Research Article

Threat and Worry (Often) Go Together; Salience Stands Apart – Patterns Across Descriptives, Correlations, and Ideological Associations

Linda C. Bomm1 , Paul K. Bergmann2 , Bert N. Bakker1

Social Psychological Bulletin, 2026, Vol. 21, Article e16605, https://doi.org/10.32872/spb.16605

Received: 2025-01-15. Accepted: 2025-10-08. Published (VoR): 2026-05-18.

Handling Editor: David S. March, Florida State University, Tallahassee, FL, USA

Corresponding Author: Linda C. Bomm, Amsterdam School of Communication Research, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands. E-mail: l.bomm@uva.nl

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Supplementary Materials: Code, Data [see Index of Supplementary Materials]

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License, CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Societal threat perception, worry, and issue salience are central to research in psychology and political science, and previous research suggests considerable overlap between the three measures. Nevertheless, they have not yet been empirically distinguished. This study addresses whether the empirical patterns of these three measures are consistent and whether they yield congruent conclusions about political ideology across twelve societal issues. Using data from a diverse Dutch sample (N = 1863), we first show that threat and worry, but not salience, produce similar empirical patterns in terms of means and correlations, as citizens find issues more important than threatening or worrying. Next, we find that, overall, threat and worry correlate similarly with ideology—but also highlight exceptions—whereas issue salience often overestimates this relationship (Type M error) but rarely reverses its direction (Type S error). These findings clarify the unique roles of threat, worry, and issue salience in (political) psychology, offering a framework for future research on the threat-politics link.

Keywords: societal threat perception, worry, issue salience, right-wing ideology, threat-politics link

Highlights

  • Societal threat perception, worry, and issue salience are central to research in psychology and political science, yet, their construct and predictive validity remain underexamined.

  • First, using data from a Dutch sample (N = 1863), we assess construct validity, and show that threat perception and worry reflect the same underlying construct, distinct from salience, as citizens find issues more important than threatening or worrying.

  • Second, we evaluate predictive validity by analyzing associations with right-wing ideology, and find that threat perception and worry correlate similarly with ideology, whereas issue salience often overestimated this relationship (Type M error) but rarely reverses its direction (Type S error).

Societal threat perception—the feeling and perception that something aversive is going to happen (Brandt & Bakker, 2022)—has been at the core of research in psychology for decades (see Crawford, 2017, for a review). Previous literature has placed limited emphasis on the relation of different measures of threat perception and its adjacent constructs to one another (for exceptions, see Onraet et al., 2013; Van Hiel, 2022). As a consequence, research on societal threat perception employs a variety of different operationalizations of the construct (Jost, 2017; Onraet et al., 2013). Some studies ask about the perceived threat posed by an issue (e.g., Kahn et al., 2022), while others assess the extent to which people are worried about an issue (e.g., Brandt et al., 2021). There is also the possibility that the adjacent construct of issue salience (Leeper & Robison, 2020) captures—at least partly—people’s worries and threat perceptions (e.g., Boninger et al., 1995; Jennings & Wlezien, 2011; Krosnick, 1990). To date, no research has systematically related threat perception measures to one another or to issue salience, leaving an important gap in the literature. We address this gap, responding to calls for more rigorous assessments of psychological constructs (Flake & Fried, 2020), and answer the research question: To what extent do threat, worry, and issue salience measures produce similar empirical patterns?

When measuring threat perception, threat and worry are both commonly employed measures for threat perception. Some researchers ask participants to what extent they feel “threatened” by a societal issue (e.g., Conway et al., 2023; Hornsey & Pearson, 2024; Kahn et al., 2022; Poushter & Huang, 2020; Smith & Kim, 2026). For example, Conway et al. (2023) measure threat perception with the item: “Thinking about [a societal issue] makes me feel threatened.” Others measure threat perception by asking how “worried” participants are about an issue (e.g., Arikan, 2023; Brandt et al., 2021; Conway, 2026; Onraet et al., 2013; Woods, 2011). For example, Brandt et al. (2021) use the item: “To what degree are you worried about the following situations: [a societal issue]?”1. Yet, Van Hiel (2022) argues that threat perception consists of two distinct psychological responses: worry, a more cognitive and adaptive process, and anxiety, a more maladaptive reaction reflecting deeper, existential responses to potential harm (see also Woods, 2011). As the reviewed literature suggests, the interchangeable use of threat and worry, as well as diverging perspectives on their distinction, highlight the need for a more systematic assessment.

It is plausible that issue-specific threat and worry measures also capture the perceived importance people attach to societal issues. In public opinion research, such importance is typically studied as issue salience. Issue salience has been defined as “the degree to which a person is passionately concerned about” an issue (Krosnick, 1990, p. 60), or as “an individual’s subjective sense of the concern, caring, and significance” of an issue (Boninger et al., 1995, p. 62). These definitions suggest a motivational and evaluative orientation toward an issue, which may be emotionally charged or even threat-relevant. The survey measures of issue salience further support this interpretation. Items such as “What is the most important problem facing the country?” tend to frame issues in negatively valenced or problem-oriented terms (Jennings & Wlezien, 2011). In such cases, the salience of an issue may reflect not just its cognitive priority, but also the degree of worry or perceived threat. The conceptual and measurement-based overlaps discussed here raise the possibility that individuals may simply find the issues important that they are threatened by or worried about, and vice versa. In summary, it is unclear whether threat and worry can both be used as proxies for one another, and to what extent these measures may also reflect issue salience. For threat, worry, and issue salience to be appropriate proxies for one another, their associations with political ideology should be highly similar (e.g., Brandt et al., 2021; Kahn et al., 2022; Leeper & Robison, 2020; Onraet et al., 2013). If threat, worry, and issue salience have different associations with political ideology, treating them as equivalent proxies could result in a Type S (sign) or Type M (magnitude) error (Gelman & Carlin, 2014). A Type S error would occur when the sign of the ideology association reverses (e.g., from positive to negative), depending on whether threat, worry, or issue salience are measured. A Type M error would arise when the effect size differs across the three measures. The presence of Type S or Type M errors would affect the conclusions people draw about the threat-politics link, and add further inconsistency to the already competing theoretical perspectives in the threat-politics literature (e.g., Brandt & Bakker, 2022; Godefroidt et al., 2019; Jost, 2017). Despite their relevance, the associations of threat, worry, and issue salience with political ideology have not yet been directly compared.

To summarize, we explore to what extent threat, worry, and issue salience measures produce similar empirical patterns. We do this using a sample of the Dutch population focusing on descriptive statistics, their associations with each other, and their associations with political ideology.

Method

Openness, Transparency and Ethics

We report the results of a secondary data analysis using an existing data set. We did not preregister our expectations or analyses. The data and code to reproduce our results can be found on our study’s OSF page (see Bomm et al., 2025). This study has been approved by the Ethics Review Board of the Faculty of Social and Behavioral Sciences, University of Amsterdam, The Netherlands, under the number 2022-YME-15725. Before starting the survey, participants signed an informed consent form.

Research Design

We rely on a large and diverse sample of Dutch respondents collected by I&O Research collected between November 30, 2022 and December 11, 2022. The online survey measured threat, worry, and issue salience regarding twelve societal issues (see full survey: https://osf.io/d958h; Azrout et al., 2022). Within the survey, participants first completed the issue salience battery, then the worry battery, and finally the threat battery. The order of the blocks was fixed, while the order of the items within each block was randomized.

Sample

Our analyses included data from N = 1863 participants (51.9% male, 47.9% female, .16% other, MSample Age = 52.41, SDSample Age = 16.30; sample education levels: 20.2% low education, 39.5% medium education, 40.3% high education). The sample is, compared to the general Dutch population, comprised of slightly more men than women, older (MPopulation Age 2024 = 42.4, Centraal Bureau voor de Statistiek, 2021), and somewhat more highly educated (Population education levels: 26.0% low education, 37.0% medium education, 36.4% high education, Centraal Bureau voor de Statistiek, 2024).

Measures

Threat, worry, and issue salience were measured for the same set of twelve societal issues: climate change, Covid-19, crime, energy costs, the housing shortage, inflation, the influx of asylum seekers, the inhumane reception of asylum seekers, the labour shortage, the nitrogen problem, polarization, and the war in Ukraine. First, issue salience was measured with the item "How important do you consider the following problems the Netherlands is currently facing?"2, rated on a 7-point Likert scale ranging from 1 (Not at all important) to 7 (Very strongly important) for each issue. Worry was measured with the item "How worried are you about the (potential) consequences for you personally/your personal situation for each following problems?"3, rated on a 7-point Likert scale ranging from 1 (Not at all worried) to 7 (Very much worried) for each issue. Threat was measured with the item "To what extent do you feel threatened by the following issues?"4, rated on a 7-point Likert scale ranging from 1 (Not at all threatened) to 7 (Very strongly threatened) for each issue. Items were “forced response” and thus have no missing values.

Political ideology was measured with the item “In politics, people sometimes talk about “left” and “right”. Where would you place yourself? Display your position using a scale of 0 to 10, where 0 means “left” and 10 means “right”. Which number best describes your position?”, on a semantic differential scale from 0 (Left) to 10 (Right) (Huber, 1989). As higher values indicate more right-wing ideology, we will subsequently refer to this measure as “right-wing ideology”. Participants who answered “I don’t know” or “I don’t want to say” (8%, N = 150) were treated as missing values in analyses including right-wing ideology.

Results

Comparing the Levels of Threat, Worry, and Issue Salience

Analyses were performed using the base-R package (R Core Team, 2023). We start by examining the average levels of threat, worry, and issue salience. Figure 1 depicts the distributions of threat (green), worry (orange), and issue salience (blue) per societal issues. Dashed lines indicate mean responses for each measure per issue. To test the difference between the levels of threat, worry, and issue salience, we conducted two-sided paired-sample t-tests with Bonferroni-Holm-corrected p-values to account for repeated testing for all pairwise comparisons. Table 1 in Appendix A provides descriptive statistics for threat, worry, and issue salience for all twelve issues. Table 2 in Appendix B provides the detailed results of all t-test comparisons.

Starting with threat and worry, the self-reported levels of threat are consistently lower than the self-reported levels of worry. These differences are statistically significant (all padj < .001). In our effect size interpretation, we follow Funder and Ozer (2019) and interpret effects of d ≈ .1 as very small, d ≈ .2 as small, d ≈ .41 as medium, d ≈ .63 as large, and d > .87 as very large. The differences between threat and worry range from small to medium effects: dCovid-19 = .23 to dHousing shortage = .48. Turning to threat and issue salience, all twelve issues are statistically significantly less threatening than salient (all padj < .001). The differences between threat and issue salience are large to very large, ranging from dCovid-19 = .68 to dHousing shortage = 1.52. All threat-issue salience differences are larger than any of the threat-worry differences. Finally, for worry and issue salience, all twelve issues are statistically significantly less worrying than salient (all padj < .001). The differences between worry and issue salience are medium to very large, ranging from dClimate change = .39 to dHousing shortage = 1.08. To conclude, Dutch citizens report issues to be slightly less threatening than worrying, and substantively less threatening or worrying than salient. This is a first indication that threat and worry, but not issue salience, produce similar empirical patterns.

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Figure 1

Distributions of Threat, Worry, and Issue Salience Responses per Issue

Note. Distributions of threat (green), worry (orange), and issue salience responses (blue) for each issue. Dashed lines represent mean responses. Across all issues, Bonferroni-Holm-corrected paired t-tests (two-sided) showed significant differences between threat, worry, and issue salience, across all 36 comparisons. Table 2 in Appendix B provides detailed t-test results.

Correlations Between Threat, Worry, and Issue Salience

To further assess the empirical patterns between self-reported threat, worry, and issue salience, we investigated the correlations between the constructs. Figure 2 plots the correlations between threat and worry (left), threat and issue salience (middle), and worry and issue salience (right) for the examined issues. To test whether there is a statistically significant difference in the correlation coefficients across issues, we first converted all correlation coefficients to z-scores using Fisher’s transformation and then conducted z-tests with Bonferroni-Holm-corrected p-values to account for repeated testing (see Table 3 in Appendix C for complete test results).

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Figure 2

Correlation Coefficients Between Threat and Worry (Left), Threat and Issue Salience (Middle), and Worry and Issue Salience (Right)

Note. Correlation coefficients are ordered by the issues’ average correlation strength. The correlation coefficients for threat and worry, threat and issue salience, and worry and issue salience all differed statistically significantly from each other, with the exception of the housing shortage. Table 3 in Appendix C provides detailed correlation difference test results.

A visual inspection of the correlation coefficients plotted in Figure 2 shows the threat-worry associations fall within a small range from rReception of asylum seekers = .59 to rClimate change = .78, with an average correlation of rThreat-Worry = .70. The correlation coefficients for the threat-issue salience pairs are overall lower than the threat-worry correlations (average rThreat-Issue salience = .47, with a larger range from rReception of asylum seekers = .31 to rClimate change = .64). Similarly, the correlations between worry and issue salience are lower than the threat-worry correlations (average rWorry-Issue salience = .58), and have a larger range (from rHousing shortage = .39 to rClimate change = .75).

Next, we test whether, within each issue, the correlations between threat and worry, threat and issue salience, and worry and issue salience differ statistically significantly from each other. Within each issue, the correlation between threat and worry is statistically significantly stronger than the correlations between a) threat and issue salience (all padj < .001), and b) worry and issue salience (all padj < .05), see Table 4 in Appendix C. The correlations between threat and issue salience are statistically significantly weaker than the correlations between worry and issue salience (all padj <.05, except padj-Housing Shortage = .078).

To summarize, self-reported threat and worry about societal issues are strongly associated with each other, while issue salience is more weakly associated with both threat and worry. This is another indication that threat and worry, but not issue salience, produce similar empirical patterns.

Associations Between Right-Wing Ideology and Measures of Threat, Worry, and Issue Salience

Next, we assess whether we reach similar conclusions about the relation to right-wing ideology when relying interchangeably on threat, worry, or issue salience measures. Figure 3 shows the results of bivariate regression models (i.e., correlation coefficients) predicting right-wing ideology on a left-right spectrum with threat, worry, and issue salience, across twelve societal issues. Positive (resp. negative) coefficients indicate a positive (resp. negative) association between right-wing ideology and threat, worry, or issue salience for that particular issue.

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Figure 3

Bivariate Correlations Between Right-Wing Ideology and Threat, Worry, and Issue Salience

Note. Correlation coefficients of threat (green), worry (orange), and issue salience (blue) with right-wing ideology on a left-right spectrum (0 = left; 10 = right). Statistically significant correlation coefficient differences from the threat baseline (square) are indicated by solid circles; non-significant differences by hollow circles. Table 5 in Appendix D provides detailed correlation difference test results.

We start by examining the correlation coefficients of threat and right-wing ideology for each of the twelve issues. In line with previous evidence in the threat-politics literature (e.g., Brandt et al., 2021), we see that the perceived threat posed by different issues is, in terms of magnitude and direction, differentially associated with right-wing ideology. The associations between threat and right-wing ideology vary considerably, from (|rWar in Ukraine| = .001) to (|rInflux of asylum seekers| = .41). Five threat ratings—crime, energy costs, inflation, the influx of asylum seekers, and the labour shortage—are positively and statistically significantly associated with right-wing ideology. At the same time, we find five negative and statistically significant associations between perceived threat—climate change, Covid-19, the nitrogen problem, polarization, and the reception of asylum seekers—and right-wing ideology.

To compare the threat-ideology correlations to the worry-ideology and issue salience-ideology correlations across the same societal issues, we conducted Fisher’s z-tests with Bonferroni-Holm-corrected p-values to account for repeated testing. Figure 3 marks statistically significant differences from the baseline threat-ideology correlation with solid (as opposed to hollow) circles. Table 5 in Appendix D provides the results of the correlation coefficient difference tests.

We do not find evidence for Type S (sign) errors when relying interchangeably on measures of threat, worry, or issue salience in separate bivariate models predicting right-wing ideology: When there is a positive association with right-wing ideology for threat posed by an issue, we see the same positive association with worry and issue salience. Out of 36 tests, only one indicates a Type S error: Perceiving the labour shortage as threatening is (statistically significantly) positively related to right-wing ideology, while perceiving it as important is negatively (but not statistically significantly) related to right-wing ideology.

We now turn to the extent to which the different measures lead to Type M (magnitude) errors in the bivariate models, i.e., errors about the magnitude of their associations with right-wing ideology conditional upon the measure used. Starting with threat and worry, as Figure 3 depicts, the correlations with right-wing ideology are highly similar for the threat and worry measures, with small differences ranging from ∆Reception of asylum seekers = −.12 to ∆Energy costs; Crime = .02. We see statistically significantly different correlations for only three of twelve issues: the influx of asylum seekers, the nitrogen problem, and the inhumane reception of asylum seekers.

Turning to issue salience, we find that issue salience is overall more strongly associated with right-wing ideology than threat, with descriptively larger statistically significant correlation differences in eight of the twelve examined issues (climate change, Covid-19, the housing shortage, the labour shortage, the nitrogen problem, polarization, the reception of asylum seekers, and the war in Ukraine). Only for the influx of asylum seekers is the threat measure more positively associated with right-wing ideology than the issue salience measure is. For the issues crime, energy costs, the housing shortage, and inflation, the associations of threat and issue salience with right-wing ideology are not statistically significantly different. Overall, issue salience is to a larger extent associated with right-wing ideology than threat is, with correlation differences ranging from ∆r Reception of asylum seekers = −.40 to ∆r Crime = .01. When comparing worry and issue salience, we see largely similar patterns: relying upon a measure of issue salience leads to larger associations with right-wing ideology compared to worry.

To summarize, using threat and worry measures interchangeably in studies on threat perception and ideology is unlikely to change conclusions about the direction of the relationship (Type S errors). However, issue salience differs: its association with ideology is substantially stronger, raising the risk of Type M errors, where the effect size is overestimated. This matters because psychology increasingly emphasizes not just whether an effect exists, but how strong it is (Lakens, 2022). For example, while all three measures show positive associations with ideology, the average correlation for issue salience (|r| = .23) is more than 1.5 times larger than for threat (|r| = .14) and worry (|r| = .16). Based on conventional benchmarks (Arceneaux et al., 2025; Funder & Ozer, 2019), this shifts the interpretation from a small to a modest effect. Such differences matter for theory and practice. Overestimating the role of threat in ideological conflict may lead scholars to exaggerate the extent of societal threat or ideological divides and misguide future studies or interventions.

Multivariate Tests of Incremental Validity

Next, we assess the incremental validity, that is, the extent to which the three measures threat, worry, and issue salience explain variance in right-wing ideology above and beyond each other (Hunsley & Meyer, 2003). To do this, we report the results of a series of multivariate regression models in which we regress right-wing ideology on 1.) threat, worry, and issue salience (Model 1; see also equation 1), and 2.) a threat-worry composite score and issue salience (Model 2, see also equation 2). Figure 4 shows the results of the multivariate regression models 1 and 2 for each of the twelve societal issues. Positive (resp. negative) regression estimates indicate a positive (resp. negative) association between right-wing ideology and threat, worry, a threat-worry composite score, or issue salience. The coefficients should be interpreted as partial associations with right-wing ideology—i.e., the association with the outcome variable controlling for the other predictors in the model. We provide the full results of the multivariate regression models in Table 6 in Appendix E.

1
Right-wing ideologyi = β0 + β1 · Threati + β2 · Worryi + β3 · Issue Saliencei + εi
2
Right-wing ideologyi = β0 + β1 · Threat-Worry Compositei + β2 · Issue Saliencei + εi

In multivariate Model 1 (see Equation 1 and Figure 4), threat and worry show very similar partial associations across most issues; only for the influx of asylum seekers and the reception of asylum seekers are their coefficients statistically significantly different from one another (thus, for these issues, rejecting H0: βthreat = βworry). Moreover, threat and worry are, overall, less associated with right-wing ideology than issue salience. In six out of the twelve societal issues, salience has a statically significantly stronger association with right-wing ideology compared to threat, specifically for: climate change, Covid-19, the nitrogen problem, polarization, the reception of asylum seekers, and the war in Ukraine. Consistent with the bivariate correlations, the only issue on which salience is statistically significantly less strongly associated with ideology than threat is the influx of asylum seekers.

The results of Model 1 further show that, when predicting right-wing ideology and controlling for issue salience, threat and worry no longer add unique predictive value in five out of the twelve issues (climate change, energy costs, inflation, the nitrogen problem, and polarization), even though they were significant in the bivariate regressions. This suggests that when predicting ideology for these issues, salience accounts for much of the explanatory power of threat and worry, making the distinction between the measures less pronounced than when examining their descriptive scores.

To summarize, the results from Model 1 suggest that when threat, worry, and issue salience are included simultaneously, worry adds little incremental validity beyond threat (and vice versa). By contrast, issue salience shows a stronger partial association with ideology than threat or worry in half of the issues, indicating that salience is sometimes the more powerful predictor of right-wing ideology.

Second, we created latent variables combining threat and worry into a threat-worry composite for each issue to reduce potential measurement error by employing a two-item measure for each issue. We regressed ideology on issue salience and the threat-worry composite using Equation 2, see Figure 4. Issue salience is statistically significantly differently and more strongly associated with right-wing ideology than the threat-worry composite is for seven out of the twelve issues: climate change, Covid-19, the housing shortage, the nitrogen problem, polarization, the reception of asylum seekers, and the war in Ukraine. Issue salience is statistically significantly less associated with right-wing ideology than the threat-worry composite on two issues: the influx of asylum seekers and the labour shortage.

These results are consistent with those from Model 1 and the bivariate associations, and suggest that although salience and threat–worry are related, salience should not be used interchangeably with threat-worry as a proxy for perceived threat.5

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Figure 4

Threat, Worry, and Salience as Predictors of Ideology in Two Standardized Multivariate Regression Models

Note. Rows 1–3 (Model 1, shaded white) and 4–5 (Model 2, shaded grey) of each plot facet depict the results of standardized multivariate regression models predicting right-wing ideology. Model 1 includes the predictors threat (green), worry (orange), and issue salience (blue). Model 2 includes a threat-worry composite (pink) and issue salience (blue) as predictors. Right-wing ideology was measured on a left-right spectrum (0 = left; 10 = right). Estimates that differ statistically significantly (p < .05) from threat (resp. the threat-worry composite in Model 2) are indicated by solid circles; non-significant differences by hollow circles. Table 6 in Appendix E provides the full output of the regression models.

Discussion

Our study demonstrates that threat and worry produce largely similar empirical patterns, warranting their use as proxies for each other in many cases—with relevant exceptions, depending on the issue under study. At the same time, citizens do not necessarily feel threatened by or worried about the issues they find most important, and vice versa. Our findings also reveal that the direction and strength of associations between political ideology on the one hand, and threat or worry about societal issues on the other, are highly similar, with the exception of asylum-related issues. Issue salience exhibits a different pattern, showing stronger associations with ideology across the board.

We see at least three opportunities to expand our research. First, by using multiple-item measures of threat, worry, and issue salience, future studies could further establish the construct validity of these concepts using factor-analytic approaches. Second, our survey used a fixed block order, raising the question of whether our results were affected by spillover effects from one measurement battery to the next. However, the fact that, overall, worry correlates more strongly with threat than with issue salience, despite being equidistant in time from both, supports our conclusion that worry is more closely related to threat than to issue salience. Ultimately, to rule out potential order effects, future studies could present issue salience, worry, and threat in a randomized order.

Third, cross-cultural research is needed to explore whether—and to what extent—our conclusions generalize to other contexts. We believe that our Dutch data can be meaningfully linked to existing research, as Dutch and English are closely related (Stefanowitsch et al., 2020). At the same time, the precise meanings attached to translations of “threat” and “worry”, as well as the relationship between these terms, may vary across languages. Cross-cultural conclusions about the relationship between threat, worry, and issue salience will therefore require additional cross-cultural validation efforts.

In sum, our findings support the practice of decades of “threat-politics research” that treated threat and worry as interchangeable indicators of a common construct (e.g., Brandt et al., 2021; Conway et al., 2023; Onraet et al., 2013), while also pointing out exceptions in which threat and worry produce different empirical patterns, and highlighting the limitations of using issue salience as a proxy. By doing so, we contribute to the growing body of work on the validation of psychological measures (Flake & Fried, 2020).

Notes

1) In personality and clinical psychology, the term worry is also used in general anxiety scales (e.g., Spielberger et al., 1970). At the same time, there is also evidence for worry and anxiety as separate constructs (e.g., Davey et al., 1992).

2) Dutch item wording: “Hoe belangrijk vindt u de volgende problemen waar Nederland momenteel voor staat?”

3) Dutch item wording: “Hoe bezorgd bent u om de (mogelijke) gevolgen voor uzelf/uw persoonlijke situatie van elk van de volgende onderwerpen/problemen?”

4) Dutch item wording: “In hoeverre voelt u zich door deze onderwerpen bedreigd?”

5) These conclusions do not change when we add sociodemographic variables as control variables to Model 2. To save space, we present these results in Appendix E.

Funding

This publication is part of the project “Under pressure: How citizens respond to threats and adopt the attitudes and behaviours to counter them” (project number VI.Vidi.211.055, awarded to Bert N. Bakker) of the NWO Talent Programme VIDI, which is financed by the Dutch Research Council (NWO). The data analyzed in this study stems from a data collection that was funded by the Amsterdam School of Communication Research.

Acknowledgments

We thank Gijs Schumacher and Jakob Kasper for their feedback, and our colleagues at the Hot Politics Lab and the Amsterdam School of Communication Research at the University of Amsterdam for their support in writing this paper.

Competing Interests

The authors have declared that no competing interests exist.

Author Contributions

Linda C. Bomm—Conceptualization | Formal analysis | Writing – original draft | Writing – review & editing | Visualization | Project administration. Paul K. Bergmann—Conceptualization | Formal analysis | Writing – original draft | Writing – review & editing | Visualization. Bert N. Bakker—Conceptualization | Resources | Writing – original draft | Writing – review & editing | Supervision | Funding acquisition.

Ethics Statement

The study has been approved by the Ethics Review Board of the Faculty of Social and Behavioral Sciences, University of Amsterdam, The Netherlands under number 2022-YME-15725. All participants provided informed consent before completing the survey.

Data Availability

All data and analysis code are available on this study’s OSF page (see Bomm et al., 2025).

Supplementary Materials

For this article, data and code are available (see Bomm et al., 2025).

Index of Supplementary Materials

  • Bomm, L. C., Bergmann, P. K., & Bakker, B. N. (2025). Threat and worry (often) go together; salience stands apart – Patterns across descriptives, correlations, and ideological associations [Data, code]. OSF. https://osf.io/h9fkv

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Appendices

Appendix A: Descriptive Statistics of Threat, Worry, and Issue Salience

Table 1 provides mean and standard deviations for threat, worry, and issue salience for all twelve issues.

Table 1

Means and Standard Deviations of Threat, Worry, and Issue Salience per Issue

Threat
Worry
Issue Salience
IssueMSDMSDMSD
Covid-192.421.492.791.573.521.56
Influx of asylum seekers3.292.023.931.995.351.51
Reception of asylum seekers2.371.503.161.824.811.74
Inflation4.281.855.021.595.651.22
Energy costs4.381.915.081.675.871.19
War in Ukraine3.751.814.371.745.511.40
Nitrogen problem3.141.803.761.814.741.77
Climate change4.051.944.681.855.371.68
Housing shortage3.131.963.892.075.791.22
Polarization3.821.774.511.685.511.36
Labour shortage2.751.663.581.765.021.37
Crime3.671.814.251.765.351.40

Appendix B: t-Test Comparisons of Threat, Worry, and Issue Salience

Table 2 provides the results of the Bonferroni-Holm corrected two-sided paired sample t-test comparisons for a) threat and worry, b) threat and issue salience, and c) worry and issue salience across twelve societal issues.

Table 2

t-test Results for Threat, Worry, and Issue Salience Across Twelve Societal Issues

IssueMeanatpadjCIlowCIupd
Threat vs. Worry
Climate change-0.63-21.58< .001-0.68-0.57-0.33
Covid-19-0.37-15.08< .001-0.41-0.32-0.24
Crime-0.58-18.70< .001-0.64-0.52-0.32
Energy costs-0.69-23.07<.001-0.75-0.64-0.38
Housing shortage-0.77-22.89< .001-0.83-0.70-0.38
Inflation-0.74-23.77< .001-0.80-0.68-0.42
Influx of asylum seekers-0.64-18.19< .001-0.71-0.57-0.32
Labour shortage-0.82-25.51< .001-0.89-0.76-0.48
Nitrogen problem-0.62-19.33< .001-0.69-0.56-0.35
Polarization-0.68-19.82< .001-0.75-0.61-0.39
Reception of asylum seekers-0.79-22.34< .001-0.86-0.72-0.47
War in Ukraine-0.61-18.77< .001-0.68-0.55-0.35
Threat vs. Issue Salience
Climate change-1.32-36.82< .001-1.39-1.25-0.72
Covid-19-1.10-32.82< .001-1.16-1.03-0.72
Crime-1.67-44.55< .001-1.75-1.60-1.02
Energy costs-1.49-38.64< .001-1.56-1.41-0.89
Housing shortage-2.67-59.86< .001-2.75-2.58-1.59
Inflation-1.37-36.40< .001-1.45-1.30-0.84
Influx of asylum seekers-2.06-48.43< .001-2.14-1.98-1.13
Labour shortage-2.27-56.94< .001-2.34-2.19-1.48
Nitrogen problem-1.60-38.50< .001-1.68-1.52-0.90
Polarization-1.68-42.62< .001-1.76-1.61-1.06
Reception of asylum seekers-2.44-55.10< .001-2.53-2.36-1.50
War in Ukraine-1.76-45.63< .001-1.84-1.68-1.07
Worry vs. Issue Salience
Climate change-0.69-24.05< .001-0.75-0.64-0.39
Covid-19-0.73-24.41< .001-0.79-0.67-0.47
Crime-1.10-34.56< .001-1.16-1.03-0.68
Energy costs-0.79-25.54< .001-0.85-0.73-0.52
Housing shortage-1.90-41.88< .001-1.99-1.81-1.08
Inflation-0.63-21.20< .001-0.69-0.58-0.44
Influx of asylum seekers-1.42-36.21< .001-1.49-1.34-0.78
Labour shortage-1.44-38.45< .001-1.52-1.37-0.90
Nitrogen problem-0.98-28.34< .001-1.04-0.91-0.54
Polarization-1.00-29.89< .001-1.07-0.94-0.65
Reception of asylum seekers-1.65-38.98< .001-1.73-1.57-0.93
War in Ukraine-1.15-34.06< .001-1.21-1.08-0.71

Note. Results of 36 two-sided paired t-tests with Bonferroni-Holm corrected p-values to correct for multiple comparisons. All tests were performed with df = 1862.

aMean indicates mean difference.

Appendix C: Correlations Between Threat, Worry, and Issue Salience

Table 3 provides the correlation coefficients of the threat, worry, and issue salience measures with each other for the twelve examined societal issues.

Table 4 provides the results of Bonferroni-Holm-corrected Fisher’s z-Tests for statistically significant differences between the correlations of threat, worry, and issue salience with each other.

Table 3

Bivariate Inter-Measure Correlation Coefficients for Threat, Worry, and Issue Salience Across Twelve Societal Issues

IssuerThreat - WorryrThreat - Issue SaliencerWorry - Issue Salience
Climate change.78.64.75
Covid-19.77.55.66
Crime.72.51.64
Energy costs.74.51.61
Housing shortage.75.34.39
Inflation.70.50.60
Influx of asylum seekers.71.49.57
Labour shortage.67.37.49
Nitrogen problem.70.49.66
Polarization.63.43.56
Reception of asylum seekers.59.31.47
War in Ukraine.68.49.59

Note. Bivariate Pearson correlation coefficients for the associations between threat and worry (left), threat and issue salience (middle), and worry and issue salience (right) across twelve societal issues.

Table 4

Fisher’s z-Test Results for Correlation Coefficients Between Threat, Worry, and Issue Salience Across Twelve Societal Issues

IssuerThreat – Issue Salience vs. rThreat – Worry
rWorry – Issue Salience vs. rThreat – Issue Salience
rWorry – Issue Salience vs. rThreat – Worry
zpzpzp
Climate change-8.76< .0016.55< .001-2.21.027
Covid-19-12.26< .0015.32< .001-6.94< .001
Crime-10.52< .0015.96< .001-4.56< .001
Energy costs-11.82< .0014.46< .001-7.37< .001
Housing shortage-18.87< .0011.76.078-17.11< .001
Inflation-9.70< .0014.39< .001-5.31< .001
Influx of asylum seekers-10.71< .0013.40.001-7.31< .001
Labour shortage-12.88< .0014.50< .001-8.38< .001
Nitrogen problem-10.10< .0017.83< .001-2.27.023
Polarization-8.59< .0015.27< .001-3.31.001
Reception of asylum seekers-10.89< .0015.78< .001-5.11< .001
War in Ukraine-8.94< .0014.32< .001-4.62< .001

Note. Results of Fisher’s z-tests comparing correlation coefficients of a) threat and issue salience vs. threat and worry (left), b) worry and issue salience vs. threat and issue salience (middle), and c) worry and issue salience vs. threat and worry (right) across twelve societal issues. All p-values were Bonferroni-Holm corrected for the 36 performed comparisons.

Appendix D: Correlations of Threat, Worry, and Issue Salience With Right-Wing Ideology

Table 5 provides the correlation coefficients of threat, worry, and issue salience measures with right-wing ideology for the twelve examined societal issues. Table 5 also provides the results of the Fisher’s z-tests for statistically significant differences between the correlations with right-wing ideology for threat and worry, and for threat and issue salience.

Table 5

Coefficients and Fisher’s z-Test Results for Bivariate Correlations of Threat, Worry, and Issue Salience with Right-Wing Ideology Across Twelve Issues

IssueCorrelation with Right-Wing Ideology
Correlation Difference from rThreat – Right-Wing Ideology
rThreat – Right-Wing IdeologyprCIlowCIuprazpadj
Threat
Climate change-0.33< .001-.38-.29
Covid-19-0.05.032-.10-.00
Crime0.21< .001.17.26
Energy costs0.14< .001.09.19
Housing shortage-0.02.410-.07.03
Inflation0.13< .001.09.18
Influx of asylum seekers0.41< .001.36.45
Labour shortage0.05.023.01.10
Nitrogen problem-0.18< .001-.23-.13
Polarization-0.06.011-.11-.01
Reception of asylum seekers-0.08.001-.13-.03
War in Ukraine0.00.971-.05.05
Worry
Climate change-.38< .001-.42-.33-.05-1.43.260
Covid-19-.10< .001-.15-.05-.05-1.43.260
Crime.23< .001.19.28.020.55.736
Energy costs.16< .001.11.20.020.45.745
Housing shortage-.01.778-.05.04.010.38.754
Inflation.14< .001.10.19.010.36.754
Influx of asylum seekers.33< .001.28.37-.08-2.50.029
Labour shortage.03.247-.02.07-.03-0.79.648
Nitrogen problem-.26< .001-.31-.22-.08-2.51.029
Polarization-.10< .001-.14-.05-.04-1.06.462
Reception of asylum seekers-.20< .001-.25-.16-.12-3.67< .001
War in Ukraine-.02.346-.07.02-.02-0.69.689
Issue Salience
Climate change-.46< .001-.51-.42-.13-4.21< .001
Covid-19-.18< .001-.22-.13-.12-3.69< .001
Crime.22< .001.17.27.010.21.836
Energy costs.12< .001.08.17-.02-0.50.743
Housing shortage-.09< .001-.14-.04-.07-2.01.090
Inflation.11< .001.06.16-.02-0.60.735
Influx of asylum seekers.26< .001.22.31-.15-4.58< .001
Labour shortage-.03.216-.08.02-.08-2.48.029
Nitrogen problem-.42< .001-.47-.38-.24-7.49< .001
Polarization-.23< .001-.28-.19-.17-5.08< .001
Reception of asylum seekers-.48< .001-.52-.44-.40-12.57< .001
War in Ukraine-.15< .001-.19-.10-.15-4.34< .001

Note. Bivariate correlations of threat, worry, and issue salience with right-wing ideology across twelve societal issues (left), and Bonferroni-Holm corrected Fisher’s z-test results comparing threat-right wing ideology correlations with worry- and issue salience-right wing ideology correlations (right) across twelve societal issues.

ar indicates correlation coefficient difference.

Appendix E: Multivariate Regressions of Right-Wing Ideology on Threat, Worry, and Issue Salience

As a robustness check, we created standardized multivariate regression Model 3, in which we predict ideology from issue salience, a threat-worry composite, age, gender (with female gender coded on the higher value), education level, and income level, for each of the twelve issues. Doing so, we assess whether our conclusions are robust when controlling for demographic variation.

Right-wing ideologyi = β0 + β1 · Threat-Worry Compositei
+ β2 · Issue Saliencei + β3 · Agei + β4 · Female Genderi
3
+ β5 · Education Leveli + β6 · Income Leveli + εi

The results for Model 3 are largely consistent with those of the models without demographic covariates, see Figure 5. When controlling for covariates, issue salience is again statistically significantly differently and more strongly associated with ideology than the threat-worry composite is for seven out of the twelve issues: climate change, Covid-19, the housing shortage, the nitrogen problem, polarization, the reception of asylum seekers, and the war in Ukraine. When controlling for demographic covariates, issue salience is statistically significantly less associated with ideology than the threat-worry composite on three issues: inflation, the influx of asylum seekers, and the labour shortage. Thus, the conclusion that issue salience is differently associated with ideology than a threat-worry composite measure holds when controlling for the demographic covariates income, education, gender, and age.

Click to enlarge
spb.16605-f5
Figure 5

Multivariate Regression Model Including Demographic Covariates (Model 3)

Note. Results of standardized multivariate regression Model 3, predicting right-wing ideology from a threat-worry composite (pink), issue salience (blue), and the demographic covariates (grey) income, education level, female gender (binary gender variable with female on the higher value), and age. Right-wing ideology was measured on a left-right spectrum (0 = left; 10 = right). Table 6 provides the detailed regression estimates.

We report the full results for the multivariate regression Models 1, 2, and 3 in Table 6.

Table 6

Robustness Checks: Three Standardized Multivariate Regression Models Predicting Ideology

PredictorModel 1
Model 2
Model 3
β1t1p1CIlow1CIup1β2t2p2CIlow2CIup2β3t3p3CIlow3CIup3
Climate change
Threat-0.04-1.03.302-0.100.03
Worry-0.04-0.90.367-0.120.04
Salience-0.41-12.68< .001-0.48-0.35-0.41-13.07< .001-0.48-0.35-0.38-11.22< .001-0.44-0.31
Threat-Worry Composite-0.07-2.17.030-0.14-0.01-0.06-1.67.096-0.120.01
Age-0.03-1.19.234-0.070.02
Female-0.04-1.98.047-0.09-0.00
Education-0.16-6.48< .001-0.21-0.11
Income0.177.00< .0010.120.21
Covid-19
Threat0.082.17.0300.010.15
Worry-0.03-0.82.412-0.110.05
Salience-0.20-6.32< .001-0.26-0.14-0.21-6.79< .001-0.27-0.15-0.18-5.72< .001-0.24-0.12
Threat-Worry Composite0.051.63.103-0.010.120.051.64.101-0.010.12
Age-0.05-1.81.070-0.100.00
Female-0.09-3.71< .001-0.14-0.04
Education-0.27-10.23< .001-0.32-0.22
Income0.187.08< .0010.130.23
Crime
Threat0.092.54.0110.020.15
Worry0.092.44.0150.020.17
Salience0.123.81< .0010.060.180.123.93< .0010.060.180.113.56< .0010.050.17
Threat-Worry Composite0.185.61< .0010.120.240.185.50< .0010.120.24
Age-0.13-5.12< .001-0.18-0.08
Female-0.14-5.69< .001-0.18-0.09
Education-0.20-7.61< .001-0.26-0.15
Income0.197.60< .0010.140.24
Energy costs
Threat0.051.38.168-0.020.12
Worry0.092.38.0170.020.17
Salience0.041.43.154-0.020.100.051.54.123-0.010.100.030.90.366-0.030.08
Threat-Worry Composite0.144.48< .0010.080.200.175.23< .0010.110.23
Age-0.07-2.64.008-0.12-0.02
Female-0.13-5.39< .001-0.18-0.08
Education-0.23-8.66< .001-0.28-0.18
Income0.238.76< .0010.180.28
Housing shortage
Threat-0.02-0.61.541-0.090.05
Worry0.051.26.207-0.030.12
Salience-0.10-3.77< .001-0.15-0.05-0.10-3.71< .001-0.15-0.05-0.08-3.14.002-0.14-0.03
Threat-Worry Composite0.020.86.391-0.030.080.062.21.0270.010.12
Age-0.06-2.21.028-0.11-0.01
Female-0.11-4.44< .001-0.16-0.06
Education-0.27-10.21< .001-0.32-0.22
Income0.207.58< .0010.150.25
Inflation
Threat0.061.66.097-0.010.12
Worry0.082.27.0240.010.15
Salience0.031.14.253-0.020.090.041.22.223-0.020.090.010.38.706-0.050.07
Threat-Worry Composite0.144.35< .0010.080.200.175.06< .0010.100.23
Age-0.06-2.24.025-0.11-0.01
Female-0.12-5.10< .001-0.17-0.08
Education-0.24-9.05< .001-0.29-0.19
Income0.228.61< .0010.170.27
Influx of asylum seekers
Threat0.3410.74< .0010.280.41
Worry0.041.17.244-0.030.11
Salience0.072.64.0090.020.120.062.03.0430.000.110.072.52.0120.020.12
Threat-Worry Composite0.3913.54< .0010.340.450.3712.15< .0010.310.43
Age-0.13-5.43< .001-0.18-0.08
Female-0.13-5.72< .001-0.18-0.09
Education-0.16-6.08< .001-0.21-0.11
Income0.177.10< .0010.120.22
Labour shortage
Threat0.072.17.0300.010.14
Worry0.010.30.766-0.060.08
Salience-0.06-2.20.028-0.12-0.01-0.07-2.39.017-0.12-0.01-0.05-1.89.060-0.110.00
Threat-Worry Composite0.082.78.0050.020.140.082.70.0070.020.14
Age-0.08-2.99.003-0.13-0.03
Female-0.12-4.73< .001-0.17-0.07
Education-0.27-10.14< .001-0.32-0.22
Income0.207.69< .0010.150.25
Nitrogen problem
Threat0.041.22.223-0.020.10
Worry-0.01-0.16.875-0.080.06
Salience-0.44-15.08< .001-0.49-0.38-0.44-15.91< .001-0.50-0.39-0.39-13.23< .001-0.44-0.33
Threat-Worry Composite0.041.21.228-0.020.090.01 0.46.642-0.050.08
Age-0.01-0.49.622-0.060.04
Female-0.05-2.02.043-0.09-0.00
Education-0.18-7.06< .001-0.23-0.13
Income0.176.91< .0010.120.21
Polarization
Threat0.031.01.311-0.030.09
Worry0.030.85.395-0.040.09
Salience-0.26-9.17< .001-0.32-0.21-0.26-9.34< .001-0.32-0.21-0.24-8.35< .001-0.30-0.18
Threat-Worry Composite0.061.93.054-0.000.120.051.66.096-0.010.11
Age-0.03-1.10.271-0.080.02
Female-0.08-3.40.001-0.13-0.04
Education-0.25-9.52< .001-0.30-0.20
Income0.207.80< .0010.150.25
Reception of asylum seekers
Threat0.093.23.0010.030.14
Worry-0.02-0.84.401-0.080.03
Salience-0.49-20.67< .001-0.54-0.44-0.50-21.49< .001-0.55-0.46-0.46-18.36< .001-0.51-0.41
Threat-Worry Composite0.072.50.0120.010.120.010.041.41.160-0.02
Age-0.01-0.44.660-0.060.04
Female-0.01-0.34.732-0.050.04
Education-0.18-7.32< .001-0.23-0.13
Income0.177.40< .0010.130.22
War in Ukraine
Threat0.061.90.058-0.000.13
Worry0.061.58.115-0.010.13
Salience-0.21-7.12< .001-0.27-0.15-0.21-7.23< .001-0.27-0.16-0.21-6.83< .001-0.27-0.15
Threat-Worry Composite0.123.75< .0010.060.180.082.65.0080.020.15
Age-0.03-0.98.326-0.080.03
Female-0.10-3.95< .001-0.14-0.05
Education-0.26-9.90< .001-0.31-0.21
Income0.207.93< .0010.150.25

Note. Results of three standardized multivariate regression models predicting ideology, including estimates (beta), test statistics (t), p-values (p1), and estimate confidence intervals (CIlow and CIup). Model 1 includes the predictors threat, worry, and issue salience. Model 2 includes a threat-worry composite and issue salience. Model 3 includes a threat-worry composite, issue salience, and the demographic covariates age, female gender (binary gender variable with female on the higher value), education level, and income level.