Plateforme de veille scientifique et de revue de littérature basée sur PubMed
Alimenté par : Madeline Desmurs
Cette application est une plateforme collaborative de veille scientifique permettant d'importer des publications depuis PubMed, de suivre leur lecture, d'en extraire les éléments méthodologiques clés (protocole, variables, résultats), et de constituer une synthèse structurée pour faciliter la réalisation de revues de littérature.
Dernière synchronisation : 18/06/2026
Clin Neuropsychol . 2014;28 (8) :1336-65
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.