A-227 A Story Told in Four Parts: Embedded Validity Indicators’ Effectiveness in Predicting Dot Counting Test Validity Classification

Abstract Objective: Combining multiple embedded performance validity tests (PVTs) can produce similar classification accuracy to freestanding PVTs. However, there is a lack of research on the incremental predictive power various combinations Thus, we compared eight PVTs assess those that best predict Dot Counting Test (DCT). Method: Sample included 225 patients (mean age=45.96; mean education=13.96; 56% female, 44% male; 35% White, 40% Black, 17% Hispanic, 5% Asian, 2% Other) undergoing neuropsychological evaluation PVTs, including: Brief Visuospatial Memory Test-Revised Recognition Discrimination (BVMT-R RD), Stroop Color and Word Reading T-Score (Stroop-T), Trail Making Part A (TMT-A), Rey Auditory Verbal Learning (RAVLT) Forced Choice, RAVLT Effort Score, Digit Span Age Corrected Scaled Reliable Span, Letter Fluency T-Score. Patients were classified into valid/invalid groups based four independent criterion Results: forward stepwise logistic regression was performed DCT pass/fail using aforementioned as predictors. The model achieved in three steps (p<.05); Step 1: BVMT-R RD (Classification Accuracy=87.6%; Nagelkerke R2 =.30), 2: + Stroop-T Accuracy=89.6%; =.44); 3: TMT-A Accuracy=90.1%; =.49). Conclusion: reliably predicted group. this combination may be reliable predictors when time prohibits delivery such DCT.