Abstract
BackgroundpainDETECT (PD-Q) is a self-reported assessment of pain qualities developed as a screening tool for pain of neuropathic origin. Rasch analysis is a strategy for examining the measurement characteristics of a scale using a form of item response theory. We conducted a Rasch analysis to consider if the scoring and measurement properties of PD-Q would support its use as an outcome measure.MethodsRasch analysis was conducted on PD-Q scores drawn from a cross-sectional study of the burden and costs of NeP. The analysis followed an iterative process based on recommendations in the literature, including examination of sequential scoring categories, unidimensionality, reliability and differential item function. Data from 624 persons with a diagnosis of painful diabetic polyneuropathy, small fibre neuropathy, and neuropathic pain associated with chronic low back pain, spinal cord injury, HIV-related pain, or chronic post-surgical pain was used for this analysis.ResultsPD-Q demonstrated fit to the Rasch model after adjustments of scoring categories for four items, and omission of the time course and radiating questions. The resulting seven-item scale of pain qualities demonstrated good reliability with a person-separation index of 0.79. No scoring bias (differential item functioning) was found for this version.ConclusionsRasch modelling suggests the seven pain-qualities items from PD-Q may be used as an outcome measure. Further research is required to confirm validity and responsiveness in a clinical setting.
Highlights
PainDETECT (PD-Q) is a self-reported assessment of pain qualities developed as a screening tool for pain of neuropathic origin
Demographic data included age, sex, and neuropathic pain (NeP) diagnostic group; other person-level characteristics included in the analysis were summary scores from the physical and mental components scales (PCS and Mental components summary (MCS)) of the Short form (SF)-12 [23] and pain severity and pain interference scores from the Brief Pain Inventory (BPI) [24, 25]
Variable selection originated from a rank-ordering exercise of six external experts in NeP from a network of clinicians and scientists working on the development of a Core Outcome Measures for complex regional PAin syndrome Clinical STudies (COMPACT) [26]
Summary
PainDETECT (PD-Q) is a self-reported assessment of pain qualities developed as a screening tool for pain of neuropathic origin. A key advantage of this type of analysis is if data produced by a measure like PD-Q fit the Rasch model, the ordinal scale measurements of individual test items (such as PD-Q’s Never to Very Strongly ratings) can be converted into interval-level scaling like 0 to 5 that can be credibly summed into total scores, with desirable measurement properties [13, 14] Another key premise of Rasch modelling is invariance of the model across samples: meaning a Rasch-validated tool can be expected to measure the same way regardless of the population being studied [15, 16] because the assessment itself is validated, not the measurement characteristics for a specific population
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