Abstract
A large literature emphasizes the importance of social relationships during the caregiving process. Yet these issues are seldom presented in a social network framework that examines the structure of caregivers’ personal networks. In this study, I examine how older caregivers experience changes in personal network structure. Using two waves from the National Social Life, Health, and Aging Project, I investigate whether caregivers are more or less likely to exhibit bridging or bonding capital potential compared to noncaregivers. I find that older adults transitioning into caregiving are more likely to develop the ability to bridge social ties within their personal networks than noncaregivers despite potential constraints in their personal freedom. Caregivers in the latter stages, meanwhile, do not differ from noncaregivers in terms of network change. These findings have implications for older adults’ potential to pool resources across social domains as well as negotiate stress and well-being during the caregiving process.
The rising age of the population, alongside limited formal care options in the United States, has placed many Americans first in line to provide care for a loved one in the event of a health decline. Longevity gains among older adults also mean that individuals are adopting the informal caregiver role at later ages. In 2011, approximately 11 million older adults provided care to another without pay (Federal Interagency Forum on Aging-Related Statistics, 2016). Depending on its intensity, informal caregiving may heighten the need for social support as well as create tension among preexisting social relationships. Consequently, considerable research addresses the relationship between social networks and caregiving in later life. Some studies focus on the networks providing care to the recipient (e.g., Koehly et al., 2015), whereas others privilege the personal networks of the caregivers themselves (e.g., Carpentier & Ducharme, 2005). Although the former is fundamental to the quality of care provided, the latter determines how individuals pool social resources as well as negotiate stress and well-being (Berkman & Glass, 2000; Smith & Christakis, 2008).
Classical theories of aging emphasize the value of dense, kin-centered personal networks (Antonucci & Akiyama, 1987; Charles & Carstensen, 2010). These networks allow well-acquainted individuals to coordinate their efforts around an older adult during a time of need (Ashida & Heaney, 2008; Schafer & Koltai, 2014). Network theorists refer to this as bonding social capital because the network structure implies that individuals use their mutual connections to form strong social bonds (Coleman, 1988). In the case of caregiving, older adults may derive support from an interconnected group of network members.
By contrast, bridging social capital notes the benefits of diverse networks in which not all individuals know each other (Burt, 2001). These networks provide two distinct advantages. First, exposure to a diversity of people increases the chances of receiving novel information, which helps individuals make health-related decisions (Goldman & Cornwell, 2015; Perry & Pescosolido, 2010). Second, the ability to bridge disconnected social ties offers a sense of independence from group conflict (Cornwell, 2011). Given that caregivers make important decisions about the care recipient—which can require special knowledge and create tension among family members (Knussen et al., 2005)—they may benefit from assembling personal networks that are rich in bridging social capital rather than maintaining dense bonding networks.
Despite its prevalence in society, caregiving remains an unexpected role transition that disrupts the daily lives of older adults (Aneshensel et al., 1995). Individuals who adopt the caregiving role must navigate a range of formerly unnecessary responsibilities (e.g., assisting with activities of daily living, coordinating physician visits). The accumulation of these care-related responsibilities tends to compound with routine daily demands (e.g., preparing meals, personal errands) thus creating the need for help (Pearlin et al., 1997). Consequently, individuals turn to others for emotional and instrumental support in the wake of such a role transition (Pescosolido, 2011). Empirical research suggests that the transition into caregiving is frequently followed by notable changes within caregivers’ personal networks (Carpentier & Ducharme, 2005; Suitor & Pillemer, 1996). For instance, older adults who transition into informal caregiving have been found to exhibit higher rates of personal network turnover compared to noncaregivers (Roth, 2018). However, little is known about the structure of older adults’ personal networks as they undergo the caregiving process. In the present study, I adopt a social network framework to assess whether older caregivers are more or less likely to develop bridging or bonding capital potential compared to noncaregivers. To explore these issues, I analyze personal network data from the National Social Life, Health, and Aging Project (NSHAP), a nationally representative panel study of older Americans.
Caregiving and Social Networks
The caregiving experience, like other unfamiliar life-course disruptions, is largely facilitated by social interactions with others (Pescosolido, 2011; Pillemer & Suitor, 2000). Most obvious among these interactions are those between the caregiver and care recipient. Prior studies demonstrate that the characteristics of this relationship are vital to determining the quality of care provided and caregiver well-being (Litwin et al., 2014; Pinquart & Sörensen, 2011). Yet caregivers maintain multiple social relationships that extend beyond the caregiver–recipient dyad (Roth, 2018).
Caregivers with supportive family, friends, and health care professionals typically have more manageable experiences than those who are either socially isolated or who routinely interact with an uncooperative social network (Francis et al., 2010; Pearlin et al., 1990; Sherman et al., 2013). The latter group includes nonsupportive individuals as well as those who are willing to provide support but are so overbearing that their actions cause more harm than good. For example, Suitor and Pillemer (1993) found that when caring for their parents, adult children frequently reported their siblings as sources of instrumental support and interpersonal stress.
Despite increasing interest in social relationships during caregiving, studies seldom adopt an explicit social network framework (cf. Carpentier & Ducharme 2005; Roth, 2018). Beyond enumerating all people with whom individuals share direct relationships, social networks represent the web of interconnections between network members (Perry et al., 2018). Acknowledging the structure of ties between network members is important because individuals do not function independently of one another. Caregivers are especially sensitive to network structure because the decisions they make regarding the care recipient are influenced and scrutinized by a larger group of individuals. Therefore, it is instructive to address the ways in which caregiver’s personal network members are (or are not) connected to each other.
Social Capital: A Network Perspective
Scholars widely acknowledge that social capital influences how individuals negotiate stress and well-being during uncertain times (Berkman & Glass, 2000; Kawachi et al., 2008; Song et al., 2010). However, there is little consensus on how to conceptualize social capital. From a network perspective, it refers to the resources residing within a set of social relationships (Lin, 2001). 1 The ability to leverage personal stocks of social capital for one’s own gain depends on the characteristics of network members and the degree to which they are interconnected (Burt, 2001). Research in the network tradition identifies two competing perspectives of social capital. In the following subsections, I highlight these perspectives and consider how they relate to informal caregiving.
Bonding Social Capital
Classical network accounts of social capital view it as a collective resource that flows through tightly knit social networks (Bourdieu, 1986; Coleman, 1988). The key idea is that individuals use their shared connections to derive benefits by virtue of the cohesive nature of the network. Bonding social capital, therefore, is recognized by high degrees of interconnectivity between network members. Individuals embedded within dense personal networks have lots of bonding social capital potential (Perry et al., 2018).
During the early stages of caregiving, individuals frequently call upon social relationships for emotional and instrumental support (Carpentier & Ducharme, 2005; Suitor & Pillemer, 1993). Because it is easier to coordinate group support when network members routinely interact with each other, caregivers may be incentivized to disengage with peripheral ties and focus their energy on central members within their personal networks. Additionally, caregiving restricts opportunities to engage in leisure activities with independent social ties (Wiles, 2003). Based on these insights, I propose the bonding capital hypothesis: Older adults transitioning into caregiving are more likely to develop bonding social capital potential than noncaregivers. Assembling a dense network that is rich in bonding capital potential would benefit older caregivers by buffering them from undesirable stressors as well coordinating care-related tasks.
Despite its advantages, bonding social capital has drawbacks. Individuals with dense networks may be subjected to excessive demands or criticism when involved in controversial situations (Portes, 1998). This proves troublesome for older adults who are located within networks of conflict while making important care-related decisions about a loved one (Widmer et al., 2018). Moreover, interacting with a group of people who are closely connected limits opportunities to receive nonredundant information (Burt, 1992; Granovetter, 1973). Those new to caregiving must face unfamiliar situations (e.g., making medical decisions on behalf of another) during which time they would benefit from multiple perspectives. However, they are likely to be unaware of alternative care-related options if they consistently interact with the same interconnected social group (Goldman & Cornwell, 2015). Given these issues, caregivers may look beyond their immediate relationships to diversify their networks.
Bridging Social Capital
In contrast to bonding social capital, the bridging perspective highlights the advantages of maintaining independent social ties (Burt, 2001). Individuals act as bridges in a network when they are connected to at least one network member who is not directly connected to any of the other members in the network. To illustrate network bridging potential, Figure 1 displays two hypothetical personal networks. In Network A, there is no bridging potential as all network members are interconnected. Conversely, there is one member in Network B who is disconnected from the others. This enables the focal individual to pool resources across social domains and maintain independence from group sanctioning (Burt, 1992; Lin, 1999).
Examples of network bridging potential. Note. Two hypothetical personal networks demonstrating network bridging potential among respondents. White nodes represent respondents, black nodes represent network members, and lines indicate that individuals are socially connected.
A key assumption of the bonding capital hypothesis is that ties between network members automatically promote group cohesion. But under the wrong conditions (e.g., interpersonal disputes), dense networks foster a hostile social atmosphere (Widmer et al., 2018). This is problematic as negative social interactions are more consequential for older adults’ health and well-being than the positive aspects of social relationships (Antonucci, 2001; Newsom et al., 2005; Sherman et al., 2013). Therefore, it would be better to dissolve preexisting negative relationships upon adopting the caregiving role. However, if the network members have an unconditional presence in their lives (e.g., immediate family), caregivers may mitigate the situation by adding social ties who are not privy to the source of conflict (e.g., nonpartisan friend).
Caregivers may also develop new relationships even if they are satisfied with their pre-caregiving networks. The transition into caregiving will likely expose older adults to new social settings (e.g., support groups, health care facilities) through which they may meet people who have a small chance of knowing anyone within their personal networks (Feld, 1981; Small, 2017). If they form relationships within any of these people, the caregivers will inadvertently develop the ability to bridge ties within their network. Collectively, these considerations inform the bridging capital hypothesis: Older adults transitioning into caregiving are more likely to develop bridging social capital potential than noncaregivers. The ability to bridge ties within a network would benefit caregivers by increasing their access to pertinent information and resources as well as preserving social autonomy.
Study Contributions
This study uses a social network framework to investigate social capital potential among older caregivers. Social networks are important because they facilitate access to social support and resources (Perry et al., 2018). Moreover, certain formations of ties between network members cause social tension which can be more debilitating than helpful (Widmer et al., 2018). Although the benefits and detriments of social networks are universally important in later life (Cornwell & Schafer, 2016), older caregivers are especially sensitive to these effects as their caregiving responsibilities increase the need for emotional and instrumental support. Yet little is known about the structural formation of caregivers’ personal networks. To address this gap in the caregiving literature, I assess the association between caregiving status and changes in social capital potential in later life.
Research Design
This study uses data from the NSHAP, a nationally representative panel of older Americans. The NSHAP is ideal for examining changes in network structure because it contains detailed personal network measurements across waves. The NSHAP sampling frame was designed using a multistage area probability method that oversampled on age, gender, and race/ethnicity. Wave 1 (W1) was gathered in 2005–2006 and included in-home interviews of 3,005 noninstitutionalized respondents between the ages of 57 and 85. In 2010–2011, 2,261 respondents were reinterviewed as part of wave 2 (W2). Although the NSHAP was not designed to study caregiving, respondents were asked to complete a leave-behind questionnaire (LBQ) that included questions about caregiving. In total, 1,589 completed the interview and LBQ during both waves. Further details regarding the NSHAP survey design are found elsewhere (O’Muircheartaigh et al., 2014).
Social Capital Potential
This study analyzes changes in older adults’ social capital potential during the caregiving process. Specifically, I compare personal network structures across waves for caregivers and noncaregivers. Network structure was assessed using data from the core discussion network module of the NSHAP. Starting at W1, interviewers asked respondents to list up to five people with whom “you discuss things that are important to you” during the past year. During W2, interviewers used a computer-assisted program interviewing (CAPI) exercise to ask the same questions. Upon recording the W2 networks, the CAPI displayed a visual representation linking matches between the W1 and W2 network rosters. Respondents verified whether the matches were accurate and corrected any mismatches.
After delineating the network, interviewers asked how often each network member interacts with the others. To measure social capital potential, I first counted the number of members who were not directly (or only poorly) connected with any other members within the network. 2 I consider a network member to be a bridging tie if the respondent reported that the member never spoke with any other network member or spoke with them less than once a year (Cornwell, 2009b). 3 Because the majority of respondents reported no bridging ties at either wave and a small percentage of respondents reported having only bridging ties, I dichotomized this measure such that respondents were considered to exhibit bridging potential if they had one or more bridging ties. Dichotomizing this measure allows some network members to be connected so long as there is at least one network member who is completely disconnected from all other members. Otherwise, respondents were considered to exhibit bonding potential if they reported no bridging ties (i.e., every network member was connected to at least one other member). Because I am interested in network change, the dependent variable consists of four mutually exclusive outcomes: (1) constant bonding (i.e., maintains bonding potential across waves), (2) constant bridging (i.e., maintains bridging potential across waves), (3) change to bridging (i.e., bonding potential at W1 → bridging potential at W2), (4) change to bonding (i.e., bridging potential at W1 → bonding potential at W2).
Caregiving Status
Caregiving status was assessed by asking respondents “Are you currently assisting an adult who needs help with day-to-day activities because of disability or age?” Due to the longitudinal nature of the data, there were four possible statuses: transition into caregiving (adopted role between waves), long-term caregiving (maintained role across waves), transition out of caregiving (dropped role between waves), and noncaregiving (no caregiving role in either wave). Although I am primarily interested in comparing those transitioning into caregiving against noncaregivers, I include respondents occupying all four statuses in order to determine whether network changes also occur in the latter stages of the caregiving process. Because the NSHAP was not specifically designed to study caregiving, there is heterogeneity in the types of care being provided. Supplementary Table 1 provides a distribution of the different types of caregiver–care recipient relationships.
Control Variables
I control for race/ethnicity (“White,” “Black,” “Hispanic,” and “Other”), gender, age, and education (“< high school,” “high school,” “some college,” and “college”) as these variables are associated with social capital potential in later life (Cornwell, 2009a). Given the importance of other life transitions on personal network change, I control for changes in marital and occupational status changes across waves. I also control for depressive symptoms and functional health, both measured at W1. Depressive symptoms are measured using a modified version of the Center for Epidemiologic Studies Depression Scale, which is the average of the standardized responses to 10 ordinal items (α = .79). Functional health is measured using the Activities of Daily Living Index by averaging the ordinal item responses from seven questions (α = .84) that assess the degree of difficulty respondents have performing daily tasks. Finally, I control for network size and proportion kin at baseline.
Missing Data
One disadvantage of the social capital measure is that it eliminates respondents who reported ties to less than two network members at either wave. Because social capital is the central focus of this study, the final analysis pertains only to respondents with two or more network members. 4 In total, 223 respondents were excluded due to the network criterion. An additional 6 respondents were excluded due to missing occupational transition data. After dropping these 229 respondents from the 1,589 that completed the interview and LBQ during both waves, the analytical sample is 1,360. I discuss how I address issues of selection bias in the following sections.
Analytic Strategy
I begin by describing the distribution of social capital potential within the sample. Next, I use multinomial logistic regression models to estimate the association between caregiving and social capital across waves. These models allow me to simultaneously assess multiple possibilities of either change or stability within a respondent’s network structure. I use “constant bonding” as the referent outcome because (a) it is theoretically the most likely scenario in later life (Charles & Carstensen, 2010) and (b) the majority of respondents in the sample reported having no bridging ties at either wave. Therefore, the odds of experiencing each of the other three outcomes are in reference to maintaining bonding potential across waves. To ease interpretation, I also calculate the predicted probabilities of each outcome to assess the differences between caregivers and noncaregivers.
The final models adjust for the clustering and stratification of the survey design by using the NSHAP-supplied person weights to account for the probability being included in the sample. The weights account for selection bias at W1 and attrition at W2. In order to readjust for the fact that I use a subsample of W2 respondents for my analytic sample, I estimated a logit regression using W1 sociodemographic and health variables as predictors. I use the inverse probability from this regression and multiply it by the NSHAP person weight. These new weights appropriately adjust for the fact that not all W1 respondents are included in the analytic sample (Austin, 2011).
Results
Table 1 shows the descriptive statistics for all variables used in the final analysis. Over half of the respondents (53%) reported having zero bridging ties at either wave. An additional 20% changed from bridging to bonding across the study period. In other words, these respondents lost the ability to act as bridges between network members during W2. Conversely, 16% of respondents demonstrated changes in the opposite direction as they developed the ability to bridging ties within their personal networks at W2. Constant bridging was the least common outcome as just 11% of respondents reported at least one bridging tie at both waves. These initial findings indicate that despite the appreciable heterogeneity in personal network structure within the sample, the majority of respondents either maintained or developed bonding networks. However, the purpose of this study is to determine whether older adults who serve as caregivers experience significant changes in their social capital potential compared to their non-caregiving counterparts. Thus, I turn to the multivariate analyses to assess the associations between caregiving and social capital.
Descriptive Statistics.
Note. N = 1,360. ADL = activities of daily living; CES-D = Center for Epidemiologic Studies–Depression Scale; HS = high school. W1 = Wave 1; W2 = Wave 2. All statistics are weighted.
Caregiving and Social Capital Potential
Table 2 presents results from the multinomial logistic regressions. 5 The relative risk ratios (RRR) in each model can be interpreted as the odds that a respondent experiences that particular outcome rather than the constant bonding outcome. For example, the third column in Model 1 shows that the odds of developing bridging potential (vs. constant bonding) are greater for respondents who transition into caregiving compared to noncaregivers, controlling for sociodemographic variables, health, and baseline network characteristics (RRR= 1.91, SE = 0.56). This trend remained significant after the introduction of the marital and occupational transitions in Model 2 (RRR = 2.04, SE = 0.60). Figure 2 substantiates these findings by plotting the differences in predicted probabilities of social capital potential.
Multinomial Logit Models Predicting Changes in Network Structure.
Note. N = 1,360. Relative risk ratios are displayed (standard errors in parentheses). All outcomes are in reference to “constant bonding.” Models control for age, gender, race/ethnicity, activities of daily living, Center for Epidemiologic Studies–Depression, network size, and kin composition.
*p < .05. **p < .01. ***p < .001.
Difference in predicted probabilities of social capital potential by caregiving status (N = 1,360). Note. Differences are not significant if the 95% confidence interval overlaps the dashed reference line. The differences in probabilities are in comparison to the probability of noncaregivers experiencing each of the specified outcomes. Probabilities are derived from Model 2 in Table 2.
As seen in Figure 2, respondents who transitioned into caregiving were 10% more likely than noncaregivers to develop bridging capital potential during the study period. At the same time, these same respondents were neither more nor less likely to experience any of the other three outcomes compared to noncaregivers. There were no significant differences between long-term caregivers and noncaregivers nor between respondents who transitioned out of caregiving and noncaregivers.
Who Are the Bridging Ties?
Although the results from the regression models demonstrate group differences regarding network bridging potential, they provide minimal insight into the types of network members who serve as bridging ties. A supplementary tie-level analysis found that most bonding ties were kin whereas most bridging ties were nonkin, a finding that makes sense given that family members are often highly interconnected (Supplementary Table 2). Despite the numerous nonkin categories, the majority of non-caregiver’s bridging ties were friends (66%) as opposed to some other form of nonkin (e.g., neighbor, health professional, coworker). Respondents who transitioned into caregiving, meanwhile, reported that nearly one quarter of their bridging ties (24%) were neighbors, whereas 54% were friends.
A useful way to investigate the intricacies of network change is to assess which ties were added between waves as opposed to which ties were consistently reported in respondents’ networks across waves. Supplementary Table 3 shows that there were consistently more long-term bonding ties (i.e., present in W1 and W2) than newly added bonding ties across caregiving statuses. Conversely, there were almost twice as many bridging ties that were added between waves compared to long-term bridging ties.
Discussion
This study adopted a social network framework to assess whether older caregivers are more or less likely to exhibit bridging or bonding capital potential compared to noncaregivers. The central finding to emerge was that those who transitioned into caregiving developed greater potential to bridge ties within their personal networks compared to noncaregivers. In other words, older adults who adopted the caregiving role between waves were more likely to alter their networks to include at least one network member who was not connected with the rest of the members in the network. There was no evidence that the transition into caregiving was related to a shift toward bonding capital potential. These findings contradict the bonding capital hypothesis, which assumed that caregiving restricts individuals’ geographic mobility and leisure time (Wiles, 2003). Although these restrictions and the desire to maintain a strong support system should make it harder—not easier—to straddle multiple social domains, the analyses refuted the bonding hypothesis in favor of the bridging hypothesis. Overall, these findings have important implications as individuals with bridging networks more likely to have access to nonredundant information that could be used to guide care-related decision making. Moreover, bridging networks enable caregivers to freely discuss sensitive matters with a network member without worrying whether their remarks will be discovered by other members within their network.
Rather than presenting obstacles to bridging prospects, the transition into informal caregiving in later life heightens the potential for bridging social capital. There are several plausible mechanisms that may explain this finding. First, caregivers may be psychologically motivated to seek out functionally specific relationships to guide them through their recent transitions. Previous network studies on caregiving and other health-related transitions suggest that experiential homophily (i.e., the tendency to interact with those who have similar experiences) is a strong predictor of social tie activation (Perry & Pescosolido, 2015; Suitor et al., 1995). In order to talk to someone who had already gone through the caregiving process, however, the older caregivers may have to look beyond their preexisting discussion networks. If this were the case, they would likely be reaching out to a bridging tie. Second, individuals must be aware of each other’s existence before they can form social ties (Feld, 1981). Older caregivers may therefore develop the ability to bridge ties within their networks not necessarily through intention but simply because the transition into the role exposes them to new potential network members (Small & Sukhu, 2016). Third, caregivers may either gain or lose social ties through forces beyond their control. This could happen if someone they already knew but did not necessarily consider a close friend initiated contact after learning about their situation. Alternatively, network members may choose to dissolve ties with the focal respondent upon the latter’s transition into caregiving.
This study is not without limitations. First, the NSHAP does not contain data on how network ties were formed. As a result, any discussion of the mechanisms contributing to caregiver’s changes in social capital potential remains speculative. Second, it would have been useful to explore the personal characteristics of network members that may have furthered respondents’ access to social capital. For instance, network members with expert knowledge of the health care system could help guide caregivers through the difficult parts of the caregiving process if the care recipient requires intensive medical treatment. Third, I was unable to adequately distinguish between the types of caregiving. Given that the reasons for caregiving (e.g., dementia) and caregiver–care recipient relationship (e.g., spouse/nonspouse) are important to the overall caregiving experience (Litwin et al., 2014), future research should address these distinctions when exploring the link between caregiving and social network outcomes. Finally, as with all personal network studies, the networks analyzed in this study are merely a subset of a much larger social network. By analyzing a small group of people with whom respondents discuss matters, I am likely missing numerous other bonding and bridging ties that may be influential in their lives.
Conclusion
Despite these limitations, the present study highlighted how older adults experience changes in their personal networks during the transition into informal caregiving. Whereas previous research addresses how broad measures of social relationships and social support manifest during the caregiving process, this study employed a network perspective to understand how older adults could leverage their positions within a group of interconnected people to navigate their new responsibilities. Drawing on social capital theory, I showed how those transitioning into caregiving developed networks that enabled them to bridge multiple social worlds. However, future research must explore how this social capital potential translates into tangible outcomes such as caregiver health and quality of care. Moving forward, researchers should remain attentive to these issues as there is a strong link between social networks and well-being.
Supplemental Material
Supplemental Material, ROA_19_153_R1-Supplementary-materials - Informal Caregiving and Social Capital: A Social Network Perspective
Supplemental Material, ROA_19_153_R1-Supplementary-materials for Informal Caregiving and Social Capital: A Social Network Perspective by Adam R. Roth in Research on Aging
Footnotes
Acknowledgments
I thank Monica Kirkpatrick Johnson, Justin T. Denney, and Thomas Rotolo for their comments on this manuscript.
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) received no financial support for the research, authorship, and/or publication of this article.
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References
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