Giving in to a phone addiction
while viewing fiction
Narrative engagement and media multitasking
Mechteld Schoemaker Student number: 10207872
Master’s Thesis
Graduate School of Communication Master’s programme Communication Science
Supervisor: Renske van Bronswijk 30th of June, 2017
2 Abstract
The purpose of this thesis was to see whether the four aspects of narrative engagement (narrative understanding, attentional focus, narrative presence, and emotional engagement) during an immersive entertainment program were affected by media multitasking, whether those with higher media multitasking habits had higher or lower narrative engagement, whether media multitasking habits moderated narrative engagement during media multitasking, and whether narrative engagement when media multitasking was different between emerging adults and regular adults. An experiment was conducted with 72
participants. Media multitasking did have an effect on participants’ narrative engagement, but the effect was only marginally significant for emotional engagement. Emotional engagement was also higher for those who media multitasked more in daily life. However, when viewing the interaction effect for narrative engagement with media multitasking habits, none of the effects were significant. Finally, only emotional engagement was significantly higher for emerging adults than older adults who were media multitasking. It can be concluded that narrative engagement generally is affected by media multitasking, but that emotional engagement is a different construct.
3 Table of contents Introduction……….…4 Theoretical framework………....6 Method………..13 Results……….…..18 Discussion……….25
Limitations and future research…….………27
References………...30
4 Introduction
Does it bother you when you are watching a movie with someone and they decide to take out their phone? It could be considered rude, but is it really as distracting to our everyday experiences as we suspect? An average emerging adult (18-25) spends several hours per day with entertainment media (Coyne, Padilla-Walker, & Howard, 2013). Examples are watching a show on Netflix, going to the cinema, watching reality television, and playing videogames. Entertainment is a big part of our daily lives. So much exposure to entertainment is bound to affect the emerging adult at least in some way. This makes them interesting subjects to study. Media multitasking, simultaneously engaging in two or more types of media or using media while engaging in non-media activities, is increasingly common as well. The habit has increased significantly during the 2000s with the increased use of information and communication technologies (ICT; Roberts, Foehr, & Rideout, 2005). It has become almost ubiquitous since the advent of smartphones and laptop computers that can readily access sites such as Facebook, Twitter, and Instagram (Oviedo, Tornquist, Cameron, & Chiappe, 2015). The habit is especially prominent among young people and college students (Carrier, Cheever, Rosen, Benitez, & Chang, 2009).
Just how distracted are media multitaskers from their entertainment? Earlier studies have shown that media multitasking does distract when trying to study or when engaging in face to face conversations (for an overview, see Van der Schuur, Baumgartner, Sumter, & Valkenburg, 2015). There seems to be a gap in the literature when it comes to entertainment, however, and specifically narrative engagement, which is someone’s engagement with a story (Busselle & Bilandzic, 2009). This term was introduced by scholars to clarify and integrate several constructs that were used to describe aspects of engaging with a narrative, such as transportation, identification, presence and flow. Busselle and Bilandzic wanted to formulate how the constructs were related to each other and how they could facilitate persuasion and reality construction. They came up with a scale that combined narrative understanding, attentional focus, narrative presence and emotional engagement.
The question remains whether phone activity really is interruptive to someone’s engagement with the story of an immersive entertainment program. This leads to the following research question:
RQ: To what extent is narrative engagement affected by media multitasking when
5 There are two sub-questions that can be extended from the main question:
SQ1: Does the amount of media multitasking normally engaged in moderate these
results?
SQ2: Are there differences between emerging adults and regular adults?
In today’s ever-changing media landscape where media multitasking is becoming an everyday standard for many, it is important to realize its implications. Researchers need to start
acknowledging not only the consequences for academic performance or social aspects, but that media multitasking may have consequences for people’s entertainment experience as well. The outcome of this study will clarify whether people will need to stop media multitasking for the full entertainment experience, or whether they can continue with the habit. Entertainment developers would do well to see whether media multitasking is detrimental to the experience they are trying to convey, and whether they should
accommodate or counteract it. In terms of academics, hopefully this study will broaden our knowledge on the effects of the never-ending trend of media multitasking and how it affects the lives of those involved, especially emerging adults. It will also clarify what we know about narrative engagement. Previous experiments on narrative engagement were conducted in a laboratory setting with little distraction (Ross, 2011). This study will replicate distraction from media as it happens in viewers’ daily lives.
6 Theoretical framework
Narrative engagement
Narrative engagement in other words is someone’s bonding experience with a story. For this study, narrative engagement will be based on four constructs: narrative understanding, attentional focus, narrative presence, and emotional engagement (Busselle & Bilandzic, 2009). Narrative understanding and attentional focus form the cognitive aspects of narrative engagement. The terms are self-explanatory. The focus of this study, however, remains especially on the emotional aspects of narrative engagement: narrative presence and emotional engagement.
Narrative presence
Narrative presence corresponds to descriptions such as “being there” or constructs such as
transportation or presence (Busselle & Bilandzic, 2009). When someone is ‘present’, they
have a conscious feeling that they are in a virtual world, caused by unconscious spatial perception processes (Wirth et al., 2007). Closely related to this are the terms immersion and
flow. The term immersion has been used often especially for videogames and sometimes for
movies (Rigby, Brumby, Cox, & Gould, 2016). Immersed viewers see the virtual world they are experiencing as immediate and present (Visch, Tan, & Molenaar, 2010). Immersion can be defined as a feature of display technology determined by inclusion (when environmental influences are excluded from the participant’s experience), extension (the number of sensory modalities addressed), surround effect (panoramic width of sensory impressions) and
vividness (display resolution; Slater & Wilbur, 1997). It has been shown that immersion is a positive and satisfying experience (Weibel, Wissmath, Habegger, Steiner, & Groner, 2008). However, getting immersed requires one’s attention, and distractions such as phone-induced media multitasking pull someone out of this immersion (Oviedo et al., 2015). According to Green, Brock, & Kaufman (2004), being transported into a narrative is a desirable state as it may remove stress factors such as personal concerns or other problems that elicit social anxiety. However, logically thought, media multitasking removes one from the state of flow in a narrative experience. This remains to be tested.
One condition that needs to be met in order to get fully immersed or be present is the willing suspension of disbelief. The term was already coined in the 1800s by Samuel Taylor Coleridge, and adapted for modern television and other media (Ferri, 2007). It means that whoever is watching an entertaining media product is willingly suspending whatever disbelief
7 they have about the fictional narrative in order to get immersed. The viewer needs to perceive the events described as if they were real, despite that they are not (Vorderer, Klimmt, & Ritterfeld, 2004). This is how the viewer can develop feelings for characters as well. If the viewer has any doubts about the realism of the fiction, the entertainment experience is inhibited. Could this happen when viewers are media multitasking? If viewers are forced to disbelieve in an entertainment experience, they start to approach it from an analytical and even critical perspective (Vorderer, 1993). But does this disbelief transfer over from another interruptive medium?
Closely related to the willful suspension of disbelief is verisimilitude. Popper emphasized its importance and the need to explicate it (Popper & Hudson, 1963). Verisimilitude is the quality or state of appearing to be true (Popper, 1972). So it is the likelihood that something appears as real. Verisimilitude is what triggers the suspension of disbelief. It is about depicting the real world with authenticity (Rosenblatt, 2009). Most of the literature seems to be about verisimilitude in branded entertainment rather than more general and in relation to suspension of disbelief.
Emotional engagement
Emotional engagement concerns emotions that viewers have with respect to characters, either feeling the emotions of the characters (empathy), or feeling for them (sympathy; Busselle & Bilandzic, 2009). Closely related to this are the terms identification and perspective taking. It seems that most literature on emotional engagement revolves around empathy. Being able to empathize with characters has been associated with the degree of transportation or presence as well (Argo, Zhu, & Dahl, 2007). Empathy is also a prerequisite to liking or disliking the protagonists and antagonists in the story (Vorderer, Knobloch, & Schramm, 2001). Another author states that there would be no possibility of entertainment if viewers could not develop hope and fear in reaction to what happens to the characters (Zillman, 2003). In a well-known model on enjoyment in entertainment, empathy has been placed on the user prerequisite side (Vorderer, Klimmt, & Ritterfeld, 2004). Others have said that what matters in entertainment is that people want to be moved (Hanich, Wagner, Shah, Jacobsen, & Menninghaus, 2014).
In regards to media use, it has been found that over ten hours a day of smartphone usage significantly decreases people’s empathy (Burch, 2013). This suggests that the mental state of people who use smartphones is occupied by their tasks, decreasing their ability to empathize. Logically thought, if we extend this to media multitasking while viewing
8 entertainment, it may very well be that people’s empathy for the characters in the film also decreases.
One thing that may happen while viewing entertainment, is that emotions may endure longer, even when media multitasking. Excitation transfer theory, coined and perfected by Zillmann in the 60s, explains this possible effect. Its base assumption is that residual excitation (or emotion) amplifies excitation to another stimulus (Byrant & Miron, 2003). In this regard, getting pulled out of the story does not necessarily mean emotional engagement should be lowered, because people hold on to it a little longer.
Media multitasking/task switching
Media multitasking can be described as engagement in several concurrent activities at least one of which is related to media use (Foehr, 2006). It can be between different devices (such as watching television and using a smartphone simultaneously), or within one device
(multiple windows on a computer screen). However, there is another term. Multitasking is usually seen as the parallel processing of two tasks at the same time. Task switching is the ability to shift between discrete tasks (Alzahabi & Becker, 2013). It can be argued that what really happens in most cases where the term multitasking is used, is actually task switching. The viewer temporarily shifts their attention away from the main task (e.g. watching a show) to another task (e.g. phone activity). However, the literature comes from both topics, and to get a complete view of the situation, both will be taken into this framework. It has been argued that when media multitasking, a person can do both, either continuously switch their attention between multiple sources of information, or divide one’s attention across multiple streams simultaneously (Ralph, Thomson, Seli, Carriere, & Smilek, 2015).
Effects and cognitive aspects of task switching and multitasking
In general, the immediate effects of task switching or multitasking while engaging in other activities are negative. For example, watching TV while doing homework decreased a
person’s performance on the recognition of the television content (Zhang, Jeong, & Fishbein, 2010). Reading and watching a video simultaneously decreased participants’ performance on the reading task (Lin, Robertson, & Lee, 2009). Using laptops to media multitask during lectures in university also decreased the students’ memory for the contents of the lecture (Hembrooke & Gay, 2003). Whether or not this effect stays negative for narrative engagement during an immersive entertainment program remains to be studied.
9 In the task switching paradigm a great deal of research has been done (Kiesel et al., 2010). Within this field, participants are presented with stimuli that require more than one action or need to perform one of two tasks on stimuli (Grange & Houghton, 2014). The cognitive aspect responsible for task switching is the executive functions (Diamond, 2002). This activates from the prefrontal cortex of the brain. One study demonstrated that people are limited in performing two stimulus-response tasks concurrently because cognitive resources required in such tasks can be used by only one task at a time (Hashler, 2000). This has been attributed to a bottleneck; the second task has to wait until some critical processing stage of the first is completed. It has indeed been found often that switching tasks induces a
performance cost, typically revealed as a slower response time (RT) and increased error, also known as switch cost (Grange & Houghton, 2014). It can be expected that task switching induces an inhibiting effect on the cognitive aspects of narrative engagement: narrative understanding and attentional focus. It can hinder narrative understanding because the
storyline will have to wait until the participant has finished processing the task on their phone, thus missing parts of the story. It can inhibit attentional focus by way of the switch itself, or the cost of the switch.
If we broaden our view towards the literal meaning of the term multitasking, i.e. performing two or more tasks simultaneously, such as listening to the radio while driving, the results are also unfavorable. If performing a single task activates some volume of the brain, x, then another task would activate y. It would be expected that the two together should activate x+y, but this is not what happens. Both tasks actually activate substantially less than x+y. This effect has been called underadditivity of multitasking activation (Newman et al., 2007).
One theory from the field of multitasking research is multiple resource theory,
proposed by Wickens in 1984. Again, the basic assumption here is that humans have a limited amount of cognitive capacity to process information (Basel, 1994). When people try to do two tasks at the same time, these limited mental resources have to be distributed according to the demands. When this exceeds someone’s processing capacities, cognitive overload happens. (Lang, 2000). After this, multitask capabilities decline. However, according to this theory, some level of parallel processing is possible until there are no more resources (Van
Cauwenberge, Schaap, & van Roy, 2014).
Another theory within this field is the threaded cognition theory, coined by Salvucci & Taatgen (2010). This is a variation of the multiple resource theory whereby task relevance is of importance. It posits that cognition maintains a set of active goals that produce threads of goal-related processing across the resources that are available (Salvucci & Taatgen, 2010).
10 Different tasks are represented by different threads. Thus, it is possible to process various simultaneous tasks effectively, as long as they have a common goal, but don’t use the same resources (Wang, Irwin, Cooper, & Srivastava, 2013). When a person is multitasking, multiple threads are active. Task relevance refers to whether the tasks serve closely related goals. In the present study, the tasks participants have to complete are irrelevant to the narrative engagement with the entertainment experience. It can be argued that the irrelevance of the tasks causes distraction from the narrative engagement.
Generally, all theories mentioned above agree that there are limitations in people’s ability to handle multiple information streams. Thus, for this hypothesis it is going to be assumed that media multitasking has a negative effect on people’s narrative engagement. This leads to the following first hypothesis:
H1: Narrative engagement with an immersive entertainment program will be lower when media multitasking compared to when not media multitasking.
Media multitasking habits
There are two opposing hypotheses about the potential benefits of and problems with media multitasking, and both have some agency. On the one hand, constant exposure to several media activities at once may lead to breadth-biased cognitive control (Ophir et al., 2009). In this case it is posited that media multitasking may negatively affect cognitive control
processes in the long run. This is referred to as the scattered attention hypothesis (Van der Schuur et al., 2015). On the other hand, some researchers argue that when someone media multitasks more in daily life, they will be better able to handle different streams of
information and still follow the story (e.g. Alzahabi & Becker, 2013). In the review by Van der Schuur et al. (2015), it is referred to as the trained attention hypothesis.
The hypothesis that seems to have gained the most support, is the scattered attention
hypothesis. The same study that introduced the breadth-biased cognitive control found that
heavy media multitaskers (HMMs), or heavy task switchers if you may, were less able to efficiently switch between tasks than light media multitaskers, and that they were more distracted by irrelevant stimuli (LMMs; Ophir, Nass, & Wagner, 2009). Another study also found that college students who spent more time Instant Messaging had greater difficulty concentrating on less externally stimulating tasks such as reading academic articles (Levine, Waite, & Bowman, 2007). However, it can be argued for this study that the main task (the immersive show) will be entertaining and thus externally stimulating. Another study found
11 that higher levels of media multitasking were related to lower performance on working
memory tasks (Sanbonmatsu, Strayer, Medeiros-Ward, & Watson, 2013).
There is however also some support for the trained attention hypothesis. One study found that HMMs were actually more efficient at task switching (Alzahabi & Becker, 2013). However, HMMs and LMMS had similar outcomes for performing two tasks at the same time. Another study found that heavy media multitaskers were better at multisensory integration (Lui & Wong, 2012). This seems especially relevant for the current study, as participants will be using only sight and touch to use their phones, but they can still hear the immersive entertainment program while doing so. Two other studies found no relation at all between heavy and light media multitaskers in terms of how efficiently they could task switch (Baumgartner, Weeda, van der Heijden, & Huizinga, 2014; Minear, Brasher, McCurdy, Lewis, & Younggren, 2013). However, the target group for one of these studies was
adolescents, a group whose brains are not fully developed yet (Valkenburg & Piotrowski, in press).
In conclusion, media multitaskers may be better or worse at task switching, or there may be no difference. For the current study the trained attention hypothesis is going to be assumed, which states that those who media multitask more in life are better at cognitive control processes.
H2: Narrative engagement with an immersive entertainment program will be higher for participants who have more pronounced media multitasking habits than
participants who have less pronounced media multitasking habits.
There may also be an interaction effect, as a person’s media multitasking habits could moderate the effects found for narrative engagement.
H3: Narrative engagement with an immersive entertainment program will be lower when media multitasking compared to when not media multitasking, but this effect will be weaker for participants who have more pronounced media multitasking habits than participants who have less pronounced media multitasking habits.
Emerging adults
An accurate term for those between the ages 18 and 25, is emerging adult (Arnett, 2005). This stage in life is characterized by identity explorations, instabilities, being self-focused, and having an (almost) endless sea of possibilities. Most notably, emerging adulthood is a period in between adolescence and adulthood. Further, Arnett postulates that the reckless behavior that characterizes adolescence reaches new heights in emerging adulthood. There are several
12 reasons. First, the emerging adult is no longer dependent as an adolescent. Second, he/she does not feel the normative responsibilities of adulthood. Third, and most importantly for this study, he/she isn’t as likely to be monitored by adults. Fourth, the emerging adult can pursue experiences more freely without the constraints of adolescence or adulthood (Arnett, 2005).
These overall characteristics are also reflected in the heavy entertainment and heavy media multitasking behaviors of the emerging adult. As an example, not being monitored or feeling no constraints could lead to Netflix binges while simultaneously scrolling through Instagram. Either emerging adults have trained themselves to become the best media multitaskers, or they are becoming more and more distracted, as said before in the section about multitasking habits. It is also possible for both of these effects to happen at the same time.
Important to remember is the late maturation of the executive functions associated with the prefrontal cortex (Segalowitz & Davies, 2004). The prefrontal cortex is crucial for task switching. The executive functions are responsible for planning, organizing, and
completing tasks. Throughout early teen hood (12-15) the prefrontal cortex is lagging behind the development of the other parts of the brain. It starts to develop rapidly when teens reach 16 (Valkenburg & Piotrowski, in press). After that, the actual executive strategies need to be learned from experience (Segalowitz & Davies, 2004). Of course, this is not something that happens overnight, this may take a few years. It could be that emerging adults still struggle with their executive functions, as can be seen from their risk-taking behaviors. Perhaps this could mean they are also less able to efficiently task switch than older adults. It could also mean the contrary, that they are training themselves to be more efficient from a younger age. There is the argument that multitasking or task switching promotes mental flexibility that can change the manner in which young people, whose neural plasticity is still high, learn and hold on to information (Dye, Green, & Bavelier, 2009; Lui & Wong, 2012). In any case, there is no compelling evidence that growing up media multitasking causes deficits in developing
attention processes (Ferguson, 2011). The hypothesis below will revolve around emerging adults being trained at media multitasking.
H4: Narrative engagement will be higher for emerging adults who are media multitasking than older adults who are media multitasking.
13 Method
Design
The design was a 3 x 2 factorial design, with the Factor Media multitasking as a between-subjects variable (2 levels, namely absent and present), the Factor Media multitasking habits as a quasi-experimental variable (2 levels, namely lower vs. higher) and Age group (2 levels, emerging adult and older adult). The conditions were ordinal. See Table 1 for an overview.
Factor: Media Multitasking Absent Present Present Age Group Emerging adult Emerging adult Older adult Media Multitasking Habits
Less Pronounced 1 3 5
More Pronounced 2 4 6
Table 1: Experimental design for Media multitasking during entertainment viewing
Sample
The main sample for the experiment was emerging adults, those between the ages of 18-25. To see whether differences found for media multitasking are age-related or not, there was another sample group of older adults, also subject to the media multitasking condition. This group was above the age 26 up to 65. Participants were recruited via the researcher’s social network and through snowballing. In the case of communication research, it is often
impossible to reach statistical soundness for the amount of participants per condition, as getting that many respondents within a short amount of time isn’t reachable. A reasonable amount as a rule of thumb is about 30 participants per condition. That brings the total participants up to 180. However, it was only possible to recruit 72 participants for the two-week data collection period.
Procedure
The experiment was held at multiple locations to increase the number of participants. It was mostly held at the available spaces at the UvA, where a television or a beamer was available for showing a short film on a bigger screen (see the Materials section for more information about the film). Participants were divided in groups ranging from one to five people, and these groups were held about twice or three times a day, depending on availability of the rooms and of the participants.
14 The main variable was manipulated between subjects, as the entertainment medium chosen could have affected the results of a within-subjects manipulation otherwise. For example, the first half of the show could be less engaging in comparison to the second half. Participants were first given an informed consent form that also explained the research, and were asked to read it carefully. Both versions can be found in Appendix 1. One group (the absent Media Multitasking group) then watched the short film without interference. This group was asked to completely silence their phone’s notification system and stow it. Another group (the present Media Multitasking group) engaged in media multitasking. This was done by an app that they needed to download onto their smartphones before the experiment (the app will also be introduced in the Materials section). All participants in this group were in possession of a smartphone. The participants were also asked to put their phones on vibrate to disturb the other participants less. They were sent a test question via the app to see if their notification system worked accordingly before commencing. Post-viewing, the participants were subject to a paper questionnaire.
Materials
Participants watched an immersive short film, called Sidekick (2016). The short film is a little over 14 minutes. It is particularly suitable for this experiment for several reasons. First, it has a very high production budget for a short film, with believable CGI (computer-generated imagery), quick camera cuts, and well-known actors. Second, it also tells a strong, perhaps relatable story. The story is about a father who is dying of cancer, and he tells his son a bedside story, where a superhero (the father) is bested by an evil villain (cancer) but his sidekick (the son) must save the superhero’s love of his life (the mother). It symbolizes that the mother will go through a hard time as the father passes away and that the son must simply be there for her. The aspect of that the father is dying can only be seen at the very end, which gives it extra emotional impact. Third, it is short enough for people to not get bored during the experiment, and immersive enough to get carried away for its short time. Fourth, because the camera cuts switch quickly between the bedtime story and the real life of the characters, it is easy to lose track of what is happening when task switching. Fifth, because it is a short film, not many of the participants had seen it before, and that should have been of a lesser influence to the results. It only has 300k views on YouTube which is relatively low for such a budget.
The participants were also asked to download the app called MyPanel. This app was used to influence the factor Media Multitasking. The app asked the attention of participants to closely resemble text, WhatsApp, or Facebook messaging as they would in daily life. Texting
15 is the single most used feature on a smartphone, with 97% of all smartphone users having texted within a week (Smith, 2015). According to some statistics, in 2014, globally about 18.7 billion texts were sent every day, averaging from 561 billion texts per month (Statistic Brain, 2015). That does not even include apps. Apps such as WhatsApp and Facebook Messenger add another 60 billion messages to that number (Goode, 2016). In the US, the age group 18 to 24 was sending 128 regular texts per day in 2014, and the age group 25-34 had 75 texts to manage every day. (Marketing Charts, 2014). That would mean about five texts per hour for the 18-24 age group. Add to that the actual non-SMS texts from apps, which is double (60 billion vs. 18.7 billion), that would lead to about 15 messages per hour coming in. The short film takes a little less than 15 minutes, which is equal to receiving five messages. To
exaggerate the experimental manipulation, this was upped to five messages during its duration. The type of questions that the app asked were also reflected on what kind of messages people could get. Three of the questions were very simple questions that the
participants were able to answer within seconds. The first was: “How many TV’s do you own in your home?” with answers ranging from ‘0’ to ‘5+’. The second question showed a meme (usually a funny picture with some text; the example image was a picture of a zebra riding a giraffe and saying “onwards, my noble steed”) and ask them whether or not they thought it was funny. The third question asked them what their favorite country in the world is. From the more difficult to interpret messages, one question asked them to look some information up. It needed them to Google (or search in whatever way they wanted) how many volcanoes there are in the world (1500), and how many have erupted (500). The last question was one with a lot of text to introduce statements, and then they had to agree with one statement that they liked the most, or disliked the least. The statements chosen were controversial, so that participants needed to give them some thought. Statements that they could tick were: “War is never an option for solving international disputes.”, “Marriage is outdated.”, “We are
becoming too dependent on computers.”, “Smoking should be banned.”, and “Software piracy is not really a crime.”. The questions were sent at random intervals so that participants did not expect a few minutes in between every time.
Measures
In the questionnaire, participants were first asked whether or not they had seen the film before (six participants had seen it before), as that could have a considerable influence on narrative engagement. Because the short film is spoken English and there are no subtitles, participants were also asked to rate their English understanding from 1 to 10 (M = 8.29 SD = 1.30).
16 There was a manipulation check where participants stated the percentage of the time that they paid attention to the film (Robertson & Lee, 2009). To exclude any external influential factors, the participants also stated the amount of time they paid attention to their phone, if applicable (only for the non-control participants).
To measure media multitasking habits, a modified version of the Media Multitasking Index (MMI) was used, originally created by Ophir et al. (2009). The modified MMI was created by Baumgartner, Lemmens, Weeda and Huizinga (2016). This version was made to fit the media multitasking habits of adolescents, but this measure was chosen because the
original MMI is very extensive, with 132 items to fill in. This may cause increased errors in participants due to fatigue or low motivation. The adjusted MMI has 72 items to fill in. The adjusted MMI is also more up to date than the original, where the original still separates SMS from instant messaging. The MMI provides a stable measure of an individual’s trait media multitasking activity. A higher score on the MMI indicates more frequent use of media multitasking. Participants filled in items for the following nine activities: watching TV, reading, listening to music, talking on the phone, sending messages via phone or computer (such as texting, WhatsApp, Facebook Messenger), using social network sites (such as Facebook or Instagram), watching movies on a computer, other computer activities (such as surfing on the web, Photoshop), and playing videogames. For each of these activities,
participants rated the concurrent use of other eight media with the primary medium on a scale of 1 to 4 (1 = “Never”, 2 = “Sometimes”, 3 = “Often” and 4 = “Very often”). An example question is “While watching TV, how often do you send messages via phone or computer at the same time?” This resulted in nine media multitasking subscales. The average of these nine subscales was then combined to create the adjusted MMI for participants. Based on the MMI scores, researchers typically compare two extreme media multitasking groups, heavy media multitaskers (HMMs) and light media multitaskers (LMMs), using different cut-off scores (Van der Schuur et al., 2015). For the current study, a cut-off point was determined to define which of the participants had less pronounced habits (first condition) and those that had more pronounced habits (second condition). The cut-off point was at the 50% mark, with half of the participants below and half of the participants above.
To measure narrative engagement, the Narrative Engagement scale was included. This scale is comprised of four subscales, each with three questions that can be answered with a 5-points Likert scale. For example, for Narrative Understanding the question “At 5-points, I had a hard time making sense of what was going on in the program” will load negatively on the scale, with answers ranging from 1 = “Strongly disagree” to 5 = “Strongly agree”. Added to
17 the end of the scale was the question whether participants enjoyed watching the short movie, which was also a 5-point Likert-scale.
Participants were also asked questions about the content of the short film itself, to see whether or not they were still able to absorb information from viewing while media
multitasking. Both questions were multiple choice with three answer options. Another question was whether the participants perceived that there were any (other) distractions (besides their smartphones). The questionnaire finished with age, gender, and education level finished. The questionnaire that was used for this thesis can be found in Appendix 2.
18 Results
Statistics
72 participants completed the experiment, 24 were in the emerging adult experimental group, 24 in the emerging adult control group, and 24 in the adult experimental group. Below in Table 1 is an overview of participants per condition.
Age group
Experimental manipulation Emerging adult Adult Total
No Low MMI 10 / 10
High MMI 14 / 14
Total 24 / 24
Yes Low MMI 7 20 27
High MMI 17 4 21
Total 24 24 48
Total Low MMI 17 20 37
High MMI 31 4 35
Total 48 24 72
Table 1: Participants in the respective categories.
50% of the participants was female. Ages ranged from 19 to 64. The mean age for the emerging adult age group was 22.7 (SD = 1.88). The mean age for the adult group was 46.8 (SD = 11.88). The most common education that was finished or being followed was university (40 participants), the second most common was higher vocational education (21 participants). The mean level of English understanding was rated by participants as 8.3, which is
successfully high for most participants to understand the short movie, which was spoken in English. Six participants indicated that they had seen the short film before, which is 8.3 percent of the total. Enjoyment of the short film was generally rated high, with a mean of 4.0 out of 5.
Manipulation check
Participants were asked to score how much of the time they were watching the short film and how much of the time they paid attention to their phone. Those in the experimental group paid attention to the film averagely 77.3% of the time, and paid attention to their phone 20.2% of
19 the time. Those in the control group said that they paid attention to the short film 93.9% of the time averagely. In both groups it is notable that the numbers don’t add up to 100%, indicating that people still found it hard to pay attention to the screen in front of them, whether in the experimental or control group. However, an independent samples t-test indicated that there was a non-significant difference between the emerging adult group (M = 76.25, SD = 15.05) and the regular adult group (M = 78.42, SD = 10.74) in the experimental condition, in terms of how much they paid attention to the short film; t(46) = -.574, p = .569.
Construction of variables
A scale was attempted to create for the main dependent variable Narrative engagement. First, however, four subscales were created, each measuring a different aspect of narrative
engagement. Two of these scales were worded negatively, Narrative understanding and Attentional focus, and needed to be recoded to positive values for the final scale to be created.
For the Narrative understanding scale, first, the three items measuring Narrative understanding were recoded to score positively, as the items on the questionnaire were worded negatively. Three variables loaded on one component which explained 78.2% of the variance, with an eigenvalue of 2.35. All component loadings were over .86. Cronbach’s alpha was .86. The scale for Narrative understanding was reliable, and thus created on the basis of the mean score across the three items (M = 3.94, SD = 0.90, Min. = 1.33, Max. = 5.00).
The next scale that was created measured Attentional focus. The three items for this scale were also recoded to score positively. Three variables loaded on one component, explaining 80.0% of the variance. The eigenvalue was 2.40. All component loadings were over .86. Cronbach’s alpha for the three items was .87, indicating that the scale for
Attentional focus was reliable. The scale was created by mean score of the three items (M = 3.66, SD = .97, Min. = 1, Max. = 5).
For the Narrative presence scale, all three variables loaded on one component, which explained 76.4% of the variance. The eigenvalue was 2.29 and all component loadings were above .86. A reliability analysis showed a Cronbach’s alpha of .84. The scale for Narrative presence was reliable, and was created on the basis of the mean score of these three items (M = 3.08, SD = .95, Min. = 1, Max. = 5).
Lastly, the Emotional engagement scale was created. Three items loaded on one component, explaining 77.4% of the variance, with an eigenvalue of 2.32. All component loadings were above .84. Cronbach’s alpha was .85, indicating a reliable scale for Emotional
20 engagement. The scale was created on the basis of the mean score across the three items (M = 3.54, SD = .88, Min. = 1, Max. = 5).
It was not possible to combine all four scales into one, despite the Narrative
engagement scale having been tried and tested. Perhaps this was due to differences between the experimental and control group. The four items loaded on one component, explaining only 54.4% of the variance. For the analyses, all aspects of the narrative engagement scale were treated separately.
To create two conditions with the Media Multitasking Index, there needed to be a cut-off score to divide participants in two equal groups. First, a mean score was created on the basis of the nine items measuring the separate aspects of multitasking habits (M = 14.56, SD = 2.89, Min. = 9.22, Max. = 24.22). For an even distribution of participants, 36 participants were to be within and below the cut-off point of 14.56. Two participants were exactly at the mean score, leaving 37 (51.4%) low media multitaskers and 35 high media multitaskers.
Main analyses
The type of analysis conducted for all four hypotheses below was a Univariate ANOVA (analysis of variance). However, separate ANOVA’s were to be conducted for all four different subscales, as they could not be combined into one reliable scale.
H1: Narrative engagement with an immersive entertainment program will be lower when media multitasking compared to when not media multitasking.
For this hypothesis, four factorial ANOVA were conducted. The first Univariate ANOVA’s main effect for the first independent variable Media multitasking on the dependent variable Narrative understanding was F(1, 70) = 6.81, p = .011, η² = .09, indicating a significant difference in narrative understanding between media multitasking (M = 3.76, SD = .92) and not media multitasking (M = 4.32, SD = .72). The second ANOVA’s main effect of Media multitasking on Attentional focus revealed F(1, 70) = 10.48, p = .002, η² = .13, which indicates a significant difference in attentional focus between media multitasking (M = 3.42,
SD = .87) and not media multitasking (M = 4.15, SD = .99). The third Univariate ANOVA
for the main effect of Media multitasking on Narrative presence revealed F(1, 70) = 5.59, p = .021, η² = .07, pointing out a significant difference in narrative presence between media multitasking (M = 2.90, SD = .91) and not media multitasking (M = 3.44, SD = .93). Finally, the fourth ANOVA’s main effect of Media multitasking on Emotional engagement was F(1,
21 70) = 3.84, p = .054, η² = .05, leaving only a marginally significant difference in emotional engagement between engaging in media multitasking (M = 3.40, SD = .87) and not media multitasking (M = 3.82, SD = .86). Hypothesis 1 can be partially accepted, as the last effect was only marginally significant. Narrative engagement with an immersive entertainment program was indeed lower when media multitasking compared to when not media multitasking, but the effect for emotional engagement was less pronounced.
H2: Narrative engagement with an immersive entertainment program will be higher for participants who have more pronounced media multitasking habits than
participants who have less pronounced media multitasking habits.
For the second hypotheses, another four factorial ANOVA were conducted. The first ANOVA’s main effect of Media multitasking habits (the MMI groups that were created) on the dependent variable Narrative understanding was F(1, 70) = 2.49, p = .119, η² = .034, indicating a non-significant difference in narrative understanding between having high media multitasking habits (M = 4.11, SD = .74) versus having low media multitasking habits (M = 3.78, SD = 1.00). The second ANOVA’s main effect of Media multitasking habits on Attentional focus was F(1, 70) = .133, p = .717, η² = .002, suggesting a non-significant difference in attentional focus between high media multitaskers (M = 3.70, SD = .96) and low media multitaskers (M = 3.62, SD = .99). The third main effect of Media multitasking habits on Narrative presence revealed F(1, 70) = .034, p = .853, η² = .00, pointing out a
non-significant difference in narrative presence between high media multitasking habits (M = 3.10,
SD = .95) and low media multitasking habits (M = 3.06, SD = .96). The final main effect of
Media multitasking habits on Emotional engagement was F(1, 70) = 4.25, p =.043, η² = .057, meaning a significant difference on emotional engagement between high media multitaskers (M = 3.75, SD = .94) and low media multitaskers (M = 3.33, SD = .78). Hypothesis 2 is partially rejected, as none of the effects were significant, except the final effect of multitasking habits on emotional engagement. Narrative engagement was not higher for participants with more pronounced media multitasking habits, only emotional engagement was higher.
H3: Narrative engagement with an immersive entertainment program will be lower when media multitasking compared to when not media multitasking, but this effect
22 will be weaker for participants who have more pronounced media multitasking habits than participants who have less pronounced media multitasking habits.
To test this hypothesis, only the interaction effect between media multitasking habits and the media multitasking manipulation on the four different aspects of narrative engagement was attended to. The first ANOVA on Narrative understanding revealed an interaction effect of
F(1, 68) = .154, p = .696, η² = .002. The effect of media multitasking on narrative
understanding was not less pronounced for those with higher media multitasking habits. The second interaction effect on Attentional focus was F(1, 68) = 2.11, p = .151, η² = .030, revealing that the effect of media multitasking on attentional focus was not less pronounced for participants with higher media multitasking habits. The third interaction effect on Narrative presence of yielded F(1, 68) = .330, p = .568, η² = .005. The effect of media multitasking on narrative presence was not less pronounced for those with higher media multitasking habits. The final interaction effect on Emotional engagement was F(1, 68) = .032, p = .858, η² = .00, which means that the effect of media multitasking on emotional engagement was not less pronounced for those with higher media multitasking habits. Hypothesis 3 was rejected, as none of the interaction effects were significant. The effect of media multitasking on narrative engagement was not in any way weakened by participants’ media multitasking habits. Means and standard deviations for each of the four interaction effects are revealed in Table 2 below.
Media multasking Not media multitasking
Narrative understanding M (SD) M (SD) High MMI 3.94 (.79) 4.38 (.60) Low MMI 3.62 (1.01) 4.23 (.89) Attentional focus High MMI 3.19 (.81) 4.26 (.91) Low MMI 3.59 (.88) 4.00 (1.13) Narrative presence High MMI 2.94 (.87) 3.36 (1.03) Low MMI 2.88 (.96) 3.57 (.80) Emotional engagement High MMI 3.62 (.88) 3.95 (1.02) Low MMI 3.22 (.83) 3.63 (.55)
Table 2: Interaction effect between Media multitasking and Media multitasking habits on the means and standard deviations for Narrative understanding, Attentional focus, Narrative presence, and Emotional engagement.
23 H4: Narrative engagement will be higher for emerging adults who are media
multitasking than older adults who are media multitasking.
For this hypothesis, first, only participants were selected that were in the experimental group. Next, four more ANOVA were conducted on each of the aspects of the narrative engagement scale. The first ANOVA of Age group on Narrative understanding revealed F(1, 46) = .024, p = .878, η² = .001, indicating a non-significant difference in narrative understanding between emerging adults (M = 3.74, SD = .96) that were media multitasking and older adults (M = 3.78, SD = .91) that were media multitasking. The second ANOVA of Age group on Attentional focus yielded F(1, 46) = 2.89, p = .096, η² = .059, revealing a non-significant difference in attentional focus between emerging adults (M = 3.21, SD = .91) and older adults (M = 3.63, SD = .78). The third ANOVA of Age group on Narrative presence was F(1, 46) = 1.12, p = .296, η² = .024. There was not a significant difference in narrative presence between media multitasking emerging adults (M = 3.04, SD = .77) and media multitasking older adults (M = 2.76, SD = 1.03). Finally, the fourth ANOVA of Age group on Emotional engagement revealed F(1, 46) = 5.068, p = .029, η² = .099, indicating a significant difference in emotional engagement between emerging adults who are media multitasking (M = 3.67, SD = .82) and older adults who are media multitasking (M = 3.13, SD = .84). Hypothesis 4 was partially rejected, as none of the effects were significant, except emotional engagement. Age group generally did not have an effect on one’s narrative engagement when media multitasking, except that older adults were less emotionally engaged than emerging adults who were media multitasking.
Other analyses
To test whether the fact that participants indicated that they had seen the short movie before influenced the results, the interaction effect between the variable Seen before and the experimental manipulation was examined. Four ANOVA were conducted for each of the Narrative engagement variables. The first ANOVA on Narrative understanding was F(1, 68) = 4.043, p = .048, η² = .056, indicating a significant interaction effect between whether participants had seen the short film before and their narrative understanding. Oddly enough, those who indicated that they had seen the short film before had lower mean scores on narrative understanding when not media multitasking but higher when media multitasking. The second ANOVA on Attentional focus revealed F(1, 68) = .546, p = .463, η² = .008, a non-significant interaction effect of whether participants had seen the short film before and
24 differences in their ability to focus on the screen for the experimental and control group. The third ANOVA on Narrative presence yielded F(1, 68) = .627, p = .431, η² = .009, revealing a non-significant interaction effect between having seen the short film before and differences in narrative presence between the groups. The final ANOVA on Emotional engagement was
F(1, 68) = .058, p = .810, η² = .001. There was not a significant interaction effect between
seeing the short film before and the experimental manipulation on emotional engagement. In sum, having seen the short film before did not make a difference in narrative engagement between the experimental and control groups, except in narrative understanding.
No hypothesis was devoted to Enjoyment, but for the overall knowledge on the subject, one ANOVA was conducted to test whether the experimental manipulation of media multitasking made a difference in participants’ enjoyment of the short film. Its’ results were
F(1, 70) = 3.028, p = .086, η² = .041, indicating a non-significant difference in enjoyment
25 Discussion
The present study examined whether narrative engagement with a short movie was lower for participants who were media multitasking, whether media multitasking habits could influence these results, and whether there were differences between the emerging adult age group and the regular adult age group. This was done by means of an experiment.
To answer the main research question: ‘To what extent is narrative engagement
affected by media multitasking when viewing entertainment media compared to when not media multitasking?’, narrative engagement with an immersive entertainment program was
lower when media multitasking was involved, compared to when there was no media multitasking, but the effect was less pronounced for emotional engagement. It was expected that narrative engagement would be lower, as most of the research on the topic of task switching, or multitasking, or media multitasking, had negative outcomes. For example, watching TV while doing homework decreased participants’ recognition of the TV content (Zhang, Jeong, & Fishbein, 2010), or reading and watching television simultaneously decreased the performance on the reading task (Lin, Robertson, & Lee, 2009). However, which of the cognitive processes is at play here remains to be determined. What can be concluded is that the switching back and forth between the short movie and smartphone made it harder for participants to understand the storyline, focus their attention, and be narratively immersed.
Unexpected was that the effect was only marginally significant for emotional
engagement. This could mean that participants’ emotional bonding experience with the story was less strongly influenced by getting pulled out of the story by another task. However, part of this can be explained by that the emotional impact only shined through at the very end of the film, where the scene cut to a hospital setting and everything fell into place. That was probably what strengthened emotional engagement with the characters, that may have been what made participants feel empathy. This is in line with the concept of valence
transformation (Oliver, 1993). What happens when films end sadly, is that the viewer can
appraise the sad emotion positively. It is also in accordance with the idea that people want to be moved by entertainment (Hanich et al., 2014). Finally, excitation transfer theory is a possible explanation for the marginally significant emotional engagement effect. Getting pulled away from the short film may not remove the emotions being felt, they may continue to be felt through the task switch. Apparently, emotions such as empathy are not influenced by media multitasking as strongly as suspected.
26 The first sub-question then examined: ‘Does the amount of media multitasking normally
engaged in moderate these results?’. Narrative engagement was not higher for participants
with more pronounced media multitasking habits, but again, emotional engagement was different. Emotional engagement with the short film was significantly higher for those who multitasked more in their life. This is in line with the trained attention hypothesis, where those who media multitask more in their daily life are better able to handle the different information streams (Alzahabi & Becker, 2013). However, when comparing this with the experimental manipulation, none of the effects were significant. This leaves the debate about the trained attention and scattered attention hypotheses wide open. It cannot be determined whether HMM’s are better at multisensory integration or that they are actually more distracted by external stimuli, as it did not make a difference in any way for media multitasking. This topic will need to be researched more extensively.
The second sub-question asked: ‘Are there differences between emerging adults and
regular adults?’. Age group did not influence one’s narrative engagement either, except that
emotional engagement was significantly lower for older adults than emerging adults. The other narrative engagement constructs were not significantly increased or reduced, leading us to think that age is not a main factor in most cases. However, it is interesting that emotional engagement produced a different result. Perhaps it’s only young people that are able to sufficiently task switch and still be emotionally invested. This is in line with the idea that younger people have had more training at media savviness (Prensky, 2001). It could also be that young people transfer excitation more strongly throughout stimuli.
One odd result was that not all people were paying attention to the screen for the full duration of the short movie, especially when not media multitasking. Either there were inner thoughts distracting them, or they were looking around the room. Age group did not seem to make a difference, but those who were not media multitasking seemed to be looking for distractions more. Apparently it is still difficult for people to pay complete attention to something. It could also mean the short film was not immersive enough in itself.
In conclusion, media multitasking does influence certain aspects of narrative
engagement, and whether people multitask often or their age does not seem to influence these results. However, emotional engagement seems to be a different construct entirely, and should be researched separately.
27 Limitations and future research
There are several limitations in this study give rise to future research. The most important limitation was the amount of participants. Next, the biggest limitations in the current study were situational factors, the MMI scale, the short movie itself, the narrative engagement scale, and finally, the survey. After that, new ideas for future research will be given based on the results of this study.
There were six conditions in the current study. For statistical significance, 180 participants were required, 30 in each condition. However, it was only possible to recruit 72 participants within the timeframe given. This will have had a considerable influence on the outcome of the study. Perhaps there is a significant difference between high media
multitaskers and low media multitaskers. Future endeavors would do well to find out.
The next three limitations are circumstance-related. First, participants viewed the short film on different screen sizes. Some participants watched on a regular television screen, for others there was a beamer available, and some could even only watch on a laptop screen. Larger screens lead to greater presence with footage that contains motion (IJsselsteijn, de Ridder, Freeman, Avons, & Bouwhuis, 2001). Very small screens lead to reduced immersion, but after a 13 inch screen and up the effect is less pronounced (Rigby et al., 2016).
Fortunately, no participant watched the short film on a screen smaller than 15 inches. Second, due to time-related factors, some participants were grouped together while others were not. This could have had a considerable influence on others’ narrative engagement. Third, due to not being in a lab, some other distractions would occur such as noises coming from outside. However, the above limitations could not be avoided because of a two-week data collection period. Any future research should eliminate these circumstances and try to replicate the results.
One of the other main limitations was that the MMI scale was lengthy and exhaustive. Participants perceived this scale with 72 items as long and boring, although this was already a shorter version than the original MMI scale. It may have been the case that participants started to ‘satisfice’, speeding through the survey, when they saw the amount of questions about the same subject. The quality and reliability of data can suffer from this. Scale reliability is decreased among weak satisficers, but increased for strong satisficers (Bargh & Gelbach, 2012). This can be explained by satisficers consistently ticking the same answers in the scale. Either way, it has an influence on results. Not only the length of the scale may cause issues, but the research surrounding MMI seems to be dated and needs to be updated to people’s ever
28 changing actual media use. For example, some participants commented after the research that they sometimes use three screens simultaneously.
Although the film did have a clear story arc, it only revealed its true colors at the very end. It was difficult to time the questions that the app needed to send would come through at the reveal of the show but before it was over. This could have considerably influenced participants’ emotional engagement. It would be wise to try to replicate the results with a different entertainment program.
It was odd that attempts to create the narrative engagement scale were unsuccessful. Either there are differences within the results or there are differences within the constructs. The narrative engagement scale needs to be meticulously tested in multiple settings.
Finally, there were two limitations because of the survey that was administered. A paper survey was used, due to its portability, ease of use for several age groups, and due to being administered to several participants at the same time. However, it is long known that electronic surveys get a better response than paper surveys (Kiesler & Sproull, 1986). Participants tend give answers that are less socially desirable in electronic surveys. Paper surveys are known to get less response because of the lack of anonymity
Another issue with the survey method was that it relied on self-report. When it comes to self-reporting, answers are subjective. For example, some participants rated their own level of English understanding a 10 and others a 6 when their actual level of understanding might be similar.
However, the research that was done increased our knowledge in the field of
entertainment and media multitasking. We now know that media multitasking takes a person out of a storyline and this has considerable implications for the entertainment industry. Creators of entertainment could look into how to avoid that people start to media multitask in the first place.
Future research should not only mind the limitations above, but also take note of what the results of this study suggest. Clearly, emotional engagement is not affected in the same way by media multitasking and media multitasking habits as the other narrative engagement constructs. Future endeavors should expand on the concepts of empathy and sympathy and what task switching does to them. The question remains whether residual emotion from entertainment is carried over across a task switch back to entertainment, or whether an unhampered emotional ending stays in our mind longer in terms of how we feel about the characters. This could translate to several conditions in another experiment. It is also still unclear which cognitive processes are at play when media multitasking influences the
29 cognitive aspects of narrative engagement. Brain activity scans done during the experiment would help explain residual emotions and cognitive aspects of media multitasking. In
addition, gender was left unexplored in this study, despite differences existing between males and females in terms of empathizing with characters (Oliver, Weaver, & Sargent, 2000).
When it comes to media multitasking, still more research needs to be done in relation to how we perceive media. Not just entertainment, not just narrative engagement, and not just adults or emerging adults, but we must broaden our view towards all walks of life. Perhaps even younger people such as teenagers respond differently to media multitasking. Perhaps media multitasking influences other aspects of daily life in a different way. It is crucial to find out.
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