Multitasking goes global: Multitasking with traditional and new electronic media and attention to media messages among college students in Kuwait,Russia,and the USA

Abstract

The current study examined multitasking with traditional and new electronic media among college students (N = 532) in three countries: Kuwait, Russia, and the USA. Television, music, phone, and the Internet were the most popular media to multitask with and were often used interchangeably, i.e., without the dominance of one medium over another. The game–music pair was the only one with clear distinction between primary (game) and secondary (music) media. Eating, socializing, and doing homework were the most popular nonmedia activities combined with traditional and new electronic media uses. Media-only and media–nonmedia multitasking were found in positive association with perceived attention paid to media messages. The study not only indicated universal media multitasking trends but also revealed cross-national differences that can be explained by economic, political, and cultural characteristics varying across the three nations.

Keywords

Cross-national comparison global media use trends Kuwait media and nonmedia activities media multitasking perceived attention Russia USA

With the growth of information and communication technologies (ICTs), electronic media have been infused in people’s everyday lives. On average, three quarters of the world’s population own a mobile phone, a third can access the Internet, about two-thirds own a TV at home, and four in every 10 individuals own a personal computer (Internet World Stats, 2013; NationMaster, 2012a; The Economist, 2009; The Independent, 2011). Mobile phones, Internet, television, audio media, and video or computer games are used for timely and efficient communication, social connectedness, and pleasure, among other motives. Media surround people at work and at home, in transit (e.g., cars and public transportation) and public places (e.g., streets, restaurants, cinema theatres). Media define lifestyles and consumer habits. While one still enjoys his or her new iPhone or iPad, Apple already works toward releasing a new model with additional, more sophisticated options. While one still extensively uses ‘omnipresent’ Facebook, Twitter, and YouTube, niche network sites, such as Digg, Delicious, and Reddit, continue to grow and fragment social media audiences.

Empirical evidence suggests that media ownership, i.e., possession of media devices and the extent to which an individual is surrounded by media in different places, affects his or her media-use behaviors (Foehr, 2006; Jeong and Fishbein, 2007; Rideout et al., 2010). With the increasing availability of new media forms and options, media users have less time to explore each medium exclusively. Therefore, they multitask. Theorizing about combined media experiences, Pilotta and Schultz (2005) analyzed media modalities and users’ sensual perceptions of media. The authors stated that media offer multiple platforms to affect human senses. Referencing Marshall McLuhan’s (1967) infamous argument that the medium is the message, Pilotta and Schults (2005) argued that modern media culture is not linear. People are no longer involved with one activity at a time. Rather, they engage in simultaneous multiple media uses, celebrating the victory of ‘audiovisual kinetic culture’ and the dominance of ‘pastiche receptivity’ (Pilotta and Schultz, 2005: 19, 24).

Multitasking with media is defined as engagement in several concurrent activities at least one of which is related to media use (Foehr, 2006; Vega, 2009). The current study explored universal trends as well as differences in multitasking with traditional and new electronic media in samples of young adults from Kuwait, Russia, and the USA, three countries that are different economically, politically, and culturally. We focused on multitasking patterns and perceived (self-reported) attention paid to primary electronic media messages as a function of media multitasking.

Media multitasking can happen within one medium (e.g., reading a news story on the Internet and performing an online search) as well as between two or more media (e.g., watching a movie and using the Internet). As media increasingly penetrate our daily life, media use is combined with nonmedia activities more often (e.g., using a mobile phone while driving). This has also been proposed as a form of multitasking with media (Jeong and Fishbein, 2007; Wallis, 2010). Media-only and media–nonmedia multitasking were in the scope of the present study.

Some earlier studies have shown that multitasking with media has become a habit of predominantly younger generations (Carrier et al., 2009; Voorveld and van der Goot, 2013). Some research explored media multitasking behaviors among school students (Foehr, 2006; Rideout et al., 2010). The present study expands this line of research by focusing on college students, young adults who have greater access to mediated technologies and more freedom in their use compared to their high school counterparts.

Furthermore, the present study investigated media multitasking patterns internationally, with three samples from the USA, Russia, and Kuwait. The addition of Kuwait and Russian samples allowed to explore similarities and differences among the national markets; this macro-level structural factor has been kept constant in some previous studies (Jeong and Fishbein, 2007). The three markets vary with regard to a number of economic, political, and cultural factors related to media multitasking, which makes them an interesting case of investigation. The countries of choice show somewhat different levels of economic development, including the development of ICT markets. They are different politically when discussed through the prism of democratization and press freedom. Finally, the three countries represent three unique cultures where time is perceived differently. The present study offers an interpretation of similarities and differences in media multitasking patterns and outcomes as a function of complex cross-national and cultural characteristics.

Pairing media

The problem of media use measures has been widely discussed in mass communication scholarship over the past decade (see Jordan et al., 2007, for a review). Explaining the challenges mass communication scholars face in their attempts to measure the time individuals spend using media, a number of authors (Ahlers, 2006; Jordan et al., 2007; Schultz et al., 2009; Roberts and Foehr, 2008; Vandewater and Lee, 2009) suggested to account for media multitasking. This entails measuring how much time people spend using two or more media at the same time, instead of measuring the use of each medium separately. In order to understand the nature of multitasking and, furthermore, develop reliable measures of media use, it is important to shed the light on how people combine different media and engage in media and nonmedia activities at the same time.

Combining the use of one medium with the use of another medium or nonmedia activities is becoming a popular habit, especially in developed countries with a higher purchasing power and, thus, media ownership. Younger generations that grew up in technology-rich environment are thought to be more likely to multitask with media (Foehr, 2006; Rideout et al., 2010; Roberts and Foehr, 2008). Young people often pair the uses of different media, such as watching television and surfing the Internet. They multitask within one medium (e.g., searching online and checking e-mail). They also multitask while interacting face to face (Wallis, 2010) or performing other, nonmedia tasks (e.g., eating, driving, completing homework; Jeong and Fishbein, 2007).

Scholarship in the field of multitasking with media can be roughly divided into three categories: the nature of media multitasking behaviors, predictors of media multitasking, and the effects of this media use habit. Each of the three categories is discussed in this literature review.

Available research about media multitasking behaviors focused on young media users in the USA and Europe. Carrier and colleagues (2009) found that generations Net and X were more likely to multitask with media and less likely to rate media multitasking activities as difficult compared with Baby Boomers. At the same time, Voorveld and van der Goot (2013) revealed that senior citizens (ages 50–65) in the Netherlands are also prone to multitask with media as much as teenagers (ages 13–16), followed by young adults (ages 20–24). Foehr (2006) examined concurrent media uses of 3rd to 12th graders the majority of whom, as it was found, engaged in media multitasking at least some of the time. Study participants were especially prone to multitask with computer (for different purposes), Internet, videogames, reading, and music. A few years later, slightly different findings were revealed in a sample of 7th to 12th graders who multitasked with music, computer, and television the most (Rideout et al., 2010). The purpose of the present study was to explore media multitasking behaviors by examining how young adults, college students, who have greater access to various mediated technologies than school students, combine different media. The study focused not only on American young adults, but also on college students from Kuwait and Russia, which contributes to the growing body of literature about media multitasking outside the USA (Voorveld and van der Goot, 2013).

Not all combinations of media and nonmedia activities become ‘reasonable’ and ‘meaningful’ (Roberts and Foehr, 2008). From a wide spectrum of options created by electronic media in today’s world, people pick a few. For example, Foehr (2006) found that American school students (3rd to 12th graders) tended to pair television and music uses with each other, and television and music with video and computer games, computer-based homework, instant messaging (IM) and checking websites. Playing computer games was also frequently paired with IM and website browsing. Doing computer-based homework was often combined with IM, checking websites, and e-mail. IM, e-mail, and surfing websites were the most popular media options to multitask with. Voorveld and van der Goot (2013) indicated that Dutch teenagers (ages 13–16) were most likely to combine music and surfing websites, while young adults (ages 17–24) showed the preference for pairing e-mail and browsing websites. In the current study, we measured how young adults from different countries combine six types of electronic media, both traditional (e.g., television, music and nonmusic audio) and new (computer or video games, the Internet), i.e., what media combinations they prefer. Examining media multitasking pairs among college students was of high interest to us as media multitasking patterns may differ from those of high school students due to lower level of parental control and, thus, greater independence in media use.
RQ1: What are the most popular media multitasking pairs among young adults?

Fast-evolving electronic media not only altered the nature of media use but also changed the way we perform other, nonmedia tasks. While the discussion of multitasking with media started before the commercialization of the Internet and increased availability of mobile phones, with traditional electronic media (television and music) being often used concurrently with other activities (e.g., doing homework; Armstrong et al., 1991; Armstrong and Chung, 2000), it was reinvigorated with the emergence of new electronic media. New electronic media changed the ways we interact with others face to face, travel, do house-related and many other ‘nonmedia’ things. Therefore, we asked how young adults use media while being engaged in nonmedia activities, such as eating, driving, exercising, socializing, doing homework, and being in class (attending lectures).
RQ2: What media do young adults frequently use while being engaged in nonmedia activities?

Pilotta and Schultz (2005) suggested that some media are used as a foreground (primary media), some as a background (secondary media), and some are used interchangeably during media multitasking. We asked:
RQ3: What media are predominantly used as primary, what media are predominantly used as secondary, and what media are used interchangeably during media multitasking?

Differences among three national media markets

We explored media multitasking not only with the sample of American students but also with the samples of Kuwaiti and Russian students, which brings us to the discussion of the second category of media multitasking research: predictors of media multitasking. Jeong and Fishbein (2007) proposed a model of media multitasking antecedents, which includes various media and audience factors. Media factors include structural predictors such as macro-level characteristics of media market (e.g., the USA vs. Kuwait vs. Russia) as well as individual predictors (e.g., a person’s media ownership). Audience factors refer to media users’ characteristics from demographics (e.g., gender and age) to psychological predictors (e.g., personality traits, sensation seeking). Some studies on media multitasking predictors have focused on motivations to use media concurrently (Wang and Tchernev, 2012). While the present study predominantly explores media multitasking behaviors of young adults and does not take into consideration individual antecedents, it contributes to this line of research by studying media pairing in different national media markets, the factor that was kept constant in some previous studies (Jeong and Fishbein, 2007). Three countries, Kuwait, Russia, and the USA, which are different economically, politically, and culturally, were selected to account for macro-level differences. These differences are discussed subsequently.

The availability of electronic media to audiences and ownership of new media technologies that positively predict media multitasking (Jeong and Fishbein, 2007) may depend on economic conditions (i.e., gross national income) as well as the development of national ICT markets. With regard to aggregated income, the USA and Kuwait represent rather developed markets with residents who have the power to buy new media devices (U.S. GDP per capita is $42,486; GDP per capita in Kuwait, an oil-rich country of the Arabia Gulf, is $47,935; United Nations Development Programme, 2013). As for Russia, people in this country have lower purchasing capacity (GDP per capita in Russia is $14,808).

The markets of traditional electronic media technology (TV and radio) are highly saturated in all three countries, accounting for over 95% of households with television and diverse satellite services (CIA World Factbook, 2013; NationMaster, 2012b). The same stands true for the market of cellular phones with at least one phone per person on average in each country (International Telecommunication Union, 2012). Some differences among the three countries, which reflect the overall economic situation, are revealed with regard to personal computer ownership and the access to the Internet. While 76% of Americans and 69% of Kuwaitis have personal computers, a little more than a half of the Russian population (55%) does. In addition, the USA indicates the highest Internet penetration rate (78%) followed by Kuwait (74%) and Russia (48%; International Telecommunication Union, 2012; Internet World Stats, 2013).

While income per capita and the level of ICT market development can positively influence media ownership and, as a result, increase the scope of media multitasking, there are certain political and cultural factors that might interfere with this process. The availability of certain mediated contents, among others, depends on the level of country’s political development (e.g., the state of press freedom and the level of democratization). The more openly information circulates in a country, the greater media diversity citizens enjoy and have more content options to multitask with. On the contrary, the less information is available, the fewer options are out there. Thus, even if one owns an expensive, sophisticated media device, the volume of content available may be limited. According to Reporters Without Borders and the Economist Intelligence Unit, the USA leads among the three countries with regard to the Press Freedom Index, taking the 32nd place, and democratization ranking (#21), followed by Kuwait (#77 for press freedom and #119 for democratization) and Russia (#148 for press freedom and #122 for democratization; Economist Intelligence Unit, 2012; Reporters Without Borders, 2013). Although the three countries have constitutions, the USA and Russia are considered to be federative/federal republics while Kuwait is an emirate (monarchy). Citizens in the USA and Russia can vote to elect presidents and the parliament and participate in local governments elections. The members of Kuwait National Assembly (parliament body) are also elected, with women having the right to vote since 2005, while the Emir (monarch) inherits his power (CIA World Factbook, 2013).

While economic and political factors may influence media ownership and content availability and, hence, the extent of media multitasking, cultural differences, especially those related to the perception of time in different world regions, may also interfere with media use processes and affect media multitasking patterns. Anthropological research about perception of time in different cultures has been growing for over 50 years. Edward Hall introduced the distinction between monochronic and polychronic cultures in 1959. According to the infamous anthropologist, countries differ with regard to time perception and management. People in some world regions, such as North America and Europe, tend to be more monochronic, i.e., prefer to do one thing at a time. People in other world regions, such as the Middle East, Africa, and Central and South America, are more polychronic, i.e., often engage in several activities at the same time (Hall, 1959; Hall and Hall 1990). According to such distinction, the USA is considered to be a monochronic culture and Kuwait (as part of the Middle East) is known as a polychronic culture. Russia, among other Eastern European and some Asian countries, is an interesting case of a culture ‘in the middle’ (Gesteland, 1999). While polychronicity-monochronicity has been widely studied as an organization- and individual-level variable (Bluedorn et al., 1999; Kaufman et al., 1991; Lindquist and Kaufman-Scarborough, 2005; Poposki and Oswald, 2009), a few empirical studies tested cross-cultural differences related to this dimension (Rose, Evaristo, and Straub, 2003).

Based on economic, political, and cultural differences discussed earlier, we hypothesized that Kuwait, a polychronic culture and a national market with high indices of income per capita, would indicate greater levels of media multitasking and using media while performing nonmedia tasks. The USA, despite it is a monochronic culture, would also show somewhat high levels of multitasking due to high development of ICT market, income per capita, and greater political freedoms. Russia would indicate rather lower levels of media-only and media–nonmedia multitasking due to lower indicators of economic and political development as well as moderate position with regard to polychronicity and monochronicity.
H1: Young adults in the USA and Kuwait will indicate somewhat similar and higher levels of multitasking with media than young adults in Russia.

RQ4: Will media multitasking patterns differ by country?

Multitasking and perceived attention to primary media messages

The third category of media multitasking research that constitutes a large body of literature includes scholarship on the effects of this media use habit. Understanding and defining media multitasking phenomenon cannot be complete without understanding its actual and perceived effects. Multiple studies have shown that pairing different tasks at least one of which is related to media use are associated with actual cognitive and behavioral costs (Armstrong et al., 1991; Armstrong and Chung, 2000; Bowman et al., 2009; Furnham et al., 1994; Furnham and Bradley, 1997; Jeong et al., 2010; Pool et al., 2003; Salvucci et al., 2007; Salvucci and Macuga, 2002; Voorveld, 2011; Zhang et al., 2010). As examples, viewing television programs and instant messaging leads to worse performance on homework and poor memory for mediated messages (Pool et al., 2003; Zhang et al., 2010) as well as increases time needed to complete homework (Bowman et al., 2009). Using iPod and cell phone while operating a vehicle negatively influences the quality of driving (Salvucci et al., 2007; Salvucci and Macuga, 2002).

Aside from actual cognitive and behavioral costs, media multitasking is associated with perceived outcomes that are often measured as self-reported variables. Despite a few positive outcomes, such as work efficiency, control, enjoyment, and connection with others (Bardhi et al., 2010), media multitasking is linked to perceived negative effects, which suggests that media multitaskers can understand undesired consequences of their media use habits. For example, college students blame instant messaging (IM) for not being able to finish their schoolwork (Junco and Cotten, 2010); also, IM-ing is associated with greater self-reported distractibility (Levine et al., 2007). Bardhi, Rohm, and Sultan (2010) stated that multitasking with media is perceived as brining chaos, inefficiency (distraction and procrastination), addiction (‘enslavement’), and inattentiveness to mediated messages (‘disengagement’, Bardhi et al., 2010: 322).

As the literature reviewed above shows, inability to concentrate on media content, pay full attention to it can be identified as perceived effect of media multitasking. The second part of the present study is devoted to the exploration of such effect. In particular, we examined how multitasking with each of the six traditional and new electronic media influence perceived attention paid to this medium’s messages. We predicted that the more individuals multitask with a certain medium (identified as a primary medium), the less attention they pay to the messages conveyed by this medium. For instance, the more someone uses other media while watching television, the less likely she/he will be to concentrate, put thought into television messages.
H2: Combining the use of a certain electronic medium with other media will be negatively associated with perceived attention paid to this medium’s messages.

As discussed in previous sections of the literature review, media users in different countries may exhibit different levels of media multitasking due to economic, political, and cultural specifics. We asked whether perceived attention paid to primary media messages would be affected by media multitasking differently in Kuwait, Russia, and the U.S.
RQ5: Will media multitasking predict perceived attention differently in American, Kuwaiti, and Russian young adult samples?

While media use deals with information intake and is associated with the availability of cognitive resources to process this information in automatic or controlled ways (Lang, 2000, 2006), i.e. requires at least some attention consciously or unconsciously paid to primary and secondary media messages, nonmedia activities may vary greatly in this regard. Driving, eating, or exercising can be considered well-practiced tasks that might not be cognitively demanding. At the same time, doing homework and listening to a lecture may require greater intellectual effort. The present study asked how combining such activities with media uses would affect perceived attention to media messages. It is also extremely important to examine how combining social interaction with the use of media can affect perceived attention to media messages.
RQ6: How will different nonmedia activities (eating, driving, exercising, social interaction, doing homework, and listening to a lecture) affect perceived attention paid to media messages when these activities are combined with media use?

RQ7: How will the relationship between media–nonmedia multitasking and perceived attention differ by country?

Method

Sample and procedure

The current study is part of a research project examining media multitasking behaviors of young adults internationally. A survey (N = 532) collected responses in three large national universities: one in USA, one in Kuwait, and one in Russia. Responses were obtained online (USA) and with the use of a paper-and-pencil questionnaire (Kuwait, Russia). The samples were convenience samples. Students majoring in media- and communication-related disciplines (journalism, strategic communication, mass communication) were recruited through several courses. In the USA, students were provided a Web link to complete the survey. In Kuwait and Russia, paper-and-pencil questionnaires were distributed in classes. After reading a consent form and agreeing to participate in the study, students were asked to complete the survey at their convenience and submit responses online (USA) or as hard copies for extra credit.

Twenty-nine percent of respondents were Kuwaiti citizens (N = 134); 28% reported they were American citizens (N = 130); and 29% were Russians (N = 135). About 14% of participants did not report their nationalities or identified them as ‘Other.’ More than half of the sample were males (54%) with the mean age of 20 (M = 19.91; SD = 1.96). About a third of participants reported being college freshmen, followed by sophomores (29%), seniors (23%), and juniors (18%).

Measures

Media multitasking pairs

In this study, we focused on six main media types: television, video or computer games, music and nonmusic audio, phone, and the Internet, and measured how they were combined with one another. As part of media multitasking index measure, respondents reported how often they used a given medium, identified as a primary, with each of the five other media, identified as secondary. They rated frequency for each media multitasking pair on the ordinal scale with four categories: ‘never,’ ‘rarely,’ ‘sometimes,’ and ‘often.’ In addition, frequency for multitasking with a given medium and nonmedia activities, such as eating, driving, exercising, social interaction, doing homework, and listening to a lecture, was measured with the use of the same ordinal scales.

Media multitasking index

Based on the information about each media pair, we calculated the index of media multitasking for each medium based on some suggestions of Ophir et al. (2009). We used this index as a quantitative representation of the extent to which respondents multitasked with each of the six media. Six indices were obtained for media multitasking with (a) television, (b) games, (c) music, (d) nonmusic audio, (e) phone, and (f) the Internet. These indices represented the ratio of time spent multitasking with a given, primary, medium to the total time of this medium use. Higher values indicated greater levels of media multitasking with a certain medium.

Perceived attention

This variable was a self-reported measure. Respondents rated on four 7-point scales from 1 ‘Strongly disagree’ to 7 ‘Strongly agree’ to what extent they paid attention to, concentrated on, found interesting, and put thought into the content of a primary medium’s messages (Potter and Choi, 2006). The indices were calculated for each of the six media: television (Cronbach’s α = .63), video or computer games (Cronbach’s α = .81), music (Cronbach’s α = .73), nonmusic audio (Cronbach’s α = .75), phone (Cronbach’s α = .73), and the Internet (Cronbach’s α = .71).

Results

Media multitasking pairs

To answer research questions and test hypotheses about media multitasking pairs, we examined frequency tables for each media-only or media–nonmedia combination. The first research question asked what the most popular media multitasking pairs among young adults were. Those media multitasking pairs that ‘sometimes’ and ‘often’ engaged 50% of respondents or more were reported in the current study. Eleven media-only multitasking combinations have been found to engage more than half of the survey sample on the regular basis. Television as a primary medium was often simultaneously used with phone (sometimes: 26.5%; often 54.5%) and the Internet (sometimes: 29.5%; often 48.1%). Respondents played video and computer games while listening to music (sometimes: 22.8%; often 27.9%). Listening to music was paired with using phone (sometimes: 26.9%; often 51.1%) and the Internet (sometimes: 22.9%; often 63%). The use of phone was combined with watching television (sometimes: 33.6%; often 39.5%), listening to music (sometimes: 29.5%; often 41.7%), and surfing the Internet (sometimes: 32.2%; often 43.9%). Similarly, the Internet was often paired with television use (sometimes: 32.1%; often 30.6%), music (sometimes: 28.6%; often 56.8%), and phone (sometimes: 33.8%; often 45.1%) (Figure 1).
Figure 1.
Multitasking with media only.

Research question 2 asked what media young adults frequently used while being engaged in nonmedia activities, such as eating, driving, exercising, social interaction, doing homework, and listening to a lecture. Eating, social interaction, and doing homework were identified as activities most commonly paired with the use of electronic media, such as television, music, phone, and the Internet. For example, respondents tended to eat while watching television (sometimes 32.9%; often 52.3%), listening to music (sometimes 32.9%; often 32.5%), using phone (sometimes 33.5%; often 31%) and the Internet (sometimes 35.3%; often 31.6%). They sometimes or often socialized while being engaged with the same four media (television: sometimes 33.5%; often 41.7%; music: sometimes 27.8%; often 27.4%; phone: sometimes 28.4%; often 29.7%; the Internet: sometimes 34.4%; often 19.19%). The same pattern was identified for homework, which was done at the time of watching television (sometimes 29.3%; often 23.3%), music (sometimes 28.4%; often 34.8%), phone (sometimes 26.4%; often 24.5%), and the Internet (sometimes 30.3%; often 30.3%). Finally, listening to music while doing physical exercises (sometimes 24.1%; often 52.8%) and listening to nonmusic audio while driving (sometimes 22.7%; often 28%) were two other somewhat popular media–nonmedia combinations (Figure 2).
Figure 2.
Multitasking with media and nonmedia activities.

Research question 3 asked what media were predominantly used as primary, what media were predominantly used as secondary, and what media were used interchangeably during media multitasking. Eleven popular media multitasking pairs were examined to answer the question. Television, music, phone, and the Internet were used interchangeably, i.e., as both primary and as secondary. The only pair that did not identify the interchangeability was the game–music pair. Playing computer or video games is often used as the primary activity and music usually plays on the background.

H1 posited that young adults in the USA and Kuwait would indicate somewhat similar and higher levels of multitasking with media than young adults in Russia. Overall, surveyed students were sometimes or often engaged in popular multitasking situations specified above (see Figures 3 –7). Similar trends in multitasking were found for Kuwait and the USA. To compare media multitasking pairs in USA and Kuwait, a number of chi-square tests were run. The results indicated that American students multitasked with music and eating (χ²(3) = 9.71, p < .05) and music and doing homework (χ²(3) = 27.58, p < .001) significantly more (74.6% for music or eating; 79.6% for music/homework) than Kuwaiti students (61.4% for music or eating; 59.7% for music/homework). In addition, American students (86.6%) tended to use the Internet and do homework at the same time more often than Kuwaiti students (66.5%; χ²(3) = 13.79, p < .05). Comparing media multitasking in Russia and Kuwait, and in Russia and the USA, we found that all but one chi-square test indicated statistical significance (statistics can be provided by request). Figures 3 –7 show that Russian students multitasked significantly less than American and Kuwaiti students. Only the difference in multitasking with games and music was found insignificant. Overall, H1 was supported.
Figure 3.
Multitasking with TV by country.

Figure 4.
Multitasking with music by country.

Figure 5.
Multitasking with nonmusic audio and games by country.

Figure 6.
Multitasking with phone by country.

Figure 7.
Multitasking with the Internet by country.

RQ4 asked whether media multitasking patterns would differ by country. Each national sample was examined to check for additional unique media multitasking pairs (other than the 11 that were popular across the samples). No additional pairs were identified in any on the samples.

Multitasking and perceived attention to media messages

Hypothesis 2 stated that combining the use of a certain electronic medium with other media would be negatively associated with perceived attention paid to this medium’s messages. Four simple linear regressions with media multitasking index for each of the four media (TV, music, phone, and the Internet) as an IV and perceived attention to messages of a given medium as a DV were run to test the hypothesis. All four tests indicated significant positive associations, meaning that those who multitasked with television (β = .10), music (β = .14), phone (β = .15), and the Internet (β = .24) more frequently reported that these types of media required more attention (F(1,503) = 4.61, p < .05; F(1,519) = 9.64, p < .05; F(1,516) = 11.39, p < .05; F(1,523) = 32.36, p < .001, respectively). Multitasking with television explained 1% of variance in attention to TV messages, multitasking with music accounted for 2% of the variance in the DV, multitasking with phone explained 2% of variance in attention paid to phone messages, and multitasking with the Internet accounted for 6% of variance explained in attention to Internet messages (Table 1).
Table 1.
Simple linear regressions with multitasking with a given medium (TV, music, phone, and the internet) as an IV and perceived attention paid to messages of the given medium as a DV.

F (df) t β

Multitasking with television 4.61 (1,503)* 2.15* .10

R² .01

Adjusted R² .007

DV Attention to TV messages

Multitasking with music 9.64 (1,519)* 3.11* .14

R² .018

Adjusted R² .016

DV Attention to music content

Multitasking with phone 11.39 (1,516) 3.37 .15

R² .022

Adjusted R² .20

DV Attention to phone messages

Multitasking with Internet 32.36 (1,523) 5.69 .24

R² .058

Adjusted R² .057

DV Attention to Internet messages

*
p= < .05, **p = <.001.

Two independent variables, media multitasking with nonmusic audio and media multitasking with games, did not meet the assumptions of normality and linearity. Two dichotomous variables were created and two t-tests were run with attention to nonmusic audio and attention to games variables as DVs. The t-tests didn’t indicate statistical significance (nonmusic audio: t(386) = .17, n.s.; games: t(386) = .28, n.s.). Therefore, H2 was not supported.

RQ5 asked whether media multitasking would predict perceived attention differently in American, Kuwaiti, and Russian samples. The same multiple regressions that were conducted to test H2 were run with the sample split by country. It was found that Russian students who tended to multitask more with television reported greater attention paid to TV messages (β = .19; F(1,128) = 4.74, p < .05), where multitasking explained 4% of variance in perceived attention. The same regression analyses were not significant for Kuwaiti and American samples (Kuwait: β = .01; F(1,177) = .02, n.s.; America: β = −.04; F(1,196) = .25, n.s.). Multitasking with phone was not significantly associated with reported attention to phone messages for Kuwait sample (β = .12; F(1,175) = 2.51, n.s.); however, it was significantly and positively associated with self-reported attention for the Russian and American samples (β = .21; F(1,142) = 6.26, p < .05; β = .15; F(1,197) = 4.26, p < .05, respectively). Multitasking explained 4% of the variance in perceived attention in the Russian sample and 2% in the American sample. As for multitasking with the Internet, this variable was positively associated with perceived attention to Internet messages in each of the three samples, Kuwaiti, Russian, and American (β = .18; F(1,175) = 6.00, p < .05; β = .19; F(1,147) = 5.72, p < .05; β = .15; F(1,199) = 4.60, p < .05, respectively), with 3% of variance explained in the Kuwaiti sample, 4% in the Russian sample, and 2% in the American sample.

Research question 6 asked how different nonmedia activities, such as eating, driving, exercising, social interaction, doing homework, and listening to a lecture, combined with media use would affect perceived attention paid to media messages. Ordinal media–nonmedia multitasking variables were recoded into nominal two- and three-level variables and entered as fixed factors in univariate analyses of variance. The number of levels for each variable was determined by numbers of respondents in groups, which we kept somewhat equal.

Television

A two-way analysis of variance indicated that those who watched television while eating (M = 4.58; SD = .07) reported they paid more attention to TV messages than those who rarely combined these two activities (M = 4.33; SD = .07), F(1,500) = 6.61, p = .01, η = .01. Another two-way ANOVA showed that those who multitasked with television and social interaction (M = 4.70; SD = 1.15) also paid more attention to TV messages than those who did not (M = 4.30; SD = 1.05), F(1,493) = 16.18, p < .001, η = .03.

Music

A three-way ANOVA indicated that those who multitasked with music and exercising often (M = 5.59; SD = 1.32) concentrated on musical contents significantly more than those who did not (M = 5.16; SD = 1.18), F(1,474) = 13.31, p < .001, η = .03. Socializing while listening to music and doing homework while listening to music also indicated significant effects on attention paid to musical contents, F(2,423) = 3.96, p < .05, η = .02 and F(2,443) = 5.80, p < .05, η = .03, respectively. Heavy multitaskers with music and socializing (M = 5.64; SD = .10) and music and doing homework (M = 5.60; SD = .09) were more likely to pay extra attention to music contents than light media multitaskers (M = 5.27; SD = .10; M = 5.10; SD = .12, respectively).

Nonmusic audio

Those who often listened to nonmusic audio while driving (M = 4.91; SD = 1.43) paid more attention to nonmusic audio messages than those who rarely did it (M = 4.31; SD = 1.31), F(1,333) = 16.00, p < .001, η = .05.

Phone and the Internet

Three three-way analyses of variance showed that heavy multitaskers with phone while eating (M = 5.77; SD = 1.15), socializing (M = 5.57; SD = 1.26), and doing homework (M = 5.73; SD = .11) concentrated on phone messages more than light multitaskers with phone and eating (M = 5.37; SD = 1.24), socializing (M = 5.27; SD = .11), doing homework (M = 4.91; SD = 1.43), F(2,471) = 5.19, p < .05, η = .02, F(2,439) = 5.82, p < .05, η = .03, and F(2,409) = 4.79, p < .05, η = .03, respectively.

The same trend was found for multitaskers with the Internet, such as heavy multitaskers with the Internet while eating (M = 5.66; SD = .90), socializing (M = 5.74; SD = .11), and doing homework (M = 5.87; SD = .09) paid more attention to the Internet messages than light multitaskers with Internet and eating (M = 4.88; SD = .11), socializing (M = 5.35; SD = .10), doing homework (M = 5.30; SD = .07), F(2,468) = 18.05, p < .001, η = .07, F(2,413) = 3.78, p < .05, η = .02, and F(1,417) = 26.00, p < .001, η = .06, respectively.

RQ7 asked how the relationship between media–nonmedia multitasking and perceived attention would differ by country. ANOVA tests with country and multitasking with a given medium and nonmedia activities as IVs were run with attention paid to messages of a given medium as a DV. None of the tests showed statistically significant interaction effects on dependent variables.

Discussion

The current study explored media multitasking behaviors among young adults in three different countries. First, it examined the most common, ‘universal’, media multitasking pairs and their specific characteristics. Second, it tested the association between the extent of media multitasking and perceived attention paid to mediated messages. Third, it examined possible differences in media multitasking pairs and effects on perceived attention among the three countries. Before the interpretation of the results, we must emphasize that the study focused on the overall perceived attention to messages of a given medium, not perceived attention paid during media multitasking.

It was found that young people in the USA, Kuwait, and Russia multitask the most with four types of traditional and new electronic media: television, music, phone, and the Internet. Combining nonmusic audio and computer or video games with other activities was not highly popular. This can be easily explained by the extent of media use and the nature of these media. Overall, participants reported low levels of nonmusic audio use (radio news, for example). As for video games, this type of media technology often requires higher levels of users’ attention by posing physical and cognitive challenges to players. This leaves little resources available to complete other tasks at the same time. Interestingly, studies with school students (3rd to 12th graders) revealed somewhat different results, where television and music were the least ‘favorite’ media to multitask with. School students were more likely to multitask with video games than with television and music (Foehr, 2006). College students in the present study, on the contrary, used television and music concurrently with other electronic media more often than video games.

Another result of the study was related to the ‘dominance’ of one electronic medium over another during media multitasking. Only computer or video games were distinctively used as primary media with music as a background medium. With other popular media multitasking pairs, both media could be primary as well as secondary. This finding suggests that the distinction between primary and secondary media activities is becoming somewhat obsolete. Media reality becomes more complex and puzzling, and individuals find it more difficult to set priorities in media use (Wallis, 2010).

Pairing traditional and new electronic media with each other can be partially explained by structural similarity or dissimilarity of messages conveyed by these media. One will find it difficult to combine structurally similar activities, such as listening to music and nonmusic audio at the same time not only because audio information may be overwhelming (Lang et al., 1999) but also because both media may require the same limited-capacity slave system, phonological loop, to ‘take care’ of the initial encoding (Baddeley, 1986). The same logic could be applied to explain why people don’t usually combine television and video or computer games. However, the question of combining media becomes more difficult to answer when phone and the Internet enter the picture. The results of the current study suggest that the uses of phone and the Internet are the most popular media activities that identify their presence in almost all spheres of respondents’ lives and are often combined with each other. Serving as true multimedia platforms, phone and the Internet allow users to be active and operate the whole variety of information types presented as text, pictures, motion, and sound. The adjustment of media multitasking instruments is recommended for future studies to clarify what phone and Internet activities are often involved in media multitasking. A better classification on electronic media forms and options is needed, as well. For example, a clear distinction should be developed among media contents (i.e., text, audio, video), media activities (i.e., ‘facebooking’, Web surfing, texting, instant messaging), and the medium itself (i.e., the Internet, phone).

Interestingly, little qualitative differences in media multitasking were found among American, Kuwaiti, and Russian samples. The present study showed that Kuwaiti respondents multitasked less often with music and eating compared to their American counterparts. This difference could be explained by the perception of eating as a social activity in family-oriented, more collectivistic Middle East, making music listening not appropriate. Kuwaiti respondents were also found less likely to multitask with homework and music, and homework and the Internet than American respondents.

Despite little qualitative differences, the extent of multitasking varied by country. Russian students multitasked with media significantly less than students in the U.S. and Kuwait. This finding is consistent with our predictions that economic, political, and cultural differences may influence media use behaviors. Lower levels of income per capita, ICT market and political developments in Russia could lead to lower ownership of media devices and availability of mediated contents, which result in lower levels of media multitasking. In addition, Russia is not identified as a highly polychronic culture, which could shape the findings of the present study. Although the USA is considered a monochronic culture, economic and political developments could possibly compensate for the preference of people in North America to do one thing at a time. Analyzing the results of the present study, we concluded that political factor played the least role in predicting cross-country differences. Kuwait and Russia stand closer to each other than to the USA with regard to the overall democratization, where media markets are constrained by political and other forms of censorship (Economist Intelligence Unit, 2012: Reporters Without Borders, 2013). However, this similarity was not reflected in media multitasking behaviors in the two countries: Kuwaiti young adults reported they multitasked significantly more than their Russian counterparts. The great extent of media multitasking in Kuwait, thus, can be explained in the context of the present study by economic and cultural characteristics.

Multitasking with four types of electronic media was positively associated with perceived attentional demands to primary media messages. The more media users multitasked with television, music, phone, and the Internet, the more attention they thought they paid to TV, musical, phone, and Internet contents. Although this finding is opposite to our predictions, it has a great value as it shows that dividing time between two or more electronic media leads to significant increases in people’s overall perceptions of cognitive demands associated with these media.

In addition to looking at media activities paired with each other, we examined what nonmedia tasks could be involved in multitasking with media. Eating, socializing, and doing homework were the three most popular media ‘companions.’ The study indicated that the engagement in media–nonmedia multitasking regardless of nonmedia activity was associated with the increase in perceived attention to media messages, as well. The reasons of such increase in perceived cognitive costs have to be scrupulously examined in the future. Increased cognitive costs of media message processing can be associated with the increase in cognitive demands of both media and nonmedia tasks (e.g., TV and homework) or, on the contrary, the easiness of one of the tasks (e.g., eating and using phone).

Finally, future studies have to focus on the investigation of cross-national differences in perceived cognitive demands of media messages. Multitasking with TV in the Russian sample was associated with greater perceived attention paid to TV messages. This finding could mean that television still plays an important role in Russian households and is often treated as a central medium holding viewers’ attention. At the same time, it could be the case that the central role of television is taken by newer forms of electronic media in American and Kuwaiti households, especially, among young users, making TV a background medium. Multitasking with phone was positively associated with perceived attention to phone contents in Russian and American samples but not in Kuwaiti sample. This finding is open to interpretations and has to be further explored, especially with a closer look at cross-country differences in cell phone technology markets. Finally, multitasking with the Internet was a ‘universal’ predictor of the increase in perceived attention in all three samples. This finding suggests that the Internet has become a new dominant medium that is vital to a young individual’s life, present in multiple multitasking situations, and requires a great deal of concentration on Web contents.

The present study has a number of limitations, mostly related to the method used to measure media multitasking behaviors and perceived attention to media messages. First, self-reported measures might not be the best in identifying how much attention individuals pay to a certain message. More sophisticated instruments exist to record cognitive processing in real time (e.g., psychophysiological measures, Lang, 2000, 2006). At the same time, the present study aimed at exploring the overall perception of attentional demands associated with traditional and new electronic media. Second, the measure of media multitasking should include the newest options available to media consumers in different countries, such as smartphones and social media. Third, the sample of countries where media multitasking behaviors are examined should be expanded to allow for testing a wider spectrum of economic, political, and cultural differences. Finally, while it is important to study media multitasking behaviors in young adults, it is also suggested that the behaviors of other age groups are explored more scrupulously (e.g., Voorveld and van der Goot, 2013).

Overall, the study contributed to the existing evidence that media multitasking has become a popular media use behavior in different countries beyond the western world. While people in economically prosperous countries embrace media multitasking behaviors in a faster pace, people in countries with lower levels of economic development have not fully adopted media multitasking as one of their media use routines. The study showed that electronic media uses are often paired with other activities, which alters individuals’ perceptions of attention they pay to media messages. Cross-cultural differences and similarities have to be explored further taking into consideration economic, political, and cultural contexts.

	F (df)	t	β
Multitasking with television	4.61 (1,503)*	2.15*	.10
R²	.01
Adjusted R²	.007
DV	Attention to TV messages
Multitasking with music	9.64 (1,519)*	3.11*	.14
R²	.018
Adjusted R²	.016
DV	Attention to music content
Multitasking with phone	11.39 (1,516)**	3.37**	.15
R²	.022
Adjusted R²	.20
DV	Attention to phone messages
Multitasking with Internet	32.36 (1,523)**	5.69**	.24
R²	.058
Adjusted R²	.057
DV	Attention to Internet messages

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