Equity and trends in general practitioners' allocation in China: based on ten years of data from 2012 to 2021.

BACKGROUND: General practitioners (GP) are the gatekeepers of residents' health, 2021 is the 10th year of the establishment of the GP system in China. This study aims to assess the equity and trends of GP allocation in China from 2012 to 2021, summarize the efforts and progress of GPs in China during the decade, predict the development trend of GPs in mainland China in the next 5 years to provide a reference for regional health planning and rational allocation of GPs in China. METHODS: Data from 2012 to 2021 on GPs in 22 provinces, 5 autonomous regions, and 4 municipalities directly under the central government in mainland China (excluding Hong Kong, Macao, and Taiwan) are collected by us. Gini coefficient, Lorenz curve and health resource agglomeration degree (HRAD) were used to analyze the equity of the allocation of GPs in China from different dimensions, a Grey prediction model was used to forecast the number of GPs in 2022-2026. RESULTS: The number of GPs in mainland China increased from 109 794 to 434 868 from 2012 to 2021, with 3.08 GPs per 10 000 people in 2021. The Gini coefficient of GPs allocation by population in China decreased from 0.312 to 0.147 from 2012 to 2021, while the Gini coefficient of geographic dimension remained between 0.700 and 0.750. Compared with the degree of curvature of the Lorenz curve in the geographic dimension, the degree of curvature of the population and economic dimension were smaller. In 2021, the HRAD in the Eastern region was 4.618, the Central region was 1.493, with different degrees of imbalance among regions, the HRAD/PAD (population agglomeration degree) in the Eastern, Central and Western regions were 1.196, 0.880 and 0.821, respectively. GPs in the Eastern region is still concentrated, while the Central and Western regions were at a similar level, GPs were more scarce. The GM (1,1) model predicts that the number of GPs in mainland China will reach about 720 000 in 2026, the number of GPs per 10 000 people will reach 4.9. CONCLUSION: After a decade of development, the number of GPs in China has increased significantly. It has reached the goal of the GP system when it was first established. However, the equity of the geographical dimension, both in terms of Gini coefficient and HRAD, has great differences between different regions. The average Gini coefficient at the geographic dimension is 0.723. The average HRAD index was 4.969 in the East and 0.293 in the West. The Western region has the problem of insufficient GP allocation in both population and geographical dimension. In the future, the number of GPs in China will continue to grow rapidly with the support of policies. The "2030" goal, proposed in 2018, is expected to be achieved by 2026. Due to certain factors (such as COVID-19), the actual situation may be different from the predicted results.

A study of primary health care service efficiency and its spatial correlation in China.

BACKGROUND: China's primary health care system has undergone major changes since the new round of medical reform in 2009, but the current status of primary health care institution service efficiency is still unsatisfactory. The purpose of this study is to compare and evaluate the China's primary health care institution service efficiency and provide a reference for improving the efficiency and promoting the development of primary health care institution. METHODS: Based on panel data of 31 provinces (municipalities directly under the central government and autonomous regions) in mainland China from 2011 to 2020, using the super efficiency slack-based measure-data envelopment analysis model, to analyze the data from a static perspective, and the changes in the efficiency of primary health care services were analyzed from a dynamic perspective by using the Malmquist index method. Spatial autocorrelation analysis method was used to verify the spatial correlation of primary health care service efficiency among various regions. RESULTS: The number of Primary health care institutions increased from 918,000 in 2011 to 970,000 in 2020. The average primary health care institution service efficiency in the northeastern region including Jilin (0.324), Heilongjiang (0.460), Liaoning (0.453) and northern regions such as Shaanxi (0.344) and Neimenggu (0.403) was at a low level, while the eastern coastal regions such as Guangdong (1.116), Zhejiang (1.211), Shanghai (1.402) have higher average service efficiency levels. The global Moran's I showed the existence of spatial autocorrelation, and the local Moran's I index suggested that the problem of uneven regional development was prominent, showing a contiguous regional distribution pattern. Among them, H-H (high-efficiency regions) were mainly concentrated in Jiangsu, Anhui and Shanghai, and L-L regions (low-efficiency regions) were mostly in northern and northeastern China. CONCLUSION: The service efficiency of primary health care institution in China showed a rising trend in general, but the overall average efficiency was still at a low level, and there were significant geographical differences, which showed a spatial distribution of "high in the east and low in the west, high in the south and low in the north". The northwestern region, after receiving relevant support, has seen a rapid development of primary health care, and its efficiency was steadily improving and gradually reaching a high level. The average primary health care institution service efficiency in the northeastern region including the northern region of China was at a low level, while the average efficiency in the eastern coastal region and some economically developed regions was high, which also verifies the dependence and high symbiosis of primary health care institution service efficiency on regional economy.

Sensorimotor knowledge from task-irrelevant feedback contributes to motor learning.

Exposure to task-irrelevant feedback leads to perceptual learning, but its effect on motor learning has been understudied. Here, we asked human participants to reach a visual target with a hand-controlled cursor while observing another cursor moving independently in a different direction. Although the task-irrelevant feedback did not change the main task's performance, it elicited robust savings in subsequent adaptation to classical visuomotor rotation perturbation. We demonstrated that the saving effect resulted from a faster formation of strategic learning through a series of experiments, not from gains in the implicit learning process. Furthermore, the saving effect was robust against drastic changes in stimulus features (i.e., rotation size or direction) or task types (i.e., for motor adaptation and skill learning). However, the effect was absent when the task-irrelevant feedback did not carry the visuomotor relationship embedded in visuomotor rotation. Thus, though previous research on perceptual learning has related task-irrelevant feedback to changes in early sensory processes, our findings support its role in acquiring abstract sensorimotor knowledge during motor learning. Motor learning studies have traditionally focused on task-relevant feedback, but our study extends the scope of feedback processes and sheds new light on the dichotomy of explicit and implicit learning in motor adaptation and motor structure learning.NEW & NOTEWORTHY When the motor system faces perturbations, such as fatigue or new environmental changes, it adapts to these changes by voluntarily selecting new action plans or implicitly fine-tuning the control. We show that the action selection part can be enhanced without practice or explicit instruction. We further demonstrate that this enhancement is probably linked to the acquisition of abstract knowledge about the to-be-adapted novel visual feedback. Our findings draw an interesting parallel between motor and perceptual learning by showing that top-down information affects both types of procedural learning.

Eliminating Direction Specificity in Visuomotor Learning.

The generalization of learning offers a unique window for investigating the nature of motor learning. Error-based motor learning reportedly cannot generalize to distant directions because the aftereffects are direction specific. This direction specificity is often regarded as evidence that motor adaptation is model-based learning, and is constrained by neuronal tuning characteristics in the primary motor cortices and the cerebellum. However, recent evidence indicates that motor adaptation also involves model-free learning and explicit strategy learning. Using rotation paradigms, here we demonstrate that savings (faster relearning), which is closely related to model-free learning and explicit strategy learning, is also direction specific. However, this new direction specificity can be abolished when the participants receive exposure to the generalization directions via an irrelevant visuomotor gain-learning task. Control evidence indicates that this exposure effect is weakened when direction error signals are absent during gain learning. Therefore, the direction specificity in visuomotor learning is not solely related to model-based learning; it may also result from the impeded expression of model-free learning and explicit strategy learning with untrained directions. Our findings provide new insights into the mechanisms underlying motor learning, and may have important implications for practical applications such as motor rehabilitation. SIGNIFICANCE STATEMENT: Motor learning is more useful if it generalizes to untrained scenarios when needed, especially for sports training and motor rehabilitation. However, as a form of motor learning, motor adaptation is typically direction specific. Here we first show that savings with motor adaptation, an index for model-free learning and explicit strategy learning in motor learning, is also direction specific. However, the participants' additional exposure to untrained directions via an irrelevant gain-learning task can enable the complete generalization of learning. Our findings challenge existing models of motor generalization and may have important implications for practical applications.

Spatial-Temporal Change Trend Analysis of Second-Hand House Price in Hefei Based on Spatial Network.

Spatial Markov chain can effectively explore the spatial evolution trend of housing price under the influence of lag factor. This paper uses spatial autocorrelation and spatial Markov to study 353 second-hand houses in Hefei. The results show that (1) the housing price of Hefei urban area presents a situation of "two points and one side," the high housing price is concentrated in the south and southwest of the urban area, and the price level gradually weakens from south to north, and the housing development shows a north-south differentiation. (2) There is a significant spatial autocorrelation between second-hand housing prices in Hefei. The "high-high" residential price clusters are mainly distributed in Shushan District and Binhu New Area, while the "low-low" residential price clusters are mostly in Yaohai district and its surrounding areas. The number of "low-high" agglomeration and "high-low" agglomeration is small, and the degree of change is not big. (3) Under the influence of different neighborhood environments, the housing prices in urban Area of Hefei show club convergence overall. At the same time, under the short-term influence of the policy, the housing prices of low level and middle and low level are promoted in the same neighborhood environment, while the housing prices of high level and middle and high level are negatively affected.