Objective: The high potential for secondary gain among college students presenting for ADHD evaluations highlights the need for psychometrically sound embedded validity indicators. The purpose of this study was to develop an embedded algorithm within the PAI to identify likely feigned ADHD. Method: A group instructed to simulate ADHD (n = 138) was compared to a valid ADHD diagnosis group (n = 142). Normed PAI data were used for all analyses and examined to determine scales with group differences of at least 10 T points. From this, scales that conceptually would be related to simulated ADHD were examined for tolerance to meet the assumptions of logistic regression. Scales that met all criteria were then examined using logistic regression to predict the simulators from the genuine ADHD group. Results: The logistic regression model was significant for all predictors and yielded the following equation: −3.270 −.041 * PIM (Positive Impression Management) −.026...

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