and engaged in binge drinking (drinking 4–5 drinks on one occasion); these two items were averaged (r = .83, < .001). For drug use, participants were asked to report on how many days during the last 12 months they had used marijuana, and used other illegal drugs (e.g., cocaine, heroin, crystal meth, and mushrooms); these two items were averaged (r = .46, < .001). Participants rated responses on a 5-point Likert-type scale ranging from 0 (none) to 5 (every day or almost every day). For the number of sexual partners, participants were asked open-ended questions on how many sexual partners they had in the past 12 months, and how many sexual partners they had in their lives; these two items were averaged (r = .70, < .001).

Self-perceptions

The Self-Perception Profile for College Students (Neeman and Harter 1986, Unpublished manuscript) was used to assess perceptions of self-worth and social acceptance. Participants rated 10 items on a Likert-type scale from 1 (not at all true for me) to 4 (very true for me). Sample items from each subscale include “I like the kind of person I am” for self-worth (six items total), and “I am able to make new friends easily” for social acceptance (four items total). Cronbach’s alphas for self-worth and social acceptance subscales were .80 and .74, respectively.

Quality of social relationships

The short-version of the Social Provisions Questionnaire (Carbery and Buhrmester 1998) was used to assess the quality of friendship and parental relationships. Participants rated 27 items regarding their best friend and their parent. Sample items include, “How happy are you with the way things are between you and this person?”, and “How often do you turn to this person for support with personal problems?” Ratings were made on a 5-point Likert-type scale that ranged from 1 (little or none) to 5 (the most). Cronbach’s alphas for relationship quality with friends and parents were .92 and .91, respectively.

Results

Percent Frequency of Video and Violent Video Game Use by Gender

Because of the paucity of research on frequency of video game use among college students, Table 1 provides a detailed examination of the two video game items by gender. These analyses display a clear picture of video game use as a male dominated leisure activity, with over 50% of young women reporting having never played a video game in the last year, and over 80% reporting having never played a violent video game in the last year. This is compared to over 50% of young men reporting playing video games weekly or more frequently, and nearly 40% reporting playing violent video games weekly or more frequently.
Table 1

Percent frequency of video and violent video game use by gender

 

Young men (%)

Young women (%)

Frequency of video games

    None

15

53

    Once a month or less

13

30

    2 or 3 days a month

18

10

    1 or 2 days a week

22

5

    3–5 days a week

18

1

    Every day or almost every day

15

<1

Frequency of violent video games

    None

25

81

    Once a month or less

16

13

    2 or 3 days a month

20

5

    1 or 2 days a week

18

1

    3–5 days a week

13

<1

    Every day or almost every day

8

<1

Descriptive Statistics as a Function of Electronic Leisure

A number of univariate analyses of variance (ANOVAs) were conducted to determine whether mean levels of electronic leisure differed as a function of gender, living arrangement (living with parents vs. not), and ethnicity (African American, European American, Asian American, and other). In regard to gender, seven of the ten analyses conducted were statistically significant (see Table 2), with young men reporting more video game and violent video game use than did young women. Indeed, young men reported playing video games over three times as often as did young women, and reported playing violent video games nearly eight times as often. Although there were no gender differences in overall internet use, males reported using the internet more frequently for entertainment, daily headline news, and pornography, while females reported using the internet more for e-mail and school work.
Table 2

Mean differences in electronic leisure by gender

 

Young men

Young women

F-test

M

SD

M

SD

Video games

2.61

1.62

.72

.97

425.07***

Violent video games

2.01

1.60

.28

.68

445.33***

Hours on internet

3.59

2.40

3.30

2.66

2.43

    Entertainment

3.64

1.07

3.17

1.17

33.14***

    Daily news headlines

3.22

1.10

2.83

1.08

24.18***

    Pornography

2.45

1.09

1.19

.50

492.55***

    E-mail

4.41

.89

4.66

.64

21.37***

    Chat rooms

1.39

.79

1.31

.68

2.67

    Shopping

2.45

1.03

2.58

1.10

3.00

    School/work

4.28

.87

4.59

.65

32.40***

*** p < .001

In regard to living arrangement, four of the 10 analyses conducted were statistically significant, with individuals living with parents reporting higher video game use (M = 1.98 vs. 1.39; F(1, 801) = 10.54, < .001), violent video game use (M = 1.45 vs. .89; F(1, 798) = 11.84, < .001), pornography use (M = 1.90 vs. 1.65; F(1, 799) = 4.73, < .05), and chatting (M = 1.51 vs. 1.32; F(1, 801) = 5.28, < .05), than did individuals living outside their parents’ home (in a residence hall or apartment). In regard to ethnicity, three of the ten analyses conducted were statistically significant, with African Americans (M = 5.73) reporting spending more time on the internet than did European Americans (M = 3.26), Asian Americans (M = 3.97), and those of other ethnicities (M = 3.34); F(3, 797) = 10.40, < .001; Asian Americans (M = 1.71) reporting chatting more than did African Americans (M = 1.20), European Americans (M = 1.29), and those of other ethnicities (M = 1.48); F(3, 799) = 8.24, < .001; and African Americans (M = 4.03) reporting using the internet for school work less than did European Americans (M = 4.48), Asian Americans (M = 4.44), and those of other ethnicities (M = 4.59); F(3, 799) = 3.97, < .01. Models below were run with university site, gender, living arrangement, and ethnicity as fixed-factors, but because there were no significant main or interaction effects of living arrangement or ethnicity on outcome variables (and removing them from the models did not alter the results), these variables were dropped from analyses for parsimony.

Role of Electronic Leisure, University Site, and Gender on Emerging Adult Outcomes

In order to examine the role of electronic leisure on emerging adult outcomes (risk behaviors, self-perceptions, and relationships), we conducted a number of fixed-effects models (i.e., analyses of covariance with traditional heterogeneity of slopes) with university site (coded as 1 = East Coast Religious, 2 = Midwest Public, 3 = East Coast Liberal Arts, and 4 = West Coast Public) and gender (coded as 0 = male, 1 = female) as fixed-factors; and video game use, violent video game use, frequency of internet use, and type of internet use as continuous predictors. We also examined two- and three-way interactions between the predictor variables and the fixed-effects. Because none of the three-way interactions were significant, they will not be presented.

Risk behaviors

First, we assessed the relationships of video game use, violent video game use, and frequency of internet use on emerging adults’ risk behaviors (separate analyses for drinking, drug use, and number of sexual partners). For drinking, there were main effects of site (F(3, 793) = 27.36, < .001) and gender (F(1, 793) = 9.02, < .01) on emerging adults’ drinking behaviors (for parsimony, main effects of site and gender on outcome variables will not be interpreted, as this is not a focus of the current study). In addition, there was a significant interaction between site and video game use (F(3, 793) = 4.20, < .05) and between gender and violent video game use (F(1, 793) = 8.61, < .01). Simple slope follow-up analyses suggested that, for sites 1 (B = .16, < .001) and 2 (B = .11, < .01), video game use was positively related to drinking behavior; and that violent video game use was related to drinking behavior for young men (B = .13, < .01), but not for young women. For drug use, there was a main effect of site (F(3, 792) = 13.05, < .001) and video game use (F(1, 792) = 14.31, < .001) on emerging adults’ drug use, with parameter estimates suggesting that video game use was positively related to drug use. For the number of sexual partners, there were no significant main effects. However, there was a significant interaction between site and violent video game use (F(3, 792) = 2.77, < .05) and between site and internet use (F(3, 792) = 2.65, < .05). Simple slope follow-up analyses suggested that, for site 3, violent video game use (B = .55, < .001) and internet use (B = .19, < .05) were positively related to number of sexual partners.

Second, we assessed the relationships between the types of internet use (entertainment, headline news, pornography, e-mail, chatting, shopping, and school work) on emerging adults’ risk behaviors. For drinking behaviors, there was a main effect of site (F(3, 759) = 39.02, < .001) and pornography (F(1, 759) = 10.91, < .001), with parameter estimates suggesting that using the internet for pornography was positively related to drinking behaviors. There were also significant interactions between site and news (F(3, 759) = 2.68, < .05) and between gender and shopping (F(1, 759) = 4.53, < .05). Simple slope follow-up analyses suggested that, for sites 2 (B = .12, < .05) and 4 (B = .25, < .01), using the internet for news was positively related to drinking behaviors; and that using the internet for shopping was positively related to drinking behaviors for young women (B = .15, < .01), but not for young men. For drug use, there was a main effect of site (F(3, 758) = 13.68, < .001), pornography (F(1, 758) = 9.36, < .01) and school (F(1, 758) = 10.66, < .001), with parameter estimates suggesting that using the internet for pornography was positively, and using the internet for school was negatively, related to drug use. For the number of sexual partners, there was a main effect of gender (F(1, 758) = 6.00, < .05) and pornography (F(1, 758) = 45.71, < .001), with parameter estimates suggesting that using the internet for pornography was positively related to the number of sexual partners.

Self-perceptions

First, we assessed the relationships between video game use, violent video game use, and frequency of internet use on emerging adults’ self-perceptions (separate analyses for self-worth and social acceptance). For self-worth, there were main effects of site (F(3, 780) = 3.40, < .05), violent video game use (F(1, 780) = 6.92, < .01), and internet use (F(1, 780) = 4.70, < .05), with parameter estimates suggesting that violent video game and internet use were negatively related to emerging adults’ perceptions of self-worth. There were also significant interactions between gender and video game use, with simple slope follow-up analyses suggesting that video game use was negatively related to self-worth for young women (B = −.06, < .05), but not for young men. For social acceptance, there was a main effect of site (F(3, 780) = 3.09, p < .05). There were also significant interactions between site and violent video game use (F(3, 780) = 2.85, < .05), and between gender and video game use (F(1, 780) = 7.80, < .01), and violent video game use (F(1, 780) = 4.25, < .05). Simple slope follow-up analyses suggested that, for site 3, violent video game use was negatively related to social acceptance (B = −.09, < .01), and that video game use (B = −.07, p < .05) and violent video game use (B = −.07, < .05) were negatively related to social acceptance for young women, but not for young men.

Second, we assessed the relationships between the types of internet use (entertainment, headline news, pornography, e-mail, chatting, shopping, and school work) on emerging adults’ self-perceptions. For self-worth, there were main effects of site (F(3, 752) = 4.27, < .01), chatting (F(1, 752) = 19.88, < .001) and school (F(1, 752) = 12.02, < .001), with parameter estimates suggesting that using the internet for chatting was negatively, and using the internet for school was positively, related to perceptions of self-worth. For social acceptance, there were main effects of site (F(3, 750) = 3.25, < .05), gender (F(1, 750) = 4.23, < .05), pornography F(1, 750) = 7.67, < .01), and school (F(1, 750) = 6.89, < .01), with parameter estimates suggesting that using the internet for pornography was negatively, and using the internet for school was positively, related to perceptions of social acceptance.

Relationship quality

First, we assessed the relationships of video game use, violent video game use, and frequency of internet use on emerging adults’ relationship quality (separate analyses for relationships with friends and parents). For relationship quality with friends, there were main effects of site (F(3, 749) = 6.65, < .001) and gender (F(1, 749) = 12.06, < .001). There were also significant interactions between site and video game use (F(3, 750) = 4.20, p < .01) and violent video game use (F(3, 750) = 2.97, < .05). Simple slope follow-up analyses suggested that, for site 3, video game use (B = −.16, < .001) and violent video game use (B = −.15, < .001) were negatively related to relationship quality with friends. For relationship quality with parents, there was a main effect of gender (F(1, 748) = 16.61, < .001). There were also significant interactions between site and video game and violent video game use. Simple slope follow-up analyses suggested that, for sites 2 and 3, video game use (B = −.08, < .01; B = −.15, < .001) and violent video game use (B = −.08, < .001; B = −.16, < .001) were negatively related to relationship quality with parents.

Second, we assessed the relationships between the types of internet use (entertainment, headline news, pornography, e-mail, chatting, shopping, and school work) on emerging adults’ relationship quality. For relationship quality with friends, there were main effects for site (F(3, 748) = 5.50, < .001), pornography (F(1, 748) = 10.11, < .01), and e-mail (F(1, 748) = 14.10, < .001), with parameter estimates suggesting that using the internet for pornography was negatively, and using the internet for e-mail was positively, related to friendship quality. There was also a significant interaction between gender and pornography (F(1, 748) = 5.07, p < .05). Simple slope follow-up analyses suggested that using the internet for pornography was negatively related to friendship quality for young women (B = −.21, < .001), but not for young men. For relationship quality with parents, there were main effects of pornography (F(1, 748) = 3.79, < .05), e-mail (F(1, 748) = 4.50, < .05), and school (F(1, 748) = 14.30, < .001), with parameter estimates suggesting that using the internet for pornography was negatively, and using the internet for e-mail and school were positively, related to relationship quality with parents. There were also significant interactions between gender and shopping (F(1, 748) = 9.31, < .01), and between gender and school (F(1, 748) = 5.33, < .05). Simple slope follow-up analyses suggested that using the internet for shopping was negatively related to parental relationship quality for young men (B = −.08, < .05), but not for young women; and using the internet for school was positively related to parental relationship quality for young men (B = .21, < .001), but not for young women.

Discussion

In today’s pop culture, video games and the internet have become a prevalent aspect of the lives of young people. Despite the pervasiveness of video game and internet use, there has been a dearth of scholarly research examining the role these forms of electronic leisure may play in individual development during emerging adulthood. Thus, the results of this study serve to shed light on the role that electronic leisure may have in the lives of young people as they transition to adulthood. Although the results of the current study are somewhat exploratory in nature, they nevertheless provide some of the first evidence that video games and internet use are related to significant aspects of individual development during emerging adulthood.

Video Game Use

Regarding video games, results suggested a stark gender difference in this type of electronic leisure, with the majority of men having played games weekly or more frequently, while the majority of women had not played a single game in the past year. However, just as important as the differences in use, were the correlates of video game use. Specifically, regardless of gender, video game use was linked to greater drug use, drinking behaviors, and lower relationship quality with friends and parents, while violent video game use was associated with more sexual partners and lower relationship quality with friends and parents. Furthermore, violent video game use by men was linked to more drinking behaviors. For women, video game use was associated with lower self-worth, and both video games and violent video games were associated with lower perceived social acceptance.

While the correlational nature of our data precludes causal inferences, these findings do suggest that video game use may be a possible risk factor for emerging adult development. Much of the work on video game use has focused on such things as fear and aggression (see Anderson and Dill 2000), with critics of video games pointing out that some violent games have been so effective in reducing inhibitions for killing that the military has employed their use as training tools (Grossman and DeGaetano 1999). While the implications of video game use on fear and aggression are of importance, our findings add to an emerging literature suggesting a need for a broader and more developmental approach to the study of video games. For example, the findings suggest that the amount of time spent playing video games by today’s young people is not a benign choice of how to spend one’s time, but may have implications for the development of emerging adults as they make the transition into adulthood. Emerging adulthood is a unique period of the lifespan in that young people are given greater autonomy to make choices for themselves, and these independent choices have greater implications for their future as adults than, arguably, any they have made as children or adolescents. In that context, it may be easy to see why the choice to spend one’s time playing video games might be more than a simple choice of how to use one’s leisure time, and may more accurately be an effort at self-socialization that is associated with potentially unhealthy behaviors (Arnett 1995; Brown 2006). Thus, future work is needed to examine how video games may impact significant aspects of development in emerging adulthood.

For example, time spent playing video games appears to impede success in the college classroom (e.g., Anand 2007; Anderson and Dill 2000). Future work may examine when during the day or night video games are being played to determine if students are (a) playing until the early morning hours and therefore sleeping during the day instead of attending class, (b) playing video games instead of attending class and/or (c) playing video games instead of doing homework. Depending on the hours spent playing video games, there may also be ramifications for a young person’s transition into the work force.

Furthermore, our findings suggest that there is an association between video game use and relationship quality. Whether a cause or result, we see that video game use is related to poor relationships with friends and parents. During a developmental period in which the formation of romantic relationships is common, these findings raise the question as to how video game use may affect romantic relationships, including early marital relationships. In particular, the formation and maintenance of romantic relationships may be at risk because there is an obvious discrepancy between men and women in their interest in video games. While some leisure activities tend to drop off in the mid twenties (e.g., levels of drinking and drug use; Schulenberg and Zarrett 2006), others appear not to (e.g., pornography use; Carroll et al. 2008). It is possible that video game use may be an activity that does not drop off once adult roles are assumed, and the implications of this for family formation are important. Furthermore, the findings regarding video games and aggression (see Anderson and Dill 2000) may have implications for the way in which men treat women as they enter romantic relationships during this period of time. These are just a few factors suggesting the need for future work on the link between video game use and relationships.

Finally, although not directly assessed in the current study, research suggests that time spent playing video games may also inhibit identity exploration, which has been identified as an important requisite in the process of becoming an adult (e.g., Arnett 2004; Erikson 1968; Nelson and Barry 2005). On the one hand, identity may be indirectly affected simply by the fact that time spent playing games could be used in more productive forms of identity exploration in areas such as career, relationships, beliefs, and values. However, playing video games may have a more direct impact on identity development. In discussing the effect that media in general has on identity formation, Brown (2006) suggests that identity may be impacted via the process of emulation as young people identify with characters in the media. If emerging adults, especially men, identify with or begin to take on the persona of the characters they control in violent video games, it may have potential negative ramifications for identity development. For example, by emulating or identifying with violent characters who engage in virtual risk behaviors (e.g., high-speed, reckless driving, breaking the law), young men may be more likely to engage in similar risk behaviors in real life. Thus, a direct result of video game use may be the development of an unhealthy identity that includes participation in risk behaviors.

Taken together, the possible implications of extensive video game use pointed to by these initial findings are numerous and underscore the need to conduct research in the future as to the potential negative effects of video game use on the healthy development of individuals making the transition to adulthood. Indeed, our findings add to the growing notion that video game use may be related to various aspects of emerging adult development (see Arnett 2004), such as exploration and experimentation, participation in risk behaviors, relationships, and preparation for adult roles. In sum, rather than being a benign way to spend one’s time, extensive video game use may negatively impact development.

Internet Use

Regarding internet use, results highlighted the need to more closely examine internet use in regard to the medium versus content debate that has existed for years regarding television use (Anderson et al. 2001). While there were findings for internet use in general (e.g., internet use was negatively related to self-worth), our findings were more consistent with content theory in that what the internet was being used for appeared to be significant in understanding its role in the lives of young people. In other words, there were different patterns of findings depending on how the internet was used. For example, when the internet was used for chat rooms, shopping, entertainment, and pornography, there was a link to negative outcomes including more risk behaviors (both drinking and drug use), number of sexual partners, lower self-perceptions and self-worth, and poorer relationships with friends and parents; but when it was used for schoolwork, it was associated with a plethora of positive outcomes including less drug use, higher self-perceptions and self-worth, and positive parent-child relationships for young men.

Thus, the content or purpose of internet use appears to matter significantly as it relates to healthy or unhealthy outcomes. Indeed, unlike video game use (which appeared to be related to mostly negative outcomes), the potential linkages between internet use and positive or negative aspects of development in emerging adulthood appear to depend on how the internet is used. Certain uses of the internet may be linked to problematic aspects of emerging adulthood, such as risk behaviors, which raises cause for concern about the problematic role they may play in other aspects of emerging adulthood, such as identify formation, preparation for adult roles, and relationships. As with video games, it may be speculated that the internet either plays a direct role in problematic development (e.g., identifying with characters in the entertainment or pornography they use on the internet Brown 2006) or impacts development indirectly by taking time away from more productive processes that would aid development, such as education, work, or broader identity exploration.

On the other hand, if the internet is used in other ways (e.g., school, e-mail) it might help foster positive aspects of development. For example, results of the study found that using the internet for e-mail was associated with better quality relationships with friends and parents. On the one hand, individuals who already have strong relationships with others may use e-mail to stay connected with them, but there is also the possibility that the internet might provide a comfortable setting for some young people to engage in, maintain, or strengthen relationships. Indeed, it may be especially helpful for certain young people (e.g., shy, socially anxious, physically less attractive) for which the internet may provide a less threatening setting for them to maintain or even strengthen relationships. It needs be reiterated that these findings do not suggest that electronic leisure causes these outcomes. It is possible that using the internet for a specific purpose may lead an individual to engage in certain behaviors, but it is equally possible that certain characteristics (such as not feeling socially accepted or having low self esteem) might lead one to withdraw into the “safer” social world of chat rooms and pornography on the internet. It may also be possible that the various purposes of the internet are relatively benign and only begin to appear problematic once they start to replace other things that might be beneficial for young people (e.g., class attendance and homework for students, reading, exercise, work, and face-to-face social interactions). It would behoove researchers to begin to examine possible causal explanations as to why different internet content is linked to different aspects of emerging adults’ lives.

Electronic Leisure, Gender, and Demographics

The results of this study also provide important findings in regard to gender. Results showed distinct differences in the usage patterns, but few differences in the outcomes, of electronic leisure. First, consistent with past research (e.g., Carroll et al. 2008), men reported viewing pornography to a greater extent than did women, but the correlates of its use did not appear to differ for men and women (with the exception of being negatively related to friendship quality for young women only). Recent work suggests that pornography use is so pervasive among male college students that it may be considered “normative” (Carroll et al. 2008). However, just as with the prevalence of alcohol use during this time period, normalcy in use does not exclude possible health risk. Indeed, findings from the current study, for men and women, point to a link between pornography use and risk behaviors (drug use, drinking behaviors, and greater number of sexual partners), as well as lower self-perceptions and lower quality relationships with parents.

These findings are particularly telling for women who engage in these typically-male behaviors (i.e., pornography and video games) in that they suggest a group who are at risk. The work of Carroll and colleagues (2008) found that those women who were accepting of pornography use were at risk for a host of negative outcomes (i.e., permissive sexuality, alcohol use, binge drinking, and cigarette smoking). The results of the current study add to this growing profile of problems associated with pornography for women by finding that pornography use (not just acceptance) by women was also linked to drinking, drug use, number of sexual partners, as well as to lower perceived social acceptance, and lower quality friendships. Interestingly, women who played video games or violent video games also tended to engage in more drinking behaviors, had more sexual partners, had lower self-worth and perceptions of social acceptance, and had lower quality relationships with friends and parents. Given the lower frequency rates for women, but extensive negative outcomes for viewing pornography and playing video games, these behaviors appear to be non-normative and possible indicators of risk for women. Therefore, it would be interesting to examine whether these women who use pornography and play video games are doing so alone, or with men. It may be that some women’s strategies for being with men include “acting” like men by playing video games and watching pornography with them (these men may be their romantic partners). The context for their playing of video games and viewing pornography is an important next step in this research. Regardless of context, however, it appears that viewing pornography and playing video games places some women at risk for both externalizing and internalizing problems.

One of the unexpected findings of the study pertained to differences between the various sites from which participants were recruited. Conceptually, we did not have reason to expect different findings based on site. Although it is still rather difficult to explain these differences, it should be noted that the site that accounted for most of the differences was a liberal arts college, whereas the rest of the sites were larger institutions. For example, for emerging adults at the liberal arts college (site 3), it was found that video game and violent video game use was positively associated with number of sexual partners, and negatively associated with social acceptance and relationship quality with both friends and parents. In addition, for the students attending the liberal arts college, internet use was positively related to number of sexual partners. This suggests that possible differences in attitudes, behaviors, and/or beliefs exist for students who attend liberal arts colleges, and future research should examine what these differences may be and how they may be linked to differences in findings regarding electronic media use and its correlates.

In addition, results found differences in electronic media use for ethnicity and residential status (i.e., living at home with parents). Most notably, African Americans reported spending more time on the internet than did European Americans, Asian Americans, and those of other ethnicities; and individuals living with parents reporting higher video game use, violent video game use, pornography use, and chatting than did individuals living outside their parents’ home (in a residence hall or apartment). Little research has been conducted regarding media use during emerging adulthood and either ethnicity or whether one lives at home or not. It is not necessarily surprising that there were some different patterns of media use based on ethnicity, given that ethnicity has accounted for differences in media use in past studies as well. For example, it has been found that African American children spend 1 h a day more on average watching television than do Hispanic children, and Hispanic children spend 1 h a day more watching television than do Caucasian children (Roberts and Foehr 2004). Most interesting was that, despite a few differences in use, there were no ethnic differences in the outcomes associated with electronic media use. The same can be said for residential status (i.e., differences in use but not outcomes were based on whether an individual was living at home with parents or elsewhere). Thus, while future work may consider ethnicity and residential status as potentially important given the different usage rates found in this study, our findings suggest similar benefits or risks (depending on its use) across ethnic and residential status groups.

Limitations and Conclusions

Despite the contributions of this study, it is not without limitations. Foremost, the correlational nature of the data precludes causal inferences. While our discussion of the findings often took a causal tone, it was done simply to present possible interpretations and to underscore the need for future work to examine these possibilities. Next, caution is needed regarding the generalizability of our findings given that our sample consisted of college students from a mostly white, middle class background. Very little work has been done with young people not attending college (i.e., the “Forgotten Half” William T. Grant Foundation Commission on Work, Family, and Citizenship 1988), and it is possible that findings would be different for this group. For example, given that most of the “positive” findings regarding internet use in the current study were found when the internet was used for schoolwork, it poses the possibility that the internet may possess even fewer benefits for non-students. Another limitation was the use of single items to assess video game and violent video game use. While assessing frequency is appropriate as a first step in understanding video game use, future research should examine video game use in more detail by assessing specific games played, as well as other contextual factors such as with whom, and at what time of day individuals are playing. Finally, the findings from this study are exploratory and modest in magnitude. Hence, there needs to be caution against overstating the impact of video games and internet use on the development of young people based on the current findings.

Despite these limitations, this study presents one of the first attempts to (a) document the pattern of both video game and internet use among college students and (b) examine how electronic leisure activity might be related to risk behaviors, self-perceptions, and the quality of relationships with others during emerging adulthood. Results suggest that playing video games and using the internet for purposes such as pornography, chat rooms, and entertainment are not benign choices void of possible negative correlates. While unable to draw causal conclusions, the findings highlight that the forms of leisure activities young people engage in are related to healthy, or in many cases unhealthy, development. Indeed, in having greater autonomy as they make the transition to adulthood, young people’s choices regarding their leisure activities may have particularly significant ramifications for their well-being both during this period of their lives, and into adulthood. Taken together, the possible implications of this study underscore the need to view the topics of video game and internet use as more than just areas of interest to pop culture, but as areas deserving of scholarly attention in helping us understand the overall health and development of young people as they transition to adulthood.

Notes

Acknowledgments

The authors would like to acknowledge Carolyn McNamara Barry and Stephanie Madsen for their extensive help on Project READY data collection. The authors also express appreciation to the instructors and students at all Project READY data collection sites for their assistance. We are grateful for the grant support from the Family Studies Center at Brigham Young University, as well as a junior faculty sabbatical grant from Loyola College in Maryland.

References

  1. America’s online pursuits: The changing picture of who’s online and what they do. (2003). Report of the Pew Research Center. Retrieved November 19, 2008, from http://www.pewinternet.org.
  2. Anand, V. (2007). A study of time management: The correlation between video game usage and academic performance markers. Cyberpsychology & Behavior, 10, 552–559. doi:10.1089/cpb.2007.9991.CrossRefGoogle Scholar
  3. Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. Journal of Personality and Social Psychology, 78, 772–790. doi:10.1037/0022-3514.78.4.772.CrossRefPubMedGoogle Scholar
  4. Anderson, D. R., Huston, A. C., Schmitt, K. L., Linebarger, D. L., & Wright, J. C. (2001). Early childhood television viewing and adolescent behavior. Monographs of the Society for Research in Child Development, 66 (1, Serial No. 264).Google Scholar
  5. Arnett, J. J. (1995). Adolescents’ uses of media for self-socialization. Journal of Youth and Adolescence, 24, 519–533. doi:10.1007/BF01537054.CrossRefGoogle Scholar
  6. Arnett, J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. The American Psychologist, 55, 469–480. doi:10.1037/0003-066X.55.5.469.CrossRefPubMedGoogle Scholar
  7. Arnett, J. J. (2004). Emerging adulthood: The winding road from the late teens through the twenties. New York: Oxford University Press.Google Scholar
  8. Brown, J. D. (2006). Emerging adults in a media-saturated world. In J. J. Arnett & J. L. Tanner (Eds.), Emerging adults in America: Coming of age in the 21st century (pp. 279–299). Washington, DC: APA.CrossRefGoogle Scholar
  9. Carbery, J., & Buhrmester, D. (1998). Friendship and need fulfillment during three phases of young adulthood. Journal of Social and Personal Relationships, 15, 393–409. doi:10.1177/0265407598153005.CrossRefGoogle Scholar
  10. Carroll, J. S., Padilla-Walker, L. M., Nelson, L. J., Olson, C. D., Barry, C. M., & Madsen, S. (2008). Generation XXX: Pornography acceptance and use among emerging adults. Journal of Adolescent Research, 23, 6–30. doi:10.1177/0743558407306348.CrossRefGoogle Scholar
  11. Collins, W. A., & Madsen, S. D. (2006). Personal relationships in adolescence and early adulthood. In A. L. Vangelisti, D. Perlman, & A. Vangelisti (Eds.), The Cambridge handbook of personal relationships (pp. 191–209). New York: Cambridge University Press.CrossRefGoogle Scholar
  12. Erikson, E. H. (1968). Identity: Youth and crisis. New York: Norton.Google Scholar
  13. Gordon, C. F., Juang, L. P., & Syed, M. (2007). Internet use and well-being among college students: Beyond frequency of use. Journal of College Student Development, 48, 674–688. doi:10.1353/csd.2007.0065.CrossRefGoogle Scholar
  14. Grossman, D., & DeGaetano, G. (1999). Stop teaching our kids to kill: A call to action against TV, movie, and video game violence. New York: Crown.Google Scholar
  15. Hendel, D. D., & Harrold, R. D. (2004). Undergraduate student leisure interests over three decades. College Student Journal, 38, 557–568.Google Scholar
  16. Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V., & Crawford, A. (2002). Internet paradox revisited. Journal of Social Issues, 58, 49–74.CrossRefGoogle Scholar
  17. Landers, R. N., & Lounsbury, J. W. (2006). An investigation of big five and narrow personality traits in relation to internet usage. Computers in Human Behavior, 22, 283–293.CrossRefGoogle Scholar
  18. Nelson, L. J., & Barry, C. M. (2005). Distinguishing features of emerging adulthood: The role of self-classification as an adult. Journal of Adolescent Research, 20, 242–262.CrossRefGoogle Scholar
  19. Niemz, K., Griffiths, M., & Banyard, P. (2005). Prevalence of pathological internet use among university students and correlations with self-esteem, the General Health Questionnaire (GHQ), and disinhibition. CyberPsychology & Behavior, 8, 562–570.CrossRefGoogle Scholar
  20. Odell, P. M., Korgen, K. O., Schumacher, P., & Delucchi, M. (2000). Internet use among female and male college students. CyberPsychology & Behavior, 3, 855–862.CrossRefGoogle Scholar
  21. Olson, C. K., Kutner, L. A., Warner, D. E., Almerigi, J. B., Baer, L., Nicholi, A. M., et al. (2007). Factors correlated with violent video game use by adolescent boys and girls. Journal of Adolescent Health, 41, 77–83.CrossRefPubMedGoogle Scholar
  22. Roberts, D. F., & Foehr, U. G. (2004). Kids and media in America. Cambridge: Cambridge University Press.Google Scholar
  23. Schulenberg, J. E., & Zarrett, N. R. (2006). Mental health during emerging adulthood: Continuity and discontinuity in courses, causes, and functions. In J. J. Arnett & J. L. Tanner (Eds.), Emerging adults in America: Coming of age in the 21st century (pp. 135–172). Washington, DC: APA.CrossRefGoogle Scholar
  24. Sherman, R. C., End, C., Kraan, E., Cole, A., Campbell, J., Birchmeier, Z., et al. (2000). The internet gender gap among college students: Forgotten but not gone? CyberPsychology & Behavior, 3, 885–894.CrossRefGoogle Scholar
  25. The Internet goes to college: How students are living in the future with today’s technology. (2002). A report of the Pew Research Center. Retrieved November 19, 2008, from http://www.pewinternet.org/reports.
  26. William T. Grant Foundation Commission on Work, Family, and Citizenship. (1988). The forgotten half: Non-college-bound youth in America. Washington, DC: William T. Grant Foundation.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Laura M. Padilla-Walker
    • 1
  • Larry J. Nelson
    • 1
  • Jason S. Carroll
    • 1
  • Alexander C. Jensen
    • 1
  1. 1.School of Family LifeBrigham Young UniversityProvoUSA

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