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. 2023 Jul 3;10(9):6517–6526. doi: 10.1002/nop2.1904

Depression mediates the relationship between social capital and health‐related quality of life among Chinese older adults in the context of the COVID‐19 pandemic: A cross‐sectional study

Ping Zhang 1, Xiao‐Li Liu 1,✉, Rong‐Mei Zhang 1,✉, Ning Xia 1
PMCID: PMC10416043  PMID: 37400957

Abstract

Aim

To explore the association between social capital and health‐related quality of life (HRQoL) and to determine whether depression mediates the association among Chinese older adults in the context of the COVID‐19 pandemic.

Design

A descriptive cross‐sectional research design.

Methods

The Geriatric Depression Scale‐15, Social Capital Questionnaire and 12‐item Short‐Form Health Survey were used to investigate 1201 older adults selected from Jinan, Shandong Province, China, using a multistage stratified cluster random sampling method.

Results

Pearson's correlation analysis revealed a significant positive correlation between social capital and HRQoL (r = 0.269, p < 0.01). Multivariate linear regression analyses demonstrated that social capital was significantly negatively associated with depression (β = −0.072, p < 0.001) and that depression was associated with HRQoL (β = −1.031, p < 0.001). The mediation analyses showed that depression mediated the association between social capital and HRQoL, and the indirect effect size was 0.073 (95% confidence interval: 0.050, 0.100).

Keywords: COVID‐19, depression, health‐related quality of life, older adults, social capital

1. INTRODUCTION

Along with the acceleration of population ageing, China in the 21st century is an irreversible ageing society. According to the latest epidemiological study, China's population of older adults aged ≥60 years is approximately 249 million, including approximately 40 million who are disabled and partially disabled (16%) (Huang et al., 2019). Ageing older adults experience life changes, such as loss of social roles, loss of lifelong companionship and loss of physical and mental abilities, combined with the heightened susceptibility and vulnerability to coronavirus disease 2019 (COVID‐19) (Chan et al., 2021; Chong et al., 2020), effectively heightening concerns about the future and fear of infection. This has seriously affected the quality of life of not only those with infections (Sun & Lu, 2020) but also the general older adult population (Wang et al., 2020).

The impact of social factors, as determinants of health (Duh‐Leong et al., 2021), on the quality of life of older adults cannot be underestimated. Social capital, as a social determinant of health, has been shown to have a positive effect on the improvement of the quality of life (Duh‐Leong et al., 2021; Xue et al., 2020). Social capital is a social network based on trust and reciprocity that facilitates individual participation in collective activities and thus, access to resources and support (Westphaln et al., 2020). Social trust, social support, social participation, social connection, cohesion and reciprocity are important dimensions of social capital measurement (Bai et al., 2020). Previous research has shown that different forms of social capital can mean different resources, help and support and that social capital has an important influence on the physical health of older people (Yang et al., 2020). Himanshu et al. (2019) identified social capital as an important protective factor for the quality of life of older people. A longitudinal study suggested that high social capital could make older people more active in community life and is an important force for health promotion (Yiengprugsawan et al., 2018). In addition, research has confirmed that social capital plays an important role in crisis management in natural disasters or pandemics (Pitas & Ehmer, 2020; Uekusa et al., 2020; Wang & Li, 2020). Given the importance of social capital, we believe it is necessary to recognize that the lack or interruption of social capital may hinder the response and recovery of older adults in the COVID‐19 pandemic, resulting in a reduced quality of life. However, only a few studies have been conducted examining the relationship between social capital and quality of life during the pandemic.

However, the rapid spread of COVID‐19 has forced most governments to impose strict lockdown and quarantine measures. Therefore, limited social activities and loss of social capital may lead to depression and deterioration of mental health. A cross‐sectional study from China showed an overall national prevalence of depression of 47.5% during the COVID‐19 outbreak (Wu et al., 2020). Although Asian countries have outperformed Western countries in the control of COVID‐19 (Landoni et al., 2021), the implementation of measures such as strict blockades, social distancing and reduction in gatherings has also had a significant negative impact on the psychosocial well‐being of individuals, especially the vulnerable groups (Guo et al., 2020; Lee et al., 2020; Marmot & Allen, 2020). Another study (Chong et al., 2020) also highlighted the importance of paying attention to the mental health of older adults during COVID‐19 and into the future, by drawing lessons learnt during the pandemic. Harpham et al. suggested that social capital can buffer the adverse effects of stressful events and thus promote health (Coll‐Planas et al., 2017). A systematic review found that older adults with higher access to social capital resources were associated with higher levels of mental health (Nyqvist et al., 2013). Grey et al. (2020) also demonstrated that social support can reduce risk factors for depression due to social isolation resulting from government policies during the pandemic. Therefore, there may be some influence mechanism between social capital and depressive symptoms, which has certain research value.

A systematic review (Paradies et al., 2015) showed that social capital is an important protective factor for mental and physical health. Hassanzadeh et al. (2016) also reported a similar finding. In addition, through effective pandemic prevention and control, social solidarity during disasters has the potential to lead to positive changes in the social capital of older adults. Sun and Lu (2020) showed that social capital was significantly and positively associated with depression and quality of life in a study of older adults in Harbin, China, during the pandemic. This suggests that high levels of social capital aid in alleviating psychological distress in older adults due to isolation during the pandemic. A population‐based study from Tehran (Asadi‐Lari et al., 2016) demonstrated that social capital can influence health‐related quality of life (HRQoL) through mental health (Hassanzadeh et al., 2016). However, no studies have yet examined the relationship between social capital, depression and quality of life in Chinese older adults in the context of the pandemic. Here, we aimed to explore the association between social capital and HRQoL and determine whether depression mediates this association among Chinese older adults in the context of the COVID‐19 pandemic.

2. METHODS

2.1. Design, participants and procedure

A descriptive cross‐sectional study was conducted using data collected from April to August 2021 in Jinan, the capital of Shandong Province in Eastern China (36.667° N, 116.983° E). Meanwhile, Strengthening the Reporting of Observational Studies in Epidemiology guidelines was followed in Epidemiology (STROBE) checklist (see Appendix S1). Jinan is a principal city in China and the political, cultural and educational centre of Shandong Province. By the end of 2020, the resident population in Jinan had reached 9.2 million, of which older adults aged ≥60 years accounted for 19.96%. A multistage stratified cluster sampling method was adopted for sample selection in this study. First, according to the quartile of per capita GDP in Shandong Province in 2020, 10 districts and two counties in Jinan were divided into four layers. Then, a random number table method was used to select one district/county from each layer, two streets/townships from each district/county and two communities/administrative villages from each street/township. Finally, six communities and 10 administrative villages were included, and those who met the inclusion criteria were investigated. The inclusion criteria were (1) age ≥ 60 years, (2) permanent residents who had a registered residence in city communities or had been residing there for at least 6 months and (3) those who provided informed consent and voluntarily participated in this study. The exclusion criteria were (1) severe hearing, vision, or language communication impairment; (2) severe cognitive impairment (such as dementia and confusion) or mental illness (such as schizophrenia and bipolar disorder); and (3) serious physical disease, such as severe renal failure, leukaemia and malignant tumours.

Sample size was calculated using the following formula: n = (μα/22 π[1 − π])/δ 2 (Charan & Biswas, 2013). A meta‐analysis showed that the prevalence of depression in China during the COVID‐19 pandemic was 45% (Deng et al., 2021). Using π = 45%, μ = 1.96, d = 0.03 and α = 0.05, our estimated sample size was 1056 in this study. Before the investigation, with the assistance of the Jinan municipal government, we communicated with the management officer of the community and obtained the names, addresses and contact information of older adults aged ≥60 years (1680 in total). In addition, community administrators volunteered to assist with the survey, and with their help, we assigned professionals to broadcast in the community service centres, gathered research materials to conduct a centralized investigation, and explained the purpose and contents of the research to the participants before the investigation. After obtaining the consent of all participants and voluntarily participating, the questionnaire was distributed. In addition, if participants encountered difficulties in answering, they could consult our researchers for assistance. For the purposes of considering convenience for some older adults, their family members (children or spouses) were allowed to take the questionnaire home and help them answer under the guidance of professionals. We need to point out that professionals refer to investigators who receive standardized and unified training on the significance, purpose, methods and content of this research before the survey begins. Finally, 1315 individuals participated in this survey, but 114 participants were excluded as they did not meet the inclusion criteria, were not interested in the study or suffered from physical discomfort during the study. Therefore, 1201 samples were used for analysis in this study (participation rate = 91.3%).

2.2. Measures

2.2.1. Geriatric Depression Scale‐15

The Geriatric Depression Scale‐15 (GDS‐15) has been used to assess depression level in Chinese older adults (Zhang, Wang, et al., 2020; Zhang, Zhang, et al., 2020) and has been reported to have good reliability and validity among Asian older adults living in the community (Nyunt et al., 2009). The scale contains 15 items, with higher scores indicating a higher level of depression (range 0–15). In this study, the internal consistency was high, with a Cronbach's α of 0.804.

2.2.2. Social Capital Questionnaire

The Social Capital Questionnaire developed by Tian et al. (Bai et al., 2020) is used to measure the level of social capital in older people, using a 5‐point Likert scale that contains 22 items. Six dimensions of social capital were included in the present study, namely (1) social participation, (2) social support, (3) social connection, (4) trust, (5) cohesion and (6) reciprocity. The total score ranges from 22 to 110, with a higher score indicating a higher level of social capital. In this study, the Cronbach's α was 0.853.

2.2.3. 12‐item Short‐Form Health Survey

The 12‐item Short‐Form Health Survey (SF‐12) scale is a simplified scale developed by the Boston Institute of Health based on the SF‐36 scale (Tabolli et al., 2011), which is used to measure HRQoL (Ibrahim et al., 2020; van der Meulen et al., 2020) and has good applicability among older adults in China (Lu et al., 2020; Shou et al., 2016). The 12 items in the SF‐12 are divided into eight main domains: (1) general health perception, (2) physical functioning, (3) role of physical problems, (4) body pain, (5) vitality, (6) social functioning, (7) role of emotional problems and (8) mental health, which can be categorized into the physical and mental component summary according to an individual's physical and mental health, respectively. A scoring method has been derived for SF‐12 (Barnett et al., 2013), which ranges from 0 to 100, with higher scores indicating better HRQoL. In this study, the Cronbach's α was 0.745.

2.2.4. Covariates

Based on previous studies on older adults in China, this study conducted a covariate analysis. All covariates were added to the study model, including sex, age (60–69, 70–79, or ≥80 years), residence (urban or rural), education level (≤primary school, junior high school, high school, or ≥university), marital status and family income level (low, medium or high). These variables were collected by a self‐reported paper questionnaire.

2.3. Research ethics committee approval

This study was approved by the ethics committee of the Second Hospital, Cheeloo College of Medicine, Shandong University, and informed consent was obtained from each participant.

2.4. Statistical analysis

We used the SPSS version 23.0 (IBM Corp.) for data analyses. In our study, all numerical variables are expressed as mean ± standard deviation or 95% confidence interval (CI), and all categorical variables are expressed as frequency. One‐way analysis of variance (ANOVA) for continuous variables and independent t‐test for categorical variables were used to compare intergroup differences. The Pearson's correlation coefficients (r) between depression, social capital and HRQoL were calculated. The PROCESS macro (Model 4) produced by Hayes (2017) was applied to verify the mediating role of depression on the relationship between social capital and quality of life. Bootstrapping was used to test the mediating effect of depression by setting a sample size of 5000 and a CI of 95%. Before the mediation effect analysis, data were standardized, and the covariates were controlled in the model to overcome potential confounding effects. p < 0.05 was considered statistically significant.

3. RESULTS

3.1. Descriptive statistics of participants

Figure 1 illustrates the enrollment of participants in this study. Table 1 shows the characteristics of the participants. In total, 1201 Chinese older adults aged ≥60 years were included in our study, with a mean age of 70.12 ± 6.29 years (range: 60–97 years). Most of them were rural residents (73.36%), women (53.37%), married (74.02%), had no higher education (59.30%) and were in the middle‐income group (61.20%).Here, we need to explain that the categories of family income level are mainly divided according to the local average wage level: Low = ≤5000¥; Medium = 5000–8000¥; High = ≥8000¥.

FIGURE 1.

FIGURE 1

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Participant enrollment procedure.

TABLE 1.

Status of depression, social capital, and quality of life by different characteristics (N = 1201).

Variables N (%) GDS‐15 t/F p Value Social capital t/F p Value SF‐12 t/F p Value
Mean SD Mean SD Mean SD
Total 4.38 3.39 72.07 13.03 56.69 13.25
Scores range 0.00–15.00 22.00–110.00 9.38–100.00
Age (in years)
60–69 622 (51.80) 4.49 3.35 1.893 0.151 72.42 13.09 1.356 0.258 57.86 12.46 7.203 <0.001
70–79 485 (40.40) 4.69 3.39 72.02 13.14 55.94 13.98
80 and above 94 (7.80) 4.76 3.60 70.05 12.04 52.86 13.57
Sex
Male 560 (46.63) 4.19 3.37 −1.754 0.080 72.01 13.61 −0.171 0.864 57.80 13.35 2.705 0.007
Female 641 (53.37) 4.54 3.40 72.13 12.52 55.73 13.09
Residence
Urban area 320 (26.64) 4.17 3.54 −1.289 0.198 72.17 14.73 0.147 0.883 57.95 13.01 2.015 0.044
Rural area 881 (73.36) 4.45 3.33 72.047 12.37 56.23 13.31
Education level
Primary school or below 712 (59.3) 4.68 3.42 6.048 <0.001 70.81 12.54 6.548 <0.001 54.97 13.52 11.257 <0.001
Junior high school 331 (27.6) 4.15 3.42 73.26 13.36 58.60 12.36
High school 124 (10.3) 3.52 2.92 74.92 14.11 59.82 13.09
University and above 34 (2.8) 3.38 3.30 76.56 12.57 62.78 10.09
Marital status
Married 889 (74.02) 4.06 3.18 −5.140 <0.001 72.84 13.10 3.519 <0.001 57.66 13.20 4.340 <0.001
Other (divorced, widowed) 312 (25.98) 5.29 3.78 69.89 12.619 53.93 13.00
Family income level
Low 340 (28.31) 5.43 3.56 25.069 <0.001 69.43 13.56 9.983 <0.001 53.87 14.44 12.644 <0.001
Medium 735 (61.20) 4.04 3.22 73.05 12.72 57.47 12.26
High 126 (10.49) 3.49 3.26 73.52 12.41 59.78 14.22
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Abbreviations: GDS‐15, Geriatric Depression Scale‐15; SD, standard deviation; SF‐12, 12‐item Short‐Form Health Survey.

The mean scores for depression, social capital and quality of life were 4.38 ± 3.39, 72.07 ± 13.03 and 56.69 ± 13.25, respectively. The t‐test and one‐way ANOVA showed significant differences in the scores of quality of life among older adults of different age, sex, residence, education level, marital status and family income level (p < 0.05). Our findings showed a significant difference in depression, social capital and scores of quality of life among older adults with different education and family income levels (p < 0.05, Table 1).

3.2. Analysis of the correlation between depression, social capital and quality of life

Pearson's correlation analysis showed that social capital and quality of life had a significant positive correlation (r = 0.269, p < 0.01), while social capital and quality of life had a negative correlation with depression (r = −0.306/−0.338, all p < 0.01). Results are presented in Table 2.

TABLE 2.

Correlations (r) between depression, social capital, and health‐related quality of life (N = 1201).

Variables GDS‐15 Social capital SF‐12
GDS‐15 1
Social capital −0.306*** 1
SF‐12 −0.338*** 0.269*** 1
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Abbreviations: GDS‐15, Geriatric Depression Scale‐15; SF‐12, 12‐item Short‐Form Health Survey.

***

p < 0.001.

3.3. Regression analysis of association among depression, social capital, and HRQoL

As shown in Table 3, after controlling for covariates such as age, sex, residence, education level, marital status and family income level, social capital (β = −0.072, p < 0.001) was significantly negatively associated with depression in Model 1, while social capital (β = 0.171, p < 0.001) and depression (β = −1.031, p < 0.001) were both associated with HRQoL in Model 2.

TABLE 3.

Multivariate linear regression analysis of association among depression, social capital and health‐related quality of life (HRQoL).

Predictors Model 1 (GDS) Model 2 (HRQoL)
β 95% CI SE p Value β 95% CI SE p Value
Age −0.298 8.692, 12.206 0.148 0.044 −1.915 −3.030, −0.799 0.568 0.001
Sex 0.176 −0.588, −0.008 0.186 0.345 −1.406 −2.808, −0.005 0.714 0.049
Residence −0.121 −0.190, 0.541 0.229 0.597 0.033 −1.686, 1.753 0.876 0.970
Education level −0.139 −0.399, 0.122 0.133 0.297 1.270 0.271, 2.270 0.509 0.013
Marital status 0.936 0.510, 1.363 0.217 <0.001 −0.694 −2.341, 0.953 0.840 0.408
Family income level −0.798 −1.120, −0.477 0.164 <0.001 0.908 −0.337, 2.154 0.635 0.153
Social capital −0.072 −0.086, −0.058 0.007 <0.001 0.171 0.115, 0.227 0.028 <0.001
GDS −1.031 −1.249, −0.813 0.111 <0.001
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Note: Model 1—total score of GDS as the dependent variable; Model 2—total score of HRQoL as the dependent variable.

Abbreviations: β, unstandardized coefficient; CI, confidence interval; GDS, Geriatric Depression Scale; SE, standardized error.

3.4. Mediation model analysis

The results of the mediation analysis based on the PROCESS macro are shown in Table 4 and Figure 2. Results of data standardization and control of demographic variables indicate that the total effect (path c) of social capital on quality of life was 0.241 (p < 0.001); social capital was significantly associated with depression (β = −0.276, p < 0.001), and depression was significantly associated with quality of life (β = −0.264, p < 0.001). Furthermore, when depression was controlled, the close relationship between social capital and quality of life was sustained (β = 0.168, p < 0.001). In addition, our results indicate that the indirect effect (a × b) size of depression in the association between social capital and quality of life was 0.073, with a 95% CI from 0.050 to 0.100, and the bootstrap test results indicated that the 95% CI of depression's indirect effect between social capital and quality of life did not include 0. Furthermore, it also revealed that depression acts as a mediator between social capital and quality of life. The standardized mediating effect accounted for 30.23% of the total effect. Figure 2 shows the final mediating model.

TABLE 4.

Mediation of depression between social capital and health‐related quality of life (HRQoL).

R 2 F Coefficient SE t p LLCI ULCI
Outcome: Depression
Social capital a 0.136 26.844 −0.276 0.027 −10.079 <0.001 −0.330 −0.222
Outcome: HRQoL
Social capital c′ 0.169 30.364 0.168 0.028 6.018 <0.001 0.114 0.223
Depression b −0.264 0.028 −9.290 <0.001 −0.320 −0.208
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Abbreviations: LLCI, lower level of confidence interval; SE, standard error; ULCI, upper level of confidence interval.

a

Path Social capital—Depression.

b

Path Depression—Quality of life.

c′

Path Social capital—Quality of life when Depression acting as a mediator (indirect effect).

FIGURE 2.

FIGURE 2

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Mediation model of depression between social capital and health‐related quality of life (HRQoL; ***p < 0.0001).

4. DISCUSSION

In this study, we examined the relationship between social capital and HRQoL and the mediating role of depression on this relationship among Chinese older adults in the context of the COVID‐19 pandemic. The results suggested a positive relationship between social capital and quality of life and that depression mediated this relationship in Chinese older adults during the pandemic. The findings of this study provide information that are beneficial for healthy ageing in older adults in the context of the pandemic: (1) increasing the level of social capital in older adults will help alleviate the psychological stress caused by the pandemic, and (2) helping older people with low levels of social capital by reducing depression will help improve their quality of life.

The mean total social capital score for Chinese older adults in this study was higher than that reported in a previous study (48.74 ± 15.21) regarding self‐isolation for 14 days during the COVID‐19 outbreak in January 2020 in China (Xiao et al., 2020). This shows that the seriousness of the COVID‐19 pandemic has prompted all sectors of the society to pay more attention to the physical and mental health of older adults, which has improved the social capital level of older adults. In addition, in the relationship between education level and depression, social capital and quality‐of‐life variables, we found an interesting phenomenon that the primary school or below had higher score in the depression and the quality of life but lower score in the social capital score. The reason may be that when we collected the data, the aged of primary school and below were mainly over 75 years old. A study showed a significant positive association between mental ill‐health (e.g. depression) and younger age (18–49 years) but a nonsignificant positive association with older age (50+ years), and suggested that older age may buffer the negative impact of the COVID‐19 pandemic on mental health (Wilson et al., 2021). This potential protective mechanism of age may be related to the level of social capital. Therefore, the emergence of this phenomenon needs to be further explored by future researchers.

Our findings showed a significant positive correlation between social capital and quality of life among older Chinese people, which was similar to previous findings (Apostolaki et al., 2021; Sun & Lu, 2020; Yang et al., 2020). This was further confirmed by our regression analysis that found that social capital positively predicts quality of life and is an important protective factor for quality of life, which was consistent with the findings of Lane et al. (2020). Zhong et al. (2017) explored the relationship between social capital and quality of life among older adults in three agricultural counties in Jiangsu Province, China, and found that low social capital was significantly associated with low quality of life after controlling for individual characteristics, and that older adults with low social capital had an EQ‐5D index of 0.055, which was lower than that of those with high social capital. Cao and Rammohan (2016) also showed that high level of social capital was significantly correlated with the ability to perform everyday tasks, mental health, and independence and suggested that policy providers should focus on improving the level of social capital in order to mitigate the consequences of poor health to thereby improve healthy ageing. It should be noted that in this study, although the correlation between quality of life and social capital and depression was not high, it still has practical guiding significance, which is still worth further discussion in the future.

The findings of the present study suggest that social capital can affect quality of life not only directly but also indirectly through depression when controlling for confounding variables such as sociodemographics. Depression is a common risk factor for suicide, self‐harm and psychiatric disorders and has serious negative effects on the mental health and quality of life of older adults (van den Berg et al., 2021). Although presently in a relatively stable phase, the COVID‐19 outbreak has caused changes in the lifestyle of older adults; for example, they are unable to participate in group social activities, such as square dances and choir activities, as in the past, which may exacerbate their sense of isolation and thus, lead to psychological problems. Social capital can reduce the likelihood of mental ill‐health by alleviating the stress of individuals who have been experiencing difficult situations and negative life events for a long time (Coll‐Planas et al., 2017). High levels of social capital enable older people to cope positively with the adverse effects of the pandemic and to adapt quickly to their environment during the post‐COVID‐19 era, thus maintaining a healthy mental state. A meta‐analysis showed that depression was a significant factor in the reduction of quality of life and that reducing depression levels improved the quality of life of individuals (Kolovos et al., 2016). A cohort study of centenarians from China also points to the positive effect of lowering depression levels on the quality of life of older adults (Han et al., 2020). This suggests that reducing depression levels by increasing the level of social capital of older adults may be an effective way to improve quality of life. Therefore, in clinical nursing practice, we should give more attention older adults, communicate with them and channelling the psychological problems in a timely manner, and involve them in various forms of activities, such as establishing geriatric activity rooms, day care homes and regular communication activities for the elderly people, so as to increase their social participation and restrain the generation of bad emotions, which is of great significance to improve the quality of life.

In addition, during our survey, we found that some older adults moved and settled in the local area from other cities, which is closely related to the large‐scale and high‐speed urbanization process in China, and their social adaptation and integration issues have become the focus of attention. From the perspective of social culture, as bicultural individuals who are influenced and impregnated by both cultures across cultural fields, migrant citizens need to integrate different norms between the two cultures to adapt to different cultural situations and achieve effective transition (Hong et al., 2016). Intergroup interactions and intergroup relationships, as important representations of social capital, are highly likely to have a positive effect on the level of bicultural identity integration. When individuals are frequently involved in different cultural exchange situations, they will gradually have cognitive and behavioural responses appropriate to the situation due to the influence of social interaction, cultural knowledge and interpersonal contextual characteristics. Previous studies have shown that individuals who are involved in different social situations, have more group friends and receive more social support are not only less negative but also more culturally integrated (Amiot et al., 2007; Brewer & Pierce, 2005). In addition, it has been shown that social interactions and social relationships provide not only access to resources but also tough emotional support, so social capital has a positive effect on individuals' sense of belonging (Amiot et al., 2007; Brewer & Pierce, 2005; Verkuyten & Yogeeswaran, 2017). The stronger the individual's sense of belonging to the domain in which they are present, the higher their level of bicultural identity integration, which is also essential for maintaining psychological well‐being and resource ownership (Hong et al., 2016; Yamaguchi et al., 2016). Therefore, from the perspective of individual cultural cognition, the level of social capital ultimately affects mental health by affecting individual cognition and behaviour. In the context of the COVID‐19 pandemic, the social interaction and activity venues of the older adults have changed. How to make the older adults obtain higher social capital is crucial.

There were certain limitations in our study. First, we could not determine the causal relationship between social capital, depression and quality of life using a cross‐sectional study. A previous study suggested that some types of social capital have a positive effect on mental health, while some may have a negative effect (Yip et al., 2007). Li and Zhang (2015) also pointed out different correlations between different types of social networks and different health indicators (such as physical and psychological). This could mean that different forms of social capital could potentially act as a deterrent to lowering depression levels and ultimately reducing the quality of life. Therefore, longitudinal studies are warranted to clarify the relationship between different forms of social capital, depression and quality of life in the future, which would be beneficial to older adults. Second, although we used a strictly randomized method to screen older adults, some of them dropped out, which may have caused bias in the results. Finally, due to time constraints, we only surveyed participants from one city and thus, the sample may not be representative and generalizable for the results.

5. CONCLUSION

In the context of the COVID‐19 pandemic, social capital and quality of life of older Chinese people showed a significant positive correlation and were important protective factors for quality of life; depression was found to mediate this relationship. This result implies that social capital plays an important role and that all members of the society should pay attention to and enhance the development and use of social capital in older people during the post‐COVID‐19 era. Improved social capital will facilitate effective ways for older people to cope, alleviating psychological stress due to the epidemic while reducing the development of adverse emotions and ultimately promoting the health of patients. Given the impact of COVID‐19, offline questionnaires were conducted in only one city in this study, and in‐depth interviews with older adults were lacking. In the future, we aim to combine in‐depth interviews and qualitative research to further explore the different effects of different forms of social capital on the quality of life of older adults.

6. RELEVANCE FOR POLICY OR CLINICAL PRACTICE

Our results showed that there was a significant positive correlation between social capital and quality of life of older adults, and depression mediates the relationship between social capital and quality of life in the context of the COVID‐19 pandemic. It was not difficult for us to find the importance of social capital for older adults. Older adults with high social capital have a rich social life and are able to establish good social relationships, which help relieve life stress and enhance their trust and sense of belonging to society, thus contributing to their good self‐actualization status. During the post‐COVID‐19 era, relevant government departments or communities can expand the social capital of older adults by establishing perfect guarantee mechanisms and appropriate incentive policies while preventing and controlling the epidemic, such as popularizing health education, establishing sound activity venues, and improving the level of retirement protection. In addition, older adults should be encouraged to actively participate in various formal or informal organizations to increase their social participation and build a diversified social support system for society, families and individuals to increase the stock of social capital and promote healthy ageing.

In clinical practice, older patients undergo psychological changes along with physical torture. As nursing staff, we should pay close attention to the psychological changes of older patients and take targeted measures to intervene and control the social capital factors that affect the mental health of older patients. On the one hand, family members, relatives and friends and the society should support, care and encourage patients and pay attention to their subjective feelings so that they can be comforted psychologically and spiritually. On the other hand, they should be motivated and guided to actively seek and receive support from their families and communities, especially to encourage older patients with depressive symptoms to make full use of the social resources around them to continuously make psychological adjustments and reduce depression.

FUNDING INFORMATION

This study was not supported by any grants.

CONFLICT OF INTEREST STATEMENT

All authors of this study declare that they have no conflict of interest.

Supporting information

Appendix S1.

Click here for additional data file. (74KB, doc)

ACKNOWLEDGEMENTS

We thank the relevant government departments and community workers for their strong support to this study; we also thank all the investigators and their families who participated in this study.

Zhang, P. , Liu, X.‐L. , Zhang, R.‐M. , & Xia, N. (2023). Depression mediates the relationship between social capital and health‐related quality of life among Chinese older adults in the context of the COVID‐19 pandemic: A cross‐sectional study. Nursing Open, 10, 6517–6526. 10.1002/nop2.1904

Contributor Information

Xiao‐Li Liu, Email: liuxiaoli79@126.com.

Rong‐Mei Zhang, Email: 15153169039@126.com.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Associated Data

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Supplementary Materials

Appendix S1.

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Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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