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Frontiers in Social Psychology ·

Volume 4 - 2026 | https://doi.org/10.3389/frsps.2026.1715876

Understanding extremist personality: the mediating influence of Regulatory Modes and the need for cognitive closure in the Quest for Significance

  • Luis Carlos Jaume1,2*corresponding author
  • Marcelo Agustin Roca1,3
  • Nahuel Hugo Ezequiel Duhalde1,4
  • Hugo Simkin1,2,5
  • Sara Liebana6
  • Pedro Altungy Labrador6
  1. 1Instituto de Investigaciones, Facultad de Psicología, Universidad de Buenos Aires, Buenos Aires, Argentina
  2. 2Consejo Nacional de Investigaciones Cientificas y Tecnicas, Buenos Aires, Argentina
  3. 3Facultad de Psicology Relaciones Humanas, Universidad Abierta Interamericana, Buenos Aires, Argentina
  4. 4Universidad Maimonides, Buenos Aires, Argentina
  5. 5Facultad de Educación y Ciencias Sociales, Universidad Andres Bello, Santiago, Chile
  6. 6Universidad Europea de Madrid, Facultad de Biomédicas, Madrid, Spain
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Abstract

Understanding the psychological mechanisms underlying extremist personality helps explain why some individuals endorse rigid or polarized positions. Extremist personality is conceptualized as a self-regulatory tendency characterized by motivational imbalance, cognitive inflexibility, and strong commitment to salient goals. This study examined how the quest for significance, regulatory modes (Locomotion and Assessment), and the need for cognitive closure relate to extremist personality. A sample of 693 Argentine adults (M age = 41.9, SD = 15.42, range: 18–85; 61.4% women) completed an online questionnaire assessing quest for significance, regulatory modes, need for cognitive closure, and extremist personality. Structural equation modeling was conducted to test direct and indirect effects. Quest for significance positively predicted extremist personality both directly (β = 0.232, p < 0.001) and indirectly through Locomotion (β = 0.190, p = 0.001). Locomotion strongly predicted extremism (β = 0.464, p < 0.001; total effect = 0.576). Assessment was not significantly related to extremism (β = −0.048, p = 0.516). Cognitive closure weakly predicted extremism (β = 0.083–0.084, p > 0.05) and did not mediate the relationship between significance and extremism, despite being strongly predicted by significance (β = 0.160–0.385, p < 0.001). Findings suggest that motivational urgency and action-oriented self-regulation are key mechanisms associated with extremist personality, highlighting the central role of locomotion rather than evaluative orientation or cognitive closure in explaining extremist tendencies.

Keywords

Introduction

Social and political extremism represents a persistent challenge to social cohesion and democratic stability (Altungy et al., 2025). Understanding the psychological mechanisms that underlie this phenomenon is essential for explaining why some individuals come to endorse beliefs and actions that fall outside socially accepted boundaries. Contemporary theorizing suggests that extremist behaviors may emerge from a motivational imbalance in which a single goal becomes so dominant that it eclipses prior norms and values (Kruglanski et al., 2019; Szumowska et al., 2023). Under such conditions, individuals may rely on prohibited or normatively unacceptable means when those means are perceived as essential to achieving the focal goal.

This imbalance is further reflected in the notion of Extreme Personality, a relatively novel proposal that has been defined as characterized by closed-mindedness, polarized beliefs, and an underestimation of the consequences of one's actions (Kruglanski et al., 2021; Szumowska et al., 2023; Zmigrod et al., 2019).

However, extremism could not be reduced to personality dispositions alone. Socio-cognitive theories show that individuals seeking certainty, strong identity, and a sense of personal value are particularly susceptible to extremist groups (Hogg and Abrams, 1999; Kruglanski and Orehek, 2011). Situations of adversity or uncertainty amplify the appeal of highly entitative groups, facilitating the adoption of rigid or even hostile ideologies (Hogg et al., 2013; Milla et al., 2022). Although the need for meaning is universal and does not inherently lead to violence (Milla et al., 2022), experiences of significance loss can intensify the urge to restore value, thereby increasing the acceptance of radical strategies (Webber and Kruglanski, 2016).

Within this broader landscape, the Quest of Significance Theory (QFS) offers a relevant starting point. It proposes that people strive to feel valued and respected, and that losses in this domain generate a powerful motivation to restore social worth (Kruglanski et al., 2022). This motivational dynamic becomes especially salient under real or perceived crises, where significance losses may stem from rejection, humiliation, or personal failure (Altungy et al., 2025; Anderson et al., 2015). The erosion of personal worth fuels efforts to regain significance, either by defending the in-group or by demonstrating one's value through socially sanctioned or culturally meaningful behaviors (Jasko et al., 2019; Kruglanski and Bertelsen, 2020; Schumpe et al., 2020). Cultural narratives play a crucial role in shaping what counts as meaningful action, and can even legitimize extreme conduct when framed as honorable or socially rewarded (Kruglanski et al., 2022). Accumulating evidence shows that QFS predicts both violent and non-violent forms of extremism, depending on the extent to which actions align with socially shared values (Molinario et al., 2025), and that significance loss combined with social networks and group narratives heightens vulnerability to extremist ideologies (Da Silva et al., 2024). A key foundational model for the present study is the serial mediation proposed by (Jasko et al. 2020), demonstrating that QFS relates to violent extremism through ideological extremism and highlighting the importance of group-based recognition and intergroup hostility (see also Kruglanski et al., 2014; Milla et al., 2022). While QFS explains why individuals may seek meaning, it does not specify how this motivation translates into action. The Theory of Regulatory Modes (Kruglanski et al., 2000) helps clarify this process by distinguishing two complementary self-regulatory orientations: (1) Locomotion - the tendency to move quickly and persistently toward goals (Jaume and Roca, 2020; Kruglanski et al., 2013)-, and (2) Assessment- the tendency to evaluate alternatives and consequences (Kruglanski et al., 2000). These orientations offer insight into how people high in QFS may differ in the way they pursue goal restoration. Locomotion fosters direct and sustained implementation of goals, potentially amplifying the urgency of significance restoration, whereas Assessment may either temper or reinforce the desire for certainty depending on contextual cues. Both modes are associated with epistemic dynamics such as the pursuit of clarity and decisiveness (Higgins et al., 2003; Morris and Pinelli, 2022; Roca et al., 2025), thereby shaping the impulsivity or rigidity with which significance-seeking becomes enacted.

Beyond the motivational dynamics of QFS, cognitive tendencies that shape how individuals process uncertainty also contribute to these processes. One such tendency is the Need for Cognitive Closure (NFC), defined as the desire for firm answers and an aversion to ambiguity (Kruglanski, 2023). High NFC leads individuals to “seize and freeze” on early information, maintaining rigid beliefs and decreasing openness to alternatives (Kruglanski, 2004; Roca et al., 2022). This cognitive style is associated with polarized attitudes, reduced flexibility, and greater susceptibility to extreme or dogmatic viewpoints (Jaume et al., 2015; Obaidi et al., 2023). NFC thus provides the epistemic terrain through which significance-seeking can be channeled into extremist commitments (Kruglanski et al., 2021; Kruglanski, 2023).

Taken together, these bodies of work delineate a motivational, regulatory, and cognitive trajectory leading to extremism. On this basis, the next sections introduces the aims and hypothesis of the present study.

Aim of the study

The present study aims to examine the psychological mechanisms that link QFS to extremist personality orientations, with a particular focus on the mediating Regulatory Modes and NFC. Understanding how these motivational dispositions contribute to extremist personality tendencies is crucial for informing interventions designed to strengthen democratic functioning, reduce polarization, and promote constructive political engagement. By identifying the pathways through which QFS fosters susceptibility to extremism, this research seeks to offer insights relevant for policymakers, educators, and civil society organizations concerned with social cohesion.

Although previous studies have explored serial mediation models connecting QFS with Extreme Personality (e.g., Jasko et al., 2020; Milla et al., 2022), no research has integrated Regulatory Mode theory into this framework. This gap is noteworthy because both Regulatory Modes and QFS share a motivational foundation in goal-directed behavior oriented toward meaningful ends. Furthermore, while NFC has been consistently associated with extremism and QFS (Kruglanski, 2023; Kruglanski et al., 2021), its potential mediational role in conjunction with Regulatory Modes remains insufficiently examined.

The need for such integration is particularly relevant in the Argentine socio-political context, where recent shifts in political participation, ideological polarization, and the emergence of anti-establishment discourses have heightened interest in understanding the motivational bases of extreme political attitudes. Although research in Argentina has examined NFC, Regulatory Modes, QFS, and extremism separately (e.g., Altungy et al., 2025; Jaume et al., 2022a, 2025; Roca et al., 2022, 2025), no study has proposed or tested a unified theoretical model capturing their joint functioning. Addressing this gap may provide context-sensitive insights into how individuals in Argentina become susceptible to extremist narratives.

To advance this literature, the present study proposes and empirically tests a model in which Regulatory Modes and NFC jointly mediate the association between QFS and extremist personality orientations. See Figure 1 for an illustrated theoretical model.

Theoretical model. EXT, Extremism; QFS, Quest for Significance; NFCP, Need for Cognitive Closure Permanence; NFCP, Need for Cognitive Closure Urgency; RMA, Regulatory Mode Assessment; RML, Regulatory Mode Locomotion.
Figure 1. Theoretical model. EXT, Extremism; QFS, Quest for Significance; NFCP, Need for Cognitive Closure Permanence; NFCP, Need for Cognitive Closure Urgency; RMA, Regulatory Mode Assessment; RML, Regulatory Mode Locomotion.

Hypothesis

Based on existing theoretical and empirical work, the following hypotheses are formulated:

Research on the QFS shows that the drive to restore or secure a sense of personal significance increases openness to identity-based, norm-transgressive, and extreme forms of self-definition (Jasko et al., 2020; Kruglanski et al., 2021). Extreme Personality—such as heightened sensitivity to symbolic threats or rigid goal-oriented behavior—has been conceptualized as a proximal expression of the QFS motivational dynamic (Milla et al., 2022). Based on this framework, we expected a positive association between QFS and Extreme Personality.

  • H1. QFS will be positively associated with Extreme Personality.

Regulatory Mode Theory posits that individuals differ in their characteristic tendency to engage in locomotion (RML) or assessment (RMA) processes during goal pursuit (Kruglanski et al., 2000). Extreme personality tendencies are theorized to intensify both modes, either by accelerating action initiation (RML) or amplifying evaluative vigilance (RMA). Furthermore, individuals with more extreme motivational dispositions often show higher NFC, as they prefer quick, unambiguous solutions that reduce uncertainty (Kruglanski, 2023). Thus, we expected Extreme Personality to predict higher RML, RMA, and NFC.

  • H2. Extreme Personality will be positively associated with RML, RMA, and NFC.

NFC has been consistently linked to categorical thinking, rigidity, and preference for clear-cut ideological positions, all of which predict authoritarian or extremist personality orientations (Kruglanski et al., 2021). Similarly, high RML has been associated with uncritical goal pursuit, greater susceptibility to mobilization pressures, and readiness to act toward high-significance goals (Kruglanski et al., 2021). Since QFS motivates individuals to regain significance through actions aligned with extreme groups or causes, the combination of high NFC or high RML may serve as pathways connecting QFS to extremist personality. Therefore, we predicted that NFC and RML would mediate this association.

  • H3. NFC and RML will be positively associated with extremist personality.

These variables are expected to mediate the relationship between QFS and extremism.

Method

Design

The study employed a non-experimental, cross-sectional, correlational design, based on the administration of self-report questionnaires online.

Sample

The study employed a non-probabilistic convenience sampling method, targeting adult participants residing in Argentina. The initial sample consisted of 737 participants who completed an online questionnaire administered anonymously between April and August 2020. Following data screening procedures (i.e., checks for completeness and multivariate outliers), 693 valid cases remained for analysis. Of these, 426 were women (61.4%) and 267 were men (38.6%), with a mean age of 41.9 years (SD = 15.42; range = 18–85). An a priori power analysis conducted with G*Power indicated that, to detect a small effect size (F2 = 0.04) with α = 0.05 and statistical power of 0.80, a minimum sample size of 277 participants was required (see Table 1).

Table 1. Sociodemographic characteristics of the sample.

VariableCategory**n (%)**
GenderWoman426 (61.4%)
Man267 (38.6%)
EducationCompleted primary school8 (1.2%)
Incomplete secondary school48 (6.9%)
Completed secondary school95 (13.7%)
Incomplete tertiary education49 (7.1%)
Completed tertiary education98 (14.1%)
Incomplete undergraduate education188 (27.1%)
Completed undergraduate education207 (29.9%)

Instruments

Regulatory Mode

The Regulatory Modes of RML and RMA were measured using the Spanish version adapted for Argentina by (Roca et al. 2025). This instrument captures two independent, yet not mutually exclusive, dimensions. The RML subscale assesses the tendency to initiate and maintain movement toward goals (e.g., “I am a 'workaholic”'), whereas the RMA subscale evaluates the tendency to reflect on and critically appraise alternative courses of action before deciding (e.g., “I like evaluating other people's plans”). Each subscale comprises six items, rated on a six-point Likert scale ranging from 1 (Completely disagree) to 6 (Completely agree). In this research, the internal reliability indicated an acceptable internal consistency in both subcales (RML; α = 0.62; ω = 0.63) and (RMA; α = 0.71; ω = 0.71).

Quest for Significance

A translated version of the Quest for Significance Scale (QFS; Molinario et al., 2021) was used, which has shown adequate internal consistency and temporal stability. It consists of 10 items assessing the motivation to achieve personal significance (e.g., “I wish I could be more respected”). Responses were recoded on a five-point Likert scale (1 = Strongly disagree to 5 = Strongly agree). In the current study, internal reliability was excellent, as estimated using the Ordinal alpha (α = 0.92; ω = 0.92).

Extreme Personality

Extreme Personality was measured using the 15-item scale developed by (Szumowska et al. 2026). This instrument assesses the intensity and rigidity of political beliefs, including the endorsement of violence and intolerance toward opposing viewpoints (e.g., “My life is usually dominated by one main pursuit/desire”). Participants responded on a five-point Likert scale ranging from 1 (Strongly disagree) to 5 (Strongly agree). In this current study, excellent internal consistency (α = 0.90; ω = 0.90).

Need for Cognitive Closure

The study employed the short version of the Revised Need for Cognitive Closure Scale (RT-NFC; Pierro and Kruglanski, 2005), adapted for the Argentine context by (Jaume et al. 2022b). This instrument used in the present study consists of eight items distributed across two subdimensions: Urgency Tendency (NFCU; e.g., “When I am uncertain, I prefer to make fast decisions, whatever they are”; α = 0.82; ω = 0.83) and Permanence Tendency (NFCP; e.g., “I prefer to engage in activities where is clear what I have to do and how I have to do it”; α = 0.60; ω = 0.62). Participants responded using a six-point Likert-type scale that assesses their level of agreement, ranging from 1 = Completely disagree to 6 = Completely agree.

Sociodemographic Data

Sociodemographic Data Information on age, gender, educational level, and place of residence was also collected (see further details in Table 1).

Procedure

Data were collected through an online questionnaire distributed via social media and mailing lists. Participants accessed the survey link voluntarily and could only submit their responses once. Before beginning the questionnaire, participants were presented with an informed consent statement outlining the study objectives, confidentiality assurances, and their right to withdraw at any time. Consent was considered implied upon participation. The questionnaire included sociodemographic questions and the instruments described above. The average completion time was approximately 15 minutes, and all procedures complied with Argentine Law No. 25,326 on Personal Data Protection (Argentina, 2000).

Data analysis

Before the analyses, the dataset was cleaned by identifying univariate and multivariate outliers using the Median Absolute Deviation (MAD) and Minimum Covariance Determinant (MCD) methods, respectively. Each dimension or subscale was first examined individually with the MAD, and multivariate outliers were then detected considering all items of each scale collectively, following the recommendations of (Leys et al. 2019). Regarding sociodemographic variables included as predictors, gender was recoded as a dichotomous variable (0 = Female, 1 = Male) to allow its inclusion as a covariate in the SEM. Although educational level is an ordinal variable, it was treated as continuous due to its eight response categories, a practice recommended for ordinal variables with five or more levels when using robust estimators such as MLR in SEM (Kline, 2023; Rhemtulla et al., 2012).

A Structural Equation Model (SEM) with latent variables was estimated to test the hypothesized relationships among constructs, thus incorporating a measurement model for each instrument. Descriptive analyses were subsequently performed, including the calculation of ordinal alpha coefficients and correlations among variables.

Model estimation was conducted using the Maximum Likelihood Robust (MLR) method, and 5,000 bootstrap samples were employed to obtain robust standard errors and to estimate direct and indirect effects. Model fit was evaluated using the Chi-square (χ2), Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR).

According to conventional criteria (Hu and Bentler, 1999; Kline, 2023), CFI and TLI values above 0.90, RMSEA values below 0.08, and SRMR values below 0.05 indicate acceptable fit. However, as (Marsh et al. 2004) emphasized, in complex models with multiple latent constructs and parameters, slightly lower values (e.g., CFI/TLI ≥0.85) can still be considered adequate when accompanied by satisfactory RMSEA and SRMR values and strong theoretical justification (see also Bentler, 2007; West et al., 2012).

All analyses were conducted in R (R Core Team, 2023) using the lavaan package (Rosseel, 2012) and complementary packages for descriptive and reliability analyses.

Results

Descriptive statistics

Outlier analyses were first conducted to ensure the quality of the data. Initially, 27 participants were excluded due to missing responses on one or more items, resulting in a reduced sample of 710 participants. Subsequently, 17 multivariate outlier cases were detected and removed following the MCD procedure recommended by (Leys et al. 2019), leading to a final sample of 693 participants. No univariate outliers were identified in any of the scales based on the median absolute deviation (MAD) criterion.

Sociodemographic characteristics of the final sample are presented in Table 1. Meanwhile, descriptive statistics and reliability indices for all scales are presented in Table 2. The psychometric variables demonstrated good reliability, as indicated by both ordinal alpha and McDonald's omega.

Table 2. Descriptive data.

Variable*M**Mdn**SD*MinMaxRangeSkewnessKurtosisαω
QFS44.04513.50107060−0.35−0.300.920.92
RMA18.3185.4253025−0.12−0.520.710.71
RML18.4194.87530250.02−0.310.620.63
EXT57.95717.1515102870.16−0.600.900.90
NFCU10.3104.35420160.38−0.700.820.83
NFCP14.2143.4442016−0.36−0.370.600.62
Age41.94015.421885670.37−0.87——

α, ordinal alpha; ω, omega; SD, standard deviation; EXT, Extremism; QFS, Quest for Significance; M, mean; Max, maximum; Mdn, median; Min, minimum; NFCP, Need for Cognitive Closure Permanence; NFCU, Need for Cognitive Closure Urgency; RMA, Regulatory Mode Assessment; RML, Regulatory Mode Locomotion. Reliability coefficients (α and ω) were estimated using polychoric correlations.

Correlation among the main variables

Descriptive statistics and correlations among the study variables are presented in Table 3. Spearman correlations indicated that QFS was positively correlated with EXT, RMA, RML, NFCU, and NFCP. Age showed significant negative correlations with QFS (r = −0.11, p < 0.01), RMA (r = −0.34, p < 0.001), and RML (r = −0.14, p < 0.001), as well as a positive correlation with NFCU (r = 0.19, p < 0.001).

Table 3. Correlation matrix.

123456789
1. QFS—
2. RMA0.36***—
3. RML0.17***0.30***—
4. EXT0.33***0.21***0.41***—
5. NFCU0.11**0.010.18***0.23***—
6. NFCP0.33**0.28***0.25***0.31***0.41***—
7. Age−0.11**−0.34***−0.14***−0.070.19***−0.07—
8. Edu0.000.06−0.04−0.09*−0.17***−0.13***0.04—
9. Gender0.000.08*−0.020.11**0.06−0.01−0.09*−0.14***—

EXT, Extremism; QFS, Quest for Significance; NFCP, Need for Cognitive Closure Permanence; NFCU, Need for Cognitive Closure Urgency; RMA, Regulatory Mode Assessment; RML, Regulatory Mode Locomotion; Gender (0 = female, 1 = male). Edu, Education (1 = Incomplete Primary School, 8 = Completed undergraduate education).

*p < 0.05.

**p < 0.01.

***p < 0.001.

Education was negatively associated with EXT (r = −0.09, p < 0.05), NFCU (r = −0.17, p < 0.001), and NFCP (r = −0.13, p < 0.001). Gender showed small but significant positive correlations with RMA (r = 0.08, p < 0.05) and EXT (r = 0.11, p < 0.01), and a negative association with Age (r = −0.09, p < 0.05) and Education (r = −0.14, p < 0.001).

Measurement model and structural equation modeling

Confirmatory factor analyses were conducted separately for each construct using Maximum Likelihood estimation with robust standard errors (MLR). The Locomotion scale (5 items) showed acceptable fit: CFI = 0.965, TLI = 0.929, RMSEA = 0.061 [90% CI (0.029, 0.095)], SRMR = 0.031. The Assessment scale (5 items) demonstrated good fit: CFI = 0.989, TLI = 0.978, RMSEA = 0.042 [90% CI (0.000, 0.081)], SRMR = 0.022. Both Need for Closure subscales showed excellent fit: NFCU (4 items): CFI = 1.000, TLI = 1.008, RMSEA = 0.000 [90% CI (0.000, 0.000)], SRMR = 0.002; NFCP (4 items): CFI = 1.000, TLI = 1.018, RMSEA = 0.000 [90% CI (0.000, 0.038)], SRMR = 0.004.

The Quest for Significance scale (10 items) initially showed suboptimal fit: CFI = 0.924, TLI = 0.902, RMSEA = 0.112 [90% CI (0.097, 0.126)], SRMR = 0.051. Four theoretically justified residual correlations were added between conceptually related items (QFS_1 ~~ QFS_2, QFS_6 ~~ QFS_7, QFS_6 ~~ QFS_9, QFS_3 ~~ QFS_10), resulting in improved fit: CFI = 0.969, TLI = 0.955, RMSEA = 0.076 [90% CI (0.060, 0.092)], SRMR = 0.038. All residual correlations were theoretically justified based on shared content and were not added solely for statistical improvement.

The Extremism scale required iterative refinement. The initial 15-item model showed poor fit: CFI = 0.792, TLI = 0.757, RMSEA = 0.119 [90% CI (0.111, 0.127)], SRMR = 0.080. Based on modification indices and theoretical considerations, items EXTREMISM_2, EXTREMISM_4, and EXTREMISM_12 were sequentially removed due to high residual correlations with other items, which could compromise the construct's discriminant validity. After removing these items, the 12-item scale showed improved but still suboptimal fit: CFI = 0.871, TLI = 0.842, RMSEA = 0.107 [90% CI (0.097, 0.118)], SRMR = 0.066. To achieve acceptable fit, three theoretically justified residual correlations were added between conceptually related items (EXTREMISM_1 ~~ EXTREMISM_6, EXTREMISM_1 ~~ EXTREMISM_3, EXTREMISM_14 ~~ EXTREMISM_15), resulting in the final model with adequate fit: CFI = 0.925, TLI = 0.903, RMSEA = 0.084 [90% CI (0.073, 0.096)], SRMR = 0.052. The final 12-item Extremism scale demonstrated improved internal consistency (α = 0.89, ω = 0.89). As with the QFS, residual correlations were justified conceptually and not introduced solely for statistical gain.

The structural component of the model specified that QFS predicted all four mediators (RML, RMA, NFCU, NFCP). At the same time, Extremism was regressed on these mediators and directly on QFS, allowing for the estimation of both direct and indirect (mediated) effects. Sociodemographic variables (Age, Education, and Gender) were included as control covariates, predicting all latent mediators and Extremism, thus accounting for their unique contributions. Covariances among the mediators were freely estimated to capture shared variance but were not theoretically interpreted.

The final structural model demonstrated adequate fit: χ2(821) = 2,031.48, p < 0.001; CFI = 0.901, TLI = 0.892, RMSEA = 0.043 [90% CI (0.041, 0.046)], SRMR = 0.052. Although the chi-square statistic was significant, as expected with large samples, the CFI and TLI values approached the conventional 0.90 threshold, while RMSEA and SRMR were well within acceptable ranges (Hu and Bentler, 1999), indicating adequate model-data correspondence.

Structural model results

Figure 2 presents the final structural model with standardized path coefficients. As shown in the figure, the model reveals both direct and indirect pathways linking Quest for Significance to political extremism through multiple motivational and cognitive mediators.

Final structural model with standardized path coefficients. Standardized coefficients are shown. Green arrows, factor loadings; Blue arrows, structural regressions. For clarity, only statistically significant structural paths (*p* < 0.05) are emphasized. Control variables and covariances among mediators are included in the model but not depicted in the figure. EXT, Extremism; QFS, Quest for Significance; NFCP, Need for Cognitive Closure Permanence; NFCP, Need for Cognitive Closure Urgency; RMA, Regulatory Mode Assessment; RML, Regulatory Mode Locomotion.
Figure 2. Final structural model with standardized path coefficients. Standardized coefficients are shown. Green arrows, factor loadings; Blue arrows, structural regressions. For clarity, only statistically significant structural paths (p < 0.05) are emphasized. Control variables and covariances among mediators are included in the model but not depicted in the figure. EXT, Extremism; QFS, Quest for Significance; NFCP, Need for Cognitive Closure Permanence; NFCP, Need for Cognitive Closure Urgency; RMA, Regulatory Mode Assessment; RML, Regulatory Mode Locomotion.

Table 4 presents the full set of structural path coefficients, including direct, indirect, and control-variable effects. Regarding the predictive effects of QFS on the mediators, the model shows that Quest for Significance significantly predicted all four mediating variables: RML (β = 0.190, p = 0.001), RMA (β = 0.430, p < 0.001), NFCU (β = 0.160, p = 0.001), and NFCP (β = 0.385, p < 0.001). These findings indicate that individuals with higher Quest for Significance tend to adopt more action-oriented regulatory styles (RML), more evaluative and comparative orientations (RMA), and higher needs for both cognitive understanding and predictability.

Table 4. Path analysis results.

Endogenous variableExogenous variableβ (Std.)SE*p*95% CI
Direct effects
RMLQFS0.1900.0520.001–
Age−0.1300.0330.006–
Education−0.0690.0360.174–
Gender−0.0710.0670.124–
RMAQFS0.4300.064< 0.001–
Age−0.3500.037< 0.001–
Education0.1210.0330.005–
Gender0.0590.0670.163–
NFCPQFS0.3850.053< 0.001–
Age−0.1210.0270.015–
Education−0.1090.0280.038–
Gender−0.0490.0530.310–
NFCUQFS0.1600.0520.001–
Age0.2120.037< 0.001–
Education−0.1170.0380.007–
Gender0.0440.0740.295–
QFSAge−0.1120.0310.005–
Education0.0210.0330.619–
Gender−0.0010.0670.975–
ExtremismQFS (direct)0.2320.054< 0.001–
RML0.4640.104< 0.001–
RMA−0.0480.0770.516–
NFCU0.0840.0490.109–
NFCP0.0830.1000.219–
Gender0.1570.064< 0.001–
Age−0.0080.0350.864–
Education−0.0240.0330.565–
Indirect effects (QFS extremism)
Via RML0.0880.0280.002(0.030, 0.150)
Via RMA−0.0210.0300.492(−0.087, 0.043)
Via NFCU0.0130.0090.123(−0.004, 0.034)
Via NFCP0.0320.0250.208(−0.018, 0.089)
Total indirect0.3440.054< 0.001(0.007, 0.218)
Total effect
ExtremismQFS (total)0.5760.054< 0.001–

RML, Regulatory Mode Locomotion; RMA, Regulatory Mode Assessment; NFCU, Need for Cognitive Closure Urgency; NFCP, Need for Cognitive Closure Permanency; QFS, Quest for Significance; Extremism, Extreme Personality; Age, age of participant; Education, educational attainment level; Gender, dichotomous variable coded (0 = female, 1 = male). Standardized coefficients (β) are reported. SE, standard error. p = significance level. The 95% confidence intervals for indirect effects were estimated using bootstrapping with 5,000 resamples.

In addition to these mediated pathways, QFS had a direct positive effect on Extremism (β = 0.232, p < 0.001), indicating that individuals higher in QFS tend to endorse more extreme political positions, independent of the mediating mechanisms.

To formally test mediation hypotheses, indirect effects were estimated using bias-corrected bootstrap procedures with 5,000 resamples (Preacher and Hayes, 2008). Among the four hypothesized mediators, only RML showed a significant indirect effect linking QFS to Extremism [β = 0.088, p = 0.002, 95% CI (.030, 0.150)]. This indicates that individuals with a higher Quest for Significance tend to adopt a more locomotion-oriented regulatory style (focused on movement, progress, and goal achievement), which in turn predicts greater political extremism.

The indirect effects through the other three mediators were not statistically significant: RMA [β = −0.021, p = 0.492, 95% CI (−0.087, 0.043)], NFCU [β = 0.013, p = 0.123, 95% CI (−0.004, 0.034)], and NFCP [β = 0.032, p = 0.208, 95% CI (−0.018, 0.089)]. Despite QFS significantly predicting these mediators, they did not, in turn, predict Extremism, resulting in non-significant mediation pathways. Interestingly, RML was the only mediator to significantly predict Extremism (β = 0.464, p < 0.001), while the effects of RMA (β = −0.048, p = 0.516), NFCU (β = 0.084, p = 0.109), and NFCP (β = 0.083, p = 0.219) on Extremism were non-significant.

The findings show that QFS strongly predicts extremist personality overall (β = 0.576, p < 0.001). Part of this influence occurs directly (β = 0.232, p < 0.001), and part operates through intermediary psychological mechanisms (β = 0.344, p < 0.001). Among these mechanisms, only locomotion showed a significant mediating role, accounting for 15.3% of the total effect (calculated as 0.088/0.576). In total, 59.7% of QFS's impact on Extremism was transmitted indirectly (calculated as 0.344/0.576), while 40.3% reflected a direct influence (calculated as 0.232/0.576) that is not explained by the mediators included in the model.

Effects of control variables

With respect to the sociodemographic covariates, Age was negatively associated with RML (β = −0.130, p = 0.006) and RMA (β = −0.350, p < 0.001), suggesting that older participants exhibited lower levels of both locomotion and assessment orientations. Conversely, Age was positively associated with NFCU (β = 0.212, p < 0.001), indicating that older individuals demonstrated a greater need for cognitive understanding. Additionally, Age was negatively associated with NFCP (β = −0.121, p = 0.015) and with QFS itself (β = −0.112, p = 0.005).

Educational level showed mixed patterns: it was negatively related to NFCU (β = −0.117, p = 0.007) and NFCP (β = −0.109, p = 0.038), but positively associated with RMA (β = 0.121, p = 0.005). This suggests that higher education is associated with greater assessment orientation but lower needs for cognitive closure.

Gender had a significant effect only on Extremism (β = 0.157, p < 0.001), with men scoring higher than women. Notably, Gender did not significantly predict any of the mediating variables (RML: β = −0.071, p = 0.124; RMA: β = 0.059, p = 0.163; NFCU: β = 0.044, p = 0.295; NFCP: β = −0.049, p = 0.310) or QFS (β = −0.001, p = 0.975), indicating that its influence on Extremism operates through a direct path rather than through the motivational or cognitive mediators. None of the other control variables (Age: β = −0.008, p = 0.864; Education: β = −0.024, p = 0.565) directly predicted Extremism, suggesting that their effects operate primarily through the mediating pathways.

Discussion

This study tested a mediation model linking Quest for Significance (QFS) to extremist personality through regulatory modes (locomotion and assessment) and Need for Cognitive Closure (NFC).

Hypothesis 1, predicting a positive association between QFS and extremism, received strong support, with QFS showing a substantial total effect on extremist personality. This finding aligns closely with theoretical predictions from the 3N model of radicalization (Kruglanski et al., 2019, 2021, 2022), which posits that individuals experiencing significance loss seek to restore meaning through extreme behaviors. Our results are consistent with prior evidence demonstrating that QFS motivates both violent and non-violent extremism (Jasko et al., 2019; Molinario et al., 2025), confirming that individuals who perceive low social value or experience significance threats are more likely to endorse extreme political positions.

However, the magnitude of this effect—accounting for approximately 33% of the variance in extremist personality—suggests that QFS is a powerful but not exclusive determinant. This aligns with (Kruglanski et al. 2022)'s argument that significance quest represents only one of three components (need, narrative, network) required for radicalization. The large direct effect implies that additional unmeasured mechanisms—such as identity fusion (Swann et al., 2012) or moral conviction (Skitka et al., 2021)—also link QFS to extremism.

Similarly, Hypothesis 2 was fully supported; QFS significantly predicted all mediating variables: RML, RMA, NFCU, and NFCP. This pattern confirms that significance threats activate multiple psychological systems simultaneously, consistent with the multidimensional nature of radicalization described by (Kruglanski et al. 2014, 2023). The findings align with prior research showing that goal pursuit under significance threat involves both motivational (regulatory modes) and cognitive (closure needs) components (Higgins et al., 2003; Milla et al., 2022; Obaidi et al., 2023).

Notably, QFS showed significant positive associations with both RMA and RML. This pattern suggests that significance threats may activate evaluative processes as individuals search for significance-restoring goals. Such activation of assessment contradicts the common portrayal of extremists as unreflective actors (Victoroff, 2005) and instead indicates that individuals experiencing significance loss engage in careful consideration of potential pathways to restore meaning. This interpretation aligns with Kruglanski and Orehek's (2011) argument that extremists carefully select goals capable of restoring significance, even if they later pursue those goals in a single-minded fashion.

In contrast, Hypothesis 3 received only partial support, marking the study's most theoretically significant finding. While RML significantly mediated the QFS–extremism relationship, accounting for approximately 15% of the total effect, neither NFCU nor NFCP showed significant mediation. Even more strikingly, RMA—most strongly predicted by QFS—failed to predict extremism, whereas locomotion—more weakly predicted by QFS—was a strong predictor.

This selective mediation pattern challenges existing theoretical models. Prior research emphasizing goal systems theory (Kruglanski et al., 2013; Webber and Kruglanski, 2018) has highlighted extremists' “single-minded” goal pursuit but has not explicitly predicted that action orientation would dominate evaluative orientation. Our results suggest that the drive to act and move toward goals, rather than the tendency to evaluate alternatives, bridges significance motivations and extremist personality.

Why would assessment, characterized by careful comparison and critical evaluation, fail to predict extremism despite being strongly activated by QFS? One possibility is that assessment inhibits extremism by fostering consideration of alternatives and potential costs. Research by (Higgins et al. 2003) and (Roca et al. 2025) demonstrates that assessment orientation involves weighing options and anticipating consequences, processes that may lead individuals to reject extreme ideologies upon closer examination.

This pattern suggests a two-stage process not previously articulated in the extremism literature. Initially, QFS activates both regulatory systems: assessment to identify possible significance-restoring goals, and locomotion to pursue them (consistent with Hogg and Abrams, 1999). However, once an extremist ideology or group is perceived as offering significance restoration, locomotion dominates, driving commitment while assessment is suppressed. This would explain why QFS predicts both orientations, but only locomotion predicts extremism.

This interpretation is indirectly supported by (Zmigrod et al. 2019), who found that extremist personality display reduced cognitive flexibility once committed to an ideology, indicating that evaluative processes may diminish as radicalization progresses. Longitudinal research could test this temporal hypothesis by examining whether assessment orientation decreases as commitment to extremist positions increases, while locomotion remains stable or intensifies.

The failure of NFC to mediate the QFS–extremism relationship contradicts prior theoretical and empirical work. (Kruglanski et al. 2014, 2023) have argued that NFC promotes extremism by reinforcing intolerance of uncertainty and preference for clear outcomes. Empirical studies have found positive correlations between NFC and extremism (Milla et al., 2022; Obaidi et al., 2023; Roets and Van Hiel, 2011). Yet, our analyses showed that neither NFCU nor NFCP significantly predicted extremism, despite QFS strongly predicting both. This result challenges NFC's assumed mediating role rather than contradicting previous correlational findings.

One interpretation is that NFC functions as a moderator rather than a mediator. Individuals high in NFC might be more vulnerable to extremist recruitment when experiencing significance loss, not because NFC directly causes extremism, but because it amplifies the motivational impact of QFS. In this sense, NFC acts as a vulnerability factor: the pathway from QFS to extremism through locomotion may be stronger among those less tolerant of ambiguity and more drawn to definitive ideological answers. Future experimental research manipulating both QFS (through significance threat paradigms) and NFC (through uncertainty induction) could test this interaction empirically.

Alternatively, measurement specificity may explain the null finding. The NFC scales used in this and most prior research assess general cognitive tendencies, while intolerance of ambiguity may be domain-specific. As (Kossowska et al. 2018) note, individuals may tolerate uncertainty in daily life but demand certainty in political or moral domains. Extremism may thus depend more on political or ideological closure than on general cognitive styles. This distinction could explain why general NFC, though predicted by QFS, did not predict extremism. Developing domain-specific measures of political intolerance of ambiguity would clarify this issue.

Finally, NFC might be more relevant at later stages of radicalization. The present cross-sectional design captures only a static snapshot, but radicalization unfolds dynamically. Cognitive closure may be crucial for maintaining long-term commitment to extremist beliefs (Webber and Kruglanski, 2018), while early attitude formation may depend more on motivational and action-oriented processes such as locomotion. Longitudinal designs could clarify whether NFC predicts sustained commitment, whereas locomotion drives initial adoption.

The sociodemographic findings also enrich the understanding of vulnerability to extremism. The significant direct effect of gender, with men showing higher extremist personality, replicates prior evidence identifying gendered psychosocial risk patterns associated with violent extremism (Rottweiler et al., 2024). Yet, gender did not predict any mediators, suggesting that masculine-specific pathways operate independently of the general mechanisms tested here. This points toward gender-differentiated processes: men may pursue extremism to restore specifically masculine forms of significance—dominance, protector/provider status, or warrior identity—distinct from the general motivations measured by QFS (Barnes et al., 2012).

The observed gender effect highlights the need to test masculine significance-restoration pathways, while cross-cultural replication would determine whether the locomotion mechanism generalizes beyond Argentina or varies across cultural contexts. Finally, sequential mediation models incorporating identity fusion, moral conviction, or perceived injustice could further clarify how motivational and cognitive systems jointly sustain extremism.

Age and education showed protective effects, but through different mechanisms. Older participants displayed lower extremism risk through reduced locomotion and assessment orientations, alongside increased NFCU. This pattern aligns with socioemotional selectivity theory (Carstensen et al., 2003), which posits that older adults prioritize emotionally meaningful goals over novelty-seeking or ideological experimentation. The increase in understanding-oriented closure may reflect wisdom-related processes (Staudinger and Glück, 2011) that allow uncertainty management without resorting to extremist simplifications. Education's protective effect operated through reduced NFCU and NFCP, but increased RMA. This suggests that education promotes tolerance of complexity and evaluative thinking (Roets and Van Hiel, 2011), reducing cognitive rigidity while enhancing critical assessment. These findings align with evidence that education mitigates extremism by promoting cognitive sophistication and evaluative reflection (Mohammadi, 2021).

Because the data are cross-sectional, causality cannot be inferred. Longitudinal and experimental designs should test whether QFS precedes locomotion and extremism, and whether manipulating QFS increases action-oriented responses and extremist personality. Future research should also examine moderators such as NFC, perceived threat, and intergroup conflict, as well as extend this model to behavioral intentions and identity processes.

Conclusion

This study highlights the role of action-oriented regulatory tendencies—specifically locomotion—in translating Quest for Significance into extremist personality, emphasizing the importance of motivational mechanisms over purely cognitive factors. By clarifying how individuals channel significance-seeking into concrete behaviors, these findings contribute to understanding radicalization pathways and suggest potential targets for intervention. Specifically, strategies aiming to redirect goal-oriented drives toward prosocial forms of significance restoration may be more effective than approaches focusing solely on cognitive rigidity or belief correction. This positions the present study within a broader framework of motivational–behavioral approaches to preventing and mitigating extremist engagement.

These findings oppose purely cognitive explanations centered on rigidity and ambiguity intolerance (Kruglanski et al., 2014) and instead support a motivational–behavioral model in which extremism arises from misdirected goal pursuit under significance threat. The lack of mediation by assessment and NFC—despite strong prediction by QFS—suggests these variables may act as moderators, stage-specific influences, or later consequences rather than initial mediators.

Understanding which psychological processes translate significance motivations into extremist orientations is critical, as they represent potential intervention points in radicalization pathways. Given that locomotion—not cognitive rigidity—appears to be the principal mechanism through which QFS fuels extremist attitudes, counter-extremism strategies should not only challenge beliefs but redirect action-oriented drives toward prosocial forms of significance restoration. This motivational reframing helps explain the limited impact of cognitive or education-based programs alone and underscores the importance of targeting goal redirection and value reconstruction. Future longitudinal and experimental studies, including gender and cultural moderators, are essential to map how significance quests evolve into extremism and how such trajectories can be effectively disrupted.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frsps.2026.1715876/full#supplementary-material

Supplementary material Supplementary material at the source

Footnotes

Edited by: Richard P. Eibach, University of Waterloo, Canada

Reviewed by: Marco Rizzo, University of eCampus, Italy

Kais Al Hadrawi, Al-Furat Al-Awsat Technical University, Iraq

Statements

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This research was supported by funding from the Facultad de Educación y Ciencias Sociales, Universidad Andrés Bello, Santiago, Chile.

Data availability

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Ethics approval

The studies involving humans were approved by Comité de Etica, Facultad de Psicología, Universidad de Buenos Aires. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

LJ: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. MR: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Validation, Writing – original draft, Writing – review & editing. ND: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing. HS: Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing – review & editing. SL: Conceptualization, Project administration, Supervision, Validation, Writing – review & editing. PL: Conceptualization, Formal analysis, Project administration, Supervision, Validation, Writing – review & editing.

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Citation

Jaume, L. C., et al. (2026). Understanding extremist personality: the mediating influence of Regulatory Modes and the need for cognitive closure in the Quest for Significance. Frontiers in Social Psychology, Volume 4. https://doi.org/
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4 - 2026

Copyright

Copyright © 2026 Jaume, Roca, Duhalde, Simkin, Liebana and Labrador.

License: https://creativecommons.org/licenses/by/4.0/

*Correspondence: Luis Carlos Jaume

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