The Structured Inventory of Malingered Symptomatology (SIMS): A Systematic Review and Meta-Analysis
We meta-analytically reviewed studies that used the Structured Inventory of Malingered Symptomatology (SIMS) to detect feigned psychopathology. We present weighted mean diagnostic accuracy and predictive power indices in various populations, based on 31 studies, including 61 subsamples and 4009 SIMS...
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| Published in | Clinical neuropsychologist Vol. 28; no. 8; pp. 1336 - 1365 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Hove
Routledge
17.11.2014
Psychology Press |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1385-4046 1744-4144 1744-4144 |
| DOI | 10.1080/13854046.2014.984763 |
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| Abstract | We meta-analytically reviewed studies that used the Structured Inventory of Malingered Symptomatology (SIMS) to detect feigned psychopathology. We present weighted mean diagnostic accuracy and predictive power indices in various populations, based on 31 studies, including 61 subsamples and 4009 SIMS protocols. In addition, we provide normative data of patients, claimants, defendants, nonclinical adults, and various experimental feigners, based on 41 studies, including 125 subsamples and 4810 SIMS protocols. We conclude that the SIMS (1) is able to differentiate well between instructed feigners and honest responders; (2) generates heightened scores in groups that are known to have a raised prevalence of feigning (e.g., offenders who claim crime-related amnesia); (3) may overestimate feigning in patients who suffer from schizophrenia, intellectual disability, or psychogenic non-epileptic seizures; and (4) is fairly robust against coaching. The diagnostic power of the traditional cut scores of the SIMS (i.e., > 14 and > 16) is not so much limited by their sensitivity-which is satisfactory-but rather by their substandard specificity. This, however, can be worked around by combining the SIMS with other symptom validity measures and by raising the cut score, although the latter solution sacrifices sensitivity for specificity. |
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| AbstractList | We meta-analytically reviewed studies that used the Structured Inventory of Malingered Symptomatology (SIMS) to detect feigned psychopathology. We present weighted mean diagnostic accuracy and predictive power indices in various populations, based on 31 studies, including 61 subsamples and 4009 SIMS protocols. In addition, we provide normative data of patients, claimants, defendants, nonclinical adults, and various experimental feigners, based on 41 studies, including 125 subsamples and 4810 SIMS protocols. We conclude that the SIMS (1) is able to differentiate well between instructed feigners and honest responders; (2) generates heightened scores in groups that are known to have a raised prevalence of feigning (e.g., offenders who claim crime-related amnesia); (3) may overestimate feigning in patients who suffer from schizophrenia, intellectual disability, or psychogenic non-epileptic seizures; and (4) is fairly robust against coaching. The diagnostic power of the traditional cut scores of the SIMS (i.e., > 14 and > 16) is not so much limited by their sensitivity-which is satisfactory-but rather by their substandard specificity. This, however, can be worked around by combining the SIMS with other symptom validity measures and by raising the cut score, although the latter solution sacrifices sensitivity for specificity. We meta-analytically reviewed studies that used the Structured Inventory of Malingered Symptomatology (SIMS) to detect feigned psychopathology. We present weighted mean diagnostic accuracy and predictive power indices in various populations, based on 31 studies, including 61 subsamples and 4009 SIMS protocols. In addition, we provide normative data of patients, claimants, defendants, nonclinical adults, and various experimental feigners, based on 41 studies, including 125 subsamples and 4810 SIMS protocols. We conclude that the SIMS (1) is able to differentiate well between instructed feigners and honest responders; (2) generates heightened scores in groups that are known to have a raised prevalence of feigning (e.g., offenders who claim crime-related amnesia); (3) may overestimate feigning in patients who suffer from schizophrenia, intellectual disability, or psychogenic non-epileptic seizures; and (4) is fairly robust against coaching. The diagnostic power of the traditional cut scores of the SIMS (i.e., > 14 and > 16) is not so much limited by their sensitivity—which is satisfactory—but rather by their substandard specificity. This, however, can be worked around by combining the SIMS with other symptom validity measures and by raising the cut score, although the latter solution sacrifices sensitivity for specificity.We meta-analytically reviewed studies that used the Structured Inventory of Malingered Symptomatology (SIMS) to detect feigned psychopathology. We present weighted mean diagnostic accuracy and predictive power indices in various populations, based on 31 studies, including 61 subsamples and 4009 SIMS protocols. In addition, we provide normative data of patients, claimants, defendants, nonclinical adults, and various experimental feigners, based on 41 studies, including 125 subsamples and 4810 SIMS protocols. We conclude that the SIMS (1) is able to differentiate well between instructed feigners and honest responders; (2) generates heightened scores in groups that are known to have a raised prevalence of feigning (e.g., offenders who claim crime-related amnesia); (3) may overestimate feigning in patients who suffer from schizophrenia, intellectual disability, or psychogenic non-epileptic seizures; and (4) is fairly robust against coaching. The diagnostic power of the traditional cut scores of the SIMS (i.e., > 14 and > 16) is not so much limited by their sensitivity—which is satisfactory—but rather by their substandard specificity. This, however, can be worked around by combining the SIMS with other symptom validity measures and by raising the cut score, although the latter solution sacrifices sensitivity for specificity. |
| Author | Merckelbach, Harald Jelicic, Marko van Impelen, Alfons Merten, Thomas |
| Author_xml | – sequence: 1 givenname: Alfons surname: van Impelen fullname: van Impelen, Alfons email: alfons.vanimpelen@maastrichtuniversity.nl organization: Forensic Psychology Section, Maastricht University – sequence: 2 givenname: Harald surname: Merckelbach fullname: Merckelbach, Harald organization: Forensic Psychology Section, Maastricht University – sequence: 3 givenname: Marko surname: Jelicic fullname: Jelicic, Marko organization: Forensic Psychology Section, Maastricht University – sequence: 4 givenname: Thomas surname: Merten fullname: Merten, Thomas organization: Department of Neurology, Vivantes Klinikum im Friedrichshain |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=29083523$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/25494444$$D View this record in MEDLINE/PubMed |
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| Keywords | Human Questionnaire Malingering Response bias Psychometrics Review Metaanalysis Symptom validity Symptomatology Sensitivity Specificity Response falsification Structured Inventory of Malingered Symptomatology Simulation behavior Psychopathology |
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| Snippet | We meta-analytically reviewed studies that used the Structured Inventory of Malingered Symptomatology (SIMS) to detect feigned psychopathology. We present... |
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| SubjectTerms | Biological and medical sciences Humans Interview, Psychological Malingering Malingering - diagnosis Medical sciences Neuropsychological Tests Personality Inventory Psychology. Psychoanalysis. Psychiatry Psychometrics. Diagnostic aid systems Psychopathology Psychopathology. Psychiatry Response bias Sensitivity and Specificity Structured Inventory of Malingered Symptomatology Symptom validity Techniques and methods |
| Title | The Structured Inventory of Malingered Symptomatology (SIMS): A Systematic Review and Meta-Analysis |
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