Models of mild cognitive deficits in risk assessment in early psychosis.

BACKGROUND: Mild cognitive deficits (MCD) emerge before the first episode of psychosis (FEP) and persist in the clinical high-risk (CHR) stage. This study aims to refine risk prediction by developing MCD models optimized for specific early psychosis stages and target populations. METHODS: A comprehensive neuropsychological battery assessed 1059 individuals with FEP, 794 CHR, and 774 matched healthy controls (HCs). CHR subjects, followed up for 2 years, were categorized into converters (CHR-C) and non-converters (CHR-NC). The MATRICS Consensus Cognitive Battery standardized neurocognitive tests were employed. RESULTS: Both the CHR and FEP groups exhibited significantly poorer performance compared to the HC group across all neurocognitive tests (all p < 0.001). The CHR-C group demonstrated poorer performance compared to the CHR-NC group on three sub-tests: visuospatial memory (p < 0.001), mazes (p = 0.005), and symbol coding (p = 0.023) tests. Upon adjusting for sex and age, the performance of the MCD model was excellent in differentiating FEP from HC, as evidenced by an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.895 (p < 0.001). However, when applied in the CHR group for predicting CHR-C (AUC = 0.581, p = 0.008), the performance was not satisfactory. To optimize the efficiency of psychotic risk assessment, three distinct MCD models were developed to distinguish FEP from HC, predict CHR-C from CHR-NC, and identify CHR from HC, achieving accuracies of 89.3%, 65.6%, and 80.2%, respectively. CONCLUSIONS: The MCD exhibits variations in domains, patterns, and weights across different stages of early psychosis and diverse target populations. Emphasizing precise risk assessment, our findings highlight the importance of tailored MCD models for different stages and risk levels.

Driving factors of spatial-temporal difference in China's transportation sector carbon productivity: an empirical analysis based on Geodetector method.

Carbon productivity is the core index to measure the performance of carbon emission reduction. Exploring the driving factors of the spatial-temporal differences in China's transportation sector, carbon productivity (TSCP) is conducive to the low-carbon sustainable development of the transportation sector. Based on the calculation of TSCP in 30 provinces in China from 2000 to 2019, we use time series, spatial visualization, and Dagum Gini coefficient to reveal the characteristics of spatial-temporal evolution and regional differences of TSCP, and uses Geodetector to identify the driving factors that affecting the spatial-temporal differences of TSCP. The results are as follows: (1) from 2000 to 2019, China's TSCP shows a U-shaped change trend of "decline to rise," and shows a spatial pattern of "high in the eastern and central, low in the western". (2) There are obvious regional differences in China's TSCP. The differences within each region show the trend of "eastern > central > western," while the differences between regions show the trend of "central-western > eastern-western > eastern-central," and the differences between regions are the main reason for the overall differences. (3) The spatial-temporal differences in China's TSCP are affected by many factors, such as social economy and self-endowment. Overall, energy intensity, foreign trade, technological innovation level, energy structure, and industrial structure are the dominant factors. Additionally, the interaction between the driving factors enhances the impact on the spatial-temporal differences of TSCP. Finally, according to the analysis results, some policy suggestions are put forward to improve TSCP.

Role of household waste, governance quality, and greener energy for public health: Evidence from developed economies.

In the current times, the global economies and international organizations declared that pollution is one of the prominent causes of declined human health. Still, most literature is biased toward economic sustainability and ignores such vital issues. The current study tends to identify the factors affecting public health in the Group of Seven economies except for Italy (G6). Specifically, this study aims to investigate the influence of household waste (HHW), bureaucratic quality (BQ), democratic accountability (DA), urbanization growth (URP), GDP per capita, and renewable energy use (EPR) on public health, throughout 1996-2020. This study uses advanced panel data approaches and finds the heterogeneity of slope coefficients, the dependence of cross-sections, and the persistence of cointegration between the variables. The asymmetric distribution of data leads to employing the novel method of moment quantile regression. The estimated results reveal that URP, GDPPC, and EPR significantly increase domestic general government health expenditures, improving public health. However, HHW and BQ adversely affect public health by reducing health expenditures. The robustness of the results is tested via utilizing the panel quantile regression. Based on the empirical findings, this study suggests policies regarding the improvement in public health expenditure, R&D investment, spending in renewable energy sector, and strengthening of the institutional quality.

Independent or Influential? Spatial-Temporal Features of Coordination Level between Urbanization Quality and Urbanization Scale in China and Its Driving Mechanism.

The quality and scale of urbanization development are the two main aspects in China's current urbanization process. By measuring and analyzing the level differences in these two aspects, the healthy development of China's urbanization and urban-rural integration will be promoted. Based on the quality of urbanization and the scale of urbanization, this paper constructs an evaluation index system for urbanization coordination level. On this basis, this paper analyzes the spatial correlation, spatial difference, and spatial pattern evolution characteristics of urbanization coordination level in 286 sample cities nationwide from 2005 to 2015. Then, by introducing the spatial econometric regression model, this paper discusses the driving mechanism of the spatial and temporal evolution of urbanization coordination level. The results show that: (1) The level of coordination between urbanization quality and urbanization scale shows a strong spatial correlation in space, which is consistent with the actual development status; (2) the level of urbanization coordination shows a trend of evolution from northeast to southwest in the evolution of spatial pattern, but the extent of change is small; and (3) the spatial and temporal pattern of urbanization coordination level is affected by different driving forces, of which internal source is the primary impact factor, followed by administrative level and investment level. In addition, the level of urbanization coordination has a positive spillover effect on the level of urbanization coordination in adjacent areas.

Using 'WeChat' online social networking in a real-world needs analysis of family members of youths at clinical high risk of psychosis.

OBJECTIVE: The argument surrounding the safety and effectiveness of interventions for the population of individuals at a clinical high risk of developing psychosis has been ongoing for the past 30 years. However, few studies have assessed the needs of this special young population, who are struggling with the recent onset of psychotic symptoms. METHOD: The sample consisted of 171 family members of 108 clinical high-risk individuals included from the ShangHai at Risk for Psychosis research programme. A 'WeChat' group was established to provide mutual support. There were 22,007 valid messages sent within the group between 1 April 2015 and 27 June 2016. Chat records were subsequently analysed to determine the needs of families during intervention at the early stages of psychosis. RESULTS: Families of clinical high-risk individuals were highly involved in the entire medical process, and the major concerns of the families of clinical high-risk individuals focused on both functional recovery and medication. The themes of 'take medication', 'go to school' and 'study in school' were often discussed within the group. CONCLUSION: A family-focused intervention targeting functional recovery and real-time professional explanations of medication would meet the major needs of families of Chinese clinical high-risk individuals.