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Comprehensiveness, Accuracy, and Readability of Exercise Recommendations Provided by an AI-Based Chatbot: Mixed

Amanda L Zaleski^1,2, Rachel Berkowsky³, Kelly Jean Thomas Craig¹

¹Clinical Evidence Development, Aetna Medical Affairs, CVS Health Corporation, Hartford, CT, United States.

JMIR Medical Education

|January 11, 2024

Summary

Artificial intelligence (AI) chatbots provide exercise recommendations that are not fully comprehensive or easily readable. Healthcare professionals should exercise caution with AI-generated advice due to accuracy gaps and potential biases.

Keywords:

AI artificial intelligence chatbot exercise prescription health literacy large language model patient education

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Area of Science:

Exercise Science
Artificial Intelligence in Healthcare
Digital Health

Background:

Physical activity is crucial for health and disease prevention.
Barriers exist for implementing evidence-based lifestyle recommendations.
Artificial intelligence (AI) offers potential to augment healthcare, but its suitability for exercise recommendations is unexplored.

Purpose of the Study:

To evaluate the comprehensiveness, accuracy, and readability of AI-generated exercise recommendations.
Assessing a novel AI chatbot's output for clinical populations.

Main Methods:

Developed a coding scheme for 10 categories of exercise recommendations.
AI chatbot generated recommendations for 26 clinical populations.
Assessed comprehensiveness, accuracy, and readability (Flesch-Kincaid).

Main Results:

AI recommendations were 41.2% comprehensive and 90.7% accurate.
Inaccuracies often related to preparticipation medical clearance.
Readability was at a college level; themes included safety concerns, aerobic bias, and potential discrimination.

Conclusions:

Significant gaps exist in AI-generated exercise recommendation comprehensiveness, accuracy, and readability.
Exercise and healthcare professionals must recognize AI technology limitations.
Caution is advised when using AI tools for exercise-based lifestyle changes.