Factors Affecting Medical Postgraduates’ Local Employment Intention in Guangxi: Implications for Talent Retention in Ethnic Minority Underdeveloped Areas in China

Factors Affecting Medical Postgraduates’ Local Employment Intention in Guangxi: Implications for Talent Retention in Ethnic Minority Underdeveloped Areas in China | 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 Factors Affecting Medical Postgraduates’ Local Employment Intention in Guangxi: Implications for Talent Retention in Ethnic Minority Underdeveloped Areas in China Jiaxiao Jiang, Liuxing Zhou, Feng Tang, Suyan Zhou, Xuna Tao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9166347/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Objective This study aimed to investigate the factors influencing the local employment intention of medical postgraduates in Guangxi,with a focus on identifying key determinants that affect their decision to work within the region.The finding are intended to provide evidence-based recommendations for enhancing talent retention strategies in underdeveloped ethnic minority areas and to support the development of targeted career guidance and policy interventions in medical education. Methods A questionnaire survey was conducted among medical postgraduates at Guangxi Medical University from March to April 2024. Chi-square tests were used for univariate analysis of factors related to employment willingness, and binary logistic regression was applied to determine the independent predictors of intention to work in Guangxi. Results A total of 670 questionnaires were collected, with 626 valid ones (effective rate 93.4%). Among the valid participants, 44.1% expressed unwillingness to work in Guangxi. Univariate analysis showed that gender, ethnicity, place of origin, household registration status, only-child status, major type, first-tier city experience, academic year, and parental preferences were significantly associated with employment willingness (all P < 0.05). Binary logistic regression further revealed that urban origin (OR = 0.524, 95%CI:0.285–0.964, P = 0.038), non-Guangxi household registration (reference: Guangxi household registration; OR = 2.958, 95%CI:1.507–5.805, P = 0.002), majoring in public health and preventive medicine (OR = 0.375, 95%CI:0.202–0.697, P = 0.002), and parental opposition (reference: parental support; OR = 0.008, 95%CI:0.002–0.034, P < 0.001) were key factors affecting willingness to stay. Conclusion The willingness of Guangxi Medical University’s medical postgraduates to work in Guangxi is jointly influenced by place of origin, household registration, major type, and parental attitudes. Targeted interventions including tailored guidance for urban-origin and public health majors, policy support for non-local registrants are needed to improve regional medical talent retention. Guangxi Medical University Medical Postgraduates Employment Intention Influencing factors 1. Introduction There is an imbalance in the distribution of medical resources between the eastern coastal regions and central-western regions in China. The flow of talents has emerged as a significant constraint for development of medical services in underdeveloped areas [1,2] . Nationally, the inter-provincial talent flow in China exhibits a distinct “eastern agglomeration” trend: According to data from the National Bureau of Statistics, over the past decade, high-skilled talents (including medical professionals) in central and western regions have migrated to first-tier cities or eastern coastal provinces, due to factors such as superior economic conditions, broad career development platforms, and favorable living environment. This “brain drain”phenomenon is particularly prominent in border and ethnic minority regions, where the shortage of high-level medical talents has become a bottleneck for improving the level of primary medical services and responding to public health emergencies. As a minority autonomous region in southwestern China, Guangxi Zhuang Autonomous Region is confronted with the dual challenges of economic underdevelopment (ranking 19th among 31 provincial-level administrative units in terms of GDP in 2024) and a shortage of medical talent [3] . Recent studies have shown that Guangxi has long experienced a net outflow of population. Evidence indicates that from 2000 to 2020, Guangxi was one of the provinces with large-scale inter-provincial labor outflow, and most of its counties still experienced net population loss in 2021 [4] . For highly educated talents, according to the data of college graduates in Guangxi in 2024, only 61% chose to work locally, and the retention rate of highly educated individuals was even lower. The retention rate of postgraduate students was only 42%, indicating a significant outflow of high-level talents [5] . Globally, talent migration from underdeveloped to developed regions is a common phenomenon [6-10] . However, China’s unique background makes the situation more complex.. Unlike the international “medical brain drain”driven primarily by salary gaps and training opportunities [4] , the medical talent flow between regions in China is further shaped by institutional factors (e.g., the household registration system), cultural connections (e.g., family origin and ethnic identity), and regional policy differences. For instance, research on the movement of medical talents in Liaoning province and ten western provinces of China have indicated that individuals with rural household registration are significantly more willing to work in rural areas than those with urban registrations. Additionally, medical students tend to choose to return to their hometowns for employment and usually receive support [11] .However, existing domestic studies primarily focus on macro-level talent flow trends or single-factor analyses (e.g., salary levels), lacking targeted empirical research on medical postgraduates in border ethnic regions like Guangxi. Specifically, there is currently a lack of evidence on how demographic characteristics (e.g., urban/rural origin), institutional constraints (e.g., household registration), and familial factors jointly influence the employment location choices of medical postgraduates in underdeveloped areas. Guangxi Medical University, the top medical institution in Guangxi, ranks 901-1000 globally in the ShanghaiRanking’s Academic Ranking of World Universities (2024) and is a major provider of high-level medical talents in the region [12] . The employment choices of its graduates directly determine the scale and quality of the future medical workforce in Guangxi. Against this backdrop, this study conducts an investigation using Guangxi Medical University as a case, aiming to systematically understand the willingness of medical graduate students to work in Guangxi and to determine the key influencing factors using quantitative methods. This study aims to contribute to the literature on the retention of medical talents in minority areas, drawing on the context of national medical talent allocation and regional development disparities. It seeks to provide evidence-based insights for refining talent policies in Guangxi and other central and western provinces of China. 2. Methods 2.1 Questionnaire Design This study employed a self-designed questionnaire, and its contents were developed through a literature review, expert consultation, and other methodologies. During the design process, opinions from professionals in relevant fields were also sought, including senior experts from university student affairs, personnel management, and enterprise human resources departments. These experts provided valuable suggestions on the validity and applicability of the questionnaire.The questionnaire consists of two sections: section one covers sociodemographic information, and section two concerns employment preferences and the influencing factors. In this study, the willingness to stay and work in Guangxi is the dependent variable. This was measured in the questionnaire through the following question: ‘Are you willing to stay and work in Guangxi after graduation?’ The question provided the following options: “Willingness” refers to considering Guangxi as the preferred region for employment and actively submitting resumes; “Unwilling”means generally not considering employment in Guangxi, or only considering it as a backup option; And “Neutral” means having no clear preference for employment location and making decisions based on available job opportunities.The questionnaire used in this study is provided as Supplementary File 1. 2.2 Data collection This cross-sectional study was conducted among postgraduate students at Guangxi Medical University between March and April 2024.The study population included several medical majors students. A priori power analysis (R4.3.1, α= 0.05, power= 0.8, effect size f = 0.15) indicated a minimum required sample size of 139.To enhance robustness and account for attrition, we targeted a larger sample.Using simple random sampling, based on randomly generated numbers by a computer, 700 students were randomly selected from the school student list (N = 4000) according to their student numbers, and were invited to participate online.Quality control procedures was performed based on three exclusion criteria: a) Completion time <40 seconds; b) identical responses across all survey items; c) Answers inconsistent with the provided options. Questionnaires satisfying any of these criteria were excluded from subsequent analyses. After removing 34 invalid responses, 626 valid questionnaires were retained for final data analysis (response rate:89.4%). The Institutional Ethics Committee of Guangxi Medical University and the Postgraduate Education Centre of Guangxi Medical University approved this study. The study was conducted in accordance with the Declaration of Helsinki regarding web-based questionnaires, and all participants signed an online consent form to participate. 2.3 Statistical Analysis Statistical analyses were conducted using SPSS 26.0 software. Categorical data were characterized by frequencies and percentages. Intergroup differences were evaluated via chi-square tests or Fisher’s exact probability tests. In the univariate analysis, the Chi-square test ( c 2 test) was employed to assess the association between each categorical independent variable (e.g., gender, ethnicity, place of origin) and the binary outcome variable (willingness to remain in Guangxi for employment). Variables that demonstrated a statistically significant association in the univariate analysis ( P < 0.05) were subsequently included as candidate variables in the binary logistic regression analysis. Multinomial logistic regression was applied for multifactorial analysis of factors influencing postgraduates’ willingness to remain in Guangxi for employment. The key dependent variable was 'willingness to remain in Guangxi for employment'.During data collection,a three-category scale(willing,Neutral,Unwilling)was used to capture respondents' initial attitudes.As the study aimed to identify and contrast individuals with a define intention to stay,and to facilitate the use of binary logistic regression,the dependent variable was processed as follows for analysis:Responses originally categorized as 'Neutral ' and 'Unwilling' were merged into a single group defined as 'Not explicitly willing '(coded as 0),which was then contrasted with the 'Willing' group(coded as 1)in a binary dependent variable.The Odds ratio (OR) and the corresponding 95% confidence interval (CI) were used to quantify the degree of influence exerted by each factor on the willingness to work in Guangxi. A two-tailed significance level of α=0.05 was adopted, with P value less than 0.05 considered statistically significant. 3. Results 3.1 Demographic Characteristics of Participants A total of 626 master’s and doctoral students were included in this study. Among these participants, 44.1% (276/626) expressed unwilling to pursue employment in Guangxi. All baseline characteristics of the study cohort are summarized in Table 1. The sample comprised 441 females (70.4%) and 185 males (29.6%). In terms of ethnicity, 438 individuals (70.0%) identified as Han Chinese, 150 (24.0%) were Zhuang, and 38 (6.0%) as belonging to other ethnic groups. Regarding place of origin, 400 students (63.9%) hailed from rural areas, while 226 (36.1%) were urban residents. The majority of participants were master’s students (93.5%) ,with 71.5% specializing in clinical medicine or public health . Table 1 Demographic characteristics of participants Demographic characteristics Number (%) Gender Male 185(29.6) Female 441(70.4) Ethnicity Han 438(70.0) Zhuang 150(24.0) Other ethnic group 38(6.1) Place of origin Urban 226(36.1) Rural 400(63.9) Place of household registration Guangxi household registration 406(64.9) non-Guangxi household registration 220(35.1) Annual household income 500000RMB 18(2.9) Single-child Yes 164(26.2) No 462(73.8) Major type Clinical Medicine 265(42.3) Public Health and Preventive Medicine 183(29.2) Pharmaceutical Sciences 66(10.5) Basic Medical Sciences 53(8.5) Nursing 19(3.0) Other majors 40(6.4) Grade First-year graduate student 212(33.9) Second-year graduate student 176(28.1) Third-year graduate student 197(31.5) First-year doctoral student 16(2.6) Second-year doctoral studen 11(1.8) Third-year doctoral studen 12(1.9) Other grade 2(0.3) 3.2 Univariate Analysis of Willingness to Work in Guangxi Univariate analysis identified multiple factors that were significantly associated with medical postgraduates’ willingness to remain in Guangxi for employment, including gender, ethnicity, place of origin, household registration status, Single-child status,major type, prior educational or internship experiences in first-tier cities (Beijing, Shanghai, Guangzhou, Shenzhen), current academic year, and parental preferences (Table 2). Specific findings are as follows: females participants (59.4%) exhibited a significantly higher willingness to stay than males participants (47.6%) (χ²=7.415, P =0.006). Zhuang students (84.0%) demonstrated a stronger intent to remain compared with Han students (47.7%) (χ²=64.106, P<0.001). Rural-origin students (62.5%) were more inclined to stay than urban-origin peers (44.2%) (χ²=19.516, P <0.001). Students with Guangxi household registration displayed a significantly higher willingness to remain (77.8%) than non-local registrants (15.5%) (χ²=225.221, P <0.001). Single-child reported a greater willingness to stay compared with non-only children (56.7% vs. 39.6%) (χ²=14.352, P <0.001).Medical students showed the strongest willingness to remain in Guangxi (61.9%), while students from other disciplines exhibited lower willingness (χ²= 22.610, P < 0.001). Students with prior experiences in first-tier cities showed a lower willingness to remain relative to those without such experiences (37.9% vs. 58.8%) (χ²=13.250, P <0.001). Third-year graduate students showed the highest willingness to remain in Guangxi (64.5%) (χ²= 19.148, P = 0.004). In addition, factors including academic performance ranking, English proficiency, and parental education level showed no significant association with the outcome of interest. Table 2 Univariate Analysis of Factors Influencing Medical Postgraduates' Willingness to Work in Guangxi (N=626) Demographic characteristics number Willingness to Work in Guangxi c 2 P unwilling willing Gender 7.415 0.006 Male 185(29.6) 97(52.4) 88(47.6) Female 441(70.4) 179(40.6) 262(59.4) Ethnicity 64.106 ＜0.001 Han 438(70.0) 229(52.3) 209(47.7) Zhuang 150(24.0) 24(16.0) 126(84.0) Other ethnic group 38(6.1) 23(60.5) 15(39.5) Place of origin 19.516 ＜0.001 Urban 226(36.1) 126(55.8) 100(44.2) Rural 400(63.9) 150(37.5) 250(62.5) Place of household registration 225.221 ＜0.001 Guangxi household registration 406(64.9) 90(22.2) 316(77.8) Non-Guangxi household registration 220(35.1) 186(84.5) 34(15.5) Single-child 14.352 ＜0.001 Yes 164(26.2) 93(56.7) 71(43.3) No 462(73.8) 183(39.6) 279(60.4) Major type 22.610 ＜0.001 Clinical Medicine 265(42.3) 101(38.1) 164(61.9) Public Health and Preventive Medicine 183(29.2) 97(53.0) 86(47.0) Pharmaceutical Sciences 66(10.5) 28(42.4) 38(57.6) Basic Medical Sciences 53(8.5) 29(54.7) 24(45.3) Nursing 19(3.0) 12(63.2) 7(36.8) Other majors 40(6.4) 9(22.5) 31(77.5) Grade 19.148 0.004 First-year graduate student 212(33.9) 108(50.9) 104(49.1) Second-year graduate student 176(28.1) 80(45.5) 96(54.5) Third-year graduate student 197(31.5) 70(35.5) 127(64.5) First-year doctoral student 16(2.6) 8(50.0) 8(50.0) Second-year doctoral studen 11(1.8) 8(72.7) 3(27.3) Third-year doctoral studen 12(1.9) 2(16.7) 10(83.3) Academic Ranking 1.509 0.470 Top 10% 104(16.6) 42(40.4) 62(59.6) 10%-50% 387(61.8) 169(43.7) 218(56.3) The latter 50% 135(21.6) 65(48.1) 70(51.9) Study or internship experience in Beijing, Shanghai, Guangzhou, or Shenzhen 13.250 ＜0.001 Yes 87(13.9) 54(62.1) 33(37.9) No 539(86.1) 222(41.2) 317(58.8) English Proficiency Level 4.346 0.226 Did not pass CET-4 20(3.2) 7(35.0) 13(65.0) Pass CET-4 168(26.8) 85(50.6) 83(49.4) pass CET-6 429(68.5) 180(42.0) 249(58.0) Pass TOELF/GRE/IELTS 9(1.4) 4(44.4) 5(55.6) Father's educational attainment 5.724 0.334 Elementary school and below 150(24.0) 61(40.7) 89(59.3) Junior High School 205(32.7) 84(41.0) 121(59.0) High School/Vocational School 131(20.9) 58(44.3) 73(55.7) Junior college 61(9.7) 31(50.8) 30(49.2) Bachelor's Degree (Correspondence Program) 66(10.5) 34(51.5) 32(48.5) Graduate students and above 13(2.1) 8(61.5) 5(38.5) Mother's educational attainment 5.083 0.406 Elementary school and below 236(37.7) 93(39.4) 143(60.6) Junior High School 195(31.2) 87(44.6) 108(55.4) High School/Vocational School 97(15.5) 45(46.4) 52(53.6) Junior college 54(8.6) 27(50.0) 27(50.0) Bachelor's Degree (Correspondence Program) 40(6.4) 22(55.0) 18(45.0) Graduate students and above 4(0.6) 2(50.0) 2(50.0) Parental preference 326.264 ＜0.001 Support 327(52.2) 35(10.7) 292(89.3) Neutral 198(31.6) 143(72.2) 55(27.8) Oppose 101(16.1) 98(97.0) 3(3.0) 3.3 Binary Logistic Regression Analysis of Influencing Factors Binary logistic regression identified key determinants of medical postgraduates’ willingness to work in Guangxi (Table 3). Students of urban-origin exhibited a lower odds of being willing compared to rural counterparts (OR=0.483, 95% CI: 0.284-0.820, P =0.007). In contrast, students with Guangxi household registration displayed a significantly higher odds of such willingness (OR=3.323, 95% CI: 1.791-6.165, P<0.001). Students majoring in Public health and preventive medicine(OR=0.170,95%CI=0.048-0.593,P=0.005)and Nursing(OR=0.126, 95%CI=0.018-0.855, P=0.034) students demonstrated a significantly lower willingness to work in Guangxi compared to those in other majors. Additionally,compared with parental opposition,parental support（OR=126.920,95%CI=33.179-485.507, p < 0.001） or neutrality(OR = 7.576, 95% CI = 2.144-26.772, p = 0.002) toward working in Guangxi was associated with a significant increase in students’ willingness to work in Guangxi . Table 3 Logistic Regression Analysis of Multiple Factors Influencing Graduate Students' Willingness to Work in Guangxi Demographic characteristics N OR(95% CI) P Place of origin Rural 400(63.9) reference Urban 226(36.1) 0.483(0.284-0.820) 0.007 Place of household registration Non-Guangxi household registration 220(35.1) reference Guangxi household registration 406(64.9) 3.323(1.791-6.165） <0.001 major type 0.008 Other majors 40(6.4) reference Clinical Medicine 265(42.3) 0.428(0.125-1.458) 0.175 Public Health and Preventive Medicine 183(29.2) 0.170(0.048-0.593) 0.005 Pharmaceutical Sciences 66(10.5) 0.258(0.063-1.048) 0.058 Basic Medical Sciences 53(8.5) 0.451(0.105-1.937) 0.284 Nursing 19(3.0) 0.126(0.018-0.855) 0.034 Parental preference <0.001 Oppose 101(16.1) reference Support 327(52.2) 126.920（33.179-485.507） <0.001 Neutral 198(31.6) 7.576（2.144-26.772） 0.002 4. Discussion This study examined the factors influencing medical postgraduates’ local employment intention in Guangxi ,Binary logistic regression analysis revealed that household registration status,place of origin ,specialty type and parental attitudes as key determinants of medical postgraduates’ willingness to work in Guangxi. Specifically, Guangxi household registration (OR=3.323, P <0.001),rural origin (compared to urban origin,OR=0.483, P =0.007),parental support (OR=3.323， P <0.001)and neutral parental attitudes(OR=7.576, P =0.002)were positively correlated with the intention to remain in Guangxi.Conversely, majors in Public Health and Preventive Medicine (OR = 0.170, P = 0.005) and Nursing (OR = 0.126, P = 0.034) were negatively correlated with this intention. The significant association between Guangxi household registration and preference for working in Guangxi essentially stems from the combined effects of institutional orientation, social capital, cost of living and policy dividends.The household registration system remains a fundamental institution influencing China’s labor allocation [13] . In Guangxi ,staffing quotas for grassroots healthcare positions are heavily favour local registrants.Local medical institutions also prefer to hire locally educated candidates with stable household status, who demonstrate higher retention rates. This employment preference perpetuates the longstanding ‘logic of dual labour market segmentation’ in Chinese cities, where high-quality positions are often tied to local registration [14] .Non-local students face intense competition in inter-regional civil service exams and challenges in family In contrast, Students with Guangxi household registration directly benefit from local staffing policies while leveraging familial networks to reduce the adapting costs. Additionally, Guangxi’s lower living costs also align with their lifestyle expectations, offering greater career stability. Family socioeconomic status (SES)—encompassing economic, education, and cultural capital—is an ascribed factor influencing occupational mobility [15] .Urban students typically come from higher SES families, enabling them to support interregional migration and seek opportunities in developed regions,following a ‘resources-returns’ logic.This aligns with existing research findings that married female PhD students who are from urban areas and have a high household income are inclined to choosing first-tier city as employment [10] .Conversely, rural students exhibit distinct socioeconomic.Their families have limited capacity to support migration, making local employment a risk mitigation strategy—consistent with studies noting that children from low SES families often prefer local employment [16,17] . Simultaneously, rural students’ employment expectations align more closely with Guangxi’s healthcare resource distribution, characterized by significant demand at the county amid concentrated urban competition [18] . This dual alignment of resource constraints and employment expectations makes rural students relatively more inclined to seek employment within Guangxi. From a disciplinary perspective,students of Public heath and prevention medicine and Nursing exhibit a significantly lower willingness to seek employment in Guangxi than student of other subjects. The underlying cause lies in the mismatch between positions attractiveness in Guangxi and the career expectations of these professionals, aligning with expectancy theory regarding the balance between expected rewards and effort [19] .For public health and preventive medicine, challenges centre on an imbalance between compensation and investment. Chinese disease control system suffers from structural issues including inadequate compensation safeguards and low utilization of incentive mechanisms [20] . Within Guangxi’s context of relatively limited financial investment,the gap between job compensation and career expectations becomes more pronounced, diminishing retention intention. Nursing students face the dual constraints of ‘uneven resource distribution and insufficient development support’. High-quality nursing positions in Guangxi are concentrated in few tertiary hospitals,while primary institutions offer low compensation and lack critical retention factors such as autonomy and training opportunities—factors identified internationally as core drivers for nurse retention [21,22] . The job characteristics of these two specialties conflict with Guangxi’s medical resource distribution of “concentrated in cities and weak at the grassroots level”. Compared to eastern coastal cities like Shenzhen, which offer better work-life balance and organizational suppoort, Guangxi’s shortcomings in compensation incentives and career paths clarity further reduce willingness to stay [23,24] . Current research indicates that parental support or neutrality significantly was positively correlated with retention intention. This aligns with social support theory,which family support reduces uncertainty in career choices [21] .Parental support provides emotional validation and practical assistance (e.g. leveraging local networks for housing and occupational adaptation ).While a neutral stance reduces decision-making resistance through tatic approval. This correlation exhibits regional specificity in Guangxi, potentially reinforced by the traditional ‘family clustering’ culture among the Zhuang ethnic group,where 84% of Zhuang students demonstrate high retention willingness. Families in east region may prioritise career development over familial bonds, whereas families in Guangxi emphasizes local retention to preserve family ties [25] . Combined with Guangxi’s practical conditions, such as institutional preference for local graduates and lower living costs, the positive relationship between parental attitudes and retention intention is strengthened. Factors significant in univariate analysis—gender, ethnicity, single-child status, grade level, and experience in Beijing, Shanghai, Guangzhou, or Shenzhen—failed to reach statistical significance in binary logistic regression.This occurs because their independent effects were confounded or masked by core variables within the model:ethnicity's explanatory power was overshadowed by household registration due to high collinearity.The latent influences of gender and single-child status were subsumed under parental attitudes.Grade differences depended on major and job-seeking stage while exhibiting weak idenpendent.Experiences in Beijing, Shanghai, Guangzhou, or Shenzhen were implicitly correlated with non-Guangxi household registration, causing their effects to be masked. The purpose of binary logistic regression was precisely to isolate such core net effects by controlling for confounders, ultimately corroborating that employment intentions in Guangxi are influenced by multiple synergistic core mechanisms. 5. Limitations This study has several limitations. First, despite the use of random sampling, Students unwilling to work in Guangxi—such as those dissatisfied with the local employment conditions or inclined to seek opportunities elsewhere—may be more likely to refuse participation.This could lead to an overestimation of the reported retention intention rate(55.9%) and potentially inflate the positive effects of factors such as parental attitude and household,while underestimating the negative impact of major type.Consequently,the generalizability of the findings to all Guangxi medical graduates may be limited.Second,the household registration was simply categorized as “Guangxi/non-Guangxi”, without further stratification by regional economic development.This may mask important variations among non-local students.For instance, those from other undeveloped provinces may have higher retention intentions than those from developed due to closer alignment with Guangxi’s economic and professional landscape.A more nuanced classification would allow for deeper insight into how registration status shapes employment decisions.Third,this study focused on exclusively on individual-level factors and did not incorporate the external factors such as job quality,salary levels,or career advancement opportunities within Guangxi’s healthcare system. Employment choices arise from the interaction between individual intention intent and external opportunity structures.Even if students have the intention to stay, inadequate job conditions may still lead to a gap between intention and actual behavior,limiting the direct applicability of our findings yo talent retention policy.The above limitations could be improved by redesigning the study in the future. 6. Conclusion In summary, this study, focusing on postgraduate students at Guangxi Medical University, yield critical insights for talent development and career guidance strategies formulation. The results highlight the necessity for institutional initiatives to design targeted career planning programs that are aligned with disciplinary characteristics and labor market exigencies, particularly for students of urban origin, those with non-Guangxi registrants, and those specializing in public health and preventive medicine and nursing. Furthermore, enhancing communication with postgraduate parents through awareness campaigns and guidance could improve students’ professional competitiveness and career satisfaction.By addressing these demographic-specific and familial determinants, universities and policymakers can more effectively bolster regional talent retention and optimize the distribution of the healthcare workforce in developing economic regions such as Guangxi. Declarations Ethics approval and consent to participate: The Institutional Ethics Committee of Guangxi Medical University and the Postgraduate Education Centre of Guangxi Medical University approved this study. The study was conducted in accordance with the Declaration of Helsinki regarding web-based questionnaires, written informed consent was obtained from all participants prior to their inclusion in the study. Clinical trial number: Not applicable Consent for publication: Not applicable. This manuscript does not contain any individual person’s data in any form. Availability of data and materials: The datasets used and analysed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors declare that they have no competing interests. Funding: University Student Employment and Entrepreneurship Research Project of Guangxi Medical University, 2025JC01. Innovation Project of GuangxiGraduate Education, JGY2021058 Authors' contributions: Qi Meng and Li Ye conceived and designed the study. Jiaxiao Jiang designed the study and drafted the manuscript. Xunan Tao and Fengning Tang were responsible for data collection. Feng Tang and Suyan Zhou performed the data analysis. Liuxing Zhou analyzed and synthesized the results and critically revised the manuscript. All authors have read and approved the final version of the manuscript. 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The Geography of Intergenerational Mobility in the United States *[J]. The Quarterly Journal of Economics, 2014, 129(4): 1553–1623. Region G O O T C G C G O O T P S G O G Z A. Implementation Plan for Further Improving the Healthcare Service System in Guangxi[R]. Health Commission of Guangxi Zhuang Autonomous Region, 2023. Wigfield A, Eccles J S. Expectancy–value theory of achievement motivation[J]. Contemporary Educational Psychology, 2000, 25(1): 68–81. Zhang N W, D.; Wang, K.; Wu, Q.; Zhao, M.; Mao, A.; Qiu, W. Optimizing compensation system in China's Disease Control and Prevention Institutions: historical evolution, current challenges, and reform pathways[J]. Chinese Journal of Public Health, 2025, 41(7): 886. Zhang X, Zhang Y, Han J, et al. Employment Intention and Associated Factors of Nursing Graduates: A Structural Equation Model[J]. J Nurs Manag, 2025, 2025: 7402874. Alshehri A M, Alqahtani W H, Moaili A A, et al. An analysis of the intention of female pharmacy students to work in community pharmacy settings in Saudi Arabia using the theory of planned behavior[J]. Saudi Pharm J, 2024, 32(4): 101996. Guo Q, Luo K, Hu R. The Spatial Correlations of Health Resource Agglomeration Capacities and Their Influencing Factors: Evidence from China[J]. Int J Environ Res Public Health, 2020, 17(22). Chen J, Lin Z, Li L A, et al. Ten years of China's new healthcare reform: a longitudinal study on changes in health resources[J]. BMC Public Health, 2021, 21(1): 2272. Zhang T, Li L, Bian Y. Final-year pharmacy undergraduate students' career intention and its influencing factors: a questionnaire study in northwest China[J]. BMC Med Educ, 2020, 20(1): 405. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFile1.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 23 May, 2026 Reviewers invited by journal 07 May, 2026 Editor assigned by journal 04 May, 2026 Editor invited by journal 13 Apr, 2026 Submission checks completed at journal 11 Apr, 2026 First submitted to journal 11 Apr, 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-9166347","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":641582976,"identity":"d88a2bce-f191-4824-825d-4dbd02545f75","order_by":0,"name":"Jiaxiao Jiang","email":"","orcid":"","institution":"Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiaxiao","middleName":"","lastName":"Jiang","suffix":""},{"id":641582977,"identity":"7bb0c386-1708-466f-bcf1-44f3a454a89c","order_by":1,"name":"Liuxing Zhou","email":"","orcid":"","institution":"Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Liuxing","middleName":"","lastName":"Zhou","suffix":""},{"id":641582980,"identity":"2710d0d5-471c-4c55-8814-b75c6a86f730","order_by":2,"name":"Feng Tang","email":"","orcid":"","institution":"Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Tang","suffix":""},{"id":641582982,"identity":"756e7353-84cf-4d36-a776-67055445918b","order_by":3,"name":"Suyan Zhou","email":"","orcid":"","institution":"Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Suyan","middleName":"","lastName":"Zhou","suffix":""},{"id":641582984,"identity":"9731c076-a0b5-4843-9d5e-960dc7c53d23","order_by":4,"name":"Xuna Tao","email":"","orcid":"","institution":"Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xuna","middleName":"","lastName":"Tao","suffix":""},{"id":641582991,"identity":"297d9506-897a-42a2-ac5f-dad3e189a9b8","order_by":5,"name":"Fengning Tang","email":"","orcid":"","institution":"Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fengning","middleName":"","lastName":"Tang","suffix":""},{"id":641582994,"identity":"723b57d9-782e-4697-8e9f-3a115c0ec5bb","order_by":6,"name":"Qi Meng","email":"","orcid":"","institution":"Guangxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"Meng","suffix":""},{"id":641583001,"identity":"6a94ee04-e425-4272-bf38-6eb09a8947db","order_by":7,"name":"Li Ye","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYFAC5oYDH6BMCSK1MDYcnEGyFmYekrQYHG9sPGzz63C0wQHmg7d5GOzyCGs5c7DhcG5fWu6GA2zJ1jwMycWEtdxIBGrpsQFq4TGT5mE4kNhAUMv9hw2HLXskgFr4vxGp5QZjw2GGH2Bb2IjTInkmseFgb0Na7szDbMaWcwySCWvhO3748Icff4AhcLz54Y03FXaEtSgcABKMbUCCGexOQuqBQB5s6B8iVI6CUTAKRsHIBQCkhUS365q98QAAAABJRU5ErkJggg==","orcid":"","institution":"Guangxi Medical University","correspondingAuthor":true,"prefix":"","firstName":"Li","middleName":"","lastName":"Ye","suffix":""}],"badges":[],"createdAt":"2026-03-19 07:38:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9166347/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9166347/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109799855,"identity":"c1bd99c1-435f-42cf-a825-38a5bbe3891f","added_by":"auto","created_at":"2026-05-22 15:34:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":383005,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9166347/v1/892d5233-4ca4-4768-9db8-f49090102966.pdf"},{"id":109438528,"identity":"248fd43e-8eec-452b-ae03-c0ec940fe752","added_by":"auto","created_at":"2026-05-18 06:44:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":96871,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9166347/v1/b9c7a566c695b81a83d4d4eb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Factors Affecting Medical Postgraduates’ Local Employment Intention in Guangxi: Implications for Talent Retention in Ethnic Minority Underdeveloped Areas in China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThere is an imbalance in the distribution of medical resources between the eastern coastal regions and central-western regions in China. The flow of talents has emerged as a significant constraint for development of medical services in underdeveloped areas\u003csup\u003e[1,2]\u003c/sup\u003e. Nationally, the inter-provincial talent flow in China exhibits a distinct \u0026ldquo;eastern agglomeration\u0026rdquo; trend: According to data from the National Bureau of Statistics, over the past decade, high-skilled talents (including medical professionals) in central and western regions have migrated to first-tier cities or eastern coastal provinces, due to factors such as superior economic conditions, broad career development platforms, and favorable living environment. This \u0026ldquo;brain drain\u0026rdquo;phenomenon is particularly prominent in border and ethnic minority regions, where the shortage of high-level medical talents has become a bottleneck for improving the level of primary medical services and responding to public health emergencies.\u003c/p\u003e\n\u003cp\u003eAs a minority autonomous region in southwestern China, Guangxi Zhuang Autonomous Region is confronted with the dual challenges of economic underdevelopment (ranking 19th among 31 provincial-level administrative units in terms of GDP in 2024) and a shortage of medical talent \u003csup\u003e[3]\u003c/sup\u003e. Recent studies have shown that Guangxi has long experienced a net outflow of population. Evidence indicates that from 2000 to 2020, Guangxi was one of the provinces with large-scale inter-provincial labor outflow, and most of its counties still experienced net population loss in 2021\u003csup\u003e[4]\u003c/sup\u003e. For highly educated talents, according to the data of college graduates in Guangxi in 2024, only 61% chose to work locally, and the retention rate of highly educated individuals was even lower. The retention rate of postgraduate students was only 42%, indicating a significant outflow of high-level talents\u003csup\u003e[5]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eGlobally, talent migration from underdeveloped to developed regions is a common phenomenon\u003csup\u003e[6-10]\u003c/sup\u003e. However, China\u0026rsquo;s unique background makes the situation more complex.. Unlike the international \u0026ldquo;medical brain drain\u0026rdquo;driven primarily by salary gaps and training opportunities\u003csup\u003e[4]\u003c/sup\u003e, the medical talent flow between regions in China is further shaped by institutional factors (e.g., the household registration system), cultural connections (e.g., family origin and ethnic identity), and regional policy differences. For instance, research on the movement of medical talents in Liaoning province and ten western provinces of China have indicated that individuals with rural household registration are significantly more willing to work in rural areas than those with urban registrations. Additionally, medical students tend to choose to return to their hometowns for employment and usually receive support\u003csup\u003e[11]\u003c/sup\u003e.However, existing domestic studies primarily focus on macro-level talent flow trends or single-factor analyses (e.g., salary levels), lacking targeted empirical research on medical postgraduates in border ethnic regions like Guangxi. Specifically, there is currently a lack of evidence on how demographic characteristics (e.g., urban/rural origin), institutional constraints (e.g., household registration), and familial factors jointly influence the employment location choices of medical postgraduates in underdeveloped areas.\u003c/p\u003e\n\u003cp\u003eGuangxi Medical University, the top medical institution in Guangxi, ranks 901-1000 globally in the ShanghaiRanking\u0026rsquo;s Academic Ranking of World Universities (2024) and is a major provider of high-level medical talents in the region\u003csup\u003e[12]\u003c/sup\u003e. The employment choices of its graduates directly determine the scale and quality of the future medical workforce in Guangxi. Against this backdrop, this study conducts an investigation using Guangxi Medical University as a case, aiming to systematically understand the willingness of medical graduate students to work in Guangxi and to determine the key influencing factors using quantitative methods. This study aims to contribute to the literature on the retention of medical talents in minority areas, drawing on the context of national medical talent allocation and regional development disparities. It seeks to provide evidence-based insights for refining talent policies in Guangxi and other central and western provinces of China.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e2.1 Questionnaire Design\u003c/p\u003e\n\u003cp\u003eThis study employed a self-designed questionnaire, and its contents were developed through a literature review, expert consultation, and other methodologies. During the design process, opinions from professionals in relevant fields were also sought, including senior experts from university student affairs, personnel management, and enterprise human resources departments. These experts provided valuable suggestions on the validity and applicability of the questionnaire.The questionnaire consists of two sections: section one covers sociodemographic information, and section two concerns employment preferences and the influencing factors. In this study, the willingness to stay and work in Guangxi is the dependent variable. This was measured in the questionnaire through the following question: \u0026lsquo;Are you willing to stay and work in Guangxi after graduation?\u0026rsquo; The question provided the following options:\u0026nbsp;\u0026ldquo;Willingness\u0026rdquo; refers to considering Guangxi as the preferred region for employment and actively submitting resumes;\u0026nbsp;\u0026ldquo;Unwilling\u0026rdquo;means generally not considering employment in Guangxi, or only considering it as a backup option; And\u0026nbsp;\u0026ldquo;Neutral\u0026rdquo; means having no clear preference for employment location and making decisions based on available job opportunities.The questionnaire used in this study is provided as Supplementary File 1.\u003c/p\u003e\n\u003cp\u003e2.2 Data collection\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study was conducted among postgraduate students at Guangxi Medical University between March and April 2024.The study population included several medical majors students. A priori power analysis (R4.3.1,\u0026nbsp;\u0026alpha;= 0.05, power= 0.8, effect size f = 0.15) indicated a minimum required sample size of 139.To enhance robustness and account for attrition, we targeted a larger sample.Using simple random sampling, based on randomly generated numbers by a computer, 700 students were randomly selected from the school student list (N = 4000) according to their student numbers, and were invited to participate online.Quality control procedures was performed based on three exclusion criteria: a) Completion time \u0026lt;40 seconds; b) identical responses across all survey items; c) Answers inconsistent with the provided options. Questionnaires satisfying any of these criteria were excluded from subsequent analyses. After removing 34 invalid responses, 626 valid questionnaires were retained for final data analysis (response rate:89.4%). The Institutional Ethics Committee of Guangxi Medical University and the Postgraduate Education Centre of Guangxi Medical University approved this study. The study was conducted in accordance with the Declaration of Helsinki regarding web-based questionnaires, and all participants signed an online consent form to participate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.3 Statistical Analysis\u003c/p\u003e\n\u003cp\u003eStatistical analyses were conducted using SPSS 26.0 software. Categorical data were characterized by frequencies and percentages. Intergroup differences were evaluated via chi-square tests or Fisher\u0026rsquo;s exact probability tests. In the univariate analysis, the Chi-square test (\u003cem\u003ec\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003cem\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/em\u003etest) was employed to assess the association between each categorical independent variable (e.g., gender, ethnicity, place of origin) and the binary outcome variable (willingness to remain in Guangxi for employment). Variables that demonstrated a statistically significant association in the univariate analysis (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) were subsequently included as candidate variables in the binary logistic regression analysis. Multinomial logistic regression was applied for multifactorial analysis of factors influencing postgraduates\u0026rsquo; willingness to remain in Guangxi for employment. The key dependent variable was \u0026apos;willingness to remain in Guangxi for employment\u0026apos;.During data collection,a three-category scale(willing,Neutral,Unwilling)was used to capture respondents\u0026apos; initial attitudes.As the study aimed to identify and contrast individuals with a define intention to stay,and to facilitate the use of binary logistic regression,the dependent variable was processed as follows for analysis:Responses originally categorized as \u0026apos;Neutral \u0026apos; and \u0026apos;Unwilling\u0026apos; were merged into a single group defined as \u0026apos;Not explicitly willing \u0026apos;(coded as 0),which was then contrasted with the \u0026apos;Willing\u0026apos; group(coded as 1)in a binary dependent variable.The Odds ratio (OR) and the corresponding 95% confidence interval (CI) were used to quantify the degree of influence exerted by each factor on the willingness to work in Guangxi. A two-tailed significance level of \u0026alpha;=0.05 was adopted, with \u003cem\u003eP\u003c/em\u003e value less than 0.05 considered statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e3.1 Demographic Characteristics of Participants\u003c/p\u003e\n\u003cp\u003eA total of 626 master\u0026rsquo;s and doctoral students were included in this study. Among these participants, 44.1% (276/626) expressed unwilling to pursue employment in Guangxi. All baseline characteristics of the study cohort are summarized in Table 1. The sample comprised 441 females (70.4%) and 185 males (29.6%). In terms of ethnicity, 438 individuals (70.0%) identified as Han Chinese, 150 (24.0%) were Zhuang, and 38 (6.0%) as belonging to other ethnic groups. Regarding place of origin, 400 students (63.9%) hailed from rural areas, while 226 (36.1%) were urban residents. The majority of participants were master\u0026rsquo;s students (93.5%) ,with 71.5% specializing in clinical medicine or public health .\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"662\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 662px;\"\u003e\n \u003cp\u003eTable 1 Demographic characteristics of participants\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eDemographic characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eNumber (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e185(29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e441(70.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eHan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e438(70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eZhuang\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e150(24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eOther ethnic group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e38(6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003ePlace of origin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e226(36.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e400(63.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003ePlace of household registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eGuangxi household registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e406(64.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003enon-Guangxi household registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e220(35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eAnnual household income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003e\u0026lt;50000RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e224(35.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003e50000-100000RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e232(37.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003e100000-200000RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e117(18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003e200000-500000RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e35(5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003e\u0026gt;500000RMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e18(2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eSingle-child\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e164(26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e462(73.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eMajor type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eClinical Medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e265(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003ePublic Health and Preventive Medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e183(29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003ePharmaceutical Sciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e66(10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eBasic Medical Sciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e53(8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eNursing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e19(3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eOther majors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e40(6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eFirst-year graduate student\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e212(33.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eSecond-year graduate student\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e176(28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eThird-year graduate student\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e197(31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eFirst-year doctoral student\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e16(2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eSecond-year doctoral studen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e11(1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eThird-year doctoral studen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e12(1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 434px;\"\u003e\n \u003cp\u003eOther grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e2(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e3.2 Univariate Analysis of Willingness to Work in Guangxi\u003c/p\u003e\n\u003cp\u003eUnivariate analysis identified multiple factors that were significantly associated with medical postgraduates\u0026rsquo; willingness to remain in Guangxi for employment, including gender, ethnicity, place of origin, household registration status, Single-child status,major type, prior educational or internship experiences in first-tier cities (Beijing, Shanghai, Guangzhou, Shenzhen), current academic year, and parental preferences (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSpecific findings are as follows: females participants (59.4%) exhibited a significantly higher willingness to stay than males participants (47.6%) (\u0026chi;\u0026sup2;=7.415, \u003cem\u003eP\u003c/em\u003e=0.006). Zhuang students (84.0%) demonstrated a stronger intent to remain compared with Han students (47.7%) (\u0026chi;\u0026sup2;=64.106, P\u0026lt;0.001). Rural-origin students (62.5%) were more inclined to stay than urban-origin peers (44.2%) (\u0026chi;\u0026sup2;=19.516, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). Students with Guangxi household registration displayed a significantly higher willingness to remain (77.8%) than non-local registrants (15.5%) (\u0026chi;\u0026sup2;=225.221, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). Single-child reported a greater willingness to stay compared with non-only children (56.7% vs. 39.6%) (\u0026chi;\u0026sup2;=14.352, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001).Medical students showed the strongest willingness to remain in Guangxi (61.9%), while students from other disciplines exhibited lower willingness (\u0026chi;\u0026sup2;= 22.610, P \u0026lt; 0.001). Students with prior experiences in first-tier cities showed a lower willingness to remain relative to those without such experiences (37.9% vs. 58.8%) (\u0026chi;\u0026sup2;=13.250, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). Third-year graduate students showed the highest willingness to remain in Guangxi (64.5%) (\u0026chi;\u0026sup2;= 19.148, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.004). In addition, factors including academic performance ranking, English proficiency, and parental education level showed no significant association with the outcome of interest.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"661\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 661px;\"\u003e\n \u003cp\u003eTable 2 Univariate Analysis of Factors Influencing Medical Postgraduates\u0026apos; Willingness to Work in Guangxi (N=626)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 260px;\"\u003e\n \u003cp\u003eDemographic characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003enumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 172px;\"\u003e\n \u003cp\u003eWillingness to Work in Guangxi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cem\u003ec\u003c/em\u003e\u003cem\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eunwilling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003ewilling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e7.415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e185(29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e97(52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e88(47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e441(70.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e179(40.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e262(59.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e64.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eHan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e438(70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e229(52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e209(47.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eZhuang\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e150(24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e24(16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e126(84.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eOther ethnic group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e38(6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e23(60.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e15(39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of origin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e19.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e226(36.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e126(55.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e100(44.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e400(63.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e150(37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e250(62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of household registration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e225.221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eGuangxi household registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e406(64.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e90(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e316(77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eNon-Guangxi household registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e220(35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e186(84.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e34(15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eSingle-child\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e14.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e164(26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e93(56.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e71(43.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e462(73.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e183(39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e279(60.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMajor type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e22.610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eClinical Medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e265(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e101(38.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e164(61.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003ePublic Health and Preventive Medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e183(29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e97(53.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e86(47.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003ePharmaceutical Sciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e66(10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e28(42.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e38(57.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eBasic Medical Sciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e53(8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e29(54.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e24(45.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eNursing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e19(3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e12(63.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e7(36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eOther majors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e40(6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e9(22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e31(77.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e19.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eFirst-year graduate student\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e212(33.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e108(50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e104(49.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eSecond-year graduate student\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e176(28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e80(45.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e96(54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eThird-year graduate student\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e197(31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e70(35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e127(64.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eFirst-year doctoral student\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e16(2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e8(50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e8(50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eSecond-year doctoral studen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e11(1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e8(72.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e3(27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eThird-year doctoral studen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e12(1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e2(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e10(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eAcademic Ranking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.470\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eTop 10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e104(16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e42(40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e62(59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003e10%-50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e387(61.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e169(43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e218(56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eThe latter 50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e135(21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e65(48.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e70(51.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eStudy or internship experience in Beijing, Shanghai, Guangzhou, or Shenzhen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e13.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e87(13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e54(62.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e33(37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e539(86.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e222(41.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e317(58.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eEnglish Proficiency Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e4.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.226\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eDid not pass CET-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e20(3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e7(35.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e13(65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003ePass CET-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e168(26.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e85(50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e83(49.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003epass CET-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e429(68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e180(42.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e249(58.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003ePass TOELF/GRE/IELTS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e9(1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e4(44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e5(55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eFather\u0026apos;s educational attainment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e5.724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eElementary school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e150(24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e61(40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e89(59.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eJunior High School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e205(32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e84(41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e121(59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eHigh School/Vocational School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e131(20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e58(44.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e73(55.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eJunior college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e61(9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e31(50.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e30(49.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eBachelor\u0026apos;s Degree (Correspondence Program)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e66(10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e34(51.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e32(48.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eGraduate students and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e13(2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e8(61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e5(38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eMother\u0026apos;s educational attainment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e5.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e0.406\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eElementary school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e236(37.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e93(39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e143(60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eJunior High School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e195(31.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e87(44.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e108(55.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eHigh School/Vocational School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e97(15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e45(46.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e52(53.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eJunior college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e54(8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e27(50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e27(50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eBachelor\u0026apos;s Degree (Correspondence Program)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e40(6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e22(55.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e18(45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eGraduate students and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e4(0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e2(50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e2(50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParental preference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e326.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eSupport\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e327(52.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e35(10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e292(89.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e198(31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e143(72.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e55(27.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 260px;\"\u003e\n \u003cp\u003eOppose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e101(16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e98(97.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e3(3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e3.3 Binary Logistic Regression Analysis of Influencing Factors\u003c/p\u003e\n\u003cp\u003eBinary logistic regression identified key determinants of medical postgraduates\u0026rsquo; willingness to work in Guangxi (Table 3). Students of urban-origin exhibited a lower odds of being willing compared to rural counterparts (OR=0.483, 95% CI: 0.284-0.820, \u003cem\u003eP\u003c/em\u003e=0.007). In contrast, students with Guangxi household registration displayed a significantly higher odds of such willingness (OR=3.323, 95% CI: 1.791-6.165, P\u0026lt;0.001). Students majoring in Public health and preventive medicine(OR=0.170,95%CI=0.048-0.593,P=0.005)and Nursing(OR=0.126, 95%CI=0.018-0.855, P=0.034) students demonstrated a significantly lower willingness to work in Guangxi compared to those in other majors. Additionally,compared with parental opposition,parental support（OR=126.920,95%CI=33.179-485.507, p \u0026lt; 0.001） or neutrality(OR = 7.576, 95% CI = 2.144-26.772, p = 0.002) toward working in Guangxi was associated with a significant increase in students\u0026rsquo; willingness to work in Guangxi .\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"661\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 661px;\"\u003e\n \u003cp\u003eTable 3 Logistic Regression Analysis of Multiple Factors Influencing Graduate Students\u0026apos; Willingness to Work in Guangxi\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eDemographic characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003eOR(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003ePlace of origin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e400(63.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003ereference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e226(36.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e0.483(0.284-0.820)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003ePlace of household registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eNon-Guangxi household registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e220(35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003ereference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eGuangxi household registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e406(64.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e3.323(1.791-6.165）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003emajor type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eOther majors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e40(6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003ereference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eClinical Medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e265(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e0.428(0.125-1.458)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003ePublic Health and Preventive Medicine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e183(29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e0.170(0.048-0.593)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003ePharmaceutical Sciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e66(10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e0.258(0.063-1.048)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eBasic Medical Sciences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e53(8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e0.451(0.105-1.937)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.284\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eNursing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e19(3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e0.126(0.018-0.855)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eParental preference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eOppose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e101(16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003ereference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eSupport\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e327(52.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e126.920（33.179-485.507）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 269px;\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e198(31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 166px;\"\u003e\n \u003cp\u003e7.576（2.144-26.772）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study examined the factors influencing medical postgraduates\u0026rsquo; local employment intention in Guangxi ,Binary logistic regression analysis revealed that household registration status,place of origin ,specialty type and parental attitudes as key determinants of medical postgraduates\u0026rsquo; willingness to work in Guangxi. Specifically, Guangxi household registration (OR=3.323,\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001),rural origin (compared to urban origin,OR=0.483,\u003cem\u003eP\u003c/em\u003e=0.007),parental support (OR=3.323，\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001)and neutral parental attitudes(OR=7.576,\u003cem\u003eP\u003c/em\u003e=0.002)were positively correlated with the intention to remain in Guangxi.Conversely, majors in Public Health and Preventive Medicine (OR = 0.170, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e= 0.005) and Nursing (OR = 0.126, \u003cem\u003eP\u003c/em\u003e = 0.034) were negatively correlated with this intention.\u003c/p\u003e\n\u003cp\u003eThe significant association between Guangxi household registration and preference for working in Guangxi essentially stems from the combined effects of institutional orientation, social capital, cost of living and policy dividends.The household registration system remains a fundamental institution influencing China\u0026rsquo;s labor allocation\u003csup\u003e[13]\u003c/sup\u003e. In Guangxi ,staffing quotas for grassroots healthcare positions are heavily favour local registrants.Local medical institutions also prefer to hire locally educated candidates with stable household status, who demonstrate higher retention rates. This employment preference perpetuates the longstanding \u0026lsquo;logic of dual labour market segmentation\u0026rsquo; in Chinese cities, where high-quality positions are often tied to local registration\u003csup\u003e[14]\u003c/sup\u003e.Non-local students face intense competition in inter-regional civil service exams and challenges in family In contrast, Students with Guangxi household registration directly benefit from local staffing policies while leveraging familial networks to reduce the adapting costs. Additionally, Guangxi\u0026rsquo;s lower living costs also align with their lifestyle expectations, offering greater career stability.\u003c/p\u003e\n\u003cp\u003eFamily socioeconomic status (SES)\u0026mdash;encompassing economic, education, and cultural capital\u0026mdash;is an ascribed factor influencing occupational mobility\u003csup\u003e[15]\u003c/sup\u003e.Urban students typically come from higher SES families, enabling them to support interregional migration and seek opportunities in developed regions,following a \u0026lsquo;resources-returns\u0026rsquo; logic.This aligns with existing research findings that married female PhD students who are from urban areas and have a high household income are inclined to choosing first-tier city as employment\u003csup\u003e[10]\u003c/sup\u003e.Conversely, rural students exhibit distinct socioeconomic.Their families have limited capacity to support migration, making local employment a risk mitigation strategy\u0026mdash;consistent with studies noting that children from low SES families often prefer local employment\u003csup\u003e[16,17]\u003c/sup\u003e. Simultaneously, rural students\u0026rsquo;\u0026nbsp;employment\u0026nbsp;expectations align more closely with Guangxi\u0026rsquo;s healthcare resource distribution,\u0026nbsp;characterized by\u0026nbsp;significant demand at the county\u0026nbsp;amid concentrated urban competition\u003csup\u003e[18]\u003c/sup\u003e.\u0026nbsp;This dual alignment of resource constraints and employment expectations makes rural students relatively more inclined to seek employment within Guangxi.\u003c/p\u003e\n\u003cp\u003eFrom a disciplinary perspective,students of Public heath and prevention medicine and Nursing exhibit a significantly lower willingness to seek employment in Guangxi than student of other subjects. The underlying cause lies in the mismatch between positions attractiveness in Guangxi and the career expectations of these professionals, aligning with expectancy theory regarding the balance between expected rewards and effort\u003csup\u003e[19]\u003c/sup\u003e.For public health and preventive medicine, challenges centre on an imbalance between compensation and investment. Chinese disease control system suffers from structural issues including inadequate compensation safeguards and low utilization of incentive mechanisms\u003csup\u003e[20]\u003c/sup\u003e. Within Guangxi\u0026rsquo;s context of relatively limited financial investment,the gap between job compensation and career expectations becomes more pronounced, diminishing retention intention. Nursing students face the dual constraints of \u0026lsquo;uneven resource distribution and insufficient development support\u0026rsquo;. High-quality nursing positions in Guangxi are concentrated in few tertiary hospitals,while primary institutions offer low compensation and lack critical retention factors such as autonomy and training opportunities\u0026mdash;factors identified internationally as core drivers for nurse retention\u003csup\u003e[21,22]\u003c/sup\u003e. The job characteristics of these two specialties conflict with Guangxi\u0026rsquo;s medical resource distribution of \u0026ldquo;concentrated in cities and weak at the grassroots level\u0026rdquo;. Compared to eastern coastal cities like Shenzhen, which offer better work-life balance and organizational suppoort, Guangxi\u0026rsquo;s shortcomings in compensation incentives and career paths clarity further reduce willingness to stay\u003csup\u003e[23,24]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eCurrent research indicates that parental support or neutrality significantly was positively correlated with retention intention. This aligns with social support theory,which family support reduces uncertainty in career choices\u003csup\u003e[21]\u003c/sup\u003e.Parental support provides emotional validation and practical assistance (e.g. leveraging local networks for housing and occupational adaptation ).While a neutral stance reduces decision-making resistance through tatic approval. This correlation exhibits regional specificity in Guangxi, potentially reinforced by the traditional \u0026lsquo;family clustering\u0026rsquo; culture among the Zhuang ethnic group,where 84% of Zhuang students demonstrate high retention willingness. Families in east region may prioritise career development over familial bonds, whereas families in Guangxi emphasizes local retention to preserve family ties\u003csup\u003e[25]\u003c/sup\u003e. Combined with Guangxi\u0026rsquo;s practical conditions, such as institutional preference for local graduates and lower living costs, the positive relationship between parental attitudes and retention intention is strengthened.\u003c/p\u003e\n\u003cp\u003eFactors significant in univariate analysis\u0026mdash;gender, ethnicity, single-child status, grade level, and experience in Beijing, Shanghai, Guangzhou, or Shenzhen\u0026mdash;failed to reach statistical significance in binary logistic regression.This occurs because their independent effects were confounded or masked by core variables within the model:ethnicity\u0026apos;s explanatory power was overshadowed by household registration due to high collinearity.The latent influences of gender and single-child status were subsumed under parental attitudes.Grade differences depended on major and job-seeking stage while exhibiting weak idenpendent.Experiences in Beijing, Shanghai, Guangzhou, or Shenzhen were implicitly correlated with non-Guangxi household registration, causing their effects to be masked. The purpose of binary logistic regression was precisely to isolate such core net effects by controlling for confounders, ultimately corroborating that employment intentions in Guangxi are influenced by multiple synergistic core mechanisms.\u003c/p\u003e"},{"header":"5.\tLimitations","content":"\u003cp\u003eThis study has several limitations. First, despite the use of random sampling, Students unwilling to work in Guangxi\u0026mdash;such as those dissatisfied with the local employment conditions or inclined to seek opportunities elsewhere\u0026mdash;may be more likely to refuse participation.This could lead to an overestimation of the reported retention intention rate(55.9%) and potentially inflate the positive effects of factors such as parental attitude and household,while underestimating the negative impact of major type.Consequently,the generalizability of the findings to all Guangxi medical graduates may be limited.Second,the household registration was simply categorized as \u0026ldquo;Guangxi/non-Guangxi\u0026rdquo;, without further stratification by regional economic development.This may mask important variations among non-local students.For instance, those from other undeveloped provinces may have higher retention intentions than those from developed due to closer alignment with Guangxi\u0026rsquo;s economic and professional landscape.A more nuanced classification would allow for deeper insight into how registration status shapes employment decisions.Third,this study focused on exclusively on individual-level factors and did not incorporate the external factors such as job quality,salary levels,or career advancement opportunities within Guangxi\u0026rsquo;s healthcare system. Employment choices arise from the interaction between individual intention intent and external opportunity structures.Even if students have the intention to stay, inadequate job conditions may still lead to a gap between intention and actual behavior,limiting the direct applicability of our findings yo talent retention policy.The above limitations could be improved by redesigning the study in the future.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eIn summary, this study, focusing on postgraduate students at Guangxi Medical University, yield critical insights for talent development and career guidance strategies formulation. The results highlight the necessity for institutional initiatives \u0026nbsp;to design targeted career planning programs that are aligned with disciplinary characteristics and labor market exigencies, particularly for students of urban origin, those with non-Guangxi registrants, and those specializing in public health and preventive medicine and nursing. Furthermore, enhancing communication with postgraduate parents through awareness campaigns and guidance could improve students\u0026rsquo; professional competitiveness and career satisfaction.By addressing these demographic-specific and familial determinants, universities and policymakers can more effectively bolster regional talent retention and optimize the distribution of the healthcare workforce in developing economic regions such as Guangxi.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Institutional Ethics Committee of Guangxi Medical University and the Postgraduate Education Centre of Guangxi Medical University approved this study. The study was conducted in accordance with the Declaration of Helsinki regarding web-based questionnaires, written informed consent was obtained from all participants prior to their inclusion in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This manuscript does not contain any individual person’s data in any form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUniversity Student Employment and Entrepreneurship Research Project of Guangxi Medical University, 2025JC01.\u003c/p\u003e\n\u003cp\u003eInnovation Project of GuangxiGraduate Education, JGY2021058\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQi Meng and Li Ye conceived and designed the study. Jiaxiao Jiang designed the study and drafted the manuscript. Xunan Tao and Fengning Tang were responsible for data collection. Feng Tang and Suyan Zhou performed the data analysis. Liuxing Zhou analyzed and synthesized the results and critically revised the manuscript. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all the students who voluntarily participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRibeiro H V, Oehlers M, Moreno-Monroy A I, et al. Association between population distribution and urban GDP scaling[J]. PLoS One, 2021, 16(1): e0245771.\u003c/li\u003e\n\u003cli\u003eMoghaddam S N M, Cao, H. . Population Distribution and Migration Patterns. In: Artificial Intelligence-Driven Geographies. City Development: Issues and Best Practices. 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Jiaoyu Jiaoxue Luntan 2024, 30: 43\u0026ndash;46.\u003c/li\u003e\n\u003cli\u003eVasile V, Bunduchi E, Stefan D, et al. Are We Facing a Radical Change in the Migration Behavior of Medical Graduates from Less Developed Countries? Demographic Profile vs. Social Push Factors[J]. Int J Environ Res Public Health, 2023, 20(6).\u003c/li\u003e\n\u003cli\u003eFerreira T, Collins A M, Feng O, et al. Career intentions of medical students in the UK: a national, cross-sectional study (AIMS study)[J]. BMJ Open, 2023, 13(9): e075598.\u003c/li\u003e\n\u003cli\u003eTeng Z S, Ser G T Z, Hong W H, et al. Malaysian Medical Students\u0026apos; Career Intention (MMSCI): a cross-sectional study[J]. Hum Resour Health, 2024, 22(1): 59.\u003c/li\u003e\n\u003cli\u003eWang J X, Yang C H, Wang J Z, et al. Factors affecting psychological health and career choice among medical students in eastern and western region of China after COVID-19 pandemic[J]. 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BMC Med Educ, 2020, 20(1): 405.\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":"Guangxi Medical University, Medical Postgraduates, Employment Intention, Influencing factors","lastPublishedDoi":"10.21203/rs.3.rs-9166347/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9166347/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aimed to investigate the factors influencing the local employment intention of medical postgraduates in Guangxi,with a focus on identifying key determinants that affect their decision to work within the region.The finding are intended to provide evidence-based recommendations for enhancing talent retention strategies in underdeveloped ethnic minority areas and to support the development of targeted career guidance and policy interventions in medical education.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA questionnaire survey was conducted among medical postgraduates at Guangxi Medical University from March to April 2024. Chi-square tests were used for univariate analysis of factors related to employment willingness, and binary logistic regression was applied to determine the independent predictors of intention to work in Guangxi.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 670 questionnaires were collected, with 626 valid ones (effective rate 93.4%). Among the valid participants, 44.1% expressed unwillingness to work in Guangxi. Univariate analysis showed that gender, ethnicity, place of origin, household registration status, only-child status, major type, first-tier city experience, academic year, and parental preferences were significantly associated with employment willingness (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Binary logistic regression further revealed that urban origin (OR\u0026thinsp;=\u0026thinsp;0.524, 95%CI:0.285\u0026ndash;0.964, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038), non-Guangxi household registration (reference: Guangxi household registration; OR\u0026thinsp;=\u0026thinsp;2.958, 95%CI:1.507\u0026ndash;5.805, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), majoring in public health and preventive medicine (OR\u0026thinsp;=\u0026thinsp;0.375, 95%CI:0.202\u0026ndash;0.697, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), and parental opposition (reference: parental support; OR\u0026thinsp;=\u0026thinsp;0.008, 95%CI:0.002\u0026ndash;0.034, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were key factors affecting willingness to stay.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe willingness of Guangxi Medical University\u0026rsquo;s medical postgraduates to work in Guangxi is jointly influenced by place of origin, household registration, major type, and parental attitudes. Targeted interventions including tailored guidance for urban-origin and public health majors, policy support for non-local registrants are needed to improve regional medical talent retention.\u003c/p\u003e","manuscriptTitle":"Factors Affecting Medical Postgraduates’ Local Employment Intention in Guangxi: Implications for Talent Retention in Ethnic Minority Underdeveloped Areas in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-18 06:44:00","doi":"10.21203/rs.3.rs-9166347/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"224126438581992393210965516572188822749","date":"2026-05-24T01:20:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-07T16:22:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-04T10:25:52+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-13T12:13:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-11T08:56:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2026-04-11T08:51:41+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":"03def1aa-f4b7-4453-b625-fd60d1516e11","owner":[],"postedDate":"May 18th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"224126438581992393210965516572188822749","date":"2026-05-24T01:20:16+00:00","index":59,"fulltext":""},{"type":"reviewersInvited","content":"30","date":"2026-05-07T16:22:42+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T06:44:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-18 06:44:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9166347","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9166347","identity":"rs-9166347","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}