Response patterns for the identification of fakers: Detecting drifting dissimulators

- Response patterns can detect fakers on self-report personality scales.
- Fakers become more positive or negative in response patterns over items.
- Response patterns can improve upon a standard lie scale for the detection of fakers.
- Results generalize across instructions, modes of test administration and answering, and response time constraints.

In this research, we provide a simple, novel operationalization of a method for identifying fakers on a self-report measure of personality. This operationalization is applied to six distinct samples of experimentally instructed fakers (total N = 1360) who completed the NEO-FFI under varying instructions, modes of test administration and answering, and response time constraints. Based on quantifying individual item response patterns that indicate changes in response positivity over items, the new index of faking demonstrated medium to large effect sizes for identifying faking. Further, this index generally demonstrated added value relative to a standard validity scale for accounting for variability in faking.