Evaluating the Potential Role of AI Chatbots in Designing Personalized Exercise Programs for Weight Management.
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| Title: | Evaluating the Potential Role of AI Chatbots in Designing Personalized Exercise Programs for Weight Management. |
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| Authors: | Saraç, Hakan (AUTHOR), Ulusoy, İsmet Tarık (AUTHOR), Alpay, Janset (AUTHOR), Ödemiş, Hasan (AUTHOR), Söğüt, Mustafa (AUTHOR) |
| Source: | International Journal of Human-Computer Interaction. Oct2025, Vol. 41 Issue 19, p12551-12558. 8p. |
| Subjects: | Chatbots, ChatGPT, Personal trainers, Regulation of body weight, Program effectiveness (Education), Physical activity, American College of Sports Medicine |
| Abstract: | This study aimed to evaluate the effectiveness and potential use of artificial intelligence (AI) chatbots in developing personalized exercise programs for weight management. Exercise programs were developed by ChatGPT-4, ChatGPT-4o, Gemini-1.5 Pro models, and a group of human expert trainers for a hypothetical obese individual case. All exercise programs were assessed based on the American College of Sports Medicine (ACSM) and National Academy of Sports Medicine (NASM) guidelines. The chatbot-generated programs were consistent with ACSM and NASM standards, indicating their potential use in low-resource settings. Nevertheless, considerable differences were found between human trainers and chatbots in key parameters, including initial load and target heart rate zone recommendations. While AI chatbots have the potential to enhance accessibility, human expertise remains essential to ensure program safety and effectiveness. The results of this study provide insights into the potential role of AI chatbots in personalized exercise programs for weight management. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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