MSc Political Communication
Master’s Thesis
The use of news media as a source of political information and political trust among adolescents by Doka Vivienne 11367962 30.06.2017 Supervisor
Abstract
The decline in political engagement and political trust of adolescents is a widespread concern in western democracies. This study analyzes the role of news media use and political trust among adolescents. Based on the Swiss cohort panel data NCCR IP10 conducted in 2011 and 2012 (N = 725), the influence of using TV, news media and online communication as a source of political information on political trust is analyzed. The results show a negative relationship between TV use and change in political trust as well as a positive relationship between regional newspaper use and political trust. However, this study finds no support for a relationship between using online news media and one’s level of political trust.
Introduction
A multitude of research claims difficult times for democracies all over the world because of a decline in political engagement and trust in government (Dalton, 2008; Patterson, 2000; Putnam, 2000). This decline in trust is said to be especially pronounced among the young as they have disconnected from conventional politics and government (Dahlgren, 2009; Forbrig, 2005; Rentsch, 2013). Reasons therefore are dissatisfaction with conventional politics caused by a predominant negativity about politics among adults, politicians not appealing directly to the young or the negativity and cynical news media (Bennett, 2008; Newton, 2001). The associated term video malaise (Robinson, 1976), which was initially used for the association between TV use and political distrust, means a great amount of the news content is of poor quality, especially on TV (Kepplinger et al., 1986; Mutz & Reeves, 2005; Putnam, 2000). In other words, negative perceptions of the economy, crime, negativity and incivility in the media negatively affect political trust (Chanley et al., 2000; De Vreese, 2004; Robinson, 1976). However, the engagement of the young is of special importance to a democracy as a lack of trust reduces election involvement and media use for public affairs (Pinkleton et al.,
2012; Uslaner, 1999). In addition, political participation is habit forming (Blais, 2006), which means young citizens who participate politically early in life are also more likely to do so when they are older (Easyvote, n.d.; Esser & De Vreese, 2007).
In contrast to the video malaise theory, the virtuous circle theory by Norris (2000a) proposes that the use of news media is associated with higher political trust. Due to a multiplication of channels (Blumler & Kavanagh, 1999) there is a variety of alternatives to traditional news to get information about current affairs (Entman, 2010). This development generates new valuable prerequisites for political participation, especially for the young. The so-called citizens of the digital age (Bennett, 2008) now have the virtue to also participate online in addition to offline participation (Dalton, 2008). Thus, the process of the young acquiring democratic competences and participatory repertoires is highly mediated, as only very few adolescents have direct experiences with politics (Kunz & Möller, 2011).
This two-sided perspective gives reason to take a closer look at the interaction of media and political trust among adolescents. This is insofar of relevance regarding the socialization of young citizens in a democracy, but also to consolidate existing research. Previous research has found an association between social trust, the degree to which people trust each other, and TV news consumption (Norris, 2001; Strömbäck et al., 2016). The same association has also been found between social trust and newspaper use (Pasek et al., 2006).
Expanding these findings is of importance as it has been claimed that media use only affects social trust and not political trust (Dahlgren, 2009; Scheufele, 1999). Moreover, much of the literature focuses on society as homogeneous group or the research was conducted in different political systems with disparate histories of origins, which also affects political trust as
discussed later in the theoretical section (Mishler & Rose, 2001; Schoon & Cheng, 2011). Therefore, to assess and expand these theories and to evaluate existing findings, the following research question was constructed:
RQ: To what extent does news media use as a source of political information affect political trust among adolescents?
To address this research question, an introductory theoretical background is provided, in which corresponding hypotheses are presented. The subsequent method section based on the Swiss cohort panel data NCCR IP10 conducted in 2011 and 2012 is then followed by
statistical analyses, a discussion of the results, and by a conclusion.
Theoretical Background
In a first step, relevant media models for this study are presented. In a second step, the models are combined with results of existing research resulting in corresponding hypotheses.
Media Effect Models
In explaining declining political trust, the media have played a central role as the decline in political trust seemed to coincide with the rise of more negative, assertive and independent news media (Earl Bennett, 1999; Nye & Zelikow, 1997). According to Steele and Brown’s (1995) Media Practice Model, media effects may influence the socialization of adolescents as their identities change after incorporating viewed media content. Cultivation theory builds up on this idea, which states that people who watch a lot of TV are more likely to have a biased reality perception (Gerbner, 1998). However, Steele and Brown’s (1995) model is based on the media consumption of the young in an environment within their own four walls, which is now changing with the mobile access to the Internet (Lee et al., 2013).
In addition, due to the multiplication of channels (Blumler & Kavanagh, 1999), individual-level factors have become more important to media-choice models as they do not only affect
one’s media choice, but also the effect of news media use on political trust (Strömbäck et al., 2016).
The O-M-A framework proposes that the three factors opportunities, motivations, and
abilities explain the extent of people’s media use (Luskin, 1990). Changing opportunities on a macro-level affect the influence of motivations and abilities of an individual such as one’s news media use (Prior, 2007). This means, the patterns of news media use and differences in news use between groups are changing, which might cause weaker media effects (Strömbäck et al., 2016).
According to Valkenburg and Peter (2013), small or inconsistent media effects might be the result of a suboptimal conceptualization of media effects. Thus, to detect media effects and media effect sizes, the DSMM model of Valkenburg and Peter (2013) calls for a correct positioning of media use in a communication effects model. This means conditional media effects must be considered as they moderate media effects on attitudes such as political trust. In other words, conditional media effects which are often individual-difference variables, interact with media effects. These conditional media effects consist of the developmental susceptibility, which is the strongest in childhood and early adulthood (i.e. age), and of the social susceptibility, meaning one’s family and societal context influence media use (Valkenburg & Peter, 2013).
Media Use and Political Trust
Based on these theories, previous research regarding news media use as a source of political information and political trust is outlined beginning with TV, followed by newspapers, and online sources of political information such as news websites, e-governance, and social media.
TV use and political trust. According to the video malaise theory, general TV use is
associated with less political trust (Aarts et al., 2012; Avery, 2009; Moy & Pfau, 2000;
Putnam, 2000). Therefore, general TV use and not TV use as a source of political information is at first of interest to this study. As for the Swiss case, TV use numbers between younger and older generations vary a lot. The higher one’s age, the more time on average one spends watching TV. Whereas the 15 to 19-year-old on average only watch around 70 minutes of TV per day, older age groups such as the 45 to 59-year-old spend nearly twice as much time watching TV. Based on these considerations, the video malaise theory, and based on cultivation theory, the first hypothesis is:
H1.1) A higher daily TV use negatively affects political trust
The video malaise and cultivation theory claim the same for watching news on TV. News programs are bad for political trust as they highlight crime, war and disease, which can lead to a misperception of thinking the real world is as cruel, people take advantage of each other and mutual trust is low (Putnam, 1996). Moy and Pfau (2000) support these theories by finding a negative effect of exposure to network news in the US on trust in government institutions. Also for the young, Sobieraj and Berry (2011) provide evidence for aggressive language in political media reducing political trust. However, Avery (2009) finds that the effect of news media on political trust is dependent on an individual’s existing level of political trust and on the news source. He found that for the less politically-trusting people, watching TV news showed no effect on political trust. For politically-trusting people however, exposure to TV news had a negative effect on political trust. Therefore, hypothesis 1.2 based on the video malaise theory is:
H1.2) For politically-trusting people, watching news on TV as a source of political
information has a negative effect on political trust
Contrasting the video malaise theory, Banaji and Cammaerts (2015) claim that blaming a single medium for disaffection with politics of the young is naïve. So does Norris (2000a), by finding positive effects of TV news use and political trust based on her virtuous circle theory, where she finds that news media use on TV is associated with higher levels of political trust. From these results, she concludes that those showing political interest, engagement, and trust are more likely to pay attention to political news and therefore also learn more about
government and politics in general (Norris, 2000a). Moreover, Rentsch (2013) and Holt et al. (2013) underline that political news formats can be certainly attractive for the young, finding that Swiss news coverage increased political trust among young citizens. Therefore, the last hypothesis for TV use as a source of political information and political trust is based on the virtuous circle theory:
H1.3) The more often one watches news formats on TV as a source of political information,
the higher one’s political trust becomes
Newspaper use and political trust. As the virtuous circle theory proposes, exposure to news
enhances political trust. Therefore, the second media source of interest when analyzing
political trust is the newspaper (Norris, 2000a; Norris, 2000b). Whereas the print newspaper is not the number one media choice of the young, due to a low willingness to pay for news (Leitgeb & Grammel, 2016), its distanced tone and ideologically biased or selective content (Banaji & Cammaerts, 2015), it is still a valuable source of political information (Bfs, 2015a). The virtuous circle theory is further supported by Newton (1999), Moy and Pfau (2000) who provide evidence for newspaper use increasing political trust. Avery (2009) also finds a
positive effect of newspaper use on political trust. Whereas he again found no effect for the politically-untrusting, newspaper use increased political trust among politically-trusting people. However, Aarts and Semetko (2003) do not support these findings, as they did not find an effect of newspaper use on political trust in their Dutch study. Therefore, to
complement these mixed findings and to assess the virtuous circle theory for adolescents, the following hypotheses were built:
H2.1) The more often one uses newspapers as a source of political information, the higher
one’s political trust becomes
H2.2) For politically-trusting people, newspaper use as a source of political information
increases political trust
The Internet and political trust. Lastly, as proposed in the O-M-A framework, the
opportunities for young citizens to access political information has become easier, not least because of the multiplication of channels and due to the rise of the Internet, which changed the adolescents’ media use (McLeod et al., 2001).
While the virtuous circle theory is rather optimistic about these developments, in terms of declining political trust, Norris (2001) finds the existing faith in the Internet and e-governance to restore the missing trust has not proved to be true (Dumitrica, 2016). Moreover, Norris (2001) claims that the Internet failed to increase access to policy makers and to facilitate political participation, for which the Internet is often praised (Rentsch, 2013; Tolbert & Mossberger, 2006).
In contrast to these critical claims, Shah et al. (2007) find that information seeking on the Internet is more potent than conventional news use. Tolbert and McNeal (2003) find that Internet use for political news and political communication can improve citizens’ trust in government. In addition, an analysis of the Eurobarometer data for 27 countries by Ceron
(2015) shows that consuming news on online media websites is positively associated with political trust. Regarding the young, Cortesi et al. (2015) could show that a growing number of Swiss teenagers read online newspapers.
Further, Tolbert and Mossberger (2006) could show that the use of e-government in the US increased and online exposure to information about government is significantly and positively related to trust in government. Strömbäck & Johansson (2007) provide the same findings for the young. Thus, in addition to online newspaper use, visiting a local government website can also affect political trust. However, not only the use of e-government, but also the use of social media has been found to increase political trust among the young (Holt et al., 2013). Social media provide access to information and enable spending time with and building personal connections between politicians and young citizens (Dumitrica, 2016).
According to Bakker and De Vreese (2011), Kruikemeier et al. (2014) and Kushin and Yamamoto (2010), the simple consumption of online news, be it consuming news on news media websites, government websites or visiting social network sites (SNS) as well as following politicians on SNS, are passive forms of online communication. This raises the question whether the changing macro-level opportunities, such as a growing offer for and an increased use of online political news, affect adolescents’ political trust. Therefore, based on the virtuous circle theory, the first hypothesis regarding Internet use as a source of political information is:
H3.1) Passive online communication as a source of political information positively affects
political trust
Lastly, media communication’s influence is often said to be indirect by shaping civic
involvement through its effects on discussion about public affairs, also among the young (Gil de Zúñiga et al., 2014; Hahn, 1998; Shah et al., 2005; Yamamoto et al., 2015). This is in line
with the DSMM model of Valkenburg and Peter (2013) who see media effects, in this case the triggered discussions through media use, as one of the three effect types of media use. Moreover, in line with this study’s focus, it is especially the young who take the lead with the use of communication tools such as messaging and chatting online (Van Deursen & Van Dijk, 2014).Therefore, the second hypothesis regarding Internet use as a source of political
information is:
H3.2) Passive online communication positively affects political trust through political
discussion via the Internet
Conditional Effects on Political Trust and Control Variables
To properly assess these hypotheses, one must consider other factors which might affect political trust aside from media use (Moy & Hussain, 2011; Strömbäck et al., 2016) as the decline in political trust is a complex phenomenon with multiple potential causes (Chanley et al., 2000). Thus, the following section provides factors, which later function as control variables to avoid omitted variable bias.
The relationship between news media use and political trust does not only vary across different media types, but also between citizens (Strömbäck et al., 2016). Regarding non-media determinants of political trust, cultural theories hypothesize that trust in political
institutions is exogenous, originated outside of the political sphere and communicated through early-life socialization (Mishler & Rose, 2001). Institutional theories see political trust more determined by endogenous factors such as the expected utility of institutions, thus more a consequence of performance and satisfaction with government, politics, and democracy (Hetherington, 1999; Mishler & Rose, 2001). And while macro theories perceive political trust as a collective group property among all members of a society, micro theories propose
that political trust varies among individuals based on differences in socialization, social background, political and economic experiences, or individual perceptions and evaluations (Mishler & Rose, 2001). Inglehart (1997) and Putnam (2000) both also find that political trust is built on conditional individual factors such as attitudes and values which are learned early in life. Particularly, political trust is determined by one’s social background, cognitive ability, education, occupational status and other sociodemographic factors such as age and gender (Schoon & Cheng, 2011). Thus, individuals with more socioeconomic, educational, and motivational resources express higher levels of political trust than those with fewer resources. This includes that the higher the education of one’s parents, the higher one’s political trust (Schoon & Cheng, 2011). Moreover, levels of trust vary between countries (Strömbäck et al., 2016). Scandinavian countries show higher levels of political trust than Great Britain and the United States as well as post-communist countries, which show the lowest levels of trust (Mishler & Rose, 2001; Schoon & Cheng, 2011).
In addition, one must consider factors affecting media use, as later presented in the media effects model. According to Norris (2000a) and Strömbäck et al. (2014), political interest is not only a determinant of political trust, but also of news media use. Moreover, one’s political orientation affects one’s media choice, as according to confirmation bias theory people
preferably choose media formats with a similar political orientation to avoid cognitive dissonance (Taber & Lodge, 2006). This gives reason to also include these factors as control variables.
Switzerland
The Swiss cohort panel data NCCR IP10 of 2011 and 2012 was mainly chosen due to its availability and its suitability of the set of variables to answer the research question.
Moreover, the data of the second wave was collected right after the national parliamentary elections in 2011. This implicates that citizens of all ages are likely to have been confronted with their attitudes about politics, either through receiving the election documents, through extensive election media coverage (Lutz, 2012) or through political discussion. Thus, the confrontation with elections sensitizes citizens about their political attitude and forms a suitable framework to analyze political trust.
In addition, Switzerland forms a special case to analyze political trust as trust in government is comparatively high due to the decision-making power of the citizens and due to the stability and efficiency of the country (Fraefel et al., 2012; Linder, 2012; Knoepfel et al., 2014).
Further, according to Blais (2006), the higher advanced a country’s economy and the smaller the size of a country, the higher turnout, of which political trust is a determinant (Bühlmann & Freitag, 2006). However, Switzerland is a small country with an advanced economy and despite the high political trust compared to other countries, turnout is very low, especially among the young (Dermont & Stadelmann-Steffen, 2014; Linder, 2012). Moreover, there is also a tendency for a decline in political trust (Freitag, 2001).
In terms of media use, Switzerland is one of the most highly mediated countries, with 88% of its population using the Internet and nearly 100% of the 14 to 19-year-old using the Internet (Bfs, 2017a). Moreover, the amount of people using the Internet to get political information strongly increased during the past years (Omnibus, 2014).
These temporal, institutional, economic, and media-conditions make Switzerland a valuable case to analyze the relationship between news media use as a source of political information and political trust.
Method
The following analysis of the influence of news media use as a source of political information on political trust is based on the three-wave NCCR IP10 cohort panel data conducted by the University of Amsterdam and the University of Zurich between 2011 and 2012.
Sample
The NCCR IP10 (National Center of Competence in Research Challenges to Democracy in the 21st Century) covers the medialization of political attitudes and educating democratic citizens in a multi-media society. The concrete aim of the conducted cohort study is to study the changes over time in ideas and preferences of the youth in both Switzerland and the Netherlands. Regarding the Swiss data, three survey waves were conducted among 15 to 20-year old adolescents of the German and French areas of Switzerland. The first wave was conducted in October and November 2010, where 1,657 respondents were recruited to fill in the online questionnaire (CAWI). Since only 702 respondents participated in the second wave, an additional 636 respondents were interviewed by telephone (CATI). Of the second wave, a total of 761 also participated in the third wave. Apart from small adaptations, the online questionnaires of the three waves are the same. Only the questionnaire of the second wave is longer since it includes a post-election block and in the third wave, questions about political interest and about the parents of the respondent were added. The GfK (Market Research and User Experience Institute Switzerland) first tested the questionnaire and then conducted the sampling by contacting a random sample of 7,782 households out of their telephone number pool. Further, the GfK weighted the data to correct differences in distribution. To have a broad set of variables regarding news media use as a source of political information and to control for existing trust, the second and third wave of the panel data are relevant for this thesis. Thus, the final sample size consists of the participants of the
second wave, which also participated in the third wave, N = 761. Finally, the data set was reduced to the number of respondents with existing cases for political trust in the third wave, resulting in a final sample of N = 725.
Regarding the representation of this sample for the population of Swiss adolescents, one sees some notable discrepancy especially in terms of gender, the age categories 17 and 19, as well as the regions Suisse romande and Westmittelland (see Table 1). To account for these discrepancies, the used data is weighted by the factor WEEG_Group1, as proposed by the creators of the study.
Regarding missing values,the variables “Education mother”, “Education father”, and “Social status” show various missing values. These missing values were recoded to the value 99, so they do not distort the analysis. Further missing values might result from missing “don’t know” and “no answer” options.
Table 1. Weighting (N = 761)
Variables Response Population
Gender Female Male Age 40.6% 60.4% 51.2% 48.8% 17 18 19 20 20.4% 24.2% 29.7% 25.8% 23.9% 24.9% 25.5% 25.7% Region Suisse romande
Alps and Alpine foothills Westmittelland Ostmittelland 15.9% 26.7% 27.7% 29.7% 26.9% 25.6% 20.8% 26.7%
Model and Measures
The theoretical framework and the DSSM model of Valkenburg and Peter (2013) call for an appropriate positioning of media use in a media use effects model, which based on the theory resulted in the model below.1 To detect an effect of media use, possible exogenous predictors2 of political trust and media use are included in the model. The factors measured in the second wave and political trust are outlined below.
Figure 1. Media Effects Model 1
Dependent Variable
Political trust. The variables to measure political trust on a national level among Swiss
adolescents (see Table 2) were measured on a 7-point scale reaching from 1 = No trust to 7 =
Full trust.
Table 2. Item Battery Political Trust and Component Matrix (n = 619)
1 A second media effects model is tested to analyze the change in political trust between wave 2 and wave
3. The model includes media use as the independent variable and change in political trust as the dependent variable. The variable change in political trust consists of the difference of political trust between wave 3 and wave 2. As the measurement of the data of wave 2 and wave 3 are only one year apart, the control variables for this model are considered constant.
2In terms of exogenous factors, there is no sign of multicollinearity. There are no high bivariate
correlations of >.60. The highest correlation is found between the education of one’s mother and father with a significant moderate correlation of .38.
Political Trust Battery Component Matrix Wave 2 (1 Component) n = 630 Component Matrix Wave 3 (1 Component) n = 725
Q29_1 “How much trust do you have in the Federal Council?”
.79 .81
Q29_2 “How much trust do you have in the national Parliament?”
.84 .86
Q29_3 “How much trust do you have in politicians?”
.82 .80
Q29_4 “How much trust do you have in parties?” .74 .72
According to a principal component analysis (PCA) the four items form a single
uni-dimensional scale with an eigenvalue above one for both wave 2 (eigenvalue 2.83) and wave 3 (eigenvalue 2.55). All items correlate positively with the first component. In both waves, trust in parliament has the strongest association (factor loading wave 2 .84, factor loading wave 3 .86). Moreover, both scales of wave 2 (Cronbach’s alpha = .81) and of wave 3 (Cronbach’s alpha = .81) are reliable. For the analysis, a new variable was constructed containing the four items above for both waves “political trust wave 2” (n = 701, M = 4.32,
SD = 1.01) and “political trust wave 3” (n = 725, M = 4.28, SD = .99).
Independent Variable
Media use. Media use was measured with three groups of variables from the data set. The
first group of media use variables consists of traditional sources of political information such as different TV news formats as well as different print newspapers: TV use in hours
(Minimum = 0, Maximum = 15, n = 724), various news formats (Minimum = 0, Maximum = 8,
n = 639) such as national news (M = 3.84, SD = 2.09), foreign news (M = 2.30, SD = 1.96,),
and other news (M = 1.91, SD = 1.50). Print newspapers are rarely used as a source of
on more than four days a week (M = 4.01, SD = 2.00, n = 568) followed by regional newspapers (M = 2.74 SD = 2.09, n = 687).
The second group of media variables includes passive forms of online communication such as reading news online (Minimum = 0, Maximum = 8, n = 568) on the websites of SRG, the Swiss national public broadcaster, (M = 2.67, SD = 2.09), daily regional papers (M = 2.18, SD = 2.01), tabloid press (M = 1.92, SD = 1.785), and of the free press (M = 3.26, SD = 2.49). Reading political news on social media (Minimum = 0, Maximum = 7, M = 2.55, SD = 1.77, n = 724) and e-government sources (Minimum = 0, Maximum = 7, n = 724) such as visiting a party website (M = 2.56, SD = 2.00) are also forms of passive online communication. The third and last group of variables used for this analysis consist of online political discussion variables (Minimum = 0, Maximum = 1). Namely, participating in an online
political discussion (M = .19, SD = .39, n = 724) and chatting or twittering about politics (M = .25, SD = 0.43, n = 724).
Control Variables
As discussed in the theory section, various factors in addition to media use might affect political trust and one’s media choice. To account for these affects, the following control variables are included in the analysis.
Gender. Gender was measured on a nominal level 0 = Female, 1 = Male. Of the respondents
who participated in both waves, 300 are male and 424 are female (n = 724, M = .41, SD = 0.49), showing a significant overrepresentation of females, χ² (1, n = 724) = 21.24, p <.000.
Age. Age was measured by asking the year of birth and a respondent’s current age.
Descriptive statistics show that the respondents in wave two are aged between 16 and 19 (n = 724, M = 17.61, SD = 1.08).
Education. Of the four variables measuring education, “Following an education”, “Current
education”, “Highest completed education” and “Educational level”, “Current education” is the most informative since the young respondents between 16 and 19 are not very likely to already have completed a higher educational level. Current education is measured on a 10-point scale with 1 = Primary school marking the lowest level of education and 10 =
University/ETH marking the highest level of education. Descriptive statistics of the variable
show that nearly half of the respondents are following a form of higher education such as an A-Level school (n = 381) and nearly the other half (n = 319) follow a form of lower
education. To differentiate between higher and lower education, the variable was recoded to a dichotomous level. The differentiation between high and low education was made between vocational school and A-level school, meaning the values 1 to 6 were recoded to 0 = Low
education and the values 7 to 12 were recoded to 1 = High education (n = 700, M = .54, SD =
.50).
Political interest. The political interest variables (see Table 3) were measured on a
seven-point scale reaching from 1 = Not at all interested to 7 = Very interested. Therefore, the variable “General political interest” had to be recoded since it was originally measured on a seven-point scale reaching from 1 = Very interested to 7 = Not at all interested. A principal component analysis (PCA) shows the four variables form a uni-dimensional scale with an eigenvalue above one (eigenvalue 2.83). Thus, all items correlate positively with the first component, whereas “Interest in national politics” has the strongest association (factor loading is .91). The four items build a reliable scale measuring political interest (Cronbach’s alpha = .86) and were summarized to a new variable “Political interest” (M = 4.34, SD = 1.30).
Political Interest Battery Component Matrix (1 Component) Q3_1 “How interested are you in international politics?” .83
Q3_2 “How interested are you in national politics?” .91
Q3_3 “How interested are you in local politics?” .77
Q25_1 “How interested are you generally in politics?” .85
SES. Since no income questions were asked, the variables “Education mother”, “Education
father” and “Social class” are used to get an idea of the social status. The variable “social class” asks respondents which social class the family the respondent grew up in belongs to. The variable was measured on a five-point scale reaching from 1 = Upper class, to 5 = Lower
class (n = 376, M = 2.55, SD = 0.69). To differentiate between higher and lower social class,
the variable was recoded to a dichotomous level with 0 = Lower SES and 1 = Higher SES. The values 1 and 2 were recoded to the value 1 and the values 3 to 5 to the value 0 (n = 376, M = 0.52, SD = 0.50). The variables education of mother and father of a respondent were
measured on a five-point scale reaching from 1 = Primary school to 5 = Don’t know. For this reason, the variables were recoded and 5 = Don’t know was assigned as missing values. Thus, the new maximum of the scale is 4 = University level. To make a distinction between high and low education, the variables are recoded to a dichotomous level consisting of 0 = Low
education, 1 = High education. 1 to 2 = Low education. 3 to 4 = Higher education (education
mother: n = 366, M = .50, SD = .50), (education father: n = 363, M = .56, SD = .50).
Political orientation. To account for bias in media selection due one’s political orientation,
the variable “Political orientation” is included as a control variable (Minimum = 0 Left,
Satisfaction. According to Hetherington (1999) and Chanley et al. (2000) the evaluations of
government affect political trust. To measure satisfaction, the two variables of the second wave “Satisfaction with Government” and “Satisfaction with Democracy”, which build a reliable scale were put together to one variable (Cronbach’s alpha = .75). (Minimum = 1,
Maximum = 7, n = 701, M = 5.05, SD = 1.12).
Approach
To answer H1.1, a multiple regression analysis is conducted for the three most frequently used news formats consisting of national news, foreign news and other news. To assess H1.2 another multiple regression is conducted. To analyze whether the effect of these formats on political trust are dependent on one’s preexisting level of political trust, an interaction effect of the respective TV news format and pre-existing political trust is included in the model. Further, to assess H1.3 again a multiple regression is run on TV news use. Regarding H2.1 and H2.2 about newspaper use, the two most frequently used print newspapers, regional newspaper and free newspapers are used for the regression models. To assess H3.1 another multiple regression is run for passive forms of online communication on political trust. Finally, in terms of H3.2, that online political discussion mediates the relationship between passive online forms of communication and political trust, the four steps to test mediation proposed by Baron and Kenny (1986) are conducted. The steps consist of testing the
significance of the relationship between the initial independent variable (IV) and dependent variable (DV) (Step 1), between the initial IV and the mediator (Step 2), between the mediator and the DV (Step 3), and between the mediator, and confirming the insignificance of the relationship between the initial IV and the DV in the presence of the mediator (Step 4).
Results
The outcome of the performed regressions to assess the hypotheses are presented below. It is to note, that for all regression analyses, statistics of collinearity were included, which showed neither low tolerance levels, nor high VIF values. This means, there is no sign of
multicollinearity between the control variables.
H1.1 predicted that higher daily TV use negatively affects political trust. The regression model with duration of TV use on trust in wave 3 is significant, F(11, 288) = 10.32, p < .000,
R2 = .283, however the coefficient is not significant, b* = -.048, t = -1.31, p = .192, (see Table 4). Thus, H1.1 is not supported.3
H1.2 predicted that for politically-trusting people, exposure to news formats on TV has a negative effect on political trust. A regression analysis shows a significant model F(16, 265) = 6.48, p < .000, R2 = .294. However only one of the three analyzed TV news formats, “other news”, shows a significant interaction effect of TV news and pre-existing political trust, b* = -.074, t = -2.26, p = .025. This means H1.2 is partly supported (see Table 4). However, the effect is only found in combination with the other news formats in the model and the effect is weak. A model only including “other news” as a media variable, is still significant, F(12, 253) = 8.78, p < .000, R2 = .294, but shows no significant effects of “other news”, b* = .056, t = -1.88, p = .061.4 These findings indicate that there might be problems of multicollinearity. However, the corresponding statistics do not support this claim.
Regarding H1.3, the hypothesis predicted the more one watches news formats on TV, the higher one’s political trust becomes. The conducted regression analysis shows a significant
3 Looking at TV use for the reduced model, the regression model of TV use on change in political trust is
significant, F(1, 699) = 4.63, p = .032, R2 = .007, showing a significant negative coefficient, b* = -.053, t = -2.15, p = .032. However, the effect is weak.
4 For the reduced model, a linear regression analysis of interaction effects of TV news formats and change
in political trust is significant, F(6, 614) = 37.83, p = .000, R2 = .273. However, no significant interaction
model F(13, 252) = 10.32, p < .000, R2 = .276. However, the model shows no significant effects for TV news formats on political trust, which is why H1.3 is not supported (see Table 4).5
Table 4. Regression model to predict political trust with TV use
Variable H1.1) TV use duration (n = 299) R2 = .283 H1.2) TV news for politically-trusting people (n = 265) R2 = .294 H1.3) TV news formats (n = 265) R2 = .276 β SE β SE β SE Intercept Gender Age Political interest Education mother Education father Current education Social status Political orientation Satisfaction
Political trust wave2 centered
TV use (hours)
National news formats Foreign news formats Other news formats National news centered National news centered* trust wave 2 centered Foreign news centered Foreign news centered* trust wave 2 centered Other news centered
1.550 -.030 -.006 .102* -.187 .036 .189 .110 .015 .152** .333*** -.048 - - - - - - - - .914 .106 .048 .042 .108 .108 .103 .103 .020 .048 .058 .037 - - - - - - - - .949 -.055 .027 .110* -.168 .116 .250* .089 .014 .152** .345*** - -.029 -.016 -.007 - - - - - .998 .113 .051 .047 .114 .114 .111 .110 .021 .050 .062 - .029 .034 .023 - - - - - 2.401* -.055 .017 .112* -.149 .108 .247* .107 .017 .150** .374*** - - - - -.032 .042 -.015 .017 -.028 .981 .113 .051 .046 .114 .113 .111 .110 .021 .050 .063 - - - - .030 .029 .034 .032 .035
5 For the reduced model, a regression of TV news formats on change in political trust shows no significant
Other news centered* trust wave 2 centered
- - - - -.074* .033
Note. * p <.05. ** p <.01. *** p <.001.
H2.1 predicted the higher one’s newspaper use as a source for political information, the higher one’s political trust becomes. A regression model shows, F(12, 278) = 9.87, p < .000,
R2 = .299, regional newspaper use has a significant positive effect on political trust, b* = .055,
t = 2.21, p = .028 (see Table 5). Albeit the weakness of the effect, H2.1 is partly supported.6
H2.2 predicted that for politically-trusting people, newspaper use as a source for political information increases political trust. The corresponding regression model is significant, F(14, 276) = 8.93, p < .000, R2 = .312, (see Table 5). However, the model neither shows a
significant interaction effect of newspaper use and political trust for regional newspapers, b* = .042, t = .09, p = .093, nor for free newspapers, b* = .000, t = .01, p = .990. Thus, H2.2 is not supported.7
Table 5. Regression model to predict political trust with print newspaper use
Variable H2.1) Newspaper print (n = 290) R2 = .299 H2.2) Politically-Trusting (n =290) R2 = .312 β SE β SE Intercept Gender Age Political interest Education mother Education father Current education 1.714 -.024 -.010 .076 -.179 .005 .148 .929 .108 .049 .045 .111 .111 .104 2.95** -.055 -.008 .107 -.167 .026 .139 .935 .108 .049 .046 .110 .111 .104
6 The regression model for reading regional and free print newspapers as a source of political information
on change in political trust is not significant, F(2, 664) = .47, p = .624. Thus, H2.1 for the reduced model is rejected.
7 A regression model including interaction effects of political trust in wave 2 and regional newspaper use as
well as the use of free newspaper shows no significant interaction effects, F(5, 661) = 47.76, p < .000. Thus, H2.2 for the reduced model is rejected.
Social status Political orientation Satisfaction
Political trust wave 2 centered Regional newspapers
Free newspapers
Regional_newspapers centered Regional_newspapers_centered* political_trust_wave_2
Free newspapers centered Free_newspapers_centered* Political_trust_wave_2 .067 .019 .164** .329 .055* -.046 - - - - .104 .020 .048 .058 .025 .026 - - - - .050 .020 .157** .343*** - - .047 .042 -.042 .000 .104 .020 .048 .059 - - .025 .025 .025 .025 Note. * p <.05. ** p <.01. *** p <.001.
The regression model concerning H3.1 is significant, n = 248, F(18, 230) = 6.19, p < .000, R2 = .326. However, no significant effects for passive online communication were found (see Table 6). For this reason, H3.1 is rejected.
Table 6. Regression model to predict political trust with passive forms of online communication
Variable
H3.1) Passive forms of online communication (n = 248) R2 = .326 β SE Intercept Gender Age Political interest Education mother Education father Current education Social status Political orientation Satisfaction
Political trust wave 2
.964 .012 .022 .059 -.096 -.046 .190 .061 .022 .141** .393*** 1.093 .121 .058 .055 .124 .122 .119 .114 .023 .053 .067
Website SRG
Website daily regional press Website local press
Website tabloid press Website free press
Reading political news on SNS Party website Online discussion Political blog Emailing politician -.005 .056 -.068 .004 -.017 -.009 -.017 - - - .029 0.30 .049 .031 .025 .034 .032 - - - Note. * p <.05. ** p <.01. *** p <.001.
Participating in an online political discussion
In Step 1 of the mediation model, the regression of passive online communication on political trust, ignoring the mediator, was weak but significant for reading political news on the SRG website, F(1, 566) = 5.50, p < .050, R2 = .010, b* = .049, t = 2.336, p = .020, (see Table 7). Step 2 showed that the regression of using the SRG website on the mediator, political discussion, was also significant, albeit weak, F(1, 566) = 19.76, p < .000, R2 = .034, b* = .040, t = 4.45, p < .000. However, as Step 3 shows, no significant effect of political discussion on political trust is found, which is why there is no mediation effect of political discussion,
F(1, 722) = .01, p = .913, R2 = .000.
Table 7. Mediation effect of participating in an online discussion on the relationship of using the website of
SRG as a passive form of online communication and political trust (n = 657)
Effect b* t p CI
Lower Upper
Step 1 .049 2.34 .020 4.00 4.26
Step 2 .040 4.45 .000 .10 .215
Step 3 -.010 -.11 .913 4.13 4.30
Note. b* = unstandardized coefficient; CI = confidence interval. Fit Step 1 F(1, 566) = 5.50, p < .050, R2 = .010. Fit Step 2 F(1, 566) = 19.76, p < .000, R2 = .034. Fit Step 3, F(1, 722) = .01, p = .913, R2 = .000
Chatting and Twittering
For chatting and twittering about politics, Step 1 of the mediation model shows again that visiting the website of SRG has a positive albeit weak effect on political trust F(1, 566) = 5.46, p = .020, R2 = .010, b* = .049, t = -.2.34, p = .020. However, Step 2 shows that the effect of visiting the SRG website on chatting and twittering for political purposes is not significant, F(1, 566) = 1.52, p = .218, R2 = .003. Therefore, there is no mediation effect of chatting and twittering about politics.
Table 8. Mediation effect of chatting and twittering about politics on the relationship of using the website
of SRG as a passive form of online communication and political trust
Effect b* t p CI
Lower Upper
Step 1 .049 2.34 .020 4.00 4.26
Step 2 .012 1.23 .218 -.007 .031
Note. b* = unstandardized coefficient; CI = confidence interval. Fit Step 1 F(1, 566) = 5.46, p = .020. Fit Step 2 F(1, 566) = 1.52, p = .218, R2 = .003.
The mediation analysis according to Baron and Kenny (1986) shows no significant mediation of online political discussion on the relationship of passive forms of political communication and political trust, despite significant bivariate correlations. For these reasons, H3.2 is also rejected.8
8 Regarding H3.1, the model for passive forms of online communication on change in political trust is not
significant, F(1, 549) = 1.85, p = .076, R2 = .023. Thus, H3.1 for the reduced model is rejected.
In terms of H3.2 for the reduced model, Step 1 of the mediation analysis shows no significant effects of passive forms of online communication on change in political trust. Thus, H3.2 for the reduced model is also rejected.
Conclusion & Discussion
First off, this study finds a negative effect of watching TV on the change in political trust. This means, the more one watches TV, the more stable one’s political trust becomes. A possible interpretation is that this is in line with cultivation theory. The more one watches TV, the more biased one’s view of the real world becomes, resulting in a state of a stable bias. Regarding the video malaise theory, TV use reducing change in political trust rather
contradicts the theory. Whereas the video malaise theory suggests a decline in political trust, this research finds that higher TV use leads to a smaller change in one’s political trust, but not to a decrease. However, for the extended model with political trust in wave 3 as the
independent variable, no effect of watching TV on political trust was found. Only a weak but significant interaction effect of watching “other news” and existing political trust was found. This means, the effect of watching “other news” on political trust is dependent on one’s existing level of political trust. However, the single effect of “other news” was not significant and one can question the meaning of this effect as it is unclear what “other news” means. This leads to a first suggestion for further research, to investigate the effect of specific news
formats on political trust. Does “other news” for instance stand for political satire? Regarding recent research on satire and political trust, this would allow to draw other interesting
conclusions, and to encourage future research (Baumgartner & Morris, 2006; Boukes & Boomgaarden, 2016).
In terms of the virtuous circle theory, no effects for watching TV news formats on political trust are found. Thus, the theory that watching TV news increases political trust cannot be supported. Also, there is no overall support for the virtuous circle theory for newspapers. However, again for a specific type of news source, for using regional newspapers, there is a positive effect on political trust, partly supporting the virtuous circle theory for newspaper use
as a source of political information. A possible explanation for finding an effect for regional newspapers might be due to the proximity to the reader (Maier et al., 2014). As discussed above, missing proximity causes the young to less use newspapers such as national newspapers.
Further, no effects were found for using the Internet as a source of political information on political trust. Additionally, discussing political content online does not mediate the relationship of using passive forms of online communication on political trust.
From a scientific point of view and regarding the research question of this study, it was shown that news media use can indeed affect political trust, despite finding no overall effects. This research supports previous findings that the media source matters for analyzing political attitudes. This because the effect of news media use differs not only between different media types but also between different news formats. Overall however, because of inexistent or low effects, news media use does not seem play a very meaningful role in affecting political trust when including control variables. Whereas cultivation theory can be supported, this study does not confirm the video malaise theory and finds no support for the claims in declining political trust among adolescents caused by news media use. Due to the positive effect of regional daily newspapers on political trust, this study takes a rather positive stance regarding news media use and political trust.
At the same time however, as no effects were found for national newspapers, and because passive online communication as a source of political information had no effect on political trust, this study does not support the praises of the Internet and its possibility to solve
declining political trust and engagement in a society. In terms of generalization of the results, it is to say that due to the weighting of the data, the sample is comparable to the population of Swiss adolescents. However, in generalizing these results for other countries, one should be cautious. As discussed in the method section, Switzerland is a special case due to its unique
political system and due to its strong public broadcasting system, which also affects the content of news media.
From a societal perspective, the results of this study implicate that there is no necessary concern that media use negatively affects political trust. This implicates that political trust is affected by other factors than media use. For example, existing research suggests, that personal discussion and political education foster political trust (Eveland, 2004). This is also in line with the non-significant results for online political discussion. Thus, direct
interpersonal discussions might be of greater importance for political trust than online political discussion (Eveland, 2004).
Regarding the implications of this study’s results from a political point of view, it should be of interest to politicians to focus on being close to their voters. Thus, they should pursue their task of representing the people and passing laws to attain coverage in regional newspapers to increase political trust, which is necessary for political leaders to make binding decisions (Gamson William, 1968). Moreover, in the light of this study which finds no significant effect for online news consumption as well as for online discussions, politicians might want to focus more on the personal contacts with their voters, since offline discussions might be more effective.
Lastly, there are some notable limitations to this study. As the data was collected in 2011 and 2012, regarding the vast development of the Internet and social media, more current data might show different effects, especially for hypotheses 3 regarding Internet use. Also, the use of some of the control variables such as education or political orientation can be weak as the young are still in their socialization process and therefore might not show big differences. Moreover, asking the young about their use of political news and how often they use media for political purposes is difficult to record. First, the problem of social desirability might
occur, and the used data do show indications of over reporting, as many of the means regarding media use are relatively high. Second, due to processes of mixing genres like infotainment (Moy & Hussain, 2011), it becomes harder to recognize political content in the first place. Thus, future research should focus more on precise media use tracking analysis instead of relying on self-reported data. Further, the content of the news programs used in this study can only be assumed by the orientation of the news source. This builds another
indication for future research, not only to analyze different media sources and formats, but the respective content, because news content can affect political trust as discussed above.
Bibliography
Aarts, K., Fladmoe, A., & Strömbäck, J. (2012). Media, political trust, and political knowledge. How media inform democracy: A comparative approach, 1, 98.
Aarts, K., & Semetko, H. A. (2003). The divided electorate: Media use and political involvement. Journal of Politics, 65(3), 759-784.
Avery, J. M. (2009). Videomalaise or virtuous circle? The influence of the news media on political trust. The international journal of press/politics, 14(4), 410-433.
Bakker, T. P., & De Vreese, C. H. (2011). Good news for the future? Young people, Internet use, and political participation. Communication research, 38(4), 451-470.
Banaji, S., & Cammaerts, B. (2015). Citizens of nowhere land: Youth and news consumption in Europe. Journalism Studies, 16(1), 115-132.
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal
of personality and social psychology, 51(6), 1173.
Baumgartner, J., & Morris, J. S. (2006). The Daily Show effect: Candidate evaluations, efficacy, and American youth. American Politics Research, 34(3), 341-367.
Bennett, W. L. (2008). Changing citizenship in the digital age. Civic life online: Learning how
digital media can engage youth, 1, 1-24.
Bfs. (2015a). Angebot Printmedien. Bundesamt für Statistik. Retrieved from
https://www.bfs.admin.ch/bfs/de/home/statistiken/kultur-medien-informationsgesellschaft-sport/medien/medienangebot-nutzung/printmedien.html Bfs. (2017a). Internetnutzung. Bundesamt für Statistik. Retrieved from
https://www.bfs.admin.ch/bfs/de/home/statistiken/kultur-medien- informationsgesellschaftsport/informationsgesellschaft/gesamtindikatoren/haushalte-bevoelkerung/internetnutzung.html
Blais, A. (2006). What affects voter turnout?. Annu. Rev. Polit. Sci., 9, 111-125.
Blumler, J. G., & Kavanagh, D. (1999). The third age of political communication: Influences and features. Political Communication, 16(3), 209-230.
Boukes, M., & Boomgaarden, H. G. (2016). Politician seeking voter: How interviews on entertainment talk shows affect trust in politicians. International Journal of
Communication, 10, 22.
Bühlmann, M., & Freitag, M. (2006). Individual and contextual determinants of electoral participation. Swiss Political Science Review, 12(4), 13-47.
Ceron, A. (2015). Internet, news, and political trust: The difference between social media and online media outlets. Journal of Computer-Mediated Communication, 20(5), 487-503.
Chanley, V. A., Rudolph, T. J., & Rahn, W. M. (2000). The origins and consequences of public trust in government: A time series analysis. Public opinion quarterly, 64(3), 239-256. Cortesi, S., Gasser, U., Genner, S., Graeff, E., Haduong, P., Junco, R., ... & Schomburg, M.
(2015). Youth and Online News: Reflections and Perspectives.
Dahlgren, P. (2009). Media and political engagement. Cambridge: Cambridge University Press.
Dalton, R. J. (2008). Citizenship norms and the expansion of political participation. Political
studies, 56(1), 76-98.
Dermont, C., & Stadelmann-Steffen, I. (2014). Die politische Partizipation der jungen
Erwachsenen. Erkenntnisse der St. Galler Stimmregisterdaten sowie Empfehlungen
zur Evaluation von easyvote. Universität Bern.
De Vreese, C. (2004). The effects of strategic news on political cynicism, issue evaluations, and policy support: A two-wave experiment. Mass Communication & Society, 7(2), 191-214.
Dumitrica, D. (2016). Imagining engagement: Youth, social media, and electoral processes. Convergence, 22(1), 35-53.
Earl Bennett, S., Rhine, S. L., Flickinger, R. S., & Bennett, L. L. (1999). "Video Malaise" Revisited: Public Trust in the Media and Government. Harvard International Journal
of Press/Politics, 4(4), 8-23.
Easyvote. (n.d.). Stimm- und Wahlbeteiligung von Jugendlichen in der Schweiz. Retrieved from https://www.easyvote.ch/ueber-uns/studien/uebersicht/
Esser, F., & De Vreese, C. H. (2007). Comparing young voters' political engagement in the United States and Europe. American Behavioral Scientist, 50(9), 1195-1213.
Entman, R. M. (2010). Improving newspapers’ economic prospects by augmenting their contributions to democracy. The International Journal of Press/Politics, 15(1), 104-125.
Eveland, Jr, W. P. (2004). The effect of political discussion in producing informed citizens: The roles of information, motivation, and elaboration. Political Communication,, 21(2), 177-193.
Forbrig, J. (Ed.). (2005). Revisiting youth political participation: Challenges for research and
Fraefel, M., Neuroni, A. C., & Brugger, J. (2012). Elektronische Partizipation in der Schweiz. E-Government und Netzpolitik im europäischen Vergleich. Nomos Verlagsgesellschaft mbH & Co. KG, 413-435.
Freitag, M. (2001). Das soziale Kapital der Schweiz: vergleichende Einschätzungen zu Aspekten des Vertrauens und der sozialen Einbindung. Swiss Political Science
Review, 7(4), 87-117.
Gamson William, A. (1968). Power and Discontent. Homewood, IL: Dorsey.
Gerbner, G. (1998). Cultivation analysis: An overview. Mass Communication and Society, 1(3-4), 175-194.
Gil de Zúñiga, H., Molyneux, L., & Zheng, P. (2014). Social media, political expression, and political participation: Panel analysis of lagged and concurrent relationships. Journal
of Communication, 64(4), 612-634.
Hahn, C. (1998). Becoming political: Comparative perspectives on citizenship education. Suny Press.
Hetherington, M. J. (1999). The effect of political trust on the presidential vote, 1968– 96. American Political Science Review, 93(2), 311-326.
Holt, K., Shehata, A., Strömbäck, J., & Ljungberg, E. (2013). Age and the effects of news media attention and social media use on political interest and participation: Do social media function as leveller?. European Journal of Communication, 28(1), 19-34.
Inglehart, R. (1997). Modernization and postmodernization: Cultural, economic, and political
change in 43 societies. Princeton University Press.
Kepplinger, H. M., Donsbach, W., Brosius, H. B., & Staab, J. F. (1986). Medientenor und Bevölkerungsmeinung: eine empirische Studies zum Image Helmut Kohls. Kölner
Zeitschrift für Soziologie und Sozialpsychologie, 38(2), 247-279.
Knoepfel, P., Papadopoulos, Y., Sciarini, P., Vatter, A., & Häusermann, S. (2014). Handbuch
Kruikemeier, S., van Noort, G., Vliegenthart, R., & de Vreese, C. H. (2014). Unraveling the effects of active and passive forms of political Internet use: Does it affect citizens’ political involvement?. New Media & Society, 16(6), 903-920.
Kunz, R., & Möller, J. E. (2011). Gleiche Chance für alle? Demokratische Partizipation Jugendlicher im Netz: Ressourcen und Motivationen. Düsseldorfer Forum Politische Kommunikation.
Kushin, M. J., & Yamamoto, M. (2010). Did social media really matter? College students' use of online media and political decision making in the 2008 election. Mass
Communication and Society, 13(5), 608-630.
Lee, N. J., Shah, D. V., & McLeod, J. M. (2013). Processes of political socialization: A communication mediation approach to youth civic engagement. Communication
Research, 40(5), 669-697.
Leitgeb, M., & Grammel, M. (2016). Überschätzte Jugend? – Medienkompetenz der Digital
Natives zwischen Zuschreibung und Realität.
Linder, W. (2012). Schweizerische Demokratie. Insitutionen – Prozesse – Perspektiven. 3.Überarbeitete Auflage. Haupt Verlag.
Luskin, R. C. (1990). Explaining political sophistication. Political Behavior, 12(4), 331-361. Maier, W. A., Leonarz, M., & Bossart, S. (2014). Politikberichterstattung in Gemeinden und
Bezirken Eine Übersicht zu Regionalmedien.
McLeod, J. M., Zubric, J., Keum, H., Deshpande, S., Cho, J., Stein, S., & Heather, M. (2001, August). Reflecting and connecting: Testing a communication mediation model of civic participation. In annual meeting of the Association for Education in Journalism
and Mass Communication, Washington, DC.
Mishler, W., & Rose, R. (2001). What are the origins of political trust? Testing institutional and cultural theories in post-communist societies. Comparative political studies, 34(1), 30-62.
Moy, P., & Hussain, M. M. (2011). Media influences on political trust and engagement. Oxford
handbook of American public opinion and the media, 220-235.
Moy, P., & Pfau, M. (2000). With malice toward all?: The media and public confidence in
democratic institutions. Greenwood Publishing Group.
Mutz, D. C., & Reeves, B. (2005). The new videomalaise: Effects of televised incivility on political trust. American Political Science Review, 99(01), 1-15.
Nccr democracy. (n.d.). IP 10 (Phase II): Die Mediatisierung politischer Einstellungen - Erziehung zu demokratischen Bürgern in einer multi-medialen Gesellschaft. Retrieved from http://www.nccr-democracy.uzh.ch/forschung/phaseII/module-3/ip-10
Newton, K. (1999). Mass media effects: mobilization or media malaise?. British Journal of
Political Science, 29(04), 577-599.
Newton, K. (2001). Trust, social capital, civil society, and democracy. International Political
Science Review, 22(2), 201-214.
Norris, P. (2000a). A virtuous circle: Political communications in postindustrial societies. Cambridge University Press.
Norris, P. (2001). Digital divide: Civic engagement, information poverty, and the Internet
worldwide. Cambridge University Press.
Norris, P. (2000b). The impact of television on civic malaise. Disaffected democracies: What’s
troubling the trilateral countries, 231-251.
Nye, J. S., Zelikow, P., & King, D. C. (1997). Why people don't trust government. Harvard University Press.
Pasek, J., Kenski, K., Romer, D., & Jamieson, K. H. (2006). America's youth and community engagement: How use of mass media is related to civic activity and political awareness in 14-to 22-year-olds. Communication Research, 33(3), 115-135.
Patterson, T. E. (2000). Doing well and doing good: How soft news and critical journalism are
about it. Joan Shorenstein Center on the Press, Politics and Public Policy, John F.
Kennedy School of Government, Harvard University.
Pinkleton, B. E., Austin, E. W., Zhou, Y., Willoughby, J. F., & Reiser, M. (2012). Perceptions of news media, external efficacy, and public affairs apathy in political decision making and disaffection. Journalism & mass communication quarterly, 89(1), 23-39.
Prior, M. (2007). Post-broadcast democracy: How media choice increases inequality in
political involvement and polarizes elections. Cambridge University Press.
Putnam, R. D. (2000). Bowling alone: America’s declining social capital. Culture and
politics (pp. 223-234). Palgrave Macmillan US.
Putnam, R. D. (1996). The strange disappearance of civic America. Policy: A Journal of Public
Policy and Ideas, 12(1), 3.
Rentsch, M. (2013). Unpolitisch, uninformiert und verdrossen?. tv diskurs. Verantwortung in
audiovisuellen Medien, 17, 36-39.
Robinson, M. J. (1976). Public Affairs Television and the Growth of Political Malaise: The Case of" The Selling of the Pentagon". The American Political Science Review, 70(2), 409-432.
Scheufele, D. A. (1999). Framing as a theory of media effects. Journal of
communication, 49(1), 103-122.
Schoon, I., & Cheng, H. (2011). Determinants of political trust: a lifetime learning model. Developmental psychology, 47(3), 619.
Shah, D. V., Cho, J., Eveland Jr, W. P., & Kwak, N. (2005). Information and expression in a digital age: Modeling Internet effects on civic participation. Communication
research, 32(5), 531-565.
Shah, D. V., Cho, J., Nah, S., Gotlieb, M. R., Hwang, H., Lee, N. J., ... & McLeod, D. M. (2007). Campaign ads, online messaging, and participation: Extending the communication mediation model. Journal of communication, 57(4), 676-703.
Sobieraj, S., & Berry, J. M. (2011). From incivility to outrage: Political discourse in blogs, talk radio, and cable news. Political Communication, 28(1), 19-41.
Steele, J. R., & Brown, J. D. (1995). Adolescent room culture: Studying media in the context of everyday life. Journal of youth and adolescence, 24(5), 551-576.
Strömbäck, J., Djerf-Pierre, M., & Shehata, A. (2016). A question of time? A longitudinal analysis of the relationship between news media consumption and political trust. The
International Journal of Press/Politics, 21(1), 88-110.
Strömbäck, J., Djerf-Pierre, M., & Shehata, A. (2014). The Changing Dynamics of News Media Consumption and Political Distrust: A Longitudinal Analysis. In ECREA 2014 5th
European Communication Conference, Lisboa, Portugal, 12-15 November 2014.
Strömbäck, J., & Johansson, B. (2007). Electoral cycles and the mobilizing effects of elections: A longitudinal study of the Swedish case. Journal of Elections, Public Opinion and
Parties, 17(1), 79-99.
Taber, C. S., & Lodge, M. (2006). Motivated skepticism in the evaluation of political beliefs. American Journal of Political Science, 50(3), 755-769.
Tolbert, C. J., & McNeal, R. S. (2003). Unraveling the effects of the Internet on political participation?. Political research quarterly, 56(2), 175-185.
Tolbert, C. J., & Mossberger, K. (2006). The effects of e-government on trust and confidence in government. Public administration review, 66(3), 354-369.
Uslaner, E. M. (1999). Trust but verify: Social capital and moral behavior. Social Science
Information, 38(1), 29-55.
Valkenburg, P. M., & Peter, J. (2013). The differential susceptibility to media effects model. Journal of Communication, 63(2), 221-243.
Van Deursen, A. J., & Van Dijk, J. A. (2014). The digital divide shifts to differences in usage. New media & society, 16(3), 507-526.
Yamamoto, M., Kushin, M. J., & Dalisay, F. (2015). Social media and mobiles as political mobilization forces for young adults: Examining the moderating role of online political expression in political participation. New Media & Society, 17(6), 880-898.
Appendix
Survey Wave 2 NCCR IP10 2011
COHORTSTUDY PROJECT 23835
GERMAN QUESTIONNAIRE - VERSION 2 Wave 2 2011
QUOTA
HARD QUOTA:
TOTAL GROSS N = 1657
QUOTA 5: Language
Code 1 = German (SCRIPTWRITER: IF SAMPLE VARIABLE “language”=1, OFFER THIS QUESTIONNAIRE)
Code 2 = French (SCRIPTWRITER: IF SAMPLE VARIABLE “language”=2, DO NOT OFFER THIS QUESTIONNAIRE)
Scriptwriter: in the SPSS datafile of wave 1 2010, the code for German language = 7 and for French language = 12. Which codes are the correct ones to use?
SOFT QUOTA (SCRIPTWRITER: THESE ARE NOT HARD QUOTA, BUT PLEASE DO MAKE SURE WE CAN TRACK THE RESPONSE PER QUOTA-VARIABLE IN MONITORING THE FIELDWORK):
QUOTA 1: Geslacht_rp Code 1 = male Code 2 = female QUOTA 2: Leeftijd_rp Code 15 = 15 Code 16 = 16 Code 17 = 17 Code 18 = 18 Code 19 = 19 Code 20 = 20
è Scriptwriter: please base this variable on question S1
QUOTA 3: Region
Code 1 = Suisse Romande Code 2 = Alpen und Voralpen Code 3 = Westmittelland Code 4 = Ostmittelland
QUOTA 4: Education Code 1 = low
Code 2 = middle and high
INTERVIEW DURATION
SCRIPTWRITER: CAPTURE THE INITIAL START-TIME AND END-TIME OF THE INTERVIEW PER RESPONDENT (SO THE WHOLE INTERVIEW DURATION).
S1 ASK: ALL
S Wie alt sind Sie?
1. 15 Jahre 2. 16 Jahre 3. 17 Jahre 4. 18 Jahre 5. 19 Jahre 6. 20 Jahre 1 ASK: ALL
O In der Schweiz gibt es viele ungelöste Probleme. Welches sind Ihrer Meinung nach gegenwärtig die wichtigsten Probleme für unser Land? Geben Sie bis zu drei Probleme an.
1. OPENEND
2. OPENEND
3. OPENEND
SCRIPTWRITER: RESPONDENTS ARE ALLOWED TO SKIP THIS QUESTION WITHOUT PROVIDING AN ANSWER
2 ASK: ALL
O Wenn Sie nun an die Berichterstattung in den Medien denken. Was ist laut den Medien das wichtigste Problem in der Schweiz?
OPENEND
SCRIPTWRITER: RESPONDENTS ARE ALLOWED TO SKIP THIS QUESTION WITHOUT PROVIDING AN ANSWER
