Should China Expand Its Medical Education Scale? Evidence From Comparative Research

Purpose This study compares doctor staffing level and the scale of medical education in China with those of other countries and proposes policy recommendations for future adjustments to the scale of China's medical education. Design/Approach/Methods This study employs a literature review and descriptive analysis. Findings China had 1.98 medical doctors per 1,000 people in 2018, ranking 85th out of the 193 member-states of the World Health Organization (WHO). In 2017, China had 1.99 practicing doctors per 1,000 people, only ranking above Turkey (1.88) in Organisation for Economic Co-operation and Development (OECD) countries. China had only 10.28 medical graduates per 100,000 people—placing in the bottom third of OECD countries. China's provision of 1.4 medical schools per 10 million people was also significantly lower than the global average (3.9). However, the average number of students enrolled in medical schools (509) in China was significantly higher than the global average (160). Originality/Value Although the scale of admission in undergraduate medical education must be expanded in China, this needs to be achieved while controlling the average number of medical students per school and reducing enrollment in low-quality medical schools. Furthermore, it is necessary to establish new medical schools while improving the operating level of existing ones.

Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects.

The Wells-Riley model invokes human physiological and engineering parameters to successfully treat airborne transmission of infectious diseases. Applications of this model would have high potentiality on evaluating policy actions and interventions intended to improve public safety efforts on preventing the spread of COVID-19 in an enclosed space. Here, we constructed the interaction relationships among basic reproduction number (R0) - exposure time - indoor population number by using the Wells-Riley model to provide a robust means to assist in planning containment efforts. We quantified SARS-CoV-2 changes in a case study of two Wuhan (Fangcang and Renmin) hospitals. We conducted similar approach to develop control measures in various hospital functional units by taking all accountable factors. We showed that inhalation rates of individuals proved crucial for influencing the transmissibility of SARS-CoV-2, followed by air supply rate and exposure time. We suggest a minimum air change per hour (ACH) of 7 h-1 would be at least appropriate with current room volume requirements in healthcare buildings when indoor population number is < 10 and exposure time is < 1 h with one infector and low activity levels being considered. However, higher ACH (> 16 h-1) with optimal arranged-exposure time/people and high-efficiency air filters would be suggested if more infectors or higher activity levels are presented. Our models lay out a practical metric for evaluating the efficacy of control measures on COVID-19 infection in built environments. Our case studies further indicate that the Wells-Riley model provides a predictive and mechanistic basis for empirical COVID-19 impact reduction planning and gives a framework to treat highly transmissible but mechanically heterogeneous airborne SARS-CoV-2.

Assessing regional emissions of vehicle-based tire wear particle from macro-to micro/nano-scales with pandemic lockdowns and electromobility scenarios implications.

Despite increasing the public awareness of ubiquity of microplastics (MPs) in air, the issue on particular source of tire wear particles (TWPs) emission into atmosphere and their exposure-associated human health has not received the attention it deserves. Here we linked vehicle kilometers traveled (VKT) estimates covering demography, socio-environmental, and transportation features and emission factors to predict regional emission patterns of TWP-derived atmospheric MPs. A data-driven probabilistic approach was developed to consider variability across the datasets and uncertainty of model parameters in terms of country-level and vehicle-type emissions. We showed that country-specific VKT from billion to trillion vehicle-kilometer resulted in 103-105 metric tons of airborne TWP-derived atmospheric MPs annually in the period 2015-2019, with the highest emissions from passenger cars and heavy-duty vehicles. On average, we found that airborne TWP emissions from passenger cars by country had substantial decreased (up to ∼33%) during COVID-19 lockdowns in 2020 and pronounced increased (by a factor ∼1.9) from vehicle electrification by the next three decades. We conclude that the stunning mass of airborne TWP is a predominant source of atmospheric MP. We underscore the necessity of TWP emissions control among the United States, China, and India. Our findings can be of great use to environmental transportation planners for devising vehicle/tire-oriented decision support tools. Our data offer information to enhance TWP-exposure estimates, to examine long-term exposure trends, and subsequently to improve health risk assessment during pandemic outbreak and future electrification.

Twin peaks of in-hospital mortality among patients with STEMI across five phases of COVID-19 outbreak in China: a nation-wide study.

Lockdown and re-opening may become cyclical due to the recurrent waves of the COVID-19 epidemic. Few studies have examined temporal trends and determinants of in-hospital mortality among patients with ST-segment elevation myocardial infarction (STEMI), a life-threatening condition that requires emergency medical care. Using nation-wide data before, during and after the Wuhan lockdown, we aimed to depict temporal patterns and major determinants of STEMI in-hospital mortality in China across five time periods of the COVID-19 epidemic. We analyzed the data of 283,661 STEMI patients who were admitted to 4,487 chest-pain-centers across China, from January 1, 2019 to May 31, 2020. Compared with the period before the lockdown, STEMI in-hospital mortality increased by 25% (OR 1.25, 95%CI 1.16-1.34) during Early Lockdown, by 12% (OR 1.12, 95%CI 1.03-1.22) during Later Lockdown, by 35% (OR 1.35, 95%CI 1.21-1.50) during Early Lift, and returned to pre-COVID risk (OR 1.04, 95%CI 0.95-1.14) during Later Lift. For each time-period, we observed a clear mortality gradient by timing and types of revascularization procedure. In conclusion, the COVID-19 epidemic had a significant adverse impact on STEMI in-hospital mortality, with bimodal peaks during early lockdown and early lift periods and clear mortality gradients by timing and types of revascularization procedure, independent of the time periods.

Professional Identity of 0.24 Million Medical Students in China Before and During the COVID-19 Pandemic: Three Waves of National Cross-Sectional Studies.

Background: Professional identity (PI) influences the doctor's thoughts and behaviors. Thus, PI formation (PIF) plays an important role in medical students' education. Major changes to the learning environment could impact PIF, but the influence of the novel coronavirus disease 2019 (COVID-19) pandemic on medical students' PI had confusing conclusions in previous studies. We aimed to compare PI of medical students by using the data from three waves of national cross-sectional surveys conducted in China in 2019, 2020, and 2021, and to examine factors that influence PIF. Method: We used data from the China Medical Student Survey (CMSS) which has conducted three national cross-sectional surveys. From 2019 to 2021, CMCC retrieved data on PI from a nationally representative sample of medical students from 33, 121, and 123 colleges, respectively. We analyzed the data using Chi-square test, analysis of variance, and multivariable logistic regression according to sociodemographic characteristics, pre-university experience, college characteristics, and college experience. Results: A total of 244,040 medical students in China participated in the surveys. The overall score of PI increased from 3.80 in 2019 to 3.85 in 2021. Medical students with family medical background, high intrinsic and extrinsic motivation of major selection, teachers' positive role model, and high personal comprehensive quality ranking were more likely to have higher PI (all p < 0.05). The more attention students paid to the COVID-19 pandemic, the higher PI they would have (aOR 1.93, 95% CI 1.67-2.24 for more attention; aOR 2.31, 95% CI 2.00-2.68 for the most attention). However, parents' participation on the front lines of COVID-19 pandemic negatively influenced the PI of medical students (aOR 0.72, 95% CI 0.57-0.93). Conclusions: PI of medical students increased during the COVID-19 pandemic. The impact of the pandemic on PI was complex. To improve the PI of medical students, the education sector, health sector and the society need to make concerted efforts.

Still want to be a doctor? Medical student dropout in the era of COVID-19.

This research examines the intention of undergraduate medical students to withdraw from the medical profession and pursue a career in a different field upon graduation during COVID-19. We leverage the first and most comprehensive nationwide survey for medical education in China, which covered 98,668 enrolled undergraduate students from 90 out of 181 Chinese medical schools in 2020. We focus on these students' self-reported intention to leave the healthcare industry (the "dropout intention") before and after the outbreak of the epidemic. We also designed a randomized experiment to test whether and to what extent medical students dropout intention responded to an information nudge that highlighted the prosociality of health professionals in the fight against the virus. Results from a difference-in-differences model and a student fixed effect model suggest that after the onset of COVID-19, the proportion of Chinese undergraduate medical students with a dropout intention declined from 13.7% to 6.8%. Furthermore, the nudge information reduced the intent-to-drop-out probability by 0.8 additional percentage points for students in their early college years. There was large heterogeneity underneath the treatment effect. Specifically, we find that prior dropout intention and exposures to COVID-19-related information tended to mitigate the nudge effects. Data on students' actual dropout outcomes support our findings.

Twelve tips for teaching medical students online under COVID-19.

Universities worldwide are pausing in an attempt to contain COVID-19's spread. In February 2019, universities in China took the lead, cancelling all in-person classes and switching to virtual classrooms, with a wave of other institutes globally following suit. The shift to online platform poses serious challenges to medical education so that understanding best practices shared by pilot institutes may help medical educators improve teaching. Provide 12 tips to highlight strategies intended to help on-site medical classes moving completely online under the pandemic. We collected 'best practices' reports from 40 medical schools in China that were submitted to the National Centre for Health Professions Education Development. Experts' review-to-summary cycle was used to finalize the best practices in teaching medical students online that can benefit peer institutions most, under the unprecedented circumstances of the COVID-19 outbreak. The 12 tips presented offer-specific strategies to optimize teaching medical students online under COVID-19, specifically highlighting the tech-based pedagogy, counselling, motivation, and ethics, as well as the assessment and modification. Learning experiences shared by pilot medical schools and customized properly are instructive to ensure a successful transition to e-learning.

Students' initial perspectives on online learning experience in China during the COVID-19 outbreak: expanding online education for future doctors on a national scale.

BACKGROUND: During the early stage of COVID-19 outbreak in China, most medical undergraduate programs have to eventually embrace the maneuver of transferring to nearly 100% online-learning as a new routine for different curricula. And there is a lack of empirical evidence of effective medical education curriculum that has been completely implemented in an online format. This study summarizes medical students' perspectives regarding online-learning experience during the COVID-19 outbreak and presents reflection on medical education. METHODS: From February 21st to March 14th, 2020, the authors conducted survey of a nationally representative sample of undergraduate medical students from 90 medical schools in China. Participant demographics and responses were tabulated, and independent sample t-tests as well as multiple logistic regression models were used to assess the associations of demographic characteristics, prior online learning experience, and orientation with students' perspectives on the online learning experience. RESULTS: Among 118,030 medical students participated in the survey (response rate 52.4%), 99,559 provided valid data for the analysis. The sample is fairly nationally representative. 65.7% (65,389/99,559) supported great orientation and 62.1% (61,818/99,559) reported that they were satisfied with the ongoing online-learning experience. The most common problem students would encounter was the network congestion (76,277/99,559; 76.6%). Demographics, learning phases, and academic performance were associated with online-learning engagement and perceptions. Formal orientation and prior PU (perceived usefulness of online learning) were significantly positively associated with the satisfaction and evaluation of the online learning experience (p <  0.001). CONCLUSIONS: Data from this national survey indicates a relatively positive role of online learning as a formal teaching/learning approach in medical education. Considerations should be made regarding such application in aspects of students' different learning phases. We suggest that further policy interventions should be taken from technological, organizational, environmental, as well as individual aspects, to help improve the outcome of online learning for future doctors.

Immune Response, Viral Shedding Time, and Clinical Characterization in COVID-19 Patients With Gastrointestinal Symptoms.

Background and Aims: Gastrointestinal (GI) symptoms are frequently observed in coronavirus disease (COVID-19) symptoms. Previous studies have mainly focused on epidemiology and characteristics in patients with GI symptoms, little is known about the roles of the immune response in susceptibility to and severity of infection. Here, we analyzed COVID-19 cases to determine immune response and clinical characteristics in COVID-19 patients with GI symptoms. Methods: Based on the presence of GI symptoms, 79 patients in Xuzhou were divided into GI and non-GI groups. A retrospective study investigating the clinical characteristics, selected laboratory abnormalities, immune response, treatment, and clinical outcome was performed to compare patients with or without GI symptoms. Results: Approximately 25% of patients reported at least one GI symptom. Our results showed significantly higher rates of fatigue, increased LDH, increased CK, higher percentage increase neutrophil-to-lymphocyte ratio (NLR), lymphopenia, and bilateral pneumonia in patients with GI symptoms. No significant changes in serum amylase (SAA), immunoglobulin (Ig) G, IgM, C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), viral shedding time, liver injury, and kidney injury between the two groups were observed. The clinical type on admission of patients with GI symptoms reported significantly higher rates of critical disease type (20 vs. 3.3%; p = 0.033). However, the survival rate did not differ between the two groups. Conclusions: Increase in total lymphocytes and NLR as well as the elevation of CRP, SAA, PCT, IL-6, CK, and LDH were closely associated with COVID-19 with GI symptoms, implying reliable indicators COVID-19 patients with GI symptoms were more likely to develop into a severe disease.

A composite risk model predicts disease progression in early stages of COVID-19: A propensity score-matched cohort study.

BACKGROUND: Recently, studies on COVID-19 have focused on the epidemiology of the disease and clinical characteristics of patients, as well as on the risk factors associated with mortality during hospitalization in critical COVID-19 cases. However, few research has been performed on the prediction of disease progression in particular group of patients in the early stages of COVID-19. METHODS: The study included 338 patients with COVID-19 treated at two hospitals in Wuhan, China, from December 2019 to March 2020. Predictors of the progression of COVID-19 from mild to severe stages were selected by the logistic regression analysis. RESULTS: COVID-19 progression to severe and critical stages was confirmed in 78 (23.1%) patients. The average value of the neutrophil-to-lymphocyte ratio (NLR) was higher in patients in the disease progression group than in the improvement group. Multivariable logistic regression analysis revealed that elevated NLR, LDH and IL-10 were independent predictors of disease progression. The optimal cut-off value of NLR was 3.75. The values of the area under the curve, reflecting the accuracy of predicting COVID-19 progression by NLR was 0.739 (95%CI: 0.605-0.804). The risk model based on NLR, LDH and IL-10 had the highest area under the ROC curve. CONCLUSIONS: The performed analysis demonstrates that high concentrations of NLR, LDH and IL-10 were independent risk factors for predicting disease progression in patients at the early stage of COVID-19. The risk model combined with NLR, LDH and IL-10 improved the accuracy of the prediction of disease progression in patients in the early stages of COVID-19.

Association between medical students' prior experiences and perceptions of formal online education developed in response to COVID-19: a cross-sectional study in China.

OBJECTIVES: (1) Understanding the characteristics of online learning experiences of Chinese undergraduate medical students; (2) Investigating students' perceptions of ongoing online education developed in response to COVID-19 and (3) Exploring how prior online learning experiences are associated with students' perceptions. DESIGN: Students' familiarity with online learning modes and corresponding perceived usefulness (PU) according to their previous experiences were investigated using an online survey. The survey also collected data on students' perceptions through their evaluation of and satisfaction with current online learning. SETTING: In response to the educational challenges created by COVID-19, medical schools in China have adopted formal online courses for students. PARTICIPANTS: The questionnaire was sent to 225 329 students, of whom 52.38% (118 080/225 329) replied, with valid data available for 44.18% (99 559/225 329). METHODS: Pearson correlations and t-tests were used to examine the relationship between familiarity and PU. Multiple linear regression and logistic regression analyses were used to determine the impact of prior learning experiences and its interactions with gender, area, learning phase and academic performance on students' perceptions. RESULTS: Students' PU had a significant positive correlation with their familiarity with online learning modes (p<0.01). Students' evaluation of and satisfaction with their current online education were positively associated with their familiarity (ß=0.46, 95% CI 0.45 to 0.48, p<0.01; OR 1.14, 95% CI 1.13 to 1.14, p<0.01) with and PU (ß=3.11, 95% CI 2.92 to 3.30, p<0.01; OR 2.55, 95% CI 2.37 to 2.75, p<0.01) of online learning. Moreover, the higher the students' learning phases, the lower the associations between PU and students' evaluation of and satisfaction with ongoing online education. CONCLUSIONS: Medical students in China have experiences with various online learning modes. Prior learning experiences are positively associated with students' evaluation of and satisfaction with current online education. Higher learning phases, in which clinical practices are crucial, and high academic performance led to lower evaluation and satisfaction scores.