ABSTRACT
Objectives
Caring for an individual with cognitive impairment carries a physical, mental, and emotional toll. This manuscript examines the relationship between caregiver psychosocial measures and longitudinal cognitive outcomes of stroke survivors, as well as analyzing the psychosocial factors as moderators of stroke severity and cognition.
Methods
This analysis was conducted on caregiver and stroke survivor dyads (n = 157) that participated in the Caring for Adults Recovering from the Effects of Stroke (CARES) project, an ancillary study of the REasons for Geographic and Racial Differences in Stroke (REGARDS) national cohort study. Stroke severity at hospitalization discharge was included as the primary predictor of cognitive outcomes and caregiver psychosocial factors were included as additional predictors. Cognition was assessed biennially and measured the domains of learning, memory, and executive functioning. Individual mixed‐effect models included each psychosocial factor and were covariate‐adjusted for pre‐stroke cognitive scores and demographic variables. Caregiver psychosocial factors included caregiver strain, depressive symptoms, life and leisure time satisfaction, and overall quality of life.
Results
Decreased caregiver strain (b = −0.230, 95% CI: −0.39 to −0.07; p = 0.006) and increased leisure time satisfaction (b = 0.045, 95% CI: 0.01 to 0.08; p = 0.005) were both found to be significant predictors, alongside stroke severity (b = −0.137, 95% CI: −0.22 to −0.05; p = 0.002), of better stroke survivor cognition overall. No variables were found to be moderating factors of the relationship between stroke severity and cognition.
Conclusions
Understanding the caregiver psychosocial factors that predict stroke outcomes will help clinicians to identify stroke survivor and caregiver dyads at higher risk for worst longitudinal cognitive outcomes following stroke.
Keywords: caregiver strain, caregivers, cognition, stroke
Summary.
This study demonstrates that caregiver psychosocial factors, particularly caregiver strain and leisure time satisfaction, are significant predictors of cognitive outcomes following stroke, alongside stroke severity. This finding emphasizes the dual importance of clinical factors and caregiver well‐being in predicting post‐stroke cognition.
The results emphasize integrating the caregiver into stroke survivor rehabilitation programs. Interventions that also include reducing caregiver strain and enhancing their leisure time satisfaction may improve both caregiver well‐being and stroke survivor cognitive recovery.
Stroke severity, measured at hospital discharge, remains a critical determinant of long‐term cognitive outcomes in stroke. Notably, the caregiver psychosocial factors did not moderate the relationship between stroke severity and cognition, suggesting that these relationships are independent of each other.
Future research should explore the relationship between caregiver psychosocial health and stroke survivor outcomes over longer periods of time. Investigating additional caregiver factors, such as social determinants of health, may provide further strategies to optimize both caregiver and stroke survivor well‐being.
1. Introduction
Stroke is associated with cognitive impairment in around 60% of survivors, impacting their everyday functioning and health‐related quality of life (QoL) [1]. Stroke outcomes are influenced by multiple factors, such as stroke severity and location, however cognitive deficits can remain even in stroke survivors who experience good clinical outcomes [2]. While caregivers play a crucial role in supporting survivors with post‐stroke cognitive impairment (PSCI), there is a gap in the literature related to the influence that caregivers can have on the recovery process and cognition. This manuscript utilizes the REGARDS (REasons for Geographic and Race Differences in Stroke) database to investigate the association between stroke survivor and caregiver dyads and cognitive outcomes, and how these outcomes are predicted or moderated by the psychosocial factors of their caregivers.
Several studies have indicated that having a supportive caregiver can lead to better outcomes in the care recipient broadly [3, 4, 5]. One such study explored the relationship between caregiver psychosocial functioning and outcomes of traumatic brain injury (TBI) survivors that required acute inpatient rehabilitation [6]. Worse caregiver well‐being, as measured by the Brief Symptom Inventory‐18 (BSI) and Satisfaction with Life Scale (SWLS), significantly predicted more disability, as measured by the Disability Rating Scale (DRS), of the TBI survivor care recipient at follow‐up. Higher life satisfaction of the caregiver was a strong predictor of improved functional disability at follow‐up, the only predictor that was stronger was severity of the injury at the time of hospitalization. Despite the study's age, it provides novel insights into the caregiver‐care recipient dynamic in the context of acquired brain injuries.
Existing research has found a relationship between the caregiver's well‐being and the well‐being of the care recipient [7], but the exploration of caregiver factors and post‐stroke outcomes remains limited. The Caring for Adults Recovering from the Effects of Stroke (CARES) project, an ancillary study to REGARDS, previously investigated the association of caregiver well‐being and stroke survivor well‐being [8]. The CARES study collected data from stroke survivor caregiver dyads on the individual's emotional, mental, physical, and financial well‐being. Previous work from this study has shown that caregivers who reported higher levels of depressive symptoms and lower levels of life satisfaction, were more likely to be caring for stroke survivors who also reported more depressive symptoms and less life satisfaction [8]. A 2019 study by Pucciarelli, et al. [9] indicates that this relationship may not be one‐directional. This study identified distinct QoL trajectories among stroke survivors over a 12‐month period post‐discharge, revealing significant associations with caregiver burden, anxiety, and depression [9]. Specifically, stroke survivors that experienced a worsening QoL trajectory were likely to have caregivers who reported heightened levels of burden, anxiety, and depression themselves.
Current research on the relationship between caregiver psychosocial factors and post‐stroke cognition of stroke survivors is limited. In this investigation, it is hypothesized that worse caregiver psychosocial scores, such as a higher number of depressive symptoms or lower leisure time satisfaction, will predict lower cognition in the stroke survivors. This analysis also includes an exploratory hypothesis to determine if any caregiver psychosocial factors moderate the relationship between stroke severity and cognition. The goal of this manuscript is to better understand the predictive value of a caregiver's psychological factors on the cognitive outcomes of stroke survivors to improve and inform post‐stroke interventions.
2. Methods
2.1. Participants
Participants were initially enrolled in the REasons for Geographic And Racial Differences in Stroke (REGARDS) study, a national cohort study ongoing since 2003, aimed at exploring factors behind the disparities in stroke incidence and mortality. Initially, REGARDS successfully recruited 30,239 participants between 2003 and 2007 [10]. The REGARDS study targeted individuals aged 45 and above and aimed for a diverse geographic representation. Specifically, 30% of participants were drawn from the Stroke Belt, which includes several Southeastern states in the U.S. (North Carolina, South Carolina, Georgia, Alabama, Mississippi, Tennessee, Arkansas, & Louisiana), and 20% from the Stroke Buckle (part of the Stroke Belt that covers the coastal plain regions in the remainder of North Carolina, South Carolina, and Georgia). The remaining participants were recruited from other areas across the continental United States. The study intentionally oversampled Black/African American individuals resulting in an even representation of White and Black/African American individuals in the study sample.
Upon being enrolled in REGARDS, informed consent was collected from participants who then underwent an expanded cognitive assessment every 2 years through computer‐assisted telephone interviews. This assessment evaluated various cognitive domains, including memory and verbal fluency/executive functioning. All relevant measures and assessments are detailed below. The methodologies for participant sampling, recruitment, and data collection in the REGARDS study have been described further in prior studies [10, 11]. Due to the sensitive nature of the data collected for this study, requests to access the dataset from qualified researchers trained in human subject confidentiality protocols may be sent to REGARDS at REGARDSAdmin@uab.edu.
2.1.1. CARES Enrollment and Procedures
Individuals who were initially part of the REGARDS project and had reported suffering a stroke were subsequently invited, along with their primary caregivers, to join the Caring for Adults Recovering from the Effects of Stroke (CARES) ancillary study. Recruitment for CARES spanned from 2005 to 2016. To be considered eligible for the CARES study, REGARDS participants needed to meet several criteria: (1) reside within the community nine months following their stroke, specifically excluding those in nursing homes or similar institutional care; (2) have a family member or close friend serving in the role of an informal caregiver, either currently or immediately after their stroke; and (3) informed consent from the stroke survivor and their caregiver to participate in the CARES study alongside them [12]. Following enrollment in the CARES study, the stroke survivor and caregiver dyads were administered the initial baseline CARES interview [13]. Interviews for the CARES study took place over the phone, an average 9 months after the stroke. Every participant in the stroke survivor group reported experiencing their first stroke during their most recent REGARDS follow‐up interviews. An independent review of the survivors' medical records was conducted by trained adjudicators to verify the occurrence of a stroke, identify the stroke type, and gather data on the severity of the stroke at the time of discharge from the hospital. Informed consent was collected from both the stroke survivors and their caregivers. Roth, et al. [12] provides a detailed overview of the data collection procedures employed in the CARES study. Both the REGARDS and CARES projects were reviewed and approved by the Institutional Review Boards of the University of Alabama at Birmingham and each participating institution.
2.1.2. Demographics
The specific demographic data utilized in this study included race, level of education (years), age, and gender, which were collected from both the stroke survivor and the caregiver at the CARES baseline interview. The variable of gender (men or women) was self‐reported and treated as a dichotomous variable. Descriptive statistics are reported in Table 1 for both the stroke survivor and their caregiver, including means and standard deviations for continuous measures and percentages for categorical variables.
TABLE 1.
Baseline characteristics for the caregiver‐care recipient dyads.
| Demographics | Participants N = 157 | Caregivers N = 157 |
|---|---|---|
| Age at stroke | 74.91 (SD = 7.30) | — |
| Age at CARES interview | 75.77 (SD = 7.30) | 61.82 (SD = 13.40) |
| Education (years) | 13.55 (SD = 2.16) | 14.46 (SD = 2.74) |
| Gender (n, %) | ||
| Women | 85 (55%) | 119 (77%) |
| Race (n, %) | ||
| White | 97 (62%) | 95 (62%) |
| Black/AA | 60 (38%) | 58 (37%) |
| Other | 0 (0%) | 1 (1%) |
| Stroke sequelae | ||
| mRS at discharge | 1.82 (SD = 1.3) | — |
| Stroke type (n, %) | ||
| Ischemic | 132 (84%) | — |
| Hemorrhagic | 13 (8.5%) | — |
| Not specified | 12 (7.5%) | — |
| Stroke site (n, %) | ||
| Left hemisphere | 63 (40%) | — |
| Right hemisphere | 60 (38%) | — |
| Bilateral | 3 (1.9%) | — |
| Brainstem | 9 (5.7%) | — |
| Not specified | 22 (14%) | — |
| Caregiver psychosocial measures | ||
| CES‐D | — | 6.27 (SD = 8.75) |
| PCS (QoL) | — | 46.28 (SD = 10.22) |
| MCS (QoL) | — | 53.15 (SD = 9.80) |
| LTS | — | 10.87 (SD = 3.59) |
| LSI‐Z | — | 20.84 (SD = 4.70) |
| Caregiver strain | — | 0.76 (SD = 0.74) |
Abbreviations: CES‐D, Center for Epidemiologic Studies Depression Scale; LSI‐Z, Life Satisfaction Index; LTS, Leisure Time Satisfaction; MCS, Mental Component Summary (Quality of Life); mRS, modified Rankin Scale; PCS, Physical Component Summary (Quality of Life).
2.2. Measures
2.2.1. Stroke Severity
Stroke severity was measured using modified Rankin Scale (mRS) scores that were collected from hospital chart abstraction at time of discharge. The mRS is a clinically administered measure that is commonly utilized in hospital settings as an indicator of acute phase stroke severity and may be administered by a physician or attending nurse [14]. As a measure of functional ability, the mRS assesses the degree of disability or dependence in daily activities. This measure offers a broad perspective on post‐stroke functional outcomes, with possible scores ranging from zero, indicating no symptoms, to six, representing death [14].
2.2.2. Psychosocial Measures
During the CARES interview, caregivers self‐reported depressive symptoms, caregiving strain, overall life satisfaction, leisure time satisfaction, as well as physical and mental health quality of life (QoL) within an average 9 months following the stroke event.
Depressive Symptoms. Possible symptoms of depression were measured using the Center for Epidemiologic Studies—Depression scale (CES‐D). The CES‐D is a 20‐item measure of depressive symptoms where frequency of each symptom is rated on a scale from zero to three [15]. Total possible scores range from zero to 60, with higher scores indicating more severe depressive symptoms. A cut‐off score of 16 or higher has been recommended and validated as being sensitive and specific in detecting significant levels of depressive symptoms in both the general population [16] and in caregivers of persons with dementia [17].
Caregiver Strain. The caregivers were also asked to report the amount of mental or emotional strain that they experience when providing care. Caregivers were asked to respond with zero or “no strain,” one or “some strain,” and two or “a lot of strain.” This one‐item survey question has been used in previous studies as an effective measure of the mental or emotional strain associated with caregiving [18, 19].
Life Satisfaction. Life satisfaction was measured for each caregiver using the Life Satisfaction Index (LSI‐Z). The LSI‐Z uses 13 items to determine positive feelings of accomplishment and overall morale [20]. Higher scores represent greater life satisfaction, with scores ranging from zero to 26. This measure has been utilized in previous studies of racially and ethnically diverse caregivers from different age groups [21, 22].
Leisure Time Satisfaction. The seven‐item Leisure Time Satisfaction (LTS) scale is an additional measure of life satisfaction and measures participant fulfillment with time spent on leisure activities [23]. This scale targeted activities such as hobbies, quiet time, and attendance at church. Participants were asked how satisfied they were with the time they were able to spend on these activities on a zero to two scale. The maximum score on this measure was 14, with higher scores indicating higher leisure time satisfaction.
Quality of Life. The CARES caregivers were also given an assessment of QoL using the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores of the 12‐item Short Form Health Survey (SF‐12). These measures have been standardized to have a mean of 50 and a SD of 10 in the adult US population [24]. High scores on the PCS and MCS indicate higher satisfaction with physical and mental QoL respectively.
The coefficient or Cronbach's alpha was calculated in previous CARES studies for each of the psychosocial measures listed. One CARES sample reported the coefficient alpha for the LSI‐Z as 0.73 [8]. In another CARES study, the LSI‐Z, LTS, and SF‐12 reported a coefficient alpha greater than 0.77 [25]. The Cronbach's alpha for the CES‐D was calculated to be 0.89 in the caregivers and 0.90 in the stroke survivors [8, 26]. These measures have been used extensively in previous research regarding the health and wellness of caregivers and stroke survivors, and their reliability in this sample has been well established [27].
2.2.3. Cognitive Assessment
The cognitive assessment is a brief computer‐assisted telephone battery designed to be administered to each REGARDS participant every 2 years. These measures have been validated for reliable administration using telephone interviews [28]. This battery includes the following assessments to quantify the cognitive domains of memory, language, and executive functioning: (a) Word List Learning (WLL) and Delayed Recall (WLDR), from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery [29]; (b) Animal (Semantic) Fluency; (c) Letter‐F (Phonemic) Fluency; and (d) Registration, recall, and orientation from the Montreal Cognitive Assessment (MoCA) [30] as a part of the National Institute of Neurological Disorders and Stroke—Canadian Stroke Network Vascular Cognitive Impairment Harmonization Standards (NINDS‐CSN) five‐minute Battery [31]. See Table 2 for score ranges for each assessment included in the biennial cognitive battery. The raw scores for each assessment have been converted to z‐scores using a normative sample. The cognitive composite score, the average of the z‐scores at each assessment timepoint, served as the outcome variable. This battery is outlined in more detail in the appendix of a previous REGARDS manuscript by Wadley, et al. [32].
TABLE 2.
Short cognitive assessment cognitive domains.
| Domains | Measure | Possible score range |
|---|---|---|
| Learning | WLL | Sum of three learning trials (0–30) |
| NINDS 5‐item registration | Number correct (0–5) | |
| Memory | WLD | Number correct (0–10) |
| NINDS 5‐item (delay) recall | Number correct (0–5) | |
| NINDS orientation | Number correct (0–6) | |
| Executive functioning & language | Animal fluency | Total number correct in 60 s |
| NINDS letter (F) fluency | Total number correct in 60 s | |
| Overall cognitive composite | WLL + WLD + animal fluency + NINDS registration + NINDS orientation + NINDS recall + NINDS letter fluency | z‐transformed composite of domain scores |
Abbreviations: NINDS, National Institute of Neurological Disorders and Stroke; WLD, Word List Delayed Recall; WLL, Word List Learning.
2.3. Statistical Analysis
The analyses for this manuscript was performed using SAS software Studio version 3.81 on SAS 9.4 (SAS Institute, Cary, NC). To assess the relationship between post‐stroke functional ability and cognition, a mixed effects regression model was used. Cognitive score at each time point was determined using the z‐transformed overall composite of cognitive domain scores. This model was structured to examine time (number of years post‐stroke of each assessment) logarithmically. Logarithmic models are recommended over linear models when assessing longitudinal cognitive scores in stroke survivors [33, 34]. Assessments administered more than 6 years following the stroke event were not included to minimize survivorship bias. This analysis also included the most recent pre‐stroke evaluation for each participant as a measure of baseline cognitive functioning.
An initial mixed model was created to measure the predictive validity of mRS scores on cognitive scores overall. Subsequent mixed models included each caregiver psychosocial factor as predictors to assess the association of psychosocial factors and post‐stroke cognitive scores. These individual mixed models also included the variables of stroke severity, baseline cognition, time since stroke (years), as well as the demographic covariates of stroke survivor age, gender, race, and years of education. Each model also included the interaction of baseline cognitive scores by time. Time since stroke of each assessment was included as a random effect in these models due to the variability in the administration of each assessment between participants.
Each caregiver psychosocial factor was then included, along with the covariates mentioned above, as interaction terms with mRS scores in separate models to determine if there were any significant moderators on the relationship between stroke severity and cognition. To explore how the effects of caregiver psychosocial factors vary over time, each caregiver psychosocial factor was also introduced as an interaction term with time. Random intercepts and slopes for time at the subject level were included with an unstructured covariance matrix. p values < 0.05 were considered statistically significant. All p‐values and statistical significances are based on 95% confidence intervals.
3. Results
3.1. Participant Characteristics
The original CARES study initially recruited approximately 360 stroke survivors. Figure 1 outlines the criteria for excluding selected CARES participants due to missing data. Of the 157 stroke survivors that met criteria for this analysis, there was a mean age of 75.74 years (SD = 7.32) at the time of CARES interview. The mean age at the time of stroke was 74.91 years (SD = 7.31). The stroke survivor group consisted of 86 (55%) women, 97 (62%) White participants and 60 (38%) Black/African American participants.
FIGURE 1.
Stratification of stroke survivor and caregiver dyads for CARES study analysis.
For the caregiver group (n = 157), the mean age at enrollment was 61.82 years (SD = 13.39), and the majority were women (77%; n = 121). The racial composition of the caregiver group included 97 caregivers (62%) identifying as White, 59 (37%) identifying as Black/African American, and one (1%) identifying as “Other.” As for the caregiver relationship to the stroke survivor, 73 (47%) were identified as a spouse or partner, 44 (29%) were daughters and 15 (10%) were sons of the stroke survivor, and 25 (16%) were a friend or another relative, such as a sibling or grandchild. 84 (54%) of caregivers reported living with the stroke survivors. Of the 73 caregivers that reported not living with their care recipient, 49 (67%) lived within 10 miles or less, 12 (16%) lived between 10 and 20 miles away, and 12 (16%) lived greater than 20 miles away from the stroke survivor. Table 1 displays the mean demographics of the dyads in this sample at the time of the CARES baseline interview, including the mean scores for the caregiver psychosocial factors.
3.2. Caregiver Psychosocial Factors
Higher mRS scores were a significant predictor of worse cognition, both independently (b = −0.137, 95% CI: −0.22 to −0.05; p = 0.002) and in all subsequent mixed models. Lower caregiver leisure time satisfaction was a significant predictor of worse cognitive outcomes (b = 0.038, 95% CI: 0.01 to 0.7; p = 0.014; Table 3) in stroke survivors. Higher caregiver strain was also found to be a significant predictor of worse cognitive outcomes (b = −0.198, 95% CI: −0.35 to −0.04; p = 0.012). Caregiver depressive symptoms did not significantly predict cognitive outcomes in stroke survivors (b = −0.006, 95% CI: −0.02 to 0.01; p = 0.347). Caregivers' physical and mental QoL, assessed through PCS and MCS scores respectively, were not found to be a significant predictor of cognitive outcomes in stroke survivors (PCS: b = −0.005, 95% CI: −0.02 to 0.01; p = 0.416; MCS: b = −0.001, 95% CI: −0.01 to 0.01; p = 0.864). Caregiver life satisfaction was also not found to be a significant predictor of stroke survivors' cognitive outcomes (b = 0.007, 95% CI: −0.02 to 0.03; p = 0.577).
TABLE 3.
Individual logarithmic mixed models for covariate adjusted associations of caregiver psychosocial factors and composite cognition scores.
| Caregiver factor | Estimate (b) | Standard error | t | p | 95% CI |
|---|---|---|---|---|---|
| CES‐D | −0.006 | 0.007 | −0.94 | 0.3466 | −0.019; 0.007 |
| PCS (QoL) | −0.005 | 0.006 | −0.82 | 0.4159 | −0.016; 0.006 |
| MCS (QoL) | −0.001 | 0.006 | −0.17 | 0.8635 | −0.012; 0.010 |
| LTS | 0.038 | 0.015 | 2.49 | 0.0138 | 0.008; 0.069 |
| LSI‐Z | 0.007 | 0.013 | 0.56 | 0.5767 | −0.018; 0.032 |
| Caregiver strain | −0.198 | 0.078 | −2.55 | 0.0121 | −0.353; −0.044 |
Note: This table includes the main effect of each caregiver psychosocial factor, included in individual mixed models, with composite cognitive assessment scores at each time point. Each model included stroke severity (mRS score) and the covariates of baseline cognition, time since stroke (years), as well as caregiver age, gender, race, and education (years). Each model also included the interaction of baseline cognition and time.
Abbreviations: CES‐D, Center for Epidemiologic Studies Depression Scale; LSI‐Z, Life Satisfaction Index; LTS, Leisure Time Satisfaction; MCS, Mental Component Summary (Quality of Life); PCS, Physical Component Summary (Quality of Life).
3.3. Caregiver Psychosocial Factors as Moderators
The moderation analysis revealed that caregivers' reported depressive symptoms were not significant moderators in the relationship between stroke severity and cognition in stroke survivors (p = 0.401). Neither the physical well‐being (PCS: p = 0.344) nor the mental well‐being (MCS: p = 0.706) of caregivers significantly moderated the relationship between stroke severity and cognition in stroke survivors. Caregiver satisfaction with leisure time (p = 0.857), life satisfaction (p = 0.463), and caregiver strain (p = 0.162) were also not significant moderators in this relationship. None of the psychosocial factors by time interactions reached statistical significance and were not included in the final models.
4. Discussion
The present study investigated the role of caregiver psychosocial factors as predictors and moderators in the relationship between stroke severity and cognitive outcomes. As expected, stroke severity was a significant predictor of cognition in this analysis, with higher stroke severity predicting lower cognitive composite scores. Of the caregiver psychosocial factors, both caregiving strain and caregiver leisure time satisfaction were significant predictors of longitudinal cognition in this sample of stroke survivors. Higher caregiver leisure time satisfaction and lower caregiver strain were both associated with better cognitive outcomes in stroke survivors. Depressive symptoms, life satisfaction, and overall QoL in caregivers were not significant predictors in this analysis. Regarding the exploratory hypothesis, none of the caregiver psychosocial factors served as moderators in the relationship between stroke severity and cognition. Therefore, the associations between caregiver psychosocial factors and cognition did not significantly vary depending on the severity of the stroke. None of the caregiver psychosocial factors by time interactions reached statistical significance and were not included in the final models. The lack of a significant time interaction also suggests consistency across different timepoints post‐stroke.
4.1. Caregiving Strain
The significant predictive value of caregiver strain on stroke survivor cognitive outcomes indicates an association of the challenges involved with the caregiving role and the recovery of stroke survivors. As was the case with the other caregiver psychosocial variables, caregiver strain was not found to be a moderator of the relationship between stroke severity and cognition. This indicates that the relationship between caregiving strain and cognition is independent of the severity of the stroke. The relationship between higher caregiver strain and poorer cognitive outcomes could be attributed to various factors, including reduced ability or time for caregivers to engage effectively in rehabilitation efforts, less social or cognitive stimulation, and a higher likelihood of negative interactions with their care recipients/stroke survivors, especially in stroke survivors who are experiencing more cognitive impairment [25]. This finding is in line with existing literature that suggests the well‐being of caregivers is associated with patient outcomes, particularly in post‐stroke recovery scenarios [5, 8]. As caregiver strain is a significant factor in the cognitive outcomes of stroke survivors in this analysis, interventions aimed at reducing caregiver strain should be tailored to address the specific challenges and stressors caregivers face, rather than only focusing on the severity of the stroke survivor's impairments.
4.2. Leisure Time Satisfaction
Higher caregiver leisure time satisfaction correlated with improved cognitive outcomes in stroke survivors. It is notable that leisure time satisfaction did not moderate the relationship between stroke severity and cognitive outcomes. This indicates that the suggested positive influence of caregivers' leisure time satisfaction on outcomes is independent of the severity of the care recipient's stroke. However, it is still possible that caregivers who report more leisure time are more likely to care for stroke survivors with less disabling stroke outcomes. Therefore, this relationship might be attributed to reduced burnout and enhanced emotional well‐being in either the caregiver, the stroke survivor, or both in stroke survivors who have decreased cognitive impairment. One additional conclusion of this finding suggests that caregivers who effectively manage their leisure activities could provide higher quality care. Caregivers with higher leisure satisfaction might also be more active and able to include their care recipient in their own leisure time activities, leading to better outcomes for the stroke survivors [35].
These findings indicate the importance of including caregiver well‐being in stroke intervention programs, suggesting that supporting caregivers' leisure and self‐care needs might indirectly enhance cognitive outcomes for stroke survivors. This is consistent with the current literature that supporting caregivers in maintaining their own well‐being and leisure activities may have a beneficial impact on the rehabilitation of the care recipient [5, 36]. These results contribute further evidence for holistic approaches in stroke rehabilitation that consider needs of both the caregiver and the patient.
4.3. Depressive Symptoms
Regarding caregiver depressive symptoms, reported depressive symptoms were not a significant predictor of cognition in this sample. It should be noted that the mean score in this sample falls well below the clinical depression risk cut‐off of 16 for the CES‐D [16]. This suggests that the caregivers in this study were generally not experiencing a high number of depressive symptoms. The lower prevalence of depressive symptoms could explain the lack of a significant impact on the cognitive outcomes of stroke survivors. A higher number of depressive symptoms may be necessary to observe a measurable effect on patient outcomes. The four‐factor model of depressive symptoms, outlined by Roth, et al. [37], offers a comprehensive approach to evaluating depressive symptoms in caregivers. This model explains that depression is not a singular construct and, despite the general absence of clinically significant depression, nuanced variations in well‐being and interpersonal relations could still critically influence the caregiving dynamics and the subsequent recovery outcomes of the stroke survivors. Future research should incorporate a multi‐dimensional approach to assess caregiver depression, informed by the four‐factor model. This involves evaluating depressed affect, well‐being, interpersonal problems, and somatic symptoms separately rather than relying on aggregate scores alone. Such a nuanced assessment can provide a more accurate depiction of the caregiver's mental health status and identify specific areas that may influence patient care and cognitive outcomes [38].
4.4. Quality‐Of‐Life
The caregivers' QoL was not a significant predictor of cognition. Similar to the mean CES‐D scores, the average scores on both the physical and mental QoL scales were above the clinical cut‐off for poor QoL [24]. This indicates that the caregivers in this sample perceived their QoL as generally satisfactory, and could help to explain the absence of significant findings in this domain. In scenarios where caregivers experience higher QoL satisfaction, the impact on their caregiving role and the cognitive outcomes of stroke survivors may be less observable compared to situations where caregivers report worse overall QoL. Prior research has shown an association between caregiver psychosocial symptoms, such as QoL, depression, and anxiety, and the stroke survivor's reported QoL [9, 39]. While these studies did not measure cognition as an outcome, there has been a consistent finding between these studies that stroke survivor mental health outcomes are related to the reported QoL of their caregivers. Future studies should examine cognitive outcomes in a sample of stroke survivors whose caregivers report a larger distribution of QoL scores.
4.5. Life Satisfaction
Regarding caregiver life satisfaction, the findings also did not indicate a significant relationship with cognitive outcomes in stroke survivors. This might suggest that life satisfaction, as a broader measure of well‐being, does not have a measurable impact on the specific task of caregiving for stroke survivors. The literature suggests that caregiver life satisfaction encompasses a wide range of factors that may not directly influence the day‐to‐day realities of caregiving [40]. For example, the quality and availability of available support, the stroke survivor's functional impairment, and the duration of the caregiving role are only some factors that might play significant roles in determining the extent to which caregiver life satisfaction translates into patient outcomes [25].
4.6. Strengths & Limitations
This investigation displays several strengths, including longitudinal cognitive assessments at multiple time points in stroke survivors. These repeated assessments provide a detailed exploration into how cognition changes in the years following a person's first stroke. An additional strength is the covariate adjustment of pre‐stroke cognitive performance and demographic variables. Also, leveraging a community‐drawn cohort increases the generalizability of the study findings, along with the sample's size and diversity. However, this study also has limitations. One notable limitation is the use of secondary data in this manuscript, which was not collected with the specific aim of answering the questions posed in this analysis. Further, given that the original CARES study was observational, the insights derived from this data are inherently associative. Another limitation is that, due to missing data, stroke type and location were not included in the final models. This limits the conclusions that can be drawn from the present study regarding understanding the development of vascular cognitive impairment in this sample. Future investigations from this analysis will seek to understand additional predictors of post‐stroke cognition, such as social determinants of health. Future studies should also examine the longitudinal relationship between stroke caregivers and cognition in a larger, more diverse sample of stroke survivors with caregivers that report clinically significant levels of the included psychosocial factors.
5. Conclusion
The results of this study help to inform the relationship between certain caregiver mental health aspects and post‐stroke cognition. Recently, there has been an increase in research studying the impact of the caregiving role on the caregiver itself. However, a link between caregiver factors and stroke survivor cognitive or physical outcomes is understudied in the current literature. This analysis contributes to evidence that caregiver factors are associated with post‐stroke outcomes and can better inform the factors contributing to the cognition after stroke.
Author Contributions
O.J.C. helped with designing and implementing the original CARES study. O.J.C., & J.D.R. were involved in the data collection of the CARES study. J.A.B. conceptualized this manuscript, performed the data analysis, and interpreted the data. Analysis was assisted primarily by D.L.L., S.E.J., & O.J.C., J.A.B. wrote the manuscript, all additional authors provided supporting conceptualization and manuscript revisions. D.L.R. secured partial funding for the initial CARES ancillary study.
Ethics Statement
Both the REGARDS and CARES projects were reviewed and approved by the Institutional Review Boards of the University of Alabama at Birmingham and each participating institution. Use of deidentified data was approved by the IRB at the University of Alabama at Birmingham for the purposes of this manuscript (IRB‐300009166‐001).
Consent
Informed consent was collected by all participants whom data was collected at any point during both the REGARDS and CARES projects.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgments
This research project is supported by cooperative agreement U01 NS041588 co‐funded by the National Institute of Neurological Disorders and Stroke (NINDS) and the National Institute on Aging (NIA), National Institutes of Health, Department of Health and Human Service. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NINDS or the 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/.
Funding: This research project is supported by cooperative agreement U01 NS041588 co‐funded by the National Institute of Neurological Disorders and Stroke (NINDS) and the National Institute on Aging (NIA), National Institutes of Health, Department of Health and Human Service. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NINDS or the 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/. Funding for the initial CARES ancillary study was provided by an investigator‐initiated grant (R01 NS045789, David Roth, PhD, PI) and by a cooperative agreement (U01 NS041588) from the NINDS and the NIA, National Institutes of Health, Department of Health and Human Services. Representatives from the above funding sources did not have any role in the design and conduct of the study, the collection, management, analysis, and interpretation of the data, or the preparation or approval of the manuscript. There was no external funding for the analysis of this manuscript.
Data Availability Statement
The data that support the findings of this study are available from the REGARDS Executive Committee. Due to the sensitive nature of the data collected for this study, restrictions apply to the availability of these data. Requests to access the dataset from qualified researchers trained in human subject confidentiality protocols may be sent to REGARDS at 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
The data that support the findings of this study are available from the REGARDS Executive Committee. Due to the sensitive nature of the data collected for this study, restrictions apply to the availability of these data. Requests to access the dataset from qualified researchers trained in human subject confidentiality protocols may be sent to REGARDS at REGARDSAdmin@uab.edu.