BACKGROUND: The aim of this study is to explore the influence of GPs\'information, motivation and behavior skills on EM prescribing behavior in urban and suburban districts.
METHODS: A cross-sectional study was conducted from June to November 2022 cross 3 urban districts and 4 suburban districts in Beijing. The structural equation model was used to analyze the factors influencing the essential medicine prescription behavior among general practitioners in urban and suburban districts.
RESULTS: A total of 511 valid questionnaires were collected. There was a statistically significant difference in mean scores for personal motivation and behavioral skills between urban GPs and suburban GPs. For urban GPs, the path analysis revealed that the social motivation had a direct effect on the essential medicine prescribing behavior (β = 0.225, p < 0.05). In contrast, for suburban GPs, both social motivation and personal motivation had a direct effect on the essential medicine prescribing behavior, respectively (β = 0.175, p < 0.05; β = 0.193, p < 0.01).
CONCLUSIONS: Social motivation of urban GPs were positively and significantly associated with essential medicine prescribing behavior. Social motivation and personal motivation of suburban GPs were positively and significantly associated with essential medicine prescribing behavior. Therefore, various corresponding policies and measures should be developed to promote the National Essential Medicines Policy in China.

UNASSIGNED: Previous studies exhibited differences in sensory processing, motor coordination, metacognitive executive functions (EF-MI), and sleep quality among adults with neurodevelopmental disorders (NDD). This study aims to find relationships between those abilities and organization-in-time, focusing on emotional responses after decreased organization abilities.
UNASSIGNED: This is a secondary data analysis of a larger sample from three previous studies conducted in one laboratory. Data were collected from 290 adults; 149 with NDD and 141 sex- and age- (20-50 years) matched controls completed the Adolescent/Adult Sensory Profile, Adult Developmental Coordination Disorder, Adults Behavioral Rating Inventory of Executive Functions, Mini Sleep, and Time Organization and Participation questionnaires. Structural equation model (SEM) analysed relationships and variable prediction.
UNASSIGNED: Significant between-group differences were found for all variables; SEM indicated similar paths in both groups. Sensory processing affected EF-MI and sleep quality and significantly correlated with motor coordination, affecting EF-MI; EF-MI affected organization-in-time. Sleep quality significantly affected organization-in-time, affecting emotional responses.
UNASSIGNED: Sensory, motor, EF, and sleep differences were associated with decreased organization-in-time abilities of adults with NDD, adversely affecting their emotional well-being. Early detection of such differences and targeted interventions may improve daily functioning and life quality and prevent negative emotional implications.
Neurodevelopmental disorders (NDD) emerging early in development affect lifelong well-being, and personal, social, academic, and occupational function.Adults with NDD may experience reduced quality of life due to ineffective time organization and life management.Ineffective time organization and consequence negative emotional responses are tied with deficient sensory processing, motor coordination, metacognitive executive function abilities, and sleep quality.Early diagnosis of such deficiencies following by targeted intervention may enhance daily functioning, reduce emotional challenges, and improve overall life outcomes.

UNASSIGNED: Currently, straw biodegradation and soil improvement in rice-mushroom rotation systems have attracted much attention. However, there is still a lack of studies on the effects of rice-mushroom rotation on yield, soil properties and microbial succession.
UNASSIGNED: In this study, no treatment (CK), green manure return (GM) and rice straw return (RS) were used as controls to fully evaluate the effect of Stropharia rugosoannulata cultivation substrate return (SRS) on soil properties and microorganisms.
UNASSIGNED: The results indicated that rice yield, soil nutrient (organic matter, organic carbon, total nitrogen, available nitrogen and available potassium) and soil enzyme (urease, saccharase, lignin peroxidase and laccase) activities had positive responses to the rice-mushroom rotation. At the interannual level, microbial diversity varied significantly among treatments, with the rice-mushroom rotation significantly increasing the relative alpha diversity index of soil bacteria and enriching beneficial microbial communities such as Rhizobium, Bacillus and Trichoderma for rice growth. Soil nutrients and enzymatic activities were significantly correlated with microbial communities during rice-mushroom rotation. The fungal-bacterial co-occurrence networks were modular, and Latescibacterota, Chloroflexi, Gemmatimonadota and Patescibacteria were closely related to the accumulation of nutrients in the soil. The structural equation model (SEM) showed that fungal diversity responded more to changes in soil nutrients than did bacterial diversity.
UNASSIGNED: Overall, the rice-mushroom rotation model improved soil nutrients and rice yields, enriched beneficial microorganisms and maintained microbial diversity. This study provides new insights into the use of S. rugosoannulata cultivation substrates in the sustainable development of agroecosystems.

UNASSIGNED: To investigate the influencing factors of self-management of diabetic retinopathy (DR) by constructing a structural equation model (SEM) to analyze the relationships among self-management behavior, perceived social support, and trait coping style as well as to determine the influencing path in order to provide a theoretical reference for exploring a multipath health management model that can be used to improve the quality of life of DR patients.
UNASSIGNED: A total of 388 patients with DR were enrolled in this cross-sectional study conducted from January 2020 to January 2023. All subjects completed a general questionnaire and were assessed by the Self-management Scale for Patients with Diabetic Retinopathy, the Perceived Social Support Scale, and the Trait Coping Style Scale. Structural equation modeling was employed to examine the relationship between self-management and its influencing factors. The bootstrap method was used to examine the path relationships among self-management, perceived social support, and trait coping styles in DR patients.
UNASSIGNED: A total of 346 valid questionnaires were collected in this study, with a response rate of 89% (346/388). The average score of self-management of DR patients was 69.50±18.32, and it was significantly positively correlated with perceived social support and positive coping (r=0.624, r=0.578, both P<0.01). The total effect of perceived social support on DR self-management was 1.439, with a direct effect of 1.056 and an indirect effect of 0.384. Positive coping played a mediating role in perceived social support and self-management.
UNASSIGNED: The self-management of DR was at an intermediate level. Perceived social support and trait coping styles were important influencing factors for self-management behavior in DR patients. Therefore, improving perceived social support and trait coping styles can promote the self-management behavior of DR patients, reduce their psychological burden, and improve their compliance and quality of life.

BACKGROUND: The aim of this study was to compare the predictive performance of three statistical models-logistic regression, classification tree, and structural equation model (SEM)-in predicting severe dengue illness.
RESULTS: We adopted modified classification of dengue illness severity based on WHO 1997 guideline. Predictive models were constructed using demographic factors and laboratory indicators on the day of fever occurrence. We developed statistical predictive models using data from two hospital cohorts in Thailand, consisting of 257 Thai children. Different predictive models for each category of severe dengue illness were developed employing logistic regression, classification tree, and SEM. The probability of discrimination of each model for severe output of disease was analyzed with external validation data sets from 55 and 700 patients not used in model development. From external validation using predictors on the day of presentation to the hospital, the area under the receiver operating characteristic curve was between 0.65 and 0.84 for the regression model. It was between 0.73 and 0.85 for SEM models. Classification tree models showed good results of sensitivity, ranging from 0.95 to 0.99. However, they showed poor specificity ranging from 0.10 to 0.44.
CONCLUSIONS: Our study showed that SEM is comparable to logistic regression or classification tree, which was widely used for more severe form of dengue prediction.

The supply chain for prefabricated buildings (PB) currently grapples with pressing challenges. In order to ensure the safe and stable development of the prefabricated building supply chains (PBSC), this study aims to identify the key factors and internal mechanisms affecting the PBSC, and propose a supply chain resilience enhancement mechanism, so as to promote the sustainable development of the PB industry. The study combined a literature review and survey data to identify key resilience factors in PBSC. A Structural Equation Model (SEM) was used to explore the relationships between these factors. System dynamics were applied to create a simulation model, assessing the resilience impact level and conducting sensitivity analysis. The results show that the transportation and procurement processes are the most significant factors influencing supply chain resilience. The external environmental factors wielded a more pronounced impact on the overall evaluation of supply chain resilience than the delivery and use processes, but delivery and use processes are more sensitive. The study uses the Pressure-State-Response (PSR) model to suggest strategies for enhancing supply chain resilience. This study contributes to more sustainable and efficient construction practices by offering an innovative theoretical framework to analyze the factors influencing PBSC resilience and proposing enhancement strategies.

The purpose of this study was to assess the significant factors that impact pregnant women\'s willingness to use smart fetal heart-rate monitoring devices. We propose a research model that integrates technological factors (perceived compatibility and perceived credibility) and personal factors (health anxiety, personal physiological conditions, health consciousness, and health beliefs). The subjects of this study were Chinese women who were pregnant or had previously given birth. Data were collected and analyzed from 397 paper-and-pencil and electronic questionnaires. Our structural equation model indicated that perceived usefulness (β = 0.490, t = 7.591, p < 0.001), perceived ease of use (β = 0.352, t = 5.631, p < 0.001), health anxiety (β = 0.095, t = 2.664, p = 0.008), personal physiological conditions (β = 0.075, t = 2.142, p = 0.032), and health consciousness (β = 0.078, t = 2.110, p = 0.035) were the determinants of the intention to use smart fetal heart-rate monitoring devices, with perceived usefulness having the highest degree of influence. Furthermore, we discovered that the levels of perceived compatibility and perceived credibility did not have direct correlations with the intention to use these devices, but they did significantly influence the model. Perceived compatibility (β = 0.345, t = 6.601, p < 0.001) and perceived credibility (β = 0.519, t = 9.958, p < 0.001) significantly influences perceived ease of use. Perceived credibility (β = 0.421, t = 7.802, p < 0.001) significantly influences perceived usefulness. Based on these results, suggestions for future research are put forward.

Despite decades of messaging, most Americans still consume excess fats and sugars, but inadequate fiber, potassium, and calcium. Nutrient-rich foods (NRFs) have a high density of favorable nutrients related to calories. Choosing NRFs could lower risk of nutrition-related chronic diseases and aid in their control. We hypothesized that having greater knowledge of NRFs, the presence of a nutrition-related chronic disease or risk factor, and positive Health Belief Model (HBM) views would be predictive of the likelihood of eating NRFs. Through a national online survey panel, 976 adults aged 18-80 completed demographic, health, NRF knowledge, attitudes, and HBM construct questions. Participants were 77% White, 52% women, and 55% had a nutrition-related disease or risk factor. Multivariable HBM scales were generated by theory, principal components, and reliability analysis. NRF knowledge was significantly higher for women, Whites, households without children, and persons without a nutrition-related disease (all p ≤ 0.015). \'Likelihood of eating NRFs\' was significantly higher for persons with a nutrition-related disease, Whites, married participants, main food shoppers, and households with children (all p ≤ 0.022). Regressing demographic and HBM constructs on the \'likelihood of eating NRFs\' resulted in R2 of 0.435. Nutrition-related disease and HBM constructs of self-efficacy, perceived benefits, and cues to action were predictive of the likelihood of eating NRFs, but higher NRF knowledge was negatively associated.

The transition to a low-carbon economy emphasizes the importance of green and low-carbon consumption; yet, there is often a discrepancy between consumers\' intentions and their actual behavior regarding organic foods. This study aims to identify strategies to bridge this gap. The research model of organic food consumption intention and behavior is constructed, and a structural equation model is used to test the research hypotheses based on a valid sample of 480 residents of Guangdong Province through an online questionnaire survey. Further, the intention‒behavior gap is defined and its determinants are investigated through multiclass logistic regression. Finally, we categorize and forecast the alignment between consumption intentions and behaviors using machine learning algorithms. The results reveal that attitudes, social interactions, and cognitive information play crucial roles in aligning intentions with behaviors. By enhancing social information exchange or improving cognitive understanding, consumers can reduce their intention‒behavior discrepancy. This research offers valuable policy recommendations for fostering green consumption among residents from various perspectives.

With the increasing threat of global warming, the cultivation of wine grapes in high-altitude with cool-temperature climates has become a viable option. However, the precise mechanism of environmental factors regulating grape quality remains unclear. Therefore, principal component analysis (PCA) was utilized to evaluate the quality of wine grape (Cabernet Sauvignon) in six high-altitude wine regions (1987, 2076, 2181, 2300, 2430, 2540 m). Structural equation modeling (SEM) was applied for the first time to identify the environmental contribution to grape quality. The wine grape quality existed spatial variation in basic physical attributes (BP), basic chemical compositions (BC), phenolic compounds (PC) and individual phenols. The PCA models (variance > 85 %) well separate wine grapes from the six altitudes into three groups according to scores. The score of grapes at 2300 m was significantly high (3.83), and the grapes of 2540 m showed a significantly low score (1.46). Subsequently, the malic acid, total tannin, total phenol, titratable acid, total anthocyanin, and skin thickness were the main differing indexes. SEM model characterized the relational network of differing indexes and microclimatic factors, which showed that temperature and extreme air temperature had a greater direct effect on differing indexes than light, with great contributions from soil temperature (0.98**), day-night temperature difference (0.825*), and day air temperature (0.789**). Our findings provided a theoretical basis for grape cultivation management in high-altitude regions and demonstrated that the SEM model is a useful tool for exploring the relationship between climate and fruit quality.