Objective: To conduct a scoping review on the types, construction methods and predictive performance of health literacy prediction models based on machine learning methods, so as to provide the reference for the improvement and application of such models. Methods: Publications on health literacy prediction models conducted using machine learning methods were retrieved from CNKI, Wanfang Data, VIP, PubMed and Web of Science from inception to May 1, 2024. The quality of literature was assessed using the Prediction Model Risk of Bias ASsessment Tool. Basic characteristics, modeling methods, data sources, missing value handling, predictors and predictive performance were reviewed. Results: A total of 524 publications were retrieved, and 22 publications between 2007 and 2024 were finally enrolled. Totally 48 health literacy prediction models were involved, and 25 had a high risk of bias (52.08%), with major issues focusing on missing value handling, predictor selection and model evaluation methods. Modeling methods included regression models, tree-based machine learning methods, support vector machines and neural network models. Predictors primarily encompassed factors at four aspects: individual, interpersonal, organizational and society/policy aspects, with age, educational level, economic status, health status and internet use appearing frequently. Internal validation was conducted in 14 publications, and external validation was conducted in 4 publications. Forty-two models reported the areas under the receiver operating characteristic curve, which ranged from 0.52 to 0.983, indicating good discrimination. Conclusion Health literacy prediction models based on machine learning methods perform well, but have deficiencies in risk of bias, data processing and validation.

Objective: To analyze the correlation between the levels of vitamin A, vitamin D, vitamin E with body fat mass percentage(FMP) as well as lifestyle factors among primary school students, so as to provide references for exploring the vitamin nutritional status of primary school students and its potential influencing factors. Methods: From September 1 to October 30, 2021, a cluster sampling method was used to select 750 thirdgrade students from eight primary schools in Luohu District, Shenzhen. Their body composition was measured, and blood samples were collected to detect the serum levels of vitamin A, vitamin D, and vitamin E using a mass spectrometer. Dietary and exercise habits were collected through questionnaires. Mann-Whitney U test and Kruskal-Wallis H rank sum test were used for inter group comparisons, spearman correlation was used for correlation analysis,and Logistic regression model was used to analyze the association between lifestyle and vitamin content. Results: The overall level of vitamin A in school aged children was 0.4 (0.4, 0.5) mg/L, with a deficiency rate of 0 and a marginal deficiency rate of 5.1%; the level of vitamin D was 26.0 (22.0, 30.0) ng/mL, with a deficiency rate of 0.4% and an insufficiency rate of 12.7%; the content of vitamin E was 11.8 (10.1, 13.5) mg/L, with an insufficiency rate of 0.8%. Spearman correlation analysis showed that vitamin A was positively correlated with FMP in the total population, boys, girls, and normal weight population ( r =0.18, 0.18, 0.20, 0.10), and vitamin D was positively correlated with FMP in the total population and obese population ( r =0.08,0.16)(all P <0.05). Logistic regression analysis showed that marginal deficiency of vitamin A was associated with consumption of animal, snack, and dairy/egg/bean foods ( OR =0.45, 0.55, 0.59); whether vitamin D was deficient was influenced by gender ( OR =2.65) and exercise ( OR = 1.96 ) (all P <0.05). Conclusion Vitamin A, vitamin D and vitamin E levels are associated with body fat percentage, with significant variations in vitamin status among individuals of different body types, necessitating targeted supplementation.

Purpose: This study aimed to explore the application of Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) combined with MV-Flow (Samsung Medison Co., Ltd.) to diagnose ovarian-adnexal masses. Methods: A total of 112 ovarian-adnexal masses (81 benign and 31 malignant) from 105 consecutive patients were analyzed. The O-RADS US and vascular index from MV-Flow (VIMV) were measured and compared with the reference standard. O-RADS US and MV-Flow were tested for consistency. Results: Receiver operating characteristic curves were drawn for O-RADS US, MV-Flow, and their combination. The combined methods had the largest area under the curve (0.955), followed by O-RADS US (0.929) and MV-Flow (0.923). A mass was considered malignant when the O-RADS US classification was 5 and VIMV was ≥7.15. With this definition, MV-Flow had the highest sensitivity (87.10%), with consistent findings for the combined diagnostic methods and O-RADS US (83.87%). The specificity of the combined diagnostic methods (93.83%) was higher than that of MV-Flow (91.36%). O-RADS US had the lowest specificity (90.12%). The combined diagnostic methods had the highest coincidence rate (91.07%), and MV-Flow (90.18%) had a significantly higher coincidence rate than O-RADS US (88.39%). Both O-RADS US and MV-Flow showed good consistency among different physicians (former kappa, 0.974; latter intraclass correlation coefficient [ICC], 0.986). MV-Flow had a high consistency for the same physician (ICC, 1). Conclusion O-RADS US and MV-Flow exhibited good diagnostic efficacy, and their combined diagnostic efficacy was higher than that of each individually. O-RADS US and MV-Flow can improve the diagnosis of benign and malignant ovarian-adnexal masses.

Objective:To explore the impact of the hospital health literacy environment on patients′ postoperative pain self-management behaviors, aiming to provide insights for hospitals to implement the Comprehensive Pain Management Pilot Work Program in hospitals and to promote self-health management among patients with other diseases or symptoms. Methods:From November to December 2023, a convenience sampling method was used to select postoperative patients from three grade A tertiary general hospitals in Zhejiang Province for an on-site questionnaire survey. The Chinese version of brief health literacy screen (BHLS), short-form health literacy environment scale (SF-HLES) and postoperative pain self-management behavior questionnaire (PPSMB) were used as survey tools to investigate the health literacy level of patients, the health literacy environment of the hospital, and the postoperative pain management behaviors of patients. Two-way ANOVA was used to compare the impact of different dimensions of the hospital health literacy environment on postoperative pain management behaviors among patients with different levels of health literacy. Multiple linear regression analysis was used to explore the relationship between the hospital health literacy environment, individual health literacy, and patients′ postoperative pain self-management behaviors, and to discuss the impact of individual health literacy on patients′ postoperative pain self-management behaviors under different hospital health literacy environments.Results:341 valid questionnaires were collected. The average score of the hospitals′ SF-HLES was (73.62±19.54) points. The average score of the patients′ BHLS was (9.65±2.88) points. The average score of the patients′ PPSMB was (25.99±6.35) points. Two-way ANOVA results showed that the interaction between individual health literacy and the clinical dimension ( F=5.463, P=0.020) and structural dimension ( F=6.470, P=0.011) of the hospital health literacy environment had a statistically significant impact on patients′ postoperative pain self-management behaviors, while the interaction with the interpersonal dimension ( F=0, P=0.984) had no statistically significant impact on pain self-management behaviors. Simple effect analysis indicated that only in the high health literacy environment of the clinical and structural dimensions did the difference in pain self-management behaviors between patients with good health literacy and those with limited health literacy had statistical significance ( P<0.001). Multiple linear regression analysis results showed that for each 1-point increase in the patients′ BHLS score, their PPSMB score increased by 3.74 points ( β1=0.832, P<0.001); for each 1-point increase in the hospital′s SF-HLES score, the patients′ PPSMB score could increase by 0.198 points ( β2=0.610, P<0.001). In a low health literacy environment, individual health literacy did not affect pain self-management behaviors ( P>0.05); however, in a high health literacy environment, for each 1-point increase in the patients′ BHLS score, their PPSMB score correspondingly increased by 4.037 points ( β4=0.317, P<0.001). Conclusions:The positive impact of individual health literacy on pain self-management is contingent upon a high-quality hospital health literacy environment. This suggests that optimizing the hospital health literacy environment is a necessary precondition for implementing the relevant content of the Comprehensive Pain Management Pilot Work Program and can provide a reference for promote self-health management among patients with pain and other diseases or symptoms.

Purpose: This study aimed to explore the application of Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) combined with MV-Flow (Samsung Medison Co., Ltd.) to diagnose ovarian-adnexal masses. Methods: A total of 112 ovarian-adnexal masses (81 benign and 31 malignant) from 105 consecutive patients were analyzed. The O-RADS US and vascular index from MV-Flow (VIMV) were measured and compared with the reference standard. O-RADS US and MV-Flow were tested for consistency. Results: Receiver operating characteristic curves were drawn for O-RADS US, MV-Flow, and their combination. The combined methods had the largest area under the curve (0.955), followed by O-RADS US (0.929) and MV-Flow (0.923). A mass was considered malignant when the O-RADS US classification was 5 and VIMV was ≥7.15. With this definition, MV-Flow had the highest sensitivity (87.10%), with consistent findings for the combined diagnostic methods and O-RADS US (83.87%). The specificity of the combined diagnostic methods (93.83%) was higher than that of MV-Flow (91.36%). O-RADS US had the lowest specificity (90.12%). The combined diagnostic methods had the highest coincidence rate (91.07%), and MV-Flow (90.18%) had a significantly higher coincidence rate than O-RADS US (88.39%). Both O-RADS US and MV-Flow showed good consistency among different physicians (former kappa, 0.974; latter intraclass correlation coefficient [ICC], 0.986). MV-Flow had a high consistency for the same physician (ICC, 1). Conclusion O-RADS US and MV-Flow exhibited good diagnostic efficacy, and their combined diagnostic efficacy was higher than that of each individually. O-RADS US and MV-Flow can improve the diagnosis of benign and malignant ovarian-adnexal masses.

Purpose: This study aimed to explore the application of Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) combined with MV-Flow (Samsung Medison Co., Ltd.) to diagnose ovarian-adnexal masses. Methods: A total of 112 ovarian-adnexal masses (81 benign and 31 malignant) from 105 consecutive patients were analyzed. The O-RADS US and vascular index from MV-Flow (VIMV) were measured and compared with the reference standard. O-RADS US and MV-Flow were tested for consistency. Results: Receiver operating characteristic curves were drawn for O-RADS US, MV-Flow, and their combination. The combined methods had the largest area under the curve (0.955), followed by O-RADS US (0.929) and MV-Flow (0.923). A mass was considered malignant when the O-RADS US classification was 5 and VIMV was ≥7.15. With this definition, MV-Flow had the highest sensitivity (87.10%), with consistent findings for the combined diagnostic methods and O-RADS US (83.87%). The specificity of the combined diagnostic methods (93.83%) was higher than that of MV-Flow (91.36%). O-RADS US had the lowest specificity (90.12%). The combined diagnostic methods had the highest coincidence rate (91.07%), and MV-Flow (90.18%) had a significantly higher coincidence rate than O-RADS US (88.39%). Both O-RADS US and MV-Flow showed good consistency among different physicians (former kappa, 0.974; latter intraclass correlation coefficient [ICC], 0.986). MV-Flow had a high consistency for the same physician (ICC, 1). Conclusion O-RADS US and MV-Flow exhibited good diagnostic efficacy, and their combined diagnostic efficacy was higher than that of each individually. O-RADS US and MV-Flow can improve the diagnosis of benign and malignant ovarian-adnexal masses.

Abstract Health literate schools (HeLit-Schools) play a significant role in fostering students health literacy. The paper elucidates the background and conceptual connotations of HeLit-Schools, and analyzes how HeLit-Schools effectively integrate and enhance the health literacy of schools in three aspects: philosophy and core drivers, strategy and method implementation, as well as evaluation mechanisms and standard setting. Furthermore, the paper explores the implications of foreign HeLit-Schools research and practice for China under the context of "Healthy China" construction, as well as the key strategies for Chinese schools in the implementation of HeLit-Schools, aiming to provide a new perspective and theoretical support for Chinese schools to practice the "Healthy China initiative" and strengthen school construction from the perspective of health literacy.

Parkinson's disease (PD) is a chronic neurodegenerative disease. At present, levodopa and other drugs are mainly used for dopamine supplementation therapy. However, the absorption of levodopa in the gastrointestinal tract is unstable and its half-life is short, and long-term use of levodopa will lead to the end-of-dose deterioration, dyskinesia, the "ON-OFF" phenomenon and other symptoms. Therefore, new preparations need to be developed to improve drug efficacy, reduce side effects or improve compliance of patients. Based on the above clinical needs, this review briefly introduced the preparation modification strategies for the treatment of PD through case analysis, in order to provide references for the research and development of related preparations.

OBJECTIVE To establish the quality standards of medicinal materials in light of related methods in the general principles of part four of Chinese Pharmacopoeia(2020 Edition), and to conduct systematic research on the Tibetan medicine "Yajima"(Chrysosplenium axillare). METHODS The powder characteristics of medicinal materials were described by microscopic identification method. Silica gel GF254 thin-layer plate was employed to establish a TLC identification method with 5-O-demethylapulein and oxyayanin A as reference substances. Loss on drying, total ash, acid-insoluble ash and ethanol-soluble extractives of 10 batches of Chrysosplenium axillare were determined according to the general principles of part four of Chinese Pharmacopoeia(2020 Edition). HPLC was used to establish the characteristic chromatogram of Chrysosplenium axillare, and the content determination method was established with chrysosplenoside I(CI) and chrysosplenoside A(CA) as the quality control index components of Chrysosplenium axillare. RESULTS The water content, total ash, acid-insoluble ash, ethanol-soluble extractive and the content of CI and CA of all samples varied in the ranges of 9.17%−12.52%, 14.11%−16.74%, 1.50%−4.72%, 32.77%−40.30%, 0.30%−0.99% and 0.28%−0.88%, respectively. CONCLUSION The identification and content determination methods of Yajima(Chrysosplenium axillare) are established for the first time. The methods are easy to operate and exclusive, which is of great significance to accurately evaluate the internal quality of medicinal materials and ensure the quality of drug used.

Abstract As dietary issues of children and adolescents become increasingly complex, the assessment of food literacy (FL) is increasingly importance. FL involves a comprehensive cognition and practical ability concerning food among children, playing a key role in fostering healthy eating habits and improving health levels. The article explores the definition and connotations of FL, and introduces eight FL assessment tools in terms of theoretical foundations, dimensions, assessment methods, and their reliability and validity. Moreover, it provides a comparative analysis of these tools by examining their dimensional design, evaluation indicators, strengths, and weaknesses, as well as their applicable subjects and scenarios, aiming to offer references for implementing relevant policies and developing more comprehensive and effective FL assessment tools.