Establishing severity and impairment associated with anxiety is important in many settings. We developed a brief (five-item) continuous measure, the Overall Anxiety Severity and Impairment Scale (OASIS), which can be used across anxiety disorders, with multiple anxiety disorders, and with subthreshold anxiety symptoms. Seven hundred eleven college students completed the OASIS and additional self-report assessments of anxiety-related concerns and symptoms. A subset of students completed several measures again 1 month later. Results of a split-sample analysis suggested a single-factor structure, with all five items having salient loadings. The OASIS demonstrated excellent 1-month test-retest reliability, and convergent and divergent validity. The OASIS merits consideration as a brief measure of anxiety-related severity and impairment that can be used across anxiety disorders.

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Posttraumatic stress disorder (PTSD) has been associated with neuropsychological impairments across multiple domains, but consensus regarding the cognitive profile of PTSD has not been reached. In this study of women with PTSD related to intimate partner violence (n = 55) and healthy, demographically similar comparison participants (NCs; n = 20), we attempted to control for many potential confounds in PTSD samples. All participants were assessed with a comprehensive neuropsychological battery emphasizing executive functioning, including inhibition, switching, and abstraction. NCs outperformed PTSD participants on most neuropsychological measures, but the differences were significant only on speeded tasks (with and without executive functioning components). The PTSD group's mean performance was within the average range on all neuropsychological tests. Within the PTSD group, more severe PTSD symptoms were associated with slower processing speed, and more severe dissociative symptoms were associated with poorer reasoning performance. These results suggest that women with PTSD related to intimate partner violence demonstrate slower than normal processing speed, which is associated with the severity of psychiatric symptoms. We speculate that the cognitive slowing seen in PTSD may be attributable to reduced attention due to a need to allocate resources to cope with psychological distress or unpleasant internal experiences.

We developed an algorithm for identifying U.S. veterans with a history of posttraumatic stress disorder (PTSD), using the Department of Veterans Affairs (VA) electronic medical record (EMR) system. This work was motivated by the need to create a valid EMR-based phenotype to identify thousands of cases and controls for a genome-wide association study of PTSD in veterans. We used manual chart review (n = 500) as the gold standard. For both the algorithm and chart review, three classifications were possible: likely PTSD, possible PTSD, and likely not PTSD. We used Lasso regression with cross-validation to select statistically significant predictors of PTSD from the EMR and then generate a predicted probability score of being a PTSD case for every participant in the study population (range: 0-1.00). Comparing the performance of our probabilistic approach (Lasso algorithm) to a rule-based approach (International Classification of Diseases [ICD] algorithm), the Lasso algorithm showed modestly higher overall percent agreement with chart review than the ICD algorithm (80% vs. 75%), higher sensitivity (0.95 vs. 0.84), and higher accuracy (AUC = 0.95 vs. 0.90). We applied a 0.7 probability cut-point to the Lasso results to determine final PTSD case-control status for the VA population. The final algorithm had a 0.99 sensitivity, 0.99 specificity, 0.95 positive predictive value, and 1.00 negative predictive value for PTSD classification (grouping possible PTSD and likely not PTSD) as determined by chart review. This algorithm may be useful for other research and quality improvement endeavors within the VA.We would like to thank Dr. Joan Kaufman for conducting medical chart reviews during the first wave of reviews and for providing constructive feedback on the chart review protocol for CSP #575B. We would also like to thank Rebecca Song for performing a quality control check on all programs used for participant selection and analysis.Widespread implementation of electronic medical record (EMR) systems provides opportunities for transforming population-based research by enabling efficient, cost-effective collection of data on a large scale and thus helps to address a

Despite the ubiquity of sleep complaints among individuals with anxiety disorders, few prior studies have examined whether sleep quality improves during anxiety treatment. The current study examined pre- to post-treatment sleep quality improvement during cognitive behavioral therapy (CBT) for panic disorder (PD; n = 26) or generalized anxiety disorder (GAD; n = 24). Among sleep quality indices, only global sleep quality and sleep latency improved significantly (but modestly) during CBT. Sleep quality improvement was greater for treatment responders, but did not vary by diagnosis. Additionally, poor baseline sleep quality was independently associated with worse anxiety treatment outcome, as measured by higher intolerance of uncertainty. Additional intervention targeting sleep prior to or during CBT for anxiety may be beneficial for poor sleepers.

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