Hao Ji

Background: Smart wearable devices are increasingly incorporated into later-life health management, but longitudinal evidence concerning device ownership and depressive symptoms remains limited. Objective: This study examined the within-person association between smart wearable device ownership and depressive symptoms among older adults in China, alongside concurrent psychosocial and behavioral characteristics and variation across digital and sociodemographic contexts. Methods: Data were drawn from the 2018, 2020, and 2023 waves of the China Longitudinal Aging Social Survey. The baseline analytical sample comprised 30,255 person-year observations from 16,752 respondents. Two-way fixed-effects models were estimated using 22,536 observations from 9,033 repeatedly observed respondents, including 902 ownership switchers. Depressive symptoms were measured using a reverse-coded nine-item CES-D score. Additional analyses examined health perception, social adaptation, leisure participation, mobile phone proficiency, sociodemographic heterogeneity, sample selection, and attrition. Results: Smart wristband or smartwatch ownership was positively associated with the reverse-coded CES-D score within individuals ( β = 0.719, 95% CI [0.414, 1.024]), indicating fewer depressive symptoms during waves in which ownership was reported. The association remained positive across multiple sensitivity analyses. Ownership also covaried positively with health perception, social adaptation, and leisure participation, although their contemporaneous measurement precluded causal mediation claims. Contemporaneous analyses showed a more favorable ownership association at higher levels of self-rated mobile phone proficiency (linear interaction β = 1.890, p < .001), whereas prior-proficiency analyses produced weaker evidence. Heterogeneity was statistically supported for hukou origin, but not for gender, age, or education after multiplicity adjustment. Conclusions: Smart wearable device ownership was positively associated with fewer depressive symptoms within individuals, but the findings do not establish a causal effect. Digital capabilities and institutional context appear important for understanding heterogeneity in the ownership–depressive-symptom association. Clinical trial number: Not applicable.

Background: Digital government has become a critical component of contemporary public governance, yet its relationship with residents’ mental health remains insufficiently examined. This study investigates whether digital government development is associated with residents’ mental health in China and how this association varies across urban and rural populations. Methods: We linked the 2020 and 2022 provincial Digital Government Development Indices with individual-level data from the 2021 and 2023 waves of the Chinese General Social Survey. Employing a one-period lagged matching strategy within a pooled cross-sectional design, we estimated the association using Ordinary Least Squares (OLS) models. Instrumental variable (IV) estimation was used to address potential endogeneity concerns, supplemented by robustness checks, mechanism analysis, and heterogeneity analysis. Results: Digital government development is positively and consistently associated with residents’ mental health. Mechanism analyses suggest that reduced health-related activity limitations and enhanced life happiness may serve as two potential transmission pathways. This positive association appears more stable among rural residents, although the statistical significance of the urban–rural difference should be interpreted cautiously. Further heterogeneity analysis indicates that the association is more evident among individuals with higher human capital, fewer health constraints, and stronger capacity to use digital public services. Conclusion: Digital government may have implications beyond administrative efficiency by being linked to residents’ mental health, health capabilities, and psychological resources. To foster inclusive digital governance, policymakers should prioritize health service integration, digital accessibility, service usability, and offline support for vulnerable and structurally disadvantaged groups.

To provide a reference for the realization of children’s equal inheritance, this study examined the influence of child structure and means of eldercare on equitable family property distribution willingness. Using data from surveys of Chinese women’s social status, this study analyzes the impacts of child structure and means of eldercare on family property distribution, with the children’s surname choice and women’s status as moderating factors. The results indicate that a child structure in which the family consists of more girls than boys, a higher number of children, and the choice of family support for eldercare significantly inhibit the equal distribution of family assets. However, the weakening of traditional views significantly promotes the equal distribution of household assets. These findings remain robust after endogenous and robustness tests. Moreover, the study finds that the impact of the structure of children and eldercare methods varied across different age groups, household registration attributes, and genders. Research on the willingness to distribute household wealth aids in understanding the effects and differences brought about by the structure of children and eldercare methods under current traditional cultural contexts, thereby promoting a more equitable distribution of household wealth.

To study the digital needs, activities, and experiences of elderly users, evaluate the performance of age-friendly digital retrofit, and provide a path to bridge the digital divide among elderly users. Based on the user experience perspective, the age-friendly evaluation model of the “elder mode” APP was constructed, the index weights were determined based on the entropy weight method, and WeChat, Alipay, ZOA, and ZARA of the “elder mode” were selected as the research objects. We use questionnaires and in-depth interviews to collect user data and use a fuzzy comprehensive evaluation method for empirical evaluation. The overall experience of elderly users on the four APPs is at the upper level of “generally satisfied,” among which the age-friendly level of “visual experience” and “behavioral experience” is high, while the level of “interaction experience” and “value experience” needs to be improved. In particular, attention needs to be paid to the retrofit of the fault-tolerant mechanism, toughness, and error correction of digital products. The paper proposes countermeasures in terms of enhancing the compatibility of interface elements of digital products, optimizing embedded interaction procedures, improving human-computer interaction options, enhancing fault tolerance of operations, and improving age-friendly continuity and thoroughness.

BACKGROUND At present, it is common to use online diagnosis and treatment (ODT) information for self-medication, but its internal decision-making logic is still lack of understanding and verification. OBJECTIVE This paper takes quality and utility dimensions of ODT information as independent variables, takes trust and perceived value as mediating variables, and then constructs a conceptual model of self-medication intention for ODT information seekers. METHODS This paper takes quality and utility dimensions of ODT information as independent variables, takes trust and perceived value as mediating variables, and then constructs a conceptual model of self-medication intention for ODT information seekers. RESULTS Based on the data analysis of 352 respondents, we have three findings: relevance of ODT information is the most important factor for trust and perceived value, even professionalism cannot play such a key role. Trust has a greater impact on self-medication intention than perceived value, where the path coefficient reaches 0.56. the influence of relevance on trust and perceived value deserves more attention than other independent variables, since the path coefficients to trust and perceived value are higher than others. Timeliness and completeness of ODT information are not close related with perceived value, while understandability has little impact on trust. Finally, suggestions including strengthening personalized recommendation of ODT information, using readily comprehensible words, and regulating online medication guidance were put forward. CONCLUSIONS Suggestions including strengthening personalized recommendation of ODT information, using readily comprehensible words, and regulating online medication guidance were put forward.

Bipartite graph is widely used to model the complex relationships among two types of entities. Community detection (CD) is a fundamental tool for graph analysis, which aims to find all or top- densely connected subgraphs. However, the existing studies about the CD problem usually focus on structure cohesiveness, such as - core, but ignore the attributes within the relationships, which can be modeled as attribute bipartite graphs. Moreover, the returned results usually suffer from rationality issues. To overcome the limitations, in this paper, we introduce a novel metric, named rational score, which takes both preference consistency and community size into consideration to evaluate the community. Based on the proposed rational score and the widely used - core model, we propose and investigate the rational - core detection in attribute bipartite graphs (RCD-ABG), which aims to retrieve the connected - core with the largest rational score. We prove that the problem is NP-hard and the object function is nonmonotonic and non-submodular. To tackle RCD-ABG problem, a basic greedy framework is first proposed. To further improve the quality of returned results, two optimized strategies are further developed. Finally, extensive experiments are conducted on 6 real-world bipartite networks to evaluate the performance of the proposed model and techniques. As shown in experiments, the returned community is significantly better than the result returned by the traditional - core model.