Multitasking With Television Among Adolescents

Abstract

Using Ecological Momentary Assessment, we explored predictors of adolescents’ television (TV) multitasking behaviors. We investigated whether demographic characteristics (age, gender, race/ethnicity, and maternal education) predict adolescents’ likelihood of multitasking with TV. We also explored whether characteristics of the TV-multitasking moment (affect, TV genre, attention to people, and media multitasking) predict adolescents’ likelihood of paying primary versus secondary attention to TV. Demographic characteristics do not predict TV multitasking. In TV-multitasking moments, primary attention to TV was more likely if adolescents experienced negative affect, watched a drama, or attended to people; it was less likely if they used computers or video games.

Insight into everyday media use with multiple screens

“…Some studies have found that women are more likely to engage in media multitasking than men (Hwang, Kim, and Jeong 2014;Duff et al 2014;Jeong and Fishbein 2007;Voorveld and Viswanathan 2015), whereas other studies did not find significant gender differences across multitaskers (Voorveld et al 2014;Kononova 2013;Christensen et al 2015). Although gender is sometimes assumed and found to be related to media multitasking, it is unclear why there would be gender differences.…”

“…Although gender is sometimes assumed and found to be related to media multitasking, it is unclear why there would be gender differences. Some argue that women have greater neurological capacities for multitasking (Fisher 1999, in Christensen et al, 2015. However, the ability to multitask does not necessarily relate to the preference to multitask or the actual behaviour (K€ onig and Waller 2010;Poposki and Oswald 2010).…”

Impact of adolescent media multitasking on cognition and driving safety

“…Research suggests early adolescents (13–16 year olds) are more likely to engage in MM as compared to other age groups (Voorveld & van der Goot, ). Still others have found no differences in MM based on basic demographics (e.g., age, gender, and/or ethnicity) (Christensen et al, ; Moisala et al, ). Among university students, the frequency of online MM was greater among those who were more educated, younger, and Asian (compared to White) (Srivastava, Nakazawa, & Chen, ).…”

“…More recent estimates suggest MM has become pervasive earlier in development, with sixth‐ to eighth‐grade students reporting approximately 25% of their total media time was spent MM (Cain, Leonard, Gabrieli, & Finn, ). It also seems that MM increases over development, with students’ ages 12–15 years reporting MM during nearly half of the time they spent watching television (Christensen, Bickham, Ross, & Rich, ). MM is more than a leisure activity; nearly a third of adolescents use task‐related and task‐unrelated media “most of the time” while studying (Rideout et al, ), and a survey of university students indicated over half used electronic media during academic activities (Jacobsen & Forste, ).…”

The Most Social Games

“…Christensen, Bickham, Ross, and Rich (2015) found that young adults tended to watch TV while using computers and mobile devices. Braveman (2011) demonstrated that more than 40% of adults used online or social media while simultaneously watching TV.…”