Comparing what the clinician draws on a digital pain map to that of persons who have greater trochanteric pain syndrome

Do metrics derived from self-reported and clinician-reported pain drawings agree for individuals with chronic low back pain?

BACKGROUND

Clinicians commonly use pain drawings to define the spatial extent and location of a person's pain, but limited research has investigated who should perform the drawing.

OBJECTIVES

To establish the inter-rater reliability of pain extent and location derived from three sets of pain drawings for people with chronic low back pain: one self-reported and two clinician-reported. Additionally, convergent validity of pain extent was assessed using the same dataset.

DESIGN

Repeated-measures cross-sectional study.

METHOD

Fifteen patients with chronic low back pain and a pool of eight clinicians were involved to assess the reliability of pain extent and location extracted by self-report and clinician-reported pain drawings. Inter-rater reliability of pain extent was computed using intraclass correlation coefficients (ICC) and Bland Altman analysis. Convergent validity of pain extent was assessed using Spearman's rank correlation. Inter-rater reliability of pain location was assessed using the Jaccard similarity index.

RESULTS

The inter-reliability analysis for pain extent, derived from self-reported and clinician-reported pain drawings, revealed ICC scores ranging from 0.39 to 0.51, all with wide confidence intervals. The mean Jaccard similarity indexes computed for pain location ranged from 0.60 to 0.65. Moderate to good correlation was found for pain extent derived by the sets of pain drawings.

CONCLUSIONS

Inter-rater reliability of pain extent and pain location derived from self-reported and clinician-reported pain drawings is poor in patients with chronic low back pain. The lack of reliability is also confirmed when considering only clinician-reported PDs. The convergent validity analysis of pain extent revealed that the two pain drawing approaches measure a similar construct.

Visualizing and quantifying spatial and qualitative pain sensations

Similar to the purpose of an infographic, visualizing spatial and qualitative sensations on a body chart is a fast and digestible method for communicating complex information and experiences. Further, digitizing these body charts into an interactive medium creates unprecedented opportunities for collecting extensive data. Moreover, applying simple rule-based algorithms or more advanced machine learning approaches to these charts catapults the quantification and spatiotemporal relations of pain and qualitative pain sensations into a new field ripe for pioneering discoveries.