Depression is a serious mental health condition, primarily manifested by persistent sadness, diminished interest, difficulty concentrating, and lack of energy (14). It typically leads to a decline in quality of life, increased mortality, and higher risks of suicide, contributing to a substantial societal burden (15). Due to the unique physiological characteristics, economic status, and social relationships of rural older adult individuals, they often face a higher risk of depression (16). A meta-analysis reveals that the prevalence of depressive symptoms among older adult individuals in rural China reaches 24.0% (5). Another study investigating differences in depressive symptoms between urban and rural older adult populations shows that the incidence of depressive symptoms among rural older adult (12.41%) is higher than that of urban older adult (10.13%) (17). These findings, consistent with other research, confirm a significant urban–rural disparity in the incidence of depression among the older adult in China (18), underscoring the urgent need for targeted attention and intervention to address depression in rural older adult individuals.

The depressive symptoms among rural older adult individuals are intricately linked to a variety of factors, including their individual characteristics, health related risk factors, family support, and social environment. Primarily, in terms of individual characteristics of older adult individuals, the depressive symptoms status of rural seniors varies according to gender, educational background, and health status. Scholars have observed gender differences in depressive symptoms among Chinese rural older adult individuals, attributing the phenomenon to women’s tendency to be more sensitive and nuanced, and thus more susceptible to psychological problems, than men (19); Maier’s research shows that as educational attainment increases, the prevalence of depression among older adult individuals gradually decreases (20); Secondly, in terms of mental health-related risk factors for older adult individuals, older adult individuals with better self-rated health and healthier lifestyles had a lower risk of depression (21), and older adult individuals who slept less than 6 hours were more likely to experience depressive symptoms (22); In a longitudinal study, Liu et al. have found that the prevalence of depression among older adult individuals with chronic conditions was 1.17 times higher than among those without chronic conditions (23), and even higher among those with more than two to three chronic conditions (24). Furthermore, based on the millennia-old tradition of filial piety, the support of children is an important pillar for the survival of the older adult in rural China and plays an important role in their mental health (25). Research shows that the economic support, emotional interaction, and care giving behaviors of children can reduce negative emotions in older adult individuals (26), improve their subjective well-being (27), and enhance their autonomy in later life. Living with children is beneficial to the depressive symptoms among rural older adult individuals (28). However, in the process of modernization, a significant number of young and middle-aged rural workers are choosing to migrate to urban areas for work and business (29), increasing the physical distance between generations (30). This has made traditional care models impractical (31), resulting in varying degrees of deterioration in the physical and mental health of older adult individuals (32). In addition, the social environment also influences the psychological well-being of older adult individuals. A longitudinal analysis conducted in Europe suggests that inadequate social networks and levels of participation are associated with depressive symptoms among older adult individuals (33). Engaging in social activities has been shown to improve the depressive symptoms among rural older adult individuals (34); Xue et al. also found that older adult individuals with higher socioeconomic status are less likely to experience negative emotions such as loss and depression (35). Furthermore, researchers have indicated that good access to healthcare services and higher family income are beneficial for alleviating depressive symptoms among rural older adult individuals.

Under the guidance of China’s National E-Commerce Demonstration Cities (NEDC) initiative and the significant promotion of digital platforms and internet infrastructure (36), e-commerce rapidly emerges as one of the fastest-growing sectors. E-commerce is defined as “using electronic information technology to conduct business between trading partners, using or not using electronic data interchange (EDI), using or not using the Internet” (37), unlike traditional social media and internet technologies, e-commerce places greater emphasis on the online process of goods trade, including product selection, consultation, and sharing of shopping experiences. The widespread adoption of online sales models expands consumer channels, creates diverse employment opportunities, and significantly boosts economic growth (38). According to the statistics, the online retail sales in China reached 13.1 trillion yuan in 2021, of which online retail sales of physical goods accounted for over 82%, accounting for 24.5% of the total retail sales of consumer goods (39). In addition to economic benefits, e-commerce influences residents’ shopping behaviors and enriches their participation in online social interactions. Furthermore, the optimization and upgrading of logistics systems generate new services, such as offline parcel collection and returns, which, to some extent, promote residents social interactions and subsequently impact their mental health. Studies indicate that the digital economy, primarily measured by e-commerce, expands social interaction opportunities and reduces depression rates among middle-aged and older adult individuals (40). However, among university students, irrational online shopping and shopping addiction associated with e-commerce may increase the risk of depression (41). These findings suggest that the impact of e-commerce on residents’ depressive symptoms warrants further investigation.

Current studies mostly focus on the consumption capacity of residents and its income-increasing effect on rural areas under the development of e-commerce economy (42), paying little attention to exploring the impact of e-commerce on the depressive symptoms of residents and its mechanism of action, especially for the rural older adult who are socially marginalized. In view of this, this study takes the depressive symptoms among rural older adult individuals in China as the main research object to explore new dimensions of the relationship between e-commerce and depressive symptoms that have received less attention in the previous literature, with the expectation of providing references for improving the depressive symptoms among rural older adult individuals.

The theoretical foundation of this study is primarily based on Role Theory, Activity Theory, and Family Support Hypothesis. These theories provide important perspectives for understanding how rural e-commerce affects depressive symptoms among rural older adult individuals, particularly in the context of social interaction and financial support by children.

Role Theory was initially developed to explore how individual behavior changes due to variations in environment and identity (43). As research has progressed, the conceptual framework of this theory has become increasingly comprehensive, providing a theoretical foundation for understanding the role transformations of older adult individuals in the context of e-commerce in rural areas. During the aging process, rural older adult individuals undergo two primary role transformations (44). Firstly, as physical abilities decline and learning capacities diminish, they transition from active work roles to leisure roles, with many forced to withdraw from work and opt for home-based retirement (45). This shift diminishes their social functionality and contracts their social networks, resulting in a significant reduction in opportunities for social interaction. The abundance of leisure time, coupled with the lack of recreational facilities in rural areas, leaves many older adults feeling directionless, further exacerbating feelings of loneliness, loss, and confusion about the meaning of life. Secondly, cognitive and physical limitations compel rural older adult individuals to gradually cede their dominant roles within the family to their adult children, and depend on them for care and financial support (46). If the older adult fail to adapt to this transition, they may experience a profound sense of loss, which can trigger negative emotions such as anger and depression, ultimately affecting family harmony.

In this context, the development of rural e-commerce can effectively alleviate depressive symptoms among older adult individuals in two key ways. Firstly, the online trading activities facilitated by e-commerce create novel and purposeful forms of leisure for rural seniors, enabling them to easily browse and purchase a variety of goods that meet both their basic needs and emotional desires. This sense of engagement enhances their autonomy and satisfaction, helping them to redefine their life roles and alleviate the negative emotions stemming from the contraction of social relationships. Secondly, e-commerce also facilitates interaction between rural older adult individuals and their adult children. Through e-commerce platforms, children can not only guide their parents on how to shop online but also directly purchase necessary items for them. This interaction allows seniors to feel valued and cared for by their family members, alleviating feelings of role displacement while fostering joy and a sense of well-being, ultimately enhancing their mental health.

Activity Theory asserts that participation in social interaction is essential for the mental health of older adult individuals (47). We now live in an information age where the concept of social interaction has been significantly expanded. In addition to traditional face-to-face communications, rural seniors can engage in online social interactions, such as those facilitated by e-commerce, to connect with people around the world (48).

E-commerce platforms offer various avenues for interaction with merchants, other buyers, and live stream hosts, including product consultations, shopping shares, and live selling sessions (49, 50). This not only alleviates the social participation inequalities faced by older adult individuals in urban and rural areas due to inadequate infrastructure and service accessibility, but also expands their social circles and effectively reduces feelings of social isolation and loneliness (51). Additionally, the offline processes associated with e-commerce, such as product pickup and returns, facilitate communication between rural older adult individuals and delivery personnel. Therefore, e-commerce promotes the social interaction frequency among rural seniors from both online and offline perspectives. Based on this, the present study selects the social interaction frequency among rural older adult individuals as a mediating variable to explore the relationship between e-commerce and depression symptoms in this population.

According to the Family Support Hypothesis, emotional and financial support from family members can effectively reduce depression levels among the older adult (52). Multiple studies have shown that financial support by children has a positive impact on the mental health of seniors (53, 54). Rooted in the traditional Chinese concept of filial piety, such financial assistance not only provides material help but also signifies respect and care for parents (38). This emotional support can significantly enhance the life satisfaction of older adult individuals.

The development of e-commerce provides new avenues for family support. On one hand, children can directly meet their parents’ online shopping needs through financial transfers. On the other hand, they can actively purchase necessary items for their parents. These actions not only satisfy the material needs of older adult individuals but also enhance their perception of family support. Through these means, rural seniors can feel valued, which, in turn, boosts their sense of happiness and promotes their mental well-being.

Based on the preceding discussion, the following hypotheses are proposed:

The Conceptual Framework of this study is illustrated in Figure 1. This figure indicates that the development of rural e-commerce can directly and indirectly improve depressive symptoms among rural older adult individuals. First, based on “Role Theory” rural e-commerce facilitates role adaptation in the older adult, directly impacting their depressive symptoms. Second, supported by “Activity Theory,” which emphasizes that “participation in social activities is crucial for the mental health of older adult individuals,” the study finds that the growth of rural e-commerce enhances the social interactions frequency among rural older adult individuals, thereby alleviating their depressive symptoms. Additionally, the mechanism by which rural e-commerce development improves depressive symptoms through increased financial support by children is supported by the “Family Support Hypothesis.”

The data underlying this study come from two sources. The first is the China Health and Retirement Longitudinal Study (CHARLS) database, a large interdisciplinary survey project hosted by the National Institute of Aging at Peking University and conducted by the Chinese Academy of Social Sciences. The survey is randomized and has been collecting baseline data on a variety of aspects, including basic information, health status, and health care, from families and individuals aged 45 and older across China since 2011. Subsequent follow-up surveys were conducted in 2013, 2015, 2018, and 2020. To date, the CHARLS database has been used to survey 19,000 respondents from 12,400 households in 450 communities (villages) across 150 counties in 28 provinces (autonomous regions and municipalities) nationwide. This study uses five datasets from the CHARLS database, from its inception in 2011 to 2020, for empirical analysis. The second source is the China Regional Statistical Yearbook, an annual publication compiled by the National Bureau of Statistics that comprehensively reflects the economic and social development of various regions within China. The data on city-level control variables included in this study are extracted from this document.

To promote rural economic development and reduce the urban–rural economic gap, China has gradually implemented the E-commerce to Villages plan. In 2014, China launched the first batch of pilot programs for the policy, with 56 regions receiving support to establish rural e-commerce demonstration counties. The policy aims to improve e-commerce infrastructure, enhance service levels, provide e-commerce training, and cultivate e-commerce talent in the pilot areas. Subsequently, the second and third batches of pilot programs were launched, gradually expanding the scope and scale of the initiative (66).

The Difference-in-Differences (DID) method can be used to assess the impact of policies by comparing changes in the policy intervention group and the control group before and after the policy intervention, and it is currently widely applied in the field of policy evaluation (9). It is typically used to assess the effectiveness of policies implemented during the same period. However, the rural e-commerce policy involves different pilot regions and varying implementation timelines, providing a quasi-natural experimental environment for this study. Therefore, a staggered Difference-in-Differences model is employed for regression analysis. In this model, regions that implemented the rural e-commerce policy are considered the treatment group, while regions that did not implement the policy serve as the control group. To explore the impact of e-commerce development levels on the depressive status of the rural older adult, The established model is as follows:

In this model, Depressio n it represents the depressive symptoms among rural older adult individuals. The DID (Difference-in-Differences) serves as the core explanatory variable. If the rural area where the older adult individual resides implements the e-commerce policy at time t, the DID takes a value of 1; otherwise, it is 0. This variable acts as the interaction term in traditional Difference-in-Differences approaches. ∑ α 2 Contro l it represents a series of control variables for individual characteristics and social environments among rural older adult individuals, γ i is regional fixed effects, and μ t is annual fixed effects.

Table 3 presents the descriptive statistics of the main variables in this study. A total of 10,134 rural older adult individuals participated in the survey, with a median age of 68 years (ranging from 60 to 98). The average score on the CES-D-10 depression scale is 8.639 ± 5.692.

This study investigates the impact of the development level of rural e-commerce on depressive symptoms among rural older adult individuals, with the basic regression results presented in Table 4. Column (1) of Table 4 provides the estimation results without any control variables, where the DID coefficient is significantly negative at the 1% level, indicating that the development of rural e-commerce has improved the depressive symptoms among rural older adult individuals. In Column (2), individual characteristics and social variables of the older adult are added, including age, health score, educational level, marital status, smoking and drinking habits, gender, logarithm of income, logarithm of GDP growth rate, logarithm of per capita GDP, the proportion of agriculture in the total output of the primary industry, and the logarithm of the number of people per million square kilometers, as well as the logarithm of the number of practicing assistant physicians per 10,000 people. The regression results show that although the DID coefficient remains negatively significant at the 1% level, the model’s goodness of fit increases, further demonstrating the robustness of the baseline regression.

To test the robustness of the empirical results, this study conducted the following tests.

The benchmark regression results show that the development of rural e-commerce can improve the depressive symptoms among rural older adult individuals. To further explore the underlying mechanisms, an empirical analysis is conducted to test the proposed mediation effects, specifically Hypotheses 2 and 3. Hypothesis 2 suggests that the development of e-commerce impacts depressive symptoms among rural older adult individuals by increasing social interaction frequency. Hypothesis 3 proposes that e-commerce development influences depressive symptoms by enhancing the financial support by children.

The benchmark regression results demonstrate that the development of e-commerce in rural areas is capable of improving the depressive symptoms among rural older adult individuals. Our investigation findings further validate the assertion of Huang et al. that e-commerce platforms can enhance the well-being of rural residents (77). Nevertheless, the distinction lies in that our research focuses on the depressive symptoms among rural older adult individuals.

The potential explanatory mechanisms for this finding are as follows. First, e-commerce policies significantly influence the shopping behaviors of rural older adult individuals. The implementation of the rural e-commerce policy actively promotes the development of rural e-commerce infrastructure, such as expanding internet coverage and optimizing logistics networks. This provides older adult individuals with a convenient online shopping environment, greatly reducing the time and physical effort required for shopping (78). Even those in remote areas can access essential goods and medical supplies via the internet. These improvements enhances the quality of life for rural older adult individuals, increase their sense of autonomy and fulfillment, and, in turn, reduce psychological stress associated with shopping challenges (79). Second, e-commerce policies promote the well-being of rural older adult individuals by enhancing social interaction. E-commerce platforms inherently offer social features, such as product reviews and the sharing of shopping experiences, which facilitate interactions between rural older adult individuals and other users (50). These online virtual interactions not only help alleviate loneliness in the daily lives of rural older adult individuals but also foster a sense of social participation and belonging, thereby improving their mental health (51). Additionally, the increased internet accessibility and improved digital literacy among rural older adult individuals—facilitated by e-commerce policies—likely play a crucial role in further enhancing their mental well-being. As internet coverage expands, rural older adult individuals gain broader access to emotional support and social participation through various online channels, overcoming geographical barriers and effectively alleviating depressive symptoms (80). Furthermore, the widespread adoption of e-commerce platforms also facilitates interaction between older adult individuals and their children. Many children purchase daily necessities for their parents through e-commerce platforms, establishing a new mode of intergenerational interaction (81). This mode not only strengthens the emotional bond between the older adult and their children but also allows the older adult to feel familial support and care, thereby enhancing their mental well-being.

However, the development of e-commerce also introduces potential negative impacts. First, the digital divide remains a significant issue. Older adult individuals with higher digital literacy can more easily navigate e-commerce platforms, interact with others, and communicate, thereby significantly reducing their psychological stress and feelings of loneliness. However, some older adult individuals, lacking digital skills, are unable to fully utilize e-commerce platforms, preventing them from benefiting from the convenience brought by e-commerce (82). This limitation not only heightens their sense of disconnection from society but may also increase feelings of helplessness and isolation. Second, some older adult individuals may become overly reliant on e-commerce, engaging in online shopping excessively (83), particularly when unsupervised by family members. This overreliance may lead to challenges in financial management and even increase financial strain. Furthermore, while the virtual interactions facilitated by e-commerce provide more social opportunities, they may also reduce real-life social engagement to some extent. For older adult individuals who become overly dependent on online interactions, this substitution of virtual socialization may have negative consequences for their depressive symptoms (50).

The positive impacts observed in this study may partly result the unique characteristics of rural e-commerce development. First, the needs of rural older adult individuals tend to be more basic and practical (84), and the convenience of e-commerce platforms meets these needs without the unnecessary consumption that urban older adult individuals may be more prone to. Second, the development of rural e-commerce not only strengthens the economic and emotional ties between older adult individuals and their children but also compensates for the limited physical commercial infrastructure in rural areas. Particularly in remote regions, e-commerce has become the primary channel through which older adult individuals access goods (85). This convenient and efficient shopping method enhances the autonomy of older adult individuals in their daily lives while also providing greater support for their mental well-being. Finally, the social effects of e-commerce are particularly evident in rural areas. Compared to urban regions, rural areas have lower population density and fewer commercial activities, leading to narrower social networks and more limited social opportunities (86). Unlike general social media or the internet, e-commerce promotes dual interaction—with both society and family—by meeting the practical needs of older adult individuals. This dual function offers unique advantages in alleviating the depressive symptoms among rural older adult individuals, and provides effective new approaches for addressing the depressive symptoms among rural older adult individuals.

Although this study focuses on the impact of e-commerce on depressive symptoms among rural older adult individuals, its effects are often closely related to the widespread adoption of the internet and the enhancement of digital literacy among seniors. The internet’s coverage and the improvement of older adult individuals’ digital skills not only facilitate the use of e-commerce but also provide broader online social opportunities, collectively contributing to improved mental health.

Drawing upon the multi-period data from the CHARLS survey, this study examines the influence of rural e-commerce development on the depressive symptoms among rural older adult individuals, leading to the following conclusions: (1) The advancement of rural e-commerce has positively impacted the depressive symptoms among rural older adult individuals, with the findings maintaining statistical significance across parallel trend, placebo, Endogeneity, and PSM-DID tests. (2) Heterogeneity analysis reveals a more substantial effect of e-commerce development on the depressive symptoms among older adult individuals in eastern and central regions, as well as those not living with their offspring. (3) Mechanistically, rural e-commerce development influences depressive symptoms by boosting social interaction frequency among rural older adult individuals and enhancing the financial support by children. These findings offer empirical support for further inquiry into rural e-commerce development and for initiatives aimed at improving the depressive symptoms among rural older adult individuals.

This study finds that the rural e-commerce policy has a positive effect on alleviating depressive symptoms among rural older adult individuals. Future policies should address the specific needs of different regions and groups through targeted measures to further expand e-commerce coverage and enhance its impact, thereby maximizing its benefits for depressive symptoms among rural older adult individuals.

First, despite the control of multiple variables related to the demographic characteristics and social environment of rural older adult individuals in this study, these variables may not fully encompass all fundamental confounding factors influencing the depressive symptoms among rural older adult individuals. Second, the depressive symptoms data of rural older adult individuals are derived from self-reports, which may not accurately reflect their actual conditions. Third, due to data availability constraints, the CHARLS database does not provide information on actual e-commerce usage by rural older adult individuals, such as usage frequency or spending amounts. Consequently, this study examines the impact of e-commerce development on depressive symptoms among rural older adult individuals primarily from the perspective of e-commerce development levels. Future research could expand data sources to facilitate more in-depth analysis. Fourth, although we introduced instrumental variables to help mitigate endogeneity issues and used the PSM-DID model to address sample self-selection, we acknowledge that other factors may still contribute to potential endogeneity and omitted variable bias. Fifth, the heterogeneity analysis in this paper is limited to the three main economic regions of China: eastern, central, and western. Future research could delve into a more nuanced exploration of the effects of policy implementation on the depressive symptoms among rural older adult across various city sizes and cultural backgrounds.