Lying in neuropsychology

A Review of Approaches to Detecting Malingering in Forensic Contexts and Promising Cognitive Load-Inducing Lie Detection Techniques

Malingering, the feigning of psychological or physical ailment for gain, imposes high costs on society, especially on the criminal-justice system. In this article, we review some of the costs of malingering in forensic contexts. Then the most common methods of malingering detection are reviewed, including those for feigned psychiatric and cognitive impairments. The shortcomings of each are considered. The article continues with a discussion of commonly used means for detecting deception. Although not traditionally used to uncover malingering, new, innovative methods are emphasized that attempt to induce greater cognitive load on liars than truth tellers, some informed by theoretical accounts of deception. As a type of deception, we argue that such cognitive approaches and theoretical understanding can be adapted to the detection of malingering to supplement existing methods.

Detecting over-reporting of symptoms: the French version of the self-report symptom inventory

OBJECTIVE

Symptom exaggeration and malingering are core issues in forensic and clinical evaluation. Generally, experts use two main types of instruments to assess the credibility of symptoms: performance validity tests that aim to detect underperformance and self-report validity tests that appraise over-reporting of symptoms. However, while many tools can be used to assess underperformance, far fewer instruments are available to evaluate over-reporting of symptoms.

METHODS

In this study, we adapted the Self-Report Symptom Inventory (SRSI) for use with French-speaking participants and tested its psychometric properties on a sample of 575 healthy adults (aged from 18 to 65 years), alongside various smaller subgroups.

RESULTS

Exploratory and confirmatory factor analyses supported a two-factor structure for the scale, with a first factor including items questioning genuine symptoms and a second factor including items questioning bizarre or rare symptoms (i.e., pseudosymptoms). Additional analyses emphasized the SRSI's excellent internal reliability and good convergent validity. Furthermore, our results revealed that both the symptom and pseudosymptom subscales were able to discriminate between participants who were asked to feign cognitive impairments (i.e., malingerers), healthy controls, and patients with genuine cognitive symptoms.

CONCLUSION

Overall, these results suggest that the SRSI may be considered a promising tool to assess the credibility of symptoms in patients evaluated in forensic contexts.

Detecting malingering mental illness in forensics: Known-Group Comparison and Simulation Design with MMPI-2, SIMS and NIM

BACKGROUND

Criminal defendants may often exaggerate psychiatric symptoms either to appear non-accountable for their actions or to mitigate their imprisonment. Several psychometric tests have been proposed to detect malingering. These instruments are often validated by Simulation Design (SD) protocols, where normal participants are explicitly requested to either simulate a mental disorder or respond honestly. However, the real scenarios (clinical or forensic) are often very challenging because of the presence of genuine patients, so that tests accuracy frequently differs from that one obtained in well-controlled experimental settings. Here we assessed the effectiveness in criminal defendants of three well-known malingering-detecting tests (MMPI-2, SIMS and NIM) by using both Known-Group Comparison (KGC) and Simulation Design (SD) protocols.

METHODS

The study involved 151 male inmates. Participants to the KGC protocol were all characterized by a positive psychiatric history. They were considered as genuine patients (KGC_Controls) if they had some psychiatric disorders already before imprisonment and scored above the cutoff of SCL-90-R, a commonly used test for mental illness, and as suspected malingerers (KGC_SM) if they were diagnosed as psychiatric patients only after imprisonment and scored below the SCL-90-R cutoff. Participants to SD protocol had no history of psychiatric disease and scored below the SCL-90-R cutoff. They were randomly assigned to either group: Controls (requested to answer honestly, SD_Controls) and simulated malingerers (requested to feign a psychiatric disease, SD_SM). All participants were then submitted to MMPI-2, NIM and SIMS.

RESULTS

Results showed that while MMPI-2, SIMS and NIM were all effective in discriminating malingerers in the SD, SIMS only significantly discriminated between KGC_Controls and KGC_SM in the Known-Group Comparison. Receiver Operating Characteristic (ROC) curves analysis confirmed the better sensitivity of SIMS with respect to the other tests but raised some issues on SIMS specificity.

DISCUSSION

Results support the sensitivity of SIMS for the detection of malingering in forensic populations. However, some specificity issues emerged suggesting that further research and a good forensic practice should keep into account multiple measures of malingering, including psychometric data, clinical and social history and current clinical situation. These methodological constraints must be kept in mind during detection of malingering in criminal defendants reporting psychiatric symptoms.