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        <datestamp>2026-10-01T16:08:26Z</datestamp>
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          <dc:title>More than just aversive: how the dark triad traits cope with stress and the associations with psychopathology</dc:title>
          <dc:creator>Micheala McIlvenna (24304598)</dc:creator>
          <dc:subject>PUREID: 690144014</dc:subject>
          <dc:subject>dark triad</dc:subject>
          <dc:subject>adaptive</dc:subject>
          <dc:subject>depression</dc:subject>
          <dc:subject>mental health</dc:subject>
          <dc:subject>coping</dc:subject>
          <dc:subject>statistics</dc:subject>
          <dc:description>Dark personality traits have traditionally been connected with poorer mental health . However, more recent research suggests that certain dimensions of the dark triad may have adaptive qualities—for example, grandiose narcissism has been linked to lower levels of depression. This pattern is demonstrated in Studies 1 and 2 of this thesis. Studies 2 and 3 build upon Study 1 by incorporating coping strategies and coping flexibility. Study 2 identified Machiavellian agency as a key bridge between narcissistic extraversion and depression, while a similar bridging effect emerged in the maladaptive network where narcissistic antagonism influenced depression through secondary psychopathy. To further investigate these dynamics, we conducted an intensive longitudinal study measuring dark triad traits at the dimensional level alongside mood and coping strategies. Using both network analysis and multi-level modelling (Study 4a and 4b), results suggest that pride plays a crucial role in shaping personality-depression relationships. The direction of the relationship between pride and depression depended on its link with narcissistic neuroticism, a positive connection between neuroticism and pride corresponded with higher depression, whereas a negative connection corresponded with lower depression. This suggests that pride may be adaptive until it interacts with narcissistic neuroticism, at which point its influence becomes detrimental. To deepen our understanding, we applied multi-level models to analyze the same data, allowing for a direct comparison of network analysis with traditional methodologies and highlighting potential advantages of each approach.&lt;br&gt;&lt;br&gt;&lt;i&gt;Thesis is embargoed until 31 July 2027.&lt;/i&gt;</dc:description>
          <dc:date>2026-10-01T16:08:26Z</dc:date>
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          <dc:identifier>10.17034/32826377.v1</dc:identifier>
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          <dc:rights>All Rights Reserved</dc:rights>
          <dc:rights>Open Access after 2027-07-31</dc:rights>
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