Publications by authors named "Amy Sewart"

Objectives: Social anxiety disorder (SAD) and alcohol use disorder (AUD) are highly comorbid and this comorbidity is associated with poorer clinical outcomes. Integrating exposure-based treatment for SAD into the context of typical AUD treatment programs should improve engagement and treatment outcomes for this population.

Methods: After initial development of a fully integrated, intensive outpatient program (IOP) for individuals with comorbid SAD and AUD, patients with SAD and AUD were recruited from a community-based SUD specialty clinic (N = 56) and randomized to either (a) usual care (UC), consisting of the evidence-based Matrix Model of Addiction IOP; or (b) the Fully Integrated Treatment (FIT) for comorbid SAD and AUD IOP.

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Our recent trial demonstrated individuals suffering from social anxiety with performance-related concerns who received virtual reality exposure augmented with scopolamine, a cholinergic antagonist, experienced significantly less post-treatment context renewal (CX) than placebo (Craske et al., 2019). The purpose of the present investigation was to determine who specifically benefits from scopolamine by examining hippocampal (HPC) functioning as a moderator of treatment response (Placebo n = 15, SCOP 0.

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Rumination is theorized to be a cognitive avoidance process that is implicated in several manifestations of psychopathology. Few interventions directly target rumination as a core process maintaining emotional disorder symptoms. This pilot study compared the feasibility and preliminary efficacy of self-directed behavioral approaches for reducing rumination.

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The present study examines the longitudinal association between cortisol (dys)regulation - mean cortisol awakening response (CAR) and area under the curve with respect to ground (AUCg) for total daily cortisol - and autobiographical memory. 135 participants (mean age at baseline = 16.1; Females = 78.

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The high rate of comorbidity between alcohol use and emotional disorders is well demonstrated, but the mechanisms underlying their relationship remain largely unidentified. One possibility is maladaptive responding to negative affect, such as worry and rumination. The present study sought to examine worry and rumination as putative mediators explaining the link between emotional disorders and alcohol use disorders.

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Traditional cognitive-behavioral therapy (CBT) for anxiety disorders has been designed to target reductions in negative affect (NA) associated with defense-related processes. However, a subset of anxiety disorders, including social anxiety disorder (SAD), are also characterized by low positive affect (PA) resulting from separate deficits in appetitive-related processes. In contrast to CBT, "third-wave" approaches, such as acceptance and commitment therapy (ACT), align more consistently with motivational processes and, as a result, PA.

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Research has demonstrated that stressors play a critical role in the development of generalized anxiety disorder (GAD), social anxiety disorder (SAD), and major depressive disorder (MDD). Separately, deficits in positive affect (PA) have been identified in GAD, SAD, and MDD. While previous research has linked the buffering effects of PA in chronic illness, such effects have yet to be investigated for chronic stressors and emotional disorder-related symptom severity.

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Machine learning (ML) has been introduced into the medical field as a means to provide diagnostic tools capable of enhancing accuracy and precision while minimizing laborious tasks that require human intervention. There is mounting evidence that the technology fueled by ML has the potential to detect and substantially improve treatment of complex mental disorders such as depression. We developed a framework capable of detecting depression with minimal human intervention: artificial intelligence mental evaluation (AiME).

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Emotional expressions are an essential element of human interactions. Recent work has increasingly recognized that emotional vocalizations can color and shape interactions between individuals. Here we present data on the psychometric properties of a recently developed database of authentic nonlinguistic emotional vocalizations from human adults and infants (the Oxford Vocal 'OxVoc' Sounds Database; Parsons, Young, Craske, Stein, & Kringelbach, 2014).

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Childhood and adolescent adversity have been shown to predict later mental and physical health outcomes. Understanding which aspects and developmental timings of adversity are important, and the mechanisms by which they have their impact may help guide intervention approaches. A large subset of adolescents (N = 457; Female 68.

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Background: Pretreatment biases in attending toward threat have been shown to predict greater symptom reduction following cognitive behavioral therapy (CBT) for anxiety. Findings to date do not extend to clinical severity of diagnoses and they assess treatment response immediately posttreatment and not at follow-up. Research in this area has also not examined components of vigilance (e.

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