Literature DB >> 30884135

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

Marília Caseiro1, Arthur Woznowski-Vu2, Anamaria S De Oliveira3, Felipe J J Reis4, Timothy H Wideman2.   

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.
© 2019 World Institute of Pain.

Entities:  

Keywords:  pain; pain measurement; reproducibility of results

Year:  2019        PMID: 30884135     DOI: 10.1111/papr.12780

Source DB:  PubMed          Journal:  Pain Pract        ISSN: 1530-7085            Impact factor:   3.183


  3 in total

1.  Quantification of Digital Body Maps for Pain: Development and Application of an Algorithm for Generating Pain Frequency Maps.

Authors:  Abhishek Dixit; Michael Lee
Journal:  JMIR Form Res       Date:  2022-06-24

2.  'Painting my pain': the use of pain drawings to assess multisite pain in women with primary dysmenorrhea.

Authors:  Jéssica Cordeiro Rodrigues; Mariana Arias Avila; Felipe Jose Jandre Dos Reis; Roberta Moraes Carlessi; Amanda Garcia Godoy; Guilherme Tavares Arruda; Patricia Driusso
Journal:  BMC Womens Health       Date:  2022-09-07       Impact factor: 2.742

Review 3.  Current management of cancer pain in Italy: Expert opinion paper.

Authors:  Franco Marinangeli; Annalisa Saetta; Antonio Lugini
Journal:  Open Med (Wars)       Date:  2021-12-06
  3 in total

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