To explore the dilemmas faced by primary healthcare institutions in China in the practice of cardiovascular metabolic disease management and to propose systematic directions for optimization.

A qualitative research approach was adopted.Semi-structured in-depth interviews were conducted with 13 frontline healthcare professionals involved in chronic disease management across nine primary healthcare institutions in four cities representing eastern,central,and western China.Thematic analysis was used to code the interview data and extract key themes.

Current cardiovascular metabolic disease management at the primary level faced seven major challenges:1)low patient adherence,frequent loss to follow-up,and inadequate management of high-risk populations and complications;2)insufficient human resources and excessive workload for medical staff;3)drug supply significantly affected by policies such as volume-based procurement,alongside a shortage of specialized diagnostic equipment;4)poor referral coordination between primary and higher-level institutions,with barriers to information sharing;5)inadequate multidisciplinary collaboration mechanisms and significant regional disparities in the composition of family doctor teams;6)low community participation in health education and limited coverage of early screening programs;and 7)fragmented information systems characterized by overlapping functions and insufficient stability.Additionally,the study summarized specific recommendations from respondents regarding workforce expansion,investment in prevention,expert support,and innovation in management models.

Chronic disease management in primary healthcare in China is undergoing a critical transition from "establishing presence" to "achieving excellence". To enhance quality and efficiency,systematic improvements are recommended in areas such as optimizing human resource allocation and incentive mechanisms, promoting information system integration and the application of artificial intelligence technologies,implementing targeted financial investment and resource allocation policies.

To verify the effects of basic family nurse diet therapy theory and astragalus-enriched family nurse diet therapy theory on blood glucose and blood pressure control in patients with type 2 diabetes mellitus complicated with hypertension,and to compare their improvement on lipid metabolism,oxidative stress and inflammatory indicators.

Seventy patients with type 2 diabetes mellitus complicated with hypertension treated in a hospital in Shanxi province from July 2025 to January 2026 were randomly divided into control group and intervention group,with 35 cases in each group.The control group received basic family nurse diet therapy theory without astragalus,and the intervention group received astragalus-enriched family nurse diet therapy theory.The intervention lasted for 6 weeks.Blood glucose,blood pressure,metabolism,oxidative stress and inflammatory indicators were compared between the two groups.

After 6 weeks of intervention,fasting plasma glucose(FPG),diastolic blood pressure(DBP),triglyceride(TG),low-density lipoprotein cholesterol(LDL-C),malondialdehyde(MDA),superoxide dismutase(SOD),high-sensitivity C-reactive protein(hs-CRP),interleukin-6(IL-6),homocysteine(Hcy) and uric acid(UA) were improved in both groups compared with baseline(P<0.05).Compared with the control group,glycated hemoglobin(HbA1c),FPG,fasting insulin(FINS),systolic blood pressure(SBP),DBP,total cholesterol(TC),TG,MDA,SOD,hs-CRP,IL-6,tumor necrosis factor-α(TNF-α) and Hcy in the intervention group were significantly different(P<0.05).

Family nurse diet therapy theory can improve blood glucose and blood pressure control in patients with type 2 diabetes mellitus complicated with hypertension.Combined with astragalus intervention,it can further reduce blood glucose,blood pressure and blood lipid levels, alleviate inflammatory response and oxidative stress injury more effectively.

To identify joint trajectories of pain and depressive symptoms in older adults,to explore the dynamic relationship between them,and to identify common influencing factors,so as to provide a basis for developing intervention strategies.

Based on data from the China Health and Retirement Longitudinal Study(CHARLS) from 2011 to 2020,a total of 2 772 older adults were included.A group-based trajectory modeling(GBTM) dual-trajectory approach was used to analyze the joint developmental trajectories of pain and depression.Logistic regression was used to identify common influencing factors.

Two types of pain trajectories were identified: the few sites-stable group and the multiple sites-increasing group.Three types of depression trajectories were identified:the low level-stable group,the medium level-increasing group,and the high level-increasing group.Dual-trajectory analysis showed that compared with the few sites-stable group,older adults in the multiple sites-increasing group had a higher probability of experiencing the medium level-increasing depression(53.3%) and the high level-increasing depression(89.8%).Compared with the low level-stable group,older adults in the medium level-increasing depression group and the high level-increasing depression group had a higher probability of experiencing the multiple sites-increasing pain(59.8% and 29.5%,respectively).Age,gender,educational level,place of residence,nighttime sleep duration,self-rated health,number of chronic diseases,and activities of daily living were common influencing factors for both pain and depression trajectories(all P<0.05).

Pain and depression trajectories in older adults show a high degree of correlation.Attention should be given to the physical and mental health of older adults aged 60 years,females,those living in rural areas,those with poor self-rated health,low education level,a high number of chronic diseases,poor self-care ability,and insufficient sleep duration.Interventions should be developed based on the joint trajectories and common influencing factors of pain and depression.

To explore the mechanism through which role clarity influences the intent to stay among medical nursing assistants,and to examine the mediating role of professional identity and the moderating effect of decent work perception.

A convenience sampling method was used to select 473 medical nursing assistants from eight pilot medical institutions of "accompanied-free care" services in Guangdong province between August and October 2025.Data were collected using a general information questionnaire,the Role Clarity Scale,the Professional Identity Assessment Scale,the Decent Work Perception Scale,and the Intent to Stay Scale.Correlation analysis,mediation analysis,and moderated mediation analysis were conducted using SPSS 27.0.

The median intent to stay score among medical nursing assistants was 13.00(12.00,16.00).Age,education level,daily working hours,and employment relationship were significant factors influencing intent to stay(P<0.05).Role clarity,professional identity,and decent work perception were all positively correlated with intent to stay(P<0.01).Professional identity partially mediated the relationship between role clarity and intent to stay,with an indirect effect value of 0.084(accounting for 39.25% of the total effect).Decent work perception negatively moderated the path from role clarity to professional identity(interaction effect=-0.047,P<0.001),such that the marginal contribution of role clarity to professional identity was stronger under low decent work perception.

Role clarity not only directly and positively affects medical nursing assistants' intent to stay but also indirectly enhances their intent to stay through professional identity.Decent work perception serves as a moderator: under low decent work conditions,the protective effect of role clarity on professional identity becomes more pronounced.

To investigate the current status and influencing factors of digital health technology anxiety in elderly stroke patients,and to provide a basis for developing intervention strategies.

From January to July 2025,a convenience sampling method was used to select 291 hospitalized elderly stroke patients from the neurology and neurosurgery departments of a tertiary hospital in Yangzhou city.Surveys were conducted using a general information questionnaire,the Technology Anxiety Scale,the Elderly Digital Health Literacy Assessment Scale,the Lubben Social Network Scale,the Self-Perception of Aging Scale,and the Active Aging Scale.A random forest model and linear regression analysis were employed to rank and identify the influencing factors of digital health technology anxiety.

The total scores for digital health technology anxiety,elderly digital health literacy,social isolation,self-perceived aging, and active aging were 38.66±9.75,37.31±11.85,19.51±6.11,51.86±11.28,and 104.85±16.95,respectively.According to the random forest ranking and linear regression selection,the influencing factors of digital health technology anxiety in elderly stroke patients, in order of importance,were self-perceived aging,active aging,social isolation,and internet use frequency.

The level of digital health technology anxiety in elderly stroke patients is moderate.Medical staff can implement targeted interventions based on the identified influencing factors to reduce their anxiety.

To develop a father-participatory,diversified parent-child psychomotor training model and evaluate its effectiveness.

A total of 198 newborns born at a tertiary maternal and child health care hospital in Gansu Province from January to June 2024 were enrolled.They were randomly divided into an intervention group(n=99) and a control group(n=99).The control group received routine psychomotor training after delivery, while the intervention group was managed using the father-participatory diversified parent-child psychomotor training model.Infant growth and development,father involvement in infant rearing,and maternal postpartum depression were assessed at 6 months after intervention.

No significant differences were found between the two groups in birth weight,length,or head circumference(P>0.05).At 6 months of age,the intervention group showed significantly higher physical growth indicators, intellectual development index,and psychomotor development index compared to the control group(P<0.05). Fathers in the intervention group had higher paternal involvement score with infants(P<0.05),and mothers in the intervention group had lower postpartum depression scores(P<0.05).

The diversified parent-child psychomotor training model promotes infant growth and development,increases father involvement in infant rearing,and reduces maternal postpartum depression.

To establish a scientific and standardized evaluation indicator system for new media health science popularization capacity suitable for community health service centers.This system aims to provide quantitative tools and decision-making references for grassroots health institutions to systematically assess and enhance the effectiveness of health communication.It also supports fully leveraging the core role of nursing teams in health education.

Based on the "5W" communication theory framework,an initial indicator pool was built through literature analysis.Nineteen experts from multiple fields were selected to participate in two rounds of Delphi method consultation.This process completed the screening of indicators and the optimization of the system.The Analytic Hierarchy Process(AHP) was used to construct judgment matrices.The hierarchical weights of indicators at all levels were determined and consistency tests were conducted.

A three-level evaluation indicator system was finally formed.It includes five dimensions,eleven elements,and thirty-five specific indicators.The weights of the dimensions from highest to lowest were: communication effect (0.324 6),audience analysis(0.215 5),content quality(0.205 8),basic conditions(0.128 0),and platform construction(0.126 0).The consistency ratio(CR) of all judgment matrices passed the consistency test.

The constructed indicator system possesses both theoretical rationality and practical operability.It innovatively integrates the communication model with grassroots health service scenarios and nursing health education work.This integration provides evidence-based decision-making support for improving the grassroots "Internet+Health Promotion" working mechanism.It assists grassroots medical and health institutions in achieving precise and sustainable new media health science popularization capacity building.

To develop and validate a high-precision,interpretable sarcopenia risk prediction model for peritoneal dialysis patients.

A retrospective study included 441 peritoneal dialysis patients from two tertiary hospitals in Anhui province from January 2023 to June 2025 as the training set,and 198 patients as the external validation set.Core predictors were screened using univariate analysis,Logistic regression,and LASSO regression.Eight machine learning algorithms were used to build models.Internal validation employed Bootstrap sampling,and external validation used an independent dataset.The optimal model was interpreted using the Shapley additive explanations(SHAP).

Six core predictors were identified:sex,dialysis vintage,and diabetes,prealbumin、interleukin-6、25-hydroxyvitamin D.The support vector machine(SVM) model showed the best performance,with an area under the receiver operating characteristic curve(AUC) of 0.958 in the internal test set and 0.968 in the external validation set.Accuracy,sensitivity,and specificity all exceeded 0.9.SHAP analysis revealed the contribution of each predictor and their nonlinear relationships.

The developed machine learning model demonstrates high accuracy,generalizability,and interpretability.It can provide intelligent decision support for early identification and precise intervention of sarcopenia in peritoneal dialysis patients,showing potential for clinical translation.

To explore the potential categories of longitudinal trajectories of patient activation in individuals with chronic heart failure and to analyze their influencing factors.

Patients with chronic heart failure admitted to our hospital from January 2023 to August 2024 were selected as the study subjects.Before discharge(T1),surveys were conducted using a general information questionnaire,the Chinese version of the Patient Activation Measure(PAM13),the FRAIL scale(to screen for frailty risk),and the Social Support Rating Scale(SSRS).Patient activation was reassessed using the Chinese version of the PAM 13 at 1 month(T2),3 months(T3),and 6 months(T4) after discharge.Spearman correlation analysis was used to examine the correlations of patient activation scores across the four time points.Latent class growth modeling was employed to identify potential categories of patient activation trajectories,and multinomial logistic regression was performed to analyze the influencing factors of these trajectory categories.

A total of 216 patients completed the study.The patient activation scores at T1,T2,T3,and T4 were 54.6 (40.1,66.0),56.4(43.4,73.1),51.4(41.7,63.2),and 51.4(42.1,66.0),respectively.Spearman correlation analysis showed positive correlations among patient activation scores at all four time points(all P<0.01).The latent class growth model identified three distinct trajectory categories:high activation-stable group(27.3%),moderate activation-declining group(32.9%),and low activation-gradually increasing group(39.8%).Multinomial Logistic regression revealed that education level,NYHA functional class,comorbidities,frailty status,and social support were significant influencing factors for the trajectory categories of patient activation in chronic heart failure patients(all P<0.05).

There is significant inter-individual heterogeneity in the trajectories of patient activation among chronic heart failure patients,which are influenced by education level,NYHA functional class,comorbidities,frailty status,and social support.Healthcare providers should implement targeted interventions based on the characteristics of patients' activation trajectories to comprehensively improve their activation levels.