Sally A Moore1, Stacy S Welch2, Jared Michonski3, Jonathan Poquiz4, Travis L Osborne2, Jennifer Sayrs3, Alexia Spanos3. 1. Evidence Based Treatment Centers of Seattle (EBTCS), USA; University of Washington, Department of Psychiatry and Behavioral Sciences, USA. Electronic address: smoore@ebtseattle.com. 2. Evidence Based Treatment Centers of Seattle (EBTCS), USA; University of Washington, Department of Psychiatry and Behavioral Sciences, USA; University of Washington, Department of Psychology, USA. 3. Evidence Based Treatment Centers of Seattle (EBTCS), USA; University of Washington, Department of Psychology, USA. 4. Evidence Based Treatment Centers of Seattle (EBTCS), USA.
Abstract
BACKGROUND: Comorbidity among anxiety-related diagnoses is common, highlighting the need for brief, meaningful measures of anxiety that cut across diagnoses. METHODS: The current study examined the psychometric properties of one such measure, the Overall Anxiety Severity and Impairment Scale (OASIS) (Norman et al., 2006), in a naturalistic sample of individuals seeking treatment at an outpatient anxiety treatment center. We examined the measure׳s structure, convergent validity, and potential effects of respondent gender. Using ROC analysis, we estimated an optimal cut-score for determining presence of an anxiety disorder in this sample. Finally, we examined the responsiveness of the OASIS to clinical change and calculated a reliable change index. RESULTS: We found strong psychometric properties of the OASIS. A unitary factor structure with correlated residuals on the first two items provided the best fit to the data. A cut-score of eight best distinguished the presence of an anxiety-related diagnosis. In measurement invariance analyses, we found evidence that men and women respond similarly to the measure. In addition, we found that change in the OASIS was correlated with change in other measures, and we estimated that a four-point change in the OASIS can be considered clinically reliable. LIMITATIONS: Sample characteristics may limit generalizability. Diagnoses were established by clinicians using a semi-structured interview that, while based upon DSM-IV diagnostic criteria, has not been psychometrically evaluated. CONCLUSION: The results provide support for the use of the OASIS in specialty treatment for anxiety-related diagnoses and further highlight the strengths of this measure in clinical practice and research settings.
BACKGROUND: Comorbidity among anxiety-related diagnoses is common, highlighting the need for brief, meaningful measures of anxiety that cut across diagnoses. METHODS: The current study examined the psychometric properties of one such measure, the Overall Anxiety Severity and Impairment Scale (OASIS) (Norman et al., 2006), in a naturalistic sample of individuals seeking treatment at an outpatientanxiety treatment center. We examined the measure׳s structure, convergent validity, and potential effects of respondent gender. Using ROC analysis, we estimated an optimal cut-score for determining presence of an anxiety disorder in this sample. Finally, we examined the responsiveness of the OASIS to clinical change and calculated a reliable change index. RESULTS: We found strong psychometric properties of the OASIS. A unitary factor structure with correlated residuals on the first two items provided the best fit to the data. A cut-score of eight best distinguished the presence of an anxiety-related diagnosis. In measurement invariance analyses, we found evidence that men and women respond similarly to the measure. In addition, we found that change in the OASIS was correlated with change in other measures, and we estimated that a four-point change in the OASIS can be considered clinically reliable. LIMITATIONS: Sample characteristics may limit generalizability. Diagnoses were established by clinicians using a semi-structured interview that, while based upon DSM-IV diagnostic criteria, has not been psychometrically evaluated. CONCLUSION: The results provide support for the use of the OASIS in specialty treatment for anxiety-related diagnoses and further highlight the strengths of this measure in clinical practice and research settings.
Authors: Jonathan S Comer; Kristina Conroy; Danielle Cornacchio; Jami M Furr; Sonya B Norman; Murray B Stein Journal: J Affect Disord Date: 2021-12-31 Impact factor: 6.533
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