Muscles (Feb 2025)

Intra-Rater Reliability of Pressure Pain Threshold with Different Algometers in Healthy Participants

  • Alexandre Nunes,
  • Vanessa Leite

DOI
https://doi.org/10.3390/muscles4010005
Journal volume & issue
Vol. 4, no. 1
p. 5

Abstract

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Background: Algometry is a validated and reliable measurement tool, but there are still no reliable data for the different algometers used by different raters in the same participant. Objective: The aim of this study was to determine the intra-reliability of pressure pain thresholds (PPTs) measured using a digital algometer with and without a digital screen by different raters at the same time in a pain-free population. Methods: Participants were healthy adults. PPTs were assessed using two different algometers: a digital algometer with a digital screen for a feedback of the pressure curve rate (SpTech Digital Algometer); and a digital algometer without a screen (Wagner Instruments FDX-25, Greenwich, CT, USA). Four PPT points were used: upper trapezius, lumbar spine, extensor carpi ulnaris, and tibialis anterior. The Copenhagen Psychosocial Questionnaire II was used to assess burnout, stress, sleeping problems, depressive symptoms, somatic stress, and cognitive stress. The intraclass coefficients (ICCs) for intra-rater reliability was calculated using a two-way mixed effects model, single measurement type, and absolute agreement definition. Results: A total of 47 healthy participants with a mean age of 30.51 (11.35) years were included. The upper trapezius and extensor carpi ulnaris had the lowest PPT values, and the tibialis anterior had the highest PPT value. Females had the lowest PPT values when compared with males with p < 0.05 in the upper trapezius and extensor carpi ulnaris regions. The intra-rater reliability ranged from good to excellent reliability, with the ICC values of rater 1 being higher when compared with rater 2. The PPT in tibialis anterior had the highest mean ICC scores. Conclusions: The intra-rater reliability of PPTs measured by different digital algometers ranged from good to excellent reliability. The rater with more experience demonstrated higher reliability.

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