Bone and Joint Institute


Measurement properties of the SF-MPQ-2 neuropathic qualities subscale in persons with CRPs: Validity, responsiveness, and Rasch analysis

Document Type


Publication Date



Pain Medicine (United States)





First Page


Last Page


URL with Digital Object Identifier



© 2018 American Academy of Pain Medicine. All rights reserved. Objectives. The purpose of this study was to conduct classical psychometric evaluation and Rasch analysis on the Neuropathic Qualities subscale of the Short-Form McGill Pain Questionnaire-2 utilizing scores from persons with complex regional pain syndrome to consider reliability and person separation, validity (including unidimensionality), and responsiveness in this population. Methods. Secondary analysis of longitudinal data from persons with acute complex regional pain syndrome was utilized for analysis of the psychometric properties and fit to the Rasch model of the Neuropathic Qualities subscale. We followed an iterative process of Rasch analysis to evaluate and address data fitting challenges. Results. Repeated measures from 59 persons meeting the Budapest criteria were used for analysis. Both item-total correlations and unidimensionality analyses supported theoretical construct validity; all convergent construct validity hypotheses were also supported. Responsiveness was demonstrated comparing baseline and one-year data at d ¼ 0.92, with a standardized response mean of 0.97. Data were able to fit the Rasch model, but all Neuropathic Qualities items had disordered thresholds that required rescoring. Additionally, local dependency and differential item function were addressed by “bundling,” suggesting that no further item reduction would be possible. Conclusions. This study provided preliminary support for the validity and responsiveness of the Neuropathic Qualities subscale in persons with complex regional pain syndrome. Rasch analysis further endorses use of the Neuropathic Qualities subscale as a “stand-alone” measure for neuropathic features, but with substantial background data transformations. Replication with larger samples is recommended to increase confidence in these findings.

This document is currently not available here.