Feasibility of a Randomized Controlled Trial of Large AI-Based Linguistic Models for Clinical Reasoning Training of Physical Therapy Students: Pilot Randomized Parallel-Group Study.

Journal: JMIR formative research
Published Date:

Abstract

BACKGROUND: Clinical reasoning is a critical skill for physical therapists, involving the collection and interpretation of patient information to form accurate diagnoses. Traditional training often lacks the diversity of clinical cases necessary for students to develop these skills comprehensively. Large language models (LLMs) like GPT-4 have the potential to simulate a wide range of clinical scenarios, offering a novel approach to enhance clinical reasoning in physical therapy education.

Authors

  • Raúl Ferrer-Peña
    Grupo de Investigación Clínico-Docente sobre Ciencias de la Rehabilitación (INDOCLIN), Centro Superior de Estudios Universitarios La Salle, Universidad Autónoma de Madrid, La Salle 10, Aravaca, Madrid, 28023, Spain, 34 917401980.
  • Silvia Di-Bonaventura
    Grupo de Investigación Clínico-Docente sobre Ciencias de la Rehabilitación (INDOCLIN), Centro Superior de Estudios Universitarios La Salle, Universidad Autónoma de Madrid, La Salle 10, Aravaca, Madrid, 28023, Spain, 34 917401980.
  • Alberto Pérez-González
    Grupo de Investigación Clínico-Docente sobre Ciencias de la Rehabilitación (INDOCLIN), Centro Superior de Estudios Universitarios La Salle, Universidad Autónoma de Madrid, La Salle 10, Aravaca, Madrid, 28023, Spain, 34 917401980.
  • Alfredo Lerin-Calvo