Survey of Smartphones, Medical Mobile Apps and Generative AI Use among Medical Students in Nigeria: A Case Study

Survey of Smartphones, Medical Mobile Apps and Generative AI Use among Medical Students in Nigeria: A Case Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Survey of Smartphones, Medical Mobile Apps and Generative AI Use among Medical Students in Nigeria: A Case Study Bayor Joseph ODELAMI, Nimat SHEHU, Samuel Iyanuoluwa ODEYEMI, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7576725/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Smartphones, medical applications (apps) and generative artificial intelligence (GenAI) are prominent learning tools widely used in higher education. However, the pattern of use of these tools among medical students at the Nigerian Federal University of Health Sciences, Ila - Orangun, has not been studied. The study was based on seven objectives set out to identify the pattern of usage of smartphones, medical apps, and GenAI for medical education among preclinical university students. Materials and Methods A descriptive survey design was employed. Data were collected via a structured questionnaire distributed electronically via WhatsApp to 297 preclinical medical students (Years 1–3) at the Federal University of Health Sciences, Ila-Orangun, between July 28th and August 28th, 2025. A total of 203 students responded, yielding a 75.5% response rate. The questionnaire, developed and validated by experts, covered smartphones, medical apps, and GenAI frequency and purpose. The data were analyzed via SPSS (version 22), and the results are presented in tables, frequencies, and charts. Results Of the 203 respondents, 43.3% (n = 88) were male, and 56.7% (n = 115) were female. All the students owned a smartphone, with 87.7% (n = 178) using Android devices and 13.3% (n = 25) using iPhones. A majority (81.3%, n = 165) reported daily smartphone use of 1–4 hours, 10.3% (n = 21) more than 5 hours, and 8.4% (n = 17) less than 1 hour. Primary purposes included reading lecture notes/ebooks, researching academic content online, and viewing medical videos. Medical app usage was widespread, with 87.7% (n = 178) reporting installations and 68% using them daily or weekly; commonly used apps included anatomy tools, interactive learning platforms, and medical dictionaries. Generative AI tools were also highly utilized, with ChatGPT (98%) being the most frequently accessed tool, followed by grammar checkers (56.7%), Med-PaLM (28.1%), Gemini (28.1%), and Copilot (13.3%) for the purpose of generating summaries of complex topics, clarifying difficult concepts, and preparing exams. Conclusion This study revealed a high level of use of smartphones, medical applications, and generative AI among medical students, underscoring the importance of these technologies in contemporary medical education. Accordingly, universities should develop clear policies to guide and optimize the use of smartphones, medical apps, and GenAI for academic purposes. Smartphones medical apps GenAI medical students mobile apps Figures Figure 1 Figure 2 INTRODUCTION Globally, smartphones, mobile applications (“apps”) and generative artificial intelligence (GenAI) have emerged as essential tools for teaching and learning, particularly in the current era, where remote education has gained prominence due to diverse socioeconomic challenges. For example, during the COVID-19 pandemic, these technologies played a pivotal role in ensuring the continuity of teaching and learning despite widespread disruptions. Owing to their powerful features and capabilities, ease of use, usefulness and affordability, these technologies enable seamless access to information, tools and resources that support effective teaching and learning. Smartphones, which are personal device assistants with multipurpose functions and capabilities, including the ability to store large volumes of data, browse the internet, capture images, and record videos, among others, have become very popular among various populations, including medical students who utilize them for various purposes [ 1 – 2 ]. According to [ 3 ], smartphones are utilized by medical students for both academic and nonacademic purposes, including reading for examination, watching lecture videos, and collaboration, as well as for social networking and communication with friends and family. Findings from the literature indicate that medical students regard smartphones as essential tools for navigating medical school and performing effectively in the medical profession [ 4 – 5 ]. Likewise, medical mobile apps are being utilized in medical education because of their usefulness [ 6 – 7 ]. According to [ 8 ], medical mobile apps are “third-party medical and health models based on mobile communication technology that provide medical and health-related content for the purpose of promoting diagnosis and disease prevention. Like health apps, which enable individuals, patients and caregivers to keep track of their health conditions, the use of medical apps has been shown to offer various benefits for medical students, including clinical decisions [ 9 ], improved learning [ 3 – 4 ], enhanced decision making and quick access to reliable medical information [ 10 ]. In addition to smartphones and medical apps, GenAI has emerged as a widely utilized tool among students, reflecting its growing popularity within the academic spectrum. According to [ 11 ], GenAI is a subset of artificial intelligence that is based on large language models with the capacity to generate and understand human-like texts and languages. The popularity of GenAI was marked by the release of ChatGPT by OpenAI in 2020 [ 12 ]. Since then, GenAI tools such as Gemini, Claude AI, Elicit, Perplexity, Google Bard, Copilot, DeepSeek and many others have also been developed and released for public consumption. These technologies can generate texts, audios, videos, and ideas; analyze data; and visualize and perform advanced tasks without human effort. While there is yet to be a unified policy on the adoption and utilization of these technologies in higher education, particularly in developing countries, many students are utilizing the technologies for various domains of their academic endeavors [ 13 – 14 ]. Given the global trend of technology integration in education, it is essential to assess the extent to which innovations such as smartphones, mobile medical apps and GenAI are being adopted by medical students in the Global South, where the uptake of such technologies has historically lagged behind. The literature indicates significantly higher levels of adoption in developed countries, with evidence suggesting that the effective use of smartphones, mobile applications, and GenAI contributes to enhanced academic performance, improved clinical decision-making, strengthened communication, more accurate diagnoses, and overall better patient care outcomes. On the basis of this development, the need for a study that examines smartphones, medical apps and GenAI use among medical students in Nigeria became imperative. Therefore, the objectives of this study are to (1) investigate the frequency of use of smartphones among medical students, (2) determine the purpose of use of smartphones among the students, (3) ascertain the types of medical apps being utilized by the students, (4) investigate the frequency of use of medical apps among the students, (5) identify the GenAI being used by the students, (6) ascertain the frequency of use of GenAI among the students, and (7) determine the purpose of use of GenAI among the students. The outcome of this study will offer evidence on how smartphones, medical applications, and generative AI are used by medical students in Nigeria, revealing patterns, purposes, and gaps in adoption. Furthermore, the results will inform curriculum design, policy development, and digital literacy initiatives while also contributing perspectives from the Global South to the global discourse on technology in medical education. MATERIALS AND METHODS The study adopted a descriptive research design and gathered data from respondents via questionnaires. The questionnaire was distributed electronically via the WhatsApp mobile app via a known survey website (Google Form). The questionnaire was sent to the WhatsApp group of medical students from years 1–3 at Federal University of Health Sciences, Ila–Orangun (the administration was limited to years 1–3 because the university is yet to have 4–6 medical students). The total population of registered undergraduate medical students across the three levels was 297. The survey was sent several times from the 1st day in August, 2025, through the 31st August, 2025, to allow the students to complete the questionnaire. Among the total study population, 203 students completed the survey, representing a response rate of 75.5% (Table 1 ). The questionnaire (Appendix 1) was developed by the lead researcher and subsequently reviewed by an expert panel to establish content validity and reliability. The questions were derived from previous literature and the researcher’s personal experience and those of other informants. The medical apps and GenAI listed were derived from the literature. The questionnaire collected data on the following areas: frequency of use of smartphones among medical students, the purpose of use of smartphones, the types of medical apps being utilized, the frequency of use of medical apps, the GenAI being used by the students, the frequency of use of GenAI among the students and the purpose of use of GenAI among the students. An open-ended text box was provided to allow respondents to elaborate on additional issues related to the use of smartphones, medical applications, and GenAI. The quantitative data were subsequently entered and analyzed via the Statistical Package for the Social Sciences (SPSS, version 22). RESULTS Table 1 Demographic characteristics of the respondents Variable Frequency (n) Percentage (%) Gender Male 88 43.3 Female 115 56.7 Level of Study 100 level 58 28.6 200 level 66 32.5 300 level 79 38.9 Smartphone Ownership 100 level 58 100.0 200 level 66 100.0 300 level Types of Smartphones Android iPhone 79 178 25 100.0 87.7% 13.3% The results from Fig. 1 shows that 203 medical students answered the questionnaire out of a possible cohort of 269 registered undergraduate students, equating to a return rate of 75.5% (203/269). The percentages of males to females split were 43.3% (n = 88/269) and 56.7% (n = 115/269), respectively. The distribution of respondents within each year of study was 28.6% (n = 58/203) in year 1, 32.5% (n = 66/203) in year 2, and 38.9% (n = 79/203) in year 3 preclinical studies. Answers to Research Questions Question One: What is the frequency of use of smartphones among medical students? Table 2 Frequency of Use of Med Apps by Medical Students per Hour Hours Spent on Smartphones Frequency (n) Percentage (%) Less than 1 hour 17 8.4 1–2 hours 83 40.9 3–4 hours 82 40.4 More than 5 hours 21 10.3 Total 203 100.0 The results in Table 2 show medical students’ daily smartphone usage. The results indicate that the majority of students spend a considerable amount of time on their devices. Specifically, 40.9% (n = 83) reported using their smartphones for 1–2 hours per day, whereas a nearly equal proportion, 40.4% (n = 82), indicated spending 3–4 hours daily. Together, this accounts for more than 81% of the sample. A smaller group, 10.3% (n = 21), reported using their smartphones for more than 5 hours per day, whereas only 8.4% (n = 17) used their smartphones for less than one hour per day. Overall, the findings reveal that smartphones are an integral part of students’ daily routines, with most spending between 1 and 4 hours per day on these devices. Question Two: What is the purpose of the use of smartphones among students? Table 3 Purpose of smartphone use among students SN Purpose of Use Frequency (n) Percentage (%) 1. Reading lecture notes or e-books 195 96.1 2. Watching medical tutorials or lectures 166 81.8 3. Participating in online discussions or study groups 156 76.8 4. Taking notes during class or clinical sessions 56 27.6 5. Researching academic content online 185 91.1 The results revealed that the most common purposes of smartphone use by medical students were reading lecture notes or e-books (96.1%, n = 195) and researching academic content online (91.1%, n = 185). A large proportion also reported watching medical tutorials or lectures (81.8%, n = 166) and participating in online discussions or study groups (76.8%, n = 156). In contrast, only 27.6% (n = 56) used smartphones, primarily for taking notes during class or clinical sessions, implying that students still prefer traditional note-taking methods (e.g., writing in notebooks). Question Three: What types of medical apps are utilized by students? The results of medical app utilization revealed that anatomy learning apps were the most frequently used apps, reported by 157 students (77.3%). This was followed closely by interactive learning platforms such as Osmosis and TeachMeAnatomy, which were used by 146 students (71.9%). Exam preparation apps were also widely adopted, with 109 students (53.7%) reporting use, whereas basic sciences revision apps were utilized by 107 students (52.7%). Moderate usage was recorded for medical dictionaries or reference apps (88 students, 43.3%) and medical terminology apps (68 students, 33.5%). Fewer students reported using drug classification and pharmacology basic apps (36 students, 17.7%), whereas 46 students (22.7%) indicated using other apps, such as reference medical apps. Question Four: What is the frequency of use of medical apps among students? The results of the frequency of medical app usage revealed that the largest group of respondents reported using medical apps daily (n = 82/203, 0.4%). A smaller but notable proportion indicated using them on a weekly basis (n = 56/203, 27.6%), whereas an equal number reported using them occasionally (n = 56/203, 27.6%). Only a small minority stated that they never used medical apps (n = 9/203, 4.4%). These findings indicate that medical apps are widely adopted among medical students, with the majority engaging with them regularly (daily or weekly). Questions Five: What are the types of GenAI used by medical students? Table 4 GenAI being used by medical students SN Type of GenAI tool N % 1 ChatGPT 199 98.0 2 Gemini 57 28.1 3 Microsoft Copilot 27 13.3 4 Med-PaLM 57 28.1 5 Others 115 56.7 6 Never used GenAI tools 1 0.5 The results show that ChatGPT is by far the most widely used generative AI tool among the students, with 199/203 (98%) reporting its use. A smaller proportion reported using Gemini (57/203, 28.1%) and Med-PaLM (n = 57/203, 28.1%), whereas Microsoft Copilot was the least common (n = 27/203, 13.3%). In addition, 115/203 respondents (56.7%) indicated the use of other GenAI tools beyond those listed, such as DeepSeek and grammar checker AI. Only one respondent (0.5%) reported never having used any GenAI tool. Question Six: What is the frequency of GenAI use among medical students? Table 5 Frequency of GenAI use SN Frequency of Use n % 1 Daily 94 46.3 2 Weekly 56 27.6 3 Occasionally 49 24.1 4 Rarely 1 0.5 5 Never 3 1.5 The analysis of students’ frequency of use of generative AI tools revealed that almost half of the respondents reported daily use (46.3%, n = 94), whereas 27.6% ( n = 56) indicated weekly use. Approximately one-fourth (24.1%, n = 49) used the tools occasionally, whereas only 0.5% ( n = 1) reported rare use. A very small proportion of the students (1.5%, n = 3) indicated that they had never used generative AI tools. These findings suggest that the use of generative AI is widespread, with most students engaging with such tools regularly. Question Seven: What is the purpose of use of GenAI among the students? Table 6 Purpose of GenAI Use by Medical Students SN Purpose of Use n % 1 Generating summaries of complex topics 186 91.6 2 Clarifying difficult medical concepts 176 86.7 3 Practicing clinical scenarios or MCQs 143 70.4 4 Drafting assignments or research papers 162 79.8 5 Generating study schedules/reminders 96 47.3 6 Others 103 50.7 The most common application of generative AI among students was generating summaries of complex topics (91.6%, n = 186), followed closely by clarifying difficult medical concepts (86.7%, n = 176). A substantial number also reported using tools for drafting assignments or research work (79.8%, n = 162) and for practicing clinical scenarios or multiple-choice questions (70.4%, n = 143). Fewer students indicated the use of generative AI to generate study schedules or reminders (47.3%, n = 96). Additionally, 50.7% ( n = 103) reported other purposes of use, some of which include suggesting references or resources to read, answering practice questions and generating notes for reading. DISCUSSION Smartphones, medical apps and GenAI have become essential learning tools widely adopted by students worldwide. These resources promote independent learning and provide convenient access to diverse information in multiple formats. To the best of the researchers’ knowledge, this is the first study that will investigate the use of smartphones, medical apps, and GenAI among medical students at FUHSI, focusing on the types, frequency, and purposes of the use of these learning resources. However, the usage patterns of these learning resources have been studied in various contexts globally. Overall, the findings revealed that all the surveyed students predominantly owned smartphones and had reliable access to the internet (Table 1 ), providing them with the necessary tools to engage with digital learning resources effectively. This finding is consistent with that of [ 5 ], who similarly revealed that over 90% of the students surveyed owned a smartphone. A previous study by [ 9 ] and [ 2 ] also attested to the increasing accessibility and ownership of smartphones among medical students. This reveals the growing importance of smartphones as essential tools in medical education, facilitating access to information, learning resources, and digital applications that support academic and clinical training. With respect to the types of smartphones owned, this study revealed that medical students possessed both Android and iPhone smartphones. However, the majority (87.7%) reported owning an Android phone, whereas only 11.3% reported owning an iPhone (Table 1 ). This finding is consistent with that of [ 15 ] who reported higher ownership of Android devices among medical students. In contrast, Sarkar [ 16 ] reported that Apple’s iPhone was the most owned brand (55.4%), followed by Google Android phones (43.8%). The preference for Android devices among the surveyed students in this study may be attributed to their relatively lower cost and affordability compared with Apple’s iPhones, which are often more expensive to purchase and maintain in this part of the world. The frequency of smartphone use among medical students in this study was notably high (Table 2 ). More than 80% of the respondents reported using their smartphones between one and four hours daily, 10% reported using them for more than five hours, and only 8.4% reported using them for less than one hour per day (Table 3 ). These findings are consistent with those of [ 17 ], who similarly reported a high frequency of smartphone use among medical students in India. Similarly, our results align with those of [ 18 ], who highlighted extensive smartphone usage among medical students in Pakistan. Collectively, these findings reinforce existing evidence that smartphones have become indispensable in medical education globally [ 19 , 5 ]. The purpose for which medical students in this study used smartphones for academic activities correlates with [ 20 ]. A significant proportion of respondents reported using their smartphones to read lecture notes and e-books, followed by conducting online research for academic content, watching medical tutorials, participating in online discussions or study groups, and taking notes during classes. Furthermore, the study revealed that medical students utilized a wide range of medical applications to support their learning. These included anatomy-focused apps such as 3D Anatomy, Kenhub, TeachMeAnatomy, Visible Body, Osmosis, and Anatomography; interactive learning apps such as Prognosis, Ninja Nerd Science, and MDcalc; and revision or exam preparation apps such as Osmosis, Geeky Medics, and Prognosis (Fig. 1 ). In addition, the students reported frequent use of medical dictionaries, terminology apps, drug classification tools, and psychology-based apps such as Drugs.com. Reference tools, particularly PubMed and Medscape, were also identified as commonly used resources. These findings are consistent with those of previous studies, which reported similar trends in the types of medical apps frequently adopted by medical students, especially those in the preclinical stage [ 21 – 23 ]. Notably, the students in this study also suggested that the university should consider subscribing to UpToDate, depicting a demand for access to more advanced, evidence-based clinical decision-support resources. The frequency of use of these apps among the students was moderate, with more than 40% using the apps on a daily basis, 27.6% using them weekly and 27.6% using them occasionally (Fig. 2 ). With respect to the use of GenAI, this study revealed that among the most frequently utilized tools were ChatGPT, Gemini, Microsoft Copilot, and Med-PaLM. In addition, the students identified other GenAI platforms, such as MetaSeek and DeepSeek, as well as grammar-enhancing tools, such as QuillBot and Grammarly, as part of their regular use (Table 4 ). These findings align with earlier studies by [ 24 – 26 ], which also reported widespread adoption of GenAI tools among medical students in Nigeria. The frequency of GenAI use was notably high, with more than 70% of the students indicating daily or weekly use for academic purposes (Table 5 ). Reported applications included generating summaries of complex topics, practicing clinical scenarios or multiple-choice questions (MCQs), clarifying difficult medical concepts, drafting assignments or research papers, and creating study schedules or reminders (Table 6 ). These results are consistent with [ 14 ], who highlighted similar patterns of GenAI adoption in medical education. The additional purposes of use identified by the students in this study included generating reading notes, suggesting references or supplementary resources, and answering practice questions, further demonstrating the versatility of GenAI in supporting medical learning. While the widespread adoption of GenAI reflects its potential to enhance personalized learning, efficiency, and academic productivity, it also raises important concerns. Overreliance on AI-generated content may limit the development of critical thinking and independent problem-solving skills. In addition, issues such as misinformation, plagiarism, data privacy, and academic integrity have been identified as potential risks in medical education [ 27 – 28 ]. Therefore, although GenAI holds promise as a powerful educational tool, there is a need for structured guidelines, ethical training, and institutional support to ensure that medical students use these tools responsibly and effectively. Implications of the study On the basis of the findings of this study, several implications for medical education, policy, and practice are identified. First, the widespread ownership and frequent use of smartphones among medical students at FUHSI reveals the vital role of mobile technology as a major learning tool. As such, our findings highlight the need for medical schools to intentionally integrate mobile-based learning strategies into the curriculum, ensuring that students are guided to use smartphones productively rather than merely as social or entertainment devices. Second, our finding that a variety of medical applications are used by medical students demonstrates that students are actively utilizing technology to complement traditional learning methods. Therefore, institutional support in terms of providing technological infrastructure, subscribing to premium medical apps (e.g., UpToDate ), and training staff and students should be intensified to increase the quality of medical training by broadening access to authoritative, evidence-based resources. Furthermore, the high level of awareness and frequent use of generative AI tools discovered in our study points to a shift in how medical students engage with information. While these tools offer clear benefits in terms of efficiency, independent learning, and academic support, their widespread adoption raises concerns about overreliance, misinformation, and academic integrity. Finally, our findings contribute to the growing body of literature on digital literacy in medical education, particularly within the African context. Limitations of the study While the findings of this study offer practical insights into the patterns of smartphone, medical app and GenAI use among medical students in Nigeria, several limitations are recognized. First, the scope of the study was limited to a single university in Nigeria, which may limit the generalizability of the findings. The category of medical students examined was also preclinical students, who may not truly have a pressing need for the use of core medical apps and GenAI at their levels. Therefore, future research can expand the scope by incorporating more universities and levels of study into the investigation. Additionally, the study focused primarily on the types, frequency and purpose of the use of these emerging learning tools in medication. Further studies can examine the correlation between the use of these tools and the performance of medical students. Conclusion Our study revealed that the usage patterns of smartphones, medical apps and GenAI among the medical students surveyed were high due to the accessibility, affordability and vital roles these tools play in facilitating independent learning in medical education. However, we observed that most of the medical apps used by the students surveyed were open access apps and that the students did not use core medical apps such as UpToDate due to a lack of subscription by the students. Additionally, most GenAI being used is general, so there is a need to introduce medical students to core medical GenAI, which will aid their learning as they proceed to the clinical stages. Recommendations On the basis of the findings of this study, we recommend the following: University management should formally integrate the use of smartphones, medical apps, and GenAI into the medical education curriculum. The university should prioritize providing access to essential medical apps and GenAI platforms through institutional subscriptions Continuous training and workshops should be organized for medical students to increase their digital literacy and skills in effectively utilizing smartphones, medical apps, and GenAI. Abbreviations AI Artificial Intelligence Apps Applications FUHSI Federal University of Health Sciences, Ila-Orangun GenAI Declarations Ethics and Consent to Participate declarations : Ethical approval for this study was obtained from the Federal University of Health Sciences Ila Orangun Research and Ethics Committee. All procedures involving human participants were conducted in accordance with the ethical standards of the institutional research committee and the principles of the Declaration of Helsinki (2013 revision) . Participation was voluntary, and all respondents provided informed consent prior to completing the survey. Anonymity and confidentiality were assured, and no identifying information was collected. Consent for Publication: This study did not involve the publication of any individual participant’s data in any form (including images, videos, or personal details). Therefore, consent for publication is not required. Availability of Data and Materials: The raw data generated from respondents for this study can be found at https://drive.google.com/file/d/1YlMXO09rnLd7YDse30Wqe5jpfBpKq7m1/view?usp=sharing Competing Interests: The authors report no conflicts of interest. Funding Declaration: The authors do not receive any funding from any individuals or organizations for the research. Authors' contributions: All authors contributed significantly to the conception, design, execution, and analysis of the study. O.B. conceptualized the study and developed the methodology. N. S, O. S and A.A. coordinated data collection. O. B drafted the initial manuscript. A. A contributed to data analysis and interpretation. All authors reviewed, revised, and approved the final version of the manuscript for submission. Acknowledgements: The authors would like to acknowledge the support of the Federal University of Health Sciences, Ila-Orangun (FUHSI), and thank the students who participated in this study for their time and valuable responses. We also appreciate the contributions of colleagues and faculty members who provided guidance during the research process. References Whyte J. Smartphone. In: Beyes T, Holt R, Pias C, editors. The Oxford handbook of media, technology and organization studies. Oxford: Oxford University Press; 2019. pp. 1–14. 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Supplementary Files SurveySmartphonesMedAppsGenAIFUHSI.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Oct, 2025 Reviews received at journal 23 Oct, 2025 Reviews received at journal 13 Oct, 2025 Reviewers agreed at journal 12 Oct, 2025 Reviewers agreed at journal 11 Oct, 2025 Reviewers invited by journal 05 Oct, 2025 Editor assigned by journal 29 Sep, 2025 Editor invited by journal 29 Sep, 2025 Submission checks completed at journal 27 Sep, 2025 First submitted to journal 27 Sep, 2025 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. 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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-7576725","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":530152431,"identity":"ccca4a6a-9386-4741-9154-739fb65969ff","order_by":0,"name":"Bayor Joseph 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1","display":"","copyAsset":false,"role":"figure","size":72608,"visible":true,"origin":"","legend":"\u003cp\u003eTypes of Med Apps Being Utilized by Medical Students\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7576725/v1/beb0980fde08dec90c1d72f7.png"},{"id":93730447,"identity":"bb5e1e71-f89a-4a78-b9a6-b364ef0dec3d","added_by":"auto","created_at":"2025-10-17 02:20:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":65542,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency of Use of Medical Apps\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7576725/v1/bd6c25119c8bb907ca041594.png"},{"id":93732251,"identity":"0936cd5a-cb60-40d0-9198-d0f29c50f625","added_by":"auto","created_at":"2025-10-17 02:28:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":863576,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7576725/v1/63079789-1b7d-4171-a596-ae94d6fb1a04.pdf"},{"id":93730442,"identity":"bafd7d0a-bdd4-4a90-8531-81642a7527d6","added_by":"auto","created_at":"2025-10-17 02:20:48","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":27037,"visible":true,"origin":"","legend":"","description":"","filename":"SurveySmartphonesMedAppsGenAIFUHSI.docx","url":"https://assets-eu.researchsquare.com/files/rs-7576725/v1/f8f5692aed3cb638ad65c348.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Survey of Smartphones, Medical Mobile Apps and Generative AI Use among Medical Students in Nigeria: A Case Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eGlobally, smartphones, mobile applications (\u0026ldquo;apps\u0026rdquo;) and generative artificial intelligence (GenAI) have emerged as essential tools for teaching and learning, particularly in the current era, where remote education has gained prominence due to diverse socioeconomic challenges. For example, during the COVID-19 pandemic, these technologies played a pivotal role in ensuring the continuity of teaching and learning despite widespread disruptions. Owing to their powerful features and capabilities, ease of use, usefulness and affordability, these technologies enable seamless access to information, tools and resources that support effective teaching and learning.\u003c/p\u003e\u003cp\u003eSmartphones, which are personal device assistants with multipurpose functions and capabilities, including the ability to store large volumes of data, browse the internet, capture images, and record videos, among others, have become very popular among various populations, including medical students who utilize them for various purposes [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], smartphones are utilized by medical students for both academic and nonacademic purposes, including reading for examination, watching lecture videos, and collaboration, as well as for social networking and communication with friends and family. Findings from the literature indicate that medical students regard smartphones as essential tools for navigating medical school and performing effectively in the medical profession [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Likewise, medical mobile apps are being utilized in medical education because of their usefulness [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAccording to [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], medical mobile apps are \u0026ldquo;third-party medical and health models based on mobile communication technology that provide medical and health-related content for the purpose of promoting diagnosis and disease prevention. Like health apps, which enable individuals, patients and caregivers to keep track of their health conditions, the use of medical apps has been shown to offer various benefits for medical students, including clinical decisions [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], improved learning [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], enhanced decision making and quick access to reliable medical information [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In addition to smartphones and medical apps, GenAI has emerged as a widely utilized tool among students, reflecting its growing popularity within the academic spectrum.\u003c/p\u003e\u003cp\u003eAccording to [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], GenAI is a subset of artificial intelligence that is based on large language models with the capacity to generate and understand human-like texts and languages. The popularity of GenAI was marked by the release of ChatGPT by OpenAI in 2020 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Since then, GenAI tools such as Gemini, Claude AI, Elicit, Perplexity, Google Bard, Copilot, DeepSeek and many others have also been developed and released for public consumption. These technologies can generate texts, audios, videos, and ideas; analyze data; and visualize and perform advanced tasks without human effort. While there is yet to be a unified policy on the adoption and utilization of these technologies in higher education, particularly in developing countries, many students are utilizing the technologies for various domains of their academic endeavors [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven the global trend of technology integration in education, it is essential to assess the extent to which innovations such as smartphones, mobile medical apps and GenAI are being adopted by medical students in the Global South, where the uptake of such technologies has historically lagged behind. The literature indicates significantly higher levels of adoption in developed countries, with evidence suggesting that the effective use of smartphones, mobile applications, and GenAI contributes to enhanced academic performance, improved clinical decision-making, strengthened communication, more accurate diagnoses, and overall better patient care outcomes. On the basis of this development, the need for a study that examines smartphones, medical apps and GenAI use among medical students in Nigeria became imperative. Therefore, the objectives of this study are to (1) investigate the frequency of use of smartphones among medical students, (2) determine the purpose of use of smartphones among the students, (3) ascertain the types of medical apps being utilized by the students, (4) investigate the frequency of use of medical apps among the students, (5) identify the GenAI being used by the students, (6) ascertain the frequency of use of GenAI among the students, and (7) determine the purpose of use of GenAI among the students. The outcome of this study will offer evidence on how smartphones, medical applications, and generative AI are used by medical students in Nigeria, revealing patterns, purposes, and gaps in adoption. Furthermore, the results will inform curriculum design, policy development, and digital literacy initiatives while also contributing perspectives from the Global South to the global discourse on technology in medical education.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003eThe study adopted a descriptive research design and gathered data from respondents via questionnaires. The questionnaire was distributed electronically via the WhatsApp mobile app via a known survey website (Google Form). The questionnaire was sent to the WhatsApp group of medical students from years 1\u0026ndash;3 at Federal University of Health Sciences, Ila\u0026ndash;Orangun (the administration was limited to years 1\u0026ndash;3 because the university is yet to have 4\u0026ndash;6 medical students). The total population of registered undergraduate medical students across the three levels was 297. The survey was sent several times from the 1st day in August, 2025, through the 31st August, 2025, to allow the students to complete the questionnaire. Among the total study population, 203 students completed the survey, representing a response rate of 75.5% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The questionnaire (Appendix 1) was developed by the lead researcher and subsequently reviewed by an expert panel to establish content validity and reliability. The questions were derived from previous literature and the researcher\u0026rsquo;s personal experience and those of other informants. The medical apps and GenAI listed were derived from the literature. The questionnaire collected data on the following areas: frequency of use of smartphones among medical students, the purpose of use of smartphones, the types of medical apps being utilized, the frequency of use of medical apps, the GenAI being used by the students, the frequency of use of GenAI among the students and the purpose of use of GenAI among the students. An open-ended text box was provided to allow respondents to elaborate on additional issues related to the use of smartphones, medical applications, and GenAI. The quantitative data were subsequently entered and analyzed via the Statistical Package for the Social Sciences (SPSS, version 22).\u003c/p\u003e"},{"header":"RESULTS","content":"\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\u003eDemographic characteristics of the respondents\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=\"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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency (n)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLevel of Study\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e100 level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e200 level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e300 level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSmartphone Ownership\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e100 level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e200 level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e300 level\u003c/p\u003e\u003cp\u003e\u003cb\u003eTypes of Smartphones\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAndroid\u003c/p\u003e\u003cp\u003eiPhone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e79\u003c/p\u003e\u003cp\u003e178\u003c/p\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100.0\u003c/p\u003e\u003cp\u003e87.7%\u003c/p\u003e\u003cp\u003e13.3%\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\u003eThe results from Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that 203 medical students answered the questionnaire out of a possible cohort of 269 registered undergraduate students, equating to a return rate of 75.5% (203/269). The percentages of males to females split were 43.3% (n\u0026thinsp;=\u0026thinsp;88/269) and 56.7% (n\u0026thinsp;=\u0026thinsp;115/269), respectively. The distribution of respondents within each year of study was 28.6% (n\u0026thinsp;=\u0026thinsp;58/203) in year 1, 32.5% (n\u0026thinsp;=\u0026thinsp;66/203) in year 2, and 38.9% (n\u0026thinsp;=\u0026thinsp;79/203) in year 3 preclinical studies.\u003c/p\u003e\n\u003ch3\u003eAnswers to Research Questions\u003c/h3\u003e\n\u003cp\u003eQuestion One: What is the frequency of use of smartphones among medical students?\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\u003eFrequency of Use of Med Apps by Medical Students per Hour\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=\"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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHours Spent on Smartphones\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency (n)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than 1 hour\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;2 hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026ndash;4 hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than 5 hours\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100.0\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\u003eThe results in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e show medical students\u0026rsquo; daily smartphone usage. The results indicate that the majority of students spend a considerable amount of time on their devices. Specifically, 40.9% (n\u0026thinsp;=\u0026thinsp;83) reported using their smartphones for 1\u0026ndash;2 hours per day, whereas a nearly equal proportion, 40.4% (n\u0026thinsp;=\u0026thinsp;82), indicated spending 3\u0026ndash;4 hours daily. Together, this accounts for more than 81% of the sample. A smaller group, 10.3% (n\u0026thinsp;=\u0026thinsp;21), reported using their smartphones for more than 5 hours per day, whereas only 8.4% (n\u0026thinsp;=\u0026thinsp;17) used their smartphones for less than one hour per day. Overall, the findings reveal that smartphones are an integral part of students\u0026rsquo; daily routines, with most spending between 1 and 4 hours per day on these devices.\u003c/p\u003e\u003cp\u003eQuestion Two: What is the purpose of the use of smartphones among students?\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\u003e\u003cem\u003ePurpose of smartphone use among students\u003c/em\u003e\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePurpose of Use\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFrequency (n)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReading lecture notes or e-books\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.1\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\u003e2.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWatching medical tutorials or lectures\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e81.8\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\u003e3.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eParticipating in online discussions or study groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e76.8\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.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTaking notes during class or clinical sessions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e27.6\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\u003e5.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eResearching academic content online\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e185\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e91.1\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\u003eThe results revealed that the most common purposes of smartphone use by medical students were reading lecture notes or e-books (96.1%, n\u0026thinsp;=\u0026thinsp;195) and researching academic content online (91.1%, n\u0026thinsp;=\u0026thinsp;185). A large proportion also reported watching medical tutorials or lectures (81.8%, n\u0026thinsp;=\u0026thinsp;166) and participating in online discussions or study groups (76.8%, n\u0026thinsp;=\u0026thinsp;156). In contrast, only 27.6% (n\u0026thinsp;=\u0026thinsp;56) used smartphones, primarily for taking notes during class or clinical sessions, implying that students still prefer traditional note-taking methods (e.g., writing in notebooks).\u003c/p\u003e\u003cp\u003eQuestion Three: What types of medical apps are utilized by students?\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe results of medical app utilization revealed that anatomy learning apps were the most frequently used apps, reported by 157 students (77.3%). This was followed closely by interactive learning platforms such as Osmosis and TeachMeAnatomy, which were used by 146 students (71.9%). Exam preparation apps were also widely adopted, with 109 students (53.7%) reporting use, whereas basic sciences revision apps were utilized by 107 students (52.7%). Moderate usage was recorded for medical dictionaries or reference apps (88 students, 43.3%) and medical terminology apps (68 students, 33.5%). Fewer students reported using drug classification and pharmacology \u003cb\u003ebasic\u003c/b\u003e apps (36 students, 17.7%), whereas 46 students (22.7%) indicated using other apps, such as reference medical apps.\u003c/p\u003e\u003cp\u003eQuestion Four: What is the frequency of use of medical apps among students?\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe results of the frequency of medical app usage revealed that the largest group of respondents reported using medical apps daily (n\u0026thinsp;=\u0026thinsp;82/203, 0.4%). A smaller but notable proportion indicated using them on a weekly basis (n\u0026thinsp;=\u0026thinsp;56/203, 27.6%), whereas an equal number reported using them occasionally (n\u0026thinsp;=\u0026thinsp;56/203, 27.6%). Only a small minority stated that they never used medical apps (n\u0026thinsp;=\u0026thinsp;9/203, 4.4%). These findings indicate that medical apps are widely adopted among medical students, with the majority engaging with them regularly (daily or weekly).\u003c/p\u003e\u003cp\u003eQuestions Five: What are the types of GenAI used by medical students?\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGenAI being used by medical students\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eType of GenAI tool\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChatGPT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e199\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e98.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGemini\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMicrosoft Copilot\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e13.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMed-PaLM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNever used GenAI tools\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5\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\u003eThe results show that ChatGPT is by far the most widely used generative AI tool among the students, with 199/203 (98%) reporting its use. A smaller proportion reported using Gemini (57/203, 28.1%) and Med-PaLM (n\u0026thinsp;=\u0026thinsp;57/203, 28.1%), whereas Microsoft Copilot was the least common (n\u0026thinsp;=\u0026thinsp;27/203, 13.3%). In addition, 115/203 respondents (56.7%) indicated the use of other GenAI tools beyond those listed, such as DeepSeek and grammar checker AI. Only \u003cb\u003eone\u003c/b\u003e respondent (0.5%) reported never having used any GenAI tool.\u003c/p\u003e\u003cp\u003eQuestion Six: What is the frequency of GenAI use among medical students?\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFrequency of GenAI use\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency of Use\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDaily\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e46.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWeekly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOccasionally\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRarely\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.5\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\u003eThe analysis of students\u0026rsquo; frequency of use of generative AI tools revealed that almost half of the respondents reported daily use (46.3%, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;94), whereas 27.6% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;56) indicated weekly use. Approximately one-fourth (24.1%, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;49) used the tools occasionally, whereas only 0.5% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1) reported rare use. A very small proportion of the students (1.5%, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) indicated that they had never used generative AI tools. These findings suggest that the use of generative AI is widespread, with most students engaging with such tools regularly.\u003c/p\u003e\u003cp\u003eQuestion Seven: What is the purpose of use of GenAI among the students?\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePurpose of GenAI Use by Medical Students\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePurpose of Use\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGenerating summaries of complex topics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e91.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eClarifying difficult medical concepts\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e176\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e86.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePracticing clinical scenarios or MCQs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e143\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e70.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDrafting assignments or research papers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e79.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGenerating study schedules/reminders\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e50.7\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\u003eThe most common application of generative AI among students was generating summaries of complex topics (91.6%, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;186), followed closely by clarifying difficult medical concepts (86.7%, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;176). A substantial number also reported using tools for drafting assignments or research work (79.8%, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;162) and for practicing clinical scenarios or multiple-choice questions (70.4%, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;143). Fewer students indicated the use of generative AI to generate study schedules or reminders (47.3%, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;96). Additionally, 50.7% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;103) reported other purposes of use, some of which include suggesting references or resources to read, answering practice questions and generating notes for reading.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eSmartphones, medical apps and GenAI have become essential learning tools widely adopted by students worldwide. These resources promote independent learning and provide convenient access to diverse information in multiple formats. To the best of the researchers\u0026rsquo; knowledge, this is the first study that will investigate the use of smartphones, medical apps, and GenAI among medical students at FUHSI, focusing on the types, frequency, and purposes of the use of these learning resources. However, the usage patterns of these learning resources have been studied in various contexts globally.\u003c/p\u003e\u003cp\u003eOverall, the findings revealed that all the surveyed students predominantly owned smartphones and had reliable access to the internet (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), providing them with the necessary tools to engage with digital learning resources effectively. This finding is consistent with that of [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], who similarly revealed that over 90% of the students surveyed owned a smartphone. A previous study by [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] also attested to the increasing accessibility and ownership of smartphones among medical students. This reveals the growing importance of smartphones as essential tools in medical education, facilitating access to information, learning resources, and digital applications that support academic and clinical training.\u003c/p\u003e\u003cp\u003eWith respect to the types of smartphones owned, this study revealed that medical students possessed both Android and iPhone smartphones. However, the majority (87.7%) reported owning an Android phone, whereas only 11.3% reported owning an iPhone (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This finding is consistent with that of [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] who reported higher ownership of Android devices among medical students. In contrast, Sarkar [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] reported that Apple\u0026rsquo;s iPhone was the most owned brand (55.4%), followed by Google Android phones (43.8%). The preference for Android devices among the surveyed students in this study may be attributed to their relatively lower cost and affordability compared with Apple\u0026rsquo;s iPhones, which are often more expensive to purchase and maintain in this part of the world. The frequency of smartphone use among medical students in this study was notably high (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). More than 80% of the respondents reported using their smartphones between one and four hours daily, 10% reported using them for more than five hours, and only 8.4% reported using them for less than one hour per day (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These findings are consistent with those of [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], who similarly reported a high frequency of smartphone use among medical students in India. Similarly, our results align with those of [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], who highlighted extensive smartphone usage among medical students in Pakistan. Collectively, these findings reinforce existing evidence that smartphones have become indispensable in medical education globally [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The purpose for which medical students in this study used smartphones for academic activities correlates with [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. A significant proportion of respondents reported using their smartphones to read lecture notes and e-books, followed by conducting online research for academic content, watching medical tutorials, participating in online discussions or study groups, and taking notes during classes.\u003c/p\u003e\u003cp\u003eFurthermore, the study revealed that medical students utilized a wide range of medical applications to support their learning. These included anatomy-focused apps such as 3D Anatomy, Kenhub, TeachMeAnatomy, Visible Body, Osmosis, and Anatomography; interactive learning apps such as Prognosis, Ninja Nerd Science, and MDcalc; and revision or exam preparation apps such as Osmosis, Geeky Medics, and Prognosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In addition, the students reported frequent use of medical dictionaries, terminology apps, drug classification tools, and psychology-based apps such as Drugs.com. Reference tools, particularly PubMed and Medscape, were also identified as commonly used resources. These findings are consistent with those of previous studies, which reported similar trends in the types of medical apps frequently adopted by medical students, especially those in the preclinical stage [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Notably, the students in this study also suggested that the university should consider subscribing to UpToDate, depicting a demand for access to more advanced, evidence-based clinical decision-support resources. The frequency of use of these apps among the students was moderate, with more than 40% using the apps on a daily basis, 27.6% using them weekly and 27.6% using them occasionally (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWith respect to the use of GenAI, this study revealed that among the most frequently utilized tools were ChatGPT, Gemini, Microsoft Copilot, and Med-PaLM. In addition, the students identified other GenAI platforms, such as MetaSeek and DeepSeek, as well as grammar-enhancing tools, such as QuillBot and Grammarly, as part of their regular use (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These findings align with earlier studies by [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], which also reported widespread adoption of GenAI tools among medical students in Nigeria. The frequency of GenAI use was notably high, with more than 70% of the students indicating daily or weekly use for academic purposes (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Reported applications included generating summaries of complex topics, practicing clinical scenarios or multiple-choice questions (MCQs), clarifying difficult medical concepts, drafting assignments or research papers, and creating study schedules or reminders (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). These results are consistent with [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], who highlighted similar patterns of GenAI adoption in medical education. The additional purposes of use identified by the students in this study included generating reading notes, suggesting references or supplementary resources, and answering practice questions, further demonstrating the versatility of GenAI in supporting medical learning.\u003c/p\u003e\u003cp\u003eWhile the widespread adoption of GenAI reflects its potential to enhance personalized learning, efficiency, and academic productivity, it also raises important concerns. Overreliance on AI-generated content may limit the development of critical thinking and independent problem-solving skills. In addition, issues such as misinformation, plagiarism, data privacy, and academic integrity have been identified as potential risks in medical education [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Therefore, although GenAI holds promise as a powerful educational tool, there is a need for structured guidelines, ethical training, and institutional support to ensure that medical students use these tools responsibly and effectively.\u003c/p\u003e\n\u003ch3\u003eImplications of the study\u003c/h3\u003e\n\u003cp\u003eOn the basis of the findings of this study, several implications for medical education, policy, and practice are identified. First, the widespread ownership and frequent use of smartphones among medical students at FUHSI reveals the vital role of mobile technology as a major learning tool. As such, our findings highlight the need for medical schools to intentionally integrate mobile-based learning strategies into the curriculum, ensuring that students are guided to use smartphones productively rather than merely as social or entertainment devices. Second, our finding that a variety of medical applications are used by medical students demonstrates that students are actively utilizing technology to complement traditional learning methods. Therefore, institutional support in terms of providing technological infrastructure, subscribing to premium medical apps (e.g., \u003cem\u003eUpToDate\u003c/em\u003e), and training staff and students should be intensified to increase the quality of medical training by broadening access to authoritative, evidence-based resources.\u003c/p\u003e\u003cp\u003eFurthermore, the high level of awareness and frequent use of generative AI tools discovered in our study points to a shift in how medical students engage with information. While these tools offer clear benefits in terms of efficiency, independent learning, and academic support, their widespread adoption raises concerns about overreliance, misinformation, and academic integrity. Finally, our findings contribute to the growing body of literature on digital literacy in medical education, particularly within the African context.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eLimitations of the study\u003c/h2\u003e\u003cp\u003eWhile the findings of this study offer practical insights into the patterns of smartphone, medical app and GenAI use among medical students in Nigeria, several limitations are recognized. First, the scope of the study was limited to a single university in Nigeria, which may limit the generalizability of the findings. The category of medical students examined was also preclinical students, who may not truly have a pressing need for the use of core medical apps and GenAI at their levels. Therefore, future research can expand the scope by incorporating more universities and levels of study into the investigation. Additionally, the study focused primarily on the types, frequency and purpose of the use of these emerging learning tools in medication. Further studies can examine the correlation between the use of these tools and the performance of medical students.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study revealed that the usage patterns of smartphones, medical apps and GenAI among the medical students surveyed were high due to the accessibility, affordability and vital roles these tools play in facilitating independent learning in medical education. However, we observed that most of the medical apps used by the students surveyed were open access apps and that the students did not use core medical apps such as UpToDate due to a lack of subscription by the students. Additionally, most GenAI being used is general, so there is a need to introduce medical students to core medical GenAI, which will aid their learning as they proceed to the clinical stages.\u003c/p\u003e\n\u003ch3\u003eRecommendations\u003c/h3\u003e\n\u003cp\u003eOn the basis of the findings of this study, we recommend the following:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eUniversity management should formally integrate the use of smartphones, medical apps, and GenAI into the medical education curriculum.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe university should prioritize providing access to essential medical apps and GenAI platforms through institutional subscriptions\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eContinuous training and workshops should be organized for medical students to increase their digital literacy and skills in effectively utilizing smartphones, medical apps, and GenAI.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eAI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eArtificial Intelligence\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eApps\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eApplications\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eFUHSI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFederal University of Health Sciences, Ila-Orangun\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eGenAI\u003c/b\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics and Consent to Participate declarations\u003c/strong\u003e:\u0026nbsp;Ethical approval for this study was obtained from the Federal University of Health Sciences Ila Orangun Research and Ethics Committee. All procedures involving human participants were conducted in accordance with the ethical standards of the institutional research committee and the principles of the \u003cstrong\u003eDeclaration of Helsinki (2013 revision)\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e Participation was voluntary, and all respondents provided informed consent prior to completing the survey. Anonymity and confidentiality were assured, and no identifying information was collected.\u003c/p\u003e\n\u003cp\u003eConsent for Publication: This study did not involve the publication of any individual participant\u0026rsquo;s data in any form (including images, videos, or personal details). Therefore, consent for publication is not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials:\u0026nbsp;\u003c/strong\u003eThe raw data generated from respondents for this study can be found at https://drive.google.com/file/d/1YlMXO09rnLd7YDse30Wqe5jpfBpKq7m1/view?usp=sharing\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e The authors report no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration:\u0026nbsp;\u003c/strong\u003eThe authors\u0026nbsp;do not receive any funding from any individuals or organizations for the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e All authors contributed significantly to the conception, design, execution, and analysis of the study. O.B. conceptualized the study and developed the methodology. N. S, O. S and A.A. coordinated data collection. O. B drafted the initial manuscript. A. A contributed to data analysis and interpretation. All authors reviewed, revised, and approved the final version of the manuscript for submission.\u003c/p\u003e\n\u003cp\u003eAcknowledgements: The authors would like to acknowledge the support of the Federal University of Health Sciences, Ila-Orangun (FUHSI), and thank the students who participated in this study for their time and valuable responses. We also appreciate the contributions of colleagues and faculty members who provided guidance during the research process.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWhyte J. Smartphone. In: Beyes T, Holt R, Pias C, editors. The Oxford handbook of media, technology and organization studies. Oxford: Oxford University Press; 2019. pp. 1\u0026ndash;14. 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Interact J Med Res. 2024;13:e53616. doi:10.2196/53616\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Smartphones, medical apps, GenAI, medical students, mobile apps","lastPublishedDoi":"10.21203/rs.3.rs-7576725/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7576725/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eSmartphones, medical applications (apps) and generative artificial intelligence (GenAI) are prominent learning tools widely used in higher education. However, the pattern of use of these tools among medical students at the Nigerian Federal University of Health Sciences, Ila - Orangun, has not been studied. The study was based on seven objectives set out to identify the pattern of usage of smartphones, medical apps, and GenAI for medical education among preclinical university students.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e\u003cp\u003eA descriptive survey design was employed. Data were collected via a structured questionnaire distributed electronically via WhatsApp to 297 preclinical medical students (Years 1\u0026ndash;3) at the Federal University of Health Sciences, Ila-Orangun, between July 28th and August 28th, 2025. A total of 203 students responded, yielding a 75.5% response rate. The questionnaire, developed and validated by experts, covered smartphones, medical apps, and GenAI frequency and purpose. The data were analyzed via SPSS (version 22), and the results are presented in tables, frequencies, and charts.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf the 203 respondents, 43.3% (n\u0026thinsp;=\u0026thinsp;88) were male, and 56.7% (n\u0026thinsp;=\u0026thinsp;115) were female. All the students owned a smartphone, with 87.7% (n\u0026thinsp;=\u0026thinsp;178) using Android devices and 13.3% (n\u0026thinsp;=\u0026thinsp;25) using iPhones. A majority (81.3%, n\u0026thinsp;=\u0026thinsp;165) reported daily smartphone use of 1\u0026ndash;4 hours, 10.3% (n\u0026thinsp;=\u0026thinsp;21) more than 5 hours, and 8.4% (n\u0026thinsp;=\u0026thinsp;17) less than 1 hour. Primary purposes included reading lecture notes/ebooks, researching academic content online, and viewing medical videos. Medical app usage was widespread, with 87.7% (n\u0026thinsp;=\u0026thinsp;178) reporting installations and 68% using them daily or weekly; commonly used apps included anatomy tools, interactive learning platforms, and medical dictionaries. Generative AI tools were also highly utilized, with ChatGPT (98%) being the most frequently accessed tool, followed by grammar checkers (56.7%), Med-PaLM (28.1%), Gemini (28.1%), and Copilot (13.3%) for the purpose of generating summaries of complex topics, clarifying difficult concepts, and preparing exams.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis study revealed a high level of use of smartphones, medical applications, and generative AI among medical students, underscoring the importance of these technologies in contemporary medical education. Accordingly, universities should develop clear policies to guide and optimize the use of smartphones, medical apps, and GenAI for academic purposes.\u003c/p\u003e","manuscriptTitle":"Survey of Smartphones, Medical Mobile Apps and Generative AI Use among Medical Students in Nigeria: A Case Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-17 02:20:43","doi":"10.21203/rs.3.rs-7576725/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-24T04:33:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-23T18:05:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-13T19:17:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269375632936733703580265781635493265094","date":"2025-10-12T16:55:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18912952201637274289327038934990286969","date":"2025-10-11T07:27:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-05T15:02:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-29T14:23:33+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-29T05:08:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-27T17:33:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2025-09-27T10:24:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d15dba6e-5414-4cb7-b7c9-575acef54d3c","owner":[],"postedDate":"October 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-26T20:38:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-17 02:20:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7576725","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7576725","identity":"rs-7576725","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}