Disentangle the Elderly’s Positive Coping Behavior in Times of COVID-19: Perspectives from the Social Network,Information Acquisition,and Perceived Community Support

Abstract

Given the severe impact of the global COVID-19 pandemic, there is an urgent need for scientific research on strategies to help vulnerable populations, such as the elderly, cope effectively. Drawing upon the weak ties theory and information literacy, this study started with preliminary interviews to explore potential factors influencing the positive coping behavior of a group of elderly Chinese individuals. It further disentangled the impact of social networks (including network size, network strength, and network heterogeneity) and information acquisition on the elderly’s positive coping behavior during the COVID-19 pandemic and elucidated their underlying mechanisms. The hypotheses were tested by surveying 916 individuals aged 60 to 96 in southwest China. Structural equation modeling analysis conducted using AMOS (24.0) revealed that social network (network strength and heterogeneity) and information acquisition were directly associated with positive coping behavior, respectively. Perceived community support mediated such associations. Findings enrich the theoretical literature and provide new perspectives on how to help the elderly cope with health crises by enhancing social network, information acquisition, and perceived community support.

Plain language summary

Disentangle the elderly’s positive coping behavior in times of COVID-19: Perspectives from the social network, information acquisition, and perceived community support

Given the far-reaching impact of the global COVID-19 pandemic, scientific research, and corresponding suggestions on how to help the elderly (the vulnerable population group) cope with positively are emergently needed. To this end, this study conducted a survey of 916 people using a questionnaire survey method and a structural equation model, exploring in depth the factors that may be affected by the active coping behavior of the Chinese elderly people during the COVID-19 pandemic. This research indicates that social networks, information acquisition, and community support can prompt them to take more active response behaviors. Findings from this research stimulate more research on how vulnerable groups such as the elderly can improve coping behavior and ability during the COVID-19 pandemic. Unavoidably, sample selection was only conducted in one provincial capital city in China, and issues such as the applicability of the scale caused by cultural differences need to be noted in future research.

Keywords

social network information acquisition perceived community support positive coping behavior COVID-19

Introduction

The outbreak of the Coronavirus Disease 2019 (COVID-19) led to global public health crises that seriously posed threats to individuals’ well-being, especially to those who are in a more vulnerable age group, such as the elderly (Van Bavel et al., 2020) who experienced with weaker immune function, constituting a susceptible and high-risk group in coping with the COVID-19 pandemic (Pedreanez et al., 2021; Sun et al., 2020). Research has suggested that if the elderly adopt positive coping strategies, including government-prescribed or discretionary behaviors like wearing masks and frequent handwashing, their infection rates could significantly decrease (Mao et al., 2022; Strizova et al., 2020). In response, comprehensive prevention and control measures were implemented globally, emphasizing pro-environmental and healthy personal hygiene practices effective in protecting individuals from infection (Frieden & Lee, 2020). These measures included practices such as attention to hand hygiene, mask-wearing, and maintaining social distancing (Bielecki et al., 2021; Ebrahim & Memish, 2020; Lu et al., 2021; World Health Organization [WHO], 2021), proving effective in reducing the spread of COVID-19 (Kraemer et al., 2020; Leung et al., 2020; Peng et al., 2021). In essence, adopting positive coping strategies has played a crucial role in mitigating the threats posed by the COVID-19 pandemic.

Coping, defined as “conscious and volitional efforts to regulate the emotion, cognition, behavior, physiology, and environment in response to stressful life events or circumstances” (Billings & Moos, 1981), is generally conceptualized as a two-dimensional construct, namely, approach coping and avoidance coping. In recent years, scholars have paid more attention to the study of positive coping behaviors of the elderly (Paans et al., 2018; Provencher et al., 2016), for they constitute a high-risk group and their positive coping responses should be boosted (e.g., vaccine responses; Collier et al., 2021). Moreover, research has shown that age is a risk factor for complications and related mortality (O’Driscoll et al., 2021; Remuzzi & Remuzzi, 2020). In particular, elderly individuals with chronic medical conditions face the highest risk of contracting and succumbing to severe cases of COVID-19 (Palmer et al., 2020). In this context, the quality of life of the elderly is facing tough challenges (Khorani et al., 2022). Therefore, WHO recommends encouraging families to provide practical and emotional support to help the elderly take preventive measures (e.g., wearing masks, maintaining social distancing, and washing hands; Bielecki et al., 2021; Ebrahim & Memish, 2020), which can contribute to encouraging their engagement in physical activities and promoting their psychological well-being (Palmer et al., 2020). Other evidence has also suggested that greater use of proactive coping strategies is associated with lower COVID-19 pandemic-related stress among the elderly compared with the younger group (Klaiber et al., 2021; Minahan et al., 2020). However, although previous work has demonstrated the importance of improving the positive coping behavior of the elderly during the COVID-19 period, strategies for the COVID-19 positive coping behavior of the elderly have not been adequately addressed yet. Therefore, this study raises the issue of strengthening the positive coping behavior of the elderly to improve their health and well-being during such turbulent COVID-19 pandemic challenges.

Previous literature has indicated that the elderly’s coping behavior is affected by various social factors, such as coping mechanisms and social support (Van Bavel et al., 2020). In addition, the elderly’s coping behavior is influenced by crucial factors such as their gender, age, self-care ability, and assessment of COVID-19 information provided by the government (Sun et al., 2020). More importantly, the elderly’s COVID-19 positive coping behavior is affected by their social network resources at the individual level and their psychological resources at the community level (Carmel et al., 2017; Jia et al., 2021). Due to the different research findings, determining the influence factor of the elderly’s coping behavior is critical in this new context. Additionally, in alignment with the weak ties theory, which asserts that weak connections can offer diverse and innovative information by bridging social gaps and establishing links with a broader spectrum of individuals, such associations can be invaluable for acquiring vital information or resources (Granovetter, 1973; Rajkumar et al., 2022). This highlights the need for further investigation to develop targeted intervention programs and policies aimed at mitigating infection risks within this population. Moreover, in the digital era, where an abundance information prevails, the ability to discern reliable, accurate, and pertinent information—information literacy—is essential for informed decision-making. Information literacy encompasses the capacity to access, evaluate, utilize, and communicate information effectively (Zurkowski, 1974). Previous research has demonstrated that the source of information, particularly from social media, can significantly influence people’s attitudes and behaviors (Yan et al., 2020). For instance, the spread of highly infectious COVID-19 can speed up the dissemination of related rumors to a certain extent (H. Huang et al., 2021).

Hence, drawing on the weak ties theory and information literacy, we conducted preliminary interviews with 20 Chinese elderly individuals to identify key factors influencing positive coping behavior. Our intention is to explore strategies associated with these factors, examining them through the perspectives of social networks, information acquisition, and perceived community support. This exploration aims to predict the positive coping behavior of the elderly amidst the challenges presented by the COVID-19 pandemic. By doing so, we aim to offer practical insights and recommendations to address the pressing global challenges faced by the elderly, testing the proposed hypothetical model in the process.

Development of the Model

According to the preliminary interview, combined with the weak ties theory and information literacy, our proposed conceptual model (see Figure 1) is developed to investigate the predictors (i.e., social network, information acquisition, and perceived community support) of positive coping behavior of the elderly during the COVID-19 pandemic.

Figure 1.

The proposed conceptual model.

The first predictor is social network, which is the integration of social relations and is associated with how individuals interact and form social relationships (Rheingold, 1993). Within the process of establishing a social network, social ties represent the perceived strength of social relationships between individuals and others (Hsiao et al., 2016). These social ties can be categorized into strong ties and weak ties, as described by Granovetter (1973). The weak ties theory posits that weak ties can provide individuals with access to diverse and novel information for weak ties have the capacity to traverse wide social distances, reaching a broader audience and facilitating the acquisition of crucial information or resources (Granovetter, 1973; Rajkumar et al., 2022). Moreover, serving as the primary tool for the elderly to interact with society, social network plays a crucial role in responding to sudden changes in the external environment (MacLeod et al., 2016), such as the challenges posed by the COVID-19 pandemic (Lu et al., 2021; Van Bavel et al., 2020). Additionally, research has indicated that streetscape greenery can positively influence the walking behavior of the elderly, potentially connecting them to social networks, given the dynamic and interactive nature of people and their surroundings (L. Yang et al., 2021). Simultaneously, variations in coping behavior may arise due to individual differences such as gender, age, intelligence level, response to previous stressors, mood, and self-efficacy (Caplan, 1983; Catanzaro et al., 1995). Studies have demonstrated that the social network can impact coping mechanisms in high-stress situations (Phan & Airoldi, 2015). Therefore, it is of great significance to explore the influence of the social network on the positive coping behavior of the elderly during the COVID-19 pandemic. By leveraging social network, we can mobilize resources to assist elderly individuals in adopting positive coping strategies, thereby enhancing their overall quality of life and mental health.

The second predictor, information acquisition, has been identified as a significant factor in coping with risks among the general public (A. T. Chen et al., 2021; P. L. Liu, 2020; Z. Zhang et al., 2021). When faced with new challenges, such as the COVID-19 pandemic, individuals typically acquire relevant knowledge and information through their own information literacy, enabling them to respond effectively. Information literacy, as defined by Zurkowski (1974), refers to the ability of individuals to recognize when they need information and to effectively obtain, evaluate, and use the information they require. The broader the dissemination of risk information, the more likely risk-averse behavior will become regular (T. Z. Liu & Jiao, 2018). Studies, such as one focused on patients with multiple sclerosis, have indicated that individuals satisfied with the information they acquire are more inclined to adopt active coping strategies for managing their diseases (Okanli et al., 2017). However, compared to other age groups, the elderly may face challenges in seeking and identifying necessary information from various platforms, especially those commonly used by younger individuals (Pan et al., 2020). Older individuals tend to trust traditional media, such as newspapers and television news, while younger individuals are more inclined toward new media (Media Insight Project [MIP], 2021). Consequently, the elderly may become susceptible to online misinformation due to limitations in the breadth and depth of information they can access (Guess et al., 2019; Seo et al., 2020; Xu & Cavusgil, 2019). In this context, information acquisition, encompassing both breadth and depth, becomes crucial for the elderly to adopt correspondingly appropriate coping strategies to navigate the challenges posed by the COVID-19 pandemic. This comprehensive understanding plays a pivotal role in formulating and implementing coping strategies, enabling effective responses to the challenges posed by the COVID-19 pandemic among the elderly. Essentially, when elderly individuals have access to sufficient information, they are better equipped to make informed decisions and adopt measures that align with the challenges brought about by the pandemic. Therefore, it is crucial to prioritize initiatives that promote the elderly’s access to and comprehension of information. This emphasis is of critical significance in enhancing their ability to cope with the ongoing impact of the COVID-19 pandemic.

The third predictor is the community support experienced by the elderly, specifically referred to as perceived community support. In the context of the COVID-19 pandemic, research indicates that the support provided by the community for pandemic prevention positively and significantly influences the adoption of preventive strategies by its residents (Gabarrell-Pascuet et al., 2021; Kuo et al., 2021). This implies that social support from the community can effectively reduce depressive and anxiety symptoms among community residents (Gabarrell-Pascuet et al., 2021). Strengthening the perceived social support within the public can indeed alleviate anxiety and promote overall well-being (L. Huang & Zhang, 2022). Numerous studies have established a close relationship between social network and perceived social support, including perceived community support (Oh et al., 2014; Russell et al., 1997). A robust social network among the elderly correlates with an increased perception of community support, contributing to better subjective well-being. Conversely, those lacking close social network connections with family or friends, relying solely on voluntary services or social care, face additional risks (Rook et al., 2012; Simons et al., 2021). Moreover, the level of perceived social support, varying with factors such as age, significantly impacts one’s coping behavior to maintain health (Abbas et al., 2019; Zamanian et al., 2021). Considering research highlighting the critical role of perceived community support in sustaining a social network (Oh et al., 2014), we hypothesize that community support perceived by the elderly through their social network is positively associated with their positive coping behavior. In other words, perceived community support mediates the relationship between the social network and positive coping behavior.

Numerous studies have identified the relationship between information acquisition and community support (Deng & Liu, 2017; Shovlin & Kunkel, 2018). Coping with daily-life hassles is a complex issue requiring the involvement of various efforts and strategies (Folkman & Moskowitz, 2004), such as strategies for information seeking (Pan et al., 2020), good information access, therefore, can enhance people’s perception of community support and other services. Prior research has pointed out that community-based interventions should consider improving perceived community resilience by making more information-seeking channels available for residents to improve disaster preparedness (Guo et al., 2020). In addition, previous studies have also provided evidence for the impact of perceived community support on individual behavior (Lewis et al., 2021). W. L. Liu et al. (2020) discovered that individuals supported by organizations are more likely to exhibit organizational citizenship behavior, encompassing various forms of community participation behavior such as information sharing, knowledge contribution, thematic discussion, and community interaction, as per the theory of organizational support. These findings offer a foundation for the hypothesis that perceived community support could play a mediating role between information acquisition and positive coping behavior. This suggests that the positive influence of information acquisition on individual coping behavior may be influenced by their perceived community support. The accumulated evidence underscores the need to explore and understand these variables’ potential interrelationships in the investigation context.

Based on the above-mentioned theoretical reasoning and grounded on prior empirical evidence, four specific hypotheses embedded in our conceptual model (see Figure 1) are proposed in this study: (1) Social network (network size, network strength, and network heterogeneity) positively relates to the elderly’s positive coping behavior; (2) Information acquisition has a positive impact on the elderly’s positive coping behavior; (3) Perceived community support mediates the relationship between social network and positive coping behavior; (4) Perceived community support mediates the relationship between information acquisition and positive coping behavior. These hypotheses establish a structured framework for examining the complex interplay among social networks, information acquisition, perceived community support, and positive coping behavior within the context of the elderly during the COVID-19 pandemic. They unveil the genuine needs of the elderly in response to the challenges posed by the pandemic, offering a foundation for targeted recommendations. Such insights can guide governments and social organizations in developing more effective support measures and intervention plans tailored to the specific requirements of the elderly population during the ongoing pandemic.

Methods

Procedure and Participants

Our sampling survey targets the elderly over 60 years old. With the support of our research collaborators, who have affiliations with the community through work or residence, we successfully recruited the initial group of participants who met the specified criteria. Then, the snowball sampling method was applied. Once some respondents completed the questionnaire, they were invited to recommend other participants who meet the research’s target population requirements. Those who could not read or write were assisted by our research collaborators (through reading and ticking the items), during which the research collaborators made no suggestions, comments, or hints. The questionnaire, which required approximately 20 min to complete, was devoid of sensitive language and required no information, such as the participants’ names to protect their privacy. Participants were told that their responses would be used for scientific research only, and they could quit and withdraw their data at any time.

Ethical approval was obtained from the board member of the ethical committee of the first author’s institute, and the survey was carried out to capture the relevant data in southwest China from September to October 2020. A total of 1,300 participants were invited with the assistance of research collaborators, and 997 responded (the response rate was 76.69%). After excluding invalid responses (i.e., missing data on crucial variables, response failed from attentional check, relatively short time frame for responses), there were 916 valid responses retained (M_age = 68.87, SD = 6.80, Age range = 60–96; see Table 1 for detailed info).

Table 1.

Social Demographic Features of the Participants (N = 916).

Category	Options	Responses	Response rate (%)
Gender	Male	478	52.20
Gender	Female	438	47.80
Age	60–65	372	40.60
	66–75	385	42.00
	≥76	159	17.40
Family structure	Multigenerational families	351	38.30
	Live with spouse only	499	54.50
	Live alone	66	7.20
Health status	Very unhealthy	8	0.90
	Unhealthy	57	6.20
	Normal	274	29.90
	Healthy	503	54.90
	Very healthy	74	8.10
Educational degree	Primary school and below	285	31.10
	Junior middle school	299	32.60
	Senior high school	181	19.80
	Undergraduate	97	10.60
	Above bachelor	54	5.90

Measures

Social Network

We adopted a 9-item scale originated from the 19-item Stroke Social Network Scale (SSNS) (Northcott & Hilari, 2013) to measure social network: network size (e.g., “I know more people in society than other elders in this community do”), network strength (e.g., “I keep in touch with my relatives, friends, and neighbors frequently”), and network heterogeneity (e.g., “People who keep in touch with me come from all walks of life”). All items were registered on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). For this sample, the Cronbach’s alpha of network size (α = .71), network strength (α = .62), and network heterogeneity (α = .68) were all acceptable. Cronbach’s alpha regarding all items for the present sample was .80.

Information Acquisition

A 6-item scale was adapted from Ferreras-Méndez et al. (2015) to measure the information acquisition of the elderly from two aspects, namely, the breadth and depth of information acquisition (J. Chen et al., 2011; Wang et al., 2020). The breadth is represented by the number of accesses or sources of information (X. Zhang & Lu, 2015). Specifically, the questionnaire measured the length of time spent by the elderly on various items through six common ways of information acquisition. The items were as follows, “How long do you chat online (by WeChat or QQ, etc.) every day?”, “How long do you talk on the phone every day?”“How long do you spend reading online news every day?”“How long do you spend reading newspapers every day?”“How long do you spend watching TV every day?” and “How long do you spend communicating with people face to face every day?” Answers to each statement were based on a 5-Likert type scale ranging from 1 to 5 (1 represents none; 2 means less than 30 min; 3 stands for 30 min to 1 hr; 4 refers to 1 to 2 hr, and 5 signifies more than 2 hr).

For the depth of information acquisition, many studies have found low credibility with “the more, the better” view in domains such as team project collaboration, knowledge search in economics, and social information sharing in sociology (Ismail et al., 2019; Lemi & Zeynep, 2018; Sebastian et al., 2018; C. Z. Zhang & Zhou, 2020). Therefore, this study uses the dimensions of information acquisition divided into depth and breadth to measure the effect (quantity and quality) of information acquisition. This helps obtain more reliable data to verify our assumptions. To this end, the breadth of information acquisition was obtained by calculating the number of statements participants responded to on each of the six common ways of information acquisition (1 represents few, and 6 stands for very much). The depth of information acquisition was obtained by calculating the minutes and hours regarding each of the six common statements. Finally, the variable of information acquisition was obtained by calculating the mean value of the breadth and depth of information acquisition. Cronbach’s alpha regarding the present sample was .77.

Perceived Community Support

Recognizing that the family, community, and broader societal context can influence the perceptions and behaviors of community members or residents (Kuo et al., 2021; Moussaïd et al., 2013), we utilized the Multidimensional Scale of Perceived Social Support (MSPSS) (Zimet et al., 1988) as a reference. Additionally, drawing from prior efforts, such as providing body temperature monitoring services (Kuo et al., 2021), we devised a 5-item scale to measure the elderly’s perceived community support during the COVID-19 pandemic (e.g., “My community has implemented strict measures to restrict people’s in and out via checking each pass” and “My community has popularized the knowledge of pandemic prevention and control of COVID-19 for its residents”). Each item was registered based on a 5-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). Cronbach’s alpha of the present sample was .83.

Positive Coping Behavior

Combined with the Chinese government’s response and suggestions to the public and the research on COVID-19 protective behavior (Cheng et al., 2020; O’Shea et al., 2021), the elderly’s positive coping behavior was measured by a 5-item scale adapted from the 21-item Utrecht Proactive Coping Competence scale (UPCC) (Bode et al., 2008). Sample items were “During the COVID-19 pandemic, I reduced unnecessary travel” and “During the pandemic, I had regular ventilation at home”. The 5-point Likert-type scale was employed (ranging from 1 = strongly disagree to 5 = strongly agree) for responses, and Cronbach’s alpha regarding the present sample was .84.

Data Analytical Strategy

First, the Kaiser-Meyer-Olkin coefficient (KMO ≥ 0.60) and Bartlett test (significance p < .001) were performed using SPSS (25.0) to determine whether the data was suitable for further confirmatory factor analysis (CFA) in AMOS (24.0) (Kaiser & Rice, 1974; Vignola & Tucci, 2014). Subsequently, the CFA within AMOS (24.0) was applied to test whether the measurement model fit our data (Hu & Bentler, 1999). The following indices were considered for evaluating the overall model fit: root-mean-square error of approximation (RMSEA ≤ 0.08 means acceptable fit, ≤0.05 indicates good fit; Browne & Cudeck, 1992; Steiger, 2010), standardized root-mean-square-residual (SRMR ≤ 0.08 means acceptable; ≤0.05 indicates good fit; Kline, 2015), comparative fit index (CFI ≥ 0.95 means good fit; Bentler, 1990; Kline, 2015), normative fit index (NFI ≥ 0.90 indicates good fit), goodness-of-fit index (GFI ≥ 0.90), incremental fit index (IFI ≥ 0.90) and non-normed fit index (NNFI ≥ 0.90; Hsu et al., 2012; L. P. Yang et al., 2020). The chi-square/degrees of freedom ratio (χ²/df) was also employed, with a value below 3 indicating acceptable (Wheaton et al., 1977). The structural equation modeling (SEM) approach was then utilized to test our proposed conceptual model in AMOS (24.0). More specifically, we tested the mediation effects following the bootstrap estimation procedure (with a bootstrap sample of 5,000 and a 95% confidence interval). A significant effect was detected when zero was not included in the 95% confidence interval (95% CI; MacKinnon, 2012).

Results

Measurement Model

The measurement model consisted of 6 latent variables (network size, network strength, network heterogeneity, information acquisition, perceived community support, and positive coping behavior) with 20 corresponding observed indicators. An initial test of the measurement model revealed a satisfactory fit to the data: χ² = 432.65, χ²/df = 2.79; RMSEA = 0.04; SRMR = 0.04; CFI = 0.96; GFI = 0.96; TLI = 0.95. All factor loadings for the indicators on the latent variables were significant (p < .001), indicating that all the latent variables were well represented by their respective indicators. Means, standard deviations, and correlations between all tested variables are presented in Table 2. As indicated in Table 2, the positive coping behavior of the elderly was positively associated with network size, network strength, network heterogeneity, and perceived community support, while negatively associated with information acquisition, indicating that more information acquisition would associate with less positive coping behavior.

Table 2.

Descriptive Statistics and Correlations Between Variables.

Variable	Mean	SD	PCB	NSI	NST	NH	PCS	IA
PCB	4.36	0.59	1.00
NSI	3.45	0.73	0.21**	1.00
NST	3.93	0.58	0.29**	0.44**	1.00
NH	3.55	0.72	0.23**	0.48**	0.39**	1.00
PCS	4.16	0.63	0.55**	0.26**	0.34**	0.22**	1.00
IA	3.20	0.88	−0.09*	0.23**	0.24**	0.24**	0.05	1.00

Note. PCB = positive coping behavior; NSI = network size; NST = network strength; NH = network heterogeneity; PCS = perceived community support; IA = information acquisition.

p < .01. **p < .001.

Structural Model

The direct path coefficient from the predictors (network strength, network heterogeneity, and information acquisition) to the dependent variable (COVID-19 positive coping behavior of the elderly, β = .21, p < .05; β = .16, p < .01; β = −.12, p < .01) in the absence of mediators was significant, while the direct path coefficient from network size to positive coping behavior of the elderly was insignificant (β = −.10, p > .05). A partial mediation model (Figure 2) with a mediator and a direct path from social network and information acquisition to positive coping behavior of the elderly revealed a good fit to the data (Table 3).

Figure 2.

The validated structural model.

Table 3.

Fitting Indices for Hypothesized Model and Adjusted Model.

Model	χ²/df	RMSEA	SRMR	TLI	GFI	IFI	CFI	AIC	ECVI	p
Hypothesized model	2.79	0.04	0.04	0.95	0.96	0.96	0.96	542.65	0.59	<.001
Adjusted model	1.96	0.03	0.03	0.97	0.97	0.98	0.98	414.12	0.45	<.001

Note. RMSEA = root mean square error of approximation; SRMR = standardized root mean square residual; GFI = goodness-of-fit index; IFI = incremental fit index; NNFI = non-normed fit index; CFI = comparative fit index; AIC = Akaike information criterion; ECVI = expected cross-validation index.

A series of fit indices were used to evaluate the goodness-of-fit of the default model, as shown in Table 3. SRMR values for the hypothetical and adjusted models were below 0.05. RMSEA values for both models were 0.04 and 0.03, which were also below 0.05. The GFI, IFI, NNFI, and CFI indices in these two models were above 0.90. Akaike information criterion (AIC, smaller values indicate a better fit of the model; Akaike, 1987) and expected cross-validation index (ECVI, a smaller value exhibits more significant potential for replication; Browne & Cudeck, 1992) were additionally examined to compare the two models. The covariance between the two residual items was observed in the modification indices, and a correlation path was subsequently added between the two residuals with the most significant covariance. This procedure was repeated until these values of the adjusted model were lower than the values of the saturated model. Taken together, the adjusted model fitted our data better.

In this study, it is worth pointing out that Mardia’s (1970) coefficients for multivariate kurtosis (Mardia’s kurtosis = 106.26) were above 5 (values > |5.00| indicative of non-normality; Bentler, 2005; Mardia, 1970). Although maximum likelihood (ML) estimation is apparently robust to many violations of underlying assumptions (Muthén & Kaplan, 2011), when data reveal evidence of multivariate kurtosis, interpretations based on the usual ML estimation may be problematic (Byrne, 2001). Due to the lack of multivariate normality, the Bollen–Stine bootstrap procedure (performed 5,000 times) was used to correct fit statistic bias (Bollen & Stein, 1992). After Bollen–Stine bootstrapping correction, a set of the fitting indices indicated good model fit (χ² = 176.52, df =148, χ²/df = 1.19, RMSEA = 0.01, TLI = 0.99, GFI = 0.97, IFI = 0.996, CFI = 0.995).

Bootstrapping procedures were used to test the significance of the adjusted partial mediation model (Preacher & Hayes, 2004; Zhao et al., 2010), and the 95% confidence intervals (CI) for the standardized indirect effects were calculated with 5,000 bootstrapping techniques from the original data set (N = 916). As expected, the partial mediating effect of perceived community support within the relationship between network strength and positive coping behavior was significant (as shown in Table 4). However, the mediating effect of PCS within the relationship between network size and positive coping behavior, and the link between network heterogeneity and positive coping behavior was not significant (see Figure 2).

Table 4.

Standardized Indirect Effects with 95% Confidence Intervals.

Model pathways	Estimated	95% CI
Model pathways	Estimated	Lower	Upper
NSI → PCS → PCB	0.04	−0.06	0.15
NST → PCS → PCB	0.35	0.22	0.52
NH → PCS → PCB	0.03	−0.05	0.12
IA → PCS → PCB	−0.04	−0.07	−0.01

Note. PCB = positive coping behavior; NSI = network size; NST = network strength; NH = network heterogeneity; PCS = perceived community support; IA = information acquisition. The empirical 95% confidence interval does not overlap with zero.

Discussion

This study explored factors predicting the positive coping behavior of the elderly via a new perspective by testing a proposed conceptual model in which social network, information acquisition, and perceived community support are considered significant in coping with the COVID-19 pandemic. The findings, derived from a large sample of Chinese elderly individuals (N = 916), revealed that social network factors (specifically, network strength and network heterogeneity) and information acquisition were directly associated with positive coping behavior related to COVID-19. Importantly, these associations were also found to be mediated by perceived community support, supporting the hypotheses, and providing valuable insights into the intricate connections between social network, information acquisition, and positive coping behavior within the context of the COVID-19 pandemic.

More specifically, our findings confirmed that social network plays a positive and significant role in the elderly’s positive coping behavior during COVID-19. Network strength was found to predict positive coping behavior directly and indirectly (through perceived community support). In other words, strong social ties could help the elderly respond more positively to turbulent challenges (Bian, 1997; Horak et al., 2019). This finding contradicted earlier studies that did not target the specific elderly group and suggested that weak ties promote positive behavior (Granovetter, 1973). Also, while strong social relationships are known to provide individuals with greater support (Jack, 2005; McGuire & Bielby, 2016), the present findings revealed that the expansion of network size did not necessarily predict increased social support for the elderly. This challenges the notion that simply increasing the number of individuals in one’s network ensures effective support for the elderly (Beach et al., 2018), and implies that, in the context of the COVID-19 pandemic, expanding the social network by meeting more new people to increase breadth may not significantly impact positive coping behavior. Instead, the depth of the social network, where individuals share intense, well-connected relationships, holds significance (Carmel et al., 2017). Particularly, when coupled with good relationship quality, such depth can significantly influence well-being and positive outcomes (Vaillant, 2021). Therefore, during the COVID-19 pandemic, it is essential to stay in touch and establish strong connections with family members, friends, and community members through various social media platforms for information (Embarak et al., 2021). Maintaining close contact while also improving the relationship quality (Vaillant, 2021) will effectively relieve the elderly’s anxiety, loneliness, and other negative emotions, and meet their spiritual needs to improve the knowledge and ability to use the psychological balance to deal with epidemic diseases (Ashokkumar & Pennebaker, 2021).

Concerning network heterogeneity on positive coping behavior, in line with our expectations, the specific direct effect of social network heterogeneity on positive coping behavior was positive and significant among the elderly. This also favors the previously reported model of positive coping behavior (Kim & Kim, 2017; Sohn et al., 2017). As high levels of network heterogeneity can promote people’s political participation and encourage people to adopt COVID-19 positive coping behavior, the highly heterogeneous social network can indeed provide the necessary diversified support for the elderly due to its diversity of people with a variety of age groups, professions, and education backgrounds, thus, making the elderly take advantage of more positive coping behavior in public health emergencies (He et al., 2023; Scheufele et al., 2006). Therefore, further enriching the elderly’s social network relationships by developing different groups of social networks (network heterogeneity) is conducive to promoting positive coping and physical and mental health and well-being (Kim & Kim, 2017).

Regarding the effect of information acquisition on the positive coping behavior of the elderly, our findings contradicted previous studies, which indicated that higher levels of information access could promote people’s positive coping behavior (Greco et al., 2018; Hua & Howell, 2022). Also, our research is different from what information literacy expects, which encourages people to acquire relevant information by mastering information tools, improving their understanding of knowledge, and using information to solve practical problems (Zurkowski, 1974). For the elderly, however, a higher level of information acquisition does not guarantee a higher quality of information. One possible explanation is that too much information or information load exposed to the elderly may bring about confusion. It is, therefore, possible that the overall quality of information, irrespective of the breadth or depth, can help the elderly, which is consistent with Irwin’s research on the impact of information accuracy on behavior (J. Chen et al., 2011; Irwin, 2020). For instance, actively acquiring accurate information and knowledge about the COVID-19 pandemic helps motivate the elderly to adopt positive coping behavior (i.e., social distancing, meeting avoidance, hand washing, and mask-wearing; Li et al., 2021). Moreover, as the internet continues to evolve, it has become a crucial avenue for the elderly to access health information (Salive, 2013). However, there is a need to protect the elderly from the potential risks of information overload and low digital literacy, which can lead to an “information cocoon room” effect. In this regard, community organizations play a vital role in nurturing leaders within the community who can serve as effective channels for disseminating information. These leaders can assist the elderly in acquiring and comprehending information accurately, helping them develop healthy information search habits. Their influence is crucial in promoting proactive responses among the elderly.

Our results revealed a partial mediation effect that the perceived community support played between network strength and positive coping behavior, which also confirmed prior works (Clare et al., 2021; Jiang et al., 2017). This is consistent with the understanding of expanding the social network of the elderly to strengthen their resistance to changes (Harling et al., 2020; Harper et al., 2016). The elderly need comprehensive, stable, and in-depth communication to maintain their health and well-being. As the primary carrier of social relations, the community where the elderly perform their daily activities should provide access to information (Tang et al., 2017). For instance, consider establishing a dedicated social platform that facilitates interaction and communication among the elderly, allowing them to engage with peers and professionals. This platform can provide a space for sharing experiences, discussing problems and solutions, and promoting information exchange and community support. The goal is to encourage the elderly to develop meaningful relationships within social networks, creating an environment that fosters the transmission of information and mutual assistance within the community. By implementing these social network measures, the perceived impact of community support can be maximized, leading to enhanced positive coping behaviors among the elderly.

In addition, perceived community support partially mediated the link between information acquisition and positive coping behavior. In response to the call for research on personal information access during the global health crisis (Xie et al., 2020), this study explored the elderly who cannot obtain effective information through verification. As research pointed out, although the elderly have different access to information from other groups (Armitage & Nellums, 2020), their perceived community support can be enhanced through the community resources that they can use to exchange information (Bussone et al., 2017). Meanwhile, despite the necessary quarantine of residential communities, community workers can also provide timely help to vulnerable elderly people to promote their perception of community support (Q. Yang et al., 2021), thus encouraging their positive coping behavior (Cherewick et al., 2018). For example, community organizations can proactively create dedicated online support groups for elderly individuals to provide them with real-time, accurate, and concise information. These organizations can also enhance health awareness and digital literacy among the elderly through educational activities like seminars, lectures, and training courses. This approach aims to improve their understanding and utilization of health information. By implementing these measures, community organizations can harness the influence of perceived community support and promote positive coping behaviors among the elderly. These efforts also contribute to improving their information acquisition capabilities and their ability to respond effectively to potential risks.

This work makes three significant contributions. Firstly, the findings are grounded in a population of 916 Chinese elderly individuals ranging from 60 to 96 years old. This large and diverse sample size contributes robust empirical evidence, fortifying the support for theoretical literature (i.e., weak ties theory and information literacy). Secondly, many concurrent studies often concentrate on the direct impact of perceived community support on behavior, often overlooking the underlying mechanisms (e.g., Andersen et al., 2020; Greaney et al., 2018). In contrast, this study adopts a Structural Equation Modeling (SEM) approach to uncover the contributing factors (social network, information acquisition, and perceived community support) that may predict positive coping behavior. This methodology allows for an in-depth examination of the underlying mechanisms at play. Lastly, and of paramount importance, this study addresses the unique challenges faced by the elderly, a vulnerable population more susceptible to the threats of the COVID-19 pandemic due to potential limitations in acquiring external information efficiently (Pedreanez et al., 2021).

This study has limitations that should be acknowledged for future research considerations. Firstly, our sample is confined to Chengdu, a capital city in Southwest China. Therefore, future efforts to generalize the present findings may benefit from including elderly populations from other regions in China and from different countries and cultural backgrounds. Additionally, due to the cross-sectional nature of our survey data, establishing causal inferences is not possible. We cannot definitively assert that an improved social network leads to more positive and effective coping strategies for the elderly. Future studies employing experimental or longitudinal designs are necessary to test such causal inferences. Thirdly, although our survey tools were derived from literature scales with acceptable reliability and validity, they underwent translation procedures, and cultural differences may introduce misperceptions that could impact the results. Moreover, it is essential to note that positive coping behavior is influenced by various factors, including personal, contextual, economic, and educational aspects, beyond those explored in this study. Therefore, future research could employ Structural Equation Modeling (SEM) with more comprehensive indicators and qualitative comparative analysis to explore their combined effects on the positive coping of the elderly.

Conclusions

In the crisis of the COVID-19 pandemic, the elderly, whose immunity and reaction are weaker and slower than the other age groups, deserve more attention to their health and well-being. However, scientific research and corresponding suggestions on how to help them cope effectively with COVID-19 are emergently needed. Through the investigation of the 916 Chinese elderly, we found that the network strength and heterogeneity (instead of network size) of the social network, along with the information acquisition, significantly predicts positive coping behavior. Besides, perceived community support partially mediates the relationship between the elderly’s social network (network strength and network heterogeneity) and positive coping behavior. Thus, theoretical guidance and practical concerns about helping the elderly cope with public health crises (i.e., COVID-19) are proposed.

Footnotes

Acknowledgements

We would also like to express our gratitude to Xue Zhang and Mei Xie for their invaluable support in data collection and advice in manuscript revision.

Authors’ Contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and have approved it for publication.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by the National Social Science Foundation of China (20BZZ079), Research Center for Social Development and the Social Risk Control of Social Science Key Research Base of Sichuan Province (SR20A13), the National Natural Science Foundation of China (72271205, 71801180).

Ethical Approval

This survey has been approved by the Ethics Committee of the Psychological Society of the first author’s institution. This survey has been conducted according to the Declaration of Helsinki (1964) and its later amendments or comparable ethical standards. All participants have read and agreed to the informed consent document. Their participation was voluntary, allowing them to withdraw at any time without providing a reason and without incurring any costs.

ORCID iD

Yanhui Mao

Data Availability Statement

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

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