Contributory and Developmental Social Participation and Depressive Symptoms Among Older Adults in China: Urban–Rural and Gender Disparities *

Contributory and Developmental Social Participation and Depressive Symptoms Among Older Adults in China: Urban–Rural and Gender Disparities * | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Contributory and Developmental Social Participation and Depressive Symptoms Among Older Adults in China: Urban–Rural and Gender Disparities * Yao Yu, Jing Ma, Wei Guo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9011244/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Background: Social participation is a critical determinant of mental health in later life, yet the heterogeneity of participation types and their differential impacts remains under-explored. This study proposes a contributory–developmental framework to categorize social participation and examines their distinct associations with depressive symptoms among Chinese older adults. Methods: Data were drawn from the 2020 wave of the China Longitudinal Aging Social Survey (CLASS, N = 7,443 retired older adults). OLS regression and moderation models assessed subgroup differences. Robustness checks using the 2018 wave confirmed the results. Results: Most participation types were linked to lower depressive symptoms, but intergenerational domestic support was associated with higher levels. An urban–rural paradox emerged: rural older adults engaged more in contributory participation but gained fewer mental health benefits than urban counterparts, whereas they reported greater improvements in depressive symptoms from developmental participation despite lower involvement. Gender disparities were evident: men were more engaged in beneficial activities such as post-retirement work, while women bore heavier family caregiving responsibilities. Discussion： Social participation plays a vital role in reducing depressive symptoms in later life. Recognizing heterogeneity across participation types and subgroups is essential. Policies should provide tailored, inclusive mechanisms to support diverse forms of participation among older adults. social participation depressive symptoms urban–rural gender Figures Figure 1 Introduction In the process of actively addressing population aging, promoting the health of older adults has emerged as a pivotal imperative. Although advances in healthcare have significantly improved the physical health of older adults, their mental health issues—particularly depressive symptoms—have yet to receive commensurate attention. In practice, multiple factors in real life, such as information isolation caused by the digital divide (Cotten et al., 2014 ; Liu et al., 2024 ), chronic burdens from long-term illnesses (Huang et al., 2010 ; Bisschop et al., 2014), and anxieties related to eldercare (Liu et al., 2019 ; Tiong et al., 2013 ), significantly exacerbate the risk of depression among older adults, thereby constituting a core challenge in enhancing their mental health and well-being. Focusing on the issue of reducing depression levels among the older adults, existing research has explored various perspectives, including psychosocial factors, behavioral interventions, and environmental support. Most empirical analyses indicate the positive role of social participation (Glass et al., 2006 ; Chiao et al., 2011 ; Croezen et al., 2015 ; Zhao & Wu, 2022 ). However, within the unique sociocultural structure and institutional context of China, this relationship is far from a simple linear facilitation; instead, it exhibits profound tensions and heterogeneity. More importantly, a significant limitation in much of the current research is the tendency to oversimplify social participation into binary variables (participation versus non-participation) (Baeriswyl & Oris, 2023 ; Wang et al., 2022 ) or the quantity of participatory activities (Guo et al., 2018 ), thereby somewhat neglecting the inherent typological differences and motivational distinctions within participatory behaviors. Such simplifications fail to adequately address the complexity of social participation patterns among older adults in China. Specifically, first, China’s institutional environment and social structure jointly shape the unique and diverse landscape of social participation among older adults. On one hand, China’s flexible employment policies and delayed retirement reforms have contributed to the differentiation of life trajectories in later years (Flynn, 2010 ; Piszczek & Pimputkar, 2021 ). On the other hand, the urban-rural dual structure systematically creates disparities in participation opportunities and resource constraints. Within this context, the types of social participation accessible to different subgroups of older adults in China are highly heterogeneous, with significant variations in their underlying motivations, frequencies, and objectives. These complex differences underscore the necessity of investigating how different types of social participation differentially impact depression among older adults. Second, although some studies have recognized the importance of distinguishing between types of social participation, significant discrepancies persist in existing classification systems and explanatory mechanisms. In terms of classification, existing research employs a variety of approaches, ranging from specific activity types (such as paid work, political activities, and volunteering) (Guo et al., 2018 ) to abstract participation patterns (e.g., high, medium, and low participation; economically active types) (Morrow-Howell et al., 2014 ). However, the lack of a unified theoretical framework has resulted in fragmented classification schemes, severely hindering dialogue and comparability across studies. Mechanistically, explanatory pathways diverge between the "opportunity provision theory" and the "psychological compensation theory." The former emphasizes the structural constraints imposed by unequal access to opportunities on mental health (Baeriswyl & Oris, 2023 ), while the latter focuses on the differential psychological compensatory effects of various activity types (Guo et al., 2018 ; Wang et al., 2022 ). These inconsistencies in measurement, classification, and mechanisms pose significant challenges to the precise identification and evaluation of the mental health effects of social participation. Third, the interweaving of traditional familial roles and modern individual development needs imbues participatory behaviors with complex social meanings and potential psychological costs. Notably, most classification frameworks derived from Western contexts (Guo et al., 2018 ; Amagasa, 2017; Baeriswyl & Oris, 2023 ) inadequately capture contributory activities within the family, such as intergenerational childcare and family caregiving, which are prevalent among older adults in China. As a result, the impact of such activities on depression and mental health among older Chinese adults is often underestimated or misunderstood. Motivated by these concerns, this study integrates the core principles of "Active Aging" (WHO, 2002) and "Productive Aging" (Morrow-Howell et al., 2001 ) to propose an innovative "Contributory-Developmental" analytical framework for understanding social participation among older adults in the Chinese context. The framework recognizes that the primary purposes of social participation vary—either contributing outwardly to others or focusing inwardly on personal growth—both of which are profoundly shaped by gender roles and the urban-rural structure. Accordingly, this study categorizes social participation into two main types. The first is contributory participation, which aligns with the productive aspects of aging and is further distinguished by the target of contribution: family contribution (e.g., intergenerational childcare) and societal contribution. The second is developmental participation, which focuses on inward-oriented personal growth and self-empowerment, and is categorized by the nature of the activity into learning and leisure types. To enhance the comprehensiveness of the model, drawing on Morrow-Howell et al.'s ( 2014 ) research on the determinants of participation, we also incorporate personal, social, economic, and physical environmental factors as potential influences on participation itself. Based on this dual logic of "outward contribution" and "inward development," this study constructs a refined analytical framework tailored to the sociocultural context of China. It not only moves beyond the limitations of existing studies that rely on aggregate activity counts or binary measurements but also deeply captures the lived experiences of older adults in China, where traditional family responsibilities intersect with modern aspirations for self-realization. This provides a more nuanced perspective for understanding the mental health effects of their social participation. Building on this integrated framework, and utilizing two-wave longitudinal data from the China Longitudinal Aging Social Survey (CLASS), this study aims to address the following questions: How do contributory and developmental social participation influence depressive symptoms among older adults? Furthermore, how do urban-rural and gender differences moderate these relationships, thereby shaping the "inequality landscape" of mental health benefits? By refining the logic of social participation and exploring the mechanisms specific to the Chinese context, this study seeks to uncover the complex pathways through which social participation affects depressive symptoms and mental health among older adults in China. It aims to provide a new analytical perspective for understanding mental health disparities among the older Chinese adults and offer empirical evidence to inform the development of targeted and inclusive policies for social participation among older adults. Methods Sample This study utilizes data from the 2020 and 2018 waves of the China Longitudinal Aging Social Survey (CLASS). CLASS is a nationwide, continuous, large-scale social survey project implemented by the China Survey and Data Center at Renmin University of China. The target respondents were individuals aged 60 and above. This study was determined to be exempt from ethics review because it involved the analysis of publicly available, de-identified secondary data. Our primary analyses are based on the 2020 wave, while the 2018 wave was used for supplementary robustness checks. For the main analytical sample from the 2020 wave, the original sample size was 11,398. After excluding 2,616 individuals who were not retired and removing cases with missing values on key variables, a final sample of 7,443 participants was retained for analysis. Descriptive statistics of this sample are shown in Table 1 . Measures Depressive symptoms Depressive symptoms were measured using a 9-item version of the CES-D scale from the CLASS survey, including six negatively and three positively worded items, each rated on a 3-point scale. Positively worded items were reverse-coded, and total scores ranged from 9 to 27, with higher scores indicating more severe depressive symptoms. The scale showed acceptable internal consistency (Cronbach’s α = 0.676). Contributory Participation Community Volunteering Community Volunteering was measured on the basis of older adults' participation in community environmental protection activities during the past year. Participation in such activities reflects the core spirit of volunteerism - giving time and energy to a good cause without financial compensation - and is one of the most common forms of public service. Question responses for frequency of participation were positively assigned using a 5-point Likert scale, with 0 = never, 1 = several times a year, 2 = at least once a month, 3 = at least once a week, and 4 = almost every day. Intergenerational domestic support Intergenerational domestic support was measured by the average frequency with which older adults assisted their children with household chores in the past year, with higher response assignment (1 = never, 5 = almost every day) scores indicating more frequent care. Intergenerational childcare Intergenerational childcare was assessed by the average frequency with which each adult child cared for a grandchild in the past year, with higher response assignment (1 = never, 5 = more than 8 hours per day) scores indicating more intensive caregiving. Reemployment after Retirement Reemployment after retirement was measured by how often the respondent engaged in paid work or income generating activities after retirement, with higher response assignment (1 = never, 5 = almost daily) scores indicating more frequent participation. Electoral Participation Electoral participation was assessed on the basis of self-reported participation in local council elections in the past three years, where 1 = don't know and did not participate, 2 = know but did not participate, and 3 = participated. Developmental Participation Learning activities Learning activities were measured by the frequency of participation in senior college or training programs in the past year, with responses assigned (0 = never, 4 = almost daily) Higher scores indicate more frequent participation. Leisure Activities Leisure activities among older adults are diverse. To further distinguish the differential impacts of various types of recreational activities on psychological well-being, entertainment activities were categorized into two types based on the level of participation: active leisure activities and passive leisure activities (Cho et al., 2018 ). Active leisure activities refer to those requiring physical, cognitive, technical, or social participation during participation, with the goals of entertainment, learning, or social interaction through active involvement. Active leisure was measured by the frequency of participation in three types of activities over the past year: instrumental activities (e.g., playing a musical instrument), board games or card games, and group dancing (e.g., public square dancing). Scores for each activity are assigned (0 = never, 4 = almost every day) Higher scores are associated with more frequent participation, and the scores for the three activities are summed to produce a total score of 0 to 12. Passive leisure activities mainly refer to leisure through receiving external information or pre-prepared entertainment content. In this study, passive leisure activities were assessed in terms of the frequency of the adults' use of traditional media, including watching television, listening to the radio, reading books or newspapers, and listening to traditional opera, with the same values assigned as above. Internet Participation Internet participation was measured based on how often older adults used the Internet in the past year, with responses assigned (1 = never, 5 = almost every day) Higher scores indicate more frequent use. Control variables Based on the theoretical framework described above, we incorporated control variables at the individual, household, and community levels. At the individual level, control variables included age, gender, education, subjective economic status, self-rated health and region of residence. At the family level, control variables included marital status, caregiving support from offspring, and financial support from children. At the community level, we included community community atmosphere, which was measured using a composite index based on respondents' satisfaction with eight dimensions: road conditions, fitness/activity facilities, public safety, environmental health, atmosphere of respect for older adults, competence of community council staff, street lighting, and accessibility. Each item was assessed using a five-point Likert scale. The scale showed good internal consistency (Cronbach's alpha = 0.862), indicating that it effectively reflects the overall quality of the community environment for older adults. Total scores ranged from 8 to 40, with higher scores indicating a better community environment. Statistical Analyses Ordinary Least Squares (OLS) regression models were used to estimate the associations between different types of social participation and depressive symptoms. Moderation models tested subgroup heterogeneity by gender and urban–rural residence, with demographic and socioeconomic characteristics included as controls. All analyses were conducted using Stata 17.0. Full model specifications, interaction terms, and robustness checks are provided in the Supplementary Materials. Table 1 Descriptive statistics(N = 7443) Variable Mean/ Percentage SD Min Max Depressive Symptoms 15.80 3.295 9 27 Learning activities 0.115 0.582 0 4 Passive Leisure Activities 3.079 1.537 0 4 Active Leisure Activities 1.823 2.661 0 12 Community Volunteering 0.309 0.762 0 4 Intergenerational domestic support 2.019 1.346 1 5 Intergenerational childcare 1.290 0.668 1 5 Internet Usage 2.083 1.721 1 5 Electoral Participation 2.099 0.832 1 3 Reemployment after Retirement 0.108 0.588 0 4 Urban area 55.41% - - - Age 71.85 6.698 60 98 Male 48.22% - - - Educational Attainment (in Years) 6.268 4.066 0 16 Subjective Economic Status 2.075 0.535 1 3 Self-Rated Health 3.369 0.908 1 5 Married 75.16% - - - Caregiving support from offspring 3.110 1.220 1 5 Child-provided financial support (Log-transformed) 6.466 2.289 0 10.13 Community atmosphere 30.42 4.661 8 40 Results Association between Social Participation types and Depressive Symptoms Ordinary Least Squares (OLS) regressions showed that within developmental participation, learning activities (β = -0.266, p < 0.01), active leisure activities (β = -0.039, p < 0.01), and internet usage (β = -0.218, p < 0.01) were significantly associated with fewer depressive symptoms, while passive leisure activities showed no significant association. Within Contributory participation, intergenerational childcare (β = -0.356, p < 0.01) and reemployment (β = -0.230, p < 0.01) were linked to fewer depressive symptoms, whereas intergenerational domestic support (β = 0.142, p < 0.01) was associated with more. Neither volunteering nor electoral participation showed significant effects (See Table 2 ). Robustness Checks To strengthen the credibility of the main results, we conducted two robustness checks. First, comparing separate OLS models (Table 2 ) with a full model including all nine activity types (Supplementary Table A1) showed that only learning, internet usage, and intergenerational childcare remained significant, while passive and active leisure effects disappeared. Second, lagged dependent variable (LDV) models controlling for baseline depressive symptoms in 2018 (Supplementary Tables A2–A3) largely corroborated our findings: internet usage, active leisure, intergenerational childcare, and reemployment continued to show protective effects, while intergenerational domestic support remained positively associated. The effects of learning were attenuated, suggesting sensitivity to model specification. Overall, these checks supported the validity of the baseline results and informed the subsequent heterogeneity analyses. Table 2 Gross Associations Between Each Social Participation Type and Depressive Symptoms Social Participation Types Model Activities Depression Constant Control variables R-squared Developmental Participation Model 1 Learning activities -0.266*** 19.475*** Controlled 0.134 (0.062) (0.570) Model 2 Passive Leisure Activities 0.003 19.377*** 0.131 (0.024) (0.572) Model 3 Active Leisure Activities -0.039*** 19.425*** 0.132 (0.014) (0.570) Model 4 Internet Usage -0.218*** 20.312*** 0.141 (0.024) (0.577) Contributory participation Model 5 Community Volunteering -0.018 19.404*** 0.131 (0.047) (0.573) Model 6 Intergenerational domestic support 0.142*** 18.910*** 0.134 (0.029) (0.578) Model 7 Intergenerational childcare -0.356*** 20.550*** 0.136 (0.056) (0.598) Model 8 Reemployment after Retirement -0.230*** 19.557*** 0.133 (0.061) (0.572) Model 9 Electoral Participation 0.055 19.256*** 0.132 (0.044) (0.579) Note: N = 7,443.The table present non-standardized coefficients, with standard errors in parentheses. All models control for age, gender, education, subjective economic status, self-rated health, region of residence. marital status, caregiving support from offspring financial support from children and community atmosphere. *** p < 0.01, ** p < 0.05, * p < 0.1 Moderating Role of Urban-Rural Residence This study examined how urban–rural residence moderated the relationship between social participation and depressive symptoms among older adults, by including interaction terms (Activity × Urban) in the regression models (Table 3 ). For developmental participation, significant positive interactions were observed for Active Leisure × Urban (β = 0.109, p < 0.01) and Internet Usage × Urban (β = 0.139, p < 0.01), indicating that their protective effects against depressive symptoms were weaker for urban older adults than for rural ones. In contrast, interactions for Learning Activities × Urban and Passive Leisure × Urban were not significant. For Contributory participation, Electoral Participation × Urban (β = 0.676, p < 0.01) was positive, suggesting that electoral participation reduced depressive symptoms among rural older adults but not their urban counterparts. Community Volunteering × Urban (β = -0.294, p < 0.01) showed the opposite pattern: it was linked to higher depressive symptoms in rural areas but lower in urban areas. Intergenerational Domestic Support × Urban (β = -0.253, p < 0.01) also indicated that its positive association with depressive symptoms, strong in rural settings, was much weaker among urban older adults. Interactions for Intergenerational Childcare × Urban and Reemployment × Urban were not significant. Table 3 Urban-Rural Differences in the Impact of Social Participation on the Depressive Symptoms among Retired Older Adults Model VARIABLES Depression Standard errors Control variables R-squared Model 10 Learning activities -0.057 0.143 Controlled 0.134 Learning activities \(\times\) Urban -0.256 0.158 Model 11 Passive Leisure Activities -0.007 0.032 0.131 Passive Leisure Activities \(\times\) Urban 0.022 0.047 Model 12 Active Leisure Activities -0.113*** 0.024 0.134 Active Leisure Activities \(\times\) Urban 0.109*** 0.029 Model 13 Internet Usage -0.316*** 0.041 0.142 Internet Usage \(\times\) Urban 0.139*** 0.047 Model 14 Community Volunteering 0.176** 0.081 0.132 Community Volunteering \(\times\) Urban -0.294*** 0.099 Model 15 Intergenerational domestic support 0.285*** 0.042 0.137 Intergenerational domestic support \(\times\) Urban -0.253*** 0.053 Model 16 Intergenerational childcare -0.468*** 0.091 0.136 Intergenerational childcare \(\times\) Urban 0.174 0.112 Model 17 Reemployment after Retirement -0.230*** 0.087 0.133 Reemployment after Retirement \(\times\) Urban 0.000 0.121 Model 18 Electoral Participation -0.321*** 0.065 0.133 Electoral Participation \(\times\) Urban 0.676*** 0.086 Note: N = 7,443.The table present non-standardized coefficients, with standard errors in parentheses. All models control for age, gender, education, subjective economic status, self-rated health, region of residence. marital status, caregiving support from offspring financial support from children and community atmosphere. *** p < 0.01, ** p < 0.05, * p < 0.1 Moderating Role of Gender Further analyses examined gender differences in the association between social participation and depressive symptoms among older adults using interaction terms (Activity × Female) (Table 4 ). For developmental participation, Learning × Female (β = -0.337, p < 0.01) was significant, indicating a stronger protective effect of learning activities for female older adults than for male older adults. Other activities showed no significant gender interactions. For contributory participation, Reemployment × Female (β = 0.281, p < 0.05) was significant, suggesting that while reemployment reduced depressive symptoms among male older adults (β = − 0.319, p < 0.01), the effect was reversed among female older adults. Interactions for volunteering, domestic support, childcare, and electoral participation were not significant. To further contextualize the moderation effects, we explored how gender and urban–rural residence were associated with differences in the frequency of contributory and developmental participation (Supplementary Table A4). The results reveal distinct participation profiles across demographic groups. Urban older adults exhibit a significant advantage in self-fulfilling developmental activities (e.g., learning, leisure, and internet use). In contrast, their rural counterparts are more predominantly engaged in labor-intensive contributory roles, such as intergenerational domestic support and reemployment. Furthermore, participation patterns are strikingly gendered: while women report higher involvement in active leisure and domestic support, men maintain a stronger presence in formal public spheres, including reemployment and electoral participation. These divergent patterns provide an empirical basis for the uneven distribution of psychological benefits observed in our moderation analysis. Table 4 Gender Differences in the Impact of Social Participations on the Depressive Symptoms among Retired Older Adults Model VARIABLES Depression Standard errors Control variables R-squared Model 19 Learning activities -0.076 0.093 Controlled 0.134 Learning activities \(\times\) Female -0.337*** 0.123 Model 20 Passive Leisure Activities 0.019 0.034 0.132 Passive Leisure Activities \(\times\) Female -0.031 0.046 Model 21 Active Leisure Activities -0.017 0.022 0.132 Active Leisure Activities \(\times\) Female -0.036 0.027 Model 22 Internet Usage -0.209*** 0.032 0.136 Internet Usage \(\times\) Female -0.018 0.041 Model 23 Community Volunteering -0.043 0.068 0.131 Community Volunteering \(\times\) Female 0.047 0.094 Model 24 Intergenerational domestic support 0.142*** 0.041 0.133 Intergenerational domestic support \(\times\) Female -0.000 0.053 Model 25 Intergenerational childcare -0.368*** 0.078 0.134 Intergenerational childcare \(\times\) Female 0.024 0.107 Model 26 Reemployment after Retirement -0.319*** 0.074 0.141 Reemployment after Retirement \(\times\) Female 0.281** 0.131 Model 27 Electoral Participation 0.108* 0.063 0.134 Electoral Participation \(\times\) Female -0.101 0.086 Note: N = 7,443.The table present non-standardized coefficients, with standard errors in parentheses. All models control for age, gender, education, subjective economic status, self-rated health, region of residence. marital status, caregiving support from offspring financial support from children and community atmosphere. *** p < 0.01, ** p < 0.05, * p < 0.1 Discussion Our research found that while most forms of developmental and contributory social participation had protective effect against depressive symptoms among older adults, these associations were not universally consistent. Instead, the impact of social participation on older adults’ depressive symptoms was to a large extent contingent upon whether they resided in urban or rural settings, and the effects of some social participation also varied by gender. Association between Social Participation Types and Depressive Symptoms This study categorizes older adults’ social participation into two main types: developmental and contributory. In the realm of developmental participation, we find that learning, engaging in active leisure, and using the internet are all associated with lower levels of depressive symptoms among older adults. These findings are consistent with previous studies (Schoultz et al., 2020 ; Yu et al., 2024 ; Cotten et al., 2014 ). Developmental activities tend to reduce depressive symptoms by providing cognitive stimulation, fostering a sense of self-efficacy, and promoting social interaction and connectedness (Schoultz et al., 2020 ; Yu et al., 2024 ; Chen & Schulz, 2016 ; Yu et al., 2022 ; Lin et al., 2013 ). In contrast to the generally consistent patterns found in developmental participation, contributory social participation shows a more complex relationship with older adults’ depressive symptoms. Contributory participations alleviate depressive symptoms primarily through generating social value, fulfilling social roles, and enabling reciprocity. Our findings indicate that reemployment after retirement is associated with lower levels of depressive symptoms, supporting continuity theory and the productive aging perspective, in which maintaining social roles and identity helps enhance psychological well-being (Kim & Feldman, 2000 ; Atchley, 1989 ). However, this result contrasts with findings by Xie et al. ( 2021 ). This discrepancy may reflect a bidirectional relationship between retirement and depressive symptoms—those with fewer symptoms may be more inclined to re-enter the workforce. Our study also finds that intergenerational child care was associated with a reduction in depressive symptoms, which differs from Kelley et al.'s ( 2021 ) findings and may be due to cross-cultural differences. Hughes et al. ( 2007 ) also noted that the poorer health of grandparent caregivers was more likely to be due to pre-existing disadvantages than to caregiving per se. Moderate and voluntary grandparental caregiving may result in emotional rewards, a sense of purpose, and the fulfillment of generative needs (Erikson, 1963 ), leading to lower depressive symptoms. However, not all contributory participation yields favorable outcomes. Our findings show that intergenerational domestic support (e.g., daily chores like cooking and laundry) is significantly associated with higher depressive symptoms levels among older adults. This underscores the importance of the nature and intensity of contributory behavior (Chen & Liu, 2012 ). Unlike grandchild caregiving, which often provides emotional returns, household labor is repetitive, lacks intrinsic motivation and emotional feedback, and can result in resource depletion (Hobfoll, 1989 ) and autonomy frustration (Ryan & Deci, 2000 ), particularly when perceived as obligatory. These effects may undermine psychological well-being and stand in contrast to the social recognition and psychological gains often associated with caregiving (Thang et al., 2011 ). Moreover, our study finds no significant association between depressive symptoms and participation in community volunteering, electoral activities, or passive leisure (e.g., watching TV for long hours). Passive leisure activities, due to their lack of cognitive, physical, or social interaction, may offer limited or even adverse effects on mental health, aligning with prior findings (Cho et al., 2018 ). Although some studies have found positive effects of volunteering (Morrow-Howell, 2003; Filges et al., 2020 ), our results reveal no significant impact. Likewise, political participation may be negatively associated with mental health and moderated by factors such as regional political competition (Lin & Yan, 2022 ). We speculate that the insignificant overall effects of community volunteering and political participation may stem from substantial heterogeneity in individual responses to these activities, a point we further explore in subgroup analyses. Heterogeneity by Urban-Rural Residence Our results reveal that certain types of contributory participation exert differential effects on depressive symptoms across urban and rural contexts. Notably, intergenerational domestic support is positively associated with depressive symptoms for both urban and rural older adults, but the adverse effect is significantly stronger in rural areas. This may be attributed to stronger traditional family obligations and social norms in rural regions, where older adults face greater informal pressure to undertake household duties. Moreover, rural older adults may perceive such support more as reciprocal intergenerational exchange than as altruistic emotional support; the lack of reciprocation could thus negatively impact mental well-being (Chen & Liu, 2012 ; Xu & Chi, 2011 ). In addition, the effect of community volunteering shows an opposite pattern across urban and rural areas: it is associated with lower depressive symptoms levels among urban older adults, but higher depressive symptoms among rural older adults. This suggests a fundamental difference in the nature and experience of volunteering across settings. Urban volunteering is often interest-driven, voluntary, and better organized with formal recognition mechanisms, contributing to a sense of achievement and social inclusion (Morrow-Howell et al., 2003 ). In contrast, rural volunteering may rely more on informal mobilization based on interpersonal ties or village obligations (Wei & Xu, 2023 ), driven by communal responsibility and social expectations (Pearce et al., 2023 ). These activities, though fostering social exchange, may lack institutional support or emotional rewards, leaving rural older adults feeling burdened and unfulfilled, particularly when their efforts are not reciprocated. Electoral participation presents another striking urban-rural contrast. It is negatively associated with depressive symptoms in rural areas but linked to higher depressive symptoms in urban settings. This may reflect differences in the structure and experience of elections. Rural elections often involve grassroots-level engagement and familiar interpersonal contexts, fostering a sense of agency and belonging (Liu et al., 2024 ; Tang et al., 2020 ), and providing channels for expressing local demands (Brandt & Turner, 2007 ). Urban elections, by contrast, tend to involve more complex processes and higher-level institutions, with older adults’ participation often limited to voting, lacking deeper engagement or tangible outcomes (Gui et al., 2016). Moreover, the complex urban socio-political landscape may elicit feelings of helplessness or anxiety, adversely affecting mental health (Trope et al., 2007 ). Meanwhile, some activities—including learning, passive leisure, post-retirement employment, and grandchild caregiving—do not show significant urban-rural differences in their association with depressive symptoms. This suggests that the underlying mechanisms linking these activities to psychological outcomes may be more universally applicable across contexts. When these findings are contextualized within actual participation patterns, our results indicate that urban older adults are more likely to engage in learning, leisure, internet use, volunteering, and grandchild caregiving, consistent with more abundant resource availability in urban settings. Rural older adults, in contrast, participate more frequently in household labor, post-retirement employment, and political activities, which reflect the social structure, economic needs, and local governance of rural communities. These differences not only stem from contextual constraints but may also shape the mental health impacts of various forms of participation. Special attention should be given to the potentially “double disadvantaged” rural older adults, who both participate less in mentally beneficial developmental activities and bear a heavier burden of negatively associated contributory activities. Heterogeneity by Gender Gender-based heterogeneity analysis indicates that most forms of social participation do not show significant gender differences in their impact on depressive symptoms. However, a few activities do exhibit gender-moderated outcomes. Specifically, learning and passive leisure activities (e.g., watching TV or listening to the radio) are associated with lower levels of depressive symptoms among women, while no significant effect is observed for men. This aligns with earlier findings (Takagi et al., 2013 ; Wang et al., 2022 ). Gender role theory (Eagly, 1987) posits that men are traditionally expected to fulfill the breadwinner role, and passive leisure may be viewed as "meaningless" by them, whereas women, more commonly positioned in caregiving roles within the home, may find passive leisure more acceptable and relaxing. Furthermore, women tend to derive psychological satisfaction through emotional resonance, and emotionally engaging content such as television dramas may align better with their preferences (Schulte-Rüther et al., 2008 ). Women also benefit more from learning activities in terms of mental health, consistent with previous studies (Shi et al., 2022 ), possibly due to the greater emotional support and social interaction embedded in learning environments for older women. Importantly, reemployment after retirement has opposite psychological effects by gender. Among women, it is associated with higher depressive symptoms, whereas among men, it is linked to lower depressive symptoms. This supports findings by Weber et al. ( 2019 ) that older women face more emotional challenges post-retirement. Gender differences in role expectations and motivations for re-employment may explain this pattern. Men are more concerned with social status and may re-enter the workforce to maintain their identity (Konrad et al., 2000 ; Eddleston et al., 2006 ). Women, on the other hand, may be driven more by economic pressures or caregiving needs, which can add stress and contribute to psychological distress (Weber et al., 2019 ). Integrating our findings on gendered participation patterns, we uncover a troubling coupling between these patterns and the mental health returns of the activities. We find that older men appear to gravitate towards types of participation that are demonstrably more beneficial to their own mental health (reemployment). In contrast, older women face a double jeopardy: they not only shoulder a greater burden of activities associated with higher depressive symptoms (intergenerational domestic support), but they also exhibit lower levels of participation in the very activities most beneficial to them (learning activities). This finding starkly reveals how gender norms, mediated through social participation, continue to produce and reproduce gender inequality in mental health in later life. Strengths and Limitations To our knowledge, this study is the first to classify older adults’ social participation into developmental and contributory categories. This innovative framework aligns with the concepts of active aging and productive aging, providing a more comprehensive representation of older adults’ social participation. By incorporating two broad domains encompassing nine types of activities, the study captures the major forms of social participation among older adults in the digital era. The findings suggest that both the types of social participation and individual characteristics jointly shape their effects on psychological well-being. Nevertheless, the study has limitations. Our measure was restricted to nine activities, which may not capture the full spectrum of participation. Although robustness checks with lagged variables were conducted, the causal direction between social participation and psychological well-being remains uncertain; longitudinal data would provide stronger evidence. Moreover, data were drawn solely from China, which may limit generalizability; cross-national studies are recommended to assess cultural variation. Conclusion This study develops a framework that distinguishes between developmental and contributory forms of social participation, and demonstrates that their effects on older adults’ mental health are heterogeneous across groups. The results highlight pronounced urban–rural and gender differences: contributory and developmental participation do not have uniform effects but vary depending on social context and individual characteristics. These findings underscore the need for social policies and interventions that are sensitive to such heterogeneity, and that promote more targeted and inclusive approaches to active ageing and mental health support. Declarations Ethics approval and consent to participate The data used in this study were drawn from the 2018 and 2020 waves of the China Longitudinal Aging Social Survey (CLASS). The CLASS survey was approved by the relevant institutional ethics committee, and written informed consent was obtained from all participants prior to data collection. The present study is a secondary analysis of anonymized survey data and did not require additional ethical approval. Consent for publication Not applicable. No individual person’s data are presented in this manuscript. Availability of data and materials Data from the 2018 and 2020 waves of the China Longitudinal Aging Social Survey (CLASS) are available by applying to the China Survey and Data Center at Renmin University of China (http://class.ruc.edu.cn/). Competing interests The authors declare that they have no competing interests. Funding This work was supported by the Major Research Project of Philosophy and Social Sciences of the Ministry of Education of the People’s Republic of China, “Population Opportunities, Challenges, and Policy Research in the Construction of Chinese-style Modernization” (Grant No. 23JZD028). The funding body had no role in the design of the study, data analysis, interpretation of the findings, or in writing the manuscript. Authors’ contributions Yao Yu： Writing – original draft, Methodology, Data curation, Investigation, Formal analysis, Visualization, Conceptualization. Jing MA: Supervision, Writing – original draft. Wei Guo: Project administration. All authors read and approved the final manuscript. References Amagasa, S., Fukushima, N., Kikuchi, H., Oka, K., Takamiya, T., Odagiri, Y., & Inoue, S. (2017). Types of social participation and psychological distress in Japanese older adults: A five-year cohort study. PloS one , 12 (4), e0175392. Atchley, R. C. (1989). A continuity theory of normal aging. The gerontologist , 29 (2), 183-190. Baeriswyl, M., & Oris, M. (2023). Social participation and life satisfaction among older adults: Diversity of practices and social inequality in Switzerland. Ageing & Society , 43 (6), 1259-1283. Bisschop, M. I., Kriegsman, D. M., Deeg, D. J., Beekman, A. T., & Van Tilburg, W. (2004). The longitudinal relation between chronic diseases and depressive symptoms in older persons in the community: the Longitudinal Aging Study Amsterdam. Journal of clinical epidemiology , 57 (2), 187-194. Brandt, L., & Turner, M. A. (2007). The usefulness of imperfect elections: The case of village elections in rural China. Economics & Politics , 19 (3), 453-480. Chen, F., & Liu, G. (2012). The health implications of grandparents caring for grandchildren in China. Journals of Gerontology Series B: Psychological Sciences and Social Sciences , 67 (1), 99-112. Chen, Y. R. R., & Schulz, P. J. (2016). The effect of information communication technology interventions on reducing social isolation in the elderly: a systematic review. Journal of medical Internet research , 18 (1), e4596. Chiao, C., Weng, L. J., & Botticello, A. L. (2011). Social participation reduces depressive symptoms among older adults: an 18-year longitudinal analysis in Taiwan. BMC public health , 11 , 1-9. Cho, D., Post, J., & Kim, S. K. (2018). Comparison of passive and active leisure activities and life satisfaction with aging. Geriatrics & gerontology international , 18 (3), 380-386. Cotten, S. R., Ford, G., Ford, S., & Hale, T. M. (2014). Internet use and depression among retired older adults in the United States: A longitudinal analysis. Journals of Gerontology Series B: Psychological Sciences and Social Sciences , 69 (5), 763-771. Croezen, S., Avendano, M., Burdorf, A., & Van Lenthe, F. J. (2015). Social participation and depressive symptoms in old age: a fixed-effects analysis in 10 European countries. American journal of epidemiology , 182 (2), 168-176. Eagly, A. H. (2013). Sex differences in social behavior: A social-role interpretation. Psychology Press. (pp. 458-476) Eddleston, K. A., Veiga, J. F., & Powell, G. N. (2006). Explaining sex differences in managerial career satisfier preferences: The role of gender self-schema. Journal of Applied Psychology , 91 (2), 437. Erikson, E. H. (1963). Childhood and society (Vol. 445). Norton. Filges, T., Siren, A., Fridberg, T., & Nielsen, B. C. (2020). Voluntary work for the physical and mental health of older volunteers: A systematic review. Campbell Systematic Reviews , 16 (4), e1124. Flynn, M. (2010). Who would delay retirement? Typologies of older workers. Personnel review , 39 (3), 308-324 Glass, T. A., De Leon, C. F. M., Bassuk, S. S., & Berkman, L. F. (2006). Social engagement and depressive symptoms in late life: longitudinal findings. Journal of aging and health , 18 (4), 604-628. Gui, Y., Cheng, J. Y., & Ma, W. (2006). Cultivation of grass-roots democracy: a study of direct elections of residents committees in Shanghai. China Information , 20 (1), 7-31. Guo, Q., Bai, X., & Feng, N. (2018). Social participation and depressive symptoms among Chinese older adults: A study on rural–urban differences. Journal of Affective Disorders , 239 , 124-130. Hobfoll, S. E. (1989). Conservation of resources: a new attempt at conceptualizing stress. American psychologist , 44 (3), 513. Huang, C. Q., Dong, B. R., Lu, Z. C., Yue, J. R., & Liu, Q. X. (2010). Chronic diseases and risk for depressive symptoms in old age: a meta-analysis of published literature. Ageing research reviews , 9 (2), 131-141. Hughes, M. E., Waite, L. J., LaPierre, T. A., & Luo, Y. (2007). All in the family: The impact of caring for grandchildren on grandparents' health. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences , 62 (2), S108-S119. Kelley, S. J., Whitley, D. M., Escarra, S. R., Zheng, R., Horne, E. M., & Warren, G. L. (2021). The mental health well-being of grandparents raising grandchildren: A systematic review and meta-analysis. Marriage & Family Review , 57 (4), 329-345. Kim, S., & Feldman, D. C. (2000). Working in retirement: The antecedents of bridge employment and its consequences for quality of life in retirement. Academy of management Journal , 43 (6), 1195-1210. Konrad, A. M., Ritchie Jr, J. E., Lieb, P., & Corrigall, E. (2000). Sex differences and similarities in job attribute preferences: a meta-analysis. Psychological bulletin , 126 (4), 593. Lin, Y. C., & Yan, H. T. (2022). Association between political group participation and depressive symptoms among older adults: an 11-year longitudinal study in Taiwan. Journal of Public Health , 44 (4), 778-786. Lin, Y. C., Liang, J. C., Yang, C. J., & Tsai, C. C. (2013). Exploring middle-aged and older adults’ sources of Internet self-efficacy: A case study. Computers in Human Behavior , 29 (6), 2733-2743. Liu, D., Zhang, B., & Guo, J. (2024). Triple digital divide and depressive symptoms among middle-aged and older Chinese adults: a disparity analysis. General Psychiatry , 37 (4), e101562. Liu, W., Li, J. J. T., & Chen, J. (2024). Voting participation in grassroots elections and rural residents’ subjective well‐being in China: The mediation roles of social class and fairness. Analyses of Social Issues and Public Policy , 24 (3), 1189-1207. Liu, Z. W., Yu, Y., Fang, L., Hu, M., Zhou, L., & Xiao, S. Y. (2019). Willingness to receive institutional and community-based eldercare among the rural elderly in China. PLoS One , 14 (11), e0225314. Morrow-Howell, N., Hinterlong, J., & Sherraden, M. (Eds.). (2001). Productive aging: Concepts and challenges . JHU Press. Morrow-Howell, N., Hinterlong, J., Rozario, P. A., & Tang, F. (2003). Effects of volunteering on the well-being of older adults. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences , 58 (3), S137-S145. Morrow-Howell, N., Putnam, M., Lee, Y. S., Greenfield, J. C., Inoue, M., & Chen, H. (2014). An investigation of activity profiles of older adults. Journals of Gerontology Series B: Psychological Sciences and Social Sciences , 69 (5), 809-821. Pearce, S., Kristjansson, E., Lemyre, L., & Takacs, T. (2023). Understanding the volunteer motivations, barriers and experiences of urban and rural youth: a mixed-methods analysis. Voluntary Sector Review , 14 (2), 268-292. Piszczek, M. M., & Pimputkar, A. S. (2021). Flexible schedules across working lives: Age-specific effects on well-being and work. Journal of Applied Psychology , 106 (12), 1907. Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American psychologist , 55 (1), 68. Schoultz, M., Öhman, J., & Quennerstedt, M. (2020). A review of research on the relationship between learning and health for older adults. International Journal of Lifelong Education , 39 (5-6), 528-544. Schulte-Rüther, M., Markowitsch, H. J., Shah, N. J., Fink, G. R., & Piefke, M. (2008). Gender differences in brain networks supporting empathy. Neuroimage , 42 (1), 393-403. Shi, X., Li, Y., Sun, L., Yu, Y., & Zhou, S. (2022). Gender differences in the subjective well-being of older adult learners in China. Frontiers in Psychology , 13 , 1043420. Takagi, D., Kondo, K., & Kawachi, I. (2013). Social participation and mental health: moderating effects of gender, social role and rurality. BMC public health , 13 , 1-8. Tang, L., Luo, X., Yu, W., & Huang, Y. (2020). The effect of political participation and village support on farmers happiness. Journal of Chinese Political Science , 25 , 639-66 Thang, L. L., Mehta, K., Usui, T., & Tsuruwaka, M. (2011). Being a good grandparent: Roles and expectations in intergenerational relationships in Japan and Singapore. Marriage & Family Review , 47 (8), 548-570. Tiong, W. W., Yap, P., Huat Koh, G. C., Phoon Fong, N., & Luo, N. (2013). Prevalence and risk factors of depressive symptoms in the elderly nursing home residents in Singapore. Aging & mental health , 17 (6), 724-731. Trope, Y., Liberman, N., & Wakslak, C. (2007). Construal levels and psychological distance: Effects on representation, prediction, evaluation, and behavior. Journal of consumer psychology , 17 (2), 83-95. Wang, J., Xu, J., Nie, Y., Pan, P., Zhang, X., Li, Y., ... & Shah, S. (2022). Effects of social participation and its diversity, frequency, and type on depressive symptoms in middle-aged and older persons: evidence from China. Frontiers in Psychiatry , 13 , 825460. Weber, J., de Lange, A., & Müller, A. (2019). Gender differences in paid employment after retirement: Psychosocial working conditions and well-being. Zeitschrift für Gerontologie und Geriatrie, 52(Suppl 1), 32-39. Wei, X. J., and M. Y. Xu. 2023. Research on the Intrinsic Incubation of Rural Volunteer Service Organizations against the Background of Rural Revitalization. The Journal of Jiangsu Administration Institute 5: 80–7. World Health Organization. (‎2002)‎. Active Ageing: a policy framework. World Health Organization. https://iris.who.int/handle/10665/67215 Xie, L., Yao, Y. D., Tang, L. L., Zhang, S., Yang, H. L., Zhang, S. Q., ... & Li, Z. Y. (2021). Effect of working after retirement on the mental health of older people: evidence from China. Frontiers in Psychiatry , 12 , 731378. Xu, L., & Chi, I. (2011). Life satisfaction among rural Chinese grandparents: the roles of intergenerational family relationship and support exchange with grandchildren. International Journal of Social Welfare , 20 , S148-S159. Yu, J., Chiu, Y. L., Guu, S. M., & Wang, J. N. (2024). The association between leisure activity and mental health in the older adults in China: amazing Guangchangwu. Frontiers in Public Health , 11 , 1291809. Yu, X., Mu, A., Wu, X., & Zhou, L. (2022). Impact of internet use on cognitive decline in middle-aged and older adults in China: longitudinal observational study. Journal of Medical Internet Research , 24 (1), e25760. Zhao, L., & Wu, L. (2022). The association between social participation and loneliness of the Chinese older adults over time—the mediating effect of social support. International Journal of Environmental Research and Public Health , 19 (2), 815 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9011244","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":624481940,"identity":"5134c996-e72e-445a-a590-0c11d3372661","order_by":0,"name":"Yao Yu","email":"","orcid":"","institution":"Najing University","correspondingAuthor":false,"prefix":"","firstName":"Yao","middleName":"","lastName":"Yu","suffix":""},{"id":624481946,"identity":"8872c812-b7e1-4214-ac52-66955d258203","order_by":1,"name":"Jing Ma","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYHCChAMMDDZAmrERyGADiRgQoyUNpKWBaC0gcBhMHoDy8GvRbT/w8HDBr/P2uu2HGw4w7uBLbGBv3ibBUHMHpxazMwkJh2f23U7cdiYRqOUMW2IDz7EyCYZjz3BrOQDUwttzO8HsAEhLG1CLRI6ZBGPDYdxazj8AaTlnb3b+IVSL/BsCWm4AbeH5cYBx2w24LTyEtIBsaUhO3HYDaEtiG5txG09asUXCMXwOy0n+zPPHDuiw9IcPPrYdk+1nP7zxxoca3FoYGHgSGBjboOwEhmOQyEzAo4GBgf0AA8MfOK8Gr9pRMApGwSgYmQAAxiliPhga6KoAAAAASUVORK5CYII=","orcid":"","institution":"Najing University","correspondingAuthor":true,"prefix":"","firstName":"Jing","middleName":"","lastName":"Ma","suffix":""},{"id":624481950,"identity":"1b957992-aa88-4845-b64f-2b44d1232611","order_by":2,"name":"Wei Guo","email":"","orcid":"","institution":"Najing University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2026-03-02 14:23:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9011244/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9011244/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107168664,"identity":"14bcf9cd-4f36-4372-8bfa-865455c0b912","added_by":"auto","created_at":"2026-04-17 14:26:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":63021,"visible":true,"origin":"","legend":"\u003cp\u003eResearch framework\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9011244/v1/899449b30c4bbe4dc14662e4.png"},{"id":107168803,"identity":"e990da4b-5559-4d94-b309-468d3fc8d92c","added_by":"auto","created_at":"2026-04-17 14:27:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":739003,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9011244/v1/55b945c2-2454-47a5-ae4a-57b70e95d239.pdf"},{"id":107168689,"identity":"397c232c-eb50-482e-9869-9f388a6d2186","added_by":"auto","created_at":"2026-04-17 14:26:54","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":25689,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-9011244/v1/45ca73aee74d1b24b5d48585.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contributory and Developmental Social Participation and Depressive Symptoms Among Older Adults in China: Urban–Rural and Gender Disparities *","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn the process of actively addressing population aging, promoting the health of older adults has emerged as a pivotal imperative. Although advances in healthcare have significantly improved the physical health of older adults, their mental health issues\u0026mdash;particularly depressive symptoms\u0026mdash;have yet to receive commensurate attention. In practice, multiple factors in real life, such as information isolation caused by the digital divide (Cotten et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), chronic burdens from long-term illnesses (Huang et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Bisschop et al., 2014), and anxieties related to eldercare (Liu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tiong et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), significantly exacerbate the risk of depression among older adults, thereby constituting a core challenge in enhancing their mental health and well-being.\u003c/p\u003e \u003cp\u003eFocusing on the issue of reducing depression levels among the older adults, existing research has explored various perspectives, including psychosocial factors, behavioral interventions, and environmental support. Most empirical analyses indicate the positive role of social participation (Glass et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Chiao et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Croezen et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Zhao \u0026amp; Wu, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, within the unique sociocultural structure and institutional context of China, this relationship is far from a simple linear facilitation; instead, it exhibits profound tensions and heterogeneity. More importantly, a significant limitation in much of the current research is the tendency to oversimplify social participation into binary variables (participation versus non-participation) (Baeriswyl \u0026amp; Oris, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) or the quantity of participatory activities (Guo et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), thereby somewhat neglecting the inherent typological differences and motivational distinctions within participatory behaviors. Such simplifications fail to adequately address the complexity of social participation patterns among older adults in China. Specifically, first, China\u0026rsquo;s institutional environment and social structure jointly shape the unique and diverse landscape of social participation among older adults. On one hand, China\u0026rsquo;s flexible employment policies and delayed retirement reforms have contributed to the differentiation of life trajectories in later years (Flynn, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Piszczek \u0026amp; Pimputkar, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). On the other hand, the urban-rural dual structure systematically creates disparities in participation opportunities and resource constraints. Within this context, the types of social participation accessible to different subgroups of older adults in China are highly heterogeneous, with significant variations in their underlying motivations, frequencies, and objectives. These complex differences underscore the necessity of investigating how different types of social participation differentially impact depression among older adults. Second, although some studies have recognized the importance of distinguishing between types of social participation, significant discrepancies persist in existing classification systems and explanatory mechanisms. In terms of classification, existing research employs a variety of approaches, ranging from specific activity types (such as paid work, political activities, and volunteering) (Guo et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) to abstract participation patterns (e.g., high, medium, and low participation; economically active types) (Morrow-Howell et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, the lack of a unified theoretical framework has resulted in fragmented classification schemes, severely hindering dialogue and comparability across studies. Mechanistically, explanatory pathways diverge between the \"opportunity provision theory\" and the \"psychological compensation theory.\" The former emphasizes the structural constraints imposed by unequal access to opportunities on mental health (Baeriswyl \u0026amp; Oris, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), while the latter focuses on the differential psychological compensatory effects of various activity types (Guo et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These inconsistencies in measurement, classification, and mechanisms pose significant challenges to the precise identification and evaluation of the mental health effects of social participation. Third, the interweaving of traditional familial roles and modern individual development needs imbues participatory behaviors with complex social meanings and potential psychological costs. Notably, most classification frameworks derived from Western contexts (Guo et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Amagasa, 2017; Baeriswyl \u0026amp; Oris, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) inadequately capture contributory activities within the family, such as intergenerational childcare and family caregiving, which are prevalent among older adults in China. As a result, the impact of such activities on depression and mental health among older Chinese adults is often underestimated or misunderstood.\u003c/p\u003e \u003cp\u003eMotivated by these concerns, this study integrates the core principles of \"Active Aging\" (WHO, 2002) and \"Productive Aging\" (Morrow-Howell et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) to propose an innovative \"Contributory-Developmental\" analytical framework for understanding social participation among older adults in the Chinese context. The framework recognizes that the primary purposes of social participation vary\u0026mdash;either contributing outwardly to others or focusing inwardly on personal growth\u0026mdash;both of which are profoundly shaped by gender roles and the urban-rural structure. Accordingly, this study categorizes social participation into two main types. The first is contributory participation, which aligns with the productive aspects of aging and is further distinguished by the target of contribution: family contribution (e.g., intergenerational childcare) and societal contribution. The second is developmental participation, which focuses on inward-oriented personal growth and self-empowerment, and is categorized by the nature of the activity into learning and leisure types. To enhance the comprehensiveness of the model, drawing on Morrow-Howell et al.'s (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) research on the determinants of participation, we also incorporate personal, social, economic, and physical environmental factors as potential influences on participation itself. Based on this dual logic of \"outward contribution\" and \"inward development,\" this study constructs a refined analytical framework tailored to the sociocultural context of China. It not only moves beyond the limitations of existing studies that rely on aggregate activity counts or binary measurements but also deeply captures the lived experiences of older adults in China, where traditional family responsibilities intersect with modern aspirations for self-realization. This provides a more nuanced perspective for understanding the mental health effects of their social participation.\u003c/p\u003e \u003cp\u003eBuilding on this integrated framework, and utilizing two-wave longitudinal data from the China Longitudinal Aging Social Survey (CLASS), this study aims to address the following questions: How do contributory and developmental social participation influence depressive symptoms among older adults? Furthermore, how do urban-rural and gender differences moderate these relationships, thereby shaping the \"inequality landscape\" of mental health benefits? By refining the logic of social participation and exploring the mechanisms specific to the Chinese context, this study seeks to uncover the complex pathways through which social participation affects depressive symptoms and mental health among older adults in China. It aims to provide a new analytical perspective for understanding mental health disparities among the older Chinese adults and offer empirical evidence to inform the development of targeted and inclusive policies for social participation among older adults.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eSample\u003c/p\u003e \u003cp\u003eThis study utilizes data from the 2020 and 2018 waves of the China Longitudinal Aging Social Survey (CLASS). CLASS is a nationwide, continuous, large-scale social survey project implemented by the China Survey and Data Center at Renmin University of China. The target respondents were individuals aged 60 and above. This study was determined to be exempt from ethics review because it involved the analysis of publicly available, de-identified secondary data. Our primary analyses are based on the 2020 wave, while the 2018 wave was used for supplementary robustness checks. For the main analytical sample from the 2020 wave, the original sample size was 11,398. After excluding 2,616 individuals who were not retired and removing cases with missing values on key variables, a final sample of 7,443 participants was retained for analysis. Descriptive statistics of this sample are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eMeasures\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDepressive symptoms\u003c/h2\u003e \u003cp\u003eDepressive symptoms were measured using a 9-item version of the CES-D scale from the CLASS survey, including six negatively and three positively worded items, each rated on a 3-point scale. Positively worded items were reverse-coded, and total scores ranged from 9 to 27, with higher scores indicating more severe depressive symptoms. The scale showed acceptable internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.676).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eContributory Participation\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCommunity Volunteering\u003c/h2\u003e \u003cp\u003eCommunity Volunteering was measured on the basis of older adults' participation in community environmental protection activities during the past year. Participation in such activities reflects the core spirit of volunteerism - giving time and energy to a good cause without financial compensation - and is one of the most common forms of public service. Question responses for frequency of participation were positively assigned using a 5-point Likert scale, with 0\u0026thinsp;=\u0026thinsp;never, 1\u0026thinsp;=\u0026thinsp;several times a year, 2\u0026thinsp;=\u0026thinsp;at least once a month, 3\u0026thinsp;=\u0026thinsp;at least once a week, and 4\u0026thinsp;=\u0026thinsp;almost every day.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIntergenerational domestic support\u003c/h3\u003e\n\u003cp\u003eIntergenerational domestic support was measured by the average frequency with which older adults assisted their children with household chores in the past year, with higher response assignment (1\u0026thinsp;=\u0026thinsp;never, 5\u0026thinsp;=\u0026thinsp;almost every day) scores indicating more frequent care.\u003c/p\u003e\n\u003ch3\u003eIntergenerational childcare\u003c/h3\u003e\n\u003cp\u003eIntergenerational childcare was assessed by the average frequency with which each adult child cared for a grandchild in the past year, with higher response assignment (1\u0026thinsp;=\u0026thinsp;never, 5\u0026thinsp;=\u0026thinsp;more than 8 hours per day) scores indicating more intensive caregiving.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eReemployment after Retirement\u003c/h2\u003e \u003cp\u003eReemployment after retirement was measured by how often the respondent engaged in paid work or income generating activities after retirement, with higher response assignment (1\u0026thinsp;=\u0026thinsp;never, 5\u0026thinsp;=\u0026thinsp;almost daily) scores indicating more frequent participation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eElectoral Participation\u003c/h3\u003e\n\u003cp\u003eElectoral participation was assessed on the basis of self-reported participation in local council elections in the past three years, where 1\u0026thinsp;=\u0026thinsp;don't know and did not participate, 2\u0026thinsp;=\u0026thinsp;know but did not participate, and 3\u0026thinsp;=\u0026thinsp;participated.\u003c/p\u003e\n\u003ch3\u003eDevelopmental Participation\u003c/h3\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLearning activities\u003c/h2\u003e \u003cp\u003eLearning activities were measured by the frequency of participation in senior college or training programs in the past year, with responses assigned (0\u0026thinsp;=\u0026thinsp;never, 4\u0026thinsp;=\u0026thinsp;almost daily) Higher scores indicate more frequent participation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLeisure Activities\u003c/h2\u003e \u003cp\u003eLeisure activities among older adults are diverse. To further distinguish the differential impacts of various types of recreational activities on psychological well-being, entertainment activities were categorized into two types based on the level of participation: active leisure activities and passive leisure activities (Cho et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eActive leisure activities refer to those requiring physical, cognitive, technical, or social participation during participation, with the goals of entertainment, learning, or social interaction through active involvement. Active leisure was measured by the frequency of participation in three types of activities over the past year: instrumental activities (e.g., playing a musical instrument), board games or card games, and group dancing (e.g., public square dancing). Scores for each activity are assigned (0\u0026thinsp;=\u0026thinsp;never, 4\u0026thinsp;=\u0026thinsp;almost every day) Higher scores are associated with more frequent participation, and the scores for the three activities are summed to produce a total score of 0 to 12.\u003c/p\u003e \u003cp\u003ePassive leisure activities mainly refer to leisure through receiving external information or pre-prepared entertainment content. In this study, passive leisure activities were assessed in terms of the frequency of the adults' use of traditional media, including watching television, listening to the radio, reading books or newspapers, and listening to traditional opera, with the same values assigned as above.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eInternet Participation\u003c/h2\u003e \u003cp\u003eInternet participation was measured based on how often older adults used the Internet in the past year, with responses assigned (1\u0026thinsp;=\u0026thinsp;never, 5\u0026thinsp;=\u0026thinsp;almost every day) Higher scores indicate more frequent use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eControl variables\u003c/h2\u003e \u003cp\u003eBased on the theoretical framework described above, we incorporated control variables at the individual, household, and community levels. At the individual level, control variables included age, gender, education, subjective economic status, self-rated health and region of residence. At the family level, control variables included marital status, caregiving support from offspring, and financial support from children. At the community level, we included community community atmosphere, which was measured using a composite index based on respondents' satisfaction with eight dimensions: road conditions, fitness/activity facilities, public safety, environmental health, atmosphere of respect for older adults, competence of community council staff, street lighting, and accessibility. Each item was assessed using a five-point Likert scale. The scale showed good internal consistency (Cronbach's alpha\u0026thinsp;=\u0026thinsp;0.862), indicating that it effectively reflects the overall quality of the community environment for older adults. Total scores ranged from 8 to 40, with higher scores indicating a better community environment.\u003c/p\u003e \u003cp\u003eStatistical Analyses\u003c/p\u003e \u003cp\u003eOrdinary Least Squares (OLS) regression models were used to estimate the associations between different types of social participation and depressive symptoms. Moderation models tested subgroup heterogeneity by gender and urban\u0026ndash;rural residence, with demographic and socioeconomic characteristics included as controls. All analyses were conducted using Stata 17.0. Full model specifications, interaction terms, and robustness checks are provided in the Supplementary Materials.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics(N\u0026thinsp;=\u0026thinsp;7443)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean/\u003c/p\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepressive Symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLearning activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePassive Leisure Activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive Leisure Activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity Volunteering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntergenerational domestic support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntergenerational childcare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternet Usage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectoral Participation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.832\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReemployment after Retirement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48.22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational Attainment (in Years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubjective Economic Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-Rated Health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaregiving support from offspring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild-provided financial support\u003c/p\u003e \u003cp\u003e(Log-transformed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity atmosphere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAssociation between Social Participation types and Depressive Symptoms\u003c/p\u003e\n\u003cp\u003eOrdinary Least Squares (OLS) regressions showed that within developmental participation, learning activities (\u0026beta; = -0.266, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), active leisure activities (\u0026beta; = -0.039, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and internet usage (\u0026beta; = -0.218, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were significantly associated with fewer depressive symptoms, while passive leisure activities showed no significant association. Within Contributory participation, intergenerational childcare (\u0026beta; = -0.356, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and reemployment (\u0026beta; = -0.230, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were linked to fewer depressive symptoms, whereas intergenerational domestic support (\u0026beta;\u0026thinsp;=\u0026thinsp;0.142, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) was associated with more. Neither volunteering nor electoral participation showed significant effects (See Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eRobustness Checks\u003c/p\u003e\n\u003cp\u003eTo strengthen the credibility of the main results, we conducted two robustness checks. First, comparing separate OLS models (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) with a full model including all nine activity types (Supplementary Table A1) showed that only learning, internet usage, and intergenerational childcare remained significant, while passive and active leisure effects disappeared. Second, lagged dependent variable (LDV) models controlling for baseline depressive symptoms in 2018 (Supplementary Tables A2\u0026ndash;A3) largely corroborated our findings: internet usage, active leisure, intergenerational childcare, and reemployment continued to show protective effects, while intergenerational domestic support remained positively associated. The effects of learning were attenuated, suggesting sensitivity to model specification. Overall, these checks supported the validity of the baseline results and informed the subsequent heterogeneity analyses.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eGross Associations Between Each Social Participation Type and Depressive Symptoms\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial Participation Types\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eActivities\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eConstant\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eControl variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eR-squared\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\n \u003cp\u003eDevelopmental Participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eLearning activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-0.266***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e19.475***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"17\" rowspan=\"18\"\u003e\n \u003cp\u003eControlled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(0.062)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e(0.570)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003ePassive Leisure Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e19.377***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(0.024)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e(0.572)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eActive Leisure Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-0.039***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e19.425***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(0.014)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e(0.570)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eInternet Usage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-0.218***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e20.312***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(0.024)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e(0.577)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e\n \u003cp\u003eContributory participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eCommunity Volunteering\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e19.404***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(0.047)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e(0.573)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eIntergenerational domestic support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.142***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e18.910***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(0.029)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e(0.578)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eIntergenerational childcare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-0.356***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e20.550***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(0.056)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e(0.598)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eReemployment after Retirement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e-0.230***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e19.557***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(0.061)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e(0.572)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eElectoral Participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e19.256***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(0.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e(0.579)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eNote: N\u0026thinsp;=\u0026thinsp;7,443.The table present non-standardized coefficients, with standard errors in parentheses. All models control for age, gender, education, subjective economic status, self-rated health, region of residence. marital status, caregiving support from offspring financial support from children and community atmosphere. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eModerating Role of Urban-Rural Residence\u003c/p\u003e\n\u003cp\u003eThis study examined how urban\u0026ndash;rural residence moderated the relationship between social participation and depressive symptoms among older adults, by including interaction terms (Activity \u0026times; Urban) in the regression models (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFor developmental participation, significant positive interactions were observed for Active Leisure \u0026times; Urban (\u0026beta;\u0026thinsp;=\u0026thinsp;0.109, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and Internet Usage \u0026times; Urban (\u0026beta;\u0026thinsp;=\u0026thinsp;0.139, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating that their protective effects against depressive symptoms were weaker for urban older adults than for rural ones. In contrast, interactions for Learning Activities \u0026times; Urban and Passive Leisure \u0026times; Urban were not significant.\u003c/p\u003e\n\u003cp\u003eFor Contributory participation, Electoral Participation \u0026times; Urban (\u0026beta;\u0026thinsp;=\u0026thinsp;0.676, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) was positive, suggesting that electoral participation reduced depressive symptoms among rural older adults but not their urban counterparts. Community Volunteering \u0026times; Urban (\u0026beta; = -0.294, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) showed the opposite pattern: it was linked to higher depressive symptoms in rural areas but lower in urban areas. Intergenerational Domestic Support \u0026times; Urban (\u0026beta; = -0.253, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) also indicated that its positive association with depressive symptoms, strong in rural settings, was much weaker among urban older adults. Interactions for Intergenerational Childcare \u0026times; Urban and Reemployment \u0026times; Urban were not significant.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eUrban-Rural Differences in the Impact of Social Participation on the Depressive Symptoms among Retired Older Adults\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eVARIABLES\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eStandard\u003c/p\u003e\n \u003cp\u003eerrors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eControl variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eR-squared\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLearning activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"17\" rowspan=\"18\"\u003e\n \u003cp\u003eControlled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLearning activities \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePassive Leisure Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePassive Leisure Activities\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eActive Leisure Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.113***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eActive Leisure Activities\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.109***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eInternet Usage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.316***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eInternet Usage \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.139***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCommunity Volunteering\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.176**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCommunity Volunteering \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.294***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIntergenerational domestic support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.285***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIntergenerational domestic support\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.253***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIntergenerational childcare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.468***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIntergenerational childcare \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eReemployment after Retirement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.230***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eReemployment after Retirement \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eElectoral Participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.321***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eElectoral Participation \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.676***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eNote: N\u0026thinsp;=\u0026thinsp;7,443.The table present non-standardized coefficients, with standard errors in parentheses. All models control for age, gender, education, subjective economic status, self-rated health, region of residence. marital status, caregiving support from offspring financial support from children and community atmosphere. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eModerating Role of Gender\u003c/p\u003e\n\u003cp\u003eFurther analyses examined gender differences in the association between social participation and depressive symptoms among older adults using interaction terms (Activity \u0026times; Female) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFor developmental participation, Learning \u0026times; Female (\u0026beta; = -0.337, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) was significant, indicating a stronger protective effect of learning activities for female older adults than for male older adults. Other activities showed no significant gender interactions.\u003c/p\u003e\n\u003cp\u003eFor contributory participation, Reemployment \u0026times; Female (\u0026beta;\u0026thinsp;=\u0026thinsp;0.281, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was significant, suggesting that while reemployment reduced depressive symptoms among male older adults (\u0026beta; = \u0026minus;\u0026thinsp;0.319, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), the effect was reversed among female older adults. Interactions for volunteering, domestic support, childcare, and electoral participation were not significant.\u003c/p\u003e\n\u003cp\u003eTo further contextualize the moderation effects, we explored how gender and urban\u0026ndash;rural residence were associated with differences in the frequency of contributory and developmental participation (Supplementary Table A4). The results reveal distinct participation profiles across demographic groups. Urban older adults exhibit a significant advantage in self-fulfilling developmental activities (e.g., learning, leisure, and internet use). In contrast, their rural counterparts are more predominantly engaged in labor-intensive contributory roles, such as intergenerational domestic support and reemployment. Furthermore, participation patterns are strikingly gendered: while women report higher involvement in active leisure and domestic support, men maintain a stronger presence in formal public spheres, including reemployment and electoral participation. These divergent patterns provide an empirical basis for the uneven distribution of psychological benefits observed in our moderation analysis.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eGender Differences in the Impact of Social Participations on the Depressive Symptoms among Retired Older Adults\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eVARIABLES\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eStandard\u003c/p\u003e\n \u003cp\u003eerrors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eControl variables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eR-squared\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLearning activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\" morerows=\"17\" rowspan=\"18\"\u003e\n \u003cp\u003eControlled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLearning activities \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.337***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePassive Leisure Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003ePassive Leisure Activities\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eActive Leisure Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eActive Leisure Activities\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eInternet Usage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.209***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eInternet Usage \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCommunity Volunteering\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCommunity Volunteering \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIntergenerational domestic support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.142***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIntergenerational domestic support \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIntergenerational childcare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.368***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIntergenerational childcare \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eReemployment after Retirement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.319***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eReemployment after Retirement \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.281**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003eModel 27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eElectoral Participation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.108*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eElectoral Participation \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\times\\)\u003c/span\u003e\u003c/span\u003e Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e-0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eNote: N\u0026thinsp;=\u0026thinsp;7,443.The table present non-standardized coefficients, with standard errors in parentheses. All models control for age, gender, education, subjective economic status, self-rated health, region of residence. marital status, caregiving support from offspring financial support from children and community atmosphere. *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur research found that while most forms of developmental and contributory social participation had protective effect against depressive symptoms among older adults, these associations were not universally consistent. Instead, the impact of social participation on older adults\u0026rsquo; depressive symptoms was to a large extent contingent upon whether they resided in urban or rural settings, and the effects of some social participation also varied by gender.\u003c/p\u003e \u003cp\u003eAssociation between Social Participation Types and Depressive Symptoms\u003c/p\u003e \u003cp\u003eThis study categorizes older adults\u0026rsquo; social participation into two main types: developmental and contributory. In the realm of developmental participation, we find that learning, engaging in active leisure, and using the internet are all associated with lower levels of depressive symptoms among older adults. These findings are consistent with previous studies (Schoultz et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Cotten et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Developmental activities tend to reduce depressive symptoms by providing cognitive stimulation, fostering a sense of self-efficacy, and promoting social interaction and connectedness (Schoultz et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Chen \u0026amp; Schulz, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Lin et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast to the generally consistent patterns found in developmental participation, contributory social participation shows a more complex relationship with older adults\u0026rsquo; depressive symptoms. Contributory participations alleviate depressive symptoms primarily through generating social value, fulfilling social roles, and enabling reciprocity. Our findings indicate that reemployment after retirement is associated with lower levels of depressive symptoms, supporting continuity theory and the productive aging perspective, in which maintaining social roles and identity helps enhance psychological well-being (Kim \u0026amp; Feldman, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Atchley, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1989\u003c/span\u003e). However, this result contrasts with findings by Xie et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This discrepancy may reflect a bidirectional relationship between retirement and depressive symptoms\u0026mdash;those with fewer symptoms may be more inclined to re-enter the workforce.\u003c/p\u003e \u003cp\u003eOur study also finds that intergenerational child care was associated with a reduction in depressive symptoms, which differs from Kelley et al.'s (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) findings and may be due to cross-cultural differences. Hughes et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) also noted that the poorer health of grandparent caregivers was more likely to be due to pre-existing disadvantages than to caregiving per se. Moderate and voluntary grandparental caregiving may result in emotional rewards, a sense of purpose, and the fulfillment of generative needs (Erikson, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1963\u003c/span\u003e), leading to lower depressive symptoms.\u003c/p\u003e \u003cp\u003eHowever, not all contributory participation yields favorable outcomes. Our findings show that intergenerational domestic support (e.g., daily chores like cooking and laundry) is significantly associated with higher depressive symptoms levels among older adults. This underscores the importance of the nature and intensity of contributory behavior (Chen \u0026amp; Liu, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Unlike grandchild caregiving, which often provides emotional returns, household labor is repetitive, lacks intrinsic motivation and emotional feedback, and can result in resource depletion (Hobfoll, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1989\u003c/span\u003e) and autonomy frustration (Ryan \u0026amp; Deci, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), particularly when perceived as obligatory. These effects may undermine psychological well-being and stand in contrast to the social recognition and psychological gains often associated with caregiving (Thang et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMoreover, our study finds no significant association between depressive symptoms and participation in community volunteering, electoral activities, or passive leisure (e.g., watching TV for long hours). Passive leisure activities, due to their lack of cognitive, physical, or social interaction, may offer limited or even adverse effects on mental health, aligning with prior findings (Cho et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Although some studies have found positive effects of volunteering (Morrow-Howell, 2003; Filges et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), our results reveal no significant impact. Likewise, political participation may be negatively associated with mental health and moderated by factors such as regional political competition (Lin \u0026amp; Yan, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). We speculate that the insignificant overall effects of community volunteering and political participation may stem from substantial heterogeneity in individual responses to these activities, a point we further explore in subgroup analyses.\u003c/p\u003e \u003cp\u003eHeterogeneity by Urban-Rural Residence\u003c/p\u003e \u003cp\u003eOur results reveal that certain types of contributory participation exert differential effects on depressive symptoms across urban and rural contexts. Notably, intergenerational domestic support is positively associated with depressive symptoms for both urban and rural older adults, but the adverse effect is significantly stronger in rural areas. This may be attributed to stronger traditional family obligations and social norms in rural regions, where older adults face greater informal pressure to undertake household duties. Moreover, rural older adults may perceive such support more as reciprocal intergenerational exchange than as altruistic emotional support; the lack of reciprocation could thus negatively impact mental well-being (Chen \u0026amp; Liu, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Xu \u0026amp; Chi, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition, the effect of community volunteering shows an opposite pattern across urban and rural areas: it is associated with lower depressive symptoms levels among urban older adults, but higher depressive symptoms among rural older adults. This suggests a fundamental difference in the nature and experience of volunteering across settings. Urban volunteering is often interest-driven, voluntary, and better organized with formal recognition mechanisms, contributing to a sense of achievement and social inclusion (Morrow-Howell et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). In contrast, rural volunteering may rely more on informal mobilization based on interpersonal ties or village obligations (Wei \u0026amp; Xu, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), driven by communal responsibility and social expectations (Pearce et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These activities, though fostering social exchange, may lack institutional support or emotional rewards, leaving rural older adults feeling burdened and unfulfilled, particularly when their efforts are not reciprocated.\u003c/p\u003e \u003cp\u003eElectoral participation presents another striking urban-rural contrast. It is negatively associated with depressive symptoms in rural areas but linked to higher depressive symptoms in urban settings. This may reflect differences in the structure and experience of elections. Rural elections often involve grassroots-level engagement and familiar interpersonal contexts, fostering a sense of agency and belonging (Liu et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Tang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and providing channels for expressing local demands (Brandt \u0026amp; Turner, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Urban elections, by contrast, tend to involve more complex processes and higher-level institutions, with older adults\u0026rsquo; participation often limited to voting, lacking deeper engagement or tangible outcomes (Gui et al., 2016). Moreover, the complex urban socio-political landscape may elicit feelings of helplessness or anxiety, adversely affecting mental health (Trope et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMeanwhile, some activities\u0026mdash;including learning, passive leisure, post-retirement employment, and grandchild caregiving\u0026mdash;do not show significant urban-rural differences in their association with depressive symptoms. This suggests that the underlying mechanisms linking these activities to psychological outcomes may be more universally applicable across contexts.\u003c/p\u003e \u003cp\u003eWhen these findings are contextualized within actual participation patterns, our results indicate that urban older adults are more likely to engage in learning, leisure, internet use, volunteering, and grandchild caregiving, consistent with more abundant resource availability in urban settings. Rural older adults, in contrast, participate more frequently in household labor, post-retirement employment, and political activities, which reflect the social structure, economic needs, and local governance of rural communities. These differences not only stem from contextual constraints but may also shape the mental health impacts of various forms of participation. Special attention should be given to the potentially \u0026ldquo;double disadvantaged\u0026rdquo; rural older adults, who both participate less in mentally beneficial developmental activities and bear a heavier burden of negatively associated contributory activities.\u003c/p\u003e \u003cp\u003eHeterogeneity by Gender\u003c/p\u003e \u003cp\u003eGender-based heterogeneity analysis indicates that most forms of social participation do not show significant gender differences in their impact on depressive symptoms. However, a few activities do exhibit gender-moderated outcomes. Specifically, learning and passive leisure activities (e.g., watching TV or listening to the radio) are associated with lower levels of depressive symptoms among women, while no significant effect is observed for men. This aligns with earlier findings (Takagi et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Gender role theory (Eagly, 1987) posits that men are traditionally expected to fulfill the breadwinner role, and passive leisure may be viewed as \"meaningless\" by them, whereas women, more commonly positioned in caregiving roles within the home, may find passive leisure more acceptable and relaxing. Furthermore, women tend to derive psychological satisfaction through emotional resonance, and emotionally engaging content such as television dramas may align better with their preferences (Schulte-R\u0026uuml;ther et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Women also benefit more from learning activities in terms of mental health, consistent with previous studies (Shi et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), possibly due to the greater emotional support and social interaction embedded in learning environments for older women.\u003c/p\u003e \u003cp\u003eImportantly, reemployment after retirement has opposite psychological effects by gender. Among women, it is associated with higher depressive symptoms, whereas among men, it is linked to lower depressive symptoms. This supports findings by Weber et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) that older women face more emotional challenges post-retirement. Gender differences in role expectations and motivations for re-employment may explain this pattern. Men are more concerned with social status and may re-enter the workforce to maintain their identity (Konrad et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Eddleston et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Women, on the other hand, may be driven more by economic pressures or caregiving needs, which can add stress and contribute to psychological distress (Weber et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIntegrating our findings on gendered participation patterns, we uncover a troubling coupling between these patterns and the mental health returns of the activities. We find that older men appear to gravitate towards types of participation that are demonstrably more beneficial to their own mental health (reemployment). In contrast, older women face a double jeopardy: they not only shoulder a greater burden of activities associated with higher depressive symptoms (intergenerational domestic support), but they also exhibit lower levels of participation in the very activities most beneficial to them (learning activities). This finding starkly reveals how gender norms, mediated through social participation, continue to produce and reproduce gender inequality in mental health in later life.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eTo our knowledge, this study is the first to classify older adults\u0026rsquo; social participation into developmental and contributory categories. This innovative framework aligns with the concepts of active aging and productive aging, providing a more comprehensive representation of older adults\u0026rsquo; social participation. By incorporating two broad domains encompassing nine types of activities, the study captures the major forms of social participation among older adults in the digital era. The findings suggest that both the types of social participation and individual characteristics jointly shape their effects on psychological well-being.\u003c/p\u003e \u003cp\u003eNevertheless, the study has limitations. Our measure was restricted to nine activities, which may not capture the full spectrum of participation. Although robustness checks with lagged variables were conducted, the causal direction between social participation and psychological well-being remains uncertain; longitudinal data would provide stronger evidence. Moreover, data were drawn solely from China, which may limit generalizability; cross-national studies are recommended to assess cultural variation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study develops a framework that distinguishes between developmental and contributory forms of social participation, and demonstrates that their effects on older adults\u0026rsquo; mental health are heterogeneous across groups. The results highlight pronounced urban\u0026ndash;rural and gender differences: contributory and developmental participation do not have uniform effects but vary depending on social context and individual characteristics. These findings underscore the need for social policies and interventions that are sensitive to such heterogeneity, and that promote more targeted and inclusive approaches to active ageing and mental health support.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study were drawn from the 2018 and 2020 waves of the China Longitudinal Aging Social Survey (CLASS). The CLASS survey was approved by the relevant institutional ethics committee, and written informed consent was obtained from all participants prior to data collection. The present study is a secondary analysis of anonymized survey data and did not require additional ethical approval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. No individual person\u0026rsquo;s data are presented in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData from the 2018 and 2020 waves of the China Longitudinal Aging Social Survey (CLASS) are available by applying to the China Survey and Data Center at Renmin University of China (http://class.ruc.edu.cn/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Major Research Project of Philosophy and Social Sciences of the Ministry of Education of the People\u0026rsquo;s Republic of China, \u0026ldquo;Population Opportunities, Challenges, and Policy Research in the Construction of Chinese-style Modernization\u0026rdquo; (Grant No. 23JZD028).\u003c/p\u003e\n\u003cp\u003eThe funding body had no role in the design of the study, data analysis, interpretation of the findings, or in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYao Yu： Writing \u0026ndash; original draft, Methodology, Data curation, Investigation, Formal analysis, Visualization, Conceptualization. Jing MA: Supervision, Writing \u0026ndash; original draft. \u0026nbsp;Wei Guo: Project administration. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAmagasa, S., Fukushima, N., Kikuchi, H., Oka, K., Takamiya, T., Odagiri, Y., \u0026amp; Inoue, S. (2017). Types of social participation and psychological distress in Japanese older adults: A five-year cohort study. \u003cem\u003ePloS one\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(4), e0175392.\u003c/li\u003e\n \u003cli\u003eAtchley, R. C. (1989). A continuity theory of normal aging. \u003cem\u003eThe gerontologist\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(2), 183-190.\u003c/li\u003e\n \u003cli\u003eBaeriswyl, M., \u0026amp; Oris, M. (2023). Social participation and life satisfaction among older adults: Diversity of practices and social inequality in Switzerland. \u003cem\u003eAgeing \u0026amp; Society\u003c/em\u003e, \u003cem\u003e43\u003c/em\u003e(6), 1259-1283.\u003c/li\u003e\n \u003cli\u003eBisschop, M. I., Kriegsman, D. M., Deeg, D. J., Beekman, A. T., \u0026amp; Van Tilburg, W. (2004). The longitudinal relation between chronic diseases and depressive symptoms in older persons in the community: the Longitudinal Aging Study Amsterdam. \u003cem\u003eJournal of clinical epidemiology\u003c/em\u003e, \u003cem\u003e57\u003c/em\u003e(2), 187-194.\u003c/li\u003e\n \u003cli\u003eBrandt, L., \u0026amp; Turner, M. A. (2007). The usefulness of imperfect elections: The case of village elections in rural China. \u003cem\u003eEconomics \u0026amp; Politics\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(3), 453-480.\u003c/li\u003e\n \u003cli\u003eChen, F., \u0026amp; Liu, G. (2012). The health implications of grandparents caring for grandchildren in China. \u003cem\u003eJournals of Gerontology Series B: Psychological Sciences and Social Sciences\u003c/em\u003e, \u003cem\u003e67\u003c/em\u003e(1), 99-112.\u003c/li\u003e\n \u003cli\u003eChen, Y. R. R., \u0026amp; Schulz, P. J. (2016). The effect of information communication technology interventions on reducing social isolation in the elderly: a systematic review. \u003cem\u003eJournal of medical Internet research\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(1), e4596.\u003c/li\u003e\n \u003cli\u003eChiao, C., Weng, L. J., \u0026amp; Botticello, A. L. (2011). Social participation reduces depressive symptoms among older adults: an 18-year longitudinal analysis in Taiwan. \u003cem\u003eBMC public health\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e, 1-9.\u003c/li\u003e\n \u003cli\u003eCho, D., Post, J., \u0026amp; Kim, S. K. (2018). Comparison of passive and active leisure activities and life satisfaction with aging. \u003cem\u003eGeriatrics \u0026amp; gerontology international\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(3), 380-386.\u003c/li\u003e\n \u003cli\u003eCotten, S. R., Ford, G., Ford, S., \u0026amp; Hale, T. M. (2014). Internet use and depression among retired older adults in the United States: A longitudinal analysis. \u003cem\u003eJournals of Gerontology Series B: Psychological Sciences and Social Sciences\u003c/em\u003e, \u003cem\u003e69\u003c/em\u003e(5), 763-771.\u003c/li\u003e\n \u003cli\u003eCroezen, S., Avendano, M., Burdorf, A., \u0026amp; Van Lenthe, F. J. (2015). Social participation and depressive symptoms in old age: a fixed-effects analysis in 10 European countries. \u003cem\u003eAmerican journal of epidemiology\u003c/em\u003e, \u003cem\u003e182\u003c/em\u003e(2), 168-176.\u003c/li\u003e\n \u003cli\u003eEagly, A. H. (2013).\u0026nbsp;Sex differences in social behavior: A social-role interpretation. Psychology Press. (pp. 458-476)\u003c/li\u003e\n \u003cli\u003eEddleston, K. A., Veiga, J. F., \u0026amp; Powell, G. N. (2006). Explaining sex differences in managerial career satisfier preferences: The role of gender self-schema. \u003cem\u003eJournal of Applied Psychology\u003c/em\u003e, \u003cem\u003e91\u003c/em\u003e(2), 437.\u003c/li\u003e\n \u003cli\u003eErikson, E. H. (1963). \u003cem\u003eChildhood and society\u003c/em\u003e (Vol. 445). Norton.\u003c/li\u003e\n \u003cli\u003eFilges, T., Siren, A., Fridberg, T., \u0026amp; Nielsen, B. C. (2020). Voluntary work for the physical and mental health of older volunteers: A systematic review. \u003cem\u003eCampbell Systematic Reviews\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(4), e1124.\u003c/li\u003e\n \u003cli\u003eFlynn, M. (2010). Who would delay retirement? Typologies of older workers. \u003cem\u003ePersonnel review\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(3), 308-324\u003c/li\u003e\n \u003cli\u003eGlass, T. A., De Leon, C. F. M., Bassuk, S. S., \u0026amp; Berkman, L. F. (2006). Social engagement and depressive symptoms in late life: longitudinal findings. \u003cem\u003eJournal of aging and health\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(4), 604-628.\u003c/li\u003e\n \u003cli\u003eGui, Y., Cheng, J. Y., \u0026amp; Ma, W. (2006). Cultivation of grass-roots democracy: a study of direct elections of residents committees in Shanghai. \u003cem\u003eChina Information\u003c/em\u003e, \u003cem\u003e20\u003c/em\u003e(1), 7-31.\u003c/li\u003e\n \u003cli\u003eGuo, Q., Bai, X., \u0026amp; Feng, N. (2018). Social participation and depressive symptoms among Chinese older adults: A study on rural\u0026ndash;urban differences. \u003cem\u003eJournal of Affective Disorders\u003c/em\u003e, \u003cem\u003e239\u003c/em\u003e, 124-130.\u003c/li\u003e\n \u003cli\u003eHobfoll, S. E. (1989). Conservation of resources: a new attempt at conceptualizing stress. \u003cem\u003eAmerican psychologist\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(3), 513.\u003c/li\u003e\n \u003cli\u003eHuang, C. Q., Dong, B. R., Lu, Z. C., Yue, J. R., \u0026amp; Liu, Q. X. (2010). Chronic diseases and risk for depressive symptoms in old age: a meta-analysis of published literature. \u003cem\u003eAgeing research reviews\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(2), 131-141.\u003c/li\u003e\n \u003cli\u003eHughes, M. E., Waite, L. J., LaPierre, T. A., \u0026amp; Luo, Y. (2007). All in the family: The impact of caring for grandchildren on grandparents\u0026apos; health. \u003cem\u003eThe Journals of Gerontology Series B: Psychological Sciences and Social Sciences\u003c/em\u003e, \u003cem\u003e62\u003c/em\u003e(2), S108-S119.\u003c/li\u003e\n \u003cli\u003eKelley, S. J., Whitley, D. M., Escarra, S. R., Zheng, R., Horne, E. M., \u0026amp; Warren, G. L. (2021). The mental health well-being of grandparents raising grandchildren: A systematic review and meta-analysis. \u003cem\u003eMarriage \u0026amp; Family Review\u003c/em\u003e, \u003cem\u003e57\u003c/em\u003e(4), 329-345.\u003c/li\u003e\n \u003cli\u003eKim, S., \u0026amp; Feldman, D. C. (2000). Working in retirement: The antecedents of bridge employment and its consequences for quality of life in retirement. \u003cem\u003eAcademy of management Journal\u003c/em\u003e, \u003cem\u003e43\u003c/em\u003e(6), 1195-1210.\u003c/li\u003e\n \u003cli\u003eKonrad, A. M., Ritchie Jr, J. E., Lieb, P., \u0026amp; Corrigall, E. (2000). Sex differences and similarities in job attribute preferences: a meta-analysis. \u003cem\u003ePsychological bulletin\u003c/em\u003e, \u003cem\u003e126\u003c/em\u003e(4), 593.\u003c/li\u003e\n \u003cli\u003eLin, Y. C., \u0026amp; Yan, H. T. (2022). Association between political group participation and depressive symptoms among older adults: an 11-year longitudinal study in Taiwan. \u003cem\u003eJournal of Public Health\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(4), 778-786.\u003c/li\u003e\n \u003cli\u003eLin, Y. C., Liang, J. C., Yang, C. J., \u0026amp; Tsai, C. C. (2013). Exploring middle-aged and older adults\u0026rsquo; sources of Internet self-efficacy: A case study. \u003cem\u003eComputers in Human Behavior\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(6), 2733-2743.\u003c/li\u003e\n \u003cli\u003eLiu, D., Zhang, B., \u0026amp; Guo, J. (2024). Triple digital divide and depressive symptoms among middle-aged and older Chinese adults: a disparity analysis. \u003cem\u003eGeneral Psychiatry\u003c/em\u003e, \u003cem\u003e37\u003c/em\u003e(4), e101562.\u003c/li\u003e\n \u003cli\u003eLiu, W., Li, J. J. T., \u0026amp; Chen, J. (2024). Voting participation in grassroots elections and rural residents\u0026rsquo; subjective well‐being in China: The mediation roles of social class and fairness. \u003cem\u003eAnalyses of Social Issues and Public Policy\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(3), 1189-1207.\u003c/li\u003e\n \u003cli\u003eLiu, Z. W., Yu, Y., Fang, L., Hu, M., Zhou, L., \u0026amp; Xiao, S. Y. (2019). Willingness to receive institutional and community-based eldercare among the rural elderly in China. \u003cem\u003ePLoS One\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(11), e0225314.\u003c/li\u003e\n \u003cli\u003eMorrow-Howell, N., Hinterlong, J., \u0026amp; Sherraden, M. (Eds.). (2001). \u003cem\u003eProductive aging: Concepts and challenges\u003c/em\u003e. JHU Press.\u003c/li\u003e\n \u003cli\u003eMorrow-Howell, N., Hinterlong, J., Rozario, P. A., \u0026amp; Tang, F. (2003). Effects of volunteering on the well-being of older adults. \u003cem\u003eThe Journals of Gerontology Series B: Psychological Sciences and Social Sciences\u003c/em\u003e, \u003cem\u003e58\u003c/em\u003e(3), S137-S145.\u003c/li\u003e\n \u003cli\u003eMorrow-Howell, N., Putnam, M., Lee, Y. S., Greenfield, J. C., Inoue, M., \u0026amp; Chen, H. (2014). An investigation of activity profiles of older adults. \u003cem\u003eJournals of Gerontology Series B: Psychological Sciences and Social Sciences\u003c/em\u003e, \u003cem\u003e69\u003c/em\u003e(5), 809-821.\u003c/li\u003e\n \u003cli\u003ePearce, S., Kristjansson, E., Lemyre, L., \u0026amp; Takacs, T. (2023). Understanding the volunteer motivations, barriers and experiences of urban and rural youth: a mixed-methods analysis. \u003cem\u003eVoluntary Sector Review\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(2), 268-292.\u003c/li\u003e\n \u003cli\u003ePiszczek, M. M., \u0026amp; Pimputkar, A. S. (2021). Flexible schedules across working lives: Age-specific effects on well-being and work. \u003cem\u003eJournal of Applied Psychology\u003c/em\u003e, \u003cem\u003e106\u003c/em\u003e(12), 1907.\u003c/li\u003e\n \u003cli\u003eRyan, R. M., \u0026amp; Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. \u003cem\u003eAmerican psychologist\u003c/em\u003e, \u003cem\u003e55\u003c/em\u003e(1), 68.\u003c/li\u003e\n \u003cli\u003eSchoultz, M., \u0026Ouml;hman, J., \u0026amp; Quennerstedt, M. (2020). A review of research on the relationship between learning and health for older adults. \u003cem\u003eInternational Journal of Lifelong Education\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(5-6), 528-544.\u003c/li\u003e\n \u003cli\u003eSchulte-R\u0026uuml;ther, M., Markowitsch, H. J., Shah, N. J., Fink, G. R., \u0026amp; Piefke, M. (2008). Gender differences in brain networks supporting empathy. \u003cem\u003eNeuroimage\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(1), 393-403.\u003c/li\u003e\n \u003cli\u003eShi, X., Li, Y., Sun, L., Yu, Y., \u0026amp; Zhou, S. (2022). Gender differences in the subjective well-being of older adult learners in China. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e, 1043420.\u003c/li\u003e\n \u003cli\u003eTakagi, D., Kondo, K., \u0026amp; Kawachi, I. (2013). Social participation and mental health: moderating effects of gender, social role and rurality. \u003cem\u003eBMC public health\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e, 1-8.\u003c/li\u003e\n \u003cli\u003eTang, L., Luo, X., Yu, W., \u0026amp; Huang, Y. (2020). The effect of political participation and village support on farmers happiness. \u003cem\u003eJournal of Chinese Political Science\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e, 639-66\u003c/li\u003e\n \u003cli\u003eThang, L. L., Mehta, K., Usui, T., \u0026amp; Tsuruwaka, M. (2011). Being a good grandparent: Roles and expectations in intergenerational relationships in Japan and Singapore. \u003cem\u003eMarriage \u0026amp; Family Review\u003c/em\u003e, \u003cem\u003e47\u003c/em\u003e(8), 548-570.\u003c/li\u003e\n \u003cli\u003eTiong, W. W., Yap, P., Huat Koh, G. C., Phoon Fong, N., \u0026amp; Luo, N. (2013). Prevalence and risk factors of depressive symptoms in the elderly nursing home residents in Singapore. \u003cem\u003eAging \u0026amp; mental health\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(6), 724-731.\u003c/li\u003e\n \u003cli\u003eTrope, Y., Liberman, N., \u0026amp; Wakslak, C. (2007). Construal levels and psychological distance: Effects on representation, prediction, evaluation, and behavior. \u003cem\u003eJournal of consumer psychology\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(2), 83-95.\u003c/li\u003e\n \u003cli\u003eWang, J., Xu, J., Nie, Y., Pan, P., Zhang, X., Li, Y., ... \u0026amp; Shah, S. (2022). Effects of social participation and its diversity, frequency, and type on depressive symptoms in middle-aged and older persons: evidence from China. \u003cem\u003eFrontiers in Psychiatry\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e, 825460.\u003c/li\u003e\n \u003cli\u003eWeber, J., de Lange, A., \u0026amp; M\u0026uuml;ller, A. (2019). Gender differences in paid employment after retirement: Psychosocial working conditions and well-being.\u0026nbsp;Zeitschrift f\u0026uuml;r Gerontologie und Geriatrie,\u0026nbsp;52(Suppl 1), 32-39.\u003c/li\u003e\n \u003cli\u003eWei, X. J., and M. Y. Xu. 2023. Research on the Intrinsic Incubation of Rural Volunteer Service Organizations against the Background of Rural Revitalization. \u003cem\u003eThe Journal of Jiangsu Administration Institute\u0026nbsp;\u003c/em\u003e5: 80\u0026ndash;7.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. (\u0026lrm;2002)\u0026lrm;. Active Ageing: a policy framework. World Health Organization. https://iris.who.int/handle/10665/67215\u003c/li\u003e\n \u003cli\u003eXie, L., Yao, Y. D., Tang, L. L., Zhang, S., Yang, H. L., Zhang, S. Q., ... \u0026amp; Li, Z. Y. (2021). Effect of working after retirement on the mental health of older people: evidence from China. \u003cem\u003eFrontiers in Psychiatry\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e, 731378.\u003c/li\u003e\n \u003cli\u003eXu, L., \u0026amp; Chi, I. (2011). Life satisfaction among rural Chinese grandparents: the roles of intergenerational family relationship and support exchange with grandchildren. \u003cem\u003eInternational Journal of Social Welfare\u003c/em\u003e, \u003cem\u003e20\u003c/em\u003e, S148-S159.\u003c/li\u003e\n \u003cli\u003eYu, J., Chiu, Y. L., Guu, S. M., \u0026amp; Wang, J. N. (2024). The association between leisure activity and mental health in the older adults in China: amazing Guangchangwu. \u003cem\u003eFrontiers in Public Health\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e, 1291809.\u003c/li\u003e\n \u003cli\u003eYu, X., Mu, A., Wu, X., \u0026amp; Zhou, L. (2022). Impact of internet use on cognitive decline in middle-aged and older adults in China: longitudinal observational study. \u003cem\u003eJournal of Medical Internet Research\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(1), e25760.\u003c/li\u003e\n \u003cli\u003eZhao, L., \u0026amp; Wu, L. (2022). The association between social participation and loneliness of the Chinese older adults over time\u0026mdash;the mediating effect of social support. \u003cem\u003eInternational Journal of Environmental Research and Public Health\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(2), 815\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"social participation, depressive symptoms, urban–rural, gender","lastPublishedDoi":"10.21203/rs.3.rs-9011244/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9011244/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eSocial participation is a critical determinant of mental health in later life, yet the heterogeneity of participation types and their differential impacts remains under-explored. This study proposes a contributory–developmental framework to categorize social participation and examines their distinct associations with depressive symptoms among Chinese older adults.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Data were drawn from the 2020 wave of the China Longitudinal Aging Social Survey (CLASS, \u003cem\u003eN\u003c/em\u003e = 7,443 retired older adults). OLS regression and moderation models assessed subgroup differences. Robustness checks using the 2018 wave confirmed the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Most participation types were linked to lower depressive symptoms, but intergenerational domestic support was associated with higher levels. An urban–rural paradox emerged: rural older adults engaged more in contributory participation but gained fewer mental health benefits than urban counterparts, whereas they reported greater improvements in depressive symptoms from developmental participation despite lower involvement. Gender disparities were evident: men were more engaged in beneficial activities such as post-retirement work, while women bore heavier family caregiving responsibilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion：\u003c/strong\u003eSocial participation plays a vital role in reducing depressive symptoms in later life. Recognizing heterogeneity across participation types and subgroups is essential. Policies should provide tailored, inclusive mechanisms to support diverse forms of participation among older adults.\u003c/p\u003e","manuscriptTitle":"Contributory and Developmental Social Participation and Depressive Symptoms Among Older Adults in China: Urban–Rural and Gender Disparities *","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-17 14:26:14","doi":"10.21203/rs.3.rs-9011244/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-23T14:59:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T08:49:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T06:42:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-19T11:53:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-16T17:11:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"141295449284796149507775012100598851377","date":"2026-04-11T14:57:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"171754145254743985658485881783308384121","date":"2026-04-10T01:44:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152873958936657374968889684407345671023","date":"2026-04-10T00:35:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65525345325422461498959405403949338346","date":"2026-04-09T16:10:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-09T15:34:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-04T12:55:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-04T12:55:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2026-03-02T14:18:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ac41ca4e-4306-4b83-859c-ab2ff68571cb","owner":[],"postedDate":"April 17th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T17:53:08+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-17 14:26:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9011244","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9011244","identity":"rs-9011244","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}