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Towards a tool to discriminate between pain mechanistic descriptors: expert ranking of clinical features and allocation of weights using a forced choice paradigm
Univ Queensland, Ctr Innovat Pain & Hlth Res CIPHeR, Brisbane, Australia.;Univ Queensland, Sch Hlth & Rehabil Sci, Brisbane, Qld 4072, Australia..
Univ Queensland, Ctr Innovat Pain & Hlth Res CIPHeR, Brisbane, Australia.;Univ Queensland, RECOVER Injury Res Ctr, NHMRC Ctr Res Excellence Beter Hlth Outcomes Comp, Brisbane, Australia..
Univ Iowa, Dept Phys Therapy & Rehabil Sci & Neurosci & Pharm, Iowa City, IA USA..
Aalborg Univ, Ctr Neuroplast & Pain CNAP, Sch Med, Dept Hlth Sci & Technol, Gistrup, Denmark.;Aalborg Univ Hosp, Mech Sense & Steno Diabet Ctr North Denmark, Dept Gastroenterol & Hepatol, Aalborg, Denmark..
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2026 (English)In: Pain, ISSN 0304-3959, E-ISSN 1872-6623, Vol. 167, no 7, p. 1669-1682Article in journal (Refereed) Published
Abstract [en]

Pain treatments have modest effects. Health outcomes might be improved if treatments are matched to mechanisms underlying the persistence and biopsychosocial impact of an individual's pain. The International Association for the Study of Pain (IASP) defines 3 mechanistic pain descriptors presumed to involve different mechanisms - nociceptive, neuropathic, and nociplastic. Although treatments to address each descriptor have been proposed, there is no consensus on how to assign descriptors to clinical presentations. A recent consensus identified candidate clinical features to discriminate between descriptors in clinical practice and research. These need refinement to progress towards a tool. This study aimed to determine the rank and relative weight of identified clinical features to aid discrimination between mechanistic pain descriptors. Candidate clinical features (n = 196) were refined by the IASP Terminology Task Force to converge similar and remove redundant features. The Task Force (n = 24) and an expert panel (n = 39) ranked features using 1000minds conjoint analysis software and assigned weights based on discrete pairwise choices. Participants nominated from pairs of scenarios, which most likely indicated that pain aligned predominantly to a descriptor. Highest ranked features for neuropathic and nociplastic pain were aligned with IASP Clinical Criteria. Criteria for nociceptive pain have not been established. A ranked list of features shared by 2 mechanisms (indicating mixed mechanisms) was also identified. This study identified expert consensus on the highest ranked clinical features with potential to discriminate between pain descriptors, reflective of different underlying mechanisms. This study extends current frameworks by identifying and refining key discriminators for future operationalisation and validation.

Place, publisher, year, edition, pages
Wolters Kluwer, 2026. Vol. 167, no 7, p. 1669-1682
Keywords [en]
Pain, Mechanism-based classification, Nociceptive, Neuropathic, Nociplastic, Consensus, IASP
National Category
Neurology Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
URN: urn:nbn:se:uu:diva-593088DOI: 10.1097/j.pain.0000000000003979ISI: 001796693200026PubMedID: 42048572Scopus ID: 2-s2.0-105040031391OAI: oai:DiVA.org:uu-593088DiVA, id: diva2:2082152
Available from: 2026-06-30 Created: 2026-06-30 Last updated: 2026-06-30Bibliographically approved

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CiteExportLink to record
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