Educational Framework to Strengthen the Variant Scientist Workforce in Clinical Genomics

Educational Framework to Strengthen the Variant Scientist Workforce in Clinical Genomics | 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 Educational Framework to Strengthen the Variant Scientist Workforce in Clinical Genomics Dina Marek-Yagel, Rotem Greenberg, Michal Naftali, Ofer Isakov, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8737686/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background The integration of genomics into clinical care has created an urgent need for accurate, standardized variant interpretation. Variant scientists (VS) play a central role in translating sequencing results into clinically actionable findings, yet no formal framework currently supports their professional development. We surveyed practicing VS to identify training routes and knowledge gaps and used these insights to design a training program. Methods A national survey delivered to every practicing VS assessed training background, learning, access to interpretation tools, and professional challenges. A multidisciplinary committee defined core competencies and developed a phased training program. Results Thirty-eight respondents were included. Professional training was mostly acquired through observation of expert analysts (42.1%), followed by hands-on experience (39.5%). Only 18% participated in a dedicated VS course. Key challenges included keeping pace with evolving guidelines (55.2%) and copy number variant (CNV) analysis (47.3%). To help narrow these gaps and support more unified VS training, we developed a comprehensive framework combining theoretical modules, practical rotations, and assessment via a standardized proficiency test, supported by institutional forums and national meetings. Conclusion We deigned a unified, scalable VS training model to address core educational gaps and support standardization of variant interpretation training nationally and internationally. Figures Figure 1 Figure 2 Figure 3 Introduction Over the past decade, variant interpretation has evolved into a dynamic and specialized field, shaped by rapid advancements in sequencing technologies, data resources, and clinical practice guidelines. Since the publication of the ACMG/AMP guidelines in 2015 1 , followed by Clingen general guidelines 2 , 3 and gene specific specifications 4 , 5 , the process of variant classification has become significantly more complex. This complexity is driven by continual advances in sequencing technologies, including whole-genome and long-read platforms, expanding population and functional datasets, advanced prediction tools, and multiplex functional assays that need to be integrated for each variant. These challenges led to the emergence of a new professional role: the Variant Scientist (VS). Within this landscape, VS have become central to clinical genomics, transforming raw variant data into classifications that guide diagnosis, treatment selection, and prevention. Accurate variant interpretation enables early and precise care, whereas misclassification can lead to missed or incorrect diagnoses, inappropriate interventions, and unnecessary patient anxiety . 4 The scientific literature reflects a rich body of established curricula designed for physicians, genetic counselors, and related roles across multiple medical specialties 5 – 8 . These professionals benefit from well-defined educational pathways and rigorous accreditation standards. For example, in many countries, genetic counselors are required to complete a master’s degree in an accredited genetic counseling program and pass a national certification exam, ensuring a standardized level of competence across institutions. 9 Similarly physicians specializing in medical genetics complete clinical residencies and practical training programs and receive continuous education to reflect ongoing advances in genomics and clinical practice. In the same time, laboratory directors and molecular technologists are required to complete an M.Sc. or PhD, respectively, with formal training, followed by board certification to demonstrate competency in genetic testing, variant interpretation, and clinical reporting 6 . In contrast, education and training pathways for variant scientists are still largely unstandardized, relying on informal, locally defined processes that vary widely in rigor and content. Several postgraduate and continuing education programs offer training relevant to variant interpretation. These range from formal academic degrees to industry-led online courses. For example, the Graduate Certificate in Genomic Counselling & Variant Interpretation at the University of British Columbia provides a structured master’s-level program focused on clinical variant interpretation and counseling skills 10 In parallel, accessible online courses such as “Interpreting Genomic Variation: Overcoming Challenges in Diverse Populations” (FutureLearn) address variant classification guidelines and interpretation in diverse populations 11 . In addition, several companies also offer practical training modules; for instance, Geneyx provides a Clinical Variant Interpretation Analysis Course designed to teach evidence-based curation using real-life cases and platform tools 12 . Inconsistent training and practices across laboratories may contribute to discordant competency among VS across laboratories, leading to clinically significant discrepancies reported in the literature and resulting in diagnostic delays and clinical uncertainty 13 . Despite the central role of VS in clinical genomics, to our knowledge, no comprehensive educational framework has been published specifically for their training. This represents a critical deficiency in the genomic workforce pipeline, particularly as contemporary variant science now demands proficiency in a rapidly expanding array of databases, functional and in silico resources, and evolving ACMG/AMP and Clingen guidelines. To address this challenge, we developed a structured VS training program designed to empower professionals from diverse academic and clinical backgrounds with core variant interpretation competencies designed to bridge educational gaps among new and practicing VS revealed by our survey.” This work presents the development, implementation, and early impact of our VS training model, which is intended to be both practical and scalable. Methods Assessment of Educational Needs To characterize educational gaps and current learning practices in variant interpretation, we conducted an anonymous nationwide survey among professionals acting as VS across 10 genetic centers employing about 50 VS overall. The survey evaluated onboarding processes, access to mentorship, familiarity with ACMG/AMP and ClinGen guidelines, database utilization, approaches to continuous learning, and perceived barriers to achieving and sustaining interpretive competency. Items also addressed self-reported preparedness, confidence, and unmet educational needs. Full survey questionnaire, and survey answers is provided in Supplementary 1 and 2. Curriculum Design and Competency Mapping Structured curriculum design and development were conducted by a multidisciplinary working group comprising a senior VS, a clinical geneticist, a genetic counselor, a bioinformatician, and genomic laboratory representatives. The group applied principles of competency-based medical education to define the knowledge, skills, and professional attributes required for independent variant interpretation. Results Training Background, Practice Variation, and Needs Of the 39 survey submissions received, 38 were eligible for analysis. Job titles varied across centers: most respondents were VS (39.4%, 15/38), followed by laboratory technicians (28.9%, 10/38) and genetic counselors (18.4% 9/38). Participants represented diverse levels of experience, institutional settings, and variant interpretation workflows (Supplementary Materials). Training pathways were heterogeneous. Only 18% (7/38) respondents reported completing a dedicated VS course (in Israel or abroad), and 34% (13/38) reported learning primarily through structured workplace training. Notably, 42% of participants indicated that they acquired key competencies mainly through observation of expert analysts. In addition, 39.5% (15/38) reported substantial self-directed learning, and 18.4% (7/38) reported learning exclusively through self-directed, hands-on experience. To map the key challenges faced by VS, participants were asked to select one or more domains they found particularly difficult (Fig. 1 ). The most frequently reported challenge was keeping up to date with evolving guidelines (55.2%, 21/38), followed by copy number variant (CNV) analysis (deletions/duplications; 47.3%, 18/38). Challenges related to CNV analysis were more frequently reported by respondents with fewer years of experience, whereas difficulties in keeping up with evolving guidelines were reported across all experience levels. Fewer respondents reported workforce shortages and limited access to bioinformatics tools and databases (28.9%, 11/38). Difficulty understanding the clinical context was reported by 26.3% (10/38) of respondents and was not selected by genetic counselors. Variant classification was reported by 23.6% (9/38). The least frequently mentioned challenge was report drafting, selected by 10.5% (4/38) of participants. CNV- copy number variation. To better understand the methodologies used by VS, the survey evaluated four key domains: tertiary analysis tools, ClinGen specifications, scoring systems, and access to a commercially licensed database for curated genetic variant classifications (the Human Genetic Mutation Database - HGMD 14 ) (Fig. 2 ). While VS uses commercial or proprietary tertiary analysis tools (such as Franklin 16 or Varsome 17 ) as part of their variant interpretation workflow, the degree to which they rely on these tools for final classification varies. Specifically, 65.8% (25/38) participants indicated that they use these tools alongside additional classification methods, integrating the automated suggestions with manual review, database cross-referencing, and expert curation. Notably, three respondents reported relying solely on the automated classification output from the tools. In contrast, eight participants stated that they do not rely on these tools at all when determining final variant classification. Adoption of ClinGen guidance was very high (89.5%, 34/38). Most participants (32/38, 84.2%) reported using formal scoring systems for variant classification 15 , although one participant was not even familiar with this method. Use of HGMD database was common (57.9%, 22/38), and an additional 13.1% (5/38) indicated they would like to use them but lacked access (e.g., no account). Professional development and community engagement were assessed through questions on conference and forum participation. Overall, 42% (16/38) of participants attended international conferences, and 58% (22/38) engaged regularly in professional forums or enrichment lectures. However, attendance varied across institutions, and several respondents noted a lack of time, institutional support, or awareness of opportunities. Finally, respondents were asked to suggest areas for improvement in the field. The dominant themes included lack of standardization, unclear or unavailable documentation of classification processes, limited mentorship opportunities. To address these gaps, respondents recommended establishing a national, structured training program; creating a shared knowledge base for variant interpretation; and encouraging collaboration to reduce discrepancies. Variant Scientists Training Development Drawing on the survey results, the committee’s recommendations, and insights from the literature, we developed a structured VS training program to equip professionals from diverse academic and clinical backgrounds with core variant interpretation competencies and to bridge educational gaps (Fig. 3 ). Development and Implementation The foundational phase delivers core theoretical content through structured instructional sessions covering genomic variation, variant nomenclature, inheritance models, and gene-disease curation. Learners were introduced to NGS workflows and the common output file formats (e.g FASTQ, BAM, and VCF) with emphasis on quality metrics. Training also includes guided hands-on practice in the use of key genetic databases, In silico variant prediction tools and variant interpretation software. Instruction included adherence to institutional standard operating procedures (SOPs). Foundational ethics, communication, and regulatory topics were interwoven throughout. The phase integrated wet bench observations (DNA extraction, library preparation, and sequencing) via laboratory site visits. This phase spanned approximately four weeks. The complete training curriculum is provided in the Supplementary 3 Experiential Learning and Case-Based Practice The experiential phase emphasized applied learning through integration into clinically active VS workflows. Trainees conducted independent variant interpretation on clinical cases, participated in multidisciplinary review meetings, and received direct mentorship. Each trainee was accompanied by a senior, experienced VS for more than 50 cases, followed by structured feedback. This phase lasted 3–6 months, and spanned approximately 500 hours adjusted based on the learner’s background and entry pathway. Competency-Based Assessment A summative assessment at the conclusion of training consisted of blind interpretation of 20 clinical cases. This assessment evaluated the ability to apply ACMG/AMP criteria, synthesize multi-source evidence, and produce clear, accurate variant classifications. Trainees who met the benchmark performance were certified to provide independent clinical interpretation as practicing variant scientists. Discussion The rapid expansion of genomic testing has created a critical need for a highly trained and consistently workforce capable of performing accurate and reproducible variant interpretation. Despite this growing demand, a multi-center survey revealed considerable heterogeneity in training routes, access to interpretive tools, and proficiency levels. Participants consistently reported reliance on informal learning, limited mentorship, and substantial difficulty keeping pace with rapidly evolving guidelines, particularly the frequent release of ClinGen gene and disease specifications (CSpec) and the anticipated ACMG /AMP v4 update 20 . These findings highlight a structural gap in the genomic workforce pipeline: the absence of a formalized, standardized training framework for VS. The structured training program was developed directly address this gap. By integrating theoretical instruction, case analysis, and a sustained professional network, the program provides both foundational education and mechanisms for continuous competency development. A central strength of the program lies in the integration of weekly multidisciplinary case review meetings. Through systematic, team-based evaluation, these meetings enabled resolution of complex or borderline variant cases that often remain unresolved in routine workflows. This structured approach also fostered cross-disciplinary knowledge exchange and reinforced consistent application of ACMG/AMP and ClinGen criteria. Such practices are essential for reducing inter-laboratory variability, a persistent challenge in variant interpretation. Across inter-laboratory result comparisons, concordance rates of only ~ 54% among laboratories, with clinically significant discordances affecting up to 11% of variants, and even higher rates observed in disease-specific contexts such as oncology and epilepsy. While interpretation of variants is complex and may stem from multiple reasons, the finding that there are significant differences in how different VS use guidelines and tools, and that these differences contribute to this inconsistency, is clinically important. Beyond the initial training period, establishing a long-term professional network proved pivotal. Monthly educational forums provide continuous updates in clinical genetics, emerging technologies (e.g., long-reads sequencing, methylation profiles, optical genome mapping), and evolving interpretive frameworks. This structure reflects a core principle of variant interpretation: proficiency is not static but requires ongoing engagement with the rapidly evolving genomic landscape. The strong participation observed across sessions indicates that such networks are both needed and well-received and may serve as a model for continued professional development in other genomic disciplines. The training program was developed and implemented within a large health care system; adaptations may be necessary for other international contexts with different regulatory, technological, or educational infrastructures. Participants reported improved interpretive confidence and independence; however, standardized pre- and post-training assessment tools were unavailable during the initial implementation. Future iterations will incorporate objective evaluation methods, such as concordance testing and longitudinal performance tracking, to rigorously measure program impact. Our findings highlight the pressing need for a structured, standardized training framework for VS, tailored to knowledge gaps. The marked variability in current learning pathways and interpretive approaches underscores the risk of inconsistent classifications and reinforces the importance of defining core competencies and providing access to guided and case training The program demonstrated strong feasibility, improved interpretive consistency, and fostered a collaborative national learning community. As genomic testing continues toexpand globally, investment in standardized and adaptive training frameworks will be essential. This model offers a scalable foundation that can serve as a framework for establishing internationally recognized standards for variant scientist training and certification. Declarations Author Contributions Conceptualization: DM.Y., S.BS.; Writing-original draft: D.MY.; Visualization: R.G.; Tailored program design: D.MY., O.I., R.G., M.N., S.BS.; Supervision: S.BS.; Writing-review & editing: DM.Y., O.I.,R.G., M.N., S.BS. Funding The authors declare that this research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Ethics approval and consent to participate The study involved an anonymous, voluntary survey of healthcare professionals and did not include patients, human biological material, or identifiable human data. The Community Institutional Review Board (Helsinki Committee) of Clalit Health (Tel Aviv, Israel) granted a formal exemption from ethics approval on February 9, 2026, as the research did not constitute human subject research. Participation was voluntary, and informed consent was waived by the IRB due to the anonymous and non-interventional nature of the study. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki Declaration of generative AI in scientific writing During the preparation of this work, the author(s) used https://chatgpt.com/ in order to refine the language. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication. Conflict of Interest The authors declare no conflict of interest. Data Availability Statement All relevant data are included in the manuscript files and supplemental materials. References Richards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med Off J Am Coll Med Genet . 2015;17(5):405-424. doi:10.1038/gim.2015.30 Abou Tayoun AN, Pesaran T, DiStefano MT, et al. Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion. Hum Mutat . 2018;39(11):1517-1524. doi:10.1002/humu.23626 Sequence Variant Interpretation - ClinGen | Clinical Genome Resource. Accessed July 9, 2025. https://clinicalgenome.org/working-groups/sequence-variant-interpretation/ Makhnoon S, Shirts BH, Bowen DJ. Patients’ perspectives of variants of uncertain significance and strategies for uncertainty management. J Genet Couns . 2019;28(2):313-325. doi:10.1002/jgc4.1075 Demmer LA, Waggoner DJ. Professional medical education and genomics. Annu Rev Genomics Hum Genet . 2014;15:507-516. doi:10.1146/annurev-genom-090413-025522 Allen S, Loong L, Garrett A, et al. Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey. J Med Genet . 2024;61(4):305-312. doi:10.1136/jmg-2023-109645 Greenberg R, Averbuch NS, Sagi-Dain L, et al. Genetics first approach: Expanding the utility of genetic testing by nongeneticist physicians. Genet Med Off J Am Coll Med Genet . 2025;27(10):101530. doi:10.1016/j.gim.2025.101530 Patterson WG, Ward LD. Genetics and Genomics Education for Physician Assistant Students: A Review of the Literature. J Physician Assist Educ Off J Physician Assist Educ Assoc . 2023;34(1):62-68. doi:10.1097/JPA.0000000000000491 MacFarlane IM, Zierhut H. Promoting the integration of genetic counseling education and research across the spectrum of learners at a large academic institution. J Genet Couns . 2024;33(1):250-254. doi:10.1002/jgc4.1810 Graduate Certificate in Genomic Counselling and Variant Interpretation | UBC Academic Calendar. Accessed January 23, 2026. https://vancouver.calendar.ubc.ca/faculties-colleges-and-schools/faculty-medicine/graduate-certificate-genomic-counselling-and-variant-interpretation FutureLearn. Interpreting Genomic Variation - Online Course. FutureLearn. Accessed December 5, 2025. https://www.futurelearn.com/courses/interpreting-genomic-variation-overcoming-challenges-in-diverse-populations Geneyx Courses: Clinical Variant Interpretation Analysis. Udemy. Accessed December 5, 2025. https://www.udemy.com/course/geneyx-courses-clinical-variant-interpretation-analysis/ Amendola LM, Jarvik GP, Leo MC, et al. Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium. Am J Hum Genet . 2016;98(6):1067-1076. doi:10.1016/j.ajhg.2016.03.024 HGMD® home page. Accessed December 26, 2025. https://www.hgmd.cf.ac.uk/ac/index.php Tavtigian SV, Harrison SM, Boucher KM, Biesecker LG. Fitting a naturally scaled point system to the ACMG/AMP variant classification guidelines. Hum Mutat . 2020;41(10):1734-1737. doi:10.1002/humu.24088 Franklin. Accessed July 27, 2025. https://franklin.genoox.com/analysis-tool/analysis/workbench/10392 VarSome The Human Genomics Community. VarSome. Accessed December 18, 2025. https://varsome.com/ Durkie M, Cassidy EJ, Berry I, et al. ACGS Best Practice Guidelines for Variant Classification in Rare Disease 2024. Rubin AF, Stone J, Bianchi AH, et al. MaveDB 2024: a curated community database with over seven million variant effects from multiplexed functional assays. Genome Biol . 2025;26(1):13. doi:10.1186/s13059-025-03476-y Overview of DRAFT ACMG/AMP v4 Sequence Variant Guidelines - ClinGen | Clinical Genome Resource. Accessed July 29, 2025. https://clinicalgenome.org/tools/clingen-summer-workshop-series-2023/sept-15-2023/ Additional Declarations No competing interests reported. Supplementary Files SurveyQuestionnaireSupplementary1.docx Supplementary2VariantScientistsSurvey.xlsx Supplementary3Curriculum.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 17 May, 2026 Reviews received at journal 26 Apr, 2026 Reviewers agreed at journal 10 Mar, 2026 Reviewers invited by journal 24 Feb, 2026 Editor invited by journal 20 Feb, 2026 Editor assigned by journal 12 Feb, 2026 Submission checks completed at journal 11 Feb, 2026 First submitted to journal 11 Feb, 2026 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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Since the publication of the ACMG/AMP guidelines in 2015\u003csup\u003e1\u003c/sup\u003e, followed by Clingen general guidelines\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e and gene specific specifications\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, the process of variant classification has become significantly more complex. This complexity is driven by continual advances in sequencing technologies, including whole-genome and long-read platforms, expanding population and functional datasets, advanced prediction tools, and multiplex functional assays that need to be integrated for each variant. These challenges led to the emergence of a new professional role: the Variant Scientist (VS). Within this landscape, VS have become central to clinical genomics, transforming raw variant data into classifications that guide diagnosis, treatment selection, and prevention. Accurate variant interpretation enables early and precise care, whereas misclassification can lead to missed or incorrect diagnoses, inappropriate interventions, and unnecessary patient anxiety .\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe scientific literature reflects a rich body of established curricula designed for physicians, genetic counselors, and related roles across multiple medical specialties \u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. These professionals benefit from well-defined educational pathways and rigorous accreditation standards. For example, in many countries, genetic counselors are required to complete a master\u0026rsquo;s degree in an accredited genetic counseling program and pass a national certification exam, ensuring a standardized level of competence across institutions. \u003csup\u003e9\u003c/sup\u003e Similarly physicians specializing in medical genetics complete clinical residencies and practical training programs and receive continuous education to reflect ongoing advances in genomics and clinical practice. In the same time, laboratory directors and molecular technologists are required to complete an M.Sc. or PhD, respectively, with formal training, followed by board certification to demonstrate competency in genetic testing, variant interpretation, and clinical reporting\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn contrast, education and training pathways for variant scientists are still largely unstandardized, relying on informal, locally defined processes that vary widely in rigor and content.\u003c/p\u003e \u003cp\u003eSeveral postgraduate and continuing education programs offer training relevant to variant interpretation. These range from formal academic degrees to industry-led online courses. For example, the Graduate Certificate in Genomic Counselling \u0026amp; Variant Interpretation at the University of British Columbia provides a structured master\u0026rsquo;s-level program focused on clinical variant interpretation and counseling skills\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e In parallel, accessible online courses such as \u0026ldquo;Interpreting Genomic Variation: Overcoming Challenges in Diverse Populations\u0026rdquo; (FutureLearn) address variant classification guidelines and interpretation in diverse populations\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In addition, several companies also offer practical training modules; for instance, Geneyx provides a Clinical Variant Interpretation Analysis Course designed to teach evidence-based curation using real-life cases and platform tools\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Inconsistent training and practices across laboratories may contribute to discordant competency among VS across laboratories, leading to clinically significant discrepancies reported in the literature and resulting in diagnostic delays and clinical uncertainty\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Despite the central role of VS in clinical genomics, to our knowledge, no comprehensive educational framework has been published specifically for their training. This represents a critical deficiency in the genomic workforce pipeline, particularly as contemporary variant science now demands proficiency in a rapidly expanding array of databases, functional and in silico resources, and evolving ACMG/AMP and Clingen guidelines. To address this challenge, we developed a structured VS training program designed to empower professionals from diverse academic and clinical backgrounds with core variant interpretation competencies designed to bridge educational gaps among new and practicing VS revealed by our survey.\u0026rdquo;\u003c/p\u003e \u003cp\u003eThis work presents the development, implementation, and early impact of our VS training model, which is intended to be both practical and scalable.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eAssessment of Educational Needs\u003c/p\u003e \u003cp\u003eTo characterize educational gaps and current learning practices in variant interpretation, we conducted an anonymous nationwide survey among professionals acting as VS across 10 genetic centers employing about 50 VS overall. The survey evaluated onboarding processes, access to mentorship, familiarity with ACMG/AMP and ClinGen guidelines, database utilization, approaches to continuous learning, and perceived barriers to achieving and sustaining interpretive competency. Items also addressed self-reported preparedness, confidence, and unmet educational needs. Full survey questionnaire, and survey answers is provided in Supplementary 1 and 2.\u003c/p\u003e \u003cp\u003eCurriculum Design and Competency Mapping\u003c/p\u003e \u003cp\u003eStructured curriculum design and development were conducted by a multidisciplinary working group comprising a senior VS, a clinical geneticist, a genetic counselor, a bioinformatician, and genomic laboratory representatives. The group applied principles of competency-based medical education to define the knowledge, skills, and professional attributes required for independent variant interpretation.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTraining Background, Practice Variation, and Needs\u003c/h2\u003e \u003cp\u003eOf the 39 survey submissions received, 38 were eligible for analysis. Job titles varied across centers: most respondents were VS (39.4%, 15/38), followed by laboratory technicians (28.9%, 10/38) and genetic counselors (18.4% 9/38). Participants represented diverse levels of experience, institutional settings, and variant interpretation workflows (Supplementary Materials).\u003c/p\u003e \u003cp\u003eTraining pathways were heterogeneous. Only 18% (7/38) respondents reported completing a dedicated VS course (in Israel or abroad), and 34% (13/38) reported learning primarily through structured workplace training. Notably, 42% of participants indicated that they acquired key competencies mainly through observation of expert analysts. In addition, 39.5% (15/38) reported substantial self-directed learning, and 18.4% (7/38) reported learning exclusively through self-directed, hands-on experience.\u003c/p\u003e \u003cp\u003eTo map the key challenges faced by VS, participants were asked to select one or more domains they found particularly difficult (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The most frequently reported challenge was keeping up to date with evolving guidelines (55.2%, 21/38), followed by copy number variant (CNV) analysis (deletions/duplications; 47.3%, 18/38). Challenges related to CNV analysis were more frequently reported by respondents with fewer years of experience, whereas difficulties in keeping up with evolving guidelines were reported across all experience levels.\u003c/p\u003e \u003cp\u003eFewer respondents reported workforce shortages and limited access to bioinformatics tools and databases (28.9%, 11/38). Difficulty understanding the clinical context was reported by 26.3% (10/38) of respondents and was not selected by genetic counselors. Variant classification was reported by 23.6% (9/38). The least frequently mentioned challenge was report drafting, selected by 10.5% (4/38) of participants.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCNV- copy number variation.\u003c/p\u003e \u003cp\u003eTo better understand the methodologies used by VS, the survey evaluated four key domains: tertiary analysis tools, ClinGen specifications, scoring systems, and access to a commercially licensed database for curated genetic variant classifications (the Human Genetic Mutation Database - HGMD\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). While VS uses commercial or proprietary tertiary analysis tools (such as Franklin\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e or Varsome\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e) as part of their variant interpretation workflow, the degree to which they rely on these tools for final classification varies. Specifically, 65.8% (25/38) participants indicated that they use these tools alongside additional classification methods, integrating the automated suggestions with manual review, database cross-referencing, and expert curation. Notably, three respondents reported relying solely on the automated classification output from the tools. In contrast, eight participants stated that they do not rely on these tools at all when determining final variant classification. Adoption of ClinGen guidance was very high (89.5%, 34/38). Most participants (32/38, 84.2%) reported using formal scoring systems for variant classification\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, although one participant was not even familiar with this method. Use of HGMD database was common (57.9%, 22/38), and an additional 13.1% (5/38) indicated they would like to use them but lacked access (e.g., no account).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e Professional development and community engagement were assessed through questions on conference and forum participation. Overall, 42% (16/38) of participants attended international conferences, and 58% (22/38) engaged regularly in professional forums or enrichment lectures. However, attendance varied across institutions, and several respondents noted a lack of time, institutional support, or awareness of opportunities.\u003c/p\u003e \u003cp\u003eFinally, respondents were asked to suggest areas for improvement in the field. The dominant themes included lack of standardization, unclear or unavailable documentation of classification processes, limited mentorship opportunities. To address these gaps, respondents recommended establishing a national, structured training program; creating a shared knowledge base for variant interpretation; and encouraging collaboration to reduce discrepancies.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eVariant Scientists Training Development\u003c/h3\u003e\n\u003cp\u003eDrawing on the survey results, the committee\u0026rsquo;s recommendations, and insights from the literature, we developed a structured VS training program to equip professionals from diverse academic and clinical backgrounds with core variant interpretation competencies and to bridge educational gaps (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eDevelopment and Implementation\u003c/h3\u003e\n\u003cp\u003eThe foundational phase delivers core theoretical content through structured instructional sessions covering genomic variation, variant nomenclature, inheritance models, and gene-disease curation. Learners were introduced to NGS workflows and the common output file formats (e.g FASTQ, BAM, and VCF) with emphasis on quality metrics. Training also includes guided hands-on practice in the use of key genetic databases, In silico variant prediction tools and variant interpretation software. Instruction included adherence to institutional standard operating procedures (SOPs). Foundational ethics, communication, and regulatory topics were interwoven throughout. The phase integrated wet bench observations (DNA extraction, library preparation, and sequencing) via laboratory site visits. This phase spanned approximately four weeks. The complete training curriculum is provided in the Supplementary 3\u003c/p\u003e\n\u003ch3\u003eExperiential Learning and Case-Based Practice\u003c/h3\u003e\n\u003cp\u003eThe experiential phase emphasized applied learning through integration into clinically active VS workflows. Trainees conducted independent variant interpretation on clinical cases, participated in multidisciplinary review meetings, and received direct mentorship. Each trainee was accompanied by a senior, experienced VS for more than 50 cases, followed by structured feedback. This phase lasted 3\u0026ndash;6 months, and spanned approximately 500 hours adjusted based on the learner\u0026rsquo;s background and entry pathway.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCompetency-Based Assessment\u003c/h2\u003e \u003cp\u003eA summative assessment at the conclusion of training consisted of blind interpretation of 20 clinical cases. This assessment evaluated the ability to apply ACMG/AMP criteria, synthesize multi-source evidence, and produce clear, accurate variant classifications. Trainees who met the benchmark performance were certified to provide independent clinical interpretation as practicing variant scientists.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe rapid expansion of genomic testing has created a critical need for a highly trained and consistently workforce capable of performing accurate and reproducible variant interpretation. Despite this growing demand, a multi-center survey revealed considerable heterogeneity in training routes, access to interpretive tools, and proficiency levels. Participants consistently reported reliance on informal learning, limited mentorship, and substantial difficulty keeping pace with rapidly evolving guidelines, particularly the frequent release of ClinGen gene and disease specifications (CSpec) and the anticipated ACMG /AMP v4 update \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. These findings highlight a structural gap in the genomic workforce pipeline: the absence of a formalized, standardized training framework for VS.\u003c/p\u003e \u003cp\u003eThe structured training program was developed directly address this gap. By integrating theoretical instruction, case analysis, and a sustained professional network, the program provides both foundational education and mechanisms for continuous competency development.\u003c/p\u003e \u003cp\u003eA central strength of the program lies in the integration of weekly multidisciplinary case review meetings. Through systematic, team-based evaluation, these meetings enabled resolution of complex or borderline variant cases that often remain unresolved in routine workflows. This structured approach also fostered cross-disciplinary knowledge exchange and reinforced consistent application of ACMG/AMP and ClinGen criteria. Such practices are essential for reducing inter-laboratory variability, a persistent challenge in variant interpretation. Across inter-laboratory result comparisons, concordance rates of only\u0026thinsp;~\u0026thinsp;54% among laboratories, with clinically significant discordances affecting up to 11% of variants, and even higher rates observed in disease-specific contexts such as oncology and epilepsy. While interpretation of variants is complex and may stem from multiple reasons, the finding that there are significant differences in how different VS use guidelines and tools, and that these differences contribute to this inconsistency, is clinically important.\u003c/p\u003e \u003cp\u003eBeyond the initial training period, establishing a long-term professional network proved pivotal. Monthly educational forums provide continuous updates in clinical genetics, emerging technologies (e.g., long-reads sequencing, methylation profiles, optical genome mapping), and evolving interpretive frameworks. This structure reflects a core principle of variant interpretation: proficiency is not static but requires ongoing engagement with the rapidly evolving genomic landscape. The strong participation observed across sessions indicates that such networks are both needed and well-received and may serve as a model for continued professional development in other genomic disciplines.\u003c/p\u003e \u003cp\u003eThe training program was developed and implemented within a large health care system; adaptations may be necessary for other international contexts with different regulatory, technological, or educational infrastructures. Participants reported improved interpretive confidence and independence; however, standardized pre- and post-training assessment tools were unavailable during the initial implementation. Future iterations will incorporate objective evaluation methods, such as concordance testing and longitudinal performance tracking, to rigorously measure program impact.\u003c/p\u003e \u003cp\u003eOur findings highlight the pressing need for a structured, standardized training framework for VS, tailored to knowledge gaps. The marked variability in current learning pathways and interpretive approaches underscores the risk of inconsistent classifications and reinforces the importance of defining core competencies and providing access to guided and case training\u003c/p\u003e \u003cp\u003eThe program demonstrated strong feasibility, improved interpretive consistency, and fostered a collaborative national learning community. As genomic testing continues toexpand globally, investment in standardized and adaptive training frameworks will be essential. This model offers a scalable foundation that can serve as a framework for establishing internationally recognized standards for variant scientist training and certification.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: DM.Y., S.BS.; Writing-original draft: D.MY.; Visualization: R.G.; Tailored program design: D.MY., O.I., R.G., M.N., S.BS.; Supervision: S.BS.; Writing-review \u0026amp; editing: DM.Y., O.I.,R.G., M.N., S.BS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that this research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study involved an anonymous, voluntary survey of healthcare professionals and did not include patients, human biological material, or identifiable human data. The Community Institutional Review Board (Helsinki Committee) of Clalit Health (Tel Aviv, Israel) granted a formal exemption from ethics approval on February 9, 2026, as the research did not constitute human subject research. Participation was voluntary, and informed consent was waived by the IRB due to the anonymous and non-interventional nature of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the ethical principles of the Declaration of Helsinki\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI in scientific writing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work, the author(s) used https://chatgpt.com/ in order to refine the language. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll relevant data are included in the manuscript files and supplemental materials.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRichards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. \u003cem\u003eGenet Med Off J Am Coll Med Genet\u003c/em\u003e. 2015;17(5):405-424. doi:10.1038/gim.2015.30\u003c/li\u003e\n\u003cli\u003eAbou Tayoun AN, Pesaran T, DiStefano MT, et al. Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion. \u003cem\u003eHum Mutat\u003c/em\u003e. 2018;39(11):1517-1524. doi:10.1002/humu.23626\u003c/li\u003e\n\u003cli\u003eSequence Variant Interpretation - ClinGen | Clinical Genome Resource. Accessed July 9, 2025. https://clinicalgenome.org/working-groups/sequence-variant-interpretation/\u003c/li\u003e\n\u003cli\u003eMakhnoon S, Shirts BH, Bowen DJ. Patients\u0026rsquo; perspectives of variants of uncertain significance and strategies for uncertainty management. \u003cem\u003eJ Genet Couns\u003c/em\u003e. 2019;28(2):313-325. doi:10.1002/jgc4.1075\u003c/li\u003e\n\u003cli\u003eDemmer LA, Waggoner DJ. Professional medical education and genomics. \u003cem\u003eAnnu Rev Genomics Hum Genet\u003c/em\u003e. 2014;15:507-516. doi:10.1146/annurev-genom-090413-025522\u003c/li\u003e\n\u003cli\u003eAllen S, Loong L, Garrett A, et al. Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey. \u003cem\u003eJ Med Genet\u003c/em\u003e. 2024;61(4):305-312. doi:10.1136/jmg-2023-109645\u003c/li\u003e\n\u003cli\u003eGreenberg R, Averbuch NS, Sagi-Dain L, et al. Genetics first approach: Expanding the utility of genetic testing by nongeneticist physicians. \u003cem\u003eGenet Med Off J Am Coll Med Genet\u003c/em\u003e. 2025;27(10):101530. doi:10.1016/j.gim.2025.101530\u003c/li\u003e\n\u003cli\u003ePatterson WG, Ward LD. Genetics and Genomics Education for Physician Assistant Students: A Review of the Literature. \u003cem\u003eJ Physician Assist Educ Off J Physician Assist Educ Assoc\u003c/em\u003e. 2023;34(1):62-68. doi:10.1097/JPA.0000000000000491\u003c/li\u003e\n\u003cli\u003eMacFarlane IM, Zierhut H. Promoting the integration of genetic counseling education and research across the spectrum of learners at a large academic institution. \u003cem\u003eJ Genet Couns\u003c/em\u003e. 2024;33(1):250-254. doi:10.1002/jgc4.1810\u003c/li\u003e\n\u003cli\u003eGraduate Certificate in Genomic Counselling and Variant Interpretation | UBC Academic Calendar. Accessed January 23, 2026. https://vancouver.calendar.ubc.ca/faculties-colleges-and-schools/faculty-medicine/graduate-certificate-genomic-counselling-and-variant-interpretation\u003c/li\u003e\n\u003cli\u003eFutureLearn. Interpreting Genomic Variation - Online Course. FutureLearn. Accessed December 5, 2025. https://www.futurelearn.com/courses/interpreting-genomic-variation-overcoming-challenges-in-diverse-populations\u003c/li\u003e\n\u003cli\u003eGeneyx Courses: Clinical Variant Interpretation Analysis. Udemy. Accessed December 5, 2025. https://www.udemy.com/course/geneyx-courses-clinical-variant-interpretation-analysis/\u003c/li\u003e\n\u003cli\u003eAmendola LM, Jarvik GP, Leo MC, et al. Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium. \u003cem\u003eAm J Hum Genet\u003c/em\u003e. 2016;98(6):1067-1076. doi:10.1016/j.ajhg.2016.03.024\u003c/li\u003e\n\u003cli\u003eHGMD\u0026reg; home page. Accessed December 26, 2025. https://www.hgmd.cf.ac.uk/ac/index.php\u003c/li\u003e\n\u003cli\u003eTavtigian SV, Harrison SM, Boucher KM, Biesecker LG. Fitting a naturally scaled point system to the ACMG/AMP variant classification guidelines. \u003cem\u003eHum Mutat\u003c/em\u003e. 2020;41(10):1734-1737. doi:10.1002/humu.24088\u003c/li\u003e\n\u003cli\u003eFranklin. Accessed July 27, 2025. https://franklin.genoox.com/analysis-tool/analysis/workbench/10392\u003c/li\u003e\n\u003cli\u003eVarSome The Human Genomics Community. VarSome. Accessed December 18, 2025. https://varsome.com/\u003c/li\u003e\n\u003cli\u003eDurkie M, Cassidy EJ, Berry I, et al. ACGS Best Practice Guidelines for Variant Classification in Rare Disease 2024.\u003c/li\u003e\n\u003cli\u003eRubin AF, Stone J, Bianchi AH, et al. MaveDB 2024: a curated community database with over seven million variant effects from multiplexed functional assays. \u003cem\u003eGenome Biol\u003c/em\u003e. 2025;26(1):13. doi:10.1186/s13059-025-03476-y\u003c/li\u003e\n\u003cli\u003eOverview of DRAFT ACMG/AMP v4 Sequence Variant Guidelines - ClinGen | Clinical Genome Resource. Accessed July 29, 2025. https://clinicalgenome.org/tools/clingen-summer-workshop-series-2023/sept-15-2023/\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":"","lastPublishedDoi":"10.21203/rs.3.rs-8737686/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8737686/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe integration of genomics into clinical care has created an urgent need for accurate, standardized variant interpretation. Variant scientists (VS) play a central role in translating sequencing results into clinically actionable findings, yet no formal framework currently supports their professional development. We surveyed practicing VS to identify training routes and knowledge gaps and used these insights to design a training program.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA national survey delivered to every practicing VS assessed training background, learning, access to interpretation tools, and professional challenges. A multidisciplinary committee defined core competencies and developed a phased training program.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThirty-eight respondents were included. Professional training was mostly acquired through observation of expert analysts (42.1%), followed by hands-on experience (39.5%). Only 18% participated in a dedicated VS course. Key challenges included keeping pace with evolving guidelines (55.2%) and copy number variant (CNV) analysis (47.3%). To help narrow these gaps and support more unified VS training, we developed a comprehensive framework combining theoretical modules, practical rotations, and assessment via a standardized proficiency test, supported by institutional forums and national meetings.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eWe deigned a unified, scalable VS training model to address core educational gaps and support standardization of variant interpretation training nationally and internationally.\u003c/p\u003e","manuscriptTitle":"Educational Framework to Strengthen the Variant Scientist Workforce in Clinical Genomics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-27 14:34:41","doi":"10.21203/rs.3.rs-8737686/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"149031827705013098488509311489072769085","date":"2026-05-17T15:18:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-26T08:33:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248617695155243537202563709293454498887","date":"2026-03-10T07:20:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T12:05:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-20T10:57:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-12T06:35:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-11T18:45:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2026-02-11T18:42:22+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":"0a7452aa-35e8-4acc-b79b-6e7aeafaf7b7","owner":[],"postedDate":"February 27th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"149031827705013098488509311489072769085","date":"2026-05-17T15:18:38+00:00","index":77,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T14:34:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-27 14:34:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8737686","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8737686","identity":"rs-8737686","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}