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Scandinavian Journal of Pain

Official Journal of the Scandinavian Association for the Study of Pain

Editor-in-Chief: Breivik, Harald


CiteScore 2017: 0.84

SCImago Journal Rank (SJR) 2017: 0.401
Source Normalized Impact per Paper (SNIP) 2017: 0.452

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1877-8879
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Volume 13, Issue 1

Issues

How to analyze the Visual Analogue Scale: Myths, truths and clinical relevance

Gillian Z. Heller
  • Corresponding author
  • Department of Statistics, Faculty of Science and Engineering, Macquarie University, NSW, 2109, Australia
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Maurizio Manuguerra
  • Department of Statistics, Faculty of Science and Engineering, Macquarie University, NSW, 2109, Australia
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Roberta Chow
Published Online: 2016-10-01 | DOI: https://doi.org/10.1016/j.sjpain.2016.06.012

Abstract

Background and aims

The Visual Analogue Scale (VAS) is a popular tool for the measurement of pain. A variety of statistical methods are employed for its analysis as an outcome measure, not all of them optimal or appropriate. An issue which has attracted much discussion in the literature is whether VAS is at a ratio or ordinal level of measurement. This decision has an influence on the appropriate method of analysis. The aim of this article is to provide an overview of current practice in the analysis of VAS scores, to propose a method of analysis which avoids the shortcomings of more traditional approaches, and to provide best practice recommendations for the analysis of VAS scores.

Methods

We report on the current usage of statistical methods, which fall broadly into two categories: those that assume a probability distribution for VAS, and those that do not. We give an overview of these methods, and propose continuous ordinal regression, an extension of current ordinal regression methodology, which is appropriate for VAS at an ordinal level of measurement. We demonstrate the analysis of a published data set using a variety of methods, and use simulation to compare the power of the various methods to detect treatment differences, in differing pain situations.

Results

We demonstrate that continuous ordinal regression provides the most powerful statistical analysis under a variety of conditions.

Conclusions and Implications

We recommend that in the situation in which no covariates besides treatment group are included in the analysis, distribution-free methods (Wilcoxon, Mann–Whitney) be used, as their power is indistinguishable from that of the proposed method. In the situation in which there are covariates which affect VAS, the proposed method is optimal. However, in this case, if the VAS scores are not concentrated around either extreme of the scale, normal-distribution methods (t-test, linear regression) are almost as powerful, and are recommended as a pragmatic choice. In the case of small sample size and VAS skewed to either extreme of the scale, the proposed method has vastly superior power to other methods.

Keywords: Visual Analogue Scale; Level of measurement; Ordinal measure; Ordinal regression analysis; Wilcoxon test; Linear regression

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About the article

Tel.: +61 2 98508541.


Received: 2016-03-16

Revised: 2016-06-07

Accepted: 2016-06-30

Published Online: 2016-10-01

Published in Print: 2016-10-01


Ethical issues: The article uses previously published data and a simulation study, and therefore was not subject to ethics approval.

Funding and conflict of Interest: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.


Citation Information: Scandinavian Journal of Pain, Volume 13, Issue 1, Pages 67–75, ISSN (Online) 1877-8879, ISSN (Print) 1877-8860, DOI: https://doi.org/10.1016/j.sjpain.2016.06.012.

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