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Using the yes/no recognition response pattern to detect memory malingering.

ABSTRACT: BACKGROUND: Detection of feigned neurocognitive deficits is a challenge for neuropsychological assessment. We conducted two studies to examine whether memory malingering is characterized by an elevated proportion of false negatives during yes/no recognition testing and whether this could be a useful measure for assessment. METHODS: Study 1 examined 51 participants claiming compensation due to mental disorders, 51 patients with affective disorders not claiming compensation and 13 patients with established dementia. Claimants were sub-divided into suspected malingerers (n?=?11) and non-malingerers (n?=?40) according to the Test of Memory Malingering (TOMM). In study 2, non-clinical participants were instructed to either malinger memory deficits due to depression (n?=?20), or to perform normally (n?=?20). RESULTS: In study 1, suspected malingerers had more false negative responses on the recognition test than all other groups and false negative responding was correlated with Minnesota-Multiphasic Personality Inventory (MMPI) measures of deception. In study 2, using a cut-off score derived from the clinical study, the number of false negative responses on the yes/no recognition test predicted group membership with comparable accuracy as the TOMM, combining both measures yielded the best classification. Upon interview, participants suspected the TOMM more often as a malingering test than the yes/no recognition test. CONCLUSION: Results indicate that many malingers adopt a strategy of exaggerated false negative responding on a yes/no recognition memory test. This differentiates them from both dementia and affective disorder, recommending false negative responses as an efficient and inconspicuous screening measure of memory malingering.

SUBMITTER: Schindler S

PROVIDER: S-EPMC4270012 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Using the yes/no recognition response pattern to detect memory malingering.

Schindler Sebastian S Kissler Johanna J Kühl Klaus-Peter KP Hellweg Rainer R Bengner Thomas T

BMC psychology 20130625 1

<h4>Background</h4>Detection of feigned neurocognitive deficits is a challenge for neuropsychological assessment. We conducted two studies to examine whether memory malingering is characterized by an elevated proportion of false negatives during yes/no recognition testing and whether this could be a useful measure for assessment.<h4>Methods</h4>Study 1 examined 51 participants claiming compensation due to mental disorders, 51 patients with affective disorders not claiming compensation and 13 pat ...[more]

PMID: 25566364

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Project description:There is currently no "gold standard" marker of cognitive performance impairment resulting from sleep loss. We utilized pattern recognition algorithms to determine which features of data collected under controlled laboratory conditions could most reliably identify cognitive performance impairment in response to sleep loss using data from only one testing session, such as would occur in the "real world" or field conditions. A training set for testing the pattern recognition algorithms was developed using objective Psychomotor Vigilance Task (PVT) and subjective Karolinska Sleepiness Scale (KSS) data collected from laboratory studies during which subjects were sleep deprived for 26-52h. The algorithm was then tested in data from both laboratory and field experiments. The pattern recognition algorithm was able to identify performance impairment with a single testing session in individuals studied under laboratory conditions using PVT, KSS, length of time awake and time of day information with sensitivity and specificity as high as 82%. When this algorithm was tested on data collected under real-world conditions from individuals whose data were not in the training set, accuracy of predictions for individuals categorized with low performance impairment were as high as 98%. Predictions for medium and severe performance impairment were less accurate. We conclude that pattern recognition algorithms may be a promising method for identifying performance impairment in individuals using only current information about the individual's behavior. Single testing features (e.g., number of PVT lapses) with high correlation with performance impairment in the laboratory setting may not be the best indicators of performance impairment under real-world conditions. Pattern recognition algorithms should be further tested for their ability to be used in conjunction with other assessments of sleepiness in real-world conditions to quantify performance impairment in response to sleep loss.

Dataset Information

Using the yes/no recognition response pattern to detect memory malingering.

Publications

Using the yes/no recognition response pattern to detect memory malingering.

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