No significant incremental predictive utility of dark triad traits for leadership performance: Evidence from a high-fidelity simulation

Despite the growing prominence of the Dark Triad framework in leadership research, empirical findings remain mixed regarding the predictive value of narcissism, Machiavellianism, and psychopathy. The present study tested whether Dark Triad traits predict leadership performance beyond the Big Five personality traits and general mental ability using a high-fidelity, behavioral-based leadership simulation. In a multi-phase design (final N = 100; 68 women, 31 men, M age = 27.11, SD = 6.38), participants completed individual difference assessment before engaging in a leadership simulation that required approximately 150 decisions across complex, interpersonally rich scenarios and lasted, on average, six hours ( SD = 2.5 h). Results indicated that, in this sample and setting, none of the Dark Triad traits were significantly associated with leadership performance, either at the correlational level or in hierarchical regression analysis testing incremental validity. In contrast, openness, agreeableness (negatively), and GMA emerged as significant predictors. These findings suggest limited incremental predictive utility of Dark Triad traits for leadership performance in the present context when performance is assessed using objective, behavior-based criteria. • DT did not predict leadership performance in a high-fidelity simulation • Leadership was assessed using a behavior-based simulation • DT showed no incremental validity beyond Big Five and general mental ability • Openness, agreeableness, and general mental ability predicted performance

Authors

Institutions

Publication Details

Journal
Personality and Individual Differences
Published
2026-04-25
DOI
https://doi.org/10.1016/j.paid.2026.113850
Primary Topic
Personality Traits and Psychology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

No significant incremental predictive utility of dark triad traits for leadership performance: Evidence from a high-fidelity simulation

Zsolt Péter Szabó
Personality and Individual Differences
Personality Traits and Psychology
article

No significant incremental predictive utility of dark triad traits for leadership performance: Evidence from a high-fidelity simulation

Zsolt Péter Szabó
article en

Abstract

Despite the growing prominence of the Dark Triad framework in leadership research, empirical findings remain mixed regarding the predictive value of narcissism, Machiavellianism, and psychopathy. The present study tested whether Dark Triad traits predict leadership performance beyond the Big Five personality traits and general mental ability using a high-fidelity, behavioral-based leadership simulation. In a multi-phase design (final N = 100; 68 women, 31 men, M age = 27.11, SD = 6.38), participants completed individual difference assessment before engaging in a leadership simulation that required approximately 150 decisions across complex, interpersonally rich scenarios and lasted, on average, six hours ( SD = 2.5 h). Results indicated that, in this sample and setting, none of the Dark Triad traits were significantly associated with leadership performance, either at the correlational level or in hierarchical regression analysis testing incremental validity. In contrast, openness, agreeableness (negatively), and GMA emerged as significant predictors. These findings suggest limited incremental predictive utility of Dark Triad traits for leadership performance in the present context when performance is assessed using objective, behavior-based criteria. • DT did not predict leadership performance in a high-fidelity simulation • Leadership was assessed using a behavior-based simulation • DT showed no incremental validity beyond Big Five and general mental ability • Openness, agreeableness, and general mental ability predicted performance

Personality and Individual DifferencesVol. 258
Eötvös Loránd University (HU), Corvinus University of Budapest (HU)
Openalex Percentile: Top 4%
Personality Traits and Psychology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.