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Natural Language Processing in Clinical Research Recruitment: A Scoping Review Enriched with Stakeholder Insights.

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|September 27, 2025
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Natural language processing (NLP) in clinical trial recruitment is emerging, but ethical considerations are underreported. More research and guidelines are needed for responsible implementation of these AI tools.

Keywords:
AI ethicsanonymizationartificial intelligence (AI)clinical researchconsentequitynatural language processing (NLP)patient autonomypatient recruitment

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Clinical Trial Management

Background:

  • Natural Language Processing (NLP) offers potential for optimizing clinical trial recruitment.
  • Ethical considerations surrounding AI in healthcare are increasingly important.
  • Current literature lacks comprehensive analysis of ethical aspects in NLP for clinical trials.

Purpose of the Study:

  • To characterize NLP applications in clinical trial recruitment.
  • To explore stakeholders' perspectives on NLP technologies in this domain.
  • To identify ethical considerations related to patient autonomy and equity.

Main Methods:

  • A scoping review of English-language articles (Jan 2021-June 2024) from Ovid Medline.
  • Extraction of data on NLP system characteristics, evaluations, and ethical issues.
  • Thematic analysis of semistructured interviews with multidisciplinary experts.

Main Results:

  • 47 articles were eligible, primarily focusing on NLP models for electronic health record screening.
  • Emphasis in literature was on model accuracy and efficiency, with limited attention to ethical concerns.
  • Interviews revealed a need for ethical reflection, implementation analysis, and differing views on anonymization and consent.

Conclusions:

  • NLP applications for clinical trial recruitment are nascent, with a notable gap between ethical discourse and published research.
  • There is a need for practical guidelines on ethical implementation and reporting throughout the NLP lifecycle.
  • Empirical research is required to assess the real-world ethical impact of NLP tools in clinical research.