Abstract
In this paper, we explore the complex relationship between news use and intentional news avoidance. Based on a survey conducted (N = 2,798) in the Netherlands and a latent profile analysis, we first identified nine different types of news users. We find that news avoidance differs across those types. While people that belong to the profiles that use news less frequently or through less established channels report that they engage more in news avoiding behavior, also news omnivores frequently avoid the news. Mainly individuals that belong to profiles where traditional media use features most prominently report never avoiding the news. These findings confirm the idea that intentional news avoidance is not a simple concept that divides people into those that consume and those that do not consume news, but is rather a more complex and dynamic phenomenon.
1 Introduction
The relationship between news avoidance and news use is more complicated than is often assumed. While scholars have equated avoidance with low levels of news use, recent research has suggested that news avoidance is a more dynamic and multifaceted phenomenon, and that people who have higher levels of media use also deliberately avoid the news (Vandenplas et al., 2021). However, research into the relation between news use and news avoidance is scarce and inconclusive at best. It often does not acknowledge that the latter is a more multi-faceted phenomenon (for a similar argument, see Villi et al., 2022). In this article, we explore the relationship between news use and intentional news avoidance and the degree to which different types of news users differ in their levels of intentional news avoidance. Here, we move beyond previous research that focuses on the relationship between the two and which relies on simple conceptualizations of news consumption in terms of low versus high (Damstra et al., 2023; Betakova et al., 2024). More specifically, we rely on a large survey among a representative sample of the Dutch population, where we ask about the use of a large range of news sources in a more encompassing way, as well as news avoidance. Using latent profile analyses, we identify different types of news users and subsequently compare their news avoidance behavior. Overall, our results reveal that news avoidance is indeed present among different types of news users. While people that can be considered ‘news minimalists’ do report most often that they engage in news avoiding behavior at any level, also people who consume a lot of news (‘news omnivores’) report a large amount of regular avoidance. It demonstrates that avoidance coincides with the (combined) use of different types and modes of news sources. In particular, news users who get their news through online channels report high levels of avoidance.
2 News repertoires and news avoidance
We live in a high choice media environment (Van Aelst et al., 2017) – information on any topic is one click away and available 24/7. Navigating the large amounts of news is not self-evident: many citizens ‘tune out’, either occasionally or not, and avoid the news (De Bruin et al., 2021). Concerns about high levels of news avoidance have frequently been voiced and recent inventarizations indeed indicate that news avoidance is on the rise in many countries, including the Netherlands (Newman, 2024). Reasons can be multiple and this behavior can stem, for example, from feelings of being overwhelmed, be due to a lack of time, or simply disinterest. Furthermore, it is often related to political perceptions, such as political efficacy, trust, and interest (Betakova et al., 2024) and connected to specific concerns with the drawbacks of technological innovation (Woodstock, 2014a). News avoidance often has a negative connotation – as it arguably makes individuals less informed and thus less able to execute well their roles as citizens in a democratic society (Skovsgaard and Andersen, 2020). However, research is not clear-cut on the impact of news avoidance on knowledge. Damstra and colleagues (2023), for instance, find that intentional avoidance is negatively related to the accuracy of beliefs on contested issues, but not to more general political knowledge. Studies have furthermore also pointed to potential positive consequences. Research on news use during the COVID-19 pandemic, for example, demonstrates that avoidance is positively associated with mental well-being (De Bruin et al., 2021) and political participation (Ohme et al., 2023, see also Woodstock, 2014b).
Conceptually, news avoidance is not an uncontested phenomenon. In particular, its relationship with news use is far from evident. In some studies, avoidance and use are considered two sides of the same coin. In those instances, avoidance equals very low levels of news use and some relative or absolute cut-off point is used to distinguish avoiders from non-avoiders (e.g., Strömbäck, 2017; Wolfsfeld et al., 2016). In other studies, news consumers are clustered into several groups, one of them being identified as news minimalists or news avoiders (e.g., Bos et al., 2016; Strömbäck et al., 2018). However, when a self-reported measure of avoidance is being used – that is asking people directly whether they avoid the news – the relationship between news avoidance and news use turns out to be more complicated. Toff and Kalegoropoulos (2020), for example, find a weak link between media use and news avoidance. A useful distinction that might partly resolve these two contradictory approaches is one between intentional and unintentional avoidance. Skovsgaard and Andersen (2020) make this distinction on conceptual grounds and argue that different antecedents underlie those different types of avoidances. Intentional avoidance stems from actively disliking the negativity of news, distrusting in media, or being overwhelmed. This type of avoidance might have a more dynamic nature and individuals might be involved in this behavior more or less over time. Unintentional avoidance is driven by a relative preference for other media content instead of news that is subsequently sustained by algorithms.
However, while low news use might be a consequence of both intentional and unintentional avoidance, sustained low news consumption is likely to have a habitual nature and is mostly a consequence of the latter. In other words, minimal news use might mainly reflect unintentional news avoidance. Asking people explicitly about the degree to which they avoid the news probably captures the more manifest, and thus intentional avoidance. This intentional avoidance might relate to minimal news use as well, but it could also be associated with more heavy users that consciously navigate through their rich news diet and sometimes decide to ‘tune out’, for example, to cope with feelings of information overload (Holton and Chyi, 2012). The latter would be in line with recent findings of Betakova et al. (2024), who demonstrate that in Austria, only a small minority of citizens combine low levels of actual news consumption with high levels of intentional news avoidance. Here, we further explore the relationship between news use and intentional avoidance. We are not only interested in knowing whether intentional avoidance is indeed coinciding with a minimal news diet but also take a broader perspective; we investigate whether different individuals with different news repertoires vary in intentional avoidance behavior. The notion of news repertoires has been extensively used to describe individuals’ patterns of media use to fulfill their needs for information on current affairs. Repertoires are more than the sum of the media individuals use and are considered to provide consistent and subjective orientations, e.g., towards quality news or local affairs (Peters and Schrøder, 2018). Important in this respect is that media sources include, but are not limited to traditional news media, especially in the high-choice media environment we currently live in (Schrøder, 2015; Swart et al., 2017).
Thus, we pose the following research question:
RQ1: How are different repertoires of news consumption related to levels of intentional news avoidance?
3 Method
Study design
For this paper, we rely on a survey that was conducted by ISO-certified research company I&O Research among a representative part of the Dutch population in the run-up to the 2022 Dutch local elections. On the one hand, election campaigns might heighten political interest and thus news consumption. On the other hand, the abundance of political information might yield higher levels of fatigue and thus avoidance. However, here, we are not primarily interested in absolute levels of consumption, making this potential bias less problematic. A stratified sample from the I&O’s panel was drawn by gender, age, region, and education level. About 5,752 panel members were invited. The relevant parts of the questionnaire were fully completed by 2,798 panel members, a response rate of 48.6 %. The mean age of the sample is 53.7 (SD = 16.7) and 49.6 % identified as female. The survey was in the field between March 9 and March 22. In this survey, a wide range of questions on news use were asked. More specifically, for 24 different news sources, both traditional as well as more hybrid ones, we asked the frequency of use in the past week on a seven-point scale (categories ‘never’, ‘one time per week’, ‘two times per week’, ‘three times per week’, ‘more than three times per week’, ‘daily’ and ‘multiple times per day’). We deliberately included both more established news sources, but also a range of alternative and maybe less intuitive ones. We recorded the variables on a 0 to 6 scale. Table 1 provides a complete overview of the sources and their average use and also includes respondents that did not complete the full survey. We see that most people rely on news sites and television news for their news. Newspapers, radio, and talk shows on television are also used somewhat frequently. Alternatives like alternative media, online talk shows, or political parties’ own channels are less frequently used.
Descriptive statistics news source use.
Number |
Source |
M |
SD |
1 |
online news sites or apps from established media |
4.05 |
2.13 |
2 |
news collection site |
1.09 |
1.85 |
3 |
social media |
2.12 |
2.40 |
4 |
alternative media |
0.23 |
0.92 |
5 |
private communication apps |
2.15 |
2.42 |
6 |
newsletters |
1.24 |
1.69 |
7 |
national newspaper |
2.10 |
2.33 |
8 |
regional newspaper |
1.62 |
2.17 |
9 |
local newspaper |
0.94 |
1.32 |
10 |
television news from public broadcast |
3.80 |
2.01 |
11 |
television news from commercial broadcast |
2.26 |
2.20 |
12 |
television news from regional or local broadcast |
0.93 |
1.63 |
13 |
radio news |
2.19 |
2.30 |
14 |
magazines |
0.34 |
0.92 |
15 |
podcasts from news media |
0.34 |
1.04 |
16 |
own media channels political parties |
0.13 |
0.65 |
17 |
blogs |
0.34 |
1.04 |
18 |
websites (local) political parties |
0.18 |
0.67 |
19 |
talkshows |
2.06 |
1.98 |
20 |
current affairs programmes |
1.75 |
1.87 |
21 |
online talkshows |
0.19 |
0.77 |
22 |
documentaries |
1.10 |
1.37 |
23 |
Youtube channels |
0.75 |
1.46 |
24 |
satirical current affairs programmes |
1.40 |
1.69 |
N = 2,886 respondents
To identify different types of news users, we rely on a latent profile analysis (see Vliegenthart et al., 2024 for a similar approach). Latent profile analysis is a clustering approach that groups individuals based on a range of continuous variables (here: use of different sources) to identify different clusters or subgroups that are homogenous in a population (i.e., news repertoires). This type of approach is useful in identifying latent classes based on interval variables). We rely on the TidyLPA package in R and do not specify the number of profiles in advance. Previous research has demonstrated that typically four or five types of media repertoires can be identified (Andersen et al., 2022; Bos et al. 2016; Strömbäck et al., 2018), but these studies have usually used a less elaborate and diverse set of potential news sources that are considered. We compare models from six to ten profiles and the appropriate number is identified based on fit statistics (Akaike Info Criterion and Bayes Info Criterion). For the most optimal solution, we report the profile count and proportions. We also report the average probabilities for the most likely membership for each profile. Based on those scores, each respondent can be assigned to one of the profiles. In our data, this means having a certain news repertoire. Average scores on each of the earlier identified sources can be used to provide meaningful descriptions for each of the profiles.
Model comparison of models with different number of profiles.
Profiles |
AIC |
BIC |
6 |
233319.45 |
234351.85 |
7 |
233337.76 |
234519.35 |
8 |
233616.32 |
234947.10 |
9 |
231254.64* |
232734.61* |
10 |
231341.03 |
232970.19 |
Note: *Lowest score indicates best fitting model.
Finally, we compare the different types of news users in terms of their background characteristics, and, in particular, their levels of news avoidance. The latter was captured by the following question: Do you ever avoid the news?, with answer categories ‘No, never’ (34.8 %), ‘Yes, sometimes’ (50.4 %), ‘Yes, regularly’ (11.5 %), and ‘Yes, always’ (3.3 %). We rely on cross-tabs to explore the potential relationship between type of news use and news avoiding behavior.
4 Results
The first step in the identification of news users is the performance of latent profile analysis. Table 2 provides a comparison of model fit statistics for models with 6, 7, 8, 9, and 10 profiles. AIC and BIC both suggest that a model with nine profiles has the best fit.
Figure 1 presents the average scores on each item from each of the nine profiles. Based on these scores, all profiles have been labeled. The labels, as well as the size of each profile and its average probability of membership, are presented in Table 3.

Mean scores of different profiles on news sources.
Note: For sources see Table 1.
The nine profiles have a largely intuitive interpretation and show clear variation in use of individual news sources. The first, largest, group is labeled mainstream users. It consists of consumers that rely mainly on online news sites from established media and (public) television news and hardly use any other sources. It comprises around a third of the total sample. The second group covers over 16 % of the sample and consists of people that mainly rely on (public) television news broadcasts, talk shows and current affairs programs. We label this group television users. The third profile is the smallest (1.7 %) and consists of individuals who score comparatively high on consumption across the board. They can be considered omnivores. The fourth category brings together the minimalists who score low on each of the sources. This group is considerable comprising 22 % of the total sample. The fifth profile (roughly 9 % of the total sample) resembles the first profile, but users combine mainstream news use with private communication through messaging apps. The sixth group is small (3.4 %) and consists of people who make use of all kinds of different online sources – including social media and blogs. The seventh group is relatively small as well (6 %) and resembles the television profile, but scores particularly high on television news. The eighth group has a very particular profile – it consists of people who rely on alternative media and score low on the use of other sources, except for messaging apps. The group is small with around 2.5 % of the total sample. Finally, the ninth group consists of people who combine online news sites with the use of podcasts. We label this group online-podcasts and it consists of 4 % of the sample.
Our research question relates to the relationship between different repertoires of news consumption and intentional news avoidance. Is that behavior indeed more strongly present among those who already score low in news use (for example, among minimalists)? Table 4 provides the answer. We see that news avoidance indeed differs significantly across different types of news users. Maybe not surprisingly, news minimalists report higher levels of news avoidance than average (80 % of the respondents in that category answer they at least occasionally avoid the news, compared to 65 % on average) and they score highest on ‘almost always’. Also, alternative media users are frequent news avoiders – this might well be a consequence of their skeptical attitude towards traditional news sources. 73 % report to at least sometimes avoiding the news.
Profiles derived from LPA.
Profiles |
Label |
N(%) |
P(membership) |
1 |
mainstream |
965 (33.44 %) |
0.91 |
2 |
television |
488 (16.91 %) |
0.90 |
3 |
omnivores |
49 (1.70 %) |
1.00 |
4 |
minimalist |
651 (22.56 %) |
0.96 |
5 |
interpersonal-mainstream |
258 (8.94 %) |
0.83 |
6 |
online |
99 (3.43 %) |
0.98 |
7 |
television news |
182 (6.31 %) |
0.97 |
8 |
alternative |
79 (2.74 %) |
1.00 |
9 |
online-podcasts |
115 (3.98 %) |
0.99 |
|
total |
2,886 (100 %) |
|
Also, users that belong to different other profiles demonstrate considerable levels of avoidance. Many omnivores avoid the news sometimes (40 %) and regularly (26 %). Interestingly enough, it is mainly individuals who belong to profiles where traditional media use features most prominently that report never avoiding the news (e.g., television, interpersonal-mainstream, and television news). The rise of online and social media has on the one hand increased the amount of information present, but makes news consumers also more frequently decide to not consume the news.
5 Conclusion
News avoidance is not limited to consumers with low levels of news use. The results of our investigation demonstrate that there is indeed a weak link between (different degrees of) intentional news avoidance and belonging to a group of respondents that can be labeled news minimalists (and also alternative news users), but differences to other groups of news users are small. Furthermore, we see that omnivores engage more often in regular news avoidance and so are alternative news users. It is important to realize however, that the vast majority of our respondents rely on ‘mainstream’ media outlets, and alternative sources (in the broadest sense of the word) play only a minor role in the media diets of most news consumers.
Relation between news repertoires and intentional news avoidance.
|
Intentional news avoidance |
|||
|
no, never |
yes, sometimes |
yes, regularly |
yes, almost always |
mainstream (N) |
312 |
525 |
94 |
5 |
% |
33.33 |
56.09 |
10.04 |
0.53 |
television (N) |
201 |
251 |
24 |
2 |
% |
42.05 |
52.51 |
5.02 |
0.42 |
omnivores (N) |
14 |
19 |
12 |
2 |
% |
29.79 |
40.43 |
25.53 |
4.26 |
minimalist (N) |
125 |
296 |
134 |
73 |
% |
19.90 |
47.13 |
21.34 |
11.62 |
interpersonalmainstream (N) |
123 |
110 |
14 |
0 |
% |
49.8 |
44.53 |
5.67 |
0 |
online (N) |
38 |
47 |
13 |
0 |
% |
38.78 |
47.96 |
13.27 |
0 |
television news (N) |
90 |
75 |
9 |
1 |
% |
51.43 |
42.86 |
5.14 |
0.57 |
alternative (N) |
20 |
33 |
15 |
7 |
% |
26.67 |
44.00 |
20.00 |
9.33 |
online-podcasts (N) |
51 |
55 |
7 |
1 |
% |
44.74 |
48.25 |
6.14 |
0.88 |
Total (N) |
974 |
1,411 |
322 |
91 |
% |
34.81 |
50.43 |
11.51 |
3.25 |
Note: N = 2,798, χ2 = 391.72, df = 24, Cramer’s V = .22
This study is thus in line with previous studies that argue that the relationship between use and avoidance is indeed not strong (Toff and Kalegoropoulos, 2020), but is also unique in the sense that it provides a more detailed account of this relationship by considering a wide range of non-mainstream sources of news and focusing on news repertoires. This study uncovers an interesting paradox: omnivores are both heavy news consumers and avoiders at the same time. More specifically, this study adds insight and nuance to an important topic by comparing levels of avoidance across different types of news users relying on a wide range of potential sources that people use for their news supply. As a general observation, we see that people who belong to profiles where traditional, mostly offline, media sources are important, engage less in avoidance, while members of profiles that are characterized by online and social media sources do more frequently. This finding aligns with the idea that passive social media use might decrease mental well-being and intentional avoidance might mitigate this negative impact. News consumers compensate for the opportunities to obtain instantly vast amounts of news with the deliberate choice to sometimes ‘tune off’. Our study is not without shortcomings – most of them stemming from the its single-country, cross-sectional nature. Future research should explore in detail the dynamic interactions between news use and intentional avoidance, as well as (potentially different) underlying mechanisms and antecedents of avoidance by different types of news users in different political and media contexts.
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