Jiao Lu

Objectives: To identify joint trajectories of online and offline social activity and examine their associations with cognitive decline and frailty progression among middle-aged and older adults in China. Methods: Data from 14,340 adults aged ≥45 years in CHARLS (2011–2018) were analyzed; outcome-specific samples included 10,323 participants for cognition and 13,960 for frailty. Group-based multi-trajectory modeling identified trajectories. Linear mixed-effects models estimated associations with annual changes in cognition and frailty. Results: Three trajectories were identified: persistently low social activity engagement (G1, 47.8%), offline social activity dominant (G2, 47.0%), and online social activity increasing (G3, 5.2%). Compared with G1, G2 showed slower cognitive decline (0.010 SD units/year, 95% CI [0.002, 0.018]) and frailty progression (−0.014 SD units/year, 95% CI [−0.020, −0.007]); G3 showed stronger associations for cognition (0.044 SD units/year, 95% CI [0.029, 0.060]) and frailty (−0.041 SD units/year, 95% CI [−0.055, −0.026]). Conclusion: The Offline Social Activity Dominant Group was associated with slower cognitive decline and frailty progression, with stronger associations for the Online Social Activity Increasing Group. Integrating online and offline social participation may support healthy aging.

Cardiovascular Metabolic Comorbidities (CMM) share common physiological mechanisms in inflammation and immunity, oxidative stress, and insulin resistance, leading to mutual disease interactions and complex clinical manifestations. To address challenges in describing CMM status based solely on clinical features, this paper proposes a digital marker to characterize the differences from single to multiple diseases, systematically revealing distinct CMM subgroups based on cross-sectional data. This paper constructed a directed acyclic network for CMM using demographic characteristics, clinical laboratory parameters, and disease status as nodes via the DirectLiNGAM algorithm. Network features were described using in degree, out degree, degree centrality, betweenness centrality, and closeness centrality, ranking node importance. The top seven significant clinical laboratory parameters were selected based on this ranking. Subsequently, the performance of ten machine learning algorithms ( Random Forest , XGBoost , MLP , KNN , Gradient Boosting , SVC , Linear Regression , Ridge , ElasticNet , Lasso ) in generating digital markers by predicting death was evaluated to determine the optimal algorithm. The generated digital markers were then binned to classify CMM into Low, Middle, and High groups. Finally, linear regression validated the rationality of the network filtered clinical laboratory parameters. In the CMM network, the top three disease nodes by in degree are DM, MemD, and DL, while the top five by out degree are TC, HBALC, GLU, HCT, and HGB. Regarding network centrality, the top five nodes by degree centrality are Male, TG, DM, CYC, and DL; by betweenness centrality, Male, Stroke, TG, DL,and DM; and by closeness centrality, Male, DM, Married, Stroke, and CA. Network analysis identified top clinical laboratory parameters as GLU, HBALC, TC, UA, HCT, TG, HGB, WBC, and CYC, consistent with statistically significant parameters ( P < 0.05) in linear regression validation. Among machine learning algorithms, Ridge regression performed best in AUC , PR‑AUC , Brier Score , and Log Loss . The digital marker generated by Ridge regression yielded average scores of 0.016(0.008), 0.058(0.019), 0.296(0.197) for Low, Middle, and High groups, respectively. This paper developed a digital marker by integrating network analysis and machine learning to delineate CMM’s cross‑sectional subgroups, indicating its potential for early detection and enabling future research on stratified interventions for high risk groups.

This study explores public attitudes toward genetic sequencing (GS) services in China and identifies key factors influencing adoption. Although GS has the potential to strengthen precision public health, its uptake may be constrained by societal and attitudinal barriers. We used a sequential mixed-methods design, combining focus group discussions with a structured ranking questionnaire. A total of 28 participants (mean age 48.9 years) were included. The qualitative analysis identified five major themes reflecting participants’ understanding, concerns, and expectations regarding GS. Quantitatively, the most influential factors for adoption were the characteristics of genomic information and financial accessibility. Demographic differences were observed: men prioritized cost, whereas women emphasized clarity of information; older adults focused on affordability, whereas younger participants valued transparency and the utility of information. Psychological concerns also emerged as an important barrier, including fears of genetic discrimination and emotional distress arising from the implications of genetic information. In contrast to European studies that often highlight privacy and data protection, participants in this study placed greater emphasis on informational and financial considerations. Despite the modest sample, thematic saturation was reached and the mixed-methods approach provides complementary qualitative and quantitative evidence. Addressing public concerns through transparent communication, education, psychological support, and affordability-focused policies will be important to facilitate integration of GS into healthcare systems. These findings provide culturally grounded evidence to inform precision public health in China and similar contexts.

BACKGROUND While telehealth has become a transformative tool enhancing healthcare accessibility and efficiency, adoption rates in China remain low. Chinese healthcare professionals’ low telehealth adoption rates are poorly understood. OBJECTIVE Our study investigates the key factors influencing Chinese healthcare professionals’ intention to adopt and actual use of telehealth. Based on the results from estimating an integrated telehealth use framework, we also make recommendations for improving healthcare professionals’ telehealth adoption. METHODS Data on 10,372 healthcare professionals from the 2023 Xi’an Healthcare Worker Survey were analyzed, utilizing descriptive statistics (chi-square test, group differences), reliability testing (Cronbach’s α coefficients), Discriminant validity analysis (square root of average variance extracted) and fit tests. Based on our integrated telehealth use framework, structural equation modeling was employed to test hypotheses and path relationships, including multi-group analysis to examine demographic moderating effects. RESULTS Confirming our hypotheses on telehealth intention to use and actual use, the structural equation model showed strong fit indices. Key predictors of behavioral intention to use telehealth included effort expectancy, price value, performance expectancy, and social influence. Behavioral intention and facilitating conditions positively influenced actual use behavior, while demographic characteristics moderated specific relationships. CONCLUSIONS Our study identifies critical factors influencing healthcare professionals’ adoption of telehealth, including performance expectancy, social influence, and facilitating conditions. It offers an integrated framework to assess behavioral intentions and provides practical insights for advancing telehealth implementation in China. Tailored strategies for diverse demographics and institutions are essential for promoting sustainable adoption. CLINICALTRIAL This study was reviewed and approved by the Biomedical Ethics Committee of Xi’an Jiaotong University (approval number: XJTUAE2646).

This Research Topic is the second volume. Please see the first volume at: Impact of Environmental Factors on the Health of Children and Older AdultsEnvironme... This Research Topic is the second volume. Please see the first volume at: Impact of Environmental Factors on the Health of Children and Older AdultsEnvironme...

Background: Digital health technologies (DHTs) are transforming global health care delivery, yet physician adoption remains highly variable and influenced by a complex interplay of individual, institutional, and technological factors. In China, despite national initiatives such as the “Healthy China 2030” strategy promoting DHT integration, understanding physicians' heterogeneous perceptions is essential for effective implementation. Objective: This study aimed to identify distinct latent profiles of Chinese physicians based on their perceptions of DHT benefits, barriers, and behavioral intention, and to examine the demographic and occupational factors associated with profile membership. Methods: A cross-sectional survey was conducted among 4851 physicians (female, n=2994, 60.69% ; mean age 38.4, SD 8.7 years; 51.58% (n=2502) with more than 10 y working experience) from 46 hospitals in Shaanxi Province, China, between October and December 2023. Assessment included nine indicators across three domains: Perceived Benefits (4 items), Adoption Barriers (4 items), and Behavioral Intention (1 item). Latent profile analysis was used to identify distinct subgroups of physicians based on their response patterns. Multinomial logistic regression examined predictors of profile membership, and results were reported as odds ratios (ORs) with 95% CIs. Results: The latent profile analysis identified 5 distinct profiles: Reform-Adaptable (n=516, 10.64%; 95% CI 9.76%-11.52%), Negative (n=1003, 20.68%; 95% CI 19.50%-21.86%), Neutral (n=2276, 46.92%; 95% CI 45.50%-48.34%), Reform-Conservative (n=545, 11.23%; 95% CI 10.33%-12.13%), and Positive (n=511, 10.53%; 95% CI 9.66%-11.40%). Significant intergroup differences were observed in demographic and occupational characteristics. For instance, compared with the Negative profile, male physicians were less likely to belong to the Neutral (OR 0.76, 95% CI 0.64‐0.90; P =.001) and Reform-Conservative (OR 0.67, 95% CI 0.54‐0.84; P =.001) profiles. Compared to the Neutral profile, physicians with a master’s degree or above were less likely to be in the Reform-Conservative profile (OR 0.75, 95% CI 0.59‐0.96; P =.052). Those working in tertiary hospitals were less likely to belong to the Positive group (OR range 0.56‐0.66, P =.001). High-income physicians were more likely to be in the Reform-Conservative group (OR range 1.83‐2.38, P =.001). In addition, higher occupational stress was associated with a greater likelihood of Positive profile membership (OR range 1.12‐1.26, P =.001), while better work satisfaction predicted higher odds of Positive profile membership (OR range 1.04‐1.16, P =.001). Conclusions: This study introduces a novel, person-centered approach by identifying five distinct perceptual typologies among physicians, moving beyond traditional variable-centered analyses. This typology provides an evidence-based foundation for tailored interventions. For instance, the Reform-Adaptable group may need barrier reduction, while the Reform-Conservative group may require clearer value demonstrations. This nuanced understanding can help healthcare systems enhance the impact and scalability of digital health technologies in real-world clinical practice.

Understanding factors associated with home births is crucial for identifying appropriate interventions for mother and child survival and attaining the Sustainable Development Goals. No national studies have explicitly examined the distribution of home birth and its contributing factors. This study aims to assess the distribution of home birth and the contributing factors among mothers of reproductive age 15-49 years in Somalia. We analyzed the data of 8,631 mothers who gave birth within five years preceding the survey and provided responses on variables studied. The data was obtained from the 2020 Somali Health and Demographic Survey. Respondents' characteristics were summarized using descriptive analysis. Chi-square tests were applied to test the association between the distribution of home birth and each predictor. Multivariate logistic regression was used to assess factors contributing to home birth. We employed the STROBE checklist for manuscript reporting. The prevalence of home birth among reproductive mothers in this study was, 75.5% (95% CI: 0.74-0.76). Living in the Northeast (AOR = 1.48, 95% CI: 1.17-1.86), no level of education (AOR = 2.38, 95% CI: 1.84-3.06), no media exposure (AOR = 3.67, 95% CI: 3.25-4.13), poor household wealth status (AOR = 3.80, 95% CI: 3.07-4.71), maternal autonomy (AOR = 1.36, 95% CI: 1.21-1.53), need companionship to treatment facility (AOR = 1.20, 95% CI: 1.07-1.36), and no antenatal visits (AOR = 3.91, 95% CI: 1.66-9.26) were associated with increased likelihood of home births among mothers. By contrast, urban and rural residences, low parity, and first-trimester antenatal visits were associated with a decreased likelihood of home births among mothers of reproductive age 15-49 years in this study. The Somali government has made efforts to improve maternal health utilization and reduce the associated deaths. However, three-quarters of Somali mothers still undergo home births. To lower home births in Somalia, government and non-governmental organizations should consider scaling institutional births by improving maternal level of education, media accessibility, and household wealth status. Priority emphasis must be given to the maternal knowledge of the benefits of antenatal visits for both herself and her baby.

Background: Mobile health (mHealth) is considered an effective way to manage chronic disease patients’ health. However, patients often do not use or continue using mHealth services due to concerns about service quality. Patient satisfaction may influence their utilization, and this effect may be moderated by platform regulations and differences in physicians’ qualifications and regions. Objective: This study aims to enhance mHealth service utilization by examining how patient satisfaction affects both use and continuous use behaviors. It also explores the role of platform regulations (recommendation, commenting, and reward systems) and assesses differences due to physician proficiency and regional variations. Methods: Data were collected from Haodf, a leading mHealth platform in China, from October 2021 to March 2022 at 3-month intervals. Generalized additive models were used to verify nonlinear relationships between patient satisfaction and their utilization behaviors. The role of platform regulations and heterogeneity analysis regarding physician region was also examined. Results: Efficacy satisfaction positively influenced mHealth service utilization ( p < 0.01), while efficacy and attitude satisfaction positively influenced continuous use ( p < 0.01). Platform regulations altered these relationships ( p < 0.01). Comprehensive recommendations had a greater effect than patient recommendations ( p < 0.01). High-quality evaluations played a significant role ( p < 0.01), while nonmaterial rewards had no significant effect ( p ≥ 0.05). These relationships varied by physician region ( p < 0.01). Conclusions: Efficacy satisfaction drives mHealth service utilization, while efficacy and attitude satisfaction drive continuous use. Recommendation and commenting systems exhibit a positive synergistic effect, while the reward system plays a supplementary role. Professional recommendations and high-quality evaluations enhance the evaluation system's reliability, promoting service utilization. Patients in big cities are more sensitive to physicians’ proficiency and therapeutic effects. A multidimensional, transparent evaluation and feedback system should be integrated into the platform to improve service quality and increase patient utilization and loyalty.

Health system reform initiatives have generated high-demand and created uncertain, complex practice environments, impacting the well-being, work conditions, and behavior of primary care professionals. Psychological safety is increasingly important to organizational success, particularly in highly complex work environments. Yet, few studies have examined its application among primary care professionals. To examine the impact of psychological safety on the well-being, work conditions and guideline adherence behavior of primary care physicians (PCPs) in Community Health Centres (CHCs) in urban China. A total of 224 PCPs from 38 CHCs in four Chinese cities were recruited using convenience sampling. Research assistants conducted questionnaire surveys. Well-being was assessed through measures of depression, work-family conflict and work exhaustion, work conditions were defined by measures of professional commitment and self-directed learning, and guideline adherence behavior was measured through compliance with clinical guidelines and the provision of preventive care. Two-level hierarchical linear models were developed to analyze the impact of psychological safety. Psychological safety was negatively associated with depression, work-family conflict, and work exhaustion. Psychological safety was positively associated with professional commitment and self-directed learning and also greater adherence to clinical guidelines and the increased provision of preventive care. This study in China confirms that a psychologically safe work environment in primary care is positively associated with improved PCPs’ well-being, enhanced professional commitment, and better adherence to clinical guidelines and preventive care provision. Given that psychological safety may be embedded in national culture, further studies should develop context-based, culturally and organizationally appropriate interventions.