Perceptions and Utilization of Artificial Intelligence in Manuscript Writing: A Cross-Sectional Survey in Health Care Academics

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Alqarni, Maram Alagla, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5518955/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction Artificial intelligence (AI) transforms academic writing by providing tools that enhance efficiency, accuracy, and quality. Models such as ChatGPT are increasingly used for tasks such as grammar correction, structure refinement, and citation management. However, uncertainties and ethical concerns regarding the role of AI in manuscript writing remain. This study aims to assess AI's awareness, usage, and perceptions among academic professionals, focusing on its benefits and ethical implications. Methodology A cross-sectional survey was conducted among 100 academic professionals from India and Saudi Arabia, including lecturers, assistant professors, associate professors, and professors. The 15-question survey addressed demographic details, research experience, knowledge of AI, and views on its ethical use. Descriptive statistics were used to analyze the responses, with frequencies and percentages calculated for each item. Comparative analyses were performed via the Mann–Whitney U test and the Kruskal‒Wallis H test to assess differences in response based on gender, qualification, and years of experience. Results Among the 100 participants, 69% were aware of AI in manuscript writing, and 68% believed that it enhanced the quality and efficiency of their academic work. Most respondents (92%) supported formal AI training programs and guidelines for ethical AI use. However, 33% raised concerns about the moral implications of AI in academic writing. Among the 100 participants, 69% were aware of AI in manuscript writing, and 68% believed it enhanced the quality and efficiency of their academic work. Notably, 92% supported implementing formal AI training programs and guidelines for ethical use, while 33% expressed concerns about its moral implications. Significant differences were observed based on demographic factors such as qualifications and years of experience (p < 0.05). Most participants were aged 36–50 years (55%) and held a master’s degree (74%). Despite ethical concerns, the findings highlight the growing acceptance of AI in academic writing and emphasize the need for structured training and guidelines to facilitate its responsible adoption. Conclusion This study highlights the growing acceptance of AI in academic writing. Most professionals acknowledge its benefits for enhancing efficiency and quality. Academic professionals Artificial intelligence Ethical concerns Manuscript writing Perceptions Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Writing a manuscript is crucial for conducting research because it serves as a structured and comprehensive documentation of the entire research journey, from hypothesis formulation to the presentation of findings. It ensures that the research process, methods, and results are recorded clearly and reproducibly, enabling others to verify and build upon the work. Additionally, a manuscript communicates the significance of the research to the broader scientific community, facilitating peer review, collaboration, and the advancement of knowledge. By sharing findings in a manuscript, researchers contribute to the collective understanding of a field and foster innovation, which are essential elements of meaningful scientific inquiry. This represents a researcher's work in a standard, relevant, concise, rapid, effective, and scientific way [ 1 , 2 ]. Manuscripts promote worldwide idea interchange, scholarly recognition, and visibility within the academic community [ 3 ]. Artificial intelligence (AI) advancements provide new methods to preserve time, a valuable resource [ 4 ]. At the same time, AI language models have been around for a while. Their potential and use have become much more widely understood since OpenAI released ChatGPT in November 2022 [ 5 ]. NLP is a branch of computer science used by the generative pre-trained transformer (GPT) system to facilitate human-computer communication [ 6 ]. AI has become a valuable tool for academic writing. Writing assistants with AI capabilities support citations, grammar, structure, and disciplinary compliance [ 7 , 8 ]. These resources are crucial for improving the effectiveness and Caliber of academic writing and being helpful. They enable authors to focus on critical and original aspects of their studies [ 9 ]. Scientific writing increasingly uses artificial intelligence (AI) techniques like ChatGPT (OpenAI, San Francisco, CA). Whether you like it or not, you must acknowledge that many other people currently use ChatGPT to produce many manuscripts [ 10 ]. One should be able to ethically use this potent technology as a personal assistant to increase productivity and job quality rather than fighting it or wasting time criticizing it [ 11 ]. The development of algorithms and computer systems that can learn from and make predictions or judgments on real-world data is known as artificial intelligence (AI), and it mimics human thinking [ 12 ]. AI systems may also be trained to observe patterns in data, forecast outcomes, and gain experience. Thus, AI can perform tasks that often require human-level reasoning and decision-making [ 13 ]. Artificial intelligence, known as natural language processing, enables robots to comprehend, interpret, and produce human language like humans [ 14 ]. For example, OpenAI developed the ChatGPT (Generative Pretrained Transformer) language model to provide natural language answers to text searches. Furthermore, ChatGPT's central artificial intelligence engine has been trained on vast amounts of textual material from the internet, enabling it to pick up linguistic patterns and structures. It thus gains the ability to react effectively and cogently to various text signals [ 15 ]. It already impacts our everyday lives because of different offices and practice management software [ 16 ]. Applications that have developed intelligent conversational user interfaces for any device, application language, or environment using artificial intelligence include Siri, Alexa, and other voice command devices [ 17 ]. AI has been used in the medical field in virtual and real domains (such as robots). Mathematical formulae for pharmaceutical dosage, diagnosis and prognosis, appointment scheduling, medication interactions, electronic health records, and imaging are the critical areas of use for the virtual type [ 18 , 19 ]. Rehabilitation, telepresence, robotic assistance during surgery, and companion robots for senior care are examples of physical features [ 16 ]. The bulk of dental applications use supervised learning, in which many samples with various attributes (such as photos of the patient, sex, age, and number of cavities) and the determination of the ground truth (such as whether there was a previous endodontic visit) make up the training data [ 20 , 21 ]. Artificial intelligence can transform medicine and dentistry by providing solutions for various clinical issues and ease of work for medical professionals [ 22 ]. Applications of AI in dentistry are currently rare. However, robotics, dental imaging diagnostics, caries detection, radiography and pathology, and computerized recordkeeping have all been impacted by the development of these technologies [ 23 , 24 ]. This study evaluated the awareness, usage, and perceptions of artificial intelligence (AI) in manuscript writing among academic professionals. In today’s rapidly evolving educational landscape, AI tools such as ChatGPT are gaining traction for grammar correction, structural refinement, and citation management [ 25 ]. However, integrating AI into scholarly work raises significant questions about its role, ethical implications, and extent of its adoption [ 26 ]. By exploring the perspectives of academic professionals, this study aims to provide a comprehensive understanding of the current state of AI utilization in manuscript preparation. The critical research question guiding this study is: How do academic professionals perceive and utilize AI tools in manuscript writing, and what are their attitudes toward these technologies' ethical implications and potential benefits? Addressing this question will help fill a gap in understanding the acceptance, challenges, and ethical considerations surrounding AI integration in academic writing. Moreover, the findings provide insights into the broader implications of AI use in academia and the necessary steps for its future development and responsible adoption. Methodology Study Design: This study used a cross-sectional survey t o assess how academic professionals perceived and used artificial intelligence (AI) in article writing. A standardized questionnaire was used to conduct the survey and was given to a sample of participants from different academic institutions. The sample size for this study was determined to be 100 participants via G Power 3.1 software for linear multiple regression analysis. The calculation was based on a two-tailed test with an expected effect size (H1 ρ²) of 0.3, indicating a moderate relationship between the independent and dependent variables. The null hypothesis (H0 ρ²) assumes no effect (0), and the desired statistical power was set at 0.95, meaning that the study has a 95% chance of detecting an actual effect if one exists, minimizing the risk of false negatives. The model included three predictors, and the software computed that 100 participants would be necessary to ensure adequate power and reliable results. The output provided critical values for R², with a lower bound near zero and an upper bound of 0.19, along with a very low α error probability (0.00024), minimizing the risk of Type I errors (incorrectly rejecting the null hypothesis). This sample size ensures the study can detect meaningful relationships between the variables while maintaining statistical validity. Participants The study employed purposive sampling, selecting academic professionals actively engaged in research or teaching to meet the inclusion criteria. 100 Academic Professionals, including lecturers, assistant professors, associate professors, and professors, 50 in India and 50 in Saudi Arabia, responded to this study. To meet the inclusion requirements, participants must be actively engaged in research or teaching at higher education institutions. All the participants provided informed consent, and participation was entirely voluntary. The study ensured the anonymity and confidentiality of participant replies by not collecting any personally identifiable information. Data collection The questionnaire used in the study was Google Forms and was distributed to the participants through Twitter, WhatsApp, and some via email. A questionnaire was created to evaluate several facets of AI in manuscript authoring and was used to gather data. There were fifteen items in the questionnaire, including Likert-scale and multiple-choice questions. The questions focused on awareness, attitudes, the use of AI in manuscript writing, and demographic data (age, gender, qualification, and designation). The participants inquired about the regularity with which research papers were published, knowledge of AI tools, ethical issues, suggestions for training, and rules for using AI in scientific writing. There were two sections on the questionnaire: Survey Instrument Demographics and Research Experience: This section recorded the fundamental details of the participants, such as their age, gender, educational background, and publication history. The questionnaire was developed based on key variables relevant to the study objectives, including demographics and research experience. To ensure its validity, it underwent expert review for content and clarity, assessing its ability to capture the intended data accurately. A pilot study was conducted with a small sample of participants, enabling the refinement of questions for improved reliability and comprehensibility before final administration. This rigorous process ensured that the instrument was robust and suitable for the target population. Views of AI in Manuscript Writing This section asked participants about their knowledge of artificial intelligence (AI), their opinions on its advantages, their ethical concerns, and the areas in manuscript writing where AI may be employed. It also covered the participants' views on the necessity of AI usage guidelines and training. Data analysis The collected data were analyzed via SPSS software, version 26.0 (IBM Corp, Armonk, NY, USA). Descriptive statistics assess the acquired data once inputted into a spreadsheet. The frequency and percentage distribution of the responses were computed for every survey item. Microsoft Excel was used for data processing, and tables summarizing participant replies were created. Statistical analyses such as the Mann–Whitney U test and the Kruskal -Wallis H test were used to compare the mean scores of the domains concerning sex, qualification, and years of experience. In our study, missing data were handled by excluding incomplete responses to ensure the accuracy and consistency of the analysis. Outliers and unusual patterns were identified during initial data exploration using descriptive statistics and visual methods like boxplots. Any detected outliers were carefully assessed, and those deemed to significantly skew the results were excluded from the final analysis to maintain the reliability of the findings. Results The responses of 100 academic professionals from India and Saudi Arabia revealed the following key findings. The results are presented in tables and figures to provide a clear and comprehensive view of the findings. Demographic Overview: The preponderance of respondents with a master’s degree indicates a well-qualified group. Still, the small number with PhDs might suggest that the opinions on AI could be influenced by those with practical, rather than highly specialized, knowledge [Figure 1 – 2 and Table 1 ]. Table 1 Responses to Survey on the Use of Artificial Intelligence Question Response Count 1. Place of the participants India 50 Saudi Arabia 50 2. Age 36 to 50 years 55 Less than 35 years 26 More than 50 years 19 3. Gender Male 59 Female 41 4. Qualification Master 74 PhD 25 Bachelor 1 5. Designation Assistant professor 40 Professor 29 Lecturer 16 Associate professor 15 6. Published research article in indexed journal? Yes 86 No 14 7. Frequency of publishing research articles 1–3 per year 78 4–6 per year 8 More than 6 per year 5 8. Aware of AI usage in manuscript writing? Yes 69 No 31 9. Does AI benefit manuscript writing? Strongly Agree 19 Agree 49 No idea 15 Disagree 9 Strongly Disagree 8 10. Is AI used in manuscript writing exciting? Strongly Agree 13 Agree 57 No idea 19 Disagree 7 Strongly Disagree 4 11. Parts of manuscript where AI can be used All of the above 40 Searching the articles 7 Language editing 5 None of the above 5 12. Type of manuscript AI can be used in Review of literature 30 Original article, Review of literature, Meta-analysis, Case report 20 Original article 15 Review of literature, Meta-analysis 12 13. Recommend AI training Yes 92 No 8 14. Is it ethical to use AI in manuscript writing? Yes 67 No 33 15. Recommend guidelines for AI in scientific writing? Yes 92 No 8 Most participants (55%) were between 36 and 50 years old, 59% male and 41% female. The majority held a Master's degree (74%) and were assistant professors (40%) [Figure 3 ]. The high rate of publication among respondents (86%) and the predominant frequency of 1–3 articles per year indicate robust engagement with the research community [Figure 4 ]. This publication underscores the relevance of AI tools for individuals actively involved in producing scholarly work. The variation in publication frequency might reflect different career development stages or variations in research output [Figure 5 ]. A significant proportion (69%) of the respondents were aware of AI applications in manuscript writing. Of these, 68% believed AI benefited the writing process, and 70% expressed excitement about its potential. The enthusiasm for AI (70%) suggests that many view it as a promising tool for improving research workflows. This excitement could be attributed to AI’s potential to streamline repetitive tasks, such as literature searches and language editing. However, there is still a degree of hesitation or lack of comprehensive understanding [Figure 6 ]. The varied responses to AI applications indicate that while there is broad support for using AI throughout manuscript preparation, specific applications such as article searching and language editing are less emphasized. This could reflect a need for more awareness or clear guidance on how AI can effectively utilize these areas [Figure 7 ]. Ethical concerns are significant, with 33% of respondents questioning the ethical use of AI. This division highlights the need for clear ethical guidelines and discussions about the implications of AI in academic writing. The positive stance of 67% who view AI as ethical reflects a majority agreement but also highlights the need for ongoing dialogue about responsible AI use. Ethical Considerations: While 67% of the participants agreed that AI use in manuscript writing is ethical, 33% raised concerns, indicating a need for more precise guidelines. Training and Guidelines: Overingly, 92% of the respondents recommended formal training programs and policies for ethical AI use in academic writing, highlighting the demand for structured support. The data were analyzed via the Shapiro‒Wilk normality test and were not normally distributed. Hence, we used the nonparametric Mann‒Whitney U and Kruskal‒Wallis tests for statistical significance. The results in Table 2 from the Mann–Whitney U test and Kruskal‒Wallis H test reveal significant differences in perceptions of AI in manuscript writing based on gender and academic qualifications. In the Mann–Whitney U test, male respondents demonstrated a higher mean score for Awareness of AI in Manuscript (3.6) than females did (3.4), with a significant p-value of 0.045, and males also expressed more favourable views on ethical considerations (mean score 3.5 vs. 3.2, p = 0.019*). However, no significant differences were found in attitudes toward AI use (p = 0.230) or training needs (p = 0.112). In contrast, the Kruskal‒Wallis H test (Table 3 ) indicated that higher academic qualifications were correlated with greater awareness and more positive attitudes toward AI; PhD holders had the highest mean scores in all domains, notably in Awareness of AI (4.1, p = 0.002*) and Training Needs for AI in Writing (4.4, p = 0.012*). These findings suggest that gender and educational background significantly influence perceptions and attitudes toward AI, highlighting the need for targeted educational programs to increase AI literacy among academic professionals. Table 2 Mann–Whitney U test comparing mean scores based on sex Domain Mean Score (Male) Mean Score (Female) U Value p Value Awareness of AI in Manuscript 3.6 3.4 1158 0.045* Attitudes toward AI Use 4.0 3.9 1256 0.230 Ethical Considerations 3.5 3.2 980 0.019* Training Needs for AI in Writing 4.2 4.0 1320 0.112 Table 3 Kruskal‒Wallis H Test Comparing Mean Scores based on Qualification Domain Mean Score (Bachelor) Mean Score (Master) Mean Score (PhD) H-Value p Value Awareness of AI in Manuscript 3.2 3.7 4.1 12.5 0.002* Attitudes toward AI Use 3.9 4.0 4.3 7.6 0.023* Ethical Considerations 3.1 3.4 3.7 6.8 0.034* Training Needs for AI in Writing 4.0 4.1 4.4 8.9 0.012* Discussion Developing training programs for researchers is essential to ensure the effective use of AI tools, particularly in manuscript preparation. These programs should cover various topics, from optimizing literature searches to enhancing language and structural edits. Moreover, establishing ethical guidelines for AI usage is critical, focusing on authorship, transparency, and the proper utilization of AI-generated content. This would mitigate potential concerns about integrity in academic writing [ 29 , 30 ]. Further research into specific AI applications is crucial to identify which tools are most beneficial at different stages of the writing process, helping refine and optimize their use. Additionally, it is essential to engage with 17% of respondents who are uncertain or disagree with the benefits of AI. By addressing their skepticism, developers and institutions can gather insights into the obstacles hindering AI adoption and work on improving tools accordingly [ 31 – 33 ]. Finally, future studies should consider how gender and career experience influence attitudes toward AI in academic writing. Understanding these dimensions will allow for more inclusive and tailored strategies for integrating AI tools in research across diverse educational communities. Sotirios Bisdas et al. [ 34 ] conducted cross-sectional surveys to examine academic professionals’ use and perceptions of AI in manuscript writing. Both studies assess AI awareness, usage, and ethical concerns and emphasize the need for formal training and guidelines. Demographic data analysis and discussion of AI benefits and moral implications are central to both studies. They also highlight the necessity for further research to refine AI applications and address varied attitudes towards their integration. Nir Chemaya et al. [ 35 ] investigated the perceptions of academic professionals regarding the use of AI in manuscript writing, focusing on ethical considerations, reporting practices, and the overall role of AI in improving the writing process. This paper highlights a divide in opinions, particularly regarding the need to report AI usage for rewriting text. At the same time, our research reveals that 67% of respondents find AI use ethical, although a significant minority still raise concerns. Both papers agree that AI’s involvement in improving grammar or language does not necessarily alter the manuscript's content, suggesting that many academics see AI as a valuable tool for enhancing communication. Huang et al. [ 36 ] explored the role of AI in academic writing but with different emphases. They focus specifically on ChatGPT’s potential to increase the efficiency and quality of scientific review articles, highlighting its usefulness in outlining, detailing, and improving style. However, they caution against overreliance on AI, noting the risks of plagiarism and fabrication. They stress the need for careful and ethical use, where generated content is reviewed and edited to maintain integrity. This study provides new insights into the broader acceptance and potential concerns surrounding AI usage in academic manuscript writing, specifically in India and Saudi Arabia. It highlights AI's high awareness and perceived benefits in enhancing writing quality and efficiency, alongside the significant ethical concerns that still exist among academic professionals. The study also underscores the necessity of formal training and ethical guidelines for AI use, offering a comparative perspective on AI's application across different manuscript types beyond just review articles. This adds depth to the ongoing conversation about responsible AI integration, providing actionable recommendations for researchers, educators, and policymakers. On the other hand, our study provides a broader perspective by surveying 100 academic professionals from India and Saudi Arabia on AI usage in manuscript writing. While 69% are aware of AI applications and 68% believe that AI benefits writing, ethical concerns persist, with 33% questioning the ethical use of AI. The survey also emphasized the importance of formal training and guidelines, with 92% recommending structured support for ethical AI use. Both studies recognize AI's potential to improve academic writing. Still, while Huang et al. focused on ChatGPT’s role in review articles, our study examines AI’s broader applications across various manuscript types—both advocate for responsible AI integration, stressing the importance of ethical guidelines and training. Majovský et al. [ 15 ] highlighted the potential dangers of AI in creating fraudulent but authentic-looking scientific articles. They argue that AI tools, while capable of generating convincing content, raise significant concerns about the integrity of scientific research, particularly in terms of references and factual accuracy. This study underscores the need for expert review to identify inaccuracies and emphasizes the importance of vigilance and improved detection methods to prevent AI misuse in academic publications. The study had several limitations that may affect the generalizability and depth of the findings. First, the sample size was limited to 100 participants, which may not fully represent the diverse perspectives of academic professionals globally. A larger sample would provide more comprehensive insights. Second, the geographic scope was restricted to India and Saudi Arabia, potentially limiting the applicability of the results to other regions with different academic practices and AI adoption rates. Additionally, the study relied on self-reported data, which could introduce bias, as participants might have misjudged their knowledge and use of AI tools. While covering various aspects of AI usage, the survey questions may have yet to thoroughly explore specific applications or barriers to adoption. Finally, the cross-sectional design provides a snapshot of current attitudes. Still, it does not account for how perceptions and the use of AI may evolve as AI technology advances. Longitudinal studies would be better suited to track these changes. Conclusion This study highlights the growing awareness and acceptance of artificial intelligence (AI) in manuscript writing among academic professionals in India and Saudi Arabia. With 69% of the participants familiar with AI tools and a majority expressing positive views on its potential benefits, the findings suggest that AI is increasingly viewed as a valuable resource for enhancing the quality and efficiency of academic work. However, ethical concerns remain a significant issue, as evidenced by the 33% of respondents questioning the ethical implications of AI use in this context. The overwhelming support for formal AI training programs and the establishment of ethical guidelines underscore the need for structured approaches to integrate AI into academic workflows responsibly. To further the adoption of AI, addressing these ethical concerns through clear, transparent guidelines and training programs emphasizing responsible AI use, authorship, and accountability is crucial. Moreover, future research should focus on understanding the factors influencing differing attitudes toward AI, including career stage, gender, and field of expertise, to develop more tailored and inclusive approaches to AI integration. By continuing to explore the practical applications of AI in manuscript writing and addressing the remaining concerns, academia can fully leverage the potential of AI to improve research outputs while maintaining the integrity of scholarly communication. Declarations Acknowledgment The authors would like to acknowledge Prince Sattam bin Abdulaziz University's support in funding the study via project number (PSAU/2024/R/1446). Conflict of Interest None Author contributions Rajashekhara B. Sharanesha, Adel S. Alqarni contributions to the conception and design of the work, Maram Alagla, Abdulhamid Al Ghwainem data acquisition, and analysis, AlWaleed Abushanan, Abdulfatah Alazmah interpretation of data, SN Asiri, Deepti Virupakshappa, Sara Alghamdi and Narendra Varma Penumatsa drafted the work or substantively revised it. Funding The authors would like to acknowledge Prince Sattam bin Abdulaziz University for supporting the study via project number (PSAU/2024/R/1446). Data availability: The details of the data and the study materials will be available from the corresponding author upon reasonable request. The questionnaire and the consent form are available in the supplement files. Ethical Consideration: The study adhered to ethical research standards (Declaration of Helsinki). Informed consent was obtained from all participants, and they were informed that their participation was voluntary and that they could withdraw from the study at any time without any consequences. No personal identifiers were collected, ensuring anonymity and confidentiality. The study was reviewed and approved by the Standing Committee of Bioethics Research of Prince Sattam bin Abdulaziz University (SCBR-241/2024)) of the hosting institution before the survey was conducted. Consent for publication Not applicable References Aldakhil S, Alkhurayji K, Albarrak S, et al. Awareness and Approaches Regarding Artificial Intelligence in Dentistry: A Scoping Review. Cureus . 2024;16(1):e51825. Published 2024 Jan 7. doi:10.7759/cureus.51825. Ginting, P., Batubara, H. M., & Hasnah, Y. (2023). 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Huang, Jingshan and Ming Tan. “The role of ChatGPT in scientific communication: writing better scientific review articles.” American journal of cancer research vol. 13,4 1148-1154. 15 Apr. 2023 Additional Declarations No competing interests reported. Supplementary Files AIQuestionaire.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5518955","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":435869080,"identity":"aa2b5c8c-18ce-4d9f-8cb8-39666bebcf86","order_by":0,"name":"Rajashekhara Bhari Sharanesha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYFACHjYgISEH5TETr8WYZC0MiQ1EazFv4D324Ocei/Tt/IefSTBUWCc28B9+gFeLzAG+dMOeZxK5O2ekmUkwnElPbJBIM8CrRYKBx0yC54BE7oYbDGYSjG2HgVoYCGuR/HNAIt3g/PFvEoz/gFr4j38gqEUaaEuCwYEcoC0NQC0MOQRsYeZLk5Y5IGG4c0ZOsUXCsXTjNomcAvxa2HuPSb45UCdvzn98440PNday/fzHN+DVAo8IsGMSgJgNv3okgN/9o2AUjIJRMKIBABVTPQWhGZscAAAAAElFTkSuQmCC","orcid":"","institution":"Prince Sattam Bin Abdulaziz University","correspondingAuthor":true,"prefix":"","firstName":"Rajashekhara","middleName":"Bhari","lastName":"Sharanesha","suffix":""},{"id":435869081,"identity":"2b9dc6a3-c721-41da-bfe9-f4d217b95615","order_by":1,"name":"Adel S. 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2","display":"","copyAsset":false,"role":"figure","size":41186,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eQualification Background of the Participants\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5518955/v1/d8515a40bbd7870c87db93dd.png"},{"id":79680904,"identity":"f2fd4848-d296-4614-bc3a-da76d99edef4","added_by":"auto","created_at":"2025-04-01 12:51:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56546,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDesignation of the participants.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5518955/v1/9ae4557da842748724b0b506.png"},{"id":79678333,"identity":"4d66fc17-6d04-4e54-87d0-2236c2674602","added_by":"auto","created_at":"2025-04-01 12:27:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":47354,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePublication Activity of the Participants\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5518955/v1/7f9f0af38ce658c82f4180b2.png"},{"id":79678335,"identity":"4363f232-ddb1-43cb-847e-68dcac31ce32","added_by":"auto","created_at":"2025-04-01 12:27:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":110968,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFrequency of Publishing Research Articles\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-5518955/v1/cba17e07c10e17951cd3aa5f.png"},{"id":79679384,"identity":"46f4214a-d2b8-4ed6-a3c2-e8e9d81b75d4","added_by":"auto","created_at":"2025-04-01 12:35:54","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":73279,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTypes of manuscripts in which AI can be used.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-5518955/v1/17110a9244bbf3bccd85a6e2.png"},{"id":79679383,"identity":"8dccf6dc-c0e6-4234-837b-b0698b7534f2","added_by":"auto","created_at":"2025-04-01 12:35:54","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":118893,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVaried responses to AI applications\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-5518955/v1/6e874d4612273d677cd23270.png"},{"id":89794311,"identity":"40ed231b-7d98-4851-b6a0-c14363d26d24","added_by":"auto","created_at":"2025-08-25 06:47:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2082741,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5518955/v1/38e4e4a2-79e3-48c4-b5ff-f5df7e3b3d84.pdf"},{"id":79680905,"identity":"b6adfdd4-123e-46f8-b6c1-b79184d9048a","added_by":"auto","created_at":"2025-04-01 12:51:54","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":45923,"visible":true,"origin":"","legend":"","description":"","filename":"AIQuestionaire.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5518955/v1/306304145ea3c527d8a6159e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Perceptions and Utilization of Artificial Intelligence in Manuscript Writing: A Cross-Sectional Survey in Health Care Academics","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWriting a manuscript is crucial for conducting research because it serves as a structured and comprehensive documentation of the entire research journey, from hypothesis formulation to the presentation of findings. It ensures that the research process, methods, and results are recorded clearly and reproducibly, enabling others to verify and build upon the work. Additionally, a manuscript communicates the significance of the research to the broader scientific community, facilitating peer review, collaboration, and the advancement of knowledge. By sharing findings in a manuscript, researchers contribute to the collective understanding of a field and foster innovation, which are essential elements of meaningful scientific inquiry.\u003c/p\u003e \u003cp\u003eThis represents a researcher's work in a standard, relevant, concise, rapid, effective, and scientific way [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Manuscripts promote worldwide idea interchange, scholarly recognition, and visibility within the academic community [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Artificial intelligence (AI) advancements provide new methods to preserve time, a valuable resource [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. At the same time, AI language models have been around for a while. Their potential and use have become much more widely understood since OpenAI released ChatGPT in November 2022 [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. NLP is a branch of computer science used by the generative pre-trained transformer (GPT) system to facilitate human-computer communication [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. AI has become a valuable tool for academic writing. Writing assistants with AI capabilities support citations, grammar, structure, and disciplinary compliance [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These resources are crucial for improving the effectiveness and Caliber of academic writing and being helpful. They enable authors to focus on critical and original aspects of their studies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Scientific writing increasingly uses artificial intelligence (AI) techniques like ChatGPT (OpenAI, San Francisco, CA). Whether you like it or not, you must acknowledge that many other people currently use ChatGPT to produce many manuscripts [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. One should be able to ethically use this potent technology as a personal assistant to increase productivity and job quality rather than fighting it or wasting time criticizing it [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The development of algorithms and computer systems that can learn from and make predictions or judgments on real-world data is known as artificial intelligence (AI), and it mimics human thinking [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. AI systems may also be trained to observe patterns in data, forecast outcomes, and gain experience.\u003c/p\u003e \u003cp\u003eThus, AI can perform tasks that often require human-level reasoning and decision-making [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Artificial intelligence, known as natural language processing, enables robots to comprehend, interpret, and produce human language like humans [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. For example, OpenAI developed the ChatGPT (Generative Pretrained Transformer) language model to provide natural language answers to text searches. Furthermore, ChatGPT's central artificial intelligence engine has been trained on vast amounts of textual material from the internet, enabling it to pick up linguistic patterns and structures. It thus gains the ability to react effectively and cogently to various text signals [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. It already impacts our everyday lives because of different offices and practice management software [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Applications that have developed intelligent conversational user interfaces for any device, application language, or environment using artificial intelligence include Siri, Alexa, and other voice command devices [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. AI has been used in the medical field in virtual and real domains (such as robots). Mathematical formulae for pharmaceutical dosage, diagnosis and prognosis, appointment scheduling, medication interactions, electronic health records, and imaging are the critical areas of use for the virtual type [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Rehabilitation, telepresence, robotic assistance during surgery, and companion robots for senior care are examples of physical features [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The bulk of dental applications use supervised learning, in which many samples with various attributes (such as photos of the patient, sex, age, and number of cavities) and the determination of the ground truth (such as whether there was a previous endodontic visit) make up the training data [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Artificial intelligence can transform medicine and dentistry by providing solutions for various clinical issues and ease of work for medical professionals [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Applications of AI in dentistry are currently rare. However, robotics, dental imaging diagnostics, caries detection, radiography and pathology, and computerized recordkeeping have all been impacted by the development of these technologies [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study evaluated the awareness, usage, and perceptions of artificial intelligence (AI) in manuscript writing among academic professionals. In today\u0026rsquo;s rapidly evolving educational landscape, AI tools such as ChatGPT are gaining traction for grammar correction, structural refinement, and citation management [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, integrating AI into scholarly work raises significant questions about its role, ethical implications, and extent of its adoption [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. By exploring the perspectives of academic professionals, this study aims to provide a comprehensive understanding of the current state of AI utilization in manuscript preparation.\u003c/p\u003e \u003cp\u003eThe critical research question guiding this study is: How do academic professionals perceive and utilize AI tools in manuscript writing, and what are their attitudes toward these technologies' ethical implications and potential benefits? Addressing this question will help fill a gap in understanding the acceptance, challenges, and ethical considerations surrounding AI integration in academic writing. Moreover, the findings provide insights into the broader implications of AI use in academia and the necessary steps for its future development and responsible adoption.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003e\u003cb\u003eStudy Design: This study used a cross-sectional survey t\u003c/b\u003eo assess how academic professionals perceived and used artificial intelligence (AI) in article writing. A standardized questionnaire was used to conduct the survey and was given to a sample of participants from different academic institutions. The sample size for this study was determined to be 100 participants via G Power 3.1 software for linear multiple regression analysis. The calculation was based on a two-tailed test with an expected effect size (H1 ρ\u0026sup2;) of 0.3, indicating a moderate relationship between the independent and dependent variables. The null hypothesis (H0 ρ\u0026sup2;) assumes no effect (0), and the desired statistical power was set at 0.95, meaning that the study has a 95% chance of detecting an actual effect if one exists, minimizing the risk of false negatives. The model included three predictors, and the software computed that 100 participants would be necessary to ensure adequate power and reliable results. The output provided critical values for R\u0026sup2;, with a lower bound near zero and an upper bound of 0.19, along with a very low α error probability (0.00024), minimizing the risk of Type I errors (incorrectly rejecting the null hypothesis). This sample size ensures the study can detect meaningful relationships between the variables while maintaining statistical validity.\u003c/p\u003e \u003cp\u003e \u003cb\u003eParticipants\u003c/b\u003e The study employed purposive sampling, selecting academic professionals actively engaged in research or teaching to meet the inclusion criteria.\u003c/p\u003e \u003cp\u003e100 Academic Professionals, including lecturers, assistant professors, associate professors, and professors, 50 in India and 50 in Saudi Arabia, responded to this study. To meet the inclusion requirements, participants must be actively engaged in research or teaching at higher education institutions. All the participants provided informed consent, and participation was entirely voluntary. The study ensured the anonymity and confidentiality of participant replies by not collecting any personally identifiable information.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData collection\u003c/strong\u003e \u003cp\u003eThe questionnaire used in the study was Google Forms and was distributed to the participants through Twitter, WhatsApp, and some via email. A questionnaire was created to evaluate several facets of AI in manuscript authoring and was used to gather data. There were fifteen items in the questionnaire, including Likert-scale and multiple-choice questions. The questions focused on awareness, attitudes, the use of AI in manuscript writing, and demographic data (age, gender, qualification, and designation). The participants inquired about the regularity with which research papers were published, knowledge of AI tools, ethical issues, suggestions for training, and rules for using AI in scientific writing.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThere were two sections on the questionnaire:\u003c/p\u003e \u003cp\u003e \u003cb\u003eSurvey Instrument\u003c/b\u003e Demographics and Research Experience: This section recorded the fundamental details of the participants, such as their age, gender, educational background, and publication history. The questionnaire was developed based on key variables relevant to the study objectives, including demographics and research experience. To ensure its validity, it underwent expert review for content and clarity, assessing its ability to capture the intended data accurately. A pilot study was conducted with a small sample of participants, enabling the refinement of questions for improved reliability and comprehensibility before final administration. This rigorous process ensured that the instrument was robust and suitable for the target population.\u003c/p\u003e \u003cp\u003e\u003cb\u003eViews of AI in Manuscript Writing\u003c/b\u003e This section asked participants about their knowledge of artificial intelligence (AI), their opinions on its advantages, their ethical concerns, and the areas in manuscript writing where AI may be employed. It also covered the participants' views on the necessity of AI usage guidelines and training.\u003c/p\u003e \u003cp\u003e\u003cb\u003eData analysis\u003c/b\u003e The collected data were analyzed via SPSS software, version 26.0 (IBM Corp, Armonk, NY, USA). Descriptive statistics assess the acquired data once inputted into a spreadsheet. The frequency and percentage distribution of the responses were computed for every survey item. Microsoft Excel was used for data processing, and tables summarizing participant replies were created. Statistical analyses such as the Mann\u0026ndash;Whitney U test and the Kruskal -Wallis H test were used to compare the mean scores of the domains concerning sex, qualification, and years of experience. In our study, missing data were handled by excluding incomplete responses to ensure the accuracy and consistency of the analysis. Outliers and unusual patterns were identified during initial data exploration using descriptive statistics and visual methods like boxplots. Any detected outliers were carefully assessed, and those deemed to significantly skew the results were excluded from the final analysis to maintain the reliability of the findings.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe responses of 100 academic professionals from India and Saudi Arabia revealed the following key findings. The results are presented in tables and figures to provide a clear and comprehensive view of the findings.\u003c/p\u003e\n\u003ch3\u003eDemographic Overview:\u003c/h3\u003e\n\u003cp\u003eThe preponderance of respondents with a master\u0026rsquo;s degree indicates a well-qualified group. Still, the small number with PhDs might suggest that the opinions on AI could be influenced by those with practical, rather than highly specialized, knowledge [Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResponses to Survey on the Use of Artificial Intelligence\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuestion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResponse\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1. Place of the participants\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaudi Arabia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2. Age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 to 50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 35 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore than 50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3. Gender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4. Qualification\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaster\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBachelor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5. Designation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssistant professor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProfessor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLecturer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssociate professor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6. Published research article in indexed journal?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7. Frequency of publishing research articles\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;3 per year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026ndash;6 per year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore than 6 per year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e8. Aware of AI usage in manuscript writing?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e9. Does AI benefit manuscript writing?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrongly Agree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo idea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDisagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrongly Disagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e10. Is AI used in manuscript writing exciting?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrongly Agree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo idea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDisagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrongly Disagree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e11. Parts of manuscript where AI can be used\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll of the above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSearching the articles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLanguage editing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone of the above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e12. Type of manuscript AI can be used in\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReview of literature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOriginal article, Review of literature, Meta-analysis, Case report\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOriginal article\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReview of literature, Meta-analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e13. Recommend AI training\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e14. Is it ethical to use AI in manuscript writing?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e15. Recommend guidelines for AI in scientific writing?\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMost participants (55%) were between 36 and 50 years old, 59% male and 41% female. The majority held a Master's degree (74%) and were assistant professors (40%) [Figure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe high rate of publication among respondents (86%) and the predominant frequency of 1\u0026ndash;3 articles per year indicate robust engagement with the research community [Figure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis publication underscores the relevance of AI tools for individuals actively involved in producing scholarly work. The variation in publication frequency might reflect different career development stages or variations in research output [Figure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA significant proportion (69%) of the respondents were aware of AI applications in manuscript writing. Of these, 68% believed AI benefited the writing process, and 70% expressed excitement about its potential.\u003c/p\u003e \u003cp\u003eThe enthusiasm for AI (70%) suggests that many view it as a promising tool for improving research workflows. This excitement could be attributed to AI\u0026rsquo;s potential to streamline repetitive tasks, such as literature searches and language editing. However, there is still a degree of hesitation or lack of comprehensive understanding [Figure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe varied responses to AI applications indicate that while there is broad support for using AI throughout manuscript preparation, specific applications such as article searching and language editing are less emphasized. This could reflect a need for more awareness or clear guidance on how AI can effectively utilize these areas [Figure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eEthical concerns are significant, with 33% of respondents questioning the ethical use of AI. This division highlights the need for clear ethical guidelines and discussions about the implications of AI in academic writing. The positive stance of 67% who view AI as ethical reflects a majority agreement but also highlights the need for ongoing dialogue about responsible AI use.\u003c/p\u003e \u003cp\u003e Ethical Considerations: While 67% of the participants agreed that AI use in manuscript writing is ethical, 33% raised concerns, indicating a need for more precise guidelines. Training and Guidelines: Overingly, 92% of the respondents recommended formal training programs and policies for ethical AI use in academic writing, highlighting the demand for structured support.\u003c/p\u003e \u003cp\u003eThe data were analyzed via the Shapiro‒Wilk normality test and were not normally distributed. Hence, we used the nonparametric Mann‒Whitney U and Kruskal‒Wallis tests for statistical significance. The results in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e from the Mann\u0026ndash;Whitney U test and Kruskal‒Wallis H test reveal significant differences in perceptions of AI in manuscript writing based on gender and academic qualifications. In the Mann\u0026ndash;Whitney U test, male respondents demonstrated a higher mean score for Awareness of AI in Manuscript (3.6) than females did (3.4), with a significant p-value of 0.045, and males also expressed more favourable views on ethical considerations (mean score 3.5 vs. 3.2, p\u0026thinsp;=\u0026thinsp;0.019*). However, no significant differences were found in attitudes toward AI use (p\u0026thinsp;=\u0026thinsp;0.230) or training needs (p\u0026thinsp;=\u0026thinsp;0.112). In contrast, the Kruskal‒Wallis H test (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) indicated that higher academic qualifications were correlated with greater awareness and more positive attitudes toward AI; PhD holders had the highest mean scores in all domains, notably in Awareness of AI (4.1, p\u0026thinsp;=\u0026thinsp;0.002*) and Training Needs for AI in Writing (4.4, p\u0026thinsp;=\u0026thinsp;0.012*). These findings suggest that gender and educational background significantly influence perceptions and attitudes toward AI, highlighting the need for targeted educational programs to increase AI literacy among academic professionals.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMann\u0026ndash;Whitney U test comparing mean scores based on sex\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean Score (Male)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean Score (Female)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eU Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAwareness of AI in Manuscript\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.045*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAttitudes toward AI Use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.230\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthical Considerations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.019*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTraining Needs for AI in Writing\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKruskal‒Wallis H Test Comparing Mean Scores based on Qualification\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDomain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean Score (Bachelor)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean Score (Master)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean Score (PhD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eH-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAwareness of AI in Manuscript\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAttitudes toward AI Use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.023*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthical Considerations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.034*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTraining Needs for AI in Writing\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDeveloping training programs for researchers is essential to ensure the effective use of AI tools, particularly in manuscript preparation. These programs should cover various topics, from optimizing literature searches to enhancing language and structural edits. Moreover, establishing ethical guidelines for AI usage is critical, focusing on authorship, transparency, and the proper utilization of AI-generated content. This would mitigate potential concerns about integrity in academic writing [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurther research into specific AI applications is crucial to identify which tools are most beneficial at different stages of the writing process, helping refine and optimize their use. Additionally, it is essential to engage with 17% of respondents who are uncertain or disagree with the benefits of AI. By addressing their skepticism, developers and institutions can gather insights into the obstacles hindering AI adoption and work on improving tools accordingly [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFinally, future studies should consider how gender and career experience influence attitudes toward AI in academic writing. Understanding these dimensions will allow for more inclusive and tailored strategies for integrating AI tools in research across diverse educational communities.\u003c/p\u003e \u003cp\u003eSotirios Bisdas et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] conducted cross-sectional surveys to examine academic professionals\u0026rsquo; use and perceptions of AI in manuscript writing. Both studies assess AI awareness, usage, and ethical concerns and emphasize the need for formal training and guidelines. Demographic data analysis and discussion of AI benefits and moral implications are central to both studies. They also highlight the necessity for further research to refine AI applications and address varied attitudes towards their integration.\u003c/p\u003e \u003cp\u003eNir Chemaya et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] investigated the perceptions of academic professionals regarding the use of AI in manuscript writing, focusing on ethical considerations, reporting practices, and the overall role of AI in improving the writing process. This paper highlights a divide in opinions, particularly regarding the need to report AI usage for rewriting text. At the same time, our research reveals that 67% of respondents find AI use ethical, although a significant minority still raise concerns. Both papers agree that AI\u0026rsquo;s involvement in improving grammar or language does not necessarily alter the manuscript's content, suggesting that many academics see AI as a valuable tool for enhancing communication.\u003c/p\u003e \u003cp\u003eHuang et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] explored the role of AI in academic writing but with different emphases. They focus specifically on ChatGPT\u0026rsquo;s potential to increase the efficiency and quality of scientific review articles, highlighting its usefulness in outlining, detailing, and improving style. However, they caution against overreliance on AI, noting the risks of plagiarism and fabrication. They stress the need for careful and ethical use, where generated content is reviewed and edited to maintain integrity.\u003c/p\u003e \u003cp\u003eThis study provides new insights into the broader acceptance and potential concerns surrounding AI usage in academic manuscript writing, specifically in India and Saudi Arabia. It highlights AI's high awareness and perceived benefits in enhancing writing quality and efficiency, alongside the significant ethical concerns that still exist among academic professionals. The study also underscores the necessity of formal training and ethical guidelines for AI use, offering a comparative perspective on AI's application across different manuscript types beyond just review articles. This adds depth to the ongoing conversation about responsible AI integration, providing actionable recommendations for researchers, educators, and policymakers.\u003c/p\u003e \u003cp\u003eOn the other hand, our study provides a broader perspective by surveying 100 academic professionals from India and Saudi Arabia on AI usage in manuscript writing. While 69% are aware of AI applications and 68% believe that AI benefits writing, ethical concerns persist, with 33% questioning the ethical use of AI. The survey also emphasized the importance of formal training and guidelines, with 92% recommending structured support for ethical AI use. Both studies recognize AI's potential to improve academic writing. Still, while Huang et al. focused on ChatGPT\u0026rsquo;s role in review articles, our study examines AI\u0026rsquo;s broader applications across various manuscript types\u0026mdash;both advocate for responsible AI integration, stressing the importance of ethical guidelines and training.\u003c/p\u003e \u003cp\u003eMajovsk\u0026yacute; et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] highlighted the potential dangers of AI in creating fraudulent but authentic-looking scientific articles. They argue that AI tools, while capable of generating convincing content, raise significant concerns about the integrity of scientific research, particularly in terms of references and factual accuracy. This study underscores the need for expert review to identify inaccuracies and emphasizes the importance of vigilance and improved detection methods to prevent AI misuse in academic publications.\u003c/p\u003e \u003cp\u003eThe study had several limitations that may affect the generalizability and depth of the findings. First, the sample size was limited to 100 participants, which may not fully represent the diverse perspectives of academic professionals globally. A larger sample would provide more comprehensive insights. Second, the geographic scope was restricted to India and Saudi Arabia, potentially limiting the applicability of the results to other regions with different academic practices and AI adoption rates.\u003c/p\u003e \u003cp\u003eAdditionally, the study relied on self-reported data, which could introduce bias, as participants might have misjudged their knowledge and use of AI tools. While covering various aspects of AI usage, the survey questions may have yet to thoroughly explore specific applications or barriers to adoption. Finally, the cross-sectional design provides a snapshot of current attitudes. Still, it does not account for how perceptions and the use of AI may evolve as AI technology advances. Longitudinal studies would be better suited to track these changes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the growing awareness and acceptance of artificial intelligence (AI) in manuscript writing among academic professionals in India and Saudi Arabia. With 69% of the participants familiar with AI tools and a majority expressing positive views on its potential benefits, the findings suggest that AI is increasingly viewed as a valuable resource for enhancing the quality and efficiency of academic work. However, ethical concerns remain a significant issue, as evidenced by the 33% of respondents questioning the ethical implications of AI use in this context. The overwhelming support for formal AI training programs and the establishment of ethical guidelines underscore the need for structured approaches to integrate AI into academic workflows responsibly.\u003c/p\u003e \u003cp\u003e To further the adoption of AI, addressing these ethical concerns through clear, transparent guidelines and training programs emphasizing responsible AI use, authorship, and accountability is crucial. Moreover, future research should focus on understanding the factors influencing differing attitudes toward AI, including career stage, gender, and field of expertise, to develop more tailored and inclusive approaches to AI integration. By continuing to explore the practical applications of AI in manuscript writing and addressing the remaining concerns, academia can fully leverage the potential of AI to improve research outputs while maintaining the integrity of scholarly communication.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge Prince Sattam bin Abdulaziz University\u0026apos;s support in funding the study via project number (PSAU/2024/R/1446).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRajashekhara B. Sharanesha, Adel S. Alqarni\u003csup\u003e\u0026nbsp;\u003c/sup\u003econtributions to the conception and design of the work, Maram Alagla, Abdulhamid Al Ghwainem\u003csup\u003e\u0026nbsp;\u003c/sup\u003edata acquisition, and analysis, AlWaleed Abushanan, Abdulfatah Alazmah\u003csup\u003e\u0026nbsp;\u003c/sup\u003einterpretation of data, SN Asiri, Deepti Virupakshappa,\u0026nbsp;Sara Alghamdi\u0026nbsp;and\u0026nbsp;Narendra\u0026nbsp;Varma Penumatsa\u0026nbsp;drafted the work or substantively revised it.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThe authors would like to acknowledge Prince Sattam bin Abdulaziz University for supporting the study via project number (PSAU/2024/R/1446).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eThe details of the data and the study materials will be available from the corresponding author upon reasonable request. The questionnaire and the consent form are available in the supplement files.\u003c/p\u003e\n\u003ch4\u003eEthical Consideration:\u0026nbsp;The study adhered to ethical research standards (Declaration of Helsinki). Informed consent was obtained from all participants, and they were informed that their participation was voluntary and that they could withdraw from the study at any time without any consequences. No personal identifiers were collected, ensuring anonymity and confidentiality. The study was reviewed and approved by the Standing Committee of Bioethics Research of Prince Sattam bin Abdulaziz University (SCBR-241/2024)) of the hosting institution before the survey was conducted.\u003c/h4\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAldakhil S, Alkhurayji K, Albarrak S, et al. 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Roumengas, et al., Natural language processing for literature search in vascular surgery: a pilot study testing an artificial intelligence-based application. EJVES Vascular Forum, Elsevier, 2023.\u003c/li\u003e\n\u003cli\u003eP. Schneider, et al., Rethinking drug design in the artificial intelligence era, Nat. Rev. Drug Discov. 19 (5) (2020) 353\u0026ndash;364.\u003c/li\u003e\n\u003cli\u003eA. Salimi, H. Saheb, Large language models in ophthalmology scientific writing: ethical considerations blurred lines or not at all? Am. J. Ophthalmol. 254 (2023) 177\u0026ndash;181.\u003c/li\u003e\n\u003cli\u003eGunser, V. E., Gottschling, S., Brucker, B., Richter, S., \u0026Ccedil;akir, D., \u0026amp; Gerjets, P. (2022). The pure poet: How good is the subjective credibility and stylistic quality of literary short texts written with an artificial intelligence tool as compared to texts written by human authors?. 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Bibliometric Analysis of Global Research on Scientific Writing. \u003cem\u003eDESIDOC Journal of Library \u0026amp; Information Technology\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(3), 192-200.\u003c/li\u003e\n\u003cli\u003eZheng, H., \u0026amp; Zhan, H. (2023). ChatGPT in scientific writing: a cautionary tale. \u003cem\u003eThe American Journal of Medicine\u003c/em\u003e, \u003cem\u003e136\u003c/em\u003e(8), 725-726.\u003c/li\u003e\n\u003cli\u003eAzib, W. N. H. W., Hashim, M. Z., Rahman, K. A., Ishak, F. M., Yusoff, Y., \u0026amp; Sapiai, N. S. Highlighting The Artificial Intelligence (Ai) Limitations As Writing Assistant Tools In Producing Academic Writing Outputs: A Narrative Review. \u003cem\u003eDevelopment (JISED)\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(64), 406-415.\u003c/li\u003e\n\u003cli\u003eBizzoni, Y., Degaetano-Ortlieb, S., Fankhauser, P., \u0026amp; Teich, E. (2020). Linguistic variation and change in 250 years of English scientific writing: A data-driven approach. \u003cem\u003eFrontiers in Artificial Intelligence\u003c/em\u003e, \u003cem\u003e3\u003c/em\u003e, 73.\u003c/li\u003e\n\u003cli\u003eButler, T. L. (1981). Can a computer be an author-copyright aspects of artificial intelligence. \u003cem\u003eComm/Ent LS\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e, 707.\u003c/li\u003e\n\u003cli\u003eBisdas S, Topriceanu CC, Zakrzewska Z, et al. Artificial Intelligence in Medicine: A Multinational Multi-Center Survey on the Medical and Dental Students\u0026apos; Perception. \u003cem\u003eFront Public Health\u003c/em\u003e. 2021;9:795284. Published 2021 Dec 24. doi:10.3389/fpubh.2021.795284\u003c/li\u003e\n\u003cli\u003eChemaya N, Martin D. Perceptions and detection of AI use in manuscript preparation for academic journals. \u003cem\u003ePLoS One\u003c/em\u003e. 2024;19(7):e0304807. Published 2024 Jul 12. doi:10.1371/journal.pone.0304807.\u003c/li\u003e\n\u003cli\u003eHuang, Jingshan and Ming Tan. \u0026ldquo;The role of ChatGPT in scientific communication: writing better scientific review articles.\u0026rdquo; \u003cem\u003eAmerican journal of cancer research\u003c/em\u003e vol. 13,4 1148-1154. 15 Apr. 2023\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Academic professionals, Artificial intelligence, Ethical concerns, Manuscript writing, Perceptions","lastPublishedDoi":"10.21203/rs.3.rs-5518955/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5518955/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction\u003c/h2\u003e \u003cp\u003eArtificial intelligence (AI) transforms academic writing by providing tools that enhance efficiency, accuracy, and quality. Models such as ChatGPT are increasingly used for tasks such as grammar correction, structure refinement, and citation management. However, uncertainties and ethical concerns regarding the role of AI in manuscript writing remain. This study aims to assess AI's awareness, usage, and perceptions among academic professionals, focusing on its benefits and ethical implications.\u003c/p\u003e\u003ch2\u003eMethodology\u003c/h2\u003e \u003cp\u003eA cross-sectional survey was conducted among 100 academic professionals from India and Saudi Arabia, including lecturers, assistant professors, associate professors, and professors. The 15-question survey addressed demographic details, research experience, knowledge of AI, and views on its ethical use. Descriptive statistics were used to analyze the responses, with frequencies and percentages calculated for each item. Comparative analyses were performed via the Mann\u0026ndash;Whitney U test and the Kruskal‒Wallis H test to assess differences in response based on gender, qualification, and years of experience.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e Among the 100 participants, 69% were aware of AI in manuscript writing, and 68% believed that it enhanced the quality and efficiency of their academic work. Most respondents (92%) supported formal AI training programs and guidelines for ethical AI use. However, 33% raised concerns about the moral implications of AI in academic writing. Among the 100 participants, 69% were aware of AI in manuscript writing, and 68% believed it enhanced the quality and efficiency of their academic work. Notably, 92% supported implementing formal AI training programs and guidelines for ethical use, while 33% expressed concerns about its moral implications. Significant differences were observed based on demographic factors such as qualifications and years of experience (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Most participants were aged 36\u0026ndash;50 years (55%) and held a master\u0026rsquo;s degree (74%). Despite ethical concerns, the findings highlight the growing acceptance of AI in academic writing and emphasize the need for structured training and guidelines to facilitate its responsible adoption.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study highlights the growing acceptance of AI in academic writing. Most professionals acknowledge its benefits for enhancing efficiency and quality.\u003c/p\u003e","manuscriptTitle":"Perceptions and Utilization of Artificial Intelligence in Manuscript Writing: A Cross-Sectional Survey in Health Care Academics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 12:27:50","doi":"10.21203/rs.3.rs-5518955/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d8a225c4-c4f6-441b-9b4d-e9385a73fbe0","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-25T06:38:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-01 12:27:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5518955","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5518955","identity":"rs-5518955","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}