Exploring the Capacity of Large Language Models to Assess the Chronic Pain Experience: Algorithm Development and Validation.

Journal: Journal of medical Internet research
PMID:

Abstract

BACKGROUND: Chronic pain, affecting more than 20% of the global population, has an enormous pernicious impact on individuals as well as economic ramifications at both the health and social levels. Accordingly, tools that enhance pain assessment can considerably impact people suffering from pain and society at large. In this context, assessment methods based on individuals' personal experiences, such as written narratives (WNs), offer relevant insights into understanding pain from a personal perspective. This approach can uncover subjective, intricate, and multifaceted aspects that standardized questionnaires can overlook. However, WNs can be time-consuming for clinicians. Therefore, a tool that uses WNs while reducing the time required for their evaluation could have a significantly beneficial impact on people's pain assessment.

Authors

  • Jacopo Amidei
    AI and Data for Society Research Group, Internet Interdisciplinary Institute, Universitat Oberta de Catalunya, Barcelona, Spain.
  • Rubén Nieto
    eHealth Lab Research Group, Faculty of Psychology and Educational Sciences, Universitat Oberta de Catalunya, Barcelona, Spain.
  • Andreas Kaltenbrunner
    AI and Data for Society Research Group, Internet Interdisciplinary Institute, Universitat Oberta de Catalunya, Barcelona, Spain.
  • Jose Gregorio Ferreira De Sá
    AI and Data for Society Research Group, Internet Interdisciplinary Institute, Universitat Oberta de Catalunya, Barcelona, Spain.
  • Mayte Serrat
    Unitat d'Expertesa en Síndromes de Sensibilització Central, Servei de Reumatologia, Vall d'Hebron Hospital Universitari, Barcelona, Spain.
  • Klara Albajes
    Psyclinic Mental Health, Barcelona, Spain.