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. Author manuscript; available in PMC: 2024 Jan 1.
Published in final edited form as: Aging Ment Health. 2021 Nov 9;27(1):87–93. doi: 10.1080/13607863.2021.2000935

Positive Aspects of Caregiving in Incident and Long-Term Caregivers: Role of Social Engagement and Distress

Chelsea Liu 1, Victoria R Marino 2, Virginia J Howard 3, William E Haley 4, David L Roth 5
PMCID: PMC9126189  NIHMSID: NIHMS1801329  PMID: 34749554

Abstract

Objectives:

Positive caregiver adaptation over time may be associated with reports of positive aspects of caregiving (PAC). We examined differences in PAC by caregiving duration and social engagement, controlling for measures of distress.

Methods:

Participants included 283 African American or White caregivers from the Caregiving Transitions Study with a wide range of caregiving durations. PAC are defined as positive appraisals that caregivers report about their role, such as feeling appreciated or confident. We fit multivariable linear models with the total PAC score as the outcome to assess its association with years of caregiving and social engagement (social network, monthly social contact). Models were adjusted for age, sex, race, marital status, relationship to care recipient, care recipient’s dementia status, perceived stress and caregiving strain.

Results:

Caregivers with higher social engagement reported significantly higher PAC. A nonsignificant trend was found in most analytic models for caregivers with longer duration of care to report higher PAC. African American caregivers reported higher PAC compared to White caregivers. Dementia caregivers reported lower PAC than non-dementia caregivers in models adjusting for demographics and social network size, but the association was attenuated with the addition of caregiving strain.

Discussion:

Higher social engagement and longer duration of care tend to be associated with higher PAC after adjusting for demographics and measures of distress. Future studies should aim to leverage longitudinal data to understand whether caregivers shift appraisal to positive aspects of their role and explore implementation of caregiving interventions targeting PAC in order to improve the caregiving experience.

Keywords: family caregiving, long-term caregiving, positive aspects of caregiving, social network, social contact, adaptation

Introduction

An increasing number of older adults are caring for family members with chronic conditions (AARP and National Alliance for Caregiving, 2020). Studies have shown that caregiving is associated with adverse changes in psychological well-being such as increased perceived stress (Haley et al., 2020; Lyons et al., 2015). Other research, however, has suggested that while long-term caregivers could show declining well-being over time because of a wear-and-tear process, increased duration of caregiving could also be associated with the development of psychological resilience and positive adaptation (Townsend et al., 1989; Haley et al., 1989). An early study found that long-term caregivers who provided an average of 7.69 years of care were able to find meaning in their role (Noonan & Tennstedt, 1997). Compared to short-term caregivers, long-term caregivers may more fully integrate caregiving with their other life roles (Gaugler, Davey, Pearlin, & Zarit, 2000). These studies suggest that long-term caregiving could be a rewarding activity that leads to mastery, purpose in life, and finding positive aspects in the caregiving role.

Folkman’s (1997) revised stress process model suggests that when faced with challenging long-term tasks such as caregiving, finding benefits and meaning as well as experiencing positive psychological states becomes increasingly common as the caregiver adapts to the role. However, longitudinal research has shown that caregivers report lower available social support and decreased satisfaction with the support they receive over time (Clay et al., 2008). Caregivers who persist in their roles over many years may lose close relationships that are especially important during aging; as such, their ability to find meaning and satisfaction in caregiving may be paramount to a positive quality of life.

While caregiving research has focused heavily on distress, burden, and other negative aspects of caregiving (Marino, Roth, & Haley, 2017), positive aspects of caregiving (PAC) are increasingly recognized to be important as well. PAC are positive appraisals or benefits that caregivers report about their role (Tarlow et al., 2004). PAC are associated with positive health outcomes for caregivers such as higher quality of life and higher motivation in the caregiving role (Las Hayas et al., 2014; Grover et al., 2017). Although a substantial part of the early caregiving literature aimed to understand the negative health consequences associated with being a caregiver, several reviews and meta-analyses have since shown that a high proportion of caregivers of those with several crosscutting conditions (e.g., dementia, stroke, cancer, schizophrenia) view caregiving as a positive experience (Kulhara et al., 2012; Li & Loke, 2013; Mackenzie & Greenwood, 2012; Quinn & Toms, 2019; Roth, Fredman & Haley, 2015).

Social support has been shown to be a strong predictor of caregiver adjustment, defined as higher positive outcomes and lower distress (Pakenham, Chiu, Bursnall, & Cannon, 2007) and of resilience, measured with a 15-item resilience scale (Wilks and Croom, 2008). There is some evidence of a positive association between social support and PAC. In a study of caregivers of children and adolescents, social support mediated the relationship between caregiving burden and PAC (Wang et al., 2020). Social support was also found to be a significant predictor of PAC among African American caregivers in a multisite intervention on caregiver health (Cho et al., 2016). Caregivers of relatives with schizophrenia reported greater PAC when they received more help from family members, participated in a support group, or when their care recipient reciprocated emotional and instrumental support (Chen & Greenberg, 2004). Perceived stress, however, has been shown to negatively influence caregiver resilience (Wilks & Croom, 2008). Caregivers’ experience of distress, including perceived stress and caregiving strain, may diminish psychological benefits derived from the caregiving role. The experience of distress may also be influenced by several important demographic variables that are also predictors of PAC. Prior studies have found that African American caregivers have higher PAC than white caregivers (Roth et al., 2015). There is also evidence that older, female, married and spousal caregivers have higher PAC (Cho et al., 2016). Dementia caregivers may have lower PAC than non-dementia caregivers since high caregiving burden has been reported among caregivers providing care for persons with dementia (Sheehan et al., 2021).

In summary, previous research on caregiving suggests that long-term caregiving might provide an opportunity for increased PAC and benefit-finding, but may also be associated with lower social engagement and chronic psychological distress. We hypothesized that caregivers who provided care for a longer period of time and had larger social network size or greater monthly social contact would report higher PAC. We expected that these associations would still be significant after adjusting for perceived stress and caregiving strain, since these factors are likely associated with long-term caregiving as well as PAC.

Materials and Methods

Data source

The REasons for Geographic and Racial Differences in Stroke (REGARDS) study is an epidemiological study of stroke incidence in the United States that enrolled 30,329 White and African American adults over 45 years of age in 2003–2007. In order to be eligible, participants had to be free of cancer diagnoses requiring chemotherapy and not living in or on the waiting list for a nursing home. Study investigators randomly sampled participants from a commercially available nationwide list, oversampling for African Americans and residents of the Stroke Belt (Alabama, Arkansas, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, and Tennessee) by design (Howard et al., 2005). Participants who consented to participation underwent the REGARDS baseline interview, a computer-assisted telephone interview (CATI) followed by an in-home physical exam in which blood samples were obtained. A 2nd CATI and in-home assessment were conducted a median of 9.4 years after the first one (Howard et al., 2018).

Caregiving Transitions Study (CTS) Enrollment

Approximately 12 years after enrollment into REGARDS, participants were queried by telephone for updated information on caregiving status and family relationship variables to determine whether they were eligible to be enrolled into CTS. Each participant was asked about whether they were currently providing care on an ongoing basis to a family member, friend, or neighbor with a chronic illness or a disability; care provision could include any kind of regular help with basic activities such as dressing, bathing, grooming this person, managing bills, arranging for medical care, watching or supervising this person, or providing transportation. Participants who answered “yes” were potentially eligible for enrollment as a caregiver into CTS. A subsequent telephone interview further examined eligibility including caregiving intensity (e.g., at least 5 hours of care per week provided for persons residing in the community) and enrolled eligible caregivers (Roth, Haley, Rhodes, et al., 2020).

The CTS enrolled two types of caregivers: incident and long-term. This distinctionis based solely on whether the caregivers began provding care before (long-term) or after (incident) they enrolled as participants in the REGARDS study. Participants were eligible to be enrolled as an incident caregiver if they began providing care at least six months after the 1st REGARDS in-home assessment and at least 3 months before the 2nd REGARDS in-home assessment. Participants were eligible to be enrolled as a long-term caregiver if they began providing care at least six months before the 1st REGARDS in-home assessment and continued to provide care to that same care recipient through the 2nd REGARDS in-home assessment and the CTS interviews. Additional eligibility criteria required the care recipient to be over 18 years of age and not residing in a nursing home, assisted living facility or other residential care setting. The caregiver must have also provided at least 5 hours of care per week, lived with or within 50 miles of the care recipient, and supplied usable blood samples at both of the REGARDS in-home assessments.

After potential participants were contacted and screened for eligibility, 251 incident caregivers and 32 long-term caregivers consented to participate in the study and completed the CTS baseline telephone interview. Follow-up telephone interviews were planned to take place at 12 and 24 months. Additional information on the design, sampling, and enrollment procedures of the CTS have been described elsewhere (Roth, Haley, Rhodes, et al., 2020). The Institutional Review Boards (IRBs) of all participating institutions approved REGARDS and CTS.

Measures

PAC

The PAC scale was administered at the CTS baseline interview. The total score was defined as the sum of scores for 11 questions, each on a scale of 1–5 (5=high), regarding the extent that the caregiver agreed with the following statements: “made me feel more useful”, “made me feel good about myself”, “made me feel needed”, “made me feel appreciated”, “made me feel important”, “made me feel strong and confident”, “given more meaning to my life”, “enabled me to learn new skills”, “enabled me to appreciate life more”, “enabled me to develop a more positive attitude toward life”, and “strengthened my relationship with others” (Tarlow et al., 2004). Agreement was rated on a 5-point scale for each item. The total score ranged from 11–55, with 55 indicating the highest PAC.

Primary Predictor Variables

Duration of caregiving was calculated by subtracting the date when the caregiver reported beginning to provide care because of the care person’s chronic illness or disability from the CTS baseline interview date, converted to years and treated as a continuous variable. Relationship to the care recipient was collected at the CTS baseline interview and coded categorically (spouse, adult child, other).

Data on caregivers’ social network size and monthly social contact were collected at the CTS baseline interview. Participants’ social network size was measured by summing the responses from the first two questions of a 3-item questionnaire based on the Revised Lubben’s Social Network Scale (LSNS): “(1) How many close friends do you have? That is, people that you feel at ease with, can talk to about private matters, and can call for help? (2) How many relatives do you have that you feel close to?” Monthly social contact was measured using the third question on the Revised LSNS: “How many of these friends or relatives do you see at least once a month?” (Lubben, 2008). Numeric responses for each question were converted to a score on an ordinal scale according to the LSNS. A response of 0, 1 or 2 was coded as 0, 1 or 2, respectively; a response of 3 or 4 was coded as 3, a response between 4–8 was coded as 4, and a response greater than 8 was coded as 5. Missing data on social network size or monthly social contact at the CTS baseline interview were imputed using data from the first follow-up interview where available.

Covariates

Age was calculated by subtracting the caregiver’s reported date of birth at the REGARDS baseline interview from the date of the CTS baseline interview. Sex and race were collected by self-report at the REGARDS baseline interview. Marital status (married or living with a significant other) and dementia status of the care recipient (dementia or non-dementia care) were collected at the CTS baseline interview and coded as binary variables. Measures of distress (caregiving strain, perceived stress) were collected at the CTS baseline interview. For caregiving strain, caregivers reported whether they experienced “no strain”, “some strain”, or “a lot of strain”. Perceived stress was the sum of scores from four questions assessing how often in the past month the caregiver felt unable to control important things in life, confident in ability to handle personal problems, that things were going their way, or that they could not cope with all the things they had to do. The total score ranged from 0–16, with 16 indicating the highest perceived stress (Cohen, Kamarck & Mermelstein, 1983).

Statistical Analysis

We first assessed unadjusted differences between incident and long-term caregivers for age, sex, race, marital status, relationship of care recipient to the caregiver, dementia status of care recipient, social engagement (social network and monthly social contact), measures of distress (perceived stress and caregiving strain), years of care, and PAC. Next, we fit a series of multivariable models to assess the relationship between social engagement, duration of caregiving and PAC (with PAC as the outcome in all models), pooling the two groups of caregivers and analyzing years of care as a continuous variable. Model 1a included age, sex, race, married or living with a significant other, relationship of care recipient to the caregiver, dementia status of care recipient, social network size, and years of care. We added perceived stress and caregiving strain to Models 2a. For analyses with monthly social contact, we replaced social network size with monthly social contact for Models 1b and 2b. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC). P-values of less than 0.05 were considered statistically significant.

Results

In our analysis, we included all incident caregivers (N=251) and long-term caregivers (N=32) enrolled in CTS. Table 1 shows descriptive means or counts for demographic characteristics, measures of distress, PAC, social network size, monthly social contact and years of caregiving. Distributions for age, sex, race and dementia status of care recipient were similar between long-term caregivers and incident caregivers. Both long-term caregivers and incident caregivers were around 72 years of age on average, around two-thirds of both groups were female, half of both groups were spouse caregivers, and about 47% of both groups were dementia caregivers. A non-significantly higher proportion of long-term caregivers were married or living with a significant other, compared to the proportion of incident caregivers (87.5% vs. 73.3%; p=0.08). Caregivers in our study provided an average of 7.65 years of care (SD: 7.16); long-term caregivers provided an average of 21.3 years of care (SD: 8.4) and incident caregivers provided an average of 5.9 years of care (SD: 4.7). Measures of distress were similar between incident caregivers and long-term caregivers.

Table 1.

Characteristics of long-term caregivers and incident caregivers

Mean (SD) or N (%) Long-term caregiver n=32 Incident caregiver n=251 X 2 t-statistic
Demographics
Age 71.9 (7.0) 71.8 (8.1) -- −0.03 (p=0.98)
Sex (female) 22 (68.8%) 163 (64.9%) 0.18 (p=0.67) --
Race (African American) 12 (37.5%) 90 (35.9%) 0.033 (p=0.86) --
Care recipient relationship 8.67 (p=0.01)* --
 Spouse 16 (50.0%) 128 (51.0%))
 Parent 2 (6.3%) 63 (25.1%)
 Other 14 (43.8%) 60 (23.9%)
Married/living with significant other 28 (87.5%) 184 (73.3%) 3.04 (p=0.08) --
Dementia status of care recipient 15 (46.9%) 117 (46.6%) 0.0008 (p=0.98) --
Measures of distress
Perceived Stress Scale (PSS) 5.1 (2.7) 4.55 (3.0) -- −1.05 (p=0.29)
Caregiving strain 0.69 (p=0.71) --
 No strain 3 (9.4%) 37 (14.7%)
 Some strain 20 (62.5%) 150 (59.8%)
 A lot of strain 9 (28.1%) 64 (25.5%)
Main variables of interest
Positive aspects of caregiving (PAC) 47.4 (7.9) 44.7 (10.2) -- −1.41 (p=0.16)
Social network size 6.3 (2.0) 6.4 (2.2) -- 0.24 (p=0.81)
Monthly social contact 3.3 (1.2) 3.3 (1.4) −0.03 (p=0.98) --
Years of caregiving 23.2 (10.1) 5.8 (2.5) −0.68 (p<0.01)* --
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T-tests for continuous variables and chi-square test of significance for categorical variables

*

p<0.05

In Model 1a of Table 2, larger social network size was associated with higher PAC (0.78; SE: 0.28; p<0.01) and more years of care showed a trend to be associated with higher PAC that approached statistical significance (0.10; SE: 0.10; p=0.06). Our findings in Model 2a, which additionally adjusted for perceived stress and caregiving strain, were similar. In both models, African American caregivers reported significantly higher PAC compared to White caregivers, with African Americans approximately four points higher on average. Dementia caregivers reported lower PAC than non-dementia caregivers in Model 1a, but the effect was no longer significant after adjusting for distress variables (Model 2a). Those who reported “a lot of strain” reported an average of 5.3 points lower on PAC than those who reported no strain (p<0.01). Those who reported “some strain” had on average of 2.8 points lower on PAC compared to those who reported no strain, though this difference was not statistically significant. Table 3 includes the same covariates as models in Table 2, replacing social network size with monthly social contact. The association between PAC and demographic variables, measures of distress, social engagement (i.e. monthly social contact) and years of care in Table 3 were similar to those in Table 2.

Table 2.

Covariate-adjusted multiple linear regression of Positive Aspects of Caregiving on years of care and social network size

Model 1a R2 = 0.133 Model 2a R2 = 0.172
Estimate (SE) Standardized regression coefficient P Estimate (SE) Standardized regression coefficient P
Age 0.12 (0.09) 0.099 0.16 0.11 (0.09) 0.085 0.22
Sex (female) −2.33 (1.32) −0.11 0.08 −1.20 (1.34) −0.057 0.37
Race (African American) 4.15 (1.25) 0.20 <0.01 3.65 (1.24) 0.18 <0.01
Married or living with significant other −2.55 (1.76) −0.11 0.15 −2.30 (1.74) −0.10 0.19
Care recipient relationship
 Spouse REF REF REF REF REF REF
 Parent −2.05 (1.79) −0.089 0.25 −2.31 (1.76) −0.10 0.19
 Other −2.76 (1.81) −0.12 0.13 −3.00 (1.79) −0.14 0.09
Dementia status of care recipient −3.08 (1.19) −0.16 0.01 −1.75 (1.24) −0.089 0.16
Perceived Stress Scale (PSS) -- -- -- −0.34 (0.21) −0.10 0.11
Caregiving strain -- -- --
 No strain REF REF REF
 Some strain −2.75 (1.71) −0.14 0.11
 A lot of strain −5.32 (2.06) −0.24 0.01
Social network size 0.78 (0.28) 0.17 <0.01 0.66 (0.28) 0.14 0.02
Years of care provided 0.19 (0.10) 0.12 0.056 0.19 (0.10) 0.12 0.06
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Model 1a: age, sex, race, care recipient relationship, marital status, dementia caregiving status, social network size, years of care.

Model 2a: Model 1a + PSS + caregiving strain.

Standardized regression coefficient calculated by multiplying regression coefficient by the ratio of standard deviations of the predictor to the outcome (PAC); indicates effect size. R2 indicates proportion of variance in PAC explained by predictors in each model.

Table 3.

Covariate-adjusted multiple linear regression of Positive Aspects of Caregiving on years of care and monthly social contact

Model 1b R2 = 0.125 Model 2b R2 = 0.178
Estimate (SE) Standardized regression coefficient P Estimate (SE) Standardized regression coefficient P
Age 0.12 (0.09) 0.10 0.16 0.10 (0.09) 0.078 0.26
Sex (female) −2.35 (1.33) −0.11 0.08 −1.05 (1.35) −0.049 0.43
Race (African American) 4.51 (1.28) 0.22 <0.01 3.96 (1.26) 0.19 <0.01
Married or living with significant other −2.52 (1.79) −0.11 0.16 −1.97 (1.76) −0.087 0.26
Care recipient relationship
 Spouse REF REF REF REF REF REF
 Parent −2.25 (1.82) −0.095 0.22 −2.34 (1.78) −0.10 0.19
 Other −3.39 (1.84) −0.15 0.07 −3.28 (1.81) −0.15 0.07
Dementia status of care recipient −2.52 (1.20) −0.13 0.04 −1.00 (1.24) −0.050 0.42
Perceived Stress Scale (PSS) -- -- -- −0.48 (0.21) −0.14 0.02
Caregiving strain -- -- --
 No strain REF REF REF
 Some strain −2.82 (1.74) −0.14 0.11
 A lot of strain −5.67 (2.08) −0.25 <0.01
Monthly social contact 1.21 (0.42) 0.17 <0.01 1.00 (0.41) 0.14 0.02
Years of care provided 0.16 (0.09) 0.11 0.08 0.15 (0.09) 0.10 0.11
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Model 1b: age, sex, race, care recipient relationship, marital status, dementia caregiving status, monthly social contact, years of care.

Model 2b: Model 1a + PSS + caregiving strain.

Standardized regression coefficient calculated by multiplying regression coefficient by the ratio of standard deviations of the predictor to the outcome (PAC); indicates effect size. R2 indicates proportion of variance in PAC explained by predictors in each model.

In both tables, the models with and without measures of distress explained approximately 13% and 17–18% of the variance in PAC, respectively. Across models, the effect sizes (i.e. standardized regression coefficients) for social engagement variables are larger than effect sizes for years of care by 0.02 to 0.06 standard deviation units.

Discussion

In this analysis of long-term caregivers and incident caregivers from a national cohort study, we found that larger social network size and greater monthly social contact were associated with significantly higher PAC. Longer duration of caregiving was found to have associations with higher PAC that approached but did not achieve the statistical significance threshold selected for our analyses. Nonetheless, the direction of non-significant association between duration of care and PAC is consistent with studies showing a positive correlation between caregiving benefits and duration of care (Pendergrass et al., 2019) as well as better adaptation and resilience in long-term caregivers (Gaugler et al., 2000; Noonan & Tennstedt, 1997).

Long-term caregiving is associated not only with opportunities for appreciating some of the psychological benefits that can be gained from caregiving but also with an erosion of social engagement (Clay et al., 2008). Previous findings from our research within this cohort showed that incident caregivers declined less in monthly social contact than social network size, suggesting that incident caregivers are more selective with their social networks as they become involved in caregiving (Liu, Fabius, et al., 2020). In this study, dementia caregivers reported lower PAC than non-dementia caregivers when controlling for social network size, but no differences were observed when controlling for monthly social contact. This is consistent with the notion that the nature of social engagement may be more important for caregiver well-being than the size of social networks, particularly those facing higher caregiving burden such as dementia caregivers. Previous findings from this cohort also showed that although dementia caregivers had lower health-related quality of life than non-dementia caregivers, differences were not significant in models that accounted for hours of caregiving and the number of cognitive or memory problems experienced by the care recipient (Sheehan et al., 2020). This is consistent with findings from the present analysis showing that dementia caregivers had lower PAC than non-dementia caregivers in models that did not include measures of distress, but the difference was attenuated when caregiving strain was added to the model, suggesting that differences in PAC between dementia and non-dementia caregivers may be primarily explained by differences in their experience of distress.

In our study, the associations between PAC and the primary independent variables, years of care and social engagement, were not changed by the addition of measures of distress, which is consistent with the view that caregivers’ positive and negative experiences may occur independently. This also supports findings from other studies showing the common co-occurrence of positive and negative aspects of caregiving, such as self-efficacy and burden, respectively (Cheng et al., 2013). We found that the level of social engagement was not significantly different between incident and long-term caregivers but was strongly associated with PAC even after accounting for levels of distress. This reinforces the importance of social engagement in maintaining caregiver well-being over time, although it does not provide information about the nature of the social engagement. A study by Cheng et al. (2013b) showed that caregivers with larger social networks had more positive gains from their role, and but many excluded a large proportion of close kin from their social networks possibly to avoid negative interactions. Further study is needed on how caregivers define their social networks, specifically on whether the positive effect of social engagement is partially driven by the exclusion of social network members with whom caregivers had negative interactions from this definition.

In our study, African Americans caregivers reported higher PAC compared to White caregivers across all models. This is consistent with previous findings of racial differences in PAC (Haley et al., 2004; Roff, et al., 2004; Roth et al., 2015; Williams, 2005) as well as other positive caregiving appraisals for dementia caregivers (Liu, Badana, et al., 2020). Roff and colleagues (2004) found that African American caregivers’ higher religiosity partially mediated their higher scores on the PAC scale. Dilworth-Anderson and colleagues (2005) found that African American caregivers also expressed stronger cultural reasons for providing care compared to White caregivers, which was in turn associated with better appraisals of their own health. These findings are consistent with our finding of higher PAC among African American caregivers than White caregivers, though it should be noted that there is likely heterogeneity in religiosity and motivations for providing care within both groups.

There are several strengths and limitations to our study. We used a rigorous definition for caregiving intensity; long-term and incident caregivers enrolled in CTS were a subset of the population-based, national REGARDS study, and were actively providing substantial and sustained care of at least 5 hours per week. Given the extensive literature on the association between caregiving and distress, our study provides encouraging evidence on positive adaption for long-term caregivers. Our examination of the impact of dementia care status on PAC is also an important contribution. Though it is well established that dementia caregivers face uniquely challenging stressors that increase their likelihood of strain and adverse health outcomes (Ory et al., 1999), there are few direct comparisons of PAC in dementia and non-dementia caregivers. One extant study that compared these group found that both dementia and non-dementia caregivers experienced PAC to the same extent, despite dementia caregivers reporting greater objective and subjective strain (Karg et al., 2018). Future research is needed to further clarify these associations.

One significant limitation of this study was that our analyses were cross-sectional, and as such we could not examine how social engagement, measures of distress or PAC changed over time. Caregivers who had more positive experiences with caregiving are more likely to continue providing care, which may have contributed to our observation that caregivers who provided more years of care reported higher PAC. Additionally, social engagement variables did not provide any information about the types of contacts and whether they were part of the support network specific to caregiving or just relationships independent of that task. In future studies, this information will be especially important in understanding how caregivers were able to adapt to the caregiving role and maintain a positive outlook.

Findings from our study have several practical implications. The caregiving literature primarily assesses the negative consequences of providing substantial care and has largely overlooked PAC related to personal growth (Marino et al., 2017). Our findings, particularly with regards to the relationship between long-term caregiving, distress and PAC, suggest that the distinction between PAC’s hedonic (e.g. “made me feel good about myself”) and eudemonic (e.g. “enabled me to learn new skills”) components should be assessed separately in future studies, as caregivers may experience one and not the other. Our study also corroborates prior evidence of positive effects on caregiving well-being from caregiver interventions targeting PAC. A benefit-finding intervention with the goal of increasing PAC through cognitive reappraisal and discussion of challenges faced by caregivers resulted in lower depression for those in the benefit-finding group compared to those in the control group, the latter of whom received standard or simplified psychoeducation (Cheng et al., 2014). At the 10-month follow-up, caregivers who received the intervention had higher PAC than those in the control group, though no other differences were observed (Cheng et al., 2020). Another study of 68 Chinese stroke caregivers showed that a 9-week benefit-finding intervention compared to routine health education led to lower burden for the caregiver and higher quality of life for both the caregiver and the care recipient (Fu et al., 2020). Although these studies focused on caregivers who have provided care for a relatively short period of time compared to the long-term caregivers in our study, findings can be leveraged to help caregivers throughout their time in the role. Longer follow-up is also needed to understand whether the effects of these interventions last beyond the first year. On balance, there is potential for PAC to be further explored as a potential target in future interventions, which can be more widely implemented in different populations of caregivers in order to improve caregiver well-being and the caregiving experience overall.

The public health implications of our study are especially relevant in the context of the COVID-19 pandemic, as many individuals with little training or preparation who have never been caregivers prior to the pandemic are now caring for friends or family. Finding meaning and creating positive experiences while caring for others could help caregivers transition into, adjust to, and sustain what can be a daunting and stressful role. Future studies should aim to understand the specific ways in which caregivers were able to adapt to their role in order to provide a more balanced and nuanced view of caregiving.

Funding details:

This work was supported by the National Institute of Neurological Disorders and Stroke (NINDS), the National Institute on Aging (NIA) and the National Institutes of Health, Department of Health and Human Services under cooperative agreement [U01 NS041588]; and by the NIA under investigator-initiated grant [RF1 AG050609]. This content is solely the responsibility of the authors and does not necessarily represent the official views of the NINDS or NIA. Representatives of the NINDS were involved in the review of the manuscript but were not directly involved in the collection, management, analysis, or interpretation of the data. The authors thank the other investigators, the staff, and the participants of the REGARDS study for their valuable contributions. A full list of participating REGARDS investigators and institutions can be found at: https://www.uab.edu/soph/regardsstudy/

Footnotes

Disclosure statement: The authors report no conflicts of interest.

Contributor Information

Chelsea Liu, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.

Victoria R. Marino, University of South Florida, Tampa, FL 33620, USA.

Virginia J. Howard, Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL 35294, USA.

William E. Haley, School of Aging Studies, University of South Florida, Tampa, FL 33620, USA.

David L. Roth, Center on Aging and Health, Division of Geriatric Medicine and Gerontology, Johns Hopkins University, Baltimore, MD 21205, USA.

Data availability statement:

In cooperation with the Institutional Review Board of the University of Alabama at Birmingham, the REasons for Geographic and Racial Differences in Stroke project facilitates data sharing through formal data use agreements. Investigators who wish to access the data should send their requests to regardsadmin@uab.edu.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

In cooperation with the Institutional Review Board of the University of Alabama at Birmingham, the REasons for Geographic and Racial Differences in Stroke project facilitates data sharing through formal data use agreements. Investigators who wish to access the data should send their requests to regardsadmin@uab.edu.

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