From Paper to Digitalized Body Map: A Reliability Study of the Pain Area

Pain Pract. 2019 Jul;19(6):602-608. doi: 10.1111/papr.12780. Epub 2019 Apr 11.

Abstract

Background: Computerized methods to analyze pain drawings (PDs) have been developed and may aid to measure the pain area more precisely.

Objective: The aim of this study was to verify whether examiners can reproduce the patient's PDs with acceptable reliability.

Methods: This was an intra-rater and inter-rater reliability study. The protocol consisted of 4 steps: (1) scanning of paper PDs; (2) sharing the digitalized PD images between examiners; (3) reproducing the PD images in the sketching application; and (4) calculating the pain area in pixels and percentages. We calculated intraclass correlation coefficients (ICCs; 2,1), the standard error of the measurement (SEM), and the smallest detectable difference (SDD).

Results: Reliability was tested using 31 PDs from 17 patients in our database (11 female [64.7%], mean age: 53.23 ± 11.57 years). Intra-rater reliability varied from ICC (2,1) = 0.991 (95% confidence interval [CI] = 0.982 to 0.996; SEM = 3,432.45; SDD = 162.39 pixels; P < 0.001) to ICC (2,1) = 0.992 (95% CI = 0.978 to 0.997; SEM = 3,412.96; SDD = 161.93 pixels; P < 0.001). Inter-rater reliability for the measurement between all examiners was considered excellent (ICC [2,1] = 0.976; 95% CI = 0.956 to 0.987; SEM =8,580.75; SDD = 256.76 pixels; P < 0.001), being higher between Examiners A and C (ICC [2,1] = 0.970; 95% CI = 0.936 to 0.986; SEM = 6,453.34; SDD = 222.67 pixels; P < 0.001).

Conclusion: Our results show that intra- and inter-rater reliabilities were excellent when an examiner reproduced the paper PDs into digitalized PDs. This process gives clinicians and researchers the opportunity to analyze pain extent more precisely using a computerized method.

Keywords: pain; pain measurement; reproducibility of results.

MeSH terms

  • Adult
  • Aged
  • Algorithms
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Male
  • Middle Aged
  • Observer Variation
  • Pain Measurement / methods*
  • Reproducibility of Results