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Background Competency development is the core of residency training in general practice, as well as the key to training qualified general practitioners. Summative assessment can evaluate overall training outcome and the attainment of general practitioner competencies. Summative assessment in general practice is still in developing in China, and its relevance to competencies is relatively weak. Objective To develop competency based summative assessment indicator framework of residency training in general practice, and to provide reference for improving the summative assessment system in China. Methods From 2023-04-25 to 30, 32 experts from 10 provinces, including Beijing, Shanghai, Hebei, Jiangsu, Zhejiang, Liaoning, Inner Mongolia Autonomous Region, Hainan, Ningxia Hui Autonomous Region and Sichuan Province were invited to participate in Delphi Expert Survey. The indicator framework of summative assessment was established through literature review and Delphi expert survey. The weight of indicators was determined by multiplicative model. Results In both the first and second rounds of expert survey, 32 questionnaires were issued and 32 were recovered, which were all valid. The positive coefficient was 100.0%, the authority coefficient was > 0.8, the importance coordination coefficient of indicators at all levels respectively was 0.382, 0.284, 0.265, and the feasibility coordination coefficient was 0.415, 0.359, 0.332. The final summative assessment indicator framework consisted of 6 first-tier indicators, 24 second-tier indicators and 50 third-tier indicators. The first-tier indicators include application of clinical professional knowledge and skills, the ability to take care of the family, the ability to provide basic public health services, the ability to communicate, cooperate and coordinate, humanistic ability and professionalism, clinical teaching and scientific research ability, and the weights were 0.505, 0.061, 0.109, 0.134, 0.125 and 0.066, respectively. Conclusion This study preliminarily explored and constructed competency based summative assessment indicator framework of residency training in general practice, which provides reference for further research on the contents of summative assessment and on the improvement of summative assessment system in China. The framework is important for improving the quality of residency training and competencies of general practitioners.

Background The prevalence rate of type 2 diabetes is increasing in China. General practitioners play an important role in the prevention and treatment of type 2 diabetes and its complications. Chronic kidney disease (CKD) is a common co-existing disease in patients with diabetes. However, at present, there is little research evidence on type 2 diabetes combined with CKD in primary care in China. Objective To investigate the obstructive factors in the monitoring and management of type 2 diabetes mellitus with CKD from the perspective of general practitioners. Methods From May to July 2022, a one-to-half structured interview was conducted with snowball sampling among general practitioners in an urban area of Beijing, and the interview outline was formulated based on the theoretical domains framework (TDF). NVivo 11 software was used to encode and classify the interview contents. Subject frame analysis method was used to sort out and analyze the data, and extract the theme. Results 13 general practitioners were interviewed in this study, and the years of working in general practice ranged from 8 to 22 years. The study identified barriers related to six domains in TDF, namely knowledge/skills, beliefs about outcomes, motivation and goals, medical background, resources and norms of conduct. After refining again, the themes were lack of systematic knowledge and skills related to CKD, imperfect incentive mechanism of primary medical staff, lack of smooth referral process between primary medical institutions and higher hospitals, poor self-management ability of patients and other obstacles. Conclusion There are many factors preventing general practitioners from monitoring and managing patients with type 2 diabetes complicated with CKD in the community. It is necessary to strengthen the knowledge and skills training of general practitioners with diabetes mellitus complicated with CKD, improve the ability of general practitioners to monitor and manage CKD, improve the incentive mechanism of primary medical institutions and establish an effective referral process with superior hospitals, strengthen the health education of patients, improve the self-management ability of patients, and enhance the prevention and treatment ability of primary medical institutions with type 2 diabetes complicated with CKD.

Chronic diseases have become a major problem affecting the health of residents in China and globally. The improvement of the quality of general practice is of great significance to improving the management of chronic diseases in primary care. It is an important way to achieve continuous quality improvement by evaluating the quality of chronic disease management in general practice to identify the current problems. According to the review of current status of domestic and international research, some countries have established relatively complete quality evaluation systems for the management of chronic diseases in general practice. Compared with foreign countries, the practice of quality evaluation and improvement of chronic disease management in general practice in China is still in the exploratory stage, although some progress has been made, there are also some challenges: firstly, the quality evaluation of chronic disease management is mainly focused on hypertension and diabetes, insufficient attention has been paid to the clinical quality of other chronic diseases, and the degree of refinement of clinical indicators still needs to be further strengthened compared with foreign countries. Secondly, there are limitations in evaluating the practice process of chronic disease management in general practice, most of the researches were mainly limited to the performance indicators within the framework of services specification. It is possible to refine the evidence-based quality evaluation and quality improvement systems and specify monitoring indicators. Thirdly, there is still a big gap in the construction of information system in general practice, the "fragmentation" and lack of information have seriously hindered the effective evaluation of the quality of chronic disease management, the information system construction should be improved as soon as possible. Fourthly, quality evaluation results focus on feedback within the administrative system and health service providers lack awareness of their own service quality, more equitable and effective evaluation and feedback mechanisms should be explored to promote continuous improvement in the quality of chronic disease management.

Tropical cyclone (TC) size is an important parameter for estimating TC risks, such as precipitation distribution, gale-force wind damage, and storm surge. This paper uses the TC size dataset compiled by the Shanghai Typhoon Institute of China Meteorological Administration (STI/CMA) to investigate the interannual, monthly variation in TC size, and the relationships between TC size and intensity in the WNP basin from 1981 to 2009. The results show that the annual mean TC size oscillated within the range of 175–210 km from 1981 to 2002, then decreased following 2003. For the monthly average TC size, there are two peaks in September and October. The TC size, overall, becomes larger with increasing intensity; the samples with an unusually large size are mainly concentrated near a 40 m s−1 intensity. After the TC intensity exceeds 40 m s−1, the number of unusually large size samples gradually decreases. About 60% of the TCs reach their maximum size after reaching the peak intensity, and the average lag time is 8.3 h. [ABSTRACT FROM AUTHOR]

A tropical cyclone (TC) is a meteorological disaster that occurs over tropical or subtropical oceans. Automatic TC identification from a satellite image is essential to the subsequent automatic intelligent determination of TC positioning and intensity. Few recent studies have examined the automatic detection of TCs from satellite images. In this paper, wavelet (W) transformation, efficient (E) channel attention mechanism and YOLOX (Y) are combined to construct a deep learning model for TC detection, referred to as WEY-TCNet. WEY-TCNet automatically detects TCs from infrared satellite images. To improve the detection accuracy, a discrete wavelet transform is first used to decompose the infrared satellite image, after which the horizontal high-frequency components, including the TC rainband structure and inner core area, are extracted and fused with the original image. This step enhances the TC structure and brightness temperature gradient characterization. The fused image is then used as the input to WEY-TCNet. The ECANet channel attention mechanism was added to the original YOLOX-S network structure to focus on the key features of TC, such as structure and brightness temperature while suppressing invalid features and noise. This study constructed a satellite image dataset based on the infrared images of the Chinese Fengyun2D geostationary satellite. The dataset contains infrared satellite images of TCs in various life cycle stages, from generation to extinction. Our experiments showed that the WEY-TCNet model proposed in this paper achieves 91.49% detection mAP on the TC dataset, compared with the 86.69% detection mAP of the original YOLOX-S model, significantly improving it. [ABSTRACT FROM AUTHOR]