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
Spine J . 2005;5 (4) :404-17
BACKGROUND CONTEXT: Pain-related disability is a complex phenomenon. Malingering is a potential factor in the management of patients with pain. Methodological problems and inappropriate expectations regarding diagnostic accuracy have hampered the study of malingering detection in pain. In contrast, the study of cognitive malingering in neuropsychology has led to the development of many highly accurate and reliable detection techniques. This paper applies the methods and logic that have been successful for identifying cognitive malingering to the problem of malingering in patients with pain.PURPOSE: Outline the logic of a research methodology for studying malingering detection in pain and introduce a system for the diagnosis of malingering in pain.STUDY DESIGN: Literature review and conceptual synthesis.METHODS: Examination of the research methodology and diagnostic scheme used in the study of cognitive malingering; adaptation of these methods to the problem of malingering in pain.RESULTS: Lessons derived from the study of cognitive malingering were used to generate recommendations to enhance research into detection and diagnosis of malingered pain-related disability. A comprehensive, multidimensional system for diagnosing malingering in pain-related disability was proposed.CONCLUSIONS: Pain-related disability is a multifaceted phenomenon, therefore malingering can occur in different and sometimes multiple dimensions. It is presently possible to accurately detect and diagnose malingering in some patients with pain. More work is needed for some detection techniques to be appropriately calibrated in pain populations. This work must focus on controlling the false positive error rate.