The OCI-CV-R: A Revision of the Obsessive-Compulsive Inventory - Child Version.

The Obsessive-Compulsive Inventory-Children's Version (OCI-CV) was developed to assess obsessive-compulsive symptoms in youth. Recent changes in the Diagnostic and Statistical Manual (DSM-5) exclude hoarding from inclusion in the diagnosis of obsessive-compulsive disorder (OCD). Accordingly, the present study examined the reliability, validity, factorial structure, and diagnostic sensitivity of a revised version of the scale - the OCI-CV-R- that excludes items assessing hoarding. Participant were 1047 youth, including 489 meeting DSM criteria for primary OCD, 298 clinical controls, and 260 nonclinical controls, who completed the OCI-CV and measures of obsessive-compulsive symptom severity, depression, and anxiety at various treatment and research centers. Findings support a five-factor structure (doubting/checking, obsessing, washing, ordering, and neutralizing), with a higher order factor. Factorial invariance was found for older (12-17 years) and younger (7-11 years) children. Internal consistency of the OCI-CV-R was acceptable, and discriminant and convergent validity were adequate and akin to that of its progenitor. Diagnostic sensitivity and specificity were found for a total score of 8 and higher. It is recommended that the OCI-CV-R replace the former version, and that this measure serve as part of a comprehensive clinical assessment of youth with OCD. Recommendations for further research with ethnically and racially diverse samples, as well as the need to establish benchmark scores are discussed. Copyright © 2022 Elsevier Ltd. All rights reserved.

Citation

Amitai Abramovitch, Jonathan S Abramowitz, Dean McKay, Heining Cham, Kennedy S Anderson, Lara Farrell, Daniel A Geller, Gregory L Hanna, Sharna Mathieu, Joseph F McGuire, David R Rosenberg, S Evelyn Stewart, Eric A Storch, Sabine Wilhelm. The OCI-CV-R: A Revision of the Obsessive-Compulsive Inventory - Child Version. Journal of anxiety disorders. 2022 Mar;86:102532

Mesh Tags

PMID: 35091252

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