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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Mar 2, 2026
Date Accepted: Jun 10, 2026
Date Submitted to PubMed: Jun 12, 2026

The final, peer-reviewed published version of this preprint can be found here:

Informed Consent Disclosures and Minimum Requirements in AI Clinical Trials: Cross-Sectional Analysis

Su H, Xiao F, Chau H, Tong Y, Han S, Cheng X, Che Z, Sun L, Yang Y, Zhao J, Li Y, Li H

Informed Consent Disclosures and Minimum Requirements in AI Clinical Trials: Cross-Sectional Analysis

J Med Internet Res 2026;28:e94504

DOI: 10.2196/94504

PMID: 42284020

Informed Consent in Artificial Intelligence Clinical Trials: A Cross-Sectional Analysis and Framework for Minimum Requirements

  • Hankun Su; 
  • Fen Xiao; 
  • Hoksan Chau; 
  • Yuqian Tong; 
  • Siyi Han; 
  • Xinyu Cheng; 
  • Zhilin Che; 
  • Liye Sun; 
  • Yuemeng Yang; 
  • Jing Zhao; 
  • Yanping Li; 
  • Hui Li

ABSTRACT

Background:

The integration of artificial intelligence (AI) into clinical research challenges traditional informed consent (IC) frameworks due to algorithmic complexity, opacity, and adaptive nature. While public demand for transparency regarding AI use in healthcare is high, current ethical guidelines lack specificity, and no global assessment exists regarding AI representation in IC documentation within clinical trial registries.

Objective:

This study aimed to evaluate the prevalence, clarity, and completeness of AI-related consent disclosures in clinical trials and propose a framework for enhanced patient digital literacy and ethical robustness.

Methods:

We conducted a cross-sectional content analysis of 114 AI-involved clinical trials with publicly available IC documents from ClinicalTrials.gov (searched June 21, 2025). We assessed AI-specific disclosures, readability (SMOG index), document length, and data governance protocols against international standards (WHO/NIH) and a refined AI risk framework encompassing model autonomy, departure from standards of care, patient-facing interaction, and clinical risk.

Results:

Analysis revealed that 55% of IC documents failed to disclose the AI type or usage, and 16.4% omitted risks entirely. Only 14% of documents met dual criteria for brevity (<15,000 characters) and readability (SMOG score <13). Higher-risk trials did not demonstrate improved readability. Data handling protocols post-withdrawal were inconsistent, with 51 ICs providing no information on the matter and only 3.5% offering participants choices regarding future data use.

Conclusions:

Current IC practices in AI clinical trials significantly disconnect from ethical principles, failing to ensure participant comprehension and autonomy. There is an urgent need for standardized, participant-centered consent practices. We propose the Minimum Requirements for Informed Consent in AI-Related Clinical Trials (MRIC-AI) to transform consent into a meaningful educational encounter aligned with evolving AI realities.


 Citation

Please cite as:

Su H, Xiao F, Chau H, Tong Y, Han S, Cheng X, Che Z, Sun L, Yang Y, Zhao J, Li Y, Li H

Informed Consent Disclosures and Minimum Requirements in AI Clinical Trials: Cross-Sectional Analysis

J Med Internet Res 2026;28:e94504

DOI: 10.2196/94504

PMID: 42284020

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