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      Detection of Feigned ADHD Using the MOXO-d-CPT

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          Abstract

          Objective: The objective of this study was to assess the MOXO-d-CPT utility in detecting feigned ADHD and establish cutoffs with adequate specificity and sensitivity. Method: The study had two phases. First, using a prospective design, healthy adults who simulated ADHD were compared with healthy controls and ADHD patients who performed the tasks to the best of their ability ( n = 47 per group). Participants performed the MOXO-d-CPT and an established performance validity test (PVT). Second, the MOXO-d-CPT classification accuracy, employed in Phase 1, was retrospectively compared with archival data of 47 ADHD patients and age-matched healthy controls. Results: Simulators performed significantly worse on all MOXO-d-CPT indices than healthy controls and ADHD patients. Three MOXO-d-CPT indices (attention, hyperactivity, impulsivity) and a scale combining these indices showed adequate discriminative capacity. Conclusion: The MOXO-d-CPT showed promise for the detection of feigned ADHD and, pending replication, can be employed for this aim in clinical practice and ADHD research.

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          Most cited references58

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              A Caution Regarding Rules of Thumb for Variance Inflation Factors

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                Author and article information

                Contributors
                Journal
                Journal of Attention Disorders
                J Atten Disord
                SAGE Publications
                1087-0547
                1557-1246
                May 2021
                July 31 2019
                May 2021
                : 25
                : 7
                : 1032-1047
                Affiliations
                [1 ]Ariel University, Ariel, Israel
                [2 ]Bar-Ilan University, Ramat Gan, Israel
                [3 ]University of California, Los Angeles, USA
                Article
                10.1177/1087054719864656
                4a0c5889-9b52-4bac-a48e-efc18a55f6bd
                © 2021

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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