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Overcoming pain thresholds with multilevel models : an example using quantitative sensory testing (QST) data

  • The assessment of somatosensory function is a cornerstone of research and clinical practice in neurology. Recent initiatives have developed novel protocols for quantitative sensory testing (QST). Application of these methods led to intriguing findings, such as the presence lower pain-thresholds in healthy children compared to healthy adolescents. In this article, we (re-) introduce the basic concepts of signal detection theory (SDT) as a method to investigate such differences in somatosensory function in detail. SDT describes participants’ responses according to two parameters, sensitivity and response-bias. Sensitivity refers to individuals’ ability to discriminate between painful and non-painful stimulations. Response-bias refers to individuals’ criterion for giving a “painful” response. We describe how multilevel models can be used to estimate these parameters and to overcome central critiques of these methods. To provide an example we apply these methods to data from the mechanical pain sensitivity test of the QST protocol. The results show that adolescents are more sensitive to mechanical pain and contradict the idea that younger children simply use more lenient criteria to report pain. Overall, we hope that the wider use of multilevel modeling to describe somatosensory functioning may advance neurology research and practice.

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Metadaten
Author:Gerrit HirschfeldORCiD, Markus R. BlankenburgORCiD, Moritz Süß, Boris ZernikowORCiD
Title (English):Overcoming pain thresholds with multilevel models : an example using quantitative sensory testing (QST) data
URN:urn:nbn:de:bsz:959-opus-23918
DOI:https://doi.org/10.7717/peerj.1335
ISSN:2167-8359
Parent Title (English):PeerJ
Document Type:Article
Language:English
Year of Completion:2015
Release Date:2021/08/17
Tag:Multilevel models; Quantitative sensory testing; Sensitivity; Signal detection theory; Thresholds
Page Number:13
Faculties:Fakultät WiSo
DDC classes:600 Technik, Medizin, angewandte Wissenschaften / 610 Medizin, Gesundheit
Review Status:Veröffentlichte Fassung/Verlagsversion
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International