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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) protoco...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6064200/ https://www.ncbi.nlm.nih.gov/pubmed/30065872 http://dx.doi.org/10.7717/peerj.5259 |
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author | De Marchi, Barbara Balboni, Giulia |
author_facet | De Marchi, Barbara Balboni, Giulia |
author_sort | De Marchi, Barbara |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6064200 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60642002018-07-31 Detecting malingering mental illness in forensics: Known-Group Comparison and Simulation Design with MMPI-2, SIMS and NIM De Marchi, Barbara Balboni, Giulia PeerJ Neuroscience 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. PeerJ Inc. 2018-07-25 /pmc/articles/PMC6064200/ /pubmed/30065872 http://dx.doi.org/10.7717/peerj.5259 Text en ©2018 De Marchi and Balboni http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Neuroscience De Marchi, Barbara Balboni, Giulia Detecting malingering mental illness in forensics: Known-Group Comparison and Simulation Design with MMPI-2, SIMS and NIM |
title | Detecting malingering mental illness in forensics: Known-Group Comparison and Simulation Design with MMPI-2, SIMS and NIM |
title_full | Detecting malingering mental illness in forensics: Known-Group Comparison and Simulation Design with MMPI-2, SIMS and NIM |
title_fullStr | Detecting malingering mental illness in forensics: Known-Group Comparison and Simulation Design with MMPI-2, SIMS and NIM |
title_full_unstemmed | Detecting malingering mental illness in forensics: Known-Group Comparison and Simulation Design with MMPI-2, SIMS and NIM |
title_short | Detecting malingering mental illness in forensics: Known-Group Comparison and Simulation Design with MMPI-2, SIMS and NIM |
title_sort | detecting malingering mental illness in forensics: known-group comparison and simulation design with mmpi-2, sims and nim |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6064200/ https://www.ncbi.nlm.nih.gov/pubmed/30065872 http://dx.doi.org/10.7717/peerj.5259 |
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