Recommendations for disclosure of artificial intelligence in scientific writing and publishing: a regional anesthesia and pain medicine modified Delphi study.

Journal: Regional anesthesia and pain medicine
Published Date: Jun 5, 2026

Abstract

INTRODUCTION: The use of artificial intelligence (AI) in the scientific process is advancing at a remarkable speed, thanks to continued innovations in large language models. While AI provides widespread benefits, including editing for fluency and clarity, it also has drawbacks, including fabricated content, perpetuation of bias, and lack of accountability. The editorial board of Regional Anesthesia & Pain Medicine (RAPM) therefore sought to develop best practices for AI usage and disclosure. METHODS: A steering committee from the American Society of Regional Anesthesia and Pain Medicine used a modified Delphi process to address definitions, disclosure requirements, authorship standards, and editorial oversight for AI use in publishing. The committee reviewed existing publication guidelines and identified areas of ambiguity, which were translated into questions and distributed to an expert workgroup of authors, reviewers, editors, and AI researchers. RESULTS: Two survey rounds, with 91% and 87% response rates, were followed by focused discussion and clarification to identify consensus recommendations. The workgroup achieved consensus on recommendations to authors about definitions of AI, required items to report, disclosure locations, authorship stipulations, and AI use during manuscript preparation. The workgroup formulated recommendations to reviewers about monitoring and evaluating the responsible use of AI in the review process, including the endorsement of AI-detection software, identification of concerns about undisclosed AI use, situations where AI use may necessitate the rejection of a manuscript, and use of checklists in the review process. Finally, there was consensus about AI-driven work, including required and optional disclosures and the use of checklists for AI-associated research. DISCUSSION: Our modified Delphi study identified practical recommendations on AI use during the scientific writing and editorial process. The workgroup highlighted the need for transparency, human accountability, protection of patient confidentiality, editorial oversight, and the need for iterative updates. The proposed framework enables authors and editors to harness AI's efficiencies while maintaining the fundamental principles of responsible scientific communication and may serve as an example for other journals.

Authors

  • Michael R Fettiplace
    Anesthesiology, University of Illinois Chicago, Chicago, Illinois, USA [email protected].
  • Anuj Bhatia
    Anesthesia and Pain Management, Toronto Western Hospital and University of Toronto, Toronto, Ontario, Canada.
  • Yian Chen
    1st Fujian Normal University School of Geographical Sciences, Fuzhou, China; 2nd Fujian Normal University Institute of Geography, Fuzhou, China. Electronic address: [email protected].
  • Steven L Orebaugh
    Anesthesiology, University of Pittsburgh Medical Center Health System, Pittsburgh, Pennsylvania, USA.
  • Michael Gofeld
    Anaesthesiology, Northern Ontario School of Medicine University, North York, Ontario, Canada.
  • Rodney A Gabriel
    Department of Medicine, Division of Biomedical Informatics, University of California, San Diego, La Jolla, CA, USA.
  • Daniel I Sessler
    Michael Cudahy Professor & Chair, Department of OUTCOMES RESEARCH, Anesthesiology Institute, Cleveland Clinic, Cleveland, Ohio, USA.
  • Hannah Lonsdale
  • Brittani Bungart
    Anesthesiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  • Christopher P Cheng
    Department of Otolaryngology-Head and Neck Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Garrett W Burnett
    Anesthesiology, Perioperative & Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Lichy Han
    Biomedical Informatics Training Program, Stanford University, Stanford, CA, USA.
  • Matthew Wiles
    Academic Anaesthesia, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, England, UK.
  • Steve Coppens
    Anesthesiology, University Hospitals of Leuven, Leuven, Belgium.
  • Thomas Joseph
    Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Kristin L Schreiber
    Anesthesiology, Perioperative, and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Thomas Volk
    CBR - Center of Breach Research(1), Department of Anaesthesiology, Intensive Care and Pain Therapy, Saarland University Medical Center and Saarland University Faculty of Medicine, 66421 Homburg, Saar, Germany.
  • Richard D Urman
  • Vesela P Kovacheva
    Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Christopher L Wu
    Pain Prevention Research Center, Department of Anesthesiology, Critical Care & Pain Management, Hospital for Special Surgery, New York, New York, USA.
  • Edward R Mariano
    Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA.
  • Vivian H Y Ip
    Anesthesia, Perioperative and Pain Medicine, University of Calgary, South Health Campus, Calgary, Alberta, Canada.

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