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 h...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2015-11-01
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| Series: | PeerJ |
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| Online Access: | https://peerj.com/articles/1335.pdf |
| _version_ | 1827606777320964096 |
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| author | Gerrit Hirschfeld Markus R. Blankenburg Moritz Süß Boris Zernikow |
| author_facet | Gerrit Hirschfeld Markus R. Blankenburg Moritz Süß Boris Zernikow |
| author_sort | Gerrit Hirschfeld |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T06:43:14Z |
| format | Article |
| id | doaj.art-471ab20c3ff8421db61c8715861ca3a3 |
| institution | Directory Open Access Journal |
| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T06:43:14Z |
| publishDate | 2015-11-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ |
| spelling | doaj.art-471ab20c3ff8421db61c8715861ca3a32023-12-03T10:41:29ZengPeerJ Inc.PeerJ2167-83592015-11-013e133510.7717/peerj.1335Overcoming pain thresholds with multilevel models—an example using quantitative sensory testing (QST) dataGerrit Hirschfeld0Markus R. Blankenburg1Moritz Süß2Boris Zernikow3Faculty of Business Management and Social Sciences, University of Applied Sciences Osnabrück, Osnabrück, GermanyChair for Children’s Pain Therapy and Paediatric Palliative Care, Witten/Herdecke University, Witten/Herdecke, GermanyDepartment for Psychology, University Düsseldorf, Düsseldorf, GermanyChair for Children’s Pain Therapy and Paediatric Palliative Care, Witten/Herdecke University, Witten/Herdecke, GermanyThe 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.https://peerj.com/articles/1335.pdfPainThresholdsSignal detection theorySensitivityMultilevel modelsQuantitative sensory testing |
| spellingShingle | Gerrit Hirschfeld Markus R. Blankenburg Moritz Süß Boris Zernikow Overcoming pain thresholds with multilevel models—an example using quantitative sensory testing (QST) data PeerJ Pain Thresholds Signal detection theory Sensitivity Multilevel models Quantitative sensory testing |
| title | Overcoming pain thresholds with multilevel models—an example using quantitative sensory testing (QST) data |
| title_full | Overcoming pain thresholds with multilevel models—an example using quantitative sensory testing (QST) data |
| title_fullStr | Overcoming pain thresholds with multilevel models—an example using quantitative sensory testing (QST) data |
| title_full_unstemmed | Overcoming pain thresholds with multilevel models—an example using quantitative sensory testing (QST) data |
| title_short | Overcoming pain thresholds with multilevel models—an example using quantitative sensory testing (QST) data |
| title_sort | overcoming pain thresholds with multilevel models an example using quantitative sensory testing qst data |
| topic | Pain Thresholds Signal detection theory Sensitivity Multilevel models Quantitative sensory testing |
| url | https://peerj.com/articles/1335.pdf |
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