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Running head: Personality and Second Screening
Accepted for publication
in Telematics and Informatics
Acceptance date: February 5th, 2020
Assessing Political Second Screening Behavior and Personality Traits: The Roles of Economic
Development, Freedom of Expression and Monochromatic vs. Polychromatic Cultures
Brigitte Huber a*, Homero Gil de Zúñiga a, b, James Liu c
a Department of Communication, MiLab, University of Vienna, Währinger Str. 29, A-1090
Vienna, Austria. E-mail address: brigitte.huber@univie.ac.at
b Facultad de Comunicación y Letras, Universidad Diego Portales, Vergara 240, Santiago,
Chile. E-mail address: homero.gil.de.zuniga@univie.ac.at
c School of Psychology, Massey University, Private Bag 102904, North Shore Auckland 0745,
New Zealand. E-mail Address: j.h.liu@massey.ac.nz
* Corresponding author. Tel.: +43-1-4277-493 68; eFax: +43-1-4277-8493 68. E-mail
address: brigitte.huber@univie.ac.at (B. Huber).
This research was supported by the Asian Office of Aerospace Research and
Development (Grant FA2386-15-1-0003). Responsibility for the information and views set out in
this study lies entirely with the authors.
PERSONALITY AND SECOND SCREENING
2
Highlights
• Two-wave panel data from 19 countries worldwide.
• Extraverted people tend to second screen more than introverts do.
• Agreeableness and openness are negatively related to second screening.
• Economic, political and cultural indicators explain differences between countries.
Abstract
This study focuses on an emerging media multitasking phenomenon called second screening or dual
screening. Employing two-wave panel-data from 19 countries, we test whether the Big Five
personality traits help explain the use of an additional screen or device while watching political
content on TV to discuss the program with others or to look up for additional information. Results
show that extraversion positively predicts political second screening. In contrast, agreeableness and
openness to new experience are negatively related to political second screening. Moreover,
multilevel analysis is performed to test whether the between-country variation is related to economic,
political and cultural indicators.
Keywords: personality traits, second screening, dual screen use, multitasking, social media,
cross-national research
PERSONALITY AND SECOND SCREENING
3
Assessing Political Second Screening Behavior and Personality Traits: The Roles of Economic
Development, Freedom of Expression and Monochromatic vs. Polychromatic Cultures
1. Introduction
Second screening or dual screening can be defined as a set of communicative practices in
which individuals use an additional ‘screen’ to go online while watching TV (Gil de Zúñiga et
al., 2015; Vaccari et al., 2015). In the literature, this emerging media multitasking practice is also
referred to as “multi-screening” (Dias, 2016) or “complementary simultaneous media use
(CSMU)” (Nee and Dozier, 2015). While there is a growing body of research investigating the
effects of media multitasking (e.g., Kazakova et al., 2015; Kononova et al., 2014) and
specifically of second screening (e.g., Barnidge et al., 2017; Houston et al., 2013; Lin and Yi-
Hsuan, 2017), less is known about the antecedents of second screening. Accordingly, we are
interested in investigating predictors of this behavior: Why do some people second screen while
watching TV? How do different individual personality traits drive this process?
People engage in second screening activities across different genres such as sports, sitcoms,
dramas, news, etc. Research has shown that news is one of the genres where people tend to
second screen most (Rubenking, 2016; Voorveld and Viswanathan, 2015). Moreover, studies
suggest that second screening while watching political content on TV has implications for
democracy due to its potential to increase people’s level of political participation (Lin and
Chiang, 2017; McGregor and Mourão, 2017). Ran et al. (2016) stress that researchers should pay
more attention to media multitasking during political news consumption. Hence, we decided to
focus on second screening activities during watching the news, political speeches or debates, and
during election coverage. We call this specific type of second screening “political second
PERSONALITY AND SECOND SCREENING
4
screening”, i.e. using an additional screen or device while watching political content on TV to
discuss the program with others or to look up for additional information.
Building on studies investigating personality traits as determinants of different kinds of
digital media use (e.g., Amichai-Hamburger and Vinitzky, 2010; Andreassen et al., 2013; Buckels
et al., 2014; Marshall et al., 2015; Correa et al., 2010; Russo and Amna, 2015; Ryan and Xenos,
2011; Seidmann, 2013), as well as of media multitasking (e.g., Becker et al., 2013; Cain et al., 2016;
Wang and Tchernev, 2012), the current study examines how the Big Five personality traits help
explain political second screening behavior.
There are several possibilities to investigate media multitasking behavior such as conducting a
questionnaire study (e.g., Duff et al., 2014; Jeong and Fishbein, 2007), a media diary study (e.g.,
Papper et al., 2004; Voorveld and Van der Goot, 2013), a laboratory experiment (e.g., Brasel and
Gips, 2011; Garaus et al., 2017), or video analysis (Rigby et al., 2017). Since our study aims to
investigate media multitasking behavior in different countries worldwide, we decided to use survey
data as a less time-consuming and resources-intensive approach than collecting observational data or
conducting experiments (for an overview of methods for studying media multitasking, see Segijn et
al., 2019).
What makes comparative research especially fruitful is its recognition of the relevance of
contextual conditions, i.e. the attempt to link macro-level system conditions and micro-level
variables (Esser, 2013). This study contributes to this kind of research by including macro-
variables (economic, political and cultural indicators) in order to explain differences between
countries.
PERSONALITY AND SECOND SCREENING
5
2. Literature review
2.1 Second screening as a media multitasking behavior
Already fifteen years ago, 26.5% of people in the US reported to regularly go online while
watching TV (Pilotta et al., 2004). In 2013, 46% of people in the US who have a smartphone and
43% of people with tablet reported to use these devices to go online during television
consumption every day (Nielsen, 2014). The Nielsen survey also provides an overview of
activities users engage with while watching TV ranging from looking up information in general
or surfing the web to further engage with the program watched on TV such as reading
conversations about the program on social network site, voting or sending comments to live
program. In our study, we focus on dual screen activities that are related to the content watched
on TV. Research on media multitasking reveals differences between genres in that people show
lower levels of multitasking while watching entertainment than while watching sports or the
news (Voorveld and Viswanathan, 2015). Following the work of Gil de Zúñiga et al. (2015), we
focus on media multitasking while watching the news, political speeches or debates, and during
election coverage.
In the literature, second screening is described as a media multitasking activity (Gottfried et
al., 2017). Theoretical approaches that help explain what happens when people perform multiple
tasks simultaneously are the multiple resource theory (Wickens, 2002) as well as thread
cognition (Salvucci and Taatgen, 2008). Their basic assumption is that people’s cognitive
capacity to process information is restricted. If two tasks are not using the same cognitive
resources, multiple tasks can be handled effectively (Wickens, 2002). However, if two tasks are
competing for the same resources, people are not able to perform both tasks at the same level and
have to decide how to interleave these tasks (David et al., 2013). Research on media multitasking
PERSONALITY AND SECOND SCREENING
6
shows that people use different strategies to allocate their attention between tasks; they do not
necessarily apply one fixed strategy but are rather flexible in how to prioritize attention between
tasks (Farmer et al., 2018). Hence, when it comes to second screening while watching political
content on TV, individuals might apply different strategies to allocate attention between the two
tasks: watching news on TV and using a smartphone or another device to go online. While some
will pay more attention to the content on TV, others will engage more in what is happening on
the “second” screen. While some people’s attention will shift back and forth continuously
between the two screens, others will show higher attention for one screen than for the other or
prefer longer slots per each screen (Ran et al., 2016).
Based on the model of media exposure (Webster et al., 2006), research distinguishes between
media factors and audience factors when investigating antecedents of media multitasking (Jeong
and Fishbein, 2007; Voorveld and Viswanathan, 2015). Media factors include media market,
technology availability, etc. (see chapter on macro variables below), and audience factors include
program type preferences, tastes, gratifications sought, etc. One set of audience factors are
related to demographics: Research found that younger people engage more often in media
simultaneously than older people do (Duff et al., 2014; Pilotta et al., 2004). This is also true for
second screening; research found that younger people tend to second screen more often than
older people do (Barnidge et al., 2019; Gil de Zúñiga and Liu, 2017). Additionally, highly
educated people show higher levels of multitasking (Hwang et al., 2014). While in general,
females are more likely to engage highly in media multitasking activities (Duff et al., 2014),
when it comes to media multitasking during news use, males are more likely to multitask
(Hwang et al., 2014).
PERSONALITY AND SECOND SCREENING
7
Additionally, personality traits have become a fruitful framework for predicting media
multitasking (e.g., Becker et al., 2013; Chang, 2017; Cain et al., 2016; Loh and Kanai, 2014; Wang
and Tchernev, 2012). More specifically, research has linked personality traits to multitasking
preference and multitasking behavior. One way of measuring multitasking preference is the
Multitasking Preference Inventory (MPI). It assesses “an individual’s preference for shifting
attention among ongoing tasks, rather than focusing on one task until completion and then
switching to another task” (Poposki and Oswald, 2010, p. 250). As a meta-study reveals the Big
Five can help explain individual’s multitasking preference (Sanderson, 2012). For instance,
people who prefer multitasking show high levels of sociability – a characteristic of the Big Five
dimension extraversion (Mesmer-Magnus et al., 2014). Studies that investigate the relationship
between the Big Five and actual multitasking behavior show similar results. One widely used
measurement for assessing media multitasking behavior is the Media Multitasking Index (MMI).
It is a questionnaire-based index introduced by Ophir et al. (2009) that captures the number of
media a person simultaneously uses when consuming media. The index is used to identify heavy
vs. light media multitaskers. Recent research using a naturalistic field study has shown that the
MMI is a good predictor of actual media multitasking behavior (Rigby et al., 2017).
Drawing on results from these lines of research, in the following we theorize about the
relationship between personality traits and second screening as a specific type of media
multitasking. In addition, we refer to research on personality traits and different kinds of online
behavior that can be part of second screening activities, such as social media use (Andreassen et
al., 2013; Correa et al., 2010; Ryan and Xenos, 2011; Seidmann, 2013), posting comments online
(Buckels, et al., 2014), or online political engagement (Russo and Amna, 2015).
PERSONALITY AND SECOND SCREENING
8
2.2 Personality and second screening
There are different ways to classify personality traits; one that is often used is the five-factor
theory of personality (McCrae and John, 1992; McCrae and Costa, 1999). The five personality traits -
also known as the Big Five - are: extraversion, agreeableness, conscientiousness, emotional stability
(opposite = neuroticism), and openness to new experience.
The first personality trait is extraversion. Extroverted people are active, assertive, energetic,
enthusiastic, outgoing, and talkative (McCrae and John, 1992). They have high social skills and
numerous friendships (McCrae and Costa, 1999). Research suggests that extraversion is positively
related to social media use (Annisette and Lafreniere, 2017; Correa et al., 2010; Hong et al, 2014;
Ryan and Xenos, 2011; Seidmann, 2013; Tan and Yang, 2014). Research distinguishing between
different motives for using social network sites reveals that extraversion significantly predicts the
motivation of new connections (Orchard et al., 2014). Extraversion is generally associated with more
frequent political talk (Mondak et al. 2010). Since one motivation to dual screen is to further discuss
with others in their social networks issues about the program individuals watch, it stands to reason
personality traits may also explain this behavior. Finally, research shows a positive relationship
between extraversion and media multitasking activities (Loh and Kanai, 2014).
Building on these findings and given the positive link that has been established for extraversion
and other communication practices where people interact online, we formulate the following
hypothesis1:
H1. Extraversion will be positively associated with political second screening.
The next trait is agreeableness. Agreeable people are appreciative, trust others and are generous
and kind (McCrae and John, 1992). They prefer using inoffensive language and believe in
cooperation (McCrae and Costa, 1999). Since agreeable persons are good team players and value
PERSONALITY AND SECOND SCREENING
9
others, they might like engaging in conversations with others online (Mark and Ganzach, 2014).
However, empirical findings show that less agreeable individuals tend to be higher users of the
internet (Andreassen et al., 2013; Landers and Lounsbery, 2006), are more likely to post comments
online and discuss politics online (Russo and Amna, 2015) as well as to troll online (Buckels et al.,
2014). One reason might be that people scoring high on agreeableness try to avoid conflicts and
hostile comments (Barnes et al., 2017). While reason-based conversations might attract agreeable
persons, interactions entailing incivility might discourage them to discuss the program with others.
Hence, both directions seem plausible. Research investigating specifically media multitasking found
no relationship between MMM (media-media multitasking) and agreeableness (Shih, 2013).
Also, for conscientiousness research shows no clear pattern. Conscientious people are efficient,
reliable, responsible, and thorough (McCrae and John, 1992). They like planning and organizing
(McCrae and Costa, 1999). In general, they feel less comfortable in situations that require
multitasking (Mesmer-Magnus et al., 2014). Conscientious people may not spend that much time
online to avoid procrastination or distraction from their daily tasks (Ross et al., 2009). However,
empirical findings regarding conscientiousness and online behavior are limited and inconsistent
(Barnes et al., 2017, p. 567). Recent research shows that less conscientious people use Facebook
more often (Eşkisu et al., 2017) and engage in posting on online news comments more often (Wu
and Atkin, 2017). Other studies found that more conscientious people use Twitter for information
(Hughes et al., 2012) as well as internet for academic purposes (Landers and Lounsbery, 2006) more
often. Finally, research found no association between conscientiousness and media multitasking
(Cain et al., 2016). When it comes to second screening, different scenarios are possible: While
conscientious people may go online while watching the news in order to search for additional
information, check for facts, or discuss with others, they may avoid doing so if it distracts them from
PERSONALITY AND SECOND SCREENING
10
paying close attention to a political debate where a person wants to make sure s/he understand all
the issues thoroughly.
Also the findings for emotional stability are mixed. The opposite of emotional stability is
neuroticism. Neurotic people are anxious, unstable, and worrying (McCrae and John, 1992). They
tend to be pessimistic, show lower levels of self-esteem, and have high perfectionistic beliefs
(McCrae and Costa, 1999). Neurotics use the internet in search of a sense of belonging and social
support (Amichai-Hamburger and Ben-Artzi, 2000). Prior research shows that neuroticism
positively predicts media multitasking (Wang and Tchernev, 2012), social media use (Correa et al.,
2010; Hong et al, 2014; Tan and Yang, 2014) and Facebook informational use (Hughes et al., 2012),
but negatively predicts sharing content online (Hunt and Langstedt, 2014), Twitter use for
informational purposes (Hughes et al, 2012) as well as engaging in online political engagement on
Facebook (Quintelier and Theocharis, 2012). Finally, emotional stability is not a predictor of
commenting online news (Wu and Atkin, 2017). Accordingly, neurotic people might avoid going
online and discuss with others while watching the news, as they might not like to engage in
confrontational conversations about politics because they get easily upset. On the other hand,
neurotic people might seek to interact with others that consume the same program as this might also
create a sense of belonging.
The last personality trait is openness to new experience. Open people like new things and
changes (McCrae and Costa, 1999). They have many different interests and are curious to learn more
about the world around them (McCrae and John, 1992). Prior research shows that open people show
higher levels of social media use (Correa et al, 2010), online political participation and activities
(Jordan et al., 2015; Russo and Amna, 2015), and Facebook use for news and information (Ryan and
Xenos, 2011). This might also be true for second screening: People scoring high on openness might
PERSONALITY AND SECOND SCREENING
11
like to use an additional device while watching politics on TV to learn about different viewpoints and
ideas on a topic related to the program. They might also do so to get in contact with others and
coordinate for engaging in political activities – as research suggests that people open to new
experience engage in politics such as protest behavior more often than people scoring low on this
trait (Opp and Brandstätter, 2010). On the other hand, other studies did not find significant
association between being open and using Facebook (Moore and Elroy, 2012) or posting on online
news comments sections (Wu and Atkin, 2017). As commenting on online news is very similar to
commenting on topics related to a political program on TV, this could also be true for second
screening.
Since for the last four mentioned personality traits research shows no clear pattern, we pose the
following set of research questions:
RQ1. How do agreeableness (RQ1a), conscientiousness (RQ1b), emotional stability (RQ1c)
and openness to new experiences (RQ1d) relate to political second screening?
2.3 Cross-national comparison: Economic development, freedom of expression and
monochromatic/polychromatic cultures
Recent research has shown that political second screening behavior differs between
countries. For instance, political second screening is more common in Brazil than in the US
(McGregor et al., 2017). What might help explain differences between countries? As mentioned
above, when investigating antecedents of media multitasking behavior, not only individual
factors but also macro level factors are relevant to look at (Jeong and Fishbein, 2007; Voorveld
and Viswanathan, 2015). More specifically, at least the following three indicators should be
considered when investigating media multitasking behavior from a comparative perspective
(Kononova et al., 2014): economic, political and cultural indicators.
PERSONALITY AND SECOND SCREENING
12
Second screening behavior is technologically dependent, and users need to access to the
internet on portable devices (Nee and Dozier, 2017). Hence, the economic development of a
country might influence the second screening behavior of individuals as economically higher
developed countries will be able to provide better infrastructure (Grupp, 1995), and GDP has
been shown to positively influence media ownership, i.e., residents in high GDP countries will
have more resources to buy new media devices (Kononova et al., 2014). GDP is a widely used
indicator to measure the economic development of a country. Accordingly, we include GDP as a
context-level variable in our analysis. We test whether or not individuals in high GDP countries
will be more likely to second screen than individuals in countries with low GDP.
Beside the economic development of a country, also its political development might be of
relevance when investigating media multitasking behavior. More specifically, in countries where
information can circulate more freely, individuals may have more content options to multitask
with (Kononova et al., 2014). Hence, we assume that countries where journalists and citizens are
more free to express themselves, individuals second screen more. Accordingly, we include the V-
dem freedom of expression index in our study. The index is provided by the “Varities of
Democracy”-Institute, an independent research institute based at the Department of Political
Science at the University of Gothenburg in Sweden (for more details, see Coppedge et al., 2016).
Finally, also cultural indicators might provide a better understanding of second screening
behavior in different societies. According to Hall (1983), not all individuals do have the same
orientation toward time. While individuals in some cultures organize their lives around time,
emphasize schedules and prefer doing one thing at a time (monochronic), individuals in other
cultures are more concerned on the present moment than with schedules and prefer doing many
PERSONALITY AND SECOND SCREENING
13
things at once (polychronic). Not surprisingly, research found a positive relationship between
polychronicity and frequency of media multitasking (Srivastava et al., 2016).
As we are interested in assessing whether these three macro variables – the economic,
political and cultural indicator – may help explain differences between countries, we formulate
the following hypotheses:
H2. Individuals in countries with high GDP (H2a), high levels of freedom of expression
(H2b) and polychronic orientation (H2c) tend to second screen politics more.
Comparative research is especially fruitful when macro-level system conditions and micro-
level variables are linked to each other (Esser, 2013). Hence, besides testing the direct relationship
between macro-variables and second screening behavior, we are also interested to investigate
whether individual-level variables and macro-variables may interact to explain political second
screening behavior. More specifically, we want to explore whether the relationship between the Big
Five and political second screening activities may differ between countries with different economic,
political and cultural context. Accordingly, we pose the following research questions:
RQ2. Are there cross-level interactions between personality traits and the macro variables
GDP (RQ2a), freedom of expression (RQ2b) and monochronicity/polychronicity (RQ2c)
that affect political second screening?
3. Method
Prior research has used an array of different methods to investigate media multitasking
behavior (for an overview, see Segijn et al., 2019). To test our hypotheses and answer our research
question, we conducted an online survey in 19 countries worldwide.
3.1 Sample and data
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14
The study at hand is part of a larger international project (Digital Influence). Hence, it uses
data from a larger data set where other research has been published (Gil de Zúñiga et al., 2017;
Barnidge et al., 2018). Data have been collected in 19 countries worldwide (see Table 1). It is a
two-wave panel study: The first wave of the study was fielded online in September 2015, and the
second wave of the study in February/March 2016. A large group of scholars translated the items
for each country. Afterwards, scholars have translated the answers back into English. The survey
was distributed by Nielsen, which curates a worldwide online panel with more than 10 million
potential participants. Nielsen used stratified quota sampling techniques. The aim was to create
samples in each country with demographics similar to those provided in reports of official census
agencies (see Callegaro et al., 2014). The sample size in Wave 1 is 20,361 and the sample size in
Wave 2 is 8,708. For more details on the survey and a demographic breakdown by country see
Gil de Zúñiga et al. (2017).
3.2 Measures
3.2.1 Political second screening
The dependent variable in the analysis is political second screening, i.e., using an additional
screen (e.g., tablet or smartphone) while watching political content on TV to access the Internet
or a social media to get more information or to talk about the program. Survey respondents were
asked how often (1= never; 7 = all the time) they second screen a) while watching political
speeches or debates, b) while watching the news, and c) while following election coverage. The
items were averaged (W1 Cronbach’s alpha (α) = .92, M = 3.1, SD =1.73; W2 α = .93, M = 2.88,
SD =1.73).
The independent variables in this study are the personality traits. They have been measured
based on prior instruments (Costa and McCrae, 1992; Gosling et al., 2003; Greaves et al., 2015;
PERSONALITY AND SECOND SCREENING
15
John and Srivastava, 1999). All items are measured on a seven-point scale (1= strongly disagree;
7 = strongly agree):
3.2.2 Extraversion
We asked individuals how much they agree or disagree with the following statement: like to
start conversations, don’t like to speak in front of groups (recoded), comfortable introducing
themselves to new people, being shy around strangers (recoded), speak to a lot of different
people at events, and have difficulties to approach to others (recoded). The items were averaged
(α = .81, M= 4.23, SD = 1.23).
3.2.3 Agreeableness
We asked individuals how much they sympathize with others’ feelings, whether or not they
feel little concern for others (recoded), to what extend they are indifferent to others’ feelings
(recoded), if they love children, if they try their best to comfort others, and if they find it
tiresome when others ask for help (recoded) (α = .75, M= 5.1, SD = .99).
3.2.4 Conscientiousness
We wanted to know whether or not people get chores done right away, if they don’t like to
pay attention to detail (recoded), if they like order, to what extend they do things according to a
plan, if they are always prepared, if they like making plans and stick to it (α = .72, M= 4.76, SD
= .93).
3.2.5 Emotional stability
This construct captures people’s level of emotional and sensitive equilibrium and steadiness.
We asked people about frequent mood swings (recoded), getting upset easily (recoded), being
obsess over problems (recoded), rarely getting irritated’, don’t getting upset when problems
arise, and being calm most of the time (α = .72, M= 4.33, SD = 1.04).
PERSONALITY AND SECOND SCREENING
16
3.2.6 Openness to new experiences
This index assesses people’s willingness to try new things and live new experiences. The
following statements were used: having difficulty imagining things (recoded), not being
interested in new ideas (recoded), do not like to try new things (recoded), being full of ideas,
taking a long time to learn anything new (recoded), and being quick to understand (α = .70, M=
4.98, SD = .96).
3.2.7 Controls
Additionally, the study includes political interest, political discussion, news use variables,
and demographics as controls. We used two items to measure political interest. We measured
people’s attention to information about what is going on in politics and their levels of interest in
about what is going on in politics (Spearman-Brown Coefficient = .94, M = 4.52, SD = 1.45). To
measure political discussion, respondents were asked how often they talk with weak ties
(acquaintances, strangers) and strong ties (spose/partner, family/friends) about politics online and
face to face. The eight items were averaged (α = .88, M = 2.91, SD = 1.27). Respondents’ social
media news use was measured based on prior research (Gil de Zúñiga et al., 2012; Valenzuela et
al., 2012). We asked how often respondents use social media to get news, stay informed about
current events and public affairs, get news about their local communities, and get news about
current events from mainstream media (α = .87, M = 4.27, SD = 1.51). To measure traditional
news use, individuals were asked how often they get news from TV, newspapers (printed
version), and radio (α = .60, M = 4.52, SD = 1.32). Since general social media use has also found
to be related to the Big Five, we included it as control. We asked respondents how often they use
“social media” and “instant messaging”. The two items were averaged (Spearman-Brown
coefficient = .63, M = 4.82, SD = 1.53). Moreover, we included the following demographics as
PERSONALITY AND SECOND SCREENING
17
controls in our analysis: Age (M = 41, SD = 14.64), gender (51% female), education (measured
on an eight-point scale where 1 = none and 7 = post-graduate degree; M = 4.34, SD = 1.30),
income (annual household income, M = 2.94, SD = 1.1), and ethnicity or race (86% majority).
3.2.8 Country-level measures
GDP per capita (in thousand) per country was collected from the website of the World Bank
(M = 21.59, SD = 15.82) and ranges from 2 (Ukraine) to 57 (USA). The values for the freedom of
expression index were taken directly from the Vdem website www.v-dem.net (see Coppedge et
al., 2016). The index is based on nine indicators, namely government censorship effort media,
harassment of journalists, media self-censorship, freedom of discussion for men, freedom of
discussion for women, freedom of academic and cultural expression, media bias, print/broadcast
media critical, and print/broadcast-media perspectives). The index (M = 0.82, SD = .22) ranges
from 0.25 (China) to 0.99 (UK). Monochronicity/Polychronicity: based on the categorization by
Morden (1999) and O’Brien (2016), each country was assigned to one of the two types of
cultures in regard to their orientation toward time (0 = monochron culture; 1 = polychron
culture).
3.3 Analysis
First, one-sample t-tests were used to show how each country differs from the grand means
for political second screening. Second, hierarchical OLS regressions were used to test the first set
of hypotheses and research questions. The models include cross-sectional, lagged, and
autoregressive regressions using SPSS. While cross-sectional data do not allow for causal
inferences, this study relies on two-wave panel data and includes respondent’s prior scores on the
dependent variable in an autoregressive association in order to better deal with issues of
endogeneity and causal inference (for more details see, e.g., Greenberg, 2008; Kleinnijenhuis,
PERSONALITY AND SECOND SCREENING
18
2016). While the cross-sectional model includes the independent and dependent variables from
Wave 1, the lagged model includes the independent variables from Wave 1 and the dependent
variable from Wave 2, and the autoregressive model includes the independent variables from
Wave 1, the dependent from Wave 2 and also the dependent variable from Wave 1 as
autoregressive term. Finally, multi-level models and cross-level interactions were conducted
using R to test whether the macro-variable helps explaining differences between countries.
4. Results
4.1 Overview of political second screening behavior in different countries
One-sample t-tests were first conducted to assess each country’s difference with the overall
sample in terms of mean levels of second screening behavior2 (M = 3.1, SD = 1.73). Results are
summarized in Table 1. Results show that people in Turkey, China, Brazil, Indonesia, Taiwan,
Philippines, and Japan tend to second screen more while people in Germany, New Zealand,
USA, Russia, UK, Poland, Ukraine, and Estonia tend to second screen less.
[Table 1 about here]
4.2 Personality traits predicting political second screening
Next, we run regression models testing the effect of our control variables and personality
traits on political second screening. Results in Table 2 support H1. Extraversion at time 1 is a
positive predictor of political second screening in all three models: Cross-sectional model
(ß=.045, p<.001), the lagged model (ß=.047, p<.001), and the autoregressive model (ß=.028,
p<.05). Agreeableness (RQ1a) is negatively associated with political second screening in all
three models: People that show lower levels of agreeableness are more likely to second
screening.
[Table 2 about here]
PERSONALITY AND SECOND SCREENING
19
Additionally, results in Table 2 indicate that neither conscientiousness (RQ1b), nor emotional
stability (RQ1c) predicts political second screening, but openness to new experiences does
(RQ1d). More specifically, openness to new experiences at time 1 negatively predicts political
second screening in all three models: Cross-sectional model (ß= -.083, p<.001), the lagged model
(ß=-.058, p<.001), and the autoregressive model (ß= -.025, p<.05). That is, people less open to
new experiences tend to second screen more.
[Table 3 about here]
4.3 Comparative results
Finally, we were interested to test whether macro-variables help explain differences between
countries. First, results show that a model with a random intercept (i.e., a model with no
predictors and a random intercept) is a better fit (Log Likelihood = -38867.31) than a model with
a fixed intercept (Log Likelihood = -39791.40). That is, without accounting for the predictors,
mean levels of political second screening vary from country to country. About 5% of the
variance in political second screening is due to country differences (ICC = .053). Table 3 shows
the full model including individual-level variables, macro-level variables, and the cross-level
interactions. We expected individuals in countries with high GDP (H2a), high levels of freedom
of expression (H2b) and polychronic orientation (H2c) to show higher levels of political second
screening behavior. Results in Table 3 show that none of the three macro-level variables is
directly related to second screening. However, when it comes to the cross-level interactions the
country variables do matter. More specifically, we were interested to explore whether there are
cross-level interactions between personality traits and the macro variables GDP (RQ2a), freedom
of expression (RQ2b) and monochronicity/polychronicity (RQ2c) that affect second screening.
PERSONALITY AND SECOND SCREENING
20
Results suggest that there are significant interaction effects for extraversion and GDP, for
agreeableness and freedom of expression, for conscientiousness and freedom of expression, and
for conscientiousness and monochronicity/polychronicity.
[Figure 1 about here]
Figure 1 shows that the positive relationship between extraversion and political second
screening is the strongest in countries with low GDP. Figure 2 shows that the negative
relationship between agreeableness and political second screening is the strongest in countries
with high freedom of expression.
[Figure 2 about here]
Figure 3 illustrates the positive relationship between conscientiousness and political second
screening to be the strongest in countries with high freedom of expression. Finally, Figure 4
shows the positive relationship between conscientiousness and political second screening in
polychron cultures (right panel).
[Figure 3 about here]
[Figure 4 about here]
5. Discussion
Media multitasking is a common phenomenon worldwide. We tested whether personality
traits help explain a specific type of media multitasking behavior - second screening politics -
across 19 societies from all continents. Our results show that three of the five personality traits
included in the analysis are statistically significant predictors of political second screening in the
pooled sample. Political second screeners can be characterized as follows: First, our results
suggest that extraverted people are more likely to engage in second screening while consuming
PERSONALITY AND SECOND SCREENING
21
news and political debates. This makes perfect sense as one reason to second screening politics is
discussing with others. Second, agreeableness people are less likely to second screen. One
possible explanation for this might be that these individuals want to avoid conflicts and hostile
comments (Barnes et al., 2017). More specific, when engaging in second screening behavior,
people are very likely to encounter some kind of counter-attitudinal information. For example,
people in look for additional information online might be exposed to diverse viewpoints while
following user comments related to a political debate on TV or by reading hate comments on
social media. Moreover, one common practice of second screening is engaging in discussion
with others, which allows for politically “uncomfortable” conversations. Hence, agreeableness
people are likely to avoid all these second screening situations. Finally, our results indicate that
people scoring high on openness, are less likely to second screen. At first glance, this result
might be surprising as second screening is a relatively new communication practice and one
would expect open people to engage to this new communication practice. However, one possible
explanation might be that while open people - due to their manifold hobbies and interests - have
a lot of face-to-face contacts to discuss with, connecting with others and getting feedback have
found to be important motives for less open people to engage in online commenting (Wu and
Atkin, 2017).
These findings have important implications for our understanding of how to foster
democracy. While in general second screening about politics and public affairs is discussed to be
beneficial for democracy given its potential to increase political participation (Lin and Chiang,
2017; McGregor and Mourão, 2017), our findings imply that this new form of engaging with
politics is not evenly appealing for people with certain personality traits. Digital media might
help introverted people to partake of political behavior online (see social compensation theory,
PERSONALITY AND SECOND SCREENING
22
McKenna & Bargh, 1998; Kim et al., 2013). For instance, social media has helped introverted
people to discuss political issues more frequently (Kim et al., 2013). However, when it
particularly relates to second screening this premise does not completely hold true. It is
extraverted people who are more likely to second screen – a finding that speaks toward a “rich
get richer” model (Kraut et al., 2002). Hence, there is a need to provide digital spaces for
engaging with politics that attract people who are not feeling that comfortable interacting with
others. One important factor to be addressed in this context is the diversity of online discourse
participants. Prior research shows that only 14% of online news users comment on news;
compared to those who read news but do not comment, they tend to often be male, are less
educated, and belong to lower-income groups (Stroud, Duyn and Peacock, 2016). So, one
challenge for democracy is to find a way of enabling more diverse and inclusive discourses in the
online public sphere. Another challenge is to better deal with hate speech since hate speech
might be one decisive factor that detracts agreeable persons from engaging in second screening
activities.
Finally, our results show that economic, political and cultural indicators help explaining
differences between countries. More specifically, the positive relationship between extraversion
and second screening is the strongest in countries with low GDP. That is, individuals tend to
second screen more if they are extroverted and this is especially true in less economically
developed countries. Moreover, the negative relationship between agreeableness and second
screening is the strongest in countries with high levels of freedom of expression. In countries
where individuals are free to express themselves, less agreeable people take advantage of the
opportunity to use and additional device while watching politics on TV to discuss the program
with others. However, this finding has also a downside: In countries where individuals are less
PERSONALITY AND SECOND SCREENING
23
free to express themselves, even less agreeable individuals who are not afraid of conflicting
situations do not benefit from the possibility to digitally further engage with the content watched
on TV. It might be that they prefer to do so face-to-face because online conversations might be
traceable.
5.1. Limitations and future directions
These conclusions are limited in certain ways. First, one should consider that our
measurement of political second screening did not differentiate between various forms of
political second screening, e.g., second screening for information purposes or second screening
for discussing with others. Future studies should distinguish between these and further motives
for second screening and explore how personality traits are related to them. Second, media
multitasking behavior can never be fully assessed by using self-reported data. For instance,
asking respondents if they use an additional device while watching TV does not allow to capture
details such as whether or not the TV is blurring into the background and they stop following the
content on TV (Rigby et al., 2017). Moreover, individuals tend to underestimate the extent to
which they media multitask (Voorveld and Viswanathan, 2015). Hence, observational data is
needed to measure political second screening behavior more precisely and to better understand
specific facets of political second screening behavior. Scholars could also try to combine self-
reports and registration data (de Vreese and Neijens, 2016). Moreover, while investigating the
direct effect of personality traits on dual screening was a first important step in exploring this
relationship, further research investigating also indirect paths is needed to provide a more
nuanced understanding of the way personality traits affect second screening behavior. Another
limitation is the use of controls in this study. While we were able to control for an array of
important antecedents of second screening behavior such as media habits, political antecedents,
PERSONALITY AND SECOND SCREENING
24
general frequency of social media use, etc; we did not measure general media multitasking
frequency in our survey. However, this would be an important control since the Big Five have
shown to be related to the general media multitasking frequency. Accordingly, future studies
should consider this general media multitasking variable when investigating a specific media
multitasking behavior. Finally, we made an important first step in exploring the role of macro
variables for explaining second screening behavior in different countries worldwide. Future
studies should include additional macro-level factors in order to better understand how the
context of a country might influence second screening behavior.
5.2 Conclusions
Despite these limitations, our results help to explain why some people tend to use an additional
device to go online while watching politics on TV whereas others do not. More specifically, while
extraversion positively predicts political dual screening, the opposite is true for agreeableness
and openness. In addition, results suggest that combining personality traits as individual-level
variables and economic, political and cultural indicators as macro-level variables is a fruitful
approach. By delivering first important insights on the antecedents of political second screening
worldwide, this study provides a solid basis for the further investigation of this rising
communication practice.
Notes
1 Whenever prior research allows formulating specific expectations regarding the relationship of
the variables, we put a hypothesis. In the case of lacking theoretical expectation and/or due to
mixed empirical findings, we pose a research question.
PERSONALITY AND SECOND SCREENING
25
2 Using the grand mean is common in comparative research when investigating differences
between countries (e.g., Gainous, Wagner and Gray, 2016; Gil de Zúñiga et al, 2019). Following
this strand of literature, we decided to calculate the grand mean. However, another possibility is
to calculate a one-way ANOVA with country as the independent variable and political second
screening as the dependent variable. Results show that there are statistically significant
differences between group means (F(18, 20235) = 114.003, p = .001)).
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Table 1
Tests of Mean Differences between Country Mean and the Grand Mean for Second Screening
Second Screening
Country
M (SD)
t (df)
Argentina
3.14 (1.84)
0.76 (1139)
Brazil
3.80 (1.66) +
13.77 (1077)***
China
3.92 (1.42) +
18.34 (1001)***
Estonia
2.85 (1.62) -
-5.20 (1162)***
Germany
2.35 (1.67) -
-14.53 (1048)***
Indonesia
3.55 (1.57) +
9.37 (1072)***
Italy
3.06 (1.73)
-.77 (1035)
Japan
3.49 (1.60) +
7.58 (969)***
Korea
3.17 (1.55)
1.29 (941)
New Zealand
2.41 (1.66) -
-14.07 (1154)***
Philippines
3.49 (1.54) +
8.21 (1044)***
Poland
2.64 (1.64) -
-9.08 (1054)***
Russia
2.58 (1.63) -
-10.75 (1140)***
Spain
3.27 (1.75)
3.13 (1017)**
Taiwan
3.53 (1.66) +
8.29 (1005)***
Turkey
4.12 (1.47) +
21.50 (948)***
Ukraine
2.80 (1.60) -
-6.50 (1213)***
United Kingdom
2.54 (1.80) -
-10.10 (1058)**
United States
2.48 (1.75) -
-12.02 (1158)***
Notes. Cell entries are means (M), standard deviations (SD), test statistics (t) and degrees
freedom (df) from one-sample t-tests assessing the difference between each country mean and
the grand mean for second screening (M = 3.10, SD = 1.73). Significance values are indicated as
follows: *p < .05; ** p < .01; *** p < .001 (two-tailed tests). + or – signs denote whether the
difference with the grand mean in a positive or a negative one.
PERSONALITY AND SECOND SCREENING
38
Table 2
Cross-sectional, Lagged, and Autoregressive Regression Models Testing Personality Traits over
Second Screening (19 countries)
Second
ScreeningW1
(Cross-sectional)
Second
ScreeningW2
(Lagged)
Second
ScreeningW2
(Autoregressive)
Block1: Demographics
Age
-.137***
-.185***
-.131***
Gender (Female=1)
-.037***
-.032**
-.015
Education
-.020**
.027*
-.016
Income
.021**
.028**
.019
Race (Majority=1)
-.018**
-.011
.000
ΔR2
7.1%
8.8%
8.8%
Block 2: Political Antecedents
Political InterestW1
.063***
.046***
.029*
Political DiscussionW1
.234***
.172***
.086***
ΔR2
13.6%
8.3%
8.2%
Block 3: Media Use
Traditional News UseW1
.027***
.036**
.029**
Social Media News UseW1
.228***
.176***
.086***
Frequency of Social Media
Use
.051***
.070***
.045**
ΔR2
4.7%
3.8%
3.8%
Block 4: Autoregressive Term
Second ScreeningW1
─
─
.383***
ΔR2
11.5%
Block 5: Personality Traits
ExtraversionW1
.043***
0.46***
.027*
AgreeablenessW1
-.088***
-0.92***
-.061***
ConscientiousnessW1
-.007
.012
.017
Emotional StabilityW1
-.006
-.015
-.011
OpennessW1
-.085***
-.061***
-.027*
ΔR2
1.8%
1.3%
0.4%
Total R2
27.0%
22.0%
32.7%
Note. Cell entries are final-entry ordinary least squares (OLS) standardized coefficients (β).
* p < .05; ** p < .01; *** p < .001. Ncross = 16,277; Nlagged / auto = 6,915.
PERSONALITY AND SECOND SCREENING
39
Table 3
Multi-level models and cross-level interactions predicting second screening
Second Screening
b(se)
Individual Level Indicators
Age
-.018 (.001)***
-.018 (.001)***
Gender (Female=1)
-.123 (.024)***
-.119 (.024)***
Education
.021 (.010)*
.020 (.010)*
Income
.026 (.011)*
.027 (.011)*
Race (Majority=1)
-.103 (.035)**
-.107 (.035)**
Political Interest
.055 (.010)***
.055 (.010)***
Political Discussion
.360 (.011)***
.355 (.011)***
Traditional News Use
.065 (.010)***
.067 (.010)***
Social Media News Use
.242 (.012)***
.241 (.012)***
Frequency of Social Media Use
.062 (012)***
.063 (.012)***
Extraversion
.046 (.011)***
.050 (.011)***
Agreeableness
-.096 (.015)***
-.096 (.015)***
Conscientiousness
.003 (.015)
.006 (.015)
Emotional Stability
-.002 (.013)
-.003 (.013)
Openness
-.113 (.015)***
-.116 (.016)***
Country-Level Predictor
GDP
.011 (.007)
.011 (.007)
Freedom of Expression
-.550 (.421)
-.568 (.422)
Mono-/Polychronicity
.032 (.222)
.042 (.223)
Cross-Level Interactions
Extraversion * GDP
-.002 (.001)*
Agreeableness * GDP
.001 (.001)
Conscientiousness * GDP
-.000 (.001)
Emotional Stability * GDP
.001 (.001)
Openness * GDP
.002 (.001)
Extraversion * Freedom Ex.
.040 (.063)
Agreeableness * Freedom Ex.
-.199 (.077)**
Conscientiousness * Freedom Ex.
.219 (.078)**
Emotional Stability * Freedom Ex.
-.072 (.069)
Openness * Freedom Ex.
.002 (.081)
Extraversion * Mono/Poly
-.002 (.033)
Agreeableness * Mono/Poly
.015 (.042)
Conscientiousness * Mono/Poly
.151 (.043)***
Emotional Stability* Mono/Poly
-.032 (.035)
Openness * Mono/Poly
-.066 (.045)
Var. of Random Comp. (SD)
Variance Within Country
2.04 (1.43)
2.04 (1.43)
Variance Between Country
.12 (.34)
.12 (.34)
Log Likelihood
-28939.83
-28915.66
Note: Ncross = 16,277. *p < .05; ** p < .01; *** p < .001. Predictors and dependent variables centered to the
grand mean. Based on 19 groups. Table shows results from cross-sectional model; results from lagged and
autoregressive models (Nlagged / auto = 6,915) are not shown in the table as the cross-level interactions were no
longer significant.
PERSONALITY AND SECOND SCREENING
40
Figure 1. Cross-level interaction between extraversion and GDP as estimated by the model in
Table 3. Charts represent the effect for extraversion on second screening at the 10th, 50th, and
90th quantiles of the moderator.
PERSONALITY AND SECOND SCREENING
41
Figure 2. Cross-level interaction between agreeableness and freedom of expression as estimated
by the model in Table 3. Charts represent the effect for agreeableness on second screening at the
10th, 50th, and 90th quantiles of the moderator.
PERSONALITY AND SECOND SCREENING
42
Figure 3. Cross-level interaction between conscientiousness and freedom of expression as
estimated by the model in Table 3. Charts represent the effect for conscientiousness on second
screening at the 10th, 50th, and 90th quantiles of the moderator.
PERSONALITY AND SECOND SCREENING
43
Figure 4. Cross-level interaction between conscientiousness and monochronicity / polychronicity
as estimated by the model in Table 3. Charts represent the effect for conscientiousness on second
screening in monochron (left panel) vs. polychron cultures (right panel).
