Ethical requirements of instructions for authors of complementary and alternative medicine journals: a cross-sectional study.

BACKGROUND: Medical research in complementary and alternative medicine (CAM) has increased recently, raising ethical concerns about the moral status of CAM. Medical academic journals are responsible for conducting ethical review (ER) of manuscripts to protect the interests of human subjects and to make ethical results available before deciding to publish. However, there has been no systematic analysis of the ER in CAM journals. This study is aim to evaluate the current status of ethical requirements and compliance in CAM journals. METHODS: This is a cross-sectional study. We reviewed instructions for authors (IFAs) of CAM journals included in the Journal Citation Reports (2021) ( https://jcr.clarivate.com ) for general information and requirements for ER. We also browsed the manuscripts regarding randomized controlled trials published by CAM journals in Q1 and Q2 section from January to June, 2023, to check the actual situation of ethical requirement. Descriptive statistics and Fisher's exact test were used for statistical analysis. RESULTS: 27 journals and 68 manuscripts were ultimately included. 92.6% (25/27) IFAs included keywords of ER, indicating the presence of ethical considerations. However, no specific ER was required for CAM (n = 0). We categorized journals by Geographic origin, JCR section, Year of electronic JCR, Types of studies, % of OA Gold to explore the factors that could influence CAM journals to have certain ethical review policies. The results showed there was no statistical significance in certain ethical review policy in any classification of journals (p > 0.05). All RCT manuscripts included in the study generally met the requirements of the published journals for ethical review. CONCLUSIONS: All IFAs discussed ER, but the content was scattered, unfocused, and there were no specific ER requirements regarding CAM. Although the manuscripts basically met the requirements of the journal, it was not possible to get closer to the process of ER in the manuscript. To ensure full implementation of these policies in the future, CAM journals should require authors to provide more details, or to form a list of items necessary for CAM ethical review.

Coercion Authorship: Ubiquitous and Preventable.

Coercion authorship (CA), typically enforced by principal investigators, has detrimental effects on graduate students, young researchers, and the entire scientific endeavor. Although CA is ubiquitous, its occurrence and major determinants have been mainly explored among graduate students and junior scientists in Sweden, Norway, and Denmark where the ratio of CA ranged from 13 to 40%. In addition to lacking comparable figures, developing countries usually lack institutional plans for promoting integrity and effective deterrents against CA and other malpractices. Hence, universities and research centers therein must publish their authorship policies and implement specific strategies to instruct graduate students, junior scientists, and experienced researchers on integrity, publishing ethics, and responsible authorship. Finally, I remark that the primary responsibility of principal researchers to promote fair authorship practices and discourage unfair ones is even greater when it comes to CA due to the asymmetrical power relationship between senior authors and novice scientists.

Publication Ethics in the Era of Artificial Intelligence.

The application of new technologies, such as artificial intelligence (AI), to science affects the way and methodology in which research is conducted. While the responsible use of AI brings many innovations and benefits to science and humanity, its unethical use poses a serious threat to scientific integrity and literature. Even in the absence of malicious use, the Chatbot output itself, as a software application based on AI, carries the risk of containing biases, distortions, irrelevancies, misrepresentations and plagiarism. Therefore, the use of complex AI algorithms raises concerns about bias, transparency and accountability, requiring the development of new ethical rules to protect scientific integrity. Unfortunately, the development and writing of ethical codes cannot keep up with the pace of development and implementation of technology. The main purpose of this narrative review is to inform readers, authors, reviewers and editors about new approaches to publication ethics in the era of AI. It specifically focuses on tips on how to disclose the use of AI in your manuscript, how to avoid publishing entirely AI-generated text, and current standards for retraction.

Authorship and Citizen Science: Seven Heuristic Rules.

Citizen science (CS) is an umbrella term for research with a significant amount of contributions from volunteers. Those volunteers can occupy a hybrid role, being both 'researcher' and 'subject' at the same time. This has repercussions for questions about responsibility and credit, e.g. pertaining to the issue of authorship. In this paper, we first review some existing guidelines for authorship and their applicability to CS. Second, we assess the claim that the guidelines from the International Committee of Medical Journal Editors (ICMJE), known as 'the Vancouver guidelines', may lead to exclusion of deserving citizen scientists as authors. We maintain that the idea of including citizen scientists as authors is supported by at least two arguments: transparency and fairness. Third, we argue that it might be plausible to include groups as authors in CS. Fourth and finally, we offer a heuristic list of seven recommendations to be considered when deciding about whom to include as an author of a CS publication.

Large language models are changing landscape of academic publications. A positive transformation?

The advent of large language models (LLMs) based on neural networks marks a significant shift in academic writing, particularly in medical sciences. These models, including OpenAI's GPT-4, Google's Bard, and Anthropic's Claude, enable more efficient text processing through transformer architecture and attention mechanisms. LLMs can generate coherent texts that are indistinguishable from human-written content. In medicine, they can contribute to the automation of literature reviews, data extraction, and hypothesis formulation. However, ethical concerns arise regarding the quality and integrity of scientific publications and the risk of generating misleading content. This article provides an overview of how LLMs are changing medical writing, the ethical dilemmas they bring, and the possibilities for detecting AI-generated text. It concludes with a focus on the potential future of LLMs in academic publishing and their impact on the medical community.

Plagiarism in Non-Anglophone Countries: a Cross-sectional Survey of Researchers and Journal Editors.

BACKGROUND: Plagiarism is one of the most common violation of publication ethics, and it still remains an area with several misconceptions and uncertainties. METHODS: This online cross-sectional survey was conducted to analyze plagiarism perceptions among researchers and journal editors, particularly from non-Anglophone countries. RESULTS: Among 211 respondents (mean age 40 years; M:F, 0.85:1), 26 were scholarly journal editors and 70 were reviewers with a large representation from India (50, 24%), Turkey (28, 13%), Kazakhstan (25, 12%) and Ukraine (24, 11%). Rigid and outdated pre- and post-graduate education was considered as the origin of plagiarism by 63% of respondents. Paraphragiarism was the most commonly encountered type of plagiarism (145, 69%). Students (150, 71%), non-Anglophone researchers with poor English writing skills (117, 55%), and agents of commercial editing agencies (126, 60%) were thought to be prone to plagiarize. There was a significant disagreement on the legitimacy of text copying in scholarly articles, permitted plagiarism limit, and plagiarized text in methods section. More than half (165, 78%) recommended specifically designed courses for plagiarism detection and prevention, and 94.7% (200) thought that social media platforms may be deployed to educate and notify about plagiarism. CONCLUSION: Great variation exists in the understanding of plagiarism, potentially contributing to unethical publications and even retractions. Bridging the knowledge gap by arranging topical education and widely employing advanced anti-plagiarism software address this unmet need.