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A model to differentiate WAD patients and people with abnormal pain behaviour based on Biomechanical and self-reported tests

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A model to differentiate WAD patients and people with abnormal pain behaviour based on Biomechanical and self-reported tests

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dc.contributor.author Monaro, Merylin es_ES
dc.contributor.author De Rosario Martínez, Helios es_ES
dc.contributor.author Baydal Bertomeu, José Mª es_ES
dc.contributor.author Bernal-Lafuente, Marta es_ES
dc.contributor.author Masiero, Stefano es_ES
dc.contributor.author Macía-Calvo, Mónica es_ES
dc.contributor.author Cantele, Francesca es_ES
dc.contributor.author Sartori, Giuseppe es_ES
dc.date.accessioned 2022-05-20T18:05:44Z
dc.date.available 2022-05-20T18:05:44Z
dc.date.issued 2021-07 es_ES
dc.identifier.issn 0937-9827 es_ES
dc.identifier.uri http://hdl.handle.net/10251/182748
dc.description.abstract [EN] The prevalence of malingering among individuals presenting whiplash-related symptoms is significant and leads to a huge economic loss due to fraudulent injury claims. Various strategies have been proposed to detect malingering and symptoms exaggeration. However, most of them have been not consistently validated and tested to determine their accuracy in detecting feigned whiplash. This study merges two different approaches to detect whiplash malingering (the mechanical approach and the qualitative analysis of the symptomatology) to obtain a malingering detection model based on a wider range of indices, both biomechanical and self-reported. A sample of 46 malingerers and 59 genuine clinical patients was tested using a kinematic test and a self-report questionnaire asking about the presence of rare and impossible symptoms. The collected measures were used to train and validate a linear discriminant analysis (LDA) classification model. Results showed that malingerers were discriminated from genuine clinical patients based on a greater proportion of rare symptoms vs. possible self-reported symptoms and slower but more repeatable neck motions in the biomechanical test. The fivefold cross-validation of the LDA model yielded an area under the curve (AUC) of 0.84, with a sensitivity of 77.8% and a specificity of 84.7%. es_ES
dc.description.sponsorship Open access funding provided by Universita degli Studi di Padova within the CRUI-CARE Agreement. This work was supported by funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 777090 es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof International Journal of Legal Medicine es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject WAD es_ES
dc.subject Whiplash es_ES
dc.subject Malingering detection es_ES
dc.subject Whiplash kinematic test es_ES
dc.subject Whiplash self-report questionnaire es_ES
dc.title A model to differentiate WAD patients and people with abnormal pain behaviour based on Biomechanical and self-reported tests es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s00414-021-02572-5 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/777090/EU es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Monaro, M.; De Rosario Martínez, H.; Baydal Bertomeu, JM.; Bernal-Lafuente, M.; Masiero, S.; Macía-Calvo, M.; Cantele, F.... (2021). A model to differentiate WAD patients and people with abnormal pain behaviour based on Biomechanical and self-reported tests. International Journal of Legal Medicine. 135(4):1637-1646. https://doi.org/10.1007/s00414-021-02572-5 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s00414-021-02572-5 es_ES
dc.description.upvformatpinicio 1637 es_ES
dc.description.upvformatpfin 1646 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 135 es_ES
dc.description.issue 4 es_ES
dc.identifier.pmid 33774707 es_ES
dc.identifier.pmcid PMC8205908 es_ES
dc.relation.pasarela S\464990 es_ES
dc.contributor.funder European Commission es_ES
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