Effects of COVID-19 on Informal Caregivers and the Development and Validation of a Scale in English and Spanish to Measure the Impact of COVID-19 on Caregivers
Abstract
To understand how the COVID-19 pandemic has affected caregivers, we assessed its perceived impact on caregiving through a new measure: the Caregiver COVID-19 Limitations Scale (CCLS-9), in Spanish and English. We also compared levels of caregiver self-efficacy and burden pre-COVID-19 and early in the pandemic. We administered surveys via internet to a convenience sample of caregivers in January 2020 (pre-pandemic, n = 221) and in April–June 2020 (English, n = 177 and Spanish samples, n = 144) to assess caregiver self-efficacy, depression, pain, and stress. We used the early pandemic surveys to explore the validity of the CCLS-9. The pre-COVID-19 survey and the April English surveys were compared to determine how the COVID-19 pandemic affected caregivers. The CCLS-9 had strong construct and divergent validity in both languages. Compared to pre-COVID-19, caregiver stress (p = .002) and pain (p = .009) were significantly greater early in COVID-19, providing evidence of its validity. COVID-19 added to caregiver stress and pain.
Approximately 43.5 million people in the United States are caregivers to a family member with a disability or illness (Family Caregiver Alliance, 2020). These people are termed informal caregivers as they are seldom trained for this role nor did they necessarily desire it. These “informal” caregivers provide indispensable health services to their family members and are considered by many policy makers to be front-line health service providers (American Psychological Association, 2020). The economic value of services provided by informal caregivers was estimated to be 470 billion dollars in 2013 (Family Caregiver Alliance, 2020).
In the best of times, caregivers have high levels of stress and depression. Caregiving can affect a caregiver’s emotional well-being, finances, and routine social activities as caregivers often feel unprepared for their role due to a host of personal factors and lack of skills (R. Brown & Brown, 2014; Reinhard et al., 2012). These effects are reflected in perceived caregiver burden and stress due to caregiving, as well as depression, and health problems (Loh et al., 2017; Schulz & Martire, 2004).
Little is known about how stress, depression, caregivers’ well-being, finances, and routine social activities are changed during a pandemic such as COVID-19 (Coronavirus disease, disease caused by novel Sars-CoV-2 virus). Already stressed, caregivers are trying to navigate these difficult times along with caring for friends or family. There is limited data on the impact or added burden of a pandemic or other natural or man-made calamity on caregivers. What is available is from the HIV pandemic. A study by Kohli et al. (2012) focused on exploring the perceptions and norms regarding care being provided by family caregivers for persons living with HIV. Most of the other studies were focused on caregiving for children with HIV or the effects of caregiver and household HIV on child development (Osafo et al., 2017; Sherr et al., 2016).
Several articles have elaborated on the roles and challenges for informal caregivers during the COVID-19 pandemic; however, literature on the experience of informal caregivers and how their self-efficacy is affected during COVID-19 pandemic is lacking. In their article, E. E. Brown et al. (2020) examined the current and expected impact of the COVID-19 pandemic on individuals with Alzheimer’s disease and related dementias (ADRD). They discussed possible effects of COVID-19 on caregivers of individuals with ADRD including difficulties with social distancing, caregiving associated exhaustion, and other factors. Kent et al. (2020) elaborated on the vital role family caregivers play during pandemics as professional health care work force is busy treating COVID-19 patients. They describe three main challenges facing caregivers during the pandemic—emotional stress, economic stress, and decreased routine health care options—and provide insights on how to best support family caregivers during COVID-19.
We could not find studies that specifically focus on caregiver self-efficacy or other factors that enhances or mitigated and the leading factors that add to caregiver strains during a pandemic or other unexpected man-made or natural upheavals on a similar scale. Caregiving self-efficacy relates to caregivers’ confidence in accomplishing caregiving tasks and coping with the difficulties of caregiving (Au et al., 2009; Lorig et al., 2019; Zeiss et al., 1999). Self-efficacy is one of the major components of the social cognitive theory. Many interventions designed to manage stress and improve behavioral skills are based on self-efficacy (Bandura, 1997). Steffen et al. (2002) have showed that self-efficacy is inversely related to caregiver stress. Several studies have been successful in improving self-efficacy by different interventions (e.g., yoga, occupational therapy) thus implying that caregiver self-efficacy may be a mediator to help caregivers achieve positive outcomes (Gitlin et al., 2001; Lorig et al., 2019; Waelde et al., 2004).
As a natural disaster the magnitude of COVID-19 is unparalleled, we have taken its advent as an opportunity to study the effects of this specific disaster on caregiving. We hypothesized that caregivers would have higher stress and lower self-efficacy during the COVID-19 pandemic. We created a new Caregiver COVID-19 Limitations Scale (CCLS-9) which might be useful in future man-made or natural disasters. This scale was tested in samples of English speakers throughout the United States and Spanish speakers from Latin America, mainly Peru.
Method
Study Design and Research Questions
To examine the impact of the COVID-19 pandemic on caregivers, we report on two broad research questions based on two studies. The overall design is shown in Table 1. First, to assess directly how the pandemic affected caregivers, we developed a new measure: the CCLS-9. We administered the CCLS-9 early in the pandemic (April 2020–June 2020) to two samples of caregivers, one in English in the United States (Sample 2) and one in Spanish (primarily in Latin America, Sample 3) (Supplementary File). We report the psychometric properties of the CCLS-9 and explore its construct validity in relation to measures of caregiver self-efficacy and caregiver burden (referred to as Study A in Table 1). Second, because we had administered the same measures of caregiver self-efficacy and caregiver burden in a prior survey conducted just before the COVID-19 pandemic, we compared levels in the early COVID-19 English-speaking sample (Sample 2) to our pre-COVID-19 sample of caregivers (Sample 1) (Supplementary File). This is referred to as Study B in Table 1. We wished to determine if burden was higher in the new English-language sample than in the pre-COVID-19 sample. Thus, the research design consisted of two studies (A and B) utilizing three samples (1, 2, and 3).
| Survey content | Published study: Prior to COVID-19 pandemic (Jan 2020) | Early in COVID-19 pandemic (Apr 2020) | |
|---|---|---|---|
| Sample 1 U.S. English | Sample 2 U.S. English | Sample 3 Latin America, Spanish | |
| CCLS-9 | — | A | A |
| COVID-19 experiences | — | A | A |
| CSES-8 | B | A/B | A |
| Caregiver burden measures | B | A/B | A |
Note. A: Data relevant to Study A: Test CCLS-9 in Samples 2 and 3. B: Data relevant to Study B: Compare caregiver self-efficacy and burden pre-COVID (Sample 1) to early COVID-19 (Sample 2) (both U.S. English samples). COVID = coronavirus disease; CCLS-9 = Caregiver COVID-19 Limitations Scale-9; CSES-8 = Caregiver Self-Efficacy Scale-8.
The research was approved by our institution’s Institutional Review Board. No incentives were provided to the participants.
The Samples and Recruitment
Sample 1
The pre-COVID-19 survey (Sample 1) was originally administered in January 2020 as part of a potential study of the effect of arthritis upon caregivers. Recruitment was via the internet, using a REDCap survey link on social media, mainly Listservs and blogs to convenience samples of informal caregivers of adults. Those receiving the links were urged to send them to other populations. Information regarding the trial, including description, risks and benefits, time involvement, participant’s rights, authorization, and contact information, were described in detail on the first page of the Redcap survey. Consent was obtained by asking the following two questions on the survey: I have read and understand the information provided “above” and “I agree to participate in this study.” If a participant selected “No” to either question, they were not able to complete the survey.
Sample 2
Both English- and Spanish-speaking early-COVID-19 samples were recruited similarly to the pre-COVID-19 sample. Questions were added to January 2020 survey and the English-language survey was administered to caregivers in the United States in April 2020.
Sample 3
Parodi J, one of the authors of this article, a geriatrician in Peru, was also interested in understanding the effects of COVID-19 on caregiving. He translated the survey into Spanish. This included all items in English-language Sample 2 (variables described below). It was then back translated into English by another professional colleague whose first language was also Spanish. The Spanish survey was then administered in May and June 2020 using Listservs and social media to caregivers in South America by Parodi J, although some surveys reached and were completed by Spanish-speaking caregivers in Mexico, Spain, and the United States.
Measures
We assessed caregiver stress using a visual numeric scale (on a 1–10 scale) and pain using a visual numeric scale (Ritter et al., 2006). Depression was measured with the eight-item Patient Health Questionnaire (PHQ-8, a modified version of the PHQ-9, Kroenke & Spitzer, 2002). Overall health was ascertained with a single-item measure from the health assessment questionnaire (ranging from poor to excellent; Ramey et al., 1992). We administered the eight-item Caregiver Self-Efficacy Scale (CSES-8) that measures obtaining respite, controlling negative thoughts, coping with new situations, stress management, self-care, finding resources, and preventing disruptions (Ritter et al., in press) Basic demographic included age and gender of caregiver and care recipient, relationship between caregiver and care recipient, number of hours of caregiving, and ethnic identification of caregiver. Ages and hours of caregiving used categories rather than require volunteer respondents to fill in exact numbers.
For the early COVID-19 surveys (Samples 2 and 3), we added questions about COVID-19 testing, symptoms, and hospitalization. We also developed and added a nine-item CCLS-9 which is described below.
Study A: Development and Validation of the CCLS-9, English and Spanish
Development of the CCLS-9
We developed items with input from all authors based on emerging information on how COVID-19 was affecting the general population and extrapolating this to how it might affect caregivers. The sources of information included the national press, our local clinical experience with senior living environments, and literature review. We identified specific areas of caregiving most likely to be adversely impacted by the pandemic, building on published measures of caregiver burden. The content of the initial 10 items included questions that focused on particular aspects of COVID-19 including the anxiety of contracting the disease, need for social isolation, contagion uncertainty (how it is transmitted), enhanced hygiene, limitations on going out and having visitors (including respite), limitations in access to health care, and the effect on the economy.
As context, we assessed caregivers’ experiences with COVID-19 by asking whether the caregiver or their care recipient had experienced any of a list of COVID-19 symptoms in the past month, and if so, whether they talked to a doctor about their symptoms, were tested, and needed hospitalization.
Analyses
We evaluated the basic psychometric properties of the CCLS-9 separately for the English-language and Spanish-language samples. This included examining item means, item-scale correlations corrected for overlap, and internal consistency reliability via Cronbach alpha. Principal components analysis was applied to determine if the scale consisted of multiple components or subscales. Once items were found to meet criteria of psychometric adequacy, we created an overall CCLS-9 score by averaging non-missing items. Scores ranged from 1 to 10, and a higher score indicates more limitations. If more than two items were missing, the entire scale was set to missing.
We used Pearson correlation coefficients to examine the associations between CCLS-9 with the caregiver burden measures (depression, stress, pain, overall health) and with caregiver self-efficacy (CSES-8). We hypothesized that self-efficacy, depression, and stress would be more strongly associated with the CCLS-9 than pain and overall health.
Study B: Comparison of Caregiver Stress/Burden Pre-COVID-19 to Early COVID-19, English Samples
Study B utilized data from our pre-COVID-19 survey (Sample 1 in Table 1) to compare with the English-language early COVID-19 sample (Sample 2 in Table 1). Because the same measures were administered in the newer sample, we were able to compare scores between the sample recruited pre-COVID-19 (Sample 1) and the new English-language sample recruited in April 2020 (Sample 2). We first compared the demographic characteristics of the two samples. Because these independent samples were collected using identical methodology, we hypothesized that there would not be significant differences in age, gender, education, or ethnicity. Continuous demographic variables had been collected using categories (e.g., age 50–59). We tested these variables in two ways: using the mean of the ranked categories (e.g., coded 0–6 for the seven age categories) and dichotomizing into roughly equal groups (e.g., aged 60 and above vs. less than 60).
The primary research question was to compare scores on the measures of caregiver burden (depression, stress, pain, overall health) and CSES-8 using independent sample t-tests, as appropriate. If we found significant differences between the two samples in any demographic variable, we would then use analysis of covariance models to test if there were significant differences in burden or self-efficacy after controlling for differing demographic variables. Otherwise, we used independent sample t-tests. We hypothesized that we would see higher levels of burden and lower self-efficacy in the early COVID-19 sample than in the pre-COVID-19 sample.
Results
Description of Three Samples
Because our two research questions involve presenting information from three samples, we describe all three samples: the pre-COVID-19 study of caregivers (Sample 1), and our two newer early-COVID-19 samples (Sample 2 English, Sample 3 Spanish). The demographics and caregiving characteristics of participants in all three samples are summarized in Table 2.
| Variable | Category | Sample 1: Pre-COVID-19 survey (N = 221) (%) | Sample 2: English early COVID-19 survey (N = 177) (%) | Sample 3: Spanish early COVID-19 survey (N = 144) (%) |
|---|---|---|---|---|
| Gender (% Female) | 88.9 | 86.8 | 83.0 | |
| Age | 18–49 | 16.1 | 17.8 | 34.8 |
| 50–59 | 24.8 | 25.3 | 29.1 | |
| 60–69 | 36.2 | 38.5 | 25.5 | |
| 70–79 | 16.5 | 14.9 | 9.2 | |
| >80 | 6.4 | 3.5 | 1.4 | |
| Ethnic category | Black | 18.2 | 17.9 | 1.4 |
| White | 74.2 | 75.1 | 24.3 | |
| Two or more races | 5.3 | 1.7 | — | |
| Mestizo | — | — | 62.9 | |
| Andino | — | — | 11.4 | |
| Other (Asian, Pacific, American Indian) | 2.4 | 2.3 | 0.0 | |
| Hispanic/Latino | 7.7 | 5.2 | 99.3 | |
| Education (highest level completed) | Primary | 0.5 | 0.6 | 0.7 |
| High school | 9.7 | 13.3 | 20.0 | |
| College | 46.3 | 41.0 | 45.7 | |
| Graduate school | 43.5 | 45.1 | 33.6 | |
| Relationship to care recipient | Spouse | 22.1 | 31.8 | 7.1 |
| Parent | 5.1 | 7.5 | 1.4 | |
| Child | 51.2 | 46.8 | 61.7 | |
| Sibling | 6.5 | 2.9 | 3.6 | |
| Other | 15.2 | 11.0 | 26.2 | |
| Hours spent caregiving per week | 0–9 | 20.0 | 12.8 | 26.2 |
| 10–19 | 28.4 | 21.1 | 15.4 | |
| 20–29 | 14.0 | 18.9 | 12.8 | |
| 30–39 | 18.8 | 5.6 | 6.0 | |
| >40 | 28.8 | 41.7 | 39.6 | |
| Care partner gender (% Female) | 58.2 | 52.6 | 72.1 | |
| Care partner age | 18–49 | 5.1 | 8.7 | 1.4 |
| 50–59 | 6.1 | 3.5 | 2.1 | |
| 60–69 | 10.3 | 14.5 | 2.9 | |
| 70–79 | 24.8 | 22.7 | 25.7 | |
| >80 | 53.7 | 50.0 | 67.9 |
Note. COVID = coronavirus disease.
The pre-COVID-19 sample had a total of 228 responses, the early-COVID-19 English survey had 221 responses, and the early-COVID-19 Spanish survey had 175 responses. Of these, the number of complete surveys were 221 (pre-COVID-19), 177 (early COVID-19 English), and 144 (early COVID-19 Spanish) each.
Study A: Development and Validation of the CCLS-9
As seen in Table 2, the majority of the respondents in early-COVID-19 English sample were White (75.1%), whereas in the Spanish-language sample, the majority of the respondents were of mixed race (62.9%) followed by either White or Andino (Andes’ native) races. In the early COVID-19 English cohort, 31.1% of the care recipients were spouses, whereas only 7.1% of care recipients in the early COVID-19 Spanish cohort were spouses. The amount of time spent caregiving was similar in both samples (more than 40 hr weekly caregiving for both early COVID-19 English sample [41.7%] and early COVID-19 Spanish sample [39.6%]). One caregiver and one care partner had tested positive for COVID-19 in the English sample, whereas one caregiver and five care partners had tested positive for COVID-19 in the Spanish sample. Dementia, high blood pressure, diabetes, heart disease, and stroke were the most common primary or co-morbid conditions among the care recipients in both the samples.
After initial psychometric examination in both languages, we dropped one item that proved to be redundant, resulting in nine items. The final nine items for the CCLS-9 are shown in Table 3 in English and Spanish.
| English Version of the CCLS-9 |
|---|
| Instructions for all items are to rate difficulties, limitations, and changes at the present time on a 1–10 scale. |
| 1. How worried/anxious are you that you will get COVID-19? |
| 2. How worried/anxious are you that your care partner will get COVID-19? |
| 3. How much has coronavirus affected your household source of income? |
| 4. How much has limitations on going out changed your ability to care for your care partner? |
| 5. How much has limitations on getting respite changed your ability to care for your care partner? |
| 6. How much has limitations on outside visitors/friends/family changed your ability to care for your care partner? |
| 7. How difficult has it been for you to explain COVID-19 related limitations to your care partner? |
| 8. Have you noticed changes in your care partner’s behaviors because of limitations imposed by COVID-19? |
| 9. How much has limited ability to access health care due to COVID-19 changed your ability to care for your care partner? |
| Spanish Version of the CCLS-9 |
| Las instrucciones para todos los ítems son calificar las dificultades, limitaciones y cambios en el momento actual en una escala de 1 = 10. |
| 1. ¿Qué tan preocupado / ansioso está usted por contagiarse de COVID 19? |
| 2. ¿Qué tan preocupado / ansioso está usted de que la persona que cuida se contagie de COVID 19? |
| 3. ¿Cuánto ha impactado el coronavirus a la fuente de ingresos de su hogar? |
| 4. ¿En qué medida las limitaciones para salir cambiaron su capacidad de cuidar a la persona que cuida? |
| 5. ¿En qué medida han cambiado las limitaciones para obtener un respiro (descanso) en su capacidad de cuidar a su compañero de cuidado? |
| 6. ¿En que medida las limitaciones de los visitantes externos / amigos / familiares han cambiado su capacidad de cuidar a su compañero de cuidado? |
| 7. ¿Qué tan difícil ha sido para usted explicar las limitaciones relacionadas con COVID 19 a la persona que cuida? |
| 8. ¿Ha notado cambios en el comportamiento de la la persona que usted cuida debido a las limitaciones impuestas por COVID 19? |
| 9. ¿En qué medida la capacidad limitada para acceder a la atención médica debido a COVID 19 cambió su capacidad para cuidar a su compañero de cuidado? |
Note. CCLS = Caregiver COVID-19 Limitations Scale; COVID = coronavirus disease.
Principal components analysis resulted in two factors in both languages. Items 1 and 2 loaded on one factor, and the other seven items loaded on a second factor. This suggests that the measure comprises two dimensions: worry/anxiety about getting COVID-19 and limitations on their ability to provide caregiving.
The overall mean score was 5.42 (SD = 1.97) for the English-language caregivers (N = 175) and 5.06 (SD = 2.13, N = 140) for Spanish speakers. Mean scores for the two samples were not significantly different (Table 4). In the English-speaking sample, no participants had a minimum value of 1 and two participants (1.1%) had the maximum value of 10 on the CCLS-9. Among Spanish speakers, one participant had the minimum value of 1 (0.7%) and no participants had the maximum value of 10.
| Item # | English-language survey (N = 168) | Spanish-language survey (N = 138) | ||
|---|---|---|---|---|
| Alpha = .80 | Alpha = .84 | |||
| Item mean (SD) | Correlation with totala | Item mean (SD) | Correlation with totala | |
| 1 | 5.85 (2.64) | 0.40 | 5.91 (3.11) | 0.52 |
| 2 | 6.98 (2.87) | 0.44 | 7.13 (2.99) | 0.44 |
| 3 | 3.75 (3.32) | 0.39 | 5.42 (3.27) | 0.46 |
| 4 | 5.94 (3.28) | 0.62 | 4.24 (3.26) | 0.67 |
| 5 | 4.96 (3.69) | 0.57 | 5.14 (3.16) | 0.62 |
| 6 | 6.46 (3.16) | 0.64 | 4.84 (3.62) | 0.61 |
| 7 | 5.20 (3.45) | 0.39 | 4.38 (3.36) | 0.51 |
| 8 | 5.61 (3.26) | 0.48 | 4.16 (3.05) | 0.55 |
| 9 | 4.40 (3.33) | 0.49 | 4.64 (3.36) | 0.59 |
We had hypothesized that self-efficacy, stress, and depression would be associated with COVID-19 limitations. In both the English-language and Spanish-language samples, the CCLS-9 scale had moderate and statistically significant correlations with caregiver self-efficacy, PHQ-8 depression, and stress (all p < .001, Table 5). The CCLS-9 was only weakly associated with pain and overall health in the English-language sample (p = .045 and p = .087, respectively) but had stronger and statistically significant associations in the Spanish sample (p < .001 and p = .012, respectively).
| Health measure | English sample N = 177 r (p) | Spanish sample N = 144 r (p) |
|---|---|---|
| Caregiver Self-Efficacy (CSES-8) | −.45 (<.001) | −.35 (<.001) |
| Depression (PHQ-8) | .39 (<.001) | .50 (<.001) |
| Stress (Visual Numeric) | .40 (<.001) | .41 (<.001) |
| Pain (Visual Numeric) | .14 (.045) | .29 (<.001) |
| Overall Health In general, would you say your health is (good to poor)? | .13 (.087) | .21 (.012) |
Note. CSES = Caregiver Self-Efficacy Scale; PHQ = Patient Health Questionnaire.
Item-scale correlations ranged from .39 to .64 in the English-speaking sample and from .45 to .67 among the Spanish speakers. The internal consistency reliability (coefficient alpha) was .80 and .84 for the English-language and Spanish-language samples, respectively (Table 4).
Study B: Comparison of Caregiver Burden Pre-COVID-19 and Early in the COVID-19 Pandemic
Comparing the demographics of the two samples, there were no statistically significant differences in age, gender, age of care recipient, gender of care recipient, or caregiver education (Table 6). This was true for categorical variables as well as for taking the mean of the ranked categories. Only the dichotomized results are shown in Table 6. As hypothesized, the two samples were similar demographically.
| Variable | Pre-COVID-19 N = 221 | Early-COVID-19 N = 177 | p of difference (df, t value) |
|---|---|---|---|
| Proportion age 60 or older (0, 1) | .59 | .58 | .743 (395, 0.33) |
| Gender (proportion female) | .89 | .87 | .596 (393, 0,53) |
| Proportion care recipient 70 or older | .54 | .51 | .610 (388, 0.51) |
| Care-recipient gender (proportion female) | .64 | .57 | .222 (386, 1.22) |
| Proportion education graduate school | .44 | .44 | .952 (392. –0.06) |
| Proportion White ethnicity (0–1) | .74 | .75 | .683 (389, –0.41) |
| Proportion care-recipient a parent (0–1) | .51 | .47 | .467 (392, 0.73) |
| Caregiver self-efficacy (CSES-8) | 5.72 | 5.92 | .334 (387, –0.97) |
| Depression (PHQ-8) | 1.86 | 2.07 | .156 (391, –1.42) |
| Stress | 6.46 | 7.23 | .002 (390, –3.07) |
| Pain | 3.62 | 4.32 | .009 (335, –2.64) |
| Overall health | 2.75 | 2.60 | .095 (389, 1.68) |
| Hours caregiving ≥20 hr | .52 | .66 | .005 (388, –2.82) |
Note. ps are calculated using t-tests of independent samples. Categorical variables are dichotomized to roughly equal categories. CSES = Caregiver Self-Efficacy Scale; PHQ = Patient Health Questionnaire.
Comparing Sample 1 (Pre-COVID-19) with Sample 2 (English early COVID-19), the mean scores of stress and pain were greater in the later sample (p = .002, p = .009, respectively). PHQ-8 depression (p = .156), caregiver self-efficacy (CSES-8) (p = .334), and overall health (p = .095) were not significantly different (Table 6). Hours of caregiving were also significantly higher in the later sample than in the earlier sample.
Discussion
The COVID-19 pandemic has disrupted normal lives in multiple ways, which is expected of pandemics and several other man-made and natural disasters (e.g., hurricanes, earthquakes, political unrest). Caregiving is known to be stressful for caregivers. Little is known about the added burden of such difficult times on this population; our study suggests that pandemics such as COVID-19, at least in early stages, affects caregiving thus making it more challenging.
The CCLS-9 Scale had good internal consistency reliability in both English- and Spanish-speaking samples and was well distributed with no evidence of floor or ceiling effects. Its moderate association with other limitation and health measures suggests good discriminant validity, although this should be further tested. The overall mean score in CCLS-9 (on a scale of 1–10) was 5.42 in English-language caregivers and 5.06 in Spanish-language caregivers. This may imply that COVID-19 had an overall moderate impact on caregivers early in the pandemic. Further study would be required to determine the level of burden associated with specific values of the CCLS-9. We are not aware of a similar measure which could be used to test for content validity. International testing of this scale further supports its use on a wider population. Implementing measures to improve the health and self-efficacy of caregivers during such difficult times can be a key element, as a primary agent, for the prevention and management and functional rehabilitation of older people with chronic conditions (de Carvalho et al., 2019).
Although its wording is specific to the COVID-19 pandemic, it could be adapted to other diseases or disasters that might limit the ability of family or other caregivers. Certain questions on the COVID-19 scale are more specific for COVID-19 and similar pandemics (anxiety about caregiver or care-partner contracting the disease and limitations on going outside or limitations on visitors—questions 1, 2, 4, and 6 in Table 2). However, other validated questions on the questionnaire can have wider implementation for caregivers during other large-scale disruptions/disasters (a particular pandemic/disaster affecting household income, limitations on getting respite or explaining limitations to care-partner due to ongoing pandemic/disaster, changes in care partner’s behavior due to limitations imposed by an ongoing disaster, and limitations imposed by difficulties accessing health care; questions 3, 5, 7, 8, and 9 in Table 2).
COVID-19 has disproportionally affected the U.S. Hispanic and African American communities. In our study, we did not find a significant difference in terms of caregiver outcomes between minority and non-Hispanic White communities. The characteristics of families in Latin America and the Caribbean (LAC) are somewhat different than those in the United States. Older people with care dependency are still mostly cared for at home by family members, sometimes using a caregiver hired by themselves (National Institute of Statistics and Informatics, 2019). Long-term care systems in LAC are still under construction and health and social services are fragmented, poorly coordinated, and in many cases without universal coverage (Custodio et al., 2014). In these countries, high out-of-pocket costs have been reported for families for the care of elderly people with dementia (Custodio et al., 2015). Likewise, a high level of stress and little perception of self-efficacy of caregivers to carry out their tasks during the pandemic have been reported (Navarrete-Mejía et al., 2020). It is for this reason that it seemed pertinent to investigate and compare Spanish-speaking caregivers with English-speaking caregivers in the context of the COVID-19 Pandemic.
In our comparison to the pre-COVID-19 study, we found that COVID-19 did not seem, in the short term, to affect some symptoms including depression and self-efficacy, nor did it affect participant’s perception of their general overall health. The lack of impact of COVID-19 on depression or overall health could either be due to the fact that the disease or threat of disease do not appear to affect these parameters or that they were quite high to begin with and maybe had already reached a near-ceiling effect. We plan to conduct a follow-up survey for the participants who have left their email addresses, and it would be interesting to study these factors and changes in CCLS-9 after the newness of the pandemic wears off.
There were several limitations to this study. The major one was the use of convenience samples. We had no way to assess how many people who were eligible to respond chose not to. Very few of the respondents reported COVID-19 symptoms or care recipients with COVID-19 symptoms, so this is not a study of the direct effect of COVID-19 disease, but rather of the effects of the social environment and restrictions associated with COVID-19. We could not determine whether the caregivers were living with the care recipients and if they were the sole caregivers of the care recipients. Most of the responders were highly educated (as might be expected of those who use Listservs) and we could not determine if differences in education may affect outcomes. More caregivers in Samples 2 and 3 (early COVID-19 cohorts) were spending more than 40 hr weekly on caregiving than Sample 1 (pre-COVID-19 cohort). This could explain some differences in the outcome (particularly stress); however, more hours spent caregiving could have been a direct result of COVID-19, as help from outside may be limited. Further study would be required to confirm this.
Conclusion
To our knowledge, this is the first study to compare pre- and early-pandemic caregiving samples and to test the validity of a measure to assess the impact of a pandemic on caregivers. A wider implementation of this measure is possible for other pandemics and disasters.
Acknowledgments
We would like to acknowledge Julia Simard, ScD, for her help with developing the CCLS-9 scale and Martha Pelaez, PhD, for her help in back-translating the Spanish scale.
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.
ORCID iDs
Khushboo Sheth https://orcid.org/0000-0003-1681-3252
José F. Parodi https://orcid.org/0000-0002-0336-0584
Footnote
IRB Approval The study was approved by Stanford’s Institutional Review Board (IRB study approval numbers 54099 and 56007).
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