The scale of adoption surprised even the study team. Among thirty-nine surgeons and surgical trainees who completed a baseline survey before the workshop, 89.7 percent reported that they had already used AI tools such as ChatGPT or Copilot for scientific activities, with 35.9 percent using them occasionally, 35.9 percent frequently, and 17.9 percent systematically. Only 10.3 percent had never touched these tools. Language editing dominated at 74.4 percent, followed by manuscript structuring and literature summarization at 46.2 percent each, and data analysis or interpretation at 41 percent. More than 82 percent agreed or strongly agreed that AI improves scientific productivity, signaling that these tools are no longer experimental novelties but embedded instruments of daily academic work.

Yet the same survey revealed a striking asymmetry between enthusiasm and understanding. Before the workshop, 48.7 percent of respondents rated their knowledge of AI in scientific writing as basic, 35.9 percent as intermediate, 5.1 percent as advanced, and 10.3 percent reported none at all. Every single participant considered AI-generated errors or fabricated references at least possible, and 61.5 percent rated them as frequent or very frequent. Trust without verification was correspondingly low: 76.9 percent said they rarely or never trusted AI-generated scientific content without additional checking. Nearly 95 percent believed they needed more training in AI applied to scientific publishing, underscoring a widening educational gap between what surgeons do with these tools and what they know about them.

The workshop itself was deliberately compact. Over ninety minutes, two presentations addressed current applications of AI in scientific writing from the perspective of early-career surgeons, and the viewpoint of a scientific publisher and editorial process regarding AI use in manuscript preparation and peer review. Topics spanned technical limitations, hallucinations, fabricated references, bias, confidentiality, authorship, disclosure, peer-review implications, and the need for professional guidance. Clinical applications of AI in abdominal wall surgery were not the primary focus. Participants completed a ten-item baseline survey beforehand and a ten-item post-workshop survey immediately afterwards, using anonymous codes that allowed thirty-four responses to be matched across both time points.

The matched analysis produced the study’s most statistically robust finding. Using the Wilcoxon signed-rank test on the single ordinal knowledge item that was directly comparable between surveys, self-reported knowledge improved in 18 of 34 participants, or 52.9 percent, with a p-value of 0.0005. The median knowledge score rose from basic before the workshop to intermediate afterwards. Knowledge remained unchanged in 38.2 percent and was lower in 8.8 percent, a small subgroup the authors suggest may reflect differences in attendance, engagement, or a more critical reassessment of prior knowledge after the session. After the intervention, 68.3 percent of all post-workshop respondents rated their knowledge as intermediate or advanced, compared with roughly 41 percent at baseline.

Beyond raw knowledge scores, the workshop produced strong signals of intended responsible behavior. Ninety-two point seven percent of post-workshop respondents agreed or strongly agreed that they now better understood AI’s technical limitations, including hallucinations, bias, and fabricated references. Reference verification emerged as the single strongest post-workshop commitment: 97.6 percent said they would almost always or always verify references generated by AI, with 80.5 percent committing to always doing so. Support for disclosure of AI use in manuscripts reached 85.4 percent, with 70.7 percent specifically favoring clear regulation. And 87.8 percent considered specific guidelines from scientific societies to be recommended or essential, while 78 percent reported feeling moderately or highly prepared to use AI responsibly.

These attitudes align with a rapidly evolving policy landscape. The World Association of Medical Editors recommends that generative AI tools cannot be listed as authors because they cannot take responsibility for the work, and that their use should be disclosed when they assist with scholarly manuscripts. The Committee on Publication Ethics has issued similar guidance. The urgency is not theoretical: the JAMA Network has reported receiving manuscripts containing inaccurate or fabricated references and has updated its guidance to discourage the use of generative AI for generating or managing bibliographic references. Empirical studies have shown that large language models can produce references with low precision and high hallucination rates when prompted for systematic-review-type tasks, with error rates high enough to preclude unsupervised use for evidence synthesis.

Confidentiality emerged as another critical concern. At baseline, 89.7 percent of participants reported at least slight concern about uploading manuscripts or peer reviews to AI platforms, and 51.3 percent reported moderate or very high concern. This matters because peer-review materials are confidential and should not be uploaded to external AI systems unless explicitly permitted by journal policy. Reviews of AI in peer review describe potential efficiency gains in screening and quality control but emphasize risks to confidentiality, transparency, and the preservation of expert human judgment. The authors argue that these peer-review-specific issues deserve dedicated attention in future AI education for surgeons, many of whom serve as reviewers as well as authors.

The study also revealed the limits of a brief intervention. Only 41.5 percent of post-workshop respondents felt confident in identifying AI-related risks specific to abdominal wall surgery, with 51.2 percent answering only partially. The authors acknowledge that the workshop was designed to address responsible use in scientific publishing rather than clinical applications, and they suggest that case-based discussions covering hernia surgery, abdominal wall reconstruction, clinical prediction models, image analysis, and AI-assisted operative video assessment would be a natural next step. They also note several limitations: the sample was voluntary and modest, there was no control group, outcomes were self-reported and measured immediately, not all responses could be paired, and no demographic variables were collected, preventing subgroup analysis by career stage or editorial experience.

Despite these caveats, the study offers a practical model for integrating responsible AI training into surgical education at a moment when the technology is outpacing formal instruction. The authors conclude that scientific societies and journals are well positioned to lead this transition by producing specialty-specific guidance covering acceptable AI uses, required disclosure language, reference-verification workflows, confidentiality safeguards, authorship boundaries, peer-review restrictions, and minimum competencies for trainees. As surgeons become both users and producers of AI-related research, the gap between adoption and literacy will only widen unless deliberately addressed. Ninety minutes, this study suggests, is enough to start closing it.

Subject of Research: Impact of a brief AI education workshop on surgeons' knowledge and attitudes toward artificial intelligence in scientific publishing

Article Title: Impact of an AI workshop on knowledge and attitudes toward AI in scientific publishing among surgeons at an international abdominal wall surgery congress

Article References: Verdaguer-Tremolosa, M., Kotoreni, G., Hoggart, S., & López-Cano, M. (2026). Impact of an AI workshop on knowledge and attitudes toward AI in scientific publishing among surgeons at an international abdominal wall surgery congress. Journal of Abdominal Wall Surgery, 5, Article 17401. https://doi.org/10.3389/jaws.2026.17401

Image Credits: AI Generated

DOI: 10.3389/jaws.2026.17401

Keywords: artificial intelligence, generative AI, scientific publishing, surgical education, abdominal wall surgery, hernia surgery, peer review, research ethics, AI hallucinations, manuscript disclosure, medical education, European Hernia Society