Full length articleMedia multitasking and well-being of university students
Introduction
Media saturation and convergent technologies have made media multitasking a way of life for many. In the U.S., a majority of teenagers multitask “most” or “some” of the time when listening to music (73% of respondents), watching TV (68%), using a computer (66%), and reading (53%; Rideout, Foehr, & Roberts, 2010). In the UK, on average, 16- to 24-year-olds use media for 9.5 h a day, of which 52% involves media multitasking (Ofcom & GfK, 2010). Given its prevalence, media multitasking has drawn considerable interest from researchers.
Existing research on media multitasking has focused primarily on its increasing popularity and detrimental effects on cognitive performance and functions, but recently, its relationship with social and psychological well-being has gained attention (e.g., Pea et al., 2012, Shih, 2013). Potential negative consequences of media multitasking on well-being have been documented. For example, research has found that among children, it negatively correlates with the feeling of normalcy and capabilities to develop intimate relationship with friends (Pea et al., 2012), and it has been associated with the symptoms of depression and social anxiety in adults (Becker, Alzahabi, & Hopwood, 2012). Findings, however, have been inconsistent. For example, Shih (2013) found no significant correlation between media multitasking and a range of psychosocial well-being factors, including emotional positivity, sociability, and impulsivity. In other studies, even positive effects of media multitasking on well-being have been suggested. For example, interacting with family members while viewing television enhanced children's prosocial behavior (St. Peters, Huston, & Wright, 1989), and media multitasking was positively correlated with university students' emotional satisfaction, albeit at the cost of cognitive performance (Wang & Tchernev, 2012).
Then, is media multitasking harmful, harmless, or beneficial to social and psychological well-being? Before addressing this question, we propose to further specify the concept of “media multitasking”; we suspect that one reason for inconsistent findings in the literature is the definition of “media multitasking”. In recent literature, media multitasking refers to the simultaneous pursuit of two or more relatively independent tasks, with at least one of the tasks involving media (e.g., Jeong and Fishbein, 2007, Sanbonmatsu et al., 2013). This broad and practical definition is invoked in everyday conversations, news coverage, and research. Its breadth, however, makes comparing findings across studies a challenge because it encompasses a plethora of diverse behaviors. This may obscure critical differences in contexts and characteristics of media multitasking behaviors in well-being research.
For example, both listening to music while studying and listening to music while talking face-to-face with people are considered “media multitasking”, although these two behaviors manifest distinct intentions. On the one hand, individuals who listen to music while studying do so to make studying fun without too much distraction, and it is one of the most popular multitasking behaviors among university students (David, Kim, Brickman, Ran, & Curtis, 2014). On the other hand, listening to music during a face-to-face conversation is not common and is likely to be viewed as discourteous; it may suggest avoidance of social interaction. Hence, it is possible that frequent multitasking during face-to-fact communication could be negatively associated with social relationships and well-being in the long run, but we may not easily draw the same conclusion for multitasking during study. However, existing research on the relationship between media multitasking and well-being relies on the popular media multitasking index1 (Ophir, Nass, & Wagner, 2009) to gauge media multitasking behavior. This index, although valuable for assessing general media multitasking tendencies, aggregates a variety of media multitasking activities, making it impossible to distinguish the impacts of these different activities on well-being.
Two important criteria to differentiate media multitasking behaviors are motivations and resources demands. There is growing evidence that different goals motivate different media multitasking behaviors, which have different impacts on gratifying these goals (Hwang, Kim, & Jeong, 2014; Wang and Tchernev, 2012, Zhang and Zhang, 2012). Furthermore, based on the psychological literature, eleven cognitive dimensions of media multitasking behaviors (e.g., relevance of the tasks, modalities of the tasks, behavioral responses required by the tasks) have been identified as making some media multitasking behaviors more resource intensive than others and, thus, impacting behavioral outcomes and choices differently (Wang, Irwin, Cooper, & Srivastava, 2015). Based on Wang et al.’s cognitive dimensional framework, it is easy to see why, despite the overwhelming number of studies showing negative consequences of media multitasking on task performance, some studies have found an increase in task performance, such as when the tasks are highly relevant and executed through non-competing modality channels (e.g., Moreno and Mayer, 1999, Wang et al., 2015). Following these ideas, it seems reasonable to predict that distinct motivations and cognitive characteristics of media multitasking behaviors can impact social and psychological well-being in different ways, leading to divergent findings on their relationships. This is the general issue explored in the current study.
In this study, we compared media multitasking behaviors motivated by different goals and with different cognitive characteristics. Specifically, based on recent portrayals of the communication activities of university students (David et al., 2014, Wang and Tchernev, 2012), we categorize media multitasking behaviors by their primary task motivation (social, cognitive, and entertainment); we also consider synchronicity, an important characteristic of media multitasking behaviors that determines resource demands (Walther, 1996, Wang et al., 2015).
Section snippets
Media multitasking among university students and its motivations
Media multitasking has become increasingly popular thanks to the versatility and accessibility of computers, smartphones, and tablets, which allow for the seamless integration of work, play, and social interaction (e.g., Carrier et al., 2009, David et al., 2014, Rosen et al., 2013, Srivastava, 2013). A recent investigation in the U.S. (David et al., 2014) revealed the major communication and media activities of undergraduate students on a typical day based upon self-report of 992 respondents.
Resource characteristics of media multitasking behaviors
Another important way to specify media multitasking behaviors is to take into consideration the resource demands of the tasks. Based on psychological theories and findings on limited resources and resource allocation (Lang, 2000, Salvucci and Taatgen, 2008, Wickens, 2002), media multitasking has been conceptualized as a multidimensional behavior, with the dimensions of tasks requiring and attracting different types and amounts of resources (Wang et al., 2015). For example, multitasking
Social success
Social success is a crucial developmental task during adolescence and emerging adulthood (Erikson, 1968, Pea et al., 2012). It is conceptualized as having friends and being socially skilled, including being able to develop and maintain close and meaningful friendships (Pea et al., 2012). Research has found that those who report an increase in social support over the time of emerging adulthood show improved psychological well-being (Galambos, Barker, & Krahn, 2006), whereas perceived lack of
The feeling of normalcy
Another indicator of social well-being is normalcy, the feeling of being understood and accepted by peers (Reis & Shaver, 1988). Peer acceptance is considered to promote the development of meaningful friendships, whereas peer rejection results in challenges in establishing them (Nangle, Erdley, Newman, Mason, & Carpenter, 2003) and leads to troubling issues in later personality development (Ladd, 2006). Much research has found that by late adolescence, peers are typically the strongest
Self-control
Academic growth—a main goal and function of university experience—requires students to sustain attention to learning tasks, which demands self-control. Self-control, often used interchangeably with self-regulation (Baumeister & Alquist, 2009), has been used to predict cognitive learning outcomes in school (e.g., grade point average; see Duckworth and Seligman, 2005, Tangney et al., 2004). Self-control has been defined by Zimmerman (2002) as “the self-directive process through which learners
Participants
An online survey was conducted between March and May of 2014. Participants were undergraduate and graduate students recruited from 59 universities in Beijing, China. Participants were recruited online to complete an online survey created using Qualtrics software (Qualtrics, 2013). The survey link was distributed online through major SNS used widely by university students in Beijing. As an incentive, students were offered the opportunity to enter a lottery with a chance to win one of 10 cell
Results
The analysis began with a descriptive analysis of the variables. Then, hierarchical regression models were used to examine the effects of multitasking tendencies on well-being.
Discussion
The primary goal of this study was to explore different impacts of media multitasking on social and psychological well-being in four media multitasking contexts. Based on motivational research on media use and media multitasking behaviors (David et al., 2014; Hwang et al., 2014; Wang and Tchernev, 2012, Zhang and Zhang, 2012), we examined three types of motivations: social, cognitive, and entertainment. We also considered synchronous and asynchronous communication, an important distinction that
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