Trends in youth’s videogame playing, overall computer use, and communication technology use: The impact of self-esteem and the Big Five personality factors

Abstract

The objective of the current research is to model trends in video game playing, overall computer use, and communication technology use in a longitudinal sample of youths, aged 11–16 over a 3-year interval. In addition, individual difference characteristics that may be predictive of these trends were included, namely, socio-demographic characteristics (gender, ethnicity, and parental income) and personality characteristics (self-esteem, the Big Five personality factors). Findings suggested that youth increased their overall computer and communication technology use but decreased their videogame playing over time. Many individual differences predicted mean levels of these technologies with fewer predicting slopes. Conclusions, implications, and limitations are discussed.

Introduction

Currently, almost 90% of youth in the US use the Internet (Madell and Muncer, 2004, Willoughby, 2008), a statistic that dwarfs earlier estimates (Cravatta, 1997). Indeed technology is more a vital part of life for today’s youth than for adults, at least when social connections and entertainment are considered (Jackson et al., 2001, Jaffray, 2010). The benefits of being technologically fluent are obvious, but the liabilities of not being “tech savvy” may be more substantial (e.g., increased isolation from world, local, interpersonal, and personally meaningful events). Few studies have examined youth’s changes in technology use over time and even fewer have examined individual difference predictors of this change. The present research begins to address this gap in the literature by using a three year longitudinal study of children (12 years old at baseline). Using this sample we address not only changes in technology use over time but also individual difference characteristics that influence these changes.

We begin by discussing how a developmental perspective can shed light on the implications of children’s use of technology followed by a literature review of existing work on technology use in general and individual difference predictors of technology use. Finally, we describe the current research as tool for understanding trends in the use of three major types of technology.

Developmental theory provides the groundwork for understanding the impact of the technological revolution on children’s development (Ohannessian, 2009). Development is the interaction between contextual variables and characteristics of the individual (Bronfenbrenner & Crouter, 1982). Because youth spend more and more of their time engaged with technology, understanding the implications of this engagement are critical. Accordingly, implications for cognitive, social and psychological development in the Information age are occupying center stage in developmental initiatives of the new millennium (Durkin and Barber, 2002, Kraut et al., 1998, Ohannessian, 2009). Much of this research has taken a unidimensional approach to technology, targeting single technologies one at a time and treating technology use an either/or proposition – either the child uses this technology or she does not use it.

Rapid advancements in technology have enabled today’s youth to have access to an unprecedented quantity and quality of media. In fact, on an average day, youth spend 2.5 h watching television (Gentile, Lynch, Linder, & Walsh, 2004), 46 min on the Internet (Gross, 2004, Woodward et al., 2002), 73 min playing video games, 150 min listening to music (Media Literacy, 2010), over 60 min on the phone (Gross, Juvonen, & Gable, 2002), 30 min instant messaging (Gross et al., 2002), 25 min watching movies (Literacy, 2010) and 20 min e-mailing (Gross et al., 2002). This adds up to nearly half a day engaging in some type of technology use. Therefore any study interested in understanding technology use among youths must examine multiple technologies simultaneously. Our research focused on three types of technology use: videogame playing, general computer use and communication technology (e.g., cell phones and instant messaging).

Videogame playing is one of the most popular and controversial activities in technology use in the new millennium. Early research suggesting that videogame playing could be addictive to teens set the tone for subsequent work focused on the negative consequences of videogame playing. For example, Bushman and Anderson (2001) found that repeated violent video game play was strongly associated with aggressive behavior. Other research has shown that sustained videogame playing is associated not only with aggressive but also with delinquent behaviors (Anderson & Dill, 2000). However, not all research finds these associations. Salguero and Moran (2002), for example, found no relationship between the videogame playing and behavioral problems (Hart et al., 2009).

Research has also shown that videogame playing can have positive consequences for youth. Work by Nichols (1992) suggested that gaming may actually enhance spatial performance, reading skills, and overall academic ability. Durkin and Barber (2002) found that adolescents who engaged in videogame play were better adjusted, had higher self-esteem, used fewer illegal substances, were more involved in school activities, and were closer with family members than adolescents who did not play videogames. Thus, the effects of videogame playing are more complex than originally thought and may depend on a variety of characteristics, both of the child and the videogame.

Like the research on videogame playing, studies of the effects of computer use in general have produced mixed results. For example, Lanthier and Windham (2004) found that using the Internet was related to poorer college adjustment and Amichai-Hamburger and Ben-Artzi (2003) found that Internet use was related to higher levels of loneliness and depression.

On the other hand, Willoughby (2008) noted that adolescents who do not use the Internet for learning tasks are at a disadvantage academically. Similarly, other researchers have found that computer use improves problem solving ability and increases learning (Subrahmanyam et al., 2000, Wood et al., 2005). One explanation of these seemingly contradictory results is that the negative effects of Internet use found in other studies are short-lived (Gross, 2004, Kraut et al., 1998).

Despite the fact that many youth have or use cellular technology, relatively little research has examined its influence on their behavior and attitudes. Cell phone adoption among youth is growing exponentially, with over 65% of adolescents reporting daily usage of a cell phone. Moreover, a growing number of these youth also use advanced cell phone features such as texting. Text messaging has increased 566% each year for the last 2 years (Cell phones and texting, 2009). As such, it is surprising that research on this technology in youth is so sparse. Indeed, existing work focuses primarily on adult use of cell phone technology; specifically, examining personality traits related to adoption of cellular technology and short message services (Butt and Phillips, 2007, Massman et al., 2009).

In summary, the effects of using multiple technologies on children’s development are inconclusive. Existing studies fail to provide sufficient information on rates of use, as well as potential reasons for use. It is important to know how frequently children use technology and to understand the reasons for their use.

Very little is known about why some people use specific technologies while others do not, or why some people use technology more frequently than others. A variety of individual differences have been hypothesized to account for these differences. The following is a less than exhaustive set of individual differences factors that may affect rates of technology use.

Gender is often discussed in reference to technology adoption. Findings indicate that females use computers for communication such as e-mail, while males use computers to search the Internet for information and to play videogames (Jackson et al., 2001, Jackson et al., 2003). However, Ohannessian (2009) found no gender differences in how adolescents used computers, but found that anxiety levels between males and females differed and males used technology as an escape. Pierce (2009) found that girls tended to be more self-conscious in social settings, often relying on technology such as texting, instant messaging and social websites to communicate with their peers. Using technology for social communication may make the individual less self-conscious than in face-to-face communication. Willoughby (2008) used a two-wave study to discover changes in technology use during high school; boys maintained the same general computer use whereas girls use declined from over the high school years.

Children from lower socioeconomic status families are less likely to have access to technology of any kind than are children from higher socioeconomic status families (Pew Internet, 2005). More interesting, however, are the indirect effects that parental income has on children which in turn have implications for their technology use. Aneshensel and Sucoff (1996) found that Socioeconomic Status (SES) was associated with differing levels of stress and depressive symptoms in children. Similarly, Finkelstein, Kubzansky, Capitman, and Goodman (2007) found less psychologically healthy coping styles in adolescents from lower socioeconomic backgrounds than from higher backgrounds.

Given that technological use is sometimes a personal choice, it makes sense that personality traits should be associated with adoption and frequency of technology use. As mentioned, earlier, the existing research in this area has focused on adults. Papacharissi and Rubin (2000) found that extraverts use the Internet more to obtain information and individuals who were more socially withdrawn used the Internet more for social purposes. Landers and Lounsbury (2006) found a negative relationship between Internet use and the personality traits of agreeableness and conscientiousness. More recently, Massman et al. (2009) found that nearly all the Big Five personality factors were associated with cell phone use. Finally, Jackson et al. (2003) found that adults who scored higher on neuroticism used the Internet less than did more emotionally stable individuals. Thus there is an empirical basis for hypothesizing a relationship between personality and technology use in children.

The present study extends previous research in the following ways. First, previous research has focused on only one measurement occasion and one technology. Our approach examines multiple technologies over multiple measurement occasions. This more comprehensive approach is important because it better reflects the reality of technology use, especially among youth. Second, the present study considers gender, household income, and personality as predictors of trends in technology use, rather than just correlates of use. Finally, the longitudinal nature of our research permits speculation about causal relationships between technology use and personality, after taking into account the effects of gender and socioeconomic status.