Adequate and transparent reporting is necessary for critically appraising published research, yet ample evidence suggests that the design, conduct, analysis, interpretation, and reporting of oral health research could be greatly improved. Accordingly, the Task Force on Design and Analysis in Oral Health Research, statisticians and trialists from academia and industry, identified the minimum information needed to report and evaluate observational studies and clinical trials in oral health: the OHStat guidelines. Drafts were circulated to the editors of 85 oral health journals and to Task Force members and sponsors and discussed at a December 2020 workshop attended by 49 researchers. The guidelines were subsequently revised by the Task Force writing group. The guidelines draw heavily from the Consolidated Standards for Reporting Trials (CONSORT), Strengthening the Reporting of Observational Studies in Epidemiology, and CONSORT harms guidelines, and incorporate the SAMPL guidelines for reporting statistics, the CLIP principles for documenting images, and the GRADE indicating the quality of evidence. The guidelines also recommend reporting estimates in clinically meaningful units using confidence intervals, rather than relying on P values. In addition, OHStat introduces seven new guidelines that concern the text itself, such as checking the congruence between abstract and text, structuring the discussion, and listing conclusions to make them more specific. OHStat does not replace other reporting guidelines; it incorporates those most relevant to dental research into a single document. Manuscripts using the OHStat guidelines will provide more information specific to oral health research.

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Large language models (LLMs) are rapidly transforming medical writing and publishing. This review article focuses on experimental evidence to provide a comprehensive overview of the current applications, challenges, and future implications of LLMs in various stages of academic research and publishing process. Global surveys reveal a high prevalence of LLM usage in scientific writing, with both potential benefits and challenges associated with its adoption. LLMs have been successfully applied in literature search, research design, writing assistance, quality assessment, citation generation, and data analysis. LLMs have also been used in peer review and publication processes, including manuscript screening, generating review comments, and identifying potential biases. To ensure the integrity and quality of scholarly work in the era of LLM-assisted research, responsible artificial intelligence (AI) use is crucial. Researchers should prioritize verifying the accuracy and reliability of AI-generated content, maintain transparency in the use of LLMs, and develop collaborative human-AI workflows. Reviewers should focus on higher-order reviewing skills and be aware of the potential use of LLMs in manuscripts. Editorial offices should develop clear policies and guidelines on AI use and foster open dialogue within the academic community. Future directions include addressing the limitations and biases of current LLMs, exploring innovative applications, and continuously updating policies and practices in response to technological advancements. Collaborative efforts among stakeholders are necessary to harness the transformative potential of LLMs while maintaining the integrity of medical writing and publishing.

Writing is usually integrated in the curriculum of science studies. However, students often lack the skills to write for various audiences or, to produce a well written manuscript. We developed a concise project of 15 European Credits to improve the writing skills in an early phase of the bachelor study. Students worked on texts from various journals and looked at the writing styles. They rewrote texts in a popular and more scientific way and practiced with clear, vivid language, avoiding clutter and hedge words, considering a proper use of grammar and interpunction. Medical writing was also introduced during the project. Grading was based on rewriting for a non-expert and expert audience. A rewritten text was presented to the public in the form of a student-initiated survey. This project shows an inverted approach creating student ownership and enthusiasm for writing. In addition, we created and tested successfully a concise two-day workshop based on this project. Based on the results we herewith present the work as an idea to explore.

UNASSIGNED: Proficiency in medical writing and publishing is essential for medical researchers. Workshops can play a valuable role in addressing these issues. However, there is a lack of systematic summaries of evidence on the evaluation of their impacts. So, in this systematic review, we aimed to evaluate all articles published on the impact of such workshops worldwide.
UNASSIGNED: We searched Ovid EMBASE, Ovid Medline, ISI Web of Science, ERIC database, and grey literature with no language, time period, or geographical location limitations. Randomized controlled trials, cohort studies, before-after studies, surveys, and program evaluation and development studies were included. We performed a meta-analysis on data related to knowledge increase after the workshops and descriptively reported the evaluation of other articles that did not have sufficient data for a meta-analysis. All analyses were performed using Stata software, version 15.0.
UNASSIGNED: Of 23 040 reports, 222 articles underwent full-text review, leading to 45 articles reporting the impacts of workshops. Overall, the reports on the impact of such workshops were incomplete or lacked the necessary precision to draw acceptable conclusions. The workshops were sporadic, and researchers used their own method of assessment. Meta-analyses of the impact on the knowledge showed that workshops could nonsignificantly increase the mean or percentage of participants\' knowledge.
UNASSIGNED: In the absence of systematic academic courses on medical writing/publishing, workshops are conducted worldwide; however, reports on educational activities during such workshops, the methods of presentations, and their curricula are incomplete and vary. Their impact is not evaluated using standardized methods, and no valid and reliable measurement tools have been employed for these assessments.

The publication landscape for case reports has undergone a significant shift, with many high-impact journals deprioritizing or ceasing their publication altogether. This trend has led to the emergence of case-based reviews as an alternative to traditional case reports. Several factors drive this shift. Case-based reviews offer a more comprehensive synthesis of the literature compared to single case reports. They employ systematic search methodologies, reducing the risk of excluding relevant data, and providing robust evidence. From a publisher\'s perspective, case-based reviews have a greater potential for citation. While recommendations exist for writing traditional case reports, such as the CAse REports (CARE) guidelines, there is a lack of published recommendations for composing case-based reviews. This review aims to address this gap by providing guidance on drafting high-quality case-based reviews.

Proficiency in medical writing is crucial for disseminating reports of medical studies. The impact of workshops in this regard on participants\' confidence is a subject of debate. We assessed the impact of a hands-on workshop on participants\' confidence in medical writing. Participants of a 2-day \"learning-by-doing\" workshop held at McMaster University participated in this before-after study. We used a unique, reliable, and valid tool comprising two domains of confidence in medical writing and using English language before and after receiving the educational intervention. Of 25 participants, 21 completed the instrument before and after the workshop. Typical participants were female, and students in their 30s, who had not attended a prior workshop. The mean (95% CI) increase in the participants\' confidence for domain 1 was 15.3 (10.5, 20.1), for domain 2 was 16.8 (9.8, 23.8), and for the total score was 32.1 (20.9, 43.2) (all P<0.001). Between-subgroup analyses showed the score increase was significantly higher in participants with less than 5 years of experience in medical research. The workshop had a positive impact on enhancing participants\' confidence in writing skills, including using active verbs, crafting short sentences, summarizing main findings, and adhering to checklists like CONSORT. Hands-on medical writing workshops can boost participants\' confidence in writing medical articles and using optimal English language. Targeting junior researchers and graduate students could result in a better outcome. Emphasizing the writing areas where participants achieved higher score changes might yield better outcomes for such workshops.

The debate surrounding the integration of artificial intelligence (AI) into scientific writing has already attracted significant interest in medical and life sciences. While AI can undoubtedly expedite the process of manuscript creation and correction, it raises several criticisms. The crossover between AI and health sciences is relatively recent, but the use of AI tools among physicians and other scientists who work in the life sciences is growing very fast. Within this whirlwind, it is becoming essential to realize where we are heading and what the limits are, including an ethical perspective. Modern conversational AIs exhibit a context awareness that enables them to understand and remember any conversation beyond any predefined script. Even more impressively, they can learn and adapt as they engage with a growing volume of human language input. They all share neural networks as background mathematical models and differ from old chatbots for their use of a specific network architecture called transformer model [1]. Some of them exceed 100 terabytes (TB) (e.g., Bloom, LaMDA) or even 500 TB (e.g., Megatron-Turing NLG) of text data, the 4.0 version of ChatGPT (GPT-4) was trained with nearly 45 TB, but stays updated by the internet connection and may integrate with different plugins that enhance its functionality, making it multimodal.

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Background: When properly utilized, artificial intelligence generated content (AIGC) may improve virtually every aspect of research, from data gathering to synthesis. Nevertheless, when used inappropriately, the use of AIGC may lead to the dissemination of inaccurate information and introduce potential ethical concerns.Research Design: Cross-sectional. Study Sample: 65 top surgical journals. Data Collection: Each journals submission guidelines and portal was queried for guidelines regarding AIGC use.Results: We found that, in July 2023, 60% of the top 65 surgical journals had introduced guidelines for use, with more surgical journals (68%) introducing guidelines than surgical subspecialty journals (52.5%), including otolaryngology (40%). Furthermore, of the 39 with guidelines, only 69.2% gave specific use guidelines. No included journal, at the time of analysis, explicitly disallowed AIGC use.Conclusions: Altogether, this data suggests that while many journals have quickly reacted to AIGC usage, the quality of such guidelines is still variable. This should be pre-emptively addressed within academia.