Neurobehavioral Mechanisms of Resilience Against Emotional Distress: An Integrative Brain-Personality-Symptom Approach Using Structural Equation Modeling.
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2018-01
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Abstract
Clarifying individual differences that predict resilience or vulnerability to emotional distress is crucial for identifying etiological factors contributing to affective disturbances, and to promoting emotional well-being. Despite recent progress identifying specific brain regions and personality traits, it remains unclear whether there are common factors underlying the structural aspects of the brain and the personality traits that, in turn, protect against symptoms of emotional distress. In the present study, an integrative structural equation model was developed to examine the associations among (1) a latent construct of Control, representing the volumes of a system of prefrontal cortical (PFC) regions including middle, inferior, and orbital frontal cortices; (2) a latent construct of Resilience personality traits including cognitive reappraisal, positive affectivity, and optimism; and (3) Anxiety and Depression symptoms, in a sample of 85 healthy young adults. Results showed that the latent construct of PFC volumes positively predicted the latent construct of Resilience, which in turn negatively predicted Anxiety. Mediation analysis confirmed that greater latent PFC volume is indirectly associated with lower Anxiety symptoms through greater latent trait Resilience. The model did not show a significant mediation for Depression. These results support the idea that there are common volumetric and personality factors that help protect against symptoms of emotional distress. These findings provide strong evidence that such brain-personality-symptom approaches can provide novel insights with valuable implications for understanding the interaction of these factors in healthy and clinically diagnosed individuals.
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Moore, Matthew, Steven Culpepper, K Luan Phan, Timothy J Strauman, Florin Dolcos and Sanda Dolcos (2018). Neurobehavioral Mechanisms of Resilience Against Emotional Distress: An Integrative Brain-Personality-Symptom Approach Using Structural Equation Modeling. Personality neuroscience, 1. p. e8. 10.1017/pen.2018.11 Retrieved from https://hdl.handle.net/10161/21880.
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Timothy J. Strauman
Professor Strauman’s work is grounded in the premise that mental health and well-being are fundamentally shaped by self-regulation—how individuals pursue goals, respond to challenges, and adapt over time. His research integrates clinical psychology, affective neuroscience, and behavioral science to characterize the psychological and neurobiological systems that support self-regulation, and to understand how disruptions in these systems contribute to vulnerability to depression and related conditions.
Across a program of experimental, clinical, and neuroimaging research, his work has examined self-regulation as a multi-level system, including its cognitive and motivational mechanisms, its development through socialization, and its links to affective and immunological processes. This work has also informed the development and evaluation of novel interventions targeting self-regulatory dysfunction.
More recently, his work has focused on translating this science of self-regulation into scalable approaches to intervention and prevention. This includes the development of new models of treatment that target regulatory processes across disorders, as well as efforts to extend effective self-regulation skills beyond traditional clinical settings and into everyday contexts. This translational focus reflects a broader aim of building integrated, system-level approaches to mental health that can improve outcomes at population scale.
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.
