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. 2025 May;73(5):1365-1375.
doi: 10.1111/jgs.19362. Epub 2025 Feb 5.

Around the EQUATOR With Clin-STAR: AI-Based Randomized Controlled Trial Challenges and Opportunities in Aging Research

Betsy Yang  1   2   3 , Caroline Park  1   2   4 , Steven Lin  3   5 , Vijaytha Muralidharan  6 , Deborah M Kado  1   2
Affiliations

Around the EQUATOR With Clin-STAR: AI-Based Randomized Controlled Trial Challenges and Opportunities in Aging Research

Betsy Yang et al. J Am Geriatr Soc. 2025 May.

Abstract

The CONSORT 2010 statement is a guideline that provides an evidence-based checklist of minimum reporting standards for randomized trials. With the rapid growth of Artificial Intelligence (AI) based interventions in the past 10 years, the CONSORT-AI extension was created in 2020 to provide guidelines for AI-based randomized controlled trials (RCT). The Clin-STAR "Around the EQUATOR" series features existing reported standards while also highlighting the inherent complexities of research involving research of older participants. In this work, we propose that when designing AI-based RCTs involving older adults, researchers adopt a conceptual framework (CONSORT-AI-5Ms) designed around the 5Ms (Mind, Mobility, Medications, Matters most, and Multi-complexity) of Age-Friendly Healthcare Systems. Employing the 5Ms in this context, we provide a detailed rationale and include specific examples of challenges and potential solutions to maximize the impact and value of AI RCTs in an older adult population. By combining the original intent of CONSORT-AI with the 5Ms framework, CONSORT-AI-5Ms provides a patient-centered and equitable perspective to consider when designing AI-based RCTs to address the diverse needs and challenges associated with geriatric care.

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Conflict of interest statement

Betsy Yang and Caroline Park are supported by the Palo Alto VA GRECC Advanced Fellowship. Betsy Yang is a paid Suki AI consultant. Deborah M. Kado is a federal employee, receives royalties from UpToDate for authorship, is a WndrHLTH consultant, and funded by: Starkey Laboratories incorporated grant, Stanford Wu Tsai Human Performance Alliance grant, and NIH fundings: R01AG065876, R01AR0811, ES032649, AG066671. All authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Considerations for AI‐based RCT design rooted on the Geriatric 5Ms. Conceptual framework depicting four broad categories of AI‐based technology applications, and to consider development of these applications being rooted on the Geriatric 5Ms. Examples of the various categories of AI‐based applications in research (represented in each leaf) are shown above, and with an overall aim of improving the lives of older adults, guided by the Age‐Friendly Health Systems Geriatric 5Ms. A. Clinical Decision Support Systems (CDSS): Prescription assistance and prediction modeling; B. Diagnostic support: AI‐assisted endoscopy for cancer detection and image enhancement, classification, or analysis; C. Software and large language models (LLMs): Software interventions, chatbots for patient clinical messaging, and AI‐based companions; D. Monitoring systems: Health‐wearable devices and environment‐smart home technologies.
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