The reliability and concurrent validity of PainMAP software for automated quantification of pain drawings on body charts of patients with low back pain

Leticia Amaral Corrêa, Juliana Valentim Bittencourt, Arthur de Sá Ferreira, Felipe José Jandre Reis, Renato Santos de Almeida, Leandro Alberto Calazans Nogueira*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Background: The assessment of painful areas through printed body charts is a simple way for clinicians to identify patients with widespread pain in primary care. However, there is a lack in the literature about a simple and automated method designed to analyze pain drawings in body charts in clinical practice.

Purpose: To test the inter- and intra-rater reliabilities and concurrent validity of software (PainMAP) for quantification of pain drawings in patients with low back pain.

Methods: Thirty-eight participants (16 [42.10%] female; mean age 50.24 [11.54] years; mean body mass index 27.90 [5.42] kg/m2; duration of pain of 94.35 [96.11] months) with a current episode of low back pain were recruited from a pool of physiotherapy outpatients. Participants were instructed to shade all their painful areas on a body chart using a red pen. The body charts were digitized by separate raters using smartphone cameras and twice for one rater to analyze the intra-rater reliability. Both the number of pain sites and the pain area were calculated using ImageJ software (reference method). The PainMAP software used image processing methods to automatically quantify the data from the same digitized body charts.

Results: The reliability analyses revealed that PainMAP has excellent inter- and intra-rater reliabilities to quantify the number of pain sites (intraclass correlation coefficient [ICC]2,1: 0.998 [95% confidence interval (CI) 0.996 to 0.999]; ICC2,1: 0.995 [95% CI 0.991 to 0.998]) and the pain area [ICC2,1: 0.998 (95% CI 0.995 to 0.999); ICC2,1: 0.975 (95% CI 0.951 to 0.987)], respectively. The standard error of the measurement was 0.22 (4%) for the number of pain sites and 0.03 cm2 (4%) for the pain area. The Bland-Altman analyses revealed no substantive differences between the 2 methods for the pain area (mean difference = 0.007 [95% CI −0.053 to 0.067]).

Conclusion: PainMAP software is reliable and valid for quantification of the number of pain sites and the pain area in patients with low back pain.
Original languageEnglish
Pages (from-to)462-470
Number of pages9
JournalPain Practice
Volume20
Issue number5
DOIs
Publication statusPublished - Jun 2020
Externally publishedYes

Keywords

  • low back pain
  • validation study
  • reliability
  • pain measurement
  • pain

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