Generative Conversations in Physiotherapy
  • Overview
    • Welcome
    • Executive summary
  • Generative AI overview
  • Methods
  • The team
  • Clinical Practice
    • Introduction
    • Opportunities
    • Risks
  • Strategies
  • Guidance for stakeholders
  • Education
    • Introduction
    • Opportunities
  • Risks
  • Strategies
  • Guidance for stakeholders
  • Research
    • Introduction
    • Opportunities
    • Risks
    • Strategies
    • Guidance for stakeholders
  • Synthesis
    • Guidance for stakeholders
    • Looking ahead
    • Conclusion
    • References
Powered by GitBook
On this page
  1. Overview

Welcome

NextExecutive summary

Last updated 1 month ago

This discussion document explores the integration of generative AI in physiotherapy, developed through collaborative activities at the 2024 IFOMPT conference. It serves as a stimulus for physiotherapy departments, schools, organizations, regulators, practitioners, students, and even patients to engage in meaningful conversation about what this rapidly evolving technology might mean for the profession.

The document is intentionally designed for flexible engagement rather than linear reading. Recognising the diverse needs and contexts of our audience, we've structured the content to allow you to dip in and out according to your specific interests, working context, and use cases. Some information may be repeated across sections, as we don't expect anyone to read the document from cover to cover.

As you explore this resource, we encourage you to consider both the opportunities and challenges that generative AI presents to physiotherapy. The insights gathered here are not prescriptive, but rather aim to spark thoughtful discussion, critical reflection, and proactive planning within your own context. Whether you're a clinician, educator, researcher, student, or connected to the profession in another capacity, there's relevant content to help you navigate this technological transformation.

Note: This document deliberately focuses on generative AI's current capabilities rather than speculative future applications. We've worked to ground our discussion in what today's AI models can actually do in physiotherapy contexts, avoiding unsubstantiated claims about potential future developments. At the same time, we've structured the document to remain relevant despite rapid technological changes in AI. The key opportunities, challenges, and integration strategies we discuss are anchored in fundamental professional principles and practices that transcend specific model capabilities, ensuring the document's insights will remain valuable even as models like GPT and Claude continue to evolve.

Page cover image
Cover

An overview of the potential of AI in clinical practice, exploring how generative AI can enhance diagnosis, personalise treatment planning, improve monitoring, increase administrative efficiency, and strengthen patient education while addressing associated risks and implementation strategies.

Cover

An overview of the potential of AI in physiotherapy education, examining how AI technologies can create personalised learning experiences, enhance simulations, automate assessment processes, and develop critical research skills while considering the challenges to traditional educational approaches.

Cover

An overview of the potential of AI in clinical research, investigating how AI can streamline literature reviews, uncover complex data patterns, generate novel hypotheses, standardise protocols, and facilitate global collaboration while addressing scientific integrity and ethical considerations.

Practice
Education
Research