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Measurement Properties of Visual Analogue Scale, Numeric Rating Scale, and Pain Severity Subscale of the Brief Pain Inventory in Patients With Low Back Pain: A Systematic Review

Overview
Journal J Pain
Specialties Neurology
Psychiatry
Date 2018 Aug 13
PMID 30099210
Citations 197
Authors
Affiliations
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Abstract

The Visual Analogue Scale (VAS), Numeric Rating Scale (NRS), and Pain Severity subscale of the Brief Pain Inventory (BPI-PS) are the most frequently used instruments to measure pain intensity in low back pain. However, their measurement properties in this population have not been reviewed systematically. The goal of this study was to provide such systematic evidence synthesis. Six electronic sources (MEDLINE, EMBASE, CINAHL, PsycINFO, SportDiscus, Google Scholar) were searched (July 2017). Studies assessing any measurement property in patients with nonspecific low back pain were included. Two reviewers independently screened articles and assessed risk of bias using the COSMIN checklist. For each measurement property, evidence quality was rated as high, moderate, low, or very low (GRADE approach) and results were classified as sufficient, insufficient, or inconsistent. Ten studies assessed the VAS, 13 the NRS, 4 the BPI-PS. The 3 instruments displayed low or very low quality evidence for content validity. High-quality evidence was only available for NRS insufficient measurement error. Moderate evidence was available for NRS inconsistent responsiveness, BPI-PS sufficient structural validity and internal consistency, and BPI-PS inconsistent construct validity. All VAS measurement properties were underpinned by no, low, or very low quality evidence; likewise, the other measurement properties of NRS and BPI-PS. PERSPECTIVES: Despite their broad use, there is no evidence clearly suggesting that one among VAS, NRS, and BPI-PS has superior measurement properties in low back pain. Future adequate quality head-to-head comparisons are needed and priority should be given to assessing content validity, test-retest reliability, measurement error, and responsiveness.

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