Limited predictive accuracy of the Booklet Category Test in a criminal forensic sample
| Autor: | Robert L. Denney, William G. Myers, Rachel L Fazio, Leah Hanson Misialek |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Adult
Male Malingering Sample (statistics) Neuropsychological Tests Logistic regression Sensitivity and Specificity Discriminative model Predictive Value of Tests Statistics Developmental and Educational Psychology medicine Humans Neuropsychological assessment medicine.diagnostic_test Prisoners Neuropsychology Reproducibility of Results medicine.disease Forensic science Neuropsychology and Physiological Psychology Logistic Models Predictive value of tests Psychology Clinical psychology |
| Zdroj: | Applied neuropsychology. Adult. 20(2) |
| ISSN: | 2327-9109 |
| Popis: | A known-groups design was used to evaluate the clinical decision rules of the validity indicators of the Booklet Category Test for the detection of malingered neurocognitive dysfunction (MND) in an incarcerated male sample. Participants were 128 inmates who were classified into MND and presumed valid groups using the Slick, Sherman, and Iverson ( 1999 ) criteria. While errors on Subtests I and II had the best classification accuracy at 71.1% with 95.1% specificity and 49.3% sensitivity, the associated area under the curve (AUC) indicated only "acceptable" discrimination due to poor sensitivity. Logistic regression confirmed that errors on Subtests I and II were the only statistically significant validity indicator. The remaining validity indicators performed poorly with AUCs at < .70, indicating no discriminative power. The effectiveness of the clinical decision rules of the validity indicators in predicting the presence of MND evidenced limited support. A positive finding on Subtest I and II errors was clinically significant in this sample, but negative results revealed no utility. Validity indices composed from different items may yield more effective results among male prisoners referred for neuropsychological evaluation. |
| Databáze: | OpenAIRE |
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