Journal of Information Technology & Politics

ISSN: 1933-1681 (Print) 1933-169X (Online) Journal homepage: www.tandfonline.com/journals/witp20

Using Twitch for politics? The role of personality
across five countries
Christian Pieter Hoffmann, Thomas Feiler & Shelley Boulianne
To cite this article: Christian Pieter Hoffmann, Thomas Feiler & Shelley Boulianne (11 Jul 2025):
Using Twitch for politics? The role of personality across five countries, Journal of Information
Technology & Politics, DOI: 10.1080/19331681.2025.2530438
To link to this article: https://doi.org/10.1080/19331681.2025.2530438

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JOURNAL OF INFORMATION TECHNOLOGY & POLITICS
https://doi.org/10.1080/19331681.2025.2530438

Using Twitch for politics? The role of personality across five countries
Christian Pieter Hoffmann

, Thomas Feiler

, and Shelley Boulianne

ABSTRACT

KEYWORDS

Twitch is a popular live-streaming platform primarily used in the context of gaming. Streamers
tend to be very sensitive to the content shared in their streams, often eschewing political content.
At the same time, the platform is increasingly used by political actors, activists, journalists and
political influencers. In this study, we offer insights into the extent to which Twitch is used for
political purposes using a five-country (US, UK, France, Canada, and Germany) survey collected in
2023 (n = 7,500). With this large sample, we are able to focus on a subset of respondents who use
Twitch (n = 1,552). We examine the role of the Big Five personality traits in explaining exposure to
political information and posting of political content on Twitch. Extraversion positively relates to
political information and posting on Twitch, whereas agreeableness and conscientiousness nega­
tively relate to both. This study is important because citizens are diversifying their platform use and
little is known about Twitch and its political uses. Already, Twitch content reaches a significant
group, particularly those who are young, male, politically interested, and identify as right-wing.
Understanding this user group helps explain political behaviors on a widely used but understudied
platform.

Twitch; live-streaming;
personality; political
information; political
expression

Introduction

Twitch is the most frequently used live-streaming
app globally (Jackson & Johnson, 2024). It enables
users to become streamers by starting their own
channel, streaming whatever content they like
(Burroughs & Rama, 2015). Twitch differs from
other video and streaming platforms due to its
unique combination of features facilitating stream­
ing, interaction, and community-building
(S. L. Anderson, 2017; Ask et al., 2019). In
August 2024, on average, 2.3 million viewers
watched over 1.7 billion hours of streaming content
per hour, and 93,682 channels streamed 69 million
hours of content (Sullygnome, 2024). During the
COVID-19 pandemic, Twitch and the livestreaming industry grew by leaps and bounds
(Navarro & Tapiador, 2023). According to Pew
Research Center, 6% of the American population
uses Twitch (Shearer & Mitchell, 2021), but among
teens, the percentage is as high as 20% (M.
Anderson et al., 2023). In a cross-national survey
of the US, UK, France, and Canada in 2021 (n =
6,068), 18% of online respondents reported using
Twitch in the past 12 months, especially young
adults and males (Boulianne & Lee, 2022).
CONTACT Christian Pieter Hoffmann
christian.hoffmann@uni-leipzig.de
Nikolaisxtrasse 27–29, Leipzig 04109, Germany

To date, Twitch has rarely been studied in the
context of politics. Yet, the platform has been
described as an alternative to broadcast media for
young users (de la Feunte Prieto et al., 2022). In fact,
the audiences of successful streamers regularly sur­
pass those of broadcast media (Sjöblom et al., 2019).
Younger users, in particular, use Twitch for infor­
mation and social interaction (Gamir-Ríos et al.,
2024; Sjöblom et al., 2017). Twitch has long been
focused on videogaming content (Taylor, 2019).
However, since Amazon bought the platform in
2014, it has invested in broadening the range of
available content to include topics as diverse as
arts, science, and politics (Artwick, 2019; Jacobs &
Booth, 2021; Navarro & Tapiador, 2023).
While Twitch use among parties and intermedi­
aries is still rare (Iranzo-Cabrera & CaseroRipollés, 2023), an increasing number of political
influencers and alternative journalists employ the
platform (Foxman et al., 2024; Harris et al., 2023;
Johnson & Woodcock, 2019). Political activists also
attempt to infuse politics into discourses on Twitch
(Munoz, 2021). American youth have used this
platform to criticize Trump Literat and KliglerVilenchik (2019). The proliferation of politics on
Institute of Communication and Media Studies, University of Leipzig,

© 2025 The Author(s). Published with license by Taylor & Francis Group, LLC.
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which
permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been
published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

2

C. P. HOFFMANN ET AL.

Twitch has been met with criticism and outright
resistance by streamers and long-term, gamingfocused users (Diwanji et al., 2020; Gamir-Ríos
et al., 2024; Leith, 2021; Ruiz-Bravo et al., 2022).
This raises the question of what characterizes those
individuals using Twitch for politics.
This study will examine two political variables,
political information and political expression (cf.,
Lane et al., 2022) on Twitch. This is the first study
to use quantitative survey data collected in five
countries (n = 1,552) to examine political uses of
Twitch. Aside from socio-demographic variables,
this study will focus on the role of personality.
Specifically, we will examine the role of the Big
Five personality traits – extraversion, openness,
agreeableness, conscientiousness, and neuroticism
(Costa & McCrae, 1985; McCrae & Costa, 1985) –
in political uses of Twitch. There is an increasing
body of evidence on the role of personality in social
media use, in general, and online political engage­
ment, in particular – finding that traits like extra­
version and openness facilitate political expression,
while others, like agreeableness, may impede it
(Bromme et al., 2022; Boulianne & Galipeau,
2024; Boulianne & Koc-Michalska, 2022; Russo &
Amnå, 2016; Valli & Nai, 2023). We focus on
Twitch, a platform on which political behavior
appears rare and is considered contentious (RuizBravo et al., 2022). Twitch, therefore, offers a novel
and distinctive online environment to study the
relationship between personality and online politi­
cal engagement.
We find that extraversion positively relates to
exposure to and posting of political content on
Twitch, whereas agreeableness and conscien­
tiousness show negative relationships to both.
Contrary to our expectations, openness nega­
tively relates to our key variables. Neuroticism
does not relate to political information or posting
on Twitch. Political interest and (right-wing)
political ideology also positively relate to both
dependent variables. Compared to the US, users
in the other four examined countries report lower
frequencies of exposure to political content on
Twitch, but there are no significant differences
in the frequency of posting. Overall, the model fit
for political expression is high, which means we
have a strong model able to explain the variation
in this activity.

This study offers several contributions. It is the
first to examine the prevalence and predictors of
political uses of the popular streaming platform
Twitch. While politics remains a relatively small
segment of Twitch content, this content often pro­
liferates beyond the platform. Live-streamed con­
tent can be edited and implemented as short video
clips, audio material, or screenshots into news
reporting (Artwick, 2019). It is often shared on
various social media platforms, such as YouTube
(Ask et al., 2019; Taylor, 2019). Twitch is increas­
ingly used in the context of news, for example, to
stream events (e.g., rallies, town hall meetings,
news conferences), breaking news, or chat format
programs with the streamer serving as host
(Artwick, 2019). We add to research on online
political information and expression by covering
the usage of Twitch in five countries. These insights
are of particular importance to research on young
citizens’ online political engagement (Andersen
et al., 2021; Boulianne & Theocharis, 2020; Eddy,
2022), given its rapidly growing popularity among
youth. We also add to the emergent literature on
personality and online politics, highlighting the
particular context of a platform on which politics
is not just rare but often outright discouraged
(Ruiz-Bravo et al., 2022). Finally, we add to the
growing body of research on Twitch by highlight­
ing its usage in politics.
Streaming and politics on Twitch

On Twitch, streamers maintain channels as perso­
nalized digital spaces through which they can livebroadcast their content (H. R. Gerber & Botzakis,
2017; Navarro & Tapiador, 2023). Twitch offers an
easy-to-use software interface, so setting up
a stream is convenient and free (Ask et al., 2019).
A Twitch-stream focused on gaming typically con­
sists of a main screen showing the live (audiovisual)
stream of the videogame being played from the
gamer’s perspective, plus a boxed-off additional
video and audio feed of the streamer, captured via
webcam and microphone (S. L. Anderson, 2017;
Sjöblom et al., 2019). A synchronous real-time
online chat is depicted on the stream’s side. It
allows for interactions between viewers and strea­
mers as well as among viewers (S. L. Anderson,
2017; H. R. Gerber & Botzakis, 2017).

JOURNAL OF INFORMATION TECHNOLOGY & POLITICS

Most Twitch users take on the more passive role
of viewers, following and subscribing to streamers
(H. R. Gerber & Botzakis, 2017; Navarro &
Tapiador, 2023). In addition, some users support
their favorite streamers by moderating chats; these
users are called “mods” (H. R. Gerber & Botzakis,
2017; Taylor, 2019). A live stream can be watched
by a handful of viewers or many thousands
(Burroughs & Rama, 2015; Hamilton et al., 2014).
Over time, the professionalization of Twitch strea­
mers has increased (Törhönen et al., 2020). A study
of Spanish Twitch streamers found that about
22.4 percent of streamers produce content regu­
larly and at a professional level, generating over
80 percent of all content (Padilla Molina &
Navarro, 2022). Streamers foster parasocial rela­
tionships with viewers and fans by reading and
responding to messages from the chat and by
maintaining a lively presence on various social
media platforms (S. L. Anderson, 2017; Diwanji
et al., 2020; Kim & Kim, 2022; Sheng & Kairam,
2020; Sherrick et al., 2023). Social aspects have been
identified as the predominant motivator for view­
ers to watch and donate to their favorite streamer
(Kneisel & Sternadori, 2023; Wohn et al., 2018).
Streamers tend to be very sensitive to the content
shared in their streams, including the chats – e.g.,
taking action against trolling (Golf-Papez & Veer,
2022). As audiences grow larger, live conversations
become more difficult to monitor and moderate
(Ruiz-Bravo et al., 2022; Seering et al., 2017).
Trolling (Golf-Papez & Veer, 2022), toxicity
(Poyane, 2019), harassment and bigotry have been
identified as challenges for Twitch streamers (Ask
et al., 2019). Mihailova (2022) found that in gaming
streams, cursing, sarcasm, and jokes often occur in
conjunction with exclusionary language. To com­
bat incivility and hate speech, Twitch may sanction
streamers (Ask et al., 2019; O’Connor, 2021; Partin,
2023). Streamers, especially gaming streamers, are
therefore eager to avoid contentious topics and
often discourage political discussions in their
streams.
At the same time, political actors increasingly
incorporate live-streaming into their online com­
munications portfolio: President Donald Trump
had his State of the Union address live-streamed,
and Senator Bernie Sanders live-streamed his
response to the address on Facebook Live; former

3

Speaker of the United States House of
Representatives Nancy Pelosi used Periscope for
her live stream, and other politicians have livestreamed their speeches in memory of victims of
gun violence (Artwick, 2019). Therefore, RocaTrenchs et al. (2023) argue that Twitch holds pro­
mise as an effective tool for political communication
(i.e., real-time interactions, mixing politics with
entertainment, lack of gatekeepers). Yet, they
found that only a few political parties in Spain
maintain a Twitch presence, and those who do
only use it sporadically. Iranzo-Cabrera and CaseroRipollés (2023) found that politicians’ appearances
on Twitch can make them appear more authentic
and can facilitate dialogue with citizens.
Some political commentators reach sizable audi­
ences on Twitch (Foxman et al., 2024; Harris et al.,
2023). Non-institutional journalists (e.g., Hassan
Piker) have also used the platform for reporting
purposes (cf. Johnson & Woodcock, 2019). Munoz
(2021) finds that cyber-activists use Twitch to
quickly create content about social issues and
favor the platform for a relative lack of content
management and its opportunities for economic
transactions. Activists were found to attempt to
politicize the mainly apolitical live chats of gaming
streams by posting messages related to recent poli­
tical events; however, other members of the stream
community (either moderators or other viewers)
often counter and shut down these politicization
attempts (Ruiz-Bravo et al., 2022). As noted above,
politics is often actively avoided by streamers and
regarded as a breach of etiquette by gamingoriented long-term users. We therefore pose
a first research question:
RQ1: To what extent do individuals in the US, the
UK, France, Canada, and Germany use Twitch for
political information and political expression?

Personality and political engagement on Twitch
Theoretical framework and problematization

In this study, we examine two political behaviors
on Twitch, political information and political
expression. Globally, citizens increasingly use
digital platforms to access news (Newman et al.,
2023). For the purposes of this study, we define

4

C. P. HOFFMANN ET AL.

political information as information about cur­
rent events in the world, news about elections,
information about political figures, information
about government performance, debates about
public policy, and other political issues. Different
platforms offer different affordances that shape
opportunities for political expression (Boulianne
et al., 2024). Lane et al. (2022) define political
expression as “behaviors that involve communica­
tion of one’s political views, beliefs, or identities to
others” (p. 5). We follow this definition. There is
an increasing body of evidence on the role of
personality in online political engagement,
although no previous study has examined the
context of Twitch.
We base this study on the Five Factor model of
personality (Costa & McCrae, 1985; McCrae &
Costa, 1985), or the “Big Five” (Goldberg, 1990),
which is one of the most influential and robust
conceptual frameworks in psychological research
(Bainbridge et al., 2022). McCrae and Costa
(1985) point out that personality traits vary across
individuals in meaningful ways but are character­
ized by within-person stability. Applying
a personality framework to political online beha­
vior allows for novel insights as personality traits
constitute stable dispositions distinct from situa­
tional states (e.g., motivation, affect), attitudes or
beliefs (Gerber et al., 2011). Personality reliably
affects behavioral responses to stimuli encountered
in the world. Relationships identified through
a personality-based conceptual framework, thus,
are likely to hold across, for example, online plat­
forms or political issues.
The Big Five framework differentiates five person­
ality traits: extraversion, openness, agreeableness,
conscientiousness, and neuroticism. Extraversion is
a tendency to seek interactions with others. It is
associated with sociability and attention-seeking.
Openness describes a willingness to make new experi­
ences and is associated with curiosity and imagina­
tion. Agreeableness is an affinity toward social
harmony. It is associated with friendliness and coop­
erativeness. Conscientiousness is the ability to for con­
trol impulse control and pursue goal-directed
behaviors. It is associated with diligence and selfdiscipline. Finally, neuroticism is characterized by
low emotional stability. It is associated with anxiety
and negative affect.

Bromme et al. (2022) conducted a meta-analysis
of the Big Five personality traits and political par­
ticipation. They find that openness and extraver­
sion increase political involvement. However, they
did not consider online political involvement.
Further, a meta-analysis on personality and social
media use confirms that openness and extraversion
are the strongest predictors from the Big Five (Liu
& Campbell, 2017). We offer theoretical innovation
by adapting these theoretical claims (grounded in
robust empirical evidence) to understanding poli­
tics on Twitch.
RQ2: How do the Big Five personality traits relate
to using Twitch for political information and poli­
tical expression?
Research model

We propose hypotheses on all five traits and our
two dependent variables based on the extant
research on personality and online political
engagement, and Twitch use.
Extraversion

Social interaction and a sense of community are
important drivers of Twitch use (Schofield &
Ledone, 2019; Sherrick et al., 2023; Sjöblom &
Hamari, 2017). Extraversion has been found to posi­
tively relate to social media use (Correa et al., 2010;
Gil de Zúñiga et al., 2017; Liu & Campbell, 2017).
However, introversion may relate to problematic
social media uses (such as escapism, “addiction,”
or exposure to harmful content), in particular
(Kircaburun et al., 2020; Kuss & Griffiths, 2011).
In a meta-analysis, Liu and Campbell (2017) find
that extraversion positively predicts social network­
ing site use as well as specific activities such as
interacting with others, posting photos, and network
size. Among all five personality traits, extraversion
has most consistently been shown to correlate with
political expression/engagement online (Bromme
et al., 2022; Boulianne & Galipeau, 2024; Boulianne
& Koc-Michalska, 2022; Russo & Amnå, 2016). We
therefore propose:
H1: Extraversion is positively related to (a) poli­
tical information and (b) political expression on
Twitch.

JOURNAL OF INFORMATION TECHNOLOGY & POLITICS

Openness

Twitch users tend to use the platform to find
information and connect to others (Church, 2022;
Gros et al., 2017). Openness is broadly associated
with information seeking in social media, playing
games, posting status updates, and posting photos
(Liu & Campbell, 2017), and with fostering larger
social networks (Mondak, 2010 vs. Liu & Campbell,
2017). Valli and Nai (2023) find no relationship
between avoidance of dissonant political views and
openness. Instead, openness has been shown to
positively predict political engagement/expression
(Bromme et al., 2022; Boulianne & Koc-Michalska,
2022). We propose:
H2: Openness is positively related to (a) political
information and (b) political expression on Twitch.
Agreeableness

Agreeableness tends to be negatively related to off­
line (Mondak, 2010) and online political engage­
ment (Russo & Amnå, 2016). Based on a metaanalysis, agreeableness negatively relates to playing
games on social networking sites and positively
relates to posting photos (Liu & Campbell, 2017).
We propose that this may be especially the case on
Twitch, as the platform norms of Twitch tend to
discourage political expression (Ruiz-Bravo et al.,
2022). Agreeable individuals tend to seek harmony
over confrontation (A. S. Gerber et al., 2012).
Accordingly, Valli and Nai (2023) find
a correlation between agreeableness and avoidance
of dissonant political views. We propose:
H : Agreeableness is negatively related to (a)
political information and (b) political expression
on Twitch.
Conscientiousness

Conscientiousness negatively relates to playing
games and seeking information on social network­
ing sites (Liu & Campbell, 2017). Boulianne and
Koc-Michalska (2022) find that conscientiousness
is negatively related to online political talk, and
only positively related to like-minded discussion.
Valli and Nai (2023) find that conscientiousness
negatively relates to contestation, but not avoid­
ance. Conscientious individuals tend to adhere to
rules and norms, which might make them prone to

5

intervene against online rule-breakers (Obermaier,
2024; Porten-Cheé et al., 2020). Again, given the
prevalent norms on Twitch, especially among the
dominant gaming community (Ruiz-Bravo et al.,
2022), to avoid political content, we propose:
H4: Conscientiousness is negatively related to (a)
political information and (b) political expression
on Twitch.
Neuroticism

Neuroticism is positively associated with social
media use (Correa et al., 2010; Gil de Zúñiga
et al., 2017), especially problematic uses
(Kircaburun et al., 2020). De Wit et al. (2020)
found that Twitch users increase their platform
engagement when they feel unwell. The evidence
on the relationship between neuroticism and
online political expression is weak. Bromme et al.
(2022) find a positive association with political
engagement. Valli and Nai (2023) find that neuro­
ticism correlates with contestation of dissonant
political views. Given that many communities on
Twitch discourage political expression, it may be
more likely to occur spontaneously and due to
strong affect. We therefore propose:
H5: Neuroticism is positively related to (a) poli­
tical information and (b) political expression on
Twitch.
Our research model (Figure 1) will control for
socio-demographic variables (i.e., age, gender, edu­
cation), and three variables that have been shown
to relate to online political engagement, political
orientation, political interest, and digital skills.
Methods

This study uses survey data gathered in the United
States, United Kingdom, France, Canada, and
Germany during January and February 2023 (n =
7,500, 1,500 per country). Kantar administered the
survey to their online panel with quotas to ensure
representation of the population in each country
(sex, age, education). The project received ethics
approval in accordance with Canada’s Tri-Council
Policy Statement: Ethical Conduct for Research
Involving Humans (TCPS)]. The funding source

6

C. P. HOFFMANN ET AL.

(SD = 1.10) on a four-point scale. For more descrip­
tive findings, see Table 1 and the Results section.
Independent variables

We measured personality using the Big Five scale
originating from the Ten-Item Personality Measure
(TIPI) (Gosling et al., 2003). Respondents were
asked to respond that the trait applies to them,
using a seven-point scale ranging from strongly dis­
agree or strongly agree (1 to 7). The responses to the
two personality survey questions were added
together and then the sum divided by two.
Figure 1. Research model.

is the Social Sciences and Humanities Research
Council of Canada. The data and replication files
are available at https://doi.org/10.6084/m9.fig
share.29484104.v1.
The analysis focused on those who reported using
Twitch during the past 12 months (n = 1,552). We
asked about the frequency of using this platform, with
responses of “never, rarely, from time to time, often.”
The sample size for each country is: Canada (n =
299), the United States (n = 462), France (n = 308),
Germany (n = 220), and the United Kingdom (n =
263). We do not have country-specific hypotheses;
the theoretical frames should hold across these five
Western democracies and the small sample sizes
(especially in Germany) limit our ability to conduct
country-specific analysis. Instead, we include country
(dummy variables) as a statistical control in the
models.
Dependent variables

We defined political content: “please think about
current events in the world, news about elections,
information about political figures, information
about government performance, debates about pub­
lic policy, and other political issues.” We asked
whether they had seen this type of content on
Twitch and whether they posted this type of content.
For both questions, the response options were:
“never, rarely, from time to time, often” and the
time frame was the past 12 months. Pooling across
countries, the average for political information is
2.13 (SD = 1.02) and for political expression is 2.02

● Extraversion:

Extraverted, enthusiastic;
Reserved, quiet (reversed coded)
● Agreeableness: Sympathetic, warm; Critical,
quarrelsome (reverse coded),
● Conscientiousness:
Dependable,
selfdisciplined; Disorganized, careless (reversed
coded)
● Neuroticism: Anxious, easily upset; Calm,
emotionally stable (reversed coded)
● Openness:
Open to new experiences;
Conventional, uncreative (reversed coded)
Since our analysis focuses on the subgroup of Twitch
users, we report on the average values for this subset.
The average score on extraversion is 3.85 (SD =
1.10), agreeableness is 4.60 (SD = 1.07), conscien­
tiousness is 4.67 (SD = 1.19), neuroticism is 3.67
(SD = 1.16), and openness is 4.57 (SD = 1.06).
Controls

For political interest, we asked “How interested
would you say you are in politics?” following the
World Values Survey. Four response options were
provided, ranging from not at all to very interested.
For the subset of Twitch users, the average political
interest is 2.87 (SD = 0.91). Political ideology was
based on a self-placement question based on a scale
of left (0) to right (10). Respondents were offered an
option to say “neither left nor right.” These respon­
dents were coded in the middle of the left-right scale.
The average for the subset of Twitch users is 5.87 (SD
= 2.56). We asked respondents to rate their under­
standing of a series of digital concepts: algorithm,
memes, hashtags, and deepfakes (Cronbach’s alpha

JOURNAL OF INFORMATION TECHNOLOGY & POLITICS

7

Table 1. Descriptive statistics by country for Twitch users (n = 1,552).
Females1

Education (4 groups)

Extraversion

Agreeableness

Conscientiousness

Neuroticism

Openness

USA
UK
FRA
CA
GER
Total
USA
UK
FRA
CA
GER
Total
USA
UK
FRA
CA
GER
Total
USA
UK
FRA
CA
GER
Total
USA
UK
FRA
CA
GER
Total
USA
UK
FRA
CA
GER
Total
USA
UK
FRA
CA
GER
Total

Mean
32.10%
45.04%
43.97%
44.37%
39.72%
40.09%
2.42
2.15
1.98
2.18
2.06
2.19
3.90
3.90
3.75
3.73
3.99
3.85
4.51
4.48
4.75
4.57
4.76
4.60
4.53
4.58
4.82
4.65
4.90
4.67
3.68
3.67
3.66
3.81
3.46
3.67
4.54
4.55
4.58
4.57
4.65
4.57

SD
How interested would you say you are in
politics? (1 to 4)

1.08
1.16
1.12
1.11
1.06
1.11
1.06
1.15
1.06
1.16
1.07
1.10
1.04
1.10
1.16
0.99
1.05
1.07
1.13
1.19
1.17
1.16
1.29
1.19
1.16
1.23
1.10
1.14
1.18
1.16
1.09
1.01
1.10
1.06
1.03
1.06

In the past 12 months, how often have seen
political info on Twitch? (1 to 4)

In the past 12 months, how often have you
posted political content on Twitch? (1 to 4)

Digital skills

Age

Political ideology (0 to 10)

In the past 12 months, how often have you
used Twitch? (1 to 4)
Note: full sample

= .804). Respondents selected responses from 1 (no
understanding) to 5 (full understanding). The average
for the subset of Twitch users is 3.58 (SD = 0.96).
Gender was coded as females = 1 and males = 0.
For the subset of Twitch users, 40.1% are female.
Education was based on a series of categories: high
school or less, some college, a bachelor’s degree, and
more than a bachelor’s degree. The average for the
subset of Twitch users is 2.19 (SD = 1.11). Age was
calculated as year of birth minus year of data collec­
tion. The average age for Twitch users is 35.07 (SD =
11.95).
Results

To address RQ1, we present some initial descrip­
tive findings. Figure 2 reports the frequencies of use
by country for the full sample (n = 7,500). In the

USA
UK
FRA
CA
GER
Total
USA
UK
FRA
CA
GER
Total
USA
UK
FRA
CA
GER
Total
USA (alpha = .853)
UK (alpha = .855)
FRA (alpha = .833)
CA (alpha = .863)
GER (alpha = .790)
Total (alpha = .804)
USA
UK
FRA
CA
GER
Total
USA
UK
FRA
CA
GER
Total
USA
UK
FRA
CA
GER
Total

Mean
2.99
2.97
2.69
2.71
2.96
2.87
2.38
2.08
2.02
2.02
1.95
2.13
2.29
2.06
1.85
1.88
1.81
2.02
3.65
3.49
3.43
3.51
3.82
3.58
35.13
33.48
35.77
35.29
35.61
35.07
6.42
5.79
5.69
5.72
5.26
5.87
2.92
2.72
2.80
2.73
2.79
2.80

SD
0.89
0.83
0.93
0.97
0.86
0.91
1.02
0.99
0.99
1.01
1.03
1.02
1.13
1.09
1.04
1.08
1.08
1.10
0.89
0.95
0.96
1.03
0.99
0.96
10.16
10.96
13.88
12.67
12.56
11.95
2.51
2.56
2.52
2.76
2.23
2.56
0.74
0.75
0.79
0.76
0.71
0.76

overall sample, about a fifth of participants (20.7%)
report using Twitch at least occasionally.
Among all Twitch users, 35.7% report never
seeing political information on Twitch and 47.4%
report that they never post political content on
Twitch (see Figures 3 and 4).
Appendix Table A1 offers a correlation matrix to
help examine patterns of association among the vari­
ables, particularly among the independent variables
which may cause estimation problems due to multi­
collinearity. As observed in other studies, conscien­
tiousness is positively correlated with agreeableness
(r = .434, p < .001) and negatively correlated with
neuroticism (r = −.425, p < .001). Also, age is corre­
lated with digital skills (r = −.448, p < .001). Exposure
to political information on Twitch strongly and posi­
tively correlates with posting political content on the
platform (r = .692, p < .001).

8

C. P. HOFFMANN ET AL.

100%
90%

2.5%

4.3%

6.9%

7.0%

6.7%
5.5%

8.1%

8.9%

9.2%

3.2%

4.7%

13.7%

6.2%
8.1%

80%
70%

3.7%

7.3%

8.3%

9.9%

Often

60%

Time to time

50%
40%
30%

82.5%

79.5%

80.1%

UK

France

Canada

85.3%

Rarely
79.3%

69.2%

Never

20%
10%
0%
US

Germany

Total

Figure 2. Frequency of using Twitch in the past 12 months (n = 7,500).

To address RQ2, we turn to the regression
model presented in Table 2. We find that extra­
version is positively related to exposure to politi­
cal information (H1a) and posting political
content (H1b), as expected. Openness is nega­
tively related to exposure to political information
(H2a) and posting political content (H2b), which
is contrary to our expectations. The negative cor­
relation was also noted in the correlation matrix
(Appendix Table A1). A separate analysis of the
components of openness helps explains this unex­
pected finding. Reporting oneself to be unconven­
tional and creative is negatively related to
exposure to and posting political content, whereas
the expectation is that there would be a positive
relationship.
100%
90%

15.2%

80%
70%

As for H3, agreeableness is negatively related to
exposure to political information (H3a) and post­
ing political content (H3b), as expected; however,
the coefficient for political information does not
reach the threshold for statistical significance (p
= .073). As for H4, conscientiousness is negatively
related to exposure to political information (H4a)
and posting political content (H4b), as expected.
Finally, neuroticism does not significantly relate to
exposure to political information (H5a) and post­
ing political content (H5b).
The model fit for posting political content is
55.9%, which can be explained by the large coef­
ficient for exposure to political information. The
model fit for exposure to political information is
23.7%. Political interest significantly relates to

9.5%

8.1%

10.0%

9.1%

24.0%

25.0%

21.7%

22.7%

27.3%

28.1%

26.3%

33.1%

60%
31.2%

50%
40%

11.0%

Often

21.8%
27.1%

Rarely

26.4%

Never

30%
20%
10%

Time to time

35.4%

39.6%

40.1%

France

Canada

46.4%
35.7%

25.3%

0%
US

UK

Figure 3. Political information on Twitch (n = 1,552).

Germany

Total

JOURNAL OF INFORMATION TECHNOLOGY & POLITICS

9

100%
90%

17.7%

11.0%

80%
70%

10.9%

19.8%

20.7%

17.7%

29.0%
17.5%

14.4%

12.6%

24.0%
13.2%

Often
15.9%

14.1%

50%
18.2%

Time to time
Rarely
Never

30%
20%

10.7%

29.3%

60%

40%

9.4%

53.2%

54.2%

58.2%

France

Canada

Germany

47.4%

45.6%
35.1%

10%
0%
US

UK

Total

Figure 4. Posting political content on Twitch (n = 1,552).
Table 2. Exposure to and posting of political content on Twitch.
(1)
Exposure to political content

Extraversion (H1)
Openness (H2)
Agreeableness (H3)
Conscientiousness (H4)
Neuroticism (H5)
Political interest
Political ideology
Digital skills
Age
Female
Education
Canada
UK
France
Germany
Exposure to political content on Twitch
R-squared
Sample size

b
0.074
−0.100
−0.047
−0.098
0.003
0.286
0.060
0.059
0.000015
−0.030
0.062
−0.180
−0.225
−0.136
−0.286

SE
0.022
0.026
0.026
0.026
0.024
0.028
0.010
0.027
0.002
0.049
0.022
0.068
0.070
0.068
0.076

Beta
0.079
−0.104
−0.049
−0.113
0.003
0.255
0.151
0.056
0.00018
−0.014
0.068
−0.069
−0.083
−0.053
−0.097

(1)
Posting political content
p
0.001
<0.001
0.073
<0.001
0.910
<0.001
<0.001
0.029
0.994
0.547
0.004
0.008
0.001
0.045
<0.001

23.7%
1,533

b
0.040
−0.056
−0.071
−0.097
−0.015
0.146
0.060
−0.060
−0.003
0.011
0.017
−0.096
−0.017
−0.083
−0.083
0.598
55.9%
1,533

SE
0.018
0.021
0.022
0.021
0.020
0.024
0.008
0.022
0.002
0.040
0.018
0.056
0.058
0.056
0.063
0.021

Beta
0.039
−0.054
−0.069
−0.104
−0.016
0.121
0.139
−0.052
−0.030
0.005
0.018
−0.034
−0.006
−0.030
−0.026
0.554

p
0.028
0.008
0.001
<0.001
0.441
<0.001
<0.001
0.007
0.105
0.785
0.333
0.087
0.772
0.137
0.184
<0.001

Male and US respondents are the reference groups for the above model. Ordinary least square regression.

both dependent variables. Having a right-wing
ideology positively relates to exposure and post­
ing of political content on Twitch. Digital skills
positively relate to exposure to political content,
but negatively relate to posting of political con­
tent. As noted, the analysis is based on the subset
of Twitch users. For this subset, age, gender,
education, and country do not predict the posting
of political content. Education positively relates to
exposure to political content. Compared to the
US, all countries have lower frequencies of expo­
sure to political content on Twitch, but there are
not significant differences in posting.

As noted in the Methods section, the sample
size is not sufficient within each country to con­
duct a meaningful side-by-side comparison of the
five personality traits and each dependent vari­
able for each country (see Appendix Tables A2
and A3). Instead, we discuss results for the US
sample only, because this sample includes more
than 400 respondents (which is a critical thresh­
old for providing a reasonable margin of error
and ensuring a normal distribution in the vari­
ables). As noted in Table 3, extraversion is posi­
tively related to exposure to political information
(H1a) and posting political content (H1b), as

10

C. P. HOFFMANN ET AL.

Table 3. Exposure to and posting of political content on Twitch for US respondents.
Exposure to political content

Extraversion (H1)
Openness (H2)
Agreeableness (H3)
Conscientiousness (H4)
Neuroticism (H5)
Political interest
Political ideology
Digital skills
Age
Female
Education
Exposure to political content on Twitch
R-squared
Sample size

b
0.086
−0.199
0.030
−0.020
0.036
0.229
0.054
0.183
0.006
−0.041
0.159

SE
0.040
0.046
0.051
0.050
0.044
0.053
0.018
0.053
0.005
0.095
0.044

Beta
0.088
−0.214
0.031
−0.022
0.040
0.201
0.133
0.159
0.058
−0.019
0.168

Posting political content
p
0.033
<0.001
0.553
0.695
0.417
<0.001
0.003
0.001
0.195
0.668
<0.001

29.9%
457

b
0.086
−0.048
−0.099
−0.135
−0.038
0.174
0.054
−0.009
0.006
0.043
−0.039
0.577
54.5%
457

SE
0.036
0.041
0.045
0.045
0.039
0.048
0.016
0.048
0.004
0.084
0.040
0.042

Beta
0.080
−0.047
−0.091
−0.136
−0.039
0.139
0.121
−0.007
0.053
0.018
−0.037
0.525

p
0.017
0.247
0.029
0.003
0.338
<0.001
0.001
0.844
0.145
0.607
0.329
<0.001

Male respondents are the reference group for the above model. Ordinary least square regression.

expected, among US Twitch users. In the US
sample, openness is negatively related to expo­
sure to political information (H2a), but for the
US sample, the coefficient for posting is not sta­
tistically significant (H2b). Agreeableness is nega­
tively related to posting political content (H3b),
but the coefficient for political information does
not reach the threshold for statistical significance
(H3a) in the US sample. Conscientiousness is
negatively related to exposure to political infor­
mation (H4a), but for the US sample, the coeffi­
cient for posting is not statistically significant
(H4b). Neuroticism does not significantly relate
to exposure to political information (H5a) and
posting political content (H5b). As such, the USspecific findings mostly replicate the findings for
the pooled sample of Twitch users.

Discussion

Twitch is a widely use platform among young
adults (S. L. Anderson, 2017; Boulianne & Lee,
2022). It has grown rapidly over recent years,
particularly during the pandemic (Navarro &
Tapiador, 2023). While deeply rooted in and
primarily used for gaming (Golf-Papez & Veer,
2022; Ruiz-Bravo et al., 2022), the platform is
increasingly used for politics, too. This is partly
driven by a push by the parent company
Amazon to diversify content (Artwick, 2019),
and partly by the sheer popularity of the plat­
form. Some political actors, activists, journalists
and political influencers already use the platform
(Foxman et al., 2024; Harris et al., 2023; Munoz,

2021; Roca-Trenchs et al., 2023). In Germany,
the leading broadcast news show announced in
October of 2024 that it would stream content on
Twitch (Tagesschau, 2024). The increasing poli­
tical uses of Twitch create tension among users.
Traditionally, gaming streamers and viewers
avoid political content (Diwanji et al., 2020;
Gamir-Ríos et al., 2024; Leith, 2021; Ruiz-Bravo
et al., 2022). Streamers occasionally instruct their
“mods” to remove political content, to avoid
violating community guidelines and alienating
their communities. Many in the gaming commu­
nity consider politics on Twitch a breach of
norms.
Based on a survey in the US, the UK, France,
Canada and Germany, we find that, overall, Twitch
use is most common in the US (31%), and least
common in Germany (15%), with about 20% usage
in the other three countries. Of those using Twitch,
64% reported seeing political content, and 53%
reported posting political content. Accordingly,
these political behaviors are quite common on the
platform, despite its relatively apolitical image.
More than 10% of users report seeing and posting
political content “often.” Again, these behaviors are
most common in the US (15.2% and 17.7%), but
country differences are not significant in our
regression model on posting.
We examine the role of personality (Costa &
McCrae, 1985; Goldberg, 1990; McCrae & Costa,
1985) in political uses of Twitch, because (a)
personality is increasingly recognized as
a relevant factor in online political behavior
(Bromme et al., 2022; Boulianne & Koc-

JOURNAL OF INFORMATION TECHNOLOGY & POLITICS

Michalska, 2022; Valli & Nai, 2023), and (b) the
role of personality may play a distinctive role on
a platform on which politics is considered impro­
per by some. As hypothesized, we find that extra­
version positively relates to both political
information and political posting on Twitch.
This finding is in line with studies focusing on
other platforms, especially social media (Bromme
et al., 2022; Boulianne & Galipeau, 2024;
Boulianne & Koc-Michalska, 2022; Russo &
Amnå, 2016). As noted, Liu and Campbell’s
(2017) meta-analysis shows that extraversion
relates to interacting on social networking sites.
Contrary to our expectations, openness nega­
tively relates to the dependent variables.
Specifically, reporting oneself to be unconventional
and creative exhibits this negative relationship.
Users with these traits may tend to favor other
Twitch topics, like gaming or arts. As expected,
agreeableness and conscientiousness negatively
relate to the two political uses of Twitch.
Agreeableness tends to be negatively related to
political engagement (Mondak, 2010; Russo &
Amnå, 2016). In our data, neuroticism was not
significantly related to political information or
posting, consistent with Liu and Campbell’s
(2017) finding of a null relationship between neu­
roticism and information-seeking on social net­
working sites.
These insights are of particular importance to
understanding politics on the Twitch platform. We
find that those geared toward politics on Twitch
tend to be more brash and impulsive. They tend to
be more extraverted, they are also low on agree­
ableness and conscientiousness. This fits the profile
of norm-breakers. Twitch is a platform that focuses
on community-building (Taylor, 2019), but avid
users have been shown to eschew politics. Users
wishing to get along with other users may avoid
politics on Twitch. Similarly, those geared toward
diligence and discipline (conscientiousness) may
prefer to adhere to common platform norms by
focusing on topics other than politics.
Interestingly, openness does not relate to
political uses of Twitch. Openness is associated
with information seeking and playing games on
social media (Liu & Campbell, 2017). In studies
of other platforms, openness positively predicts
political engagement/expression (Bromme et al.,

11

2022; Boulianne & Koc-Michalska, 2022), but
that may not apply to a gaming-oriented plat­
form where politics is (or used to be) a relative
fringe topic. In other words, those using Twitch
for politics do not necessarily seek new insights
or experiences but rather wish to confirm and
express their views. This indicates that those
infusing politics into the platform may primarily
be interested in reaching, persuading or disrupt­
ing others. Previous studies have highlighted
that streamers on Twitch struggle with deviant
behavior such as trolling or hate speech among
individual members of their communities (Ask
et al., 2019; Golf-Papez & Veer, 2022; Poyane,
2019).
In practice, our study implies that streamers
wishing to avoid politics are well-advised to com­
municate their community standards clearly and to
provide specific instructions to moderators on how
to address political comments. Those posting poli­
tical comments in a chat may be prone to brash,
confrontative, even uncivil behavior and may
require swift sanctions. It is likely that muting or
removing such commentators may be necessary to
maintain a community experience devoid of dis­
ruptive political comments. Political comments
may generally lean toward incivility, as those enga­
ging in political expression tend to be low on agree­
ableness and conscientiousness. Streamers offering
political content on the platform are likely to
attract like-minded viewers and may need to simi­
larly sanction disruptive commenters strictly, as the
negative association of political uses with openness
indicates that politically-minded users may not be
interested in a good-faith exchange of views and
arguments.
Within the subsample of Twitch users, age,
gender, education, and country do not predict
posting of political content, but these variables
likely matter in the adoption of this platform;
among the user group, there may be little varia­
tion on these factors, producing null effects.
Exposure to political information is more com­
mon among the more formally educated and in
the US. Digital skills increase exposure to poli­
tical content but decrease the posting of political
content. The latter unusual finding might indi­
cate, again, that avid users of the platform tend
to avoid political engagement on Twitch.

12

C. P. HOFFMANN ET AL.

Right-wing ideology and political interest are
positively related to both seeing and posting poli­
tical content on the platform. These findings are an
important contribution to the study of politics on
Twitch. Recently, Boulianne et al. (2024) found
that right-wing individuals are more likely to post
content on a variety of social media platforms, such
as Reddit or WhatsApp. Twitch appears to fit this
pattern.
This study is subject to several limitations. We
present cross-sectional data, so our analyses are
correlational. However, causality from online
behavior to personality is unlikely given the psy­
chological literature on personality (Costa &
McCrae, 1985; Goldberg, 1990; McCrae & Costa,
1985). We focus on the Big Five personality frame­
work; however, studies of online hostility and trol­
ling have highlighted the role of “dark” personality
traits, specifically the Dark Triad (Buckels et al.,
2014; Moor & Anderson, 2019). We cannot speak
to the role of these traits, but future studies may
find this endeavor fruitful given our results on the
traits extraversion, conscientiousness and agree­
ableness. We do not differentiate the type of poli­
tical content users see or post on the platform. The
explained variance of our model of political infor­
mation is substantive, but limited, so future studies
should explore additional predictors. Finally,
future studies could delve deeper into deviant poli­
tical behaviors, like hate speech or trolling, and
examine the role of “dark” personality traits (cf.,
Buckels et al., 2014; Moor & Anderson, 2019).
As noted, this study offers a number of con­
tributions. Twitch has primarily been studied in
the context of gaming. Yet it is a widely used
platform experiencing rapid growth, especially
among young users. We descriptively analyze
political uses of Twitch in five Western demo­
cratic countries. This adds to the body of knowl­
edge on Twitch uses and online political
engagement,
particularly
among
youth
(Andersen et al., 2021; Boulianne & Theocharis,
2020; Eddy, 2022). Twitch is increasingly
described as an alternative to broadcast media
(de la Feunte Prieto et al., 2022) and that journal­
ists and influencers are increasingly active on the
platform, including Germany’s tagesschau news
program. As noted, live-streamed content can not
only be embedded in news reporting (Artwick,

2019), but Twitch content tends to be shared
widely on other social media platforms, such as
YouTube (Ask et al., 2019; Taylor, 2019). Twitch
should therefore be considered in cross-platform
analyses of the information ecosystem, particu­
larly of young citizens. While more research is
needed on the use of Twitch by political actors
and activists, this study provides an important
starting point by highlighting that politics does
appear to be quite common on the platform.
Disclosure statement
No potential conflict of interest was reported by the author(s).

Funding
This research is funded by the Social Sciences and Humanities
Research Council of Canada [Grant No. 435-2019-04-94].

Notes on contributors
Christian Pieter Hoffmann is professor of communication
management and political communication at the Institute of
Communication and Media Studies and the Institute of
Political Science, University of Leipzig. His research is focused
on online participation, trust, self-disclosure and privacy pro­
tection in social media.
Thomas Feiler is a PhD student at the Institute of
Communication and Media Studies and the Institute of
Political Science, University of Leipzig. His research is focused
on online and offline political participation.
Shelley Boulianne is the R. Klein Chair in Communication
Studies at Mount Royal University (Canada). She earned her
Ph.D. in sociology from the University of WisconsinMadison. She has held professor positions in sociology and
political science at MacEwan University (Canada), the
Université Catholique de Lille (France), and the University
of Southampton (UK). She has completed research fellow­
ships at the Weizenbaum Institute for the Networked
Society (Germany) and the Digital Democracy Center at the
University of Southern Denmark. Her research examines the
global dynamics of digital media use for citizen engagement in
civic and political life.

ORCID
Christian Pieter Hoffmann
http://orcid.org/0000-00025282-6950
Thomas Feiler
http://orcid.org/0009-0003-4318-1278
Shelley Boulianne
http://orcid.org/0000-0002-8951-1098

JOURNAL OF INFORMATION TECHNOLOGY & POLITICS

Data availability statement
Data and replication files will be made available on Figshare
upon acceptance of the article so that any changes in the
analysis during the review process can be reflected in the
published documentation.

Ethics approval
The survey received human-subject ethics approval prior to
data collection (File No. 102022), according to Canada’s TriCouncil Policy Statement: Ethical Conduct for Research
Involving Humans (TCPS).

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Appendix
Table A1. Correlation matrix.
1 Twitch political information r
p
2 Twitch political posting
r
p
3 Extraversion
r
p
4 Openness
r
p
5 Agreeableness
r
p
6
r
Conscientiousness
p
7 Neuroticism
r
p
8 Political interest
r
p
9 Political ideology
r
p
10 Digital skills
r
p
11 Age
r
p
12 Females
r
p
13 Education
r
p

1
1

2

0.692
< 0.001
0.143
< 0.001
−0.223
< 0.001
−0.210
< 0.001
−0.227
< 0.001
0.055
0.031
0.347
< 0.001
0.287
< 0.001
0.112
< 0.001
−0.010
0.693
−0.112
< 0.001
0.187
< 0.001

1

3

0.161
< 0.001
−0.297
< 0.001
−0.298
< 0.001
−0.322
< 0.001
0.088
0.001
0.350
< 0.001
0.368
< 0.001
0.039
0.121
−0.041
0.105
−0.106
< 0.001
0.174
< 0.001

4

5

6

7

8

9

10

11

12

1
0.263
< 0.001
−0.034
0.003
0.002
0.880
−0.130
< 0.001
0.135
< 0.001
0.041
< 0.001
0.086
< 0.001
−0.021
0.073
< 0.001
0.969
0.064
< 0.001

1
0.268
< 0.001
0.293
< 0.001
−0.226
< 0.001
0.088
< 0.001
−0.161
< 0.001
0.206
< 0.001
−0.001
0.919
0.048
< 0.001
0.077
< 0.001

1
0.434
< 0.001
−0.313
< 0.001
−0.039
0.001
−0.103
< 0.001
−0.067
< 0.001
0.187
< 0.001
0.149
< 0.001
−0.043
< 0.001

1
−0.425
< 0.001
0.070
< 0.001
−0.038
0.001
−0.076
< 0.001
0.330
< 0.001
0.052
< 0.001
0.038
0.001

1
−0.144
< 0.001
−0.016
0.160
0.014
0.211
−0.293
< 0.001
0.159
< 0.001
−0.091
< 0.001

1
0.031
1
0.007
0.246 −0.058
1
< 0.001 < 0.001
0.162 −0.013 −0.448
1
< 0.001
0.253 < 0.001
−0.198 −0.085 −0.056 −0.138
1
< 0.001 < 0.001 < 0.001 < 0.001
0.230
0.008
0.209 −0.023 −0.084
< 0.001
0.466 < 0.001
0.049 < 0.001

Table A2. Personality and exposure to political information.
USA

Extraversion (H1)
Openness (H2)
Agreeableness (H3)
Conscientiousness (H4)
Neuroticism (H5)
Political interest
Political ideology
Digital skills
Age
Female
Education
R-squared
Sample size

Beta
0.088
−0.214
0.031
−0.022
0.040
0.201
0.133
0.159
0.058
−0.019
0.168
29.9%
457

UK
p
0.033
< 0.001
0.553
0.695
0.417
< 0.001
0.003
0.001
0.195
0.668
< 0.001

Beta
0.135
−0.062
−0.008
−0.188
−0.003
0.198
0.240
−0.098
−0.106
0.055
0.012
25.8%
262

France
p
0.020
0.342
0.903
0.012
0.959
0.001
< 0.001
0.117
0.079
0.337
0.832

Beta
0.092
−0.044
−0.146
−0.120
−0.005
0.296
0.014
0.103
−0.091
−0.037
−0.038
20.7%
307

Canada

p
0.091
0.481
0.024
0.088
0.940
< 0.001
0.793
0.082
0.130
0.483
0.480

Beta
0.017
−0.084
0.005
−0.084
0.002
0.299
0.178
0.089
0.038
−0.062
0.051
25.2%
293

Germany

p
0.759
0.177
0.935
0.187
0.975
< 0.001
0.002
0.153
0.529
0.256
0.377

Beta
0.017
0.005
−0.170
−0.185
−0.035
0.287
0.209
−0.018
0.054
0.025
0.034
22.2%
214

p
0.793
0.949
0.028
0.043
0.657
< 0.001
0.001
0.801
0.433
0.702
0.604

Table A3. Personality and posting political information.
USA

Extraversion (H1)
Openness (H2)
Agreeableness (H3)
Conscientiousness (H4)
Neuroticism (H5)
Political interest
Political ideology
Digital skills
Age
Female
Education
Exposure to political content on Twitch
R-squared
Sample size

Beta
0.080
−0.047
−0.091
−0.136
−0.039
0.139
0.121
−0.007
0.053
0.018
−0.037
0.525
54.5%
457

p
0.017
0.247
0.029
0.003
0.338
< 0.001
0.001
0.844
0.145
0.607
0.329
< 0.001

UK
Beta
−0.032
−0.037
−0.014
−0.139
0.003
0.213
0.108
−0.105
−0.050
0.026
0.014
0.528
55.8%
262

France
p
0.485
0.467
0.774
0.018
0.960
< 0.001
0.023
0.030
0.289
0.562
0.758
< 0.001

Beta
0.055
−0.052
−0.085
−0.038
−0.010
0.102
0.076
−0.111
−0.105
0.002
0.057
0.613
53.4%
307

p
0.186
0.278
0.091
0.483
0.832
0.023
0.063
0.015
0.023
0.952
0.175
< 0.001

Canada
Beta
0.067
−0.051
−0.072
−0.077
0.005
0.079
0.217
0.004
−0.030
−0.022
0.029
0.566
62.4%
293

p
0.093
0.255
0.103
0.089
0.909
0.081
< 0.001
0.923
0.482
0.572
0.475
< 0.001

Germany
Beta
0.006
−0.147
−0.081
−0.025
−0.061
0.050
0.186
−0.111
−0.026
−0.036
−0.051
0.545
55.4%
214

p
0.910
0.017
0.167
0.725
0.310
0.333
< 0.001
0.038
0.622
0.475
0.306
< 0.001