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Improving the assessment of dark personalities for the prediction of stress and cognitive performance

Student thesis: Doctoral ThesisThesis with Publications

Abstract

The Dark Tetrad—comprising narcissism, Machiavellianism, psychopathy, and sadism—is traditionally viewed as socially undesirable. However, incomplete and overlapping measurements of these traits may have obscured their potentially adaptive aspects. This thesis aims to improve the assessment of dark personalities for predicting outcomes like stress and cognitive performance. Through four studies this work identifies dark facets, their relations, and explores how they can reveal both maladaptive and adaptive connections. Study 1 systematically reviewed 64 instruments assessing Dark Tetrad traits, recommending multidimensional measures with high psychometric quality for more comprehensive evaluations. Study 2 employed network analyses to examine dark traits independently and within collective models. Data from 821 adults indicated antagonistic facets as central to dark trait expressions. The findings suggest that unconstrained flexible analyses go beyond traditional Triad and Tetrad structures, attending the multidimensional nature of dark traits. Study 3 addressed overreliance on self-reports by examining the convergence between self and informant-reports of dark personalities in 262 dyads. Narcissistic antagonism emerged as central in both report types, with some dark facets judged (N = 266) as socially desirable, and some were associated with positive mental health and relationship outcomes. Study 4 tested the antagonistic buffering hypothesis and experimental data from 86 individuals revealed that certain dark facets had stress-buffering associations for cognitive performance under stress. Together, these studies demonstrate that Dark Tetrad traits are multidimensional and context-specific. By operationalizing these traits at the facet level, both maladaptive and adaptive connections emerge, suggesting that these traits are not inherently negative. Future research should continue to adopt this deeper level of abstraction to uncover further insights into the interconnections among dark traits and their diverse associations with outcomes.

Thesis is embargoed until 31 July 2026.
Date of AwardJul 2025
Original languageEnglish
Awarding Institution
  • Queen's University Belfast
SupervisorKonstantinos Papageorgiou (Supervisor), Mihalis Doumas (Supervisor), Tanja Gerlach (Supervisor) & Tayler Truhan (Assistant Supervisor)

Keywords

  • Dark Tetrad
  • personality
  • assessment
  • stress
  • cognitive
  • performance

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