Session 7

Aging and Gerontological Social Work: Care, Cognition, and Quality of Life

Moderator: Dr. Jierong Hu (Assistant Professor, City University of Macau, China)

O7.1  Longitudinal patterns of depression among in middle-aged and older people with chronic diseases in China: A latent growth model and growth mixture model approach

*Zexi Su¹

¹School of Social Development, Shandong Women’s University, Jinan, China

 Abstract

Background: As China’s population continues to age, the number of people living with chronic diseases is steadily increasing. The prevalence of chronic diseases among middle-aged and older adults stands at 70.6%. People with chronic diseases often face challenges such as limited mobility, dietary difficulties, reduced physical activity, and a decline in their ability to carry out daily living activities, socialize, or work. The distress and impact of these limitations significantly increase the likelihood of depression among patients with chronic diseases. It is therefore necessary to conduct an in-depth investigation into the trajectories of depressive symptoms and their predictive factors among middle-aged and elderly patients with chronic diseases.

Methods: Using data from the China Family Panel Study (2016–2022), the study sample comprised middle-aged and elderly individuals aged 45 years and over who had been diagnosed by a doctor with a chronic disease. Descriptive statistical analysis, Latent Growth Modeling (LGM), and Growth Mixture Modeling (GMM) were employed to assess the differential characteristics of depressive symptoms, whilst logistic regression was used to analyze the influence of relevant predictive factors.

Results: LGM results indicated that depressive symptoms in the middle-aged and older population exhibited a linear increase over time; GMM analysis revealed four distinct trajectories: Class 1: High depression-stable group (10.1%); Class 2: High depression-decreasing group (5.7%); Class 3: Low depression-stable group (69.7%); and Class 4: Low depression-increasing group (14.5%). Logistic regression analysis indicated that residents with rural household registration, unmarried individuals, and those with lower educational attainment were more likely to enter high-risk groups for the development of depressive symptoms.

Conclusions: This study reveals the heterogeneity of depressive trajectories among middle-aged and older patients with chronic diseases. Interventions targeting these predictive factors are needed to enhance the effectiveness of social work services.

O7.2  An Intervention Study of Group Work on Mental Health Among Institutionalized Older People

*JIachun Chen¹

¹ School of Sociology and Humanities, Jiangxi University of Finance and Economics, China

Abstract

With the increasing number of elderly people in China year by year, institutional care has become an important way of elderly support. However, the elderly living in nursing institutions generally face mental health problems. Existing services mostly focus on material needs while ignoring their spiritual needs. Taking Yee Hong Home of Hong Kong Society for Rehabilitation in Shenzhen as an example, this paper focuses on the mental health status of institutionalized elderly. From the perspective of social work and based on Activity Theory and Maslow's Hierarchy of Needs, eight rounds of psychological support activities were carried out using the group work method, and the intervention effect was analyzed through pre- and post-intervention evaluation comparison. The study finds that group work has a positive effect on alleviating depressive mood, improving social competence and enhancing self-worth among institutionalized elderly. This study provides a reference for practical intervention in mental health services for institutionalized elderly, and also offers practical evidence for relevant policies and service design.

O7.3  Digital Convenience and Depression in Older Adults: A Sequential Mediation Model of Life Satisfaction and Self-Rated Health

*Yufan Zhang¹, Maanse Hoe¹, Shiyu Liu²

¹Department of Social Welfare, Keimyung University, South Korea; 2 Department of Social Work, School of Management, Chengdu University of Information Technology, China

Abstract

Background and Purpose: Depression is a prevalent public health concern among older adults in China. With the increasing digitalization of society, the integration of digital technology into daily life has become an important factor influencing the mental health of older adults. However, existing research has focused primarily on device access and frequency of use, with insufficient attention to the subjective perception of technology. Grounded in the Technology Acceptance Model and the Selection, Optimization, and Compensation (SOC) model, which regards adaptive resource utilization as central to successful aging, this study highlights digital convenience (i.e., the perceived ease and usefulness of digital technologies in daily life) as a key adaptive resource. It aims to examine the association between digital convenience and depressive symptoms among older Chinese adults, with particular focus on the sequential mediating roles of life satisfaction and self-rated health.

Methods: This study employed a cross-sectional design utilizing data from the 2023 China Longitudinal Aging Social Survey (CLASS). The final sample comprised 6,193 older adults aged 60 and above. Depressive symptoms were measured using the 9-item Center for Epidemiologic Studies Depression Scale (CES-D). Digital convenience across 10 daily life domains, life satisfaction, and self-rated health were also assessed. Data analysis was conducted using SPSS 29.0, including descriptive statistics and Pearson's correlation analysis. Serial mediation effects were tested using the PROCESS macro (Model 6) with 5,000 bootstrap resamples.

Results: Digital convenience was negatively associated with depressive symptoms (β = -0.219, p < .001). Serial mediation analysis revealed that the total indirect effect accounted for 35.66% of the total effect, operating through three significant pathways: independent mediation by life satisfaction (b = -0.035), independent mediation by self-rated health (b = -0.039), and sequential mediation from life satisfaction to self-rated health (b = -0.018). Further analysis showed that for older internet users, the direct effect of digital convenience on reducing depression was larger (-0.268 vs. -0.064) and accounted for a higher proportion of the total effect (69.03% vs. 51.56%) compared to non-users. Conversely, for older non-internet users, this association relied more heavily on indirect mediated pathways (48.44%).

Conclusions and Implications: Digital convenience reduces depressive symptoms among older Chinese adults both directly and indirectly through sequential improvements in life satisfaction and self-rated health. Consistent with the SOC model, perceived technology ease constitutes a vital adaptive resource for psychological well-being in later life. These findings provide an evidence base for community partners and policymakers to design inclusive digital-health initiatives. By implementing stratified interventions, such as task-oriented digital training for internet users and offline proxy services for non-users, communities and healthcare organizations can effectively mitigate digital exclusion and improve late-life mental health outcomes.

O7.4  Social support factors associated with depression among older adults in mainland China: a systematic review and meta-analysis

*Ming Li¹, Duyun Wang¹, Tan Tang¹

1 Department of Social Work, School of Ethnology and Sociology, Yunnan University, Kunming, China

Abstract

Background and purpose: Although late-life depression has become a significant public health issue in mainland China, most existing studies focus on exploring the impact of one or a few social support factors on elderly depression, and lack comparative analysis of the effect sizes between different factors. To identify the most critical social support factors influencing geriatric depression and thereby facilitate the effective identification of intervention points, we designed a study to systematically estimate the effect sizes of social factors.

Methods: To identify social support factors of geriatric depression, we conducted two independent literature searches in English‐and Chinese‐language databases, and we used a random effects model to analyse effect sizes. Additionally, we performed moderation analyses to examine differences in mean effect size across variables. We assessed publication bias by using Egger's test and used Comprehensive Meta‐Analysis (version 3.0, Biostat, Englewood, NJ, USA) for data analysis.

Results: We identified 16 social support factors in 111 studies. The pooled effect sizes between the factors and geriatric depression ranged from 0.011 to 0.315. Specifically, subjective social support and the total social support score exhibited a moderate effect with geriatric depression (r = -0.315, 95% CI: -0.367 to -0.260; r = -0.303, 95% CI: -0.354 to -0.251). Additionally, geriatric depression showed small to moderate effect sizes with objective social support (r = -0.242, 95% CI: -0.291 to -0.191), friend support (r = -0.240, 95% CI: -0.370 to -0.100), and social support utilization (r = -0.205, 95% CI: -0.266 to -0.142). In contrast, medical insurance showed no significant relationship with depression (r = -0.011, 95% CI: -0.041 to 0.018). Furthermore, meta-regression analysis indicated that the year of data collection significantly moderated the relationship between geriatric depression and friend support (β = -0.0208, p = 0.030), as well as the relationship with intergenerational economic support (β = 0.0133, p = 0.023).

Conclusions and Implications: Subjective social support has a significant protective effect on geriatric depression. This suggests that enhancing individuals' perception and recognition of social support is a potential target for improving interventions for geriatric depression in mainland China. In contrast, the effectiveness of medical insurance in alleviating geriatric depression symptoms is relatively limited. Based on these findings, policymakers should place greater emphasis on the integration of medical insurance with other formal support measures, such as community services and mental health services, to establish a more comprehensive and multi-layered social support system.

O7.5  A Study on Social Work Interventions to Improve Sleep Quality in Older Women with Mild Cognitive Impairment

*Gefei Du¹

¹School of Social Development, East China Normal University, Shanghai, China

Abstract

Background and Objectives: With the accelerated aging of China's population, elderly women with mild cognitive impairment (MCI) have a significantly higher incidence of sleep disorders than their male peers, while targeted community-based non-pharmacological interventions remain scarce. This study aims to verify the effectiveness of a social work group intervention integrating Cognitive Behavioral Therapy for Insomnia (CBT-I) on sleep quality among MCI elderly women, and explore the feasible path of social work intervention for this group.

Methods: A quasi-experimental design was adopted, with 18 elderly women with MCI in Town W, Shanghai recruited as participants, randomly divided into an intervention group and a control group (9 in each). The intervention group received 6 sessions of localized group intervention based on CBT-I, while the control group received no intervention. Data were collected via the Pittsburgh Sleep Quality Index (PSQI), Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS), Montreal Cognitive Assessment (MoCA), semi-structured qualitative interviews and smart wristband monitoring, and analyzed by paired-samples t-test and independent-samples t-test, supplemented by qualitative analysis.

Results: There was no significant difference in baseline data between the two groups. After intervention, the total DBAS score of the intervention group increased significantly (p<0.01), realizing the scientific reconstruction of sleep cognition; the total PSQI score showed a positive improvement trend with small to medium effect (Hedges'g=0.31). Qualitative interviews and smart wristband monitoring further verified the intervention effects on sleep behavior optimization, emotion regulation and peer support network construction.

Conclusions and Implications: The group social work intervention integrated with CBT-I can effectively improve the sleep cognition and quality of elderly women with MCI. This study provides an operable paradigm for community non-pharmacological sleep intervention for this group, enriches the practical path of geriatric social work, and offers empirical evidence for policy formulation of early community intervention for cognitive impairment.

07.6  How Is Rural Mutual Aid Eldercare Generated? The Endogenous Action Mechanism in Mountainous Hollowed-Out Villages from an “Embedding–Empowerment” Perspective

*Chunsen Tang¹, Junyi Su¹

¹School of Public Policy and Administration, Chongqing University, Chongqing, China

Abstract

Background and Objectives: The context of sustained outmigration and rapid population aging in mountainous rural China, traditional family-based eldercare is weakening, creating an urgent need for low-cost and sustainable community-based care solutions. Mutual-aid eldercare has emerged as a promising approach, yet its formation mechanisms and sustainability remain underexplored. This study examines how mutual-aid eldercare practices are initiated, institutionalized, and sustained in resource-constrained rural settings. Focusing on Baoping Village in Chongqing, it explores how such practices emerge under the leadership of key actors, through what mechanisms they evolve into stable institutional arrangements, and how their sustainability can be understood from a multi-dimensional perspective.

Methods: The study adopts a qualitative case study design with a longitudinal process-tracing approach. Data are collected through triangulation from multiple sources, including in-depth semi-structured interviews with village leaders, elderly residents, and other stakeholders, systematic analysis of policy documents, government reports, media materials, and village-level records, as well as participant and non-participant observations capturing everyday practices and social interactions. Data analysis follows a grounded coding strategy, moving from first-order concepts to second-order themes and aggregated dimensions.

Results: The findings show that the mutual-aid eldercare model evolves into an institutionalized practice through the combined effects of key actor leadership, collective economic development, and social mobilization. Its operation is characterized by a multi-level embeddedness mechanism. At the cognitive level, shared values and role modeling foster mutual-aid norms; at the relational level, trust is reinforced through dense social networks in an acquaintance society; at the structural level, collective economic organizations integrate resources and coordinate multiple actors; and at the institutional level, service provision is stabilized through formal arrangements such as communal dining facilities. Together, these dimensions transform fragmented individual assistance into a coordinated and sustainable system, forming a governance logic of “Key Actor Leadership – Collective Mutuality – Social Collaboration.”

Conclusions and Implications: These findings contribute to the understanding of community-based eldercare by demonstrating how multi-level embeddedness facilitates the institutionalization of mutual-aid practices in rural contexts. They suggest that sustainable eldercare models can be built upon endogenous social structures, collective organizations, and culturally grounded norms. The study offers practical insights for developing low-cost, community-driven eldercare services in resource-constrained areas and highlights the importance of strengthening institutional support and enhancing the capacity of collective organizations. Future research may further explore comparative cases and examine how such models can be adapted across diverse socio-cultural settings.