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Validation of the Personality Assessment Inventory (PAI) scale of scales in a mixed clinical sample.

Kaley BoressOwen J GaasedelenAnna CroghanMarcie King JohnsonKristen CaraherMichael R BassoDouglas M Whiteside
Published in: The Clinical neuropsychologist (2021)
Objective: This exploratory study examined the classification accuracy of three derived scales aimed at detecting cognitive response bias in neuropsychological samples. The derived scales are composed of existing scales from the Personality Assessment Inventory (PAI). A mixed clinical sample of consecutive outpatients referred for neuropsychological assessment at a large Midwestern academic medical center was utilized. Participants and Methods: Participants included 332 patients who completed study's embedded and free-standing performance validity tests (PVTs) and the PAI. PASS and FAIL groups were created based on PVT performance to evaluate the classification accuracy of the derived scales. Three new scales, Cognitive Bias Scale of Scales 1-3, (CB-SOS1-3) were derived by combining existing scales by either summing the scales together and dividing by the total number of scales summed, or by logistically deriving a variable from the contributions of several scales. Results: All of the newly derived scales significantly differentiated between PASS and FAIL groups. All of the derived SOS scales demonstrated acceptable classification accuracy (i.e. CB-SOS1 AUC = 0.72; CB-SOS2 AUC = 0.73; CB-SOS3 AUC = 0.75). Conclusions: This exploratory study demonstrates that attending to scale-level PAI data may be a promising area of research in improving prediction of PVT failure.
Keyphrases
  • machine learning
  • deep learning
  • mild cognitive impairment
  • big data
  • tertiary care