Authors’ Reply: Enhancing the Clinical Relevance of Al Research for Medication Decision-Making

We appreciate the insights regarding our manuscript, “Investigating Older Adults’ Perceptions of AI Tools for Medication Decisions: Vignette-Based Experimental Survey” [Vordenberg SE, Nichols J, Marshall VD, Weir KR, Dorsch MP. Investigating older adults' perceptions of AI tools for medication decisions: vignette-based experimental survey. J Med Internet Res. Dec 16, 2024;26:e60794. [FREE Full text] [CrossRef] [Medline]1], in the letter to the editor shared by Wang and Chen [Wang Q, Chen M. Enhancing the clinical relevance of Al research for medication decision-making. J Med Internet Res. 2025:e0. [CrossRef]2]. The letter emphasizes three key points: (1) older adults may encounter practical challenges with artificial intelligence tools, necessitating user testing and scenario simulations to enhance usability; (2) although our study considered demographic differences, it did not explore underlying cultural and socioeconomic factors, which calls for further research; (3) the complexity of real-world medication decision-making remains significant.

We acknowledge the limitations the correspondents highlight, particularly usability challenges for older adults and the need to examine underlying cultural and socioeconomic factors. Our vignette-based experiment served as an intentionally focused first step in understanding older adults’ interest in artificial intelligence–assisted medication decision support.

Wang and Chen [Wang Q, Chen M. Enhancing the clinical relevance of Al research for medication decision-making. J Med Internet Res. 2025:e0. [CrossRef]2] note that our previous work showed that medication decision-making is complex [Vordenberg SE, Weir KR, Jansen J, Todd A, Schoenborn N, Scherer AM. Harm and medication-type impact agreement with hypothetical deprescribing recommendations: a vignette-based experiment with older adults across four countries. J Gen Intern Med. May 2023;38(6):1439-1448. [FREE Full text] [CrossRef] [Medline]3]. Indeed, various factors influence how patients make these decisions, including their attitudes, beliefs, and preferences regarding medications; the potential benefits and harms of the treatment under consideration; and contextual factors specific to the patient [Weir K, Marshall V, Vordenberg S. Latent class analysis identifies four distinct patient deprescribing typologies among older adults in four countries. Innov Aging. Jan 17, 2025:igaf002. [CrossRef]4-Weir KR, Vordenberg SE, Scherer AM, Jansen J, Schoenborn N, Todd A. Exploring different contexts of statin deprescribing: a vignette-based experiment with older adults across four countries. J Gen Intern Med. Jul 2024;39(9):1773-1776. [FREE Full text] [CrossRef] [Medline]6]. Our study’s experimental approach using vignettes, as indicated in the title, was selected to begin exploring this complex area in a controlled manner.

We agree that this initial study lays the foundation for future research that can tackle these important considerations through enhanced scenarios, user testing, and a more in-depth examination of sociocultural factors.