Accepted for/Published in: JMIR Human Factors
Date Submitted: Dec 31, 2023
Date Accepted: May 5, 2024
HUMAN FACTORS IN AI-DRIVEN DIGITAL SOLUTIONS FOR INCREASING PHYSICAL ACTIVITY: A SCOPING REVIEW
ABSTRACT
Background:
Human factors play a pivotal role in the successful integration of AI into mHealth solutions aimed at promoting physical activity. Understanding and optimizing the interaction between individuals and AI-driven mHealth applications is essential for achieving the desired outcomes.
Objective:
The objective of this study is to review and describe the current evidence regarding the human factors in AI-driven digital solutions for increasing physical activity
Methods:
We conducted a scoping review in which we searched for terms related to physical activity, human factors, and artificial intelligence in PubMed, EMBASE, IEEE Xplore, and Google Scholar. Additionally, we searched for relevant research cited in the articles selected for inclusion. The certainty of evidence of the included studies was evaluated drawing on the Grading of Recommendations Assessment, Development and Evaluation (GRADE)
Results:
A total of 15 studies were included in this review. Recommender systems were the most commonly used AI technology in digital solutions for physical activity, appearing in 10 out of the 15 studies, followed by conversational agents, which were used in 4 of the included studies. User acceptability and satisfaction were the human factors most frequently evaluated, with each being evaluated in five studies, followed by usability, which was assessed in four studies. The certainty of the evidence analysis indicates that there are grounds to believe that AI-driven digital technologies increase physical activity (e.g., the number of steps, distance walked, or time spent on physical activity). Furthermore, AI-driven technology, particularly recommender systems, seems to have the potential to influence changes in physical activity behavior.
Conclusions:
Current research highlights the potential of AI-driven technologies to enhance physical activity, though current evidence remains limited. Further exploration into optimizing AI's impact on physical activity is crucial for broader benefits, necessitating increased research on integrating AI and human factors effectively
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Copyright
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