Abstract
Background
The Chinese government initiated the “Top-notch Students Training Program 2.0 for Basic Disciplines” to cultivate talent in foundational fields, including basic medicine. However, existing programs lack a systematic framework tailored to the specific needs of basic medicine students. This study proposes a novel cultivation model specifically designed for basic medicine students, integrating interdisciplinary research and addressing the unique challenges inherent in foundational medical education. Compared to existing international models such as MSTP in the U.S., which focuses predominantly on streamlined clinical-research integration, and WISE in Japan, emphasizing productivity through targeted doctoral training, this model uniquely incorporates comprehensive interdisciplinary teaching, structured research training mechanisms, and explicit quality assurance procedures. These enhancements specifically address previously identified gaps in holistic, systematic cultivation frameworks for top-notch basic medicine students, aligning closely with national educational strategies and global healthcare challenges.
Methods
This study employed a modified Delphi method conducted over three rounds. An initial indicator framework was developed by analyzing documents from 12 universities, primarily those participating in the “Top-notch Students Training Program 2.0 for Basic Disciplines.”Experts specializing in medical education and academic management were invited to evaluate the relevance and importance of the proposed indicators. During each Delphi round, experts provided ratings and qualitative feedback, which informed iterative refinements of the framework. Adjustments were made based on statistical thresholds (e.g., arithmetic mean < 4, full score ratio < 0.5, or variation coefficient > 0.25) and expert consensus. The process concluded with a finalized cultivation model, incorporating 5 primary indicators, 17 secondary indicators, and 63 tertiary indicators. To validate the model, statistical analysis was conducted to ensure its reliability, practicality, and alignment with the goals of top-notch student cultivation in basic medicine. The finalized framework emphasizes interdisciplinary integration, innovation, and research-based learning, reflecting the priorities identified in the Delphi process.
Results
The effective response rates for the three rounds were 84%, 100%, and 95%, respectively, with an expert authority coefficient of 0.89. Based on these consultations, the final model includes 5 primary indicators, 17 secondary indicators, and 63 tertiary indicators. The model emphasizes five core dimensions: cultivation philosophy, cultivation standards and objectives, curriculum and teaching, scientific research training, and quality assurance and evaluation.
Conclusions
The proposed model emphasizes a systematic approach, adaptability to environmental changes, and practical operability in the cultivation process. The five core dimensions—cultivation philosophy, cultivation standards and objectives, curriculum and teaching, scientific research training, and quality assurance and evaluation—are designed to work in harmony. This ensures seamless alignment throughout the cultivation process, promoting synergy between elements to optimize pathways for top-notch students in basic medicine.
Keywords: Top-notch students cultivation, Basic medicine major, Delphi method, Cultivation model
Background
In 2018, the Chinese government launched the “Top-notch Students Training Program 2.0 for Basic Disciplines,” aiming to establish a series of national talent cultivation bases for young elites. The program focuses on selecting and nurturing top-notch innovative students in basic disciplines to build a talent training system with Chinese characteristics that meets world-class standards. The term “top-notch students” or “top-notch talent” is currently mobilized in China as a global discourse that reflects the most aspired educational subjects for the 21st century [1–3]. Top-notch students are defined by exceptional academic performance, strong research abilities, and key competencies in both global and local contexts. They excel in intelligence, academic achievements, and practical skills, surpassing their peers. Beyond academic success, they have interdisciplinary integration, critical thinking, creativity, and teamwork skills, transforming innovation into practical outcomes. Additionally, they possess an international perspective, while contributing to human welfare.Basic medicine is a foundational discipline that delves into the essence and principles governing human life and the occurrences of diseases. It serves as the bedrock of medical education, providing a foundational knowledge framework encompassing disciplines such as physiology, pathology, and immunology, which are essential for the education and practice of medical professionals [4, 5]. The program officially incorporates basic medicine major to cultivate top-notch students, driving breakthroughs in gene editing, synthetic biology, single-cell omics, regenerative medicine, precision medicine, and biomedical innovation, while addressing key technological talent bottlenecks.
Recent global initiatives have made it increasingly evident that developing new training programs for exceptional individuals in fundamental disciplines is of critical importance. To bridge the gap between basic research and clinical practice, the United States’ Medical Scientist Training Program (MSTP), for example, employs a streamlined “2 + 3 + clinical rotation” model. This study seeks to address these gaps through a comprehensive nurturing approach tailored for students excelling in Chinese basic medical sciences. Utilizing the Delphi technique, the proposed model draws from international best practices and provides a structured framework designed to enhance the global competitiveness of medical education.
The “Top-notch Students Training Program 2.0 for Basic Disciplines.” include globally renowned universities such as Peking University, Shanghai Jiao Tong University, Fudan University, and Zhejiang University, along with top domestic medical universities like Nanjing Medical University and Southern Medical University. With a longstanding emphasis on basic medical education, these universities provide abundant teaching resources, exceptional faculty, and advanced laboratory facilities. They have developed specialized research directions in basic medicine, achieved significant scientific outcomes, and established diverse cultivation models, including the integrated eight-year undergraduate-to-doctorate model, the nine-year continuous undergraduate-master-doctorate model, and the international joint bachelor-master cultivation model.
Many countries have launched specialized programs or related research to cultivate top-notch innovative students in basic medicine. Stanford University has a long-standing commitment to biomedical research and currently requires each student to complete an in-depth, mentored “scholarly concentration”. Duke University has implemented a research-based curriculum in basic medicine, aiming to cultivate future medical leaders through rigorous medical research study and practice [6–8]. MSTP widely adopted in U.S. medical colleges, focuses on an integrated path for top students in basic medicine, featuring a 2–3 year research phase seamlessly linked to medical coursework and clinical internships, thereby reducing time costs [9, 10]. Japan aims to enhance medical students productivity in areas such as medicine experimentation, neuroscience, and neurology through the Doctoral Program for World-leading Innovative & Smart Education (WISE), addressing the demand for high-level basic medicine talent [11]. In China, universities explore unique paths for cultivating top-notch students in basic medicine through mentorship, small-class teaching, deep integration with digital-intelligent learning, and interdisciplinary training [12–16].
Current research and practice in cultivating top-notch students in the basic medicine major lack the integration of key elements and a well-structured framework that distinguishes them from regular students. This has led to systemic deficiencies across universities, characterized by unclear and inconsistent indicators and insufficient motivation for adjustments and optimization of training directions and program features. Furthermore, new universities aspiring to establish top-notch student programs in basic medicine face challenges due to the absence of referable, operational models. Accordingly, this study aims to identify the core elements essential to the cultivation of top-notch students in basic medicine within the context of the “Top-notch Students Training Program 2.0 for Basic Disciplines”. It will explore relevant heterogeneous indicators and develop a comprehensive model to serve as a guide for institutions in refining and optimizing existing programs while providing a practical reference framework for universities seeking to establish such programs, thereby enhancing the overall quality of talent cultivation in basic medicine.
Methods
Research design
This study employs the Delphi method, a structured expert consultation technique developed by the RAND Corporation in the 1950s. Designed to facilitate expert consensus through anonymization and iterative feedback, the method mitigates individual biases, groupthink, and authority influence, promoting objective collective decision-making [17]. This study employed a three-round Delphi method to comprehensively solicit expert opinions [18–22]. The expert participation rates were 84% in the first round, 100% in the second round, and 95% in the third round. The overall expert authority coefficient (Cr = 0.89) indicated that the experts were highly familiar with the research topic and possessed strong judgment capabilities, ensuring the reliability of the method and the scientific validity of the findings.
For indicator screening and adjustment, clear statistical criteria were applied: indicators with an arithmetic mean below 4, a full score ratio below 50%, or a coefficient of variation above 0.25 were considered for adjustment or removal. Additionally, qualitative feedback from experts was systematically reviewed, summarized, and integrated by the research team after each Delphi round. Indicators receiving significant qualitative critique, including concerns about redundancy, ambiguity, or limited alignment with the cultivation objectives, were revisited and either revised or excluded accordingly. Expert opinion divergences were resolved through two approaches: (1) statistical screening and adjustment of data, and (2) a feedback mechanism inviting experts to re-evaluate indicators with significant disagreements. These approaches effectively addressed differences in expert opinions and progressively refined the indicator framework.
The selection of expert samples strictly adhered to the requirements of the Delphi method. The research team established explicit selection criteria: (1) holding at least a master’s degree, with preference for doctoral degree holders; (2) holding at least a mid-level academic title, with priority given to associate or full professors; (3) a minimum of five years’ experience in medical education or academic management; and (4) demonstrated expertise in basic medicine or interdisciplinary medical education research. Ultimately, 21 qualified experts from leading Chinese universities were invited to participate.The sample size range of 15–25 experts ensured the authority of the expert group while avoiding the complexity of handling excessive data.
An initial indicator framework was established through a comprehensive analysis of documents from the 12 participating universities, forming the basis for the first-round questionnaire. Experts feedback was evaluated for consensus and variability, informing the modification, addition, or removal of indicators. A second-round questionnaire followed, and the process concluded once all indicators met statistical criteria, with no further revisions proposed. The research team validated the final indicators and optimized the model to successfully complete the study.
Participant sample
The selection of participants in the Delphi process is crucial. Participants must possess extensive knowledge and practical experience, which may include academic researchers, industry experts, or seasoned practitioners [23]. Typically, 15 to 30 participants are chosen to balance broad input with manageable complexity [24, 25]. This study established the following selection criteria: (1) a master’s degree or higher; (2) a mid-level or higher professional title; (3) at least five years of experience in basic medical education or management; and (4) a commitment to the field and adherence to research ethics.
Sources of indicators
Primary data were collected from 12 universities participating in the “Top-notch Students Training Program 2.0 in Basic Medicine,” including talent cultivation program documents, admission brochures, and official website news. (1) Talent cultivation program documents define objectives, courses, teaching methods, research activities, and assessment frameworks. These documents form the core elements of the cultivation model. (2) Admission brochures outline admission methods, selection criteria, and policies, reflecting student entry requirements and academic levels. (3) Official website news supplements cultivation information by capturing students’ academic performance, practical achievements, and educational outcomes.
Questionnaire design
The questionnaire was structured into three sections to ensure effective guidance and iterative convergence of expert opinions. The first section provides instructions, introducing the research background, objectives, and significance to familiarize experts with the study’s core content and the purpose of the questionnaire. The second section presents the main content, explaining the meaning of each indicator and employing a five-point Likert scale (5 = very important, 4 = fairly important, 3 = moderately important, 2 = less important, 1 = not important) for scoring. Experts are also invited to comment on each item and offer additional suggestions. The third section includes an expert profile, comprising age, years of experience, academic title, position, and highest degree. The Expert Judgment Basis Coefficient (Ca) captures four aspects: work experience, theoretical analysis, understanding of domestic and international peers, and intuitive judgment. Each aspect is assessed at high, medium, and low levels, with corresponding weights as follows: theoretical analysis (0.5, 0.4, 0.3), practical experience (0.3, 0.2, 0.1), understanding of peers (0.1, 0.1, 0.05), and intuitive judgment (0.1, 0.1, 0.05). The Expert Familiarity Score (Cs) measures familiarity with the subject matter across five levels: very familiar (1.0), familiar (0.8), moderately familiar (0.6), unfamiliar (0.4), and very unfamiliar (0.2). With informed consent, the questionnaires were distributed through email and on-site consultations, with each round expected to be completed within one week. The process took place from August 25 to September 30, 2024.
Statistical analysis
Questionnaire data were entered using Microsoft Excel 2021, with SPSS 22.0 employed for statistical analysis, including calculations of arithmetic means, full score ratios, coefficients of variation, coordination coefficients, and chi-square tests. Disagreements during the Delphi process were resolved through structured discussions among the research team and experts, where each round’s comments were reviewed collectively to reach a consensus. Indicators were adjusted based on two key criteria: (1) statistical thresholds (arithmetic mean < 4, full score ratio < 0.5, or variation coefficient > 0.25) [25]and (2) qualitative expert feedback. In total, three Delphi rounds were conducted, with each round refining the indicator framework until all indicators met the established criteria. The final model includes 5 primary indicators, 17 secondary indicators, and 63 tertiary indicators.
Results
Participant demographics
The research group pre-selected 25 experts, with 21 participating in the first round (84% participation). The second round retained all 21 experts (100% participation), while the third round included 20 participants (95.24% participation). Among the 21 experts (including the non-participant in the third round), 18 hold doctoral degrees and 3 hold master’s degrees. The cohort comprises 8 full professors, 9 associate professors, and 4 mid-level professionals. Seven experts specialize in medical education management, while 14 are engaged in basic medical education. The average age of the experts is 44.38 ± 9.76 years, with a mean professional experience of 19.42 ± 12.5 years.
Reliability of expert consultation
The study evaluated the reliability of the expert consultation using three indicators: expert participation rate, authority coefficient, and expert opinion coordination degree. The expert participation rates were 84% in the first round, 100% in the second round, and 95.24% in the third round. The Expert Authority Coefficient (Cr) was assessed using the Ca and Cs, calculated as Cr = (Ca + Cs) / 2, resulting in an average Cr of 0.89. Since an authority coefficient above 0.7 is considered valid, the selected experts meet the Delphi study’s requirements. The coordination coefficients (W) for the first and second rounds were 0.237 and 0.260, indicating expert disagreement. In the third round, W decreased to 0.103. However, all rounds yielded a chi-square P-value of 0.00 (< 0.01), confirming the reliability and validity of the results (Table 1).
Table 1.
Three rounds of consultation expert opinion coordination degree
| Round | W2 | X2 | P |
|---|---|---|---|
| 1 | 0.237 | 453.757 | 0.00 |
| 2 | 0.260 | 535.930 | 0.00 |
| 3 | 0.103 | 171.579 | 0.00 |
The first round result
In the first round, the questionnaire included 6 primary indicators, 17 secondary indicators, and 69 tertiary indicators. Based on the degree of expert consensus (arithmetic mean < 4, full score ratio < 0.5, variation coefficient > 0.25), the first round identified 1 primary indicator, “Cultivation Mechanism,” 4 secondary indicators (e.g., “Elite Education Philosophy”), and 36 tertiary indicators (e.g., “Medical Scientist”) that did not meet the criteria. The primary indicator “Cultivation Mechanism” (arithmetic mean 3.71, full score ratio 0.33, variation coefficient 0.27) failed to meet retention criteria. Its secondary indicator “Organizational Mechanism” and 10 related tertiary indicators, including “Comprehensive Selection” “College Entrance Examination Selection” and “Applications from Other Majors” also fell short. After reviewing expert feedback, the research group concluded that this indicator and its sub-indicators do not align with the study and cannot sufficiently support the primary indicator, warranting their removal [26, 27]. Simultaneously, the secondary and tertiary indicators under the primary indicator “Examination and Evaluation” had high failure rates. These included one secondary indicator, “Degree Awarding” and 11 tertiary indicators, such as “Outcome Evaluation” “Process Evaluation” and “Comprehensive Quality Evaluation”. The primary indicator “Cultivation Mechanism” did not meet statistical thresholds. Experts noted that this indicator primarily reflected external organizational processes and overlapped with other primary indicators, such as “Cultivation Standards and Objectives.” As it lacked direct relevance to the core needs of top-notch student cultivation, as it was decided to remove it to streamline the model [28, 29]. Based on expert feedback, the research group concluded that these indicators did not reflect the specific characteristics of assessing top-notch students in basic medicine and could be applied to other majors. Therefore, they should be removed or revised.
We received 28 expert suggestions, of which 16 were accepted after discussion by the research group, leading to adjustments in the indicator system. This involved the addition and adjustment of 1 primary indicator, “Cultivation Platforms,” 8 secondary indicators such as “Excellence and Innovation” and “Interdisciplinary Collaboration” and 39 tertiary indicators such as “Research-Oriented Talent” and “Medical Educator”.
The second round result
In the second round, the questionnaire included 6 primary indicators, 21 secondary indicators, and 72 tertiary indicators. One primary indicator, “Cultivation Platforms,” along with 2 secondary indicators“Single Cultivation Platform” and“Interdisciplinary Cultivation Platform”and 9 tertiary indicators, such as “Ideals and Beliefs” failed to meet the established standards. After discussing the “Cultivation Platforms” (arithmetic mean 3.9, full score ratio 0.38, variation coefficient 0.26), we concluded that, as an external factor influencing the model, it reflects the cultivation environment but cannot serve as a core indicator in model construction [2, 30]. Through expert consultation, we determined that maintaining 5 primary indicators “Cultivation Philosophy” “Cultivation Objectives” “Curriculum and Teaching”, “Scientific Research Training” and “Quality Assurance and Evaluation” provides a clear framework for the model, rendering additional primary indicators unnecessary.
We gathered 20 expert suggestions, 15 of which were approved following discussions by the research group, leading to the addition and adjustment of 1 primary indicator, 3 secondary indicators, and 18 tertiary indicators. For instance, the primary indicator “Cultivation Objectives” was renamed “Cultivation Standards and Objectives” to more clearly encompass both indicators [31]. Additionally, new tertiary indicators such as “Critical Thinking Education”and “Collaboration between Medical and Education” were added to better support the “Educational Philosophy”.
The third round result
In the third round, the questionnaire included 5 primary indicators, 17 secondary indicators, and 63 tertiary indicators. All indicators had mean values above 4, full score frequencies over 50%, and variation coefficients below 0.25. Since none of the 20 experts provided further suggestions for adjusting or removing indicators offering only minor naming recommendations. The research group decided against conducting a fourth round of consultation. The scores for indicators from the third round are shown in the Table 2.
Table 2.
Third round expert scoring result
| Primary Indicator | Secondary Indicator | Tertiary Indicator | Mean | SD | Full Score Frequency | CV |
|---|---|---|---|---|---|---|
| Cultivation philosophy | Excellence and Innovation | Excellent Education | 4.95 | 0.22 | 0.95 | 0.04 |
| Innovation Education | 4.90 | 0.30 | 0.90 | 0.06 | ||
| Critical Thinking Education | 4.85 | 0.48 | 0.90 | 0.10 | ||
| Interdisciplinary and Collaborative | Combination of Science Research and Education | 4.80 | 0.51 | 0.85 | 0.11 | |
| Interdisciplinary Collaboration | 4.85 | 0.36 | 0.85 | 0.07 | ||
| Collaboration between Medicine and Education | 4.66 | 0.88 | 0.9 | 0.19 | ||
| Cultivation Standards and Objectives | Cultivation Standards | Research-Oriented Talent | 4.75 | 0.89 | 0.90 | 0.19 |
| Interdisciplinary Talent | 4.65 | 0.96 | 0.85 | 0.21 | ||
| Medical Educator | 4.60 | 0.92 | 0.75 | 0.20 | ||
| Integrated Knowledge Structure | Multidisciplinary Background Knowledge | 4.85 | 0.36 | 0.85 | 0.07 | |
| Comprehensive and Frontier Knowledge in Basic Medicine | 5.00 | 0.00 | 1.00 | 0.00 | ||
| Integrated “Basic-Clinical” Knowledge | 4.85 | 0.36 | 0.85 | 0.07 | ||
| Global Public Health and Social Medicine Knowledge | 4.85 | 0.36 | 0.85 | 0.07 | ||
| Modern Medical Education Knowledge | 4.75 | 0.43 | 0.75 | 0.09 | ||
| Multidimensional Competencies | Interdisciplinary Research and Innovation Capability | 4.95 | 0.22 | 0.95 | 0.04 | |
| Application of Artificial Intelligence | 4.70 | 0.46 | 0.70 | 0.10 | ||
| Information Management Skills | 4.80 | 0.40 | 0.80 | 0.08 | ||
| Global Competence | 4.45 | 0.67 | 0.55 | 0.15 | ||
| Research Leadership and Team Collaboration Skills | 4.85 | 0.36 | 0.85 | 0.07 | ||
| Medical Knowledge and Lifelong Learning Skills | 5.00 | 0.00 | 1.00 | 0.00 | ||
| Medical Education and Teaching Skills | 4.75 | 0.43 | 0.75 | 0.09 | ||
| Value Guidance | Spirit of the Scientist | 5.00 | 0.00 | 1.00 | 0.00 | |
| Spirit of the Educator | 4.85 | 0.36 | 0.85 | 0.07 | ||
| Sense of Medical Responsibility | 4.90 | 0.44 | 0.95 | 0.09 | ||
| Curriculum and Teaching | General Education Courses | Ideological and Humanities Courses | 4.75 | 0.54 | 0.80 | 0.11 |
| Mathematics and Science Courses | 4.65 | 0.48 | 0.65 | 0.10 | ||
| Tool courses | 4.75 | 0.43 | 0.75 | 0.09 | ||
| Professional Integrated Courses | Basic Medicine Integrated Courses | 4.85 | 0.36 | 0.85 | 0.07 | |
| Organ System Integrated Courses | 4.85 | 0.36 | 0.85 | 0.07 | ||
| Public Health and Social Medicine Courses | 4.85 | 0.36 | 0.85 | 0.07 | ||
| Interdisciplinary and Research-Oriented Courses | “Basic Medicine + X” Courses | 4.90 | 0.30 | 0.90 | 0.06 | |
| Frontier Courses in Basic Medicine | 5.00 | 0.00 | 1.00 | 0.00 | ||
| Multidisciplinary Lecture Courses | 4.75 | 0.43 | 0.75 | 0.09 | ||
| Research Methods and Critical Thinking Courses | 5.00 | 0.00 | 1.00 | 0.00 | ||
| International and Online Courses | Global MOOC Courses | 4.70 | 0.46 | 0.70 | 0.10 | |
| Top-University Practice Courses | 4.60 | 0.49 | 0.60 | 0.11 | ||
| Problem and Research-Oriented Teaching | Seminar-Based Teaching | 4.80 | 0.40 | 0.80 | 0.08 | |
| Problem-Based Learning (PBL) | 4.90 | 0.30 | 0.90 | 0.06 | ||
| Team-Based Learning (TBL) | 4.75 | 0.54 | 0.80 | 0.11 | ||
| Case-Based Learning (CBL) | 4.80 | 0.51 | 0.85 | 0.11 | ||
| Research-Based Learning (RBL) | 4.85 | 0.36 | 0.85 | 0.07 | ||
| Digital-Intelligence Integrated Teaching | 4.70 | 0.56 | 0.75 | 0.12 | ||
| Scientific Research Training | Academic Activities | High-Level Academic Lectures | 4.95 | 0.22 | 0.95 | 0.04 |
| Advanced Academic Seminars | 4.95 | 0.22 | 0.95 | 0.04 | ||
| National and International Academic Conferences | 4.85 | 0.36 | 0.85 | 0.07 | ||
| National and International Innovation Competitions | 4.80 | 0.40 | 0.80 | 0.08 | ||
| Research Training Mechanisms | Laboratory Rotation Mechanism | 4.75 | 0.43 | 0.75 | 0.09 | |
| Research Project Training Mechanism | 4.90 | 0.30 | 0.90 | 0.06 | ||
| International Collaborative Training Mechanism | 4.60 | 0.49 | 0.60 | 0.11 | ||
| Mentoring Mechanisms | Primary Mentor with Multiple Assistants | 4.65 | 0.96 | 0.85 | 0.21 | |
| Joint Mentorship | 4.45 | 0.97 | 0.65 | 0.22 | ||
| Quality Assurance and Evaluation | Student Quality Assurance | Independent Admissions Selection | 4.85 | 0.36 | 0.85 | 0.07 |
| Interdisciplinary Selection | 4.85 | 0.36 | 0.85 | 0.07 | ||
| Voluntary Diversion and Elimination | 4.80 | 0.40 | 0.80 | 0.08 | ||
| Phased Assessment and Elimination | 4.50 | 0.97 | 0.70 | 0.22 | ||
| Ethics and Medical Moral Evaluation | Academic Integrity | 4.95 | 0.22 | 0.95 | 0.04 | |
| Medical Ethics | 4.95 | 0.22 | 0.95 | 0.04 | ||
| Academic and Research Innovation Evaluation | High-Level Academic Thesis | 4.80 | 0.40 | 0.80 | 0.08 | |
| High-Quality Dissertation | 4.95 | 0.22 | 0.95 | 0.04 | ||
| Breakthroughs in Research Projects | 4.60 | 0.92 | 0.75 | 0.20 | ||
| Research Patents and Awards | 4.45 | 0.97 | 0.65 | 0.22 | ||
| Transformation of Innovative Achievements | 4.55 | 0.86 | 0.75 | 0.19 |
Model presentation
After the third round of research and investigation, we used EdrawMax software to create the final model diagram (Fig. 1).
Fig. 1.
The model diagram
The bar chart illustrates the changes in the number of indicators across three Delphi rounds, categorized into first-level, second-level, and third-level indicators (Fig. 2). Indicators were adjusted or removed based on expert consensus and qualitative feedback. For example, the primary indicator “Cultivation Mechanism” was removed because it overlapped significantly with “Cultivation Standards and Objectives,” lacking distinct relevance to the top-notch students’ unique needs in basic medicine. Similarly, the secondary indicator “Degree Awarding” was considered excessively broad and unsuitable specifically for evaluating elite basic medical students, prompting its removal. Additionally, indicators like “Single Cultivation Platform” were removed due to their external and environmental nature, rather than being core components integral to the cultivation model’s internal operational framework.
Fig. 2.
Indicators by Levels Across Delphi Rounds
Validation and practical considerations
Although the proposed cultivation model has undergone rigorous validation through the Delphi method, initial pilot implementation was conducted at university. Preliminary feedback indicates the model’s feasibility and positive reception from both students and faculty. However, practical implementation has revealed several barriers, such as limited interdisciplinary teaching expertise among faculty, resource constraints, and administrative challenges in cross-departmental coordination. Recommended strategies to overcome these barriers include structured cross-disciplinary faculty training, enhanced resource allocation from institutional leadership, and establishing dedicated administrative support to facilitate effective interdisciplinary collaboration.
Discussion
Characteristics of the cultivation model
The cultivation of top-notch students majoring in basic medicine, aligned with the demands of global competition in medical science and technology, cannot be achieved through conventional medical education models. Instead, it requires the establishment of an autonomous and heterogeneous cultivation framework that caters to the specific needs of these students. This framework emphasizes the design of distinctive characteristics, focusing primarily on systematic integration. Medical education is a synergistic process composed of interdependent elements, where the functionality and value of the whole exceed the sum of its individual components [32, 33]. Each element interacts dynamically with others to form a cohesive educational model. The core elements of this model “Cultivation Philosophy” “Cultivation Standards and Objectives” “Curriculum and Teaching” “Scientific Research Training” and “Quality Assurance and Evaluation” are designed to work in harmony, ensuring seamless alignment throughout the cultivation process. The model emphasizes not only the development of individual components but also on the interdependence between them [34]. For example, the teaching of integrated professional courses influences other aspects, such as research training, by shaping students academic interests and career choices. Specifically, the difficulty of teaching these courses can play a pivotal role in determining students’ research directions in basic medicine.
The model addresses both the commonalities between top-notch students in basic medicine and regular students, such as shared courses in basic and clinical medicine and common assessment methods, as well as the heterogeneity of training for top students. This includes specialized components like integrated organ system courses, frontier courses, and multidisciplinary lecture courses, alongside the application of digital-intelligent teaching methods, teaching-research integration, and innovative evaluations of academic research.The study effectively underscores the significance of interdisciplinary courses and research, exemplified by initiatives like the “Basic Medicine + Artificial Intelligence” course, which integrates bioinformatics and machine learning to enhance students’ analytical skills in complex medical data. Courses such as “Frontiers in Basic Medicine” and “Interdisciplinary Collaboration” further expose students to cutting-edge fields like regenerative medicine and gene editing, fostering innovation. Additionally, pedagogical approaches, including PBL, CBL, and TBL, are utilized to strengthen interdisciplinary collaboration. As a pilot innovation project, the interdisciplinary curriculum is still in its early stages, and thus lacks comprehensive statistical data to demonstrate how interdisciplinary concepts are fully integrated into curriculum design or how learning outcomes are assessed. Given its status as a key initiative, future efforts are expected to generate more robust data and evidence to evaluate its effectiveness. Additionally, challenges such as limited faculty expertise, resource constraints, and difficulties in cross-disciplinary coordination are inherent in the early phases of implementation. Addressing these challenges through co-teaching models, enhanced faculty training, and international collaborations will further optimize the interdisciplinary education framework. Additionally, we have carefully designed the structural hierarchy of the model, establishing layered relationships among its components [35]. A three-tier indicator structure was created to ensure vertical integration across different stages of the training process, optimizing the operational flow of top-notch student cultivation and maximizing quality.
The model emphasizes environmental adaptability to meet challenges posed by rapid advancements in medical technologies, continuous breakthroughs in basic research, and an increasing focus on sustainable higher education. The COVID-19 pandemic has particularly highlighted the need for the model to align with external environments. It aligns with national strategies such as the “Top-notch Students Training Program 2.0 for Basic Disciplines,” the “Plan for Strengthening Basic Disciplines,” and the “101 Basic Disciplines Plan,” reflecting policy guidance and addressing the national need for innovative talent [36]. The model also adapts to advanced technological environments, such as big data, bioinformatics, and artificial intelligence(AI), which have profoundly transformed medical research and education, ensuring that knowledge and competency objectives respond effectively to technological developments. Moreover, the model embraces multicultural environments by fostering global competence through international courses, academic exchanges, and research collaborations, preparing students to excel in global roles and build partnerships across cultures [37, 38]. This holistic approach ensures the cultivation of top-notch students capable of adapting to evolving global scientific and healthcare challenges [39, 40].
This model carefully considers the division of responsibilities among multiple stakeholders, including education administrators, instructors, academic mentors, and assessment experts. Each plays a vital role in ensuring the smooth operation of the model, with coordinated efforts across all stages. The model also emphasizes the importance of clear indicator definitions, ensuring that every evaluation standard is easily understood, interpreted, and applied by all participants. This focus on clarity and precision enhances the model practicality, making it highly operational in real-world settings and adaptable for continuous improvement based on feedback and evolving educational needs.
While designed within the context of Chinese higher education, the framework incorporates universal dimensions such as interdisciplinary integration, quality assurance, and innovation in medical education, making it adaptable to diverse educational systems globally. For resource-limited institutions, specific dimensions can be prioritized based on local needs and available resources. For instance, such institutions could focus on curriculum design by integrating research and teaching or building interdisciplinary courses, even with limited faculty or infrastructure. Additionally, forming partnerships with international institutions can provide access to advanced research opportunities and global academic networks. These strategies ensure the effective adoption of the framework, even in less resource-intensive contexts.
Core elements of the model
The cultivation model establishes a comprehensive, multi-tiered framework comprising five core elements: “Cultivation Philosophy” “Cultivation Standards and Objectives” “Curriculum and Teaching” “Scientific Research Training” and “Quality Assurance and Evaluation”. Each component operates within a distinct structural layer, ensuring seamless alignment of strategic direction, operational execution, and quality oversight throughout the cultivation process.
At the strategic layer, the cultivation philosophy, standards, and objectives provide the foundational framework that guides the overall trajectory of talent development. This layer integrates insights from traditional medical education with advanced paradigms such as the “New Medicine Discipline Initiative,” emphasizing excellence, innovation, interdisciplinarity, and the integration of research and teaching within medical and educational collaboration [41]. It establishes a holistic, future-oriented vision designed to cultivate research-oriented professionals, interdisciplinary experts, and medical educators. Through a multidimensional perspective spanning technical, cognitive, and collaborative competencies, the model defines three core outcomes: complex knowledge structures, multidimensional skill development, and value-based education. These outcomes address the essential knowledge, abilities, and values required of top-notch basic medical students, who are expected to surpass their peers by mastering knowledge suitable for the Medicine 4.0 era, including interdisciplinary foundations, advanced biomedical science, and integrated basic-clinical knowledge. Additionally, students develop seven essential competencies, such as interdisciplinary research capacity and AI application, ensuring they are well-equipped for the demands of a highly interconnected and transdisciplinary medical landscape [42]. The model further instills core values rooted in scientific rigor, educational commitment, and social responsibility in healthcare.
At the operational layer, the focus is on implementing a four-in-one course system covering general education, professional integration, interdisciplinary research, and internationalized online learning. This curriculum structure aligns with the strategic objectives, ensuring that the educational philosophy is realized through student engagement. General education courses nurture mathematical and analytical thinking, digital literacy, and cultural awareness. Professional integrated courses combine core biomedical knowledge with system-based modules, integrating disciplines such as anatomy, physiology, molecular biology, immunology, and pathology, along with organ system courses covering the cardiovascular, respiratory, and endocrine systems. Interdisciplinary and research-oriented courses foster the convergence of medical science, engineering, and informatics, incorporating cutting-edge research into the curriculum while cultivating students’ methodological expertise and critical thinking [43]. To foster a global outlook, the model integrates international modules, medical MOOCs, and high-impact practical courses from prestigious global institutions, offering students diverse learning experiences and encouraging cross-cultural collaboration [44, 45].
At the quality assurance layer, the model emphasizes continuous evaluation through two essential modules: medical ethics and academic innovation. This layer monitors students’ adherence to ethical and professional standards, ensuring the cultivation of integrity throughout their academic journey. It shifts the evaluation focus beyond traditional metrics, such as research publications, to emphasize outcomes such as participation in major research initiatives, patents, awards, and the translation of innovations into practice [46]. The model encourages students to engage in translational research, bridging basic science with clinical applications, thereby enhancing their practical contributions to medical advancement.
Application of the model
The model primarily addresses two categories of universities. For those already participating in the “Top-notch Students Training Program 2.0 for Basic Disciplines,” it provides a guiding framework for optimizing student cultivation. Institutions can leverage the model to assess essential components, including cultivation philosophy, cultivation standards and objectives, curriculum and teaching, scientific research training, and quality assurance and evaluation. For example, universities with underdeveloped philosophical frameworks can use the model to establish a focus on excellence, innovation, integration, and collaboration. Those with weak curriculum integration can reference the model structure to enhance both basic medical courses and “basic-clinical” integrated courses. Additionally, institutions relying heavily on conventional teaching methods can explore innovative approaches such as argumentative teaching, research-based learning, and digital integration [47, 48].
Furthermore, the model addresses the disconnect often observed between different stages of cultivation by fostering synergy among key stakeholders, including educational administrators, faculty, academic mentors, and assessment experts. This ensures coordinated efforts throughout the entire cultivation process.
For universities applying to the “Top-notch Students Training Program 2.0 for Basic Disciplines,” the model provides not only a strategic roadmap for talent development but also practical guidance for resource integration and process optimization. It enables institutions to allocate teaching staff effectively, capitalize on strengths in research and education, and construct a distinctive cultivation system. This includes designing innovative curricula, employing advanced teaching methodologies, and integrating frontier scientific research projects to ensure that students develop comprehensive expertise, research capabilities, and holistic qualities. Universities with extensive international partnerships can leverage the model international curriculum as a platform to foster cross-cultural competence and adaptability through global academic exchanges and collaborative research initiatives. Strengthening cooperation with leading global universities and research institutions will further enhance students’ academic achievements and research capacities in international medical contexts. Additionally, the model supports the establishment of joint research mentorship programs, wherein domestic and international mentors guide students through advanced research practices, preparing them to tackle academic challenges within multicultural environments and enhancing their ability to solve complex medical problems.
Universities with extensive international partnerships can leverage the model’s international curriculum as a platform to foster cross-cultural competence and adaptability through global academic exchanges and collaborative research initiatives. Frenk emphasize that fostering cross-cultural skills and global academic collaboration is crucial for preparing health professionals to address complex health challenges in an increasingly interdependent world [49]. Strengthening cooperation with leading global universities and research institutions further enhances students’ academic achievements and research capacities in international medical contexts [9]. Additionally, the model supports the establishment of joint research mentorship programs, wherein domestic and international mentors guide students through advanced research practices. These initiatives prepare students to tackle academic challenges within multicultural environments, equipping them with the skills to solve complex medical problems and contribute meaningfully to global healthcare advancements [12].
The incorporation of theoretical frameworks significantly enhances the cultivation model for top-notch students in basic medicine. Subotnik underscore the critical role of structured mentorship and deliberate practice in talent development, which aligns closely with the mentorship mechanisms embedded in the model [50]. Ryan and Deci’s Self-Determination Theory emphasizes the core dimensions of autonomy, competence, and relatedness, offering a robust foundation for enhancing student motivation through interdisciplinary and research-based learning approaches [51]. Kolb’s experiential learning theory advocates for the integration of practical engagement and reflective learning, providing a structured approach to knowledge acquisition [52]. Deardorff’s intercultural competence framework highlights the necessity of equipping students to address global healthcare challenges, emphasizing the value of international courses and cross-cultural collaboration in fostering global competence [53].
Global applicability and adaptability
While the framework is designed within the context of Chinese higher education, its core dimensions are universally applicable. For international adoption, the framework can be customized to align with local policies, resources, and cultural contexts. For example, universities in resource-limited settings can prioritize specific dimensions (e.g., curriculum design) while building capacity for interdisciplinary research and quality assurance. International collaborations can also leverage the framework to foster global competence and cross-cultural collaboration among students.
Limitations
This study has several limitations that must be acknowledged. First, the use of the Delphi method, while effective in reaching consensus, may introduce biases such as dominant opinions or insufficient diversity among experts. Although anonymity and iterative feedback minimized this impact, further validation with a more diverse expert base is recommended. Second, the framework has been piloted in a limited number of universities. Broader testing across diverse educational institutions, including those with different resources and academic focuses, is necessary to evaluate the model’s generalizability and adaptability.The model’s ability to adapt to rapidly evolving fields, such as artificial intelligence, bioinformatics, and interdisciplinary research, remains a challenge. Continuous updates and refinements are essential to ensure its relevance in addressing emerging global challenges in medical education. These limitations highlight the need for future research to expand the framework’s applicability and robustness in diverse and dynamic educational contexts.
For universities already participating in the ‘Top-notch Students Training Program 2.0,’ this model serves as a framework to optimize existing components, such as curriculum integration and research mentoring. For institutions aspiring to join the program, the model provides a roadmap for resource allocation, interdisciplinary course design, and mentoring systems. By emphasizing stakeholder coordination, the model ensures seamless implementation across all phases of student cultivation, fostering stronger alignment with institutional goals and national strategies.
Conclusions
The proposed model emphasizes a systematic approach, adaptability to environmental changes, and practical operability. While rooted in the Chinese higher education context, this cultivation model integrates universally applicable dimensions such as interdisciplinary research integration and quality assurance mechanisms. Interdisciplinary research is increasingly recognized as a cornerstone of innovation, as it fosters creative problem-solving and the generation of new knowledge across disciplines [54]. Additionally, ensuring educational quality through robust quality assurance mechanisms is essential for maintaining institutional accountability and adapting to global challenges [55].
For global implementation, institutions must adapt the model to align with local educational policies, cultural characteristics, and resource availability. In resource-constrained settings, universities might prioritize curriculum innovations, such as embedding research-based learning into existing courses, which has been proven effective in improving student engagement and academic outcomes [56]. International collaborations can further enhance research training capacity, while joint mentorship programs with global partners are particularly effective in developing students’ multicultural competencies and research skills [57].
This model also underscores the importance of systematic design and operational practicality. Key strategies include structured faculty training, the establishment of interdisciplinary research platforms, and cross-departmental collaboration [58]. On a global scale, institutions may focus on different priorities based on their contexts: resource-rich environments can emphasize comprehensive curriculum integration and meticulous quality monitoring, while resource-limited settings might benefit from optimizing global partnerships and leveraging digital resources like MOOCs to enhance educational quality [57]. By integrating these context-sensitive strategies, the model provides a flexible framework for promoting academic excellence and fostering global collaboration.
Acknowledgements
The authors thank all the experts who participated in the study.
Abbreviations
- MSTP
The medical scientist training program
- WISE
Doctoral program for world-leading innovative & smart education
- Ca
The expert judgment basis coefficient
- Cs
The expert familiarity score
- Cr
The expert authority coefficient
- PBL
Problem-based learning
- TBL
Team-based learning
- CBL
Case-based learning
- RBL
Research-based learning
- AI
Artificial intelligence
Author contributions
GN performed the research and wrote the main manuscript. YTQ and FFW revised partial content. JJH designed this work.
Funding
This research was supported by Project of Chongqing Graduate Education Teaching Reform Research (yjg201022).
Data availability
“The datasets analyzed during the current study are available from the corresponding author on reasonable request”.
Declarations
Ethics approval and consent to participate
This study was approved by the Ethics Committee of the Army Medical University. The experiment was explained to all participants to allow for questions or comments, and informed consent was obtained from all participants. Data and identity were kept confidential and used only for the purpose of this study. All procedures were performed in accordance with relevant guidelines and regulations.
Consent for publication
Not applicable. Competing interests the authors have no relevant financial or non-financial interests to disclose.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
“The datasets analyzed during the current study are available from the corresponding author on reasonable request”.