Understanding Our Own Biology: The Relevance of Auto-Biological Attributions for Mental Health
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2017-03-01
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As knowledge of the neurobiological basis of psychopathology has advanced, public perceptions have shifted toward conceptualizing mental disorders as disorders of biology. However, little is known about how patients respond to biological information about their own disorders. We refer to such information as auto-biological—describing our own biological systems as a component of our identity. Drawing on research from attribution theory, we explore the potential for auto-biological information to shape how patients view themselves in relation to their disorders. We propose an attributional framework for presenting auto-biological information in a way that encourages agency, rather than destiny. We argue that this framework has the potential to change expectations and improve outcomes in the treatment of psychiatric disorders.
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MacDuffie, KE, and TJ Strauman (2017). Understanding Our Own Biology: The Relevance of Auto-Biological Attributions for Mental Health. Clinical Psychology: Science and Practice, 24(1). pp. 50–68. 10.1111/cpsp.12188 Retrieved from https://hdl.handle.net/10161/31193.
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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.
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