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Objectives <p>Large language models are becoming increasingly significant tools in everyday life, including the context of training and sports. However, the extent to which recreational athletes actually rely on AI-generated training plans and the differences in trust towards these technologies between users and non-users have not yet been investigated. Furthermore, there is a lack of information regarding the current quality of such AI-generated training plans. The aim of this project was to examine how users and non-users differ in their trust towards these technologies and to assess the quality of AI-generated training plans.</p> Results <p>In our sample, 54% of the participants trained using a structured training plan, with 25% of those utilizing AI-generated training plans. Users of these AI-based tools exhibited significantly (<i>p</i> = 0.030) higher levels of trust in these technologies compared to non-users. The quality of the output from large language models has now reached a level where even professional coaches are often unable to distinguish whether a training plan was AI-generated or created by a human expert. This suggests that AI-generated training plans could potentially match the standards of those developed by experienced coaches, making them a viable option for athletes seeking guidance in their training.</p>

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Acceptance and trust in AI-generated exercise plans among recreational athletes and quality evaluation by experienced coaches: a pilot study

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月13日

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  • Felix Wachholz,
  • Stefano Manno,
  • Daniel Schlachter,
  • Nicole Gamper,
  • Martin Schnitzer

摘要

Objectives

Large language models are becoming increasingly significant tools in everyday life, including the context of training and sports. However, the extent to which recreational athletes actually rely on AI-generated training plans and the differences in trust towards these technologies between users and non-users have not yet been investigated. Furthermore, there is a lack of information regarding the current quality of such AI-generated training plans. The aim of this project was to examine how users and non-users differ in their trust towards these technologies and to assess the quality of AI-generated training plans.

Results

In our sample, 54% of the participants trained using a structured training plan, with 25% of those utilizing AI-generated training plans. Users of these AI-based tools exhibited significantly (p = 0.030) higher levels of trust in these technologies compared to non-users. The quality of the output from large language models has now reached a level where even professional coaches are often unable to distinguish whether a training plan was AI-generated or created by a human expert. This suggests that AI-generated training plans could potentially match the standards of those developed by experienced coaches, making them a viable option for athletes seeking guidance in their training.