The CIHS developed by Krumrei-Mancuso and Rouse (2016) covers inter- and intrapersonal aspects of IH. The 22 items load on four factors: Independence of Intellect and Ego (“When someone contradicts my most important beliefs, it feels like a personal attack”, reverse-coded), Openness to Revising One’s Viewpoint (“I am willing to change my opinions on the basis of compelling reason”), Respect for Others’ Viewpoints (“I am willing to hear others out, even if I disagree with them”), and Lack of Intellectual Overconfidence (“My ideas are usually better than other people’s ideas”, reverse-coded). The measure shows good internal consistency (α = .82 to .87) for the total scale and a test-retest reliability of .75 after one month and .70 after three months (Krumrei-Mancuso & Rouse, 2016). In the original study, the fit of the model with an overall factor (χ²(205) = 368.29, GFI = .921, CFI = .948, RMSEA = .046) was similar to the model without such a factor, χ²(203) = 367.101, GFI = .921, CFI = .948, RMSEA = .046. The CIHS covers all quadrants in the IH classification framework (Porter et al., 2021) and has frequently been used to examine the relationship between IH and various social and political constructs (e.g., Bowes et al., 2020; Krumrei-Mancuso & Newman, 2020).

The IHS (Alfano et al., 2017) is the only IH scale that has already been translated into (Swiss-)German. The scale consists of 23 items loading on four inter-correlated factors of IH: Open-Mindedness (“I feel no shame learning from someone who knows more than me”), Intellectual Modesty (“I like to be the smartest person in the room”, reverse-coded), Corrigibility (“I appreciate being corrected when I make a mistake”) and Engagement (“I find it boring to discuss things I don’t already understand”, reverse-coded). The authors’ validation study showed a good fit for the 4-factor solution (German version: χ²(224) = 359.89, CFI = 0.88, RMSEA = 0.05, SRMR = 0.06) as well as correlations between self- and informant-ratings on the four subscales between r = .28 and .47. The IHS covers all quadrants in the IH classification framework (Porter et al., 2021). The fit indices and factor structure of the Swiss-German version were shown to be similar to the English version.

The LIHS by Leary et al. (2017) consists of 6 items which load on one factor. It exhibits good internal consistency (α = .73 to .82) and good structural (CFI = .91, SRMR = .05) and construct validity in the original study. The LIHS covers the two quadrants self-directed cognitions (e.g., “I accept that my beliefs and attitudes may be wrong”) and other directed cognitions (e.g., “I recognize the value in opinions that are different from my own”) in the IH classification framework (Porter et al., 2021). Due to its brevity, the scale holds the potential to be used in a range of questionnaires without excessively burdening participants.

The SIHS (Hoyle et al., 2016) is a unidimensional scale measuring IH regarding specific opinions, beliefs, and positions (e.g., “I recognize that my views about gun control are based on limited evidence”). The SIHS covers the quadrant self-directed cognitions in the IH classification framework (Porter et al., 2021). The nine-item scale (model without equality constraints: χ²(162) = 490.1, CFI = .93, SRMR = .07, RMSEA = .12) can be abbreviated to a three-item short-scale (model with loadings, uniqueness and topics constrained to equality: χ²(18, N = 804) = 25.0, CFI = .99, SRMR = .09, RMSEA = .04). Previous research has shown that specific and general IH correlate moderately (r = .24 to .63 with LIHS) but are distinct aspects of IH (Hoyle et al., 2016). The scale shows good internal consistency (nine-item scale: α = .88 to .93; three-item scale: α = .77 to .86; Hoyle et al., 2016). In our validation study, it is the only scale that measures IH in relation to a specific political topic.

To assess structural (or factorial) validity, “the degree to which the scores of the measurement instrument are an adequate reflection of the dimensionality of the construct being measured” (Aertssen et al., 2016, p. 894), we expected that the original factor solution of each IH scale would be replicated in the German context (H1). We pre-registered to use Schermelleh-Engel et al.’s (2003) criteria to assess model fit in confirmatory factor analyses (good fit: RMSEA ≤ . 05, NNFI ≥ .97, CFI ≥ .97, SRMR ≤ .05; acceptable fit: RMSEA ≤ .08, NNFI ≥ .95, CFI ≥ .95, SRMR ≤ .10). It has to be noted, however, that the pre-registered cut-off values were stricter than those achieved in the original scale validations, which we only recognized after pre-registering the analyses.

Convergent validity “is the extent to which a construct measured in different ways yields similar results” (Boateng et al., 2018, p. 5). Based on these theoretical considerations and previous research showing that the CIHS and LIHS correlated at r = .61 to .71 (Bowes et al., 2020), we expected (H2) that all three general IH scales (CIHS, IHS, LIHS) would be highly positively correlated with each other (rs ≥ .50). Additionally, we expected the topic-specific intellectual humility scale (SIHS) to be at least moderately positively correlated (rs ≥ .20) with the general intellectual humility scales based on previous findings (Bowes et al., 2020; Hoyle et al., 2016).

To assess discriminant validity, “the extent to which a measure is novel and not simply a reflection of some other construct” (Boateng et al., 2018, p. 14), we measured social desirability, need for cognition, need for cognitive closure, the personality factors honesty-humility and openness, and demographic variables.

When introducing a new measure to a new context, it is important to justify how this measure “provides information that was formerly unavailable or less adequately obtained” (Hunsley & Meyer, 2003, p. 449). This can be achieved by assessing incremental validity, “the improvement obtained by adding a particular procedure or technique to an existing combination of assessment methods” (American Psychological Association, n.d.). As outlined in the previous section, IH is correlated with other constructs such as need for cognition or other measures of humility. Thus, one may ask how much IH measures might add to the prediction of an important criterion variable, such as seeking to explain affective polarization.

Affective polarization refers to the “extent to which partisans [or political groups more broadly] treat each other as a disliked outgroup” (Wojcieszak & Warner, 2020, p. 1). IH is a promising construct to explain less affective political polarization (Jost et al., 2022; Porter et al., 2022) as it is associated with less biased information processing. For instance, intellectually humble individuals enjoy weighing competing ideas (McElroy et al., 2014), are better in differentiating weak from strong arguments (Leary et al., 2017), and believe less in under-supported political statements (Krumrei-Mancuso & Newman, 2020). Moreover, IH might address affective polarization by making individuals constructively deal with contrary-minded others. For instance, intellectually humbles are less defensive in disagreements (McElroy et al., 2014) and can admit that other viewpoints have positive features, too (Hodge et al., 2021).

Indeed, previous research has shown that IH was associated with less affective polarization regarding political and religious groups (Krumrei-Mancuso & Newman, 2020). Bowes et al. (2020) used three of the IH measures we considered (CIHS, LIHS, SIHS) and found negative correlations (rs = -.25 to -.44) between IH scale means and different measures of affective polarization. Regarding assessing incremental validity, IH predicted open-minded thinking and tolerance towards others after accounting for social desirability and general humility (Krumrei-Mancuso & Rouse, 2016). However, there have been no strong tests of incremental validity by testing whether IH can predict affective polarization beyond other established scales, such as need for cognition or need for cognitive closure. Therefore, we assessed incremental validity by measuring affective polarization and determining the extent to which IH can explain variance in reduced affective polarization beyond the discriminant constructs assessed (H4).

The original factor solution of each IH scale is replicated in the German context. The detailed hypotheses can be found in the pre-registration (see Knöchelmann et al., 2021).

All three general IH scales (CIHS, IHS, LIHS) are highly positively correlated with each other (rs ≥ .50). The topic-specific intellectual humility scale (SIHS) is moderately positively correlated with the general intellectual humility scales (rs ≥ .20).

IH is different from other established psychological constructs. We expect zero- to small correlations (|rs| ≤ .20) of IH with: social desirability, political orientation, age, gender, and participants’ highest degree of education. Moreover, we expect small to medium correlations (|rs| ≤ .40) of IH scales with openness (+), honesty-humility (+), cognitive closure (-), and need for cognition (+).

Over and above other psychological constructs (social desirability, openness, honesty-humility, cognitive closure, need for cognition), IH predicts less affective polarization.

The pre-registration is available at https://doi.org/10.23668/psycharchives.5202. Data and analyses are available (see Knöchelmann, 2024). The study was approved by the ethics committee of the authors’ university on 24th September 2021 (file reference number ‘2021-39k’).

Based on recommendations of the International Test Commission (2018), the first two authors (both German native speakers) translated the items of the three English IH scales (CIHS, LIHS, SIHS) into German independently. Afterwards, n = 8 experts of social psychological research, who were German native speakers and fluent in English, independently rated which translation captured the original item better and made suggestions on how to improve the wording. Then, the two translators jointly chose and partially revised the translations based on the suggestions. Afterwards, n = 13 participants pre-tested the whole questionnaire. Based on their comments, we made some minor revisions to improve the comprehensibility of the items and to correct some small grammatical mistakes in the IHS.

Based on several a priori power analyses for CFA with the semPower shiny app (Moshagen & Erdfelder, 2016), we needed a sample of at least N = 697 to find an RMSEA of .05 of the most complex CFA model for H1 (LIHS with 12 degrees of freedom and six manifest variables) with a desired power of .80 and an alpha error = .05; for details see the pre-registration. Participants were sampled via the panel provider Bilendi&respondi. Participants received 1.10 € for their 20-minute participation in the study. The online study was conducted between December 3rd and 21st 2021 on the platform www.soscisurvey.de. Data collection was funded by PsychLab, a service of Leibniz Institute for Psychology (ZPID), as the pre-registration successfully went through a peer-review process before data collection.

A total of N = 744 participants finished the study. Participants who indicated they were younger than 18 years old or did not have proficient German language skills (accepted answers were “fluent” and “native”) were automatically filtered out at the beginning of the survey. Applying our pre-registered criteria, we excluded participants who indicated they had not answered the questions in a genuine manner (self-report question at the end of the survey, n = 4), who did not answer all scales/items relevant for our hypotheses (because of a programming error, n = 5), or who needed less than six minutes to fill out the questionnaire (n = 38). A sample of N = 698 participants remained. No participants had to be excluded because of failing attention checks.

We used independent quotas to stratify for age, gender, and education (highest school degree) to gain a sample similar to the German population on December 31st 2020 (DESTATIS, 2021b, 2021a). At the end of the sampling process, the panel provider could not find any more participants still going to school or having no school degree resulting in the final quotas for education being slightly different from those preregistered (see supplementary file ‘additional_analyses.pdf’). Participants’ political orientation (measured on scales from 1 to 101) offered a good range (left-right placement: M = 46.76, SD = 20.45; socialist-market liberal placement: M = 50.60, SD = 22.44; progressive-conservative placement: M = 52.39, SD = 21.55).

After clicking on the survey link provided on the panel platform, participants were informed that the purpose of the study was to test the suitability of a new questionnaire to support research in German-speaking contexts. Participants who gave consent to the data protection guidelines were asked to indicate their demographics (age, gender, occupation, highest level of education, nationality, current country of residency, and level of German) and political orientation. Underage participants and participants indicating they did not speak German fluently were filtered out automatically. For these individuals, the survey ended and they were thanked for their interest in the study.

The remaining participants filled out the three general IH scales. To fill out the SIHS and assess affective polarization, we then asked participants: “Regarding which policy do you have a clear opinion? Even if this applies to several policies, please choose one option. Participants could choose one out of three options: “Use of gendered language”, “Introduction of rent caps in cities through the federal government”, and “Stop building single family houses because of environmental reasons”. Afterwards, participants filled out the SIHS, followed by the constructs used to assess discriminant and incremental validity. The order of the three general IH scales was randomized, as was the order of the scales assessing discriminant validity, and the order of items within each scale. After asking participants whether they answered the questions in an honest manner, we thanked participants for their participation in the study, provided further information about IH and gave them the opportunity to leave an anonymous comment.

We conducted all analyses as pre-registered and peer-reviewed before data collection.

Bartlett’s tests and Kaiser-Meyer-Olkin tests revealed that our data was suitable for factor analysis (Bartlett test: all ps < .001; all KMOs ≥ .82). Additionally, the assumption of multivariate normality with Mardia’s, Royston’s, Doornik-Hansens’s, Henze-Zirkler’s tests and E-statistic was violated. This is why we ran all CFA analyses with Satorra-Bentler correction (Satorra & Bentler, 1994). Moreover, we found n = 54 cases of multivariate outliers based on robust Mahalanobis distances (97.5% adjusted quantile). In cases where the exclusion of these participants changed the results substantially (i.e., changing significance levels or cut-offs), we mention both results with and without outliers. Results without outliers are displayed in supplementary file ‘analyses_and_results_without_outliers.html’.

All IH scales and subscales showed adequate reliabilities according to our pre-registered cutoff values, i.e., Cronbach’s α ≥ .65 and McDonald’s Ω ≥.70, see Table 1. For item statistics (M, SD, item intercorrelations, item selectivity), see supplementary file ‘analyses_and_results.html’.

For testing structural validity, we ran CFA with Satorra-Bentler correction in lavaan (Version 06.14-14).

To test convergent validity—we calculated two correlation matrices. First, we created a correlation matrix with all IH measures based on scale means and/or subscale means. Additionally, we calculated correlations between the IH scales based on CFA in lavaan as this takes measurement errors into account. Here, we entered all IH scale models (CIHS, IHS, LIHS, SIHS full scale) into one model. As preregistered, we anticipated poor model fit indices when testing multiple translated IH scales simultaneously in one CFA model (with no cross-loadings and correlations of items between scales allowed) as the wording of translated items is highly similar between scales. Therefore, we do not evaluate model fit indices but only provide correlations.

Overall, our hypotheses for convergent validity were mostly confirmed when using Pearson correlations and correlations obtained via SEM (see Table 2), with the following exceptions: The IHS overall scale mean correlated less than expected with the LIHS (r = .37; φ = .48; without multivariate outliers r = .46; φ = .65) and the SIHS (r = .15, φ = .19). The subfacets of the CIHS and IHS were positively correlated with all other general IH scales and subscales, but often smaller than expected. In Pearson correlations, but not SEM, the CIHS subfacet Independence of Intellect and Ego and the IHS subfacet Corrigibility were not correlated with the SIHS (ps ≥ .05). The other subfacets were positively associated with the SIHS, but often smaller than the expected cut-off value of r = .20.²2

For disattenuated correlation coefficients, see Supplementary Materials “additional analyses.pdf”, Table 3.

For testing discriminant validity, we first created four correlation matrices with an IH scale and the scales means of the discriminant constructs assessed. Second, we calculated correlations based on CFA in lavaan without evaluating model fit. For each IH scale, we built a model consisting of the IH scale and all discriminant constructs. Each discriminant construct was represented by a first-order factor on which all items of the respective construct loaded, except for the social desirability scale for which two first-order factors were modeled (PQ+ and NQ-).

The two approaches yielded similar results (see Table 3): The SIHS met all of our pre-registered cut-off values. The CIHS met all cut-off values except for both social desirability subscales. The LIHS met all cut-off values except for one social desirability sub-scale. The IHS did not show adequate discriminant validity regarding age, political orientation, social desirability, honesty-humility, need for cognition, and cognitive closure (via Pearson-correlations).²

To assess incremental validity, we conducted a blockwise regression for each IH scale with affective polarization as the dependent variable. The first block of independent variables included the psychological constructs already used to assess discriminant validity (social desirability (NQ- and PQ+), openness, honesty-humility, cognitive closure, need for cognition). Then we entered the IH scale to assess the change in explained variance of affective polarization. For the SIHS, we used affective polarization scores regarding opinion-based groups. We found that the SIHS incrementally predicted less affective polarization as expected (β = -.13, p < .001).

For the three general IH scales (CIHS, IHS, LIHS), we used affective polarization scores regarding political parties. Contrary to our hypothesis, the CIHS overall score predicted more affective polarization, ΔR² = .013, β = .13, p = .002. However, when entering the CIHS subfacets instead of the overall mean, none of the subfacets was associated with affective polarization, ΔR² = .016, |β|s < .08, ps > .08. The IHS overall scale predicted higher affective polarization, too, ΔR² = .012, β = .14, p = .004. When entering the IHS subfacets instead of the overall mean, further variance of affective polarization could be explained, ΔR² = .032. Here, Corrigibility (β = .07, p = .159) and Engagement (β = .09, p = .062) did not predict affective polarization significantly. Open-Mindedness predicted more affective polarization, β = .12, p = .008, while, as expected, Intellectual Modesty predicted less polarization, β = -.10, p = .038. Without outliers, Engagement predicted more polarization, too, β = .10; p = .038. The LIHS did not explain affective polarization beyond the other discriminant constructs, ΔR² = .003, β = .06, p = .14. However, when excluding outliers, the LIHS predicted more polarization, too, ΔR² = .008, β = .10, p = .02. Because of these unexpected effects, we ran several exploratory analyses to understand our findings better, see supplementary materials. ³3

As suggested by an anonymous reviewer, we also tested the predictive validity of the four IH scales by running several multiple regressions with all four IH scales as predictors, and Need for Cognition, Need for Cognitive Closure, Openness to Experience, and Honesty-Humility as dependent variables. These analyses can be found in the Supplementary Materials “additional_analyses.pdf”, Table 2.

Our first aim was to provide high-quality translations in German of three widely-used English IH scales (CIHS, LIHS, SIHS). Thanks to independent item translations by two researchers, a blind evaluation of the translation by N = 8 experts and German natives as well as a pre-test (N = 13), we can now offer IH items in German to the research community. This is especially important as the only existing IH scale in German (IHS) did not show adequate structural and discriminant validity in our study. Thereby, we want to facilitate studying IH across countries and languages, addressing the call for more cross-cultural research on this topic (Porter et al., 2022).

A second aim was to validate four scales with different scopes and content. Here, we made use of the intellectual humility classification framework (Porter et al., 2021) to evaluate the chosen scales. Two of the scales (CIHS, IHS) are multifaceted scales covering both (meta-)cognitions and behaviors towards the self and others. The LIHS only includes (meta-)cognitive items towards the self and others and the SIHS is the only scale covering (meta-)cognitive and self-directed items regarding a specific (political) topic. With this variety of scope and content, researchers can choose the scale that matches their research aims best (Porter et al., 2022).

Third, we compared four different established IH scales in parallel. This allowed us to systematically compare the scales to other psychological and potentially confounded constructs measured on the same instruments. The original validation studies (Alfano et al., 2017; Hoyle et al., 2016; Krumrei-Mancuso & Rouse, 2016; Leary et al., 2017) used different scales to assess discriminant validity, making a direct comparison between the scales more difficult. In contrast, we only included established scales validated in the German context, and we were therefore able to directly compare the IH scales regarding their discriminant validity.

Our research also has several limitations that can inspire future research. Based on the insights of the study as well as its strengths and limitations, we suggest several avenues for further research on IH assessment.

First, all of the chosen IH measures were self-report questionnaires. As these are a valid tool to assess theoretical constructs and used commonly in psychological research (Haeffel & Howald, 2010), our validation of these scales addresses the needs of many researchers. However, it can be beneficial to develop behavioral measures of IH (Van Tongeren et al., 2022a, 2022b), especially when being interested in measuring IH in social interactions (Hanel et al., 2023; Meagher et al., 2020). Here, it would be fascinating to see how different self-report measures, especially those with a rather (meta-)cognitive scope, can predict intellectually humble behaviors. Previous research showed that intellectual humility in conversation (e.g., interrupting others less, more often conveying one’s opinion as tentative) coded by linguists was not associated with the CIHS (Hanel et al., 2023), potentially due to the gap between cognitions and behaviors (Minson & Chen, 2021; Van Tongeren et al., 2022a, 2022b). It would be of interest to see if this also applies to other intellectual humility measures, such as the specific intellectual humility scale.

Second, the IH scales chosen for validation conceptualize IH rather as a trait than as a state (Ballantyne, 2023; Du & Cai, 2020). This enables researchers to reliably study between-person variations of IH, and its associations with political constructs (e.g., Bowes et al., 2020; Krumrei-Mancuso & Newman, 2020). However, there might be substantive within-person variation of IH, for instance depending on the norms of a given context (Porter & Cimpian, 2023) or the availability of mental resources in a specific situation (Hanel et al., 2023). Here, it would be beneficial to develop and validate additional state-like IH measures as Zachry et al. (2018) did. This would tap potential within-person variations of IH better than the existing IH measures and enable research investigating in which contexts people show IH.

Third, despite several methodological strengths, there are still some aspects that we could not implement within our study. Future IH validation research could address these open questions. For instance, we only assessed the constructs used for evaluating discriminant and incremental validity after measuring the IH scales. We decided to do so because we did not want the participants’ responses on the IH scales to be impacted by having answered these questionnaires before. However, filling out the IH scales might have influenced answers on the discriminant scales, too. Thus, future experimental research could systematically assess order effects of when IH is measured in a survey.

Fourth, the assessment of convergent validity in our study is limited. Ideally, convergent validity of a new measurement instruments is assessed by comparing the new instrument to existing validated scales. However, no IH measurement instrument (or closely related scale such as open-minded cognition) existed in the German context when conducting the study. We therefore assessed convergent validity by correlating the different IH scales with each other. This procedure leaves the possibility that none of our translated scales measures IH very well. However, we evaluate this scenario as relatively unlikely given that all scales used were already validated in an English-speaking context. Additionally, our translated IH scales correlated with a higher need for cognition and a lower need for cognitive closure, which also hint at convergent validity. Nonetheless, future work is needed to assess convergent validity of our IH scales, for instance with behavioral data (Van Tongeren et al., 2022a, 2022b), or text-based information (Stavropoulos et al., 2024).

Lastly, as IH is a promising psychological construct to address societal issues, we assessed incremental in relation to affective polarization. Our findings showed that the SIHS had the highest incremental validity to predict lower affective polarization. This might be due to the fact that for this scale, we measured affective polarization regarding opinion-based groups. Regarding the three general IH scales, we measured affective polarization via political parties where the outgroup was chosen via the least-liked group paradigm (Gibson, 2013). There might be other paradigms, however, which are better suited to assess affective polarization in the context of multiparty-systems (Harteveld, 2021; Wagner, 2021) such as Germany. To sum up, research is just at the starting point to understand how IH is related to affective polarization and how it can bridge political divides. Here, a fascinating avenue might be to study affective polarization in more diverse ways or to use specific behaviors and behavioral intentions such as approaching contrary-minded others (Knöchelmann & Cohrs, 2025).

IH is a psychological construct relevant to addressing societal problems such as bridging political divides. It is associated with many positive outcomes such as higher well-being, or learning outcomes at school. To contribute to more research on IH outside English-speaking contexts, we validated and compared four established IH scales with different content and scope in German. Our sample was representative of age, gender, and education of Germany’s population and the study was pre-registered and peer-reviewed before data collection. Results showed that the German versions of the CIHS, LIHS, and SIHS can be compared to the original English scales, whereas the IHS did not meet all of our pre-registered criteria, potentially due to cross-cultural differences between Germany and Switzerland. We hope that our work facilitates more cross-cultural work on IH.