Clinical Adaptability and Protected Research Time as Key Determinants of Core Competency: A Cross-sectional Study of China's "Dual-Track Integration" Clinical Professional Master’s Students

Clinical Adaptability and Protected Research Time as Key Determinants of Core Competency: A Cross-sectional Study of China's "Dual-Track Integration" Clinical Professional Master’s Students | 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 Clinical Adaptability and Protected Research Time as Key Determinants of Core Competency: A Cross-sectional Study of China's "Dual-Track Integration" Clinical Professional Master’s Students Jing ZHOU, Haosheng PENG, Haiman LIU, Jiacheng YUAN, Xiaoyan CHEN, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8708160/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background In China, the integrated training model for clinical medicine professional master’s students merges postgraduate education with standardized residency training. Trainees face dual pressures from clinical rotations and academic research, which may compromise competency development. However, the role of adjustable factors, particularly clinical practice adaptability and protected research time, is not well defined. Objective This study evaluated the current state of core competencies among these students and investigated the influence of clinical practice adaptability and the sufficiency of protected research time. Methods A multicenter, cross-sectional survey was administered in Guangdong Province between December 2024 and January 2025. Participants included 921 students from 41 national standardized residency training bases. Data were collected using structured questionnaires comprising the Core Competency Scale and the Clinical Practice Adaptability Scale. Analyses involved nonparametric tests and multiple linear regression. Results Core competency dimensions were ranked by mean score (highest to lowest): Professionalism, Patient Care, Communication and Collaboration, Lifelong Learning, Knowledge and Skills, and Teaching Capability. This profile indicated relative deficits in Teaching Capability and Knowledge and Skills. Univariate analyses revealed that total competency scores were significantly associated with gender, place of origin, adequacy of protected research time, role identity, stress attitude, and clinical practice adaptability ( p < 0.05). The regression model identified both clinical practice adaptability ( β = 0.425, p < 0.001) and adequacy of protected research time ( β = 0.079, p = 0.010) as independent, positive predictors of core competency, with adaptability being the strongest contributor. The model accounted for 21.7% of the score variance (Adjusted R ² =0.217). Conclusion Students in the integrated training model show an uneven development of core competencies. Interventions aimed at improving clinical practice adaptability and guaranteeing sufficient dedicated research time are essential for balanced competency growth. Training institutions should adopt focused measures, including establishing specialized clinical teaching teams and securing protected time for scholarly activities. Clinical professional master's students Dual-track integration Core competency Clinical practice adaptability Protected research time Graduate medical education China Introduction A central challenge in global medical education is how to effectively integrate clinical skills training with scholarly development within a constrained timeframe [1]. China’s “Dual-Track Integration” training model offers a distinctive institutional context for examining this issue. Since its full implementation in 2013, standardized residency training has become a cornerstone of physician licensure in China, having trained over 630,000 resident physicians [2–3]. In 2015, the “Dual-Track Integration” reform was launched, requiring clinical professional master’s students to simultaneously complete a 33-month residency program while pursuing a professional master’s degree [3]. This places trainees in a dual institutional role as both resident physicians and postgraduate students, obligating them to meet clinical competency standards while fulfilling academic requirements, including research training and thesis completion [4]. By 2023, clinical professional master’s students trained under this model accounted for more than 50% of all resident physicians in China, representing the largest incoming cohort of new physicians in the country [3]. However, this integration creates pronounced dual pressure: trainees must undertake full-time clinical responsibilities while also meeting academic expectations. This often leads to role conflict, time competition, and challenges in professional identity formation [5–9]. A particular concern is that clinical demands frequently encroach upon already limited research time, potentially constraining the balanced development of professional competencies [5,9]. To systematically evaluate training outcomes, China has adopted the six-domain Resident Core Competency Framework as a national standard [10]. Yet, existing research has not sufficiently identified the key modifiable factors influencing competency development within this high-intensity integrated model. Specifically, there is a lack of empirical evidence on how clinical practice adaptability—defined as an individual’s capacity to adapt to high-intensity clinical environments—and the adequacy of protected research time affect comprehensive competency outcomes [11–13]. Moreover, while competency-based medical education has become a central framework for postgraduate training worldwide, the unique group of clinical professional master’s students—who simultaneously undertake both academic education and clinical service—remains understudied. Factors such as adaptability to clinical environments, supervision quality, and the availability of protected research time may significantly shape competency development, but these influences have not been systematically examined [14]. In the context of China’s rapid medical education reform, understanding the competency profiles of this trainee population is crucial for informing policy enhancements and optimizing training pathways. Identifying the determinants of competency development is especially important for institutions implementing the “Dual-Track Integration” model, as the balance between clinical practice and research training directly affects training quality and workforce preparation [15]. To address these gaps and advance understanding of how high-intensity, integrated training shapes physician development, this study conducted a multicenter investigation among clinical professional master’s students trained under China’s “Dual-Track Integration” model. The specific aims were: 1) to assess the current status and structural characteristics of core competencies in this cohort; 2) to quantitatively analyze the independent effects of clinical practice adaptability and the adequacy of protected research time on core competency; 3) to generate evidence-based recommendations for optimizing training strategies for this key group of future clinicians. Methods Study Design and Participants This was a cross-sectional, multicenter study. Participants were recruited from master’s degree students in clinical specialties at accredited teaching hospitals throughout Guangdong Province, China. Participants were eligible if they were currently engaged in clinical training under the “dual-track integration” model and had completed at least six months of clinical rotations. Students with incomplete questionnaires or missing key variables were excluded from the analysis. Measurement Instruments General Demographic and Training Questionnaire Based on the literature review and the core competency theoretical framework, data were collected using a structured questionnaire specifically designed for this study [16,17]. The questionnaire was self-administered and measured variables across three dimensions: demographic characteristics, training environment factors, and individual cognitive and psychological factors. Demographic variables included gender, age, year of study, and place of origin. Training environment factors comprised the perceived adequacy of protected research time (i.e., participants' subjective assessment of whether the time dedicated to research was sufficient) and mentor–training site alignment (i.e., whether the academic mentor was affiliated with the same hospital as the clinical rotation site). Individual cognitive and psychological factors included role identity (participants' self-identification tendency, leaning more toward a "student" or a "resident physician") and attitude toward stress, assessed by agreement with the statement, “Experiencing stress is a sign of weakness” [18]. Core Competency Scale Core competencies were assessed using a self-report scale developed in accordance with the Chinese Consensus on the Core Competency Framework for Resident Physicians (formulated by the Alliance of Elite Teaching Hospitals for Residency Training in China) [10]. The scale measures six domains: Professionalism, Medical Knowledge and Skills, Patient Care, Communication and Collaboration, Teaching Capability, and Lifelong Learning. Each item was rated on a 5-point Likert scale (1 = very poor to 5 = excellent). Higher total scores reflected stronger overall competency performance. In this study, the scale demonstrated a Cronbach's α coefficient of 0.892, the Kaiser–Meyer–Olkin (KMO) measure was 0.981, and Bartlett’s test of sphericity was significant ( χ ² = 3724.36, p < 0.001). Clinical Practice Adaptability Scale The Clinical Practice Adaptability Scale was used to assess trainees’ level of integration and adaptation within their clinical training environment. The scale measures key aspects of adaptability, including trainees’ sense of belonging within the institution and the quality of their relationships with mentors, clinical instructors, peers, and other staff members. Responses were recorded on a 5-point Likert scale from 1 (“very discordant”) to 5 (“very harmonious”). Higher total scores indicated better perceived adaptability. The scale demonstrated good internal consistency (Cronbach’s α = 0.841), with a KMO value of 0.843 and a significant Bartlett’s test ( χ ²= 2433.144, p < 0.001). Data Collection and Quality Control Data were collected using an online survey platform. The first page of the electronic questionnaire presented study information and an informed consent statement; only participants who provided consent proceeded to the survey items. Quality control procedures included: 1)Content validity: Expert review by two medical education specialists and two senior training administrators. 2)Pilot testing: A preliminary survey of 30 students (excluded from the final analysis). 3)Response integrity: IP restrictions and embedded logic checks to prevent duplicate or inattentive responses. 4)Data verification: Independent data cleaning by two researchers. Statistical Analysis Statistical analyses were conducted using IBM SPSS Statistics (Version 25.0). The normality of continuous variables was assessed using the Shapiro-Wilk test. Normally distributed data were presented as mean ± standard deviation and compared between groups using independent-samples t-tests. Non-normally distributed data were summarized as median (interquartile range) and compared using the Mann-Whitney U test (for two groups) or the Kruskal-Wallis H test (for three or more groups). Based on their total scores on the Clinical Practice Adaptability Scale, participants were categorized into tertiles (low, medium, and high adaptability groups) for intergroup comparisons of core competency scores. To identify independent predictors of core competency, a multiple linear regression analysis was performed. The total score of the Core Competency Scale served as the dependent variable. Independent variables included the continuous score of clinical practice adaptability and all variables that showed a statistically significant association ( p < 0.05) with the core competency score in the preceding univariate analyses. All statistical tests were two-sided, and a P value of less than 0.05 was considered statistically significant. Abbreviations KMO= Kaiser–Meyer–Olkin ,VIF= Variance inflation factor ,SE=standard error CI= confidence interval, OSCEs=objective structured clinical examinations Results Baseline Characteristics and Stratification by Clinical Practice Adaptability A total of 921 trainees were included. The mean age was 24.6 years (range: 22–38), and 55.3% were male. Distribution by training year was as follows: 31.8% first-year, 38.0% second-year, and 30.2% third-year. Overall, 73.9% reported insufficient protected research time. Over half (55.3%) identified primarily as “resident physicians.” Adaptability scores were skewed; participants were categorized into three groups: low (≤22 points; n=376, 40.8%), medium (23–26; n=385, 41.8%), and high (≥27; n=160, 17.4%). Current Status of Core Competencies and Differences Across Training Years The mean scores for core competency domains, listed in descending order, were as follows: Professionalism, Patient Care, Communication and Collaboration, Lifelong Learning, Knowledge and Skills, and Teaching Capability (Table 1).Participants regarded “Knowledge and Skills” as the most important domain; however, their self-assessed performance score in this area was the second lowest. In contrast, “Teaching Capability” received the lowest ratings for both perceived importance and self-assessed performance. When scores were compared across different grades, third-year trainees demonstrated a significantly higher score in the Knowledge and Skills domain compared to their junior counterparts (p = 0.016). No significant inter-grade differences were observed in the remaining domains (Table 2).The scores for Professionalism and Patient Care were notably high, with narrow distributions (median = 4.0 for both), suggesting a potential ceiling effect. Table 1 . Clinical Master's Students' Perceived Importance and Self-Assessed Scores on Core Competencies (N=921) CoreCompetencyDimension PerceivedImportanceRank Self-AssessedScore (Mean±SD) ScoreRank Professionalism 2 3.95±0.66 1 Patient Care 4 3.77±0.68 2 Communication & Collaboration 3 3.76±0.69 3 Lifelong Learning 5 3.63±0.74 4 Medical Knowledge & Skills 1 3.62±0.71 5 Teaching Ability 6 3.44±0.76 6 Note: Competency dimensions are presented in descending order of their self-assessed scores. The row for Medical Knowledge and Skills is bolded to indicate the notable divergence between its top ranking in perceived importance and its fifth-place ranking in self-assessed performance. Table 2. Comparison of Self-Assessed Core Competency Scores among Clinical Master's Students by Grade CoreCompetencyDimension Grade 1 (n=293) Median [IQR] Grade 2 (n=350) Median [IQR] Grade 3 (n=278) Median [IQR] H value P value Professionalism 4.00 [4.00, 4.00] 4.00 [4.00, 4.00] 4.00 [4.00, 4.00] 3.717 0.156 Patient Care 4.00 [3.00, 4.00] 4.00 [3.00, 4.00] 4.00 [3.00, 4.00] 4.166 0.125 Communication & Collaboration 4.00 [3.00, 4.00] 4.00 [3.00, 4.00] 4.00 [3.00, 4.00] 3.447 0.178 Lifelong Learning 4.00 [3.00, 4.00] 4.00 [3.00, 4.00] 4.00 [3.00, 4.00] 1.461 0.482 Medical Knowledge & Skills 4.00 [3.00, 4.00] 3.00 [3.00, 4.00] 4.00 [3.00, 4.00] 8.308 0.016 Teaching Ability 3.00 [3.00, 4.00] 3.00 [3.00, 4.00] 3.00 [3.00, 4.00] 0.922 0.631 Note: Data are expressed as median [interquartile range]. Intergroup comparisons were analyzed using the Kruskal–Wallis H test. Rows in bold denote competency dimensions with statistically significant differences across training years ( p < 0.05). Analysis of Factors Associated with Core Competency Clinical practice adaptability was positively correlated with core competency (r = 0.498, p < 0.001). The strongest correlations were observed for relationships with clinical instructors and other faculty members (Table 3). Table 3 Analysis of Factors Associated with Core Competency AdaptationItem Correlation Coefficient （ρ） P value Relationship with Clinical Supervisors 0.40 <0.001 Relationship with Other Faculty at the Training Site 0.40 <0.001 Relationship with Academic Mentor 0.38 <0.001 Relationship with Peers 0.38 <0.001 Sense of Belonging to the Training Site 0.37 <0.001 Progress of Degree-Related Research Project 0.37 <0.001 Note: Spearman's rank correlation coefficients are reported. All correlations were significant at * p * < .001. Univariate Analysis Results Univariate analyses (Mann–Whitney U or Kruskal–Wallis H tests) revealed that gender, place of origin, the adequacy of protected research time, role identity, attitude toward stress, and clinical practice adaptability (tertile) group were all significantly associated with the total core competency score ( p < 0.05; Table 4). Table 4 Univariate Analysis of Factors Associated with Total Core Competency Score among Clinical Master's Students (N=921) Variable Category Total Score,Median [IQR] Statistic p value Gender Male(n=509) 23.00[19.50,24.00] Z=3.22 <0.001 Female(n=412) 22.00[19.00,24.00] Hometown Rural (n=608) 22.00[19.00,24.00] Z=2.09 0.037 Urban(n=313) 23.00[20.00,24.00] Perceived Sufficiency of Research Time Sufficient(n=240) 24.00[20.25,24.00] Z=5.75 <0.001 Insufficient(n=681) 22.00[19.00,24.00] Professional Role ldentity Student(n=340) 21.00[18.00,24.00] Z=4.00 <0.001 Resident(n=509) 23.00[19.00,24.00] Attitude towards Stress Agrees "stress indicates weakness"(n=130) 21.00[18.00,24.00] Z=2.28 0.023 Disagrees(n=791) 22.00[19.00,24.00] Clinical Practice Adaptation Level Low(n=376) 20.00[18.00,23.00] H=184.68 <0.001 Medium(n=385) 23.00[20.00,24.00] High(n=160) 24.00[23.00,30.00] Note: Data are presented as median [interquartile range]. The Mann-Whitney U test (reported as Z ) was used for comparisons between two groups, and the Kruskal–Wallis H test (reported as H) was used for comparisons across the three adaptation-level groups. Statistically significant differences ( p < 0.05) are indicated by bold type. Multiple Linear Regression To identify independent predictors of overall competency, we performed a multiple linear regression analysis (variable coding is shown in Table 5). First, a baseline model (Model 1) was fitted using only the socio-demographic and cognitive factors that were significant in the univariate analysis; this model explained a limited proportion of variance (adjusted R ² = 0.056). We then added the total score of clinical practice adaptability as a continuous variable to build the full model (Model 2), which substantially improved model fit (adjusted R ² = 0.217). As presented in Table 6, both clinical practice adaptability ( β = 0.425, p < 0.001) and perceived adequacy of protected research time ( β = 0.079, p = 0.010) emerged as independent, positive predictors of the total core competency score. Collinearity diagnostics confirmed that all variance inflation factors were well below 5, indicating no substantial multicollinearity in the model. Table 5. Variable Assignment Variable Coding Gender 0=Male;1=Female Hometown 0=Rural;1=Urban Perceived Sufficiency of Research Time 0=Insufficient;1=Sufficient Professional Role Identity 0=Identifies primarily as a 'Student';1=Identifies primarily as a 'Resident' Attitude towards Stress(as a sign of weakness) 0=Agrees that stress is a sign of weakness;1= Disagrees Clinical Practice Adaptation Score Entered as the original continuous score Note: The above coding for categorical variables was used in constructing the multiple linear regression model. Table 6 . Multiple Linear Regression Analysis of Factors Associated with Total Core Competency Score (N=921) Predictor B (Unstandardized Coefficient) SE β (Standardized Coefficient) t value p value 95%CI VIF Constant 18.07 0.39 一 45.17 <0.001 17.30to18.84 _ Clinical Practice Adaptation Score 2.09 0.15 0.425 13.79 <0.001 1.79to2.38 1.12 Sufficient Research Time(Ref:Insufficient) 0.64 0.25 0.079 2.59 0.010 0.16to1.12 1.08 Role Identity:Resident(Ref:Student) 0.38 0.22 0.047 1.77 0.078 -0.04to0.81 1.02 Gender:Female (Ref:Male) -0.38 0.21 -0.052 -1.80 0.072 -0.80to0.03 1.03 Hometown:Urban (Ref:Rural) 0.09 0.22 0.012 0.40 0.689 -0.35to0.52 1.02 Attitude:Disagrees about Stress(Ref: Agrees) 0.17 0.30 0.017 0.57 0.569 -0.42to0.76 1.02 Note: The dependent variable was the Total Core Competency Score. The final model accounted for 21.7% of the variance (Adjusted R ² = 0.217). Predictor selection employed backward stepwise regression with a removal criterion of p > 0.10. Statistically significant predictors ( p < 0.05) are highlighted in bold. Variance inflation factor (VIF) values for all variables were below 5, indicating no substantial multicollinearity. Abbreviations: SE, standard error; CI, confidence interval. Discussion This cross-sectional study quantitatively evaluated core competencies and their key determinants among professional master’s students in clinical medicine trained under China’s “Dual-Track Integration” model. The main findings reveal an imbalanced competency profile in this trainee cohort, with clinical practice adaptability and the adequacy of protected research time emerging as two critical, modifiable predictors of core competency development. Competency Structure Imbalance: The Theory-Practice Gap and Role Fixation Our findings reveal a pronounced theory–practice gap. Although trainees rated “Knowledge and Skills” as the most critical competency, their self-assessed performance in this domain ranked among the lowest. This discrepancy may stem from the intensive demands of rotational clinical training combined with thesis-related pressures, which likely hinder the consolidation of systematic knowledge and the refinement of clinical reasoning, thereby limiting the translation of experiential learning into a robust knowledge foundation [7,8]. Furthermore, the pervasive weakness in teaching capability highlights a misalignment with the contemporary expectation that physicians also serve as educators [10]. This finding not only reflects a systematic neglect of pedagogical training within the curriculum but also suggests a deeper institutional tendency to position trainees primarily as passive learners [19,20]. Consistent with the importance of professional socialization, our data indicate that trainees who primarily identified as “resident physicians” demonstrated higher overall competency levels than those who identified as “students.” Clinical Practice Adaptability: The Central Role of the Learning Environment A key contribution of this study lies in its quantitative demonstration that clinical practice adaptability is the strongest independent predictor of core competency ( β = 0.425). This finding shifts the focus of potential interventions from individual trainee characteristics to modifiable features of the clinical learning environment. Specifically, relationships with clinical instructors emerged as the most critical component of adaptability, reinforcing the foundational role of supportive supervisory relationships in providing guidance, feedback, and psychosocial support [21]. Notably, after adjusting for adaptability, the influence of several demographic factors was substantially attenuated, suggesting that cultivating an inclusive and supportive clinical environment may promote educational equity by mitigating disparities associated with inherent or background-related differences. Protected Research Time: A Foundational Element for Clinical-Research Synergy This study confirmed the independent positive contribution of perceived adequacy of protected research time to competency development. This finding supports the concept of clinical–research synergy, whereby scholarly inquiry grounded in clinical questions strengthens evidence-based thinking, deepens understanding of pathophysiology, and ultimately enhances clinical decision-making [22]. Insights and Recommendations Building on these findings, we propose the following targeted recommendations to improve training outcomes. First, the clinical learning environment should be systematically optimized by establishing clear expectations, providing structured guidance, and reinforcing developmental progress—approaches aligned with supportive educational frameworks that enhance trainees’ sense of belonging and adaptive capacity [23]. Second, institutional policies must actively protect dedicated research time and promote clinically grounded scholarly projects to foster meaningful integration between practice and inquiry. Third, intentional interventions should be implemented to address identified competency gaps. For example, incorporating graduated teaching responsibilities—such as involving senior trainees in supervising and mentoring junior peers—can simultaneously enhance teaching skills, consolidate medical knowledge, and reinforce the dual professional identity of the clinician-educator [24]. Insights and Recommendations Building on these findings, we propose the following targeted recommendations to improve training outcomes. First, the clinical learning environment should be systematically optimized by establishing clear expectations, providing structured guidance, and reinforcing developmental progress—approaches aligned with supportive educational frameworks that enhance trainees’ sense of belonging and adaptive capacity [23]. Second, institutional policies must actively protect dedicated research time and promote clinically grounded scholarly projects to foster meaningful integration between practice and inquiry. Third, intentional interventions should be implemented to address identified competency gaps. For example, incorporating graduated teaching responsibilities—such as involving senior trainees in supervising and mentoring junior peers—can simultaneously enhance teaching skills, consolidate medical knowledge, and reinforce the dual professional identity of the clinician-educator [24]. Limitations This study has several limitations. First, the cross-sectional design precludes causal inferences regarding the observed associations. Second, reliance on self-reported measures may introduce social desirability bias. Third, because the sample was drawn from a single province, the generalizability of the findings to other regions of China is limited, and external validation in more diverse populations is warranted. Future research would benefit from longitudinal designs to track competency development over time. Incorporating objective assessments, such as supervisor evaluations and objective structured clinical examinations (OSCEs), would provide valuable multisource validation. Finally, interventional studies are needed to develop and test strategies aimed at improving clinical practice adaptability and safeguarding dedicated research time. Conclusion This multicenter study demonstrated that core competencies among clinical professional master’s students trained under the dual-track integration model are shaped by both individual and contextual factors. Clinical practice adaptability and the adequacy of protected research time were independent predictors of competency performance. Enhancing supportive learning environments, strengthening supervision, and ensuring sufficient protected research time are critical. Targeted interventions to enhance adaptability and reduce training fragmentation may further promote competency development among this critical group of future clinicians. Declarations Acknowledgments The authors gratefully acknowledge the Graduate School of Guangdong Medical University and its postgraduate training bases for their collaboration and support in the facilitation of this survey. Funding This study was funded by Huaihua City Ideological and Political Research Project: Innovating the "Holistic Ideological-Political Education" Pathway for Clinical Medicine Master’s Students through Red Heritage and Medical Ethics Cultivation. Hunan University of Medicine Research Project: Building the "Young Marxist Training Project" System for Clinical Medicine Professional Master’s Students (grant number 2023SK12). Research on the Ideological Transformation of Clinical Professional Master's Students in the New Era(grant number 2023GXJK004) Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Declarations Conflict of interest Not applicable Ethica l approval This study was reviewed and approved by the Medical Ethics Committee of The General Hospital of Hunan University of Medicine (Approval No. KY-2026010601) and was performed in line with the Declaration of Helsinki. Inform consent Informed consent was obtained electronically. Participation was voluntary, and consent was confirmed by a mandatory agreement option at the beginning of the online survey. All data were collected and stored anonymously. Author contributions .Jing ZHOU (First & Co-corresponding Author): Was responsible for conceptualizing and designing the study, conducting data collection and curation, performing statistical analysis, and drafting the initial manuscript. Holds primary responsibility for the core content.Haosheng PENG (Co-corresponding Author): Assisted in questionnaire optimization with a focus on clinical practice and data cross-verification. Participated in coordination of collaboration and resources.Haiman LIU (Third Author): Assisted in data surveys related to research time and core competencies.Jiacheng YUAN (Fourth Author): Assisted in conducting in-depth interviews and extracting qualitative insights.Xiaoyan CHEN (Fifth Author): Assisted in data collection, organization, and manuscript proofreading.Jianchao GUO (Sixth Author): Assisted in conducting in-depth interviews and extracting qualitative insights.Jindong NI (Co-corresponding Author): Oversaw the entire research process, reviewed scientific and ethical rigor, and was responsible for reviewing, revising, and finalizing the manuscript. References Payne R, Frejah I, Abbey E, Badcoe R, Delaney B, Mitchell C (2025) Transitioning between clinical and academic practice from the perspectives of clinical academic trainees, academic training programme directors and academic supervisors: a mixed methods study. 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Supplementary Files 1769497854362.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 25 Mar, 2026 Editor invited by journal 02 Mar, 2026 Editor assigned by journal 09 Feb, 2026 Submission checks completed at journal 07 Feb, 2026 First submitted to journal 07 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8708160","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":612086312,"identity":"157c1826-9ae4-42f1-a823-a1b17cdb1437","order_by":0,"name":"Jing ZHOU","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsUlEQVRIiWNgGAWjYBACPgbmBhAtx8befoA4LWwMjGAtxnw8ZxJI05I4T8LBgEgt7AcbH/xss0lvk2BIYPhRsY0ILTyJzYa9bWm5bdKNBxh7ztwmxmGJbRI8Zw7ntskcSGBmbCNGC//D9p9/zvxPZ5NIMCBSi0RiGzNPxYEEUrQ8bJaWqUg2bAMG8kGi/MLPn3zw4xsDO3n59vaDD35UEKEFBRwgUf0oGAWjYBSMAlwAAEb0OFCAAUUIAAAAAElFTkSuQmCC","orcid":"","institution":"Hunan University of Medicine General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jing","middleName":"","lastName":"ZHOU","suffix":""},{"id":612086313,"identity":"ac82bc34-86ee-47e8-a47e-027d0059f924","order_by":1,"name":"Haosheng PENG","email":"","orcid":"","institution":"Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Haosheng","middleName":"","lastName":"PENG","suffix":""},{"id":612086314,"identity":"185f6666-8aae-4072-b5f5-9364830252c8","order_by":2,"name":"Haiman LIU","email":"","orcid":"","institution":"Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Haiman","middleName":"","lastName":"LIU","suffix":""},{"id":612086315,"identity":"d9a369f6-00c4-4ac9-bf78-3b470285c479","order_by":3,"name":"Jiacheng YUAN","email":"","orcid":"","institution":"Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiacheng","middleName":"","lastName":"YUAN","suffix":""},{"id":612086316,"identity":"47bb1354-d5c1-49bb-8b19-0f333211af10","order_by":4,"name":"Xiaoyan CHEN","email":"","orcid":"","institution":"Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyan","middleName":"","lastName":"CHEN","suffix":""},{"id":612086317,"identity":"89c3330b-f213-4b18-9f1a-710f4d68ed30","order_by":5,"name":"Jianchao GUO","email":"","orcid":"","institution":"Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jianchao","middleName":"","lastName":"GUO","suffix":""},{"id":612086319,"identity":"5b83454e-320c-468a-b571-09451ae35a31","order_by":6,"name":"Jindong NI","email":"","orcid":"","institution":"Guangdong Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jindong","middleName":"","lastName":"NI","suffix":""}],"badges":[],"createdAt":"2026-01-27 08:57:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8708160/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8708160/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105470474,"identity":"5ab04369-ab02-4fe7-8d0f-969fbf089356","added_by":"auto","created_at":"2026-03-26 11:46:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":994046,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8708160/v1/c0a808e1-5318-4b5c-8e79-4af3473ebb95.pdf"},{"id":105470472,"identity":"d194be7a-c4de-41c7-8080-887fc7b5015c","added_by":"auto","created_at":"2026-03-26 11:46:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1246858,"visible":true,"origin":"","legend":"","description":"","filename":"1769497854362.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8708160/v1/88f5bc0b1c79a5256f76a705.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical Adaptability and Protected Research Time as Key Determinants of Core Competency: A Cross-sectional Study of China's \"Dual-Track Integration\" Clinical Professional Master’s Students","fulltext":[{"header":"Introduction","content":"\u003cp\u003eA central challenge in global medical education is how to effectively integrate clinical skills training with scholarly development within a constrained timeframe [1]. China’s “Dual-Track Integration” training model offers a distinctive institutional context for examining this issue. Since its full implementation in 2013, standardized residency training has become a cornerstone of physician licensure in China, having trained over 630,000 resident physicians [2–3]. In 2015, the “Dual-Track Integration” reform was launched, requiring clinical professional master’s students to simultaneously complete a 33-month residency program while pursuing a professional master’s degree [3]. This places trainees in a dual institutional role as both resident physicians and postgraduate students, obligating them to meet clinical competency standards while fulfilling academic requirements, including research training and thesis completion [4].\u003c/p\u003e\n\u003cp\u003eBy 2023, clinical professional master’s students trained under this model accounted for more than 50% of all resident physicians in China, representing the largest incoming cohort of new physicians in the country [3]. However, this integration creates pronounced dual pressure: trainees must undertake full-time clinical responsibilities while also meeting academic expectations. This often leads to role conflict, time competition, and challenges in professional identity formation [5–9]. A particular concern is that clinical demands frequently encroach upon already limited research time, potentially constraining the balanced development of professional competencies [5,9].\u003c/p\u003e\n\u003cp\u003eTo systematically evaluate training outcomes, China has adopted the six-domain Resident Core Competency Framework as a national standard [10]. Yet, existing research has not sufficiently identified the key modifiable factors influencing competency development within this high-intensity integrated model. Specifically, there is a lack of empirical evidence on how clinical practice adaptability—defined as an individual’s capacity to adapt to high-intensity clinical environments—and the adequacy of protected research time affect comprehensive competency outcomes [11–13].\u003c/p\u003e\n\u003cp\u003eMoreover, while competency-based medical education has become a central framework for postgraduate training worldwide, the unique group of clinical professional master’s students—who simultaneously undertake both academic education and clinical service—remains understudied. Factors such as adaptability to clinical environments, supervision quality, and the availability of protected research time may significantly shape competency development, but these influences have not been systematically examined [14].\u003c/p\u003e\n\u003cp\u003eIn the context of China’s rapid medical education reform, understanding the competency profiles of this trainee population is crucial for informing policy enhancements and optimizing training pathways. Identifying the determinants of competency development is especially important for institutions implementing the “Dual-Track Integration” model, as the balance between clinical practice and research training directly affects training quality and workforce preparation [15].\u003c/p\u003e\n\u003cp\u003eTo address these gaps and advance understanding of how high-intensity, integrated training shapes physician development, this study conducted a multicenter investigation among clinical professional master’s students trained under China’s “Dual-Track Integration” model. The specific aims were:\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;1) to assess the current status and structural characteristics of core competencies in this cohort;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;2) to quantitatively analyze the independent effects of clinical practice adaptability and the adequacy of protected research time on core competency;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;3) to generate evidence-based recommendations for optimizing training strategies for this key group of future clinicians.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy Design and Participants\u003c/p\u003e\n\u003cp\u003eThis was a cross-sectional, multicenter study. Participants were recruited from master’s degree students in clinical specialties at accredited teaching hospitals throughout Guangdong Province, China. Participants were eligible if they were currently engaged in clinical training under the “dual-track integration” model and had completed at least six months of clinical rotations. Students with incomplete questionnaires or missing key variables were excluded from the analysis.\u003c/p\u003e\n\u003cp\u003eMeasurement Instruments \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGeneral Demographic and Training Questionnaire\u003c/p\u003e\n\u003cp\u003eBased on the literature review and the core competency theoretical framework, data were collected using a structured questionnaire specifically designed for this study [16,17]. The questionnaire was self-administered and measured variables across three dimensions: demographic characteristics, training environment factors, and individual cognitive and psychological factors. Demographic variables included gender, age, year of study, and place of origin. Training environment factors comprised the perceived adequacy of protected research time (i.e., participants' subjective assessment of whether the time dedicated to research was sufficient) and mentor–training site alignment (i.e., whether the academic mentor was affiliated with the same hospital as the clinical rotation site). Individual cognitive and psychological factors included role identity (participants' self-identification tendency, leaning more toward a \"student\" or a \"resident physician\") and attitude toward stress, assessed by agreement with the statement, “Experiencing stress is a sign of weakness” [18].\u003c/p\u003e\n\u003cp\u003eCore Competency Scale\u003c/p\u003e\n\u003cp\u003eCore competencies were assessed using a self-report scale developed in accordance with the Chinese Consensus on the Core Competency Framework for Resident Physicians (formulated by the Alliance of Elite Teaching Hospitals for Residency Training in China) [10]. The scale measures six domains: Professionalism, Medical Knowledge and Skills, Patient Care, Communication and Collaboration, Teaching Capability, and Lifelong Learning. Each item was rated on a 5-point Likert scale (1 = very poor to 5 = excellent). Higher total scores reflected stronger overall competency performance.\u003c/p\u003e\n\u003cp\u003eIn this study, the scale demonstrated a Cronbach's α coefficient of 0.892, the Kaiser–Meyer–Olkin (KMO) measure was 0.981, and Bartlett’s test of sphericity was significant (\u003cem\u003eχ\u003c/em\u003e² = 3724.36, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eClinical Practice Adaptability Scale\u003c/p\u003e\n\u003cp\u003eThe Clinical Practice Adaptability Scale was used to assess trainees’ level of integration and adaptation within their clinical training environment. The scale measures key aspects of adaptability, including trainees’ sense of belonging within the institution and the quality of their relationships with mentors, clinical instructors, peers, and other staff members. Responses were recorded on a 5-point Likert scale from 1 (“very discordant”) to 5 (“very harmonious”). Higher total scores indicated better perceived adaptability. The scale demonstrated good internal consistency (Cronbach’s \u003cem\u003eα\u003c/em\u003e= 0.841), with a KMO value of 0.843 and a significant Bartlett’s test (\u003cem\u003eχ\u003c/em\u003e²= 2433.144, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eData Collection and Quality Control\u003c/p\u003e\n\u003cp\u003eData were collected using an online survey platform. The first page of the electronic questionnaire presented study information and an informed consent statement; only participants who provided consent proceeded to the survey items.\u003c/p\u003e\n\u003cp\u003eQuality control procedures included:\u003c/p\u003e\n\u003cp\u003e1)Content validity: Expert review by two medical education specialists and two senior training administrators.\u003c/p\u003e\n\u003cp\u003e2)Pilot testing: A preliminary survey of 30 students (excluded from the final analysis).\u003c/p\u003e\n\u003cp\u003e3)Response integrity: IP restrictions and embedded logic checks to prevent duplicate or inattentive responses.\u003c/p\u003e\n\u003cp\u003e4)Data verification: Independent data cleaning by two researchers.\u003c/p\u003e\n\u003cp\u003eStatistical Analysis\u003c/p\u003e\n\u003cp\u003eStatistical analyses were conducted using IBM SPSS Statistics (Version 25.0). The normality of continuous variables was assessed using the Shapiro-Wilk test. Normally distributed data were presented as mean ± standard deviation and compared between groups using independent-samples t-tests. Non-normally distributed data were summarized as median (interquartile range) and compared using the Mann-Whitney\u003cem\u003e\u0026nbsp;U\u003c/em\u003e test (for two groups) or the Kruskal-Wallis \u003cem\u003eH\u003c/em\u003e test (for three or more groups).\u003c/p\u003e\n\u003cp\u003eBased on their total scores on the Clinical Practice Adaptability Scale, participants were categorized into tertiles (low, medium, and high adaptability groups) for intergroup comparisons of core competency scores.\u003c/p\u003e\n\u003cp\u003eTo identify independent predictors of core competency, a multiple linear regression analysis was performed. The total score of the Core Competency Scale served as the dependent variable. Independent variables included the continuous score of clinical practice adaptability and all variables that showed a statistically significant association (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05) with the core competency score in the preceding univariate analyses. All statistical tests were two-sided, and a \u003cem\u003eP\u003c/em\u003e value of less than 0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003eAbbreviations\u003c/p\u003e\n\u003cp\u003eKMO= Kaiser–Meyer–Olkin ,VIF= Variance inflation factor ,SE=standard error \u0026nbsp;CI= confidence interval, OSCEs=objective structured clinical examinations\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBaseline Characteristics and Stratification by Clinical Practice Adaptability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 921 trainees were included. The mean age was 24.6 years (range: 22\u0026ndash;38), and 55.3% were male. Distribution by training year was as follows: 31.8% first-year, 38.0% second-year, and 30.2% third-year. Overall, 73.9% reported insufficient protected research time. Over half (55.3%) identified primarily as \u0026ldquo;resident physicians.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eAdaptability scores were skewed; participants were categorized into three groups: low (\u0026le;22 points; n=376, 40.8%), medium (23\u0026ndash;26; n=385, 41.8%), and high (\u0026ge;27; n=160, 17.4%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCurrent Status of Core Competencies and Differences Across Training Years\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean scores for core competency domains, listed in descending order, were as follows: Professionalism, Patient Care, Communication and Collaboration, Lifelong Learning, Knowledge and Skills, and Teaching Capability (Table 1).Participants regarded \u0026ldquo;Knowledge and Skills\u0026rdquo; as the most important domain; however, their self-assessed performance score in this area was the second lowest. In contrast, \u0026ldquo;Teaching Capability\u0026rdquo; received the lowest ratings for both perceived importance and self-assessed performance.\u003c/p\u003e\n\u003cp\u003eWhen scores were compared across different grades, third-year trainees demonstrated a significantly higher score in the Knowledge and Skills domain compared to their junior counterparts (p = 0.016). No significant inter-grade differences were observed in the remaining domains (Table 2).The scores for Professionalism and Patient Care were notably high, with narrow distributions (median = 4.0 for both), suggesting a potential ceiling effect.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e. Clinical Master\u0026apos;s Students\u0026apos; Perceived Importance and Self-Assessed Scores on Core Competencies (N=921)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"638\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCoreCompetencyDimension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePerceivedImportanceRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-AssessedScore\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean\u0026plusmn;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eScoreRank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eProfessionalism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.95\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePatient Care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.77\u0026plusmn;0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCommunication \u0026amp; Collaboration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.76\u0026plusmn;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLifelong Learning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.63\u0026plusmn;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedical Knowledge \u0026amp; Skills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.62\u0026plusmn;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTeaching Ability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.44\u0026plusmn;0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003eCompetency dimensions are presented in descending order of their self-assessed scores. The row for Medical Knowledge and Skills is bolded to indicate the notable divergence between its top ranking in perceived importance and its fifth-place ranking in self-assessed performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eComparison of Self-Assessed Core Competency Scores among Clinical Master\u0026apos;s Students by Grade\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCoreCompetencyDimension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGrade 1\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=293)\u003cbr\u003e\u0026nbsp;Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGrade 2\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=350)\u003cbr\u003e\u0026nbsp;Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGrade 3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=278)\u003cbr\u003e\u0026nbsp;Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eH\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eProfessionalism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [4.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [4.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [4.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePatient Care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCommunication \u0026amp; Collaboration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLifelong Learning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.482\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMedical Knowledge \u0026amp; Skills\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e4.00 [3.00, 4.00]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e3.00 [3.00, 4.00]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e4.00 [3.00, 4.00]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e8.308\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTeaching Ability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.00 [3.00, 4.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Data are expressed as median [interquartile range]. Intergroup comparisons were analyzed using the Kruskal\u0026ndash;Wallis H test. Rows in bold denote competency dimensions with statistically significant differences across training years (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of Factors Associated with Core Competency\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical practice adaptability was positively correlated with core competency (r = 0.498, p \u0026lt; 0.001). The strongest correlations were observed for relationships with clinical instructors and other faculty members (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e Analysis of Factors Associated with Core Competency\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"77%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAdaptationItem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCorrelation Coefficient\u003c/strong\u003e\u003cstrong\u003e（\u0026rho;）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRelationship with Clinical Supervisors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRelationship with Other Faculty at the Training Site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRelationship with Academic Mentor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRelationship with Peers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSense of Belonging to the Training Site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eProgress of Degree-Related Research Project\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Spearman\u0026apos;s rank correlation coefficients are reported. All correlations were significant at\u0026nbsp;*\u003cem\u003ep\u003c/em\u003e*\u0026nbsp;\u0026lt; .001.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUnivariate Analysis Results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnivariate analyses (Mann\u0026ndash;Whitney U or Kruskal\u0026ndash;Wallis H tests) revealed that gender, place of origin, the adequacy of protected research time, role identity, attitude toward stress, and clinical practice adaptability (tertile) group were all significantly associated with the total core competency score (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e Univariate Analysis of Factors Associated with Total Core Competency Score among Clinical Master\u0026apos;s Students (N=921)\u003c/p\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"619\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Score,Median [IQR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eStatistic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale(n=509)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.00[19.50,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eZ=3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale(n=412)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.00[19.00,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eHometown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRural \u0026nbsp;(n=608)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.00[19.00,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eZ=2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.037\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUrban(n=313)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.00[20.00,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ePerceived Sufficiency of Research Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSufficient(n=240)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.00[20.25,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eZ=5.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eInsufficient(n=681)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.00[19.00,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eProfessional Role ldentity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eStudent(n=340)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.00[18.00,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eZ=4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eResident(n=509)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.00[19.00,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAttitude towards Stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAgrees \u0026quot;stress indicates weakness\u0026quot;(n=130)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.00[18.00,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eZ=2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.023\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDisagrees(n=791)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.00[19.00,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eClinical Practice Adaptation Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLow(n=376)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.00[18.00,23.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eH=184.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedium(n=385)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.00[20.00,24.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHigh(n=160)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.00[23.00,30.00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e Data are presented as median [interquartile range]. The Mann-Whitney \u003cem\u003eU\u003c/em\u003e test (reported as \u003cem\u003eZ\u003c/em\u003e) was used for comparisons between two groups, and the Kruskal\u0026ndash;Wallis H test (reported as H) was used for comparisons across the three adaptation-level groups. Statistically significant differences (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) are indicated by bold type.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiple Linear Regression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify independent predictors of overall competency, we performed a multiple linear regression analysis (variable coding is shown in Table 5). First, a baseline model (Model 1) was fitted using only the socio-demographic and cognitive factors that were significant in the univariate analysis; this model explained a limited proportion of variance (adjusted \u003cem\u003eR\u003c/em\u003e\u0026sup2; = 0.056). We then added the total score of clinical practice adaptability as a continuous variable to build the full model (Model 2), which substantially improved model fit (adjusted \u003cem\u003eR\u003c/em\u003e\u0026sup2; = 0.217). As presented in Table 6, both clinical practice adaptability (\u003cem\u003e\u0026beta;\u003c/em\u003e = 0.425, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) and perceived adequacy of protected research time (\u003cem\u003e\u0026beta;\u003c/em\u003e = 0.079, \u003cem\u003ep\u003c/em\u003e = 0.010) emerged as independent, positive predictors of the total core competency score. Collinearity diagnostics confirmed that all variance inflation factors were well below 5, indicating no substantial multicollinearity in the model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eVariable Assignment\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"82%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Coding\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; 0=Male;1=Female\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHometown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; 0=Rural;1=Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePerceived Sufficiency of Research Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; 0=Insufficient;1=Sufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eProfessional Role Identity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; 0=Identifies primarily as a \u0026apos;Student\u0026apos;;1=Identifies\u003cbr\u003e\u0026nbsp; \u0026nbsp;primarily as a \u0026apos;Resident\u0026apos;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAttitude towards Stress(as a sign of weakness)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; 0=Agrees that stress is a sign of weakness;1=\u003cbr\u003e\u0026nbsp; \u0026nbsp;Disagrees\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eClinical Practice Adaptation Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Entered as the original continuous score\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u0026nbsp;\u003c/strong\u003eThe above coding for categorical variables was used in constructing the multiple linear regression model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u003c/strong\u003e. Multiple Linear Regression Analysis of Factors Associated with Total Core Competency Score (N=921)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"101%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePredictor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003cp\u003e(Unstandardized Coefficient)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003cp\u003e(Standardized Coefficient)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003et value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eVIF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.07\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.39\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e一\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45.17\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.30to18.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e_\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eClinical Practice Adaptation Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.09\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.15\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.425\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.79\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.79to2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSufficient Research Time(Ref:Insufficient)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.64\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.25\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.079\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.59\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.010\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.16to1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRole Identity:Resident(Ref:Student)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.38\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.22\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.047\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.77\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.078\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.04to0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGender:Female \u0026nbsp;(Ref:Male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.38\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.21\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.052\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-1.80\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.072\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.80to0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHometown:Urban \u0026nbsp;(Ref:Rural)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.09\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.22\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.012\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.40\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.689\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.35to0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAttitude:Disagrees about Stress(Ref:\u003cbr\u003e\u0026nbsp;Agrees)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.17\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.30\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.017\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.57\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.569\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.42to0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e The dependent variable was the Total Core Competency Score. The final model accounted for 21.7% of the variance (Adjusted \u003cem\u003eR\u003c/em\u003e\u0026sup2;\u0026nbsp;= 0.217). Predictor selection employed backward stepwise regression with a removal criterion of \u003cem\u003ep\u003c/em\u003e \u0026gt; 0.10. Statistically significant predictors (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) are highlighted in bold. Variance inflation factor (VIF) values for all variables were below 5, indicating no substantial multicollinearity. Abbreviations: SE, standard error; CI, confidence interval.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cross-sectional study quantitatively evaluated core competencies and their key determinants among professional master’s students in clinical medicine trained under China’s “Dual-Track Integration” model. The main findings reveal an imbalanced competency profile in this trainee cohort, with clinical practice adaptability and the adequacy of protected research time emerging as two critical, modifiable predictors of core competency development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompetency Structure Imbalance: The Theory-Practice Gap and Role Fixation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur findings reveal a pronounced theory–practice gap. Although trainees rated “Knowledge and Skills” as the most critical competency, their self-assessed performance in this domain ranked among the lowest. This discrepancy may stem from the intensive demands of rotational clinical training combined with thesis-related pressures, which likely hinder the consolidation of systematic knowledge and the refinement of clinical reasoning, thereby limiting the translation of experiential learning into a robust knowledge foundation [7,8].\u003c/p\u003e\n\u003cp\u003eFurthermore, the pervasive weakness in teaching capability highlights a misalignment with the contemporary expectation that physicians also serve as educators [10]. This finding not only reflects a systematic neglect of pedagogical training within the curriculum but also suggests a deeper institutional tendency to position trainees primarily as passive learners [19,20].\u003c/p\u003e\n\u003cp\u003eConsistent with the importance of professional socialization, our data indicate that trainees who primarily identified as “resident physicians” demonstrated higher overall competency levels than those who identified as “students.”\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Practice Adaptability: The Central Role of the Learning Environment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA key contribution of this study lies in its quantitative demonstration that clinical practice adaptability is the strongest independent predictor of core competency (\u003cem\u003eβ\u003c/em\u003e = 0.425). This finding shifts the focus of potential interventions from individual trainee characteristics to modifiable features of the clinical learning environment. Specifically, relationships with clinical instructors emerged as the most critical component of adaptability, reinforcing the foundational role of supportive supervisory relationships in providing guidance, feedback, and psychosocial support [21].\u003c/p\u003e\n\u003cp\u003eNotably, after adjusting for adaptability, the influence of several demographic factors was substantially attenuated, suggesting that cultivating an inclusive and supportive clinical environment may promote educational equity by mitigating disparities associated with inherent or background-related differences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtected Research Time: A Foundational Element for Clinical-Research Synergy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study confirmed the independent positive contribution of perceived adequacy of protected research time to competency development. This finding supports the concept of clinical–research synergy, whereby scholarly inquiry grounded in clinical questions strengthens evidence-based thinking, deepens understanding of pathophysiology, and ultimately enhances clinical decision-making [22].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInsights and Recommendations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBuilding on these findings, we propose the following targeted recommendations to improve training outcomes. First, the clinical learning environment should be systematically optimized by establishing clear expectations, providing structured guidance, and reinforcing developmental progress—approaches aligned with supportive educational frameworks that enhance trainees’ sense of belonging and adaptive capacity [23]. Second, institutional policies must actively protect dedicated research time and promote clinically grounded scholarly projects to foster meaningful integration between practice and inquiry. Third, intentional interventions should be implemented to address identified competency gaps. For example, incorporating graduated teaching responsibilities—such as involving senior trainees in supervising and mentoring junior peers—can simultaneously enhance teaching skills, consolidate medical knowledge, and reinforce the dual professional identity of the clinician-educator [24].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInsights and Recommendations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBuilding on these findings, we propose the following targeted recommendations to improve training outcomes. First, the clinical learning environment should be systematically optimized by establishing clear expectations, providing structured guidance, and reinforcing developmental progress—approaches aligned with supportive educational frameworks that enhance trainees’ sense of belonging and adaptive capacity [23]. Second, institutional policies must actively protect dedicated research time and promote clinically grounded scholarly projects to foster meaningful integration between practice and inquiry. Third, intentional interventions should be implemented to address identified competency gaps. For example, incorporating graduated teaching responsibilities—such as involving senior trainees in supervising and mentoring junior peers—can simultaneously enhance teaching skills, consolidate medical knowledge, and reinforce the dual professional identity of the clinician-educator [24].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. First, the cross-sectional design precludes causal inferences regarding the observed associations. Second, reliance on self-reported measures may introduce social desirability bias. Third, because the sample was drawn from a single province, the generalizability of the findings to other regions of China is limited, and external validation in more diverse populations is warranted.\u003c/p\u003e\n\u003cp\u003eFuture research would benefit from longitudinal designs to track competency development over time. Incorporating objective assessments, such as supervisor evaluations and objective structured clinical examinations (OSCEs), would provide valuable multisource validation. Finally, interventional studies are needed to develop and test strategies aimed at improving clinical practice adaptability and safeguarding dedicated research time.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis multicenter study demonstrated that core competencies among clinical professional master’s students trained under the dual-track integration model are shaped by both individual and contextual factors. Clinical practice adaptability and the adequacy of protected research time were independent predictors of competency performance. Enhancing supportive learning environments, strengthening supervision, and ensuring sufficient protected research time are critical. Targeted interventions to enhance adaptability and reduce training fragmentation may further promote competency development among this critical group of future clinicians.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e The authors gratefully acknowledge the Graduate School of Guangdong Medical University and its postgraduate training bases for their collaboration and support in the facilitation of this survey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e This study was funded by Huaihua City Ideological and Political Research Project: Innovating the \"Holistic Ideological-Political Education\" Pathway for Clinical Medicine Master’s Students through Red Heritage and Medical Ethics Cultivation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHunan University of Medicine Research Project: Building the \"Young Marxist Training Project\" System for Clinical Medicine Professional Master’s Students (grant number 2023SK12).\u003c/p\u003e\n\u003cp\u003eResearch\u0026nbsp;on\u0026nbsp;the\u0026nbsp;Ideological\u0026nbsp;Transformation\u0026nbsp;of\u0026nbsp;Clinical\u0026nbsp;Professional\u0026nbsp;Master's\u0026nbsp;Students\u0026nbsp;in\u0026nbsp;the\u0026nbsp;New\u0026nbsp;Era(grant number 2023GXJK004)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003eDeclarations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthica\u003c/strong\u003e\u003cstrong\u003el approval\u003c/strong\u003e This study was reviewed and approved by the Medical Ethics Committee of The General Hospital of Hunan University of Medicine (Approval No. KY-2026010601) and was performed in line with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInform\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;consent\u003c/strong\u003e Informed consent was obtained electronically. Participation was voluntary, and consent was confirmed by a mandatory agreement option at the beginning of the online survey. All data were collected and stored anonymously.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e.Jing ZHOU (First \u0026amp; Co-corresponding Author): Was responsible for conceptualizing and designing the study, conducting data collection and curation, performing statistical analysis, and drafting the initial manuscript. Holds primary responsibility for the core content.Haosheng PENG (Co-corresponding Author): Assisted in questionnaire optimization with a focus on clinical practice and data cross-verification. Participated in coordination of collaboration and resources.Haiman LIU (Third Author): Assisted in data surveys related to research time and core competencies.Jiacheng YUAN (Fourth Author): Assisted in conducting in-depth interviews and extracting qualitative insights.Xiaoyan CHEN (Fifth Author): Assisted in data collection, organization, and manuscript proofreading.Jianchao GUO (Sixth Author): Assisted in conducting in-depth interviews and extracting qualitative insights.Jindong NI (Co-corresponding Author): Oversaw the entire research process, reviewed scientific and ethical rigor, and was responsible for reviewing, revising, and finalizing the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePayne R, Frejah I, Abbey E, Badcoe R, Delaney B, Mitchell C (2025) Transitioning between clinical and academic practice from the perspectives of clinical academic trainees, academic training programme directors and academic supervisors: a mixed methods study. BMC Med Educ 25(1): 1-9. https://doi.org/10.1186/s12909-025-06803-w\u003c/li\u003e\n\u003cli\u003eQi XJ.(2024) Ten-year review and reflection on standardized residency training in China. Chin J Grad Med Educ 8(1):1\u0026ndash;6. https://doi.org/10.3969/j.issn.2096-4293.2024.01.001\u003c/li\u003e\n\u003cli\u003eXu SX (2024) Ten years of standardized residency training: advancing amid challenges. Hosp Adm J 20(9):46\u0026ndash;56\u003c/li\u003e\n\u003cli\u003eMo XQ, Tao LH, Tang QL, et al (2016) Cultivation of research competence among clinical master\u0026rsquo;s degree postgraduates under the \u0026ldquo;dual-track integration\u0026rdquo; model. Chin Med Educ Technol (1) :12\u0026ndash;14. https://doi.org/10.13566/j.cnki.cmet.cn61-1317/g4.201601004\u003c/li\u003e\n\u003cli\u003eHuang L, Hu Y, Jin LJ et al (2018) Problems and countermeasures in cultivating research ability of clinical medicine master\u0026rsquo;s degree postgraduates under the dual-track integration model. In: Proceedings of the 2018 Jiangsu-Zhejiang-Shanghai Medical Education Annual Conference; 2018\u003c/li\u003e\n\u003cli\u003eWang B, Lai WJ, Liu XY et al (2024) Mental health status and influencing factors of medical professional degree master\u0026rsquo;s students under the \u0026ldquo;dual-track integration\u0026rdquo; model. West China Med J 39(7):1114\u0026ndash;1120. https://doi.org/10.7507/1002-0179.202406090\u003c/li\u003e\n\u003cli\u003eXu SX (2024) Addressing the era-specific questions of China\u0026rsquo;s standardized residency training. Hosp Adm J 20(9):57\u0026ndash;60\u003c/li\u003e\n\u003cli\u003eHua XJ, Qi LJ, Li M (2024) Practical dilemmas and feasible pathways of standardized residency training for clinical medicine professional degree postgraduates. Health Vocat Educ 42(24):128\u0026ndash;131. https://doi.org/10.20037/j.issn.1671-1246.2024.24.36\u003c/li\u003e\n\u003cli\u003eSun XY, Cui WJ, Han B (2024) Investigation and analysis of employment intentions of residents from \u0026ldquo;5+3\u0026rdquo; clinical medicine professional degree master\u0026rsquo;s programs. Chin J Grad Med Educ 8(12):918\u0026ndash;922. https://doi.org/10.3969/j.issn.2096-4293.2024.12.009\u003c/li\u003e\n\u003cli\u003eChina Elite Teaching Hospital Alliance for Residency Training (2022) Consensus on the core competency framework for residents in China. Med J Peking Union Med Coll Hosp 13(1):17\u0026ndash;23. https://doi.org/10.12290/xhyxzz.2021-0755\u003c/li\u003e\n\u003cli\u003eChen YL, Hu YZ, Li XR (2021) Competency-based cultivation of clinical medicine postgraduates and related issues. Hosp Manag Forum 38(3):84\u0026ndash;86. https://doi.org/10.3969/j.issn.1671-9069.2021.03.023\u003c/li\u003e\n\u003cli\u003eWang YL, Xu AY, Wang Y et al (2022) Construction of a competency-based quality evaluation system for clinical professional degree postgraduates. Chin Contin Med Educ 14(17):160\u0026ndash;163. https://doi.org/10.3969/j.issn.1674-9308.2022.17.041\u003c/li\u003e\n\u003cli\u003eDi X, Jin Q, Ma TG et al (2025) Practice exploration of interdisciplinary integration in competency cultivation of respiratory clinical postgraduates. Int J Geriatr Med 46(2):249\u0026ndash;252. https://doi.org/10.3969/j.issn.1674-7593.2025.02.023\u003c/li\u003e\n\u003cli\u003eMa MJ, Huang XY, Wang S, et al (2024) Problems in cultivating research ability of clinical professional master\u0026rsquo;s degree postgraduates. Asian Case Rep Emerg Med 12(3):71\u0026ndash;75. https://doi.org/10.12677/acrem.2024.123010\u003c/li\u003e\n\u003cli\u003eXin Z, Zhang JF, Sun J et al (2019) Consideration on the training of postgraduates with degrees in imaging medicine under the model of dual-track integration. Educ Modernization\u003c/li\u003e\n\u003cli\u003eFrank JR, Snell LS, Cate OT et al (2010) Competency-based medical education: theory to practice. Med Teach 32(8):638\u0026ndash;645. https://doi.org/10.3109/0142159X.2010.501190\u003c/li\u003e\n\u003cli\u003eFrenk J, Chen L, Bhutta ZA et al (2010) Health professionals for a new century: transforming education to strengthen health systems in an interdependent world. Lancet 376(9756):1923\u0026ndash;1958. https://doi.org/10.1016/S0140-6736(10)61854-5\u003c/li\u003e\n\u003cli\u003eCrum AJ, Salovey P, Achor S (2013) Rethinking stress: the role of mindsets in determining the stress response. J Pers Soc Psychol 104(4):716\u0026ndash;733. https://doi.org/10.1037/a0031201\u003c/li\u003e\n\u003cli\u003eJia XY, Chang X, Shi YX et al (2023) Current status and reflections on core competencies of clinical professional postgraduates. Chin J Med Educ Res 22(5):786\u0026ndash;790. https://doi.org/10.3760/cma.j.cn116021-20210608-01295\u003c/li\u003e\n\u003cli\u003eQi XJ (2024) Ten years of standardized residency training: from \u0026ldquo;5+0\u0026rdquo; to \u0026ldquo;5+3+X\u0026rdquo;. China Health (2):79\u0026ndash;82. https://doi.org/10.15973/j.cnki.cn11-3708/d.2024.02.041\u003c/li\u003e\n\u003cli\u003eHou L, Zhang Z (2019) Stressors and anxiety symptoms among medical postgraduates: mediating role of negative emotions and moderating effect of social support. Chin J Behav Med Brain Sci 28(12):1108\u0026ndash;1112. https://doi.org/10.3760/cma.j.issn.1674-6554.2019.12.010\u003c/li\u003e\n\u003cli\u003eChen XC, Li N, Zheng ZM et al (2020) Impact of medical-education collaborative training reform on research ability of clinical master\u0026rsquo;s degree students. Chin High Med Educ (12):5\u0026ndash;7. https://doi.org/10.3969/j.issn.1002-1701.2020.12.003\u003c/li\u003e\n\u003cli\u003eChipeta MC, Hwang HF (2024) Defining and characterizing the nursing student\u0026ndash;faculty relationship in clinical practice: a concept analysis. Adv Med Educ Pract 15:1113\u0026ndash;1125. https://doi.org/10.2147/AMEP.S494380\u003c/li\u003e\n\u003cli\u003eCusimano MC, Ting DK, Kwong JL et al (2019) Medical students learn professionalism in near-peer led, discussion-based small groups. Teach Learn Med 31(3):307\u0026ndash;318. https://doi.org/10.1080/10401334.2018.1516555\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":"Clinical professional master's students, Dual-track integration, Core competency, Clinical practice adaptability, Protected research time, Graduate medical education, China","lastPublishedDoi":"10.21203/rs.3.rs-8708160/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8708160/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIn China, the integrated training model for clinical medicine professional master\u0026rsquo;s students merges postgraduate education with standardized residency training. Trainees face dual pressures from clinical rotations and academic research, which may compromise competency development. However, the role of adjustable factors, particularly clinical practice adaptability and protected research time, is not well defined.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study evaluated the current state of core competencies among these students and investigated the influence of clinical practice adaptability and the sufficiency of protected research time.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA multicenter, cross-sectional survey was administered in Guangdong Province between December 2024 and January 2025. Participants included 921 students from 41 national standardized residency training bases. Data were collected using structured questionnaires comprising the Core Competency Scale and the Clinical Practice Adaptability Scale. Analyses involved nonparametric tests and multiple linear regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCore competency dimensions were ranked by mean score (highest to lowest): Professionalism, Patient Care, Communication and Collaboration, Lifelong Learning, Knowledge and Skills, and Teaching Capability. This profile indicated relative deficits in Teaching Capability and Knowledge and Skills. Univariate analyses revealed that total competency scores were significantly associated with gender, place of origin, adequacy of protected research time, role identity, stress attitude, and clinical practice adaptability (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The regression model identified both clinical practice adaptability (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.425, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and adequacy of protected research time (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.079, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010) as independent, positive predictors of core competency, with adaptability being the strongest contributor. The model accounted for 21.7% of the score variance (Adjusted \u003cem\u003eR\u003c/em\u003e\u0026sup2; =0.217).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eStudents in the integrated training model show an uneven development of core competencies. Interventions aimed at improving clinical practice adaptability and guaranteeing sufficient dedicated research time are essential for balanced competency growth. Training institutions should adopt focused measures, including establishing specialized clinical teaching teams and securing protected time for scholarly activities.\u003c/p\u003e","manuscriptTitle":"Clinical Adaptability and Protected Research Time as Key Determinants of Core Competency: A Cross-sectional Study of China's \"Dual-Track Integration\" Clinical Professional Master’s Students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 11:46:28","doi":"10.21203/rs.3.rs-8708160/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-03-25T07:31:59+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-02T10:51:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-09T11:56:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-07T14:00:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2026-02-07T13:51:38+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":"9de753db-0aa6-477a-81ae-f679dd3fd32a","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-26T11:46:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 11:46:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8708160","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8708160","identity":"rs-8708160","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}