Date of Award

Summer 8-12-2014

Degree Type


Degree Name

Doctor of Philosophy (PhD)



First Advisor

Robin D. Morris, PhD

Second Advisor

Suzanne Penna, PhD, ABPP-Cn

Third Advisor

Erin Tone, PhD

Fourth Advisor

Lindsey Cohen, PhD

Fifth Advisor

David Washburn, PhD


The Saint Louis University Mental Status (SLUMS) Examination is a relatively new brief cognitive screening measure developed for use with veterans. To date, there has been a paucity of research on its psychometric properties. Using a sample of 148 male veterans referred to a VA Mild Cognitive Impairment (MCI) Clinic for evaluation, the SLUMS’ ability to discriminate between MCI versus other diagnoses or no diagnosis was compared to results from a more comprehensive neuropsychological battery. Approximately 51% of the sample was diagnosed with MCI, 16% with Major Depressive Disorder (MDD), 17% did not meet criteria for a diagnosis, and 16% were given some other DSM-IV-TR diagnosis. The SLUMS demonstrated poor internal consistency (Cronbach’s alpha = .57), but scores were significantly correlated with scores on every neuropsychological measure, except for Trails B. Diagnostic discriminability was comparable to that of the more time intensive neuropsychological battery for discriminating between MCI and no diagnosis, and MCI and MDD. In the current sample, a cutoff score of 25 was optimal for discriminating between MCI and no diagnosis, whereas a slightly lower cutoff score of 24 is recommended for discriminating between MCI and those with MDD. Diagnostic indicators were poor for the SLUMS and the battery when discriminating between MCI and a heterogeneous group of other disorders. Possible reasons for low reliability in such a screening measure in the context of convergent validity are discussed. It is concluded that the SLUMS may be a viable brief cognitive screening measure in such veteran populations, particularly when discriminating between MCI and MDD; however, additional studies should be completed to evaluate other forms of consistency, such as test-retest reliability.