Caregiving for a family member or friend who needs a level of daily assistance that is outside of the normal range of duties for a specific life role (e.g. outside of normal parenting duties) has been conceptualized as both a categorical stressor exposure variable and as a continuous stress response variable.
As a stressor exposure, caregivers are categorized as either performing caregiving duties (options for defining this presented below) or not (this group serves as the non-caregiving controls). As a stress response variable, for those who are caregiving, respondents are asked to what degree the caregiving activities are distressing and disruptive to their life using a variety of self-report measures.
Informal (unpaid) caregivers are at increased risk for health problems compared to age-matched non-caregivers. Two meta-analyses have found that informal caregivers have poorer physical health than non-caregivers (Pinquart & Sörensen, 2007; Vitaliano, Zhang, & Scanlan, 2003). These studies included measures of both self-reported physical health and objective physical health indices, including stress hormones and medication use. Caregivers may be at increased risk of health problems for multiple reasons. For example, there may be physiological changes relevant for disease states that are caused or exacerbated by psychological distress, and/or because psychological distress and caregiving duties interfere with healthy lifestyle choices (e.g. exercise, sleeping well, eating nutritiously). The effect of caregiving on caregiver health is likely dependent on how vulnerable the caregiver is, the resources available to them, and the interaction of vulnerability factors (e.g. comorbidities, psychiatric history) and resources (e.g. income, social support; Vitaliano, Zhang, & Scanlan, 2003). These individual difference factors have largely been ignored in caregiver research which has limited progress in this area since identifying these may help detect caregivers at risk, and contribute to the development of tailored interventions.
In addition to the studies cited above linking caregiving status to worse health, there have been several studies showing that caregiving has a beneficial effect on health (Brown et al., 2009; Fredman, Cauley, Hochberg, Ensrud, & Doros, 2010; Herrera et al., 2013). For example, several epidemiological studies reported that caregivers have significantly lower rates of mortality than non-caregivers. These studies generally did not include measures of perceived stress, though they did use sophisticated methods to adjust for confounders (Roth et al., 2013), bias (Fredman, Lyons, Cauley, Hochberg, & Applebaum, 2015), or used population census data (O’Reilly, Connolly, Rosato, & Patterson, 2008). Fredman & Roth (2010) explain these contradictory findings with their Healthy Aging Hypothesis, which suggests that if you track caregivers longitudinally, the cohort is likely healthier than non-caregivers because in order for them to be able to maintain their role as caregivers, they must be uniquely healthy, given the demands of a caregiving role. Unhealthy caregivers drop out of caregiving. Further exploration of this idea is needed, and the longitudinal tracking of caregiving status (whether someone is caregiving at multiple study time points, not just at the beginning of study entry) is an essential component of addressing this question in future research.
Another explanation for the contradictory findings is that it is not about caregiving status per se, but rather, the psychological stress of the caregiving that is predictive of health decline. Indeed, Fredman et al (2010) found that dementia caregivers reported both the highest levels of stress and have worse health than other sub-types of caregivers and non-caregivers. Furthermore, in the same study, regardless of caregiver status, adults who reported high levels of psychological stress had significantly higher mortality rates over the following three years compared to low-stress adults. This is in line with a now-classic study by Schulz & Beach (1999) which found that there were no mortality rate differences between caregivers and non-caregivers, but for caregivers who reported being stressed by caregiving responsibilities had a 63% greater mortality risk over 4 years. As a more recent exploration of this, Epel et al. (2004) compared young maternal caregivers (caring for children with autism) and age-matched controls (mother with normally developing children) on physiological indices of healthy aging. While the two groups had similar levels of telomere length and oxidative stress, women with greater perceptions of global perceived stress (both caregivers and controls) had worse biomarker profiles. This is in line with decades of stress research which has shown that mere exposure to stressors is not associated with worse health for everyone. Instead, it is having the exposure – and in addition – having a strong perceived stress response to the exposure that is essential to the stressor’s ability to influence health.
Here, we suggest measures to capture both the objective aspects of caregiving (e.g. duration, intensity) and the caregiver’s response to caregiving (e.g. how much distress is it causing). We focus on measures that capture perceptions of stress related to caregiving. Other important aspects to capture include vulnerability factors (as described briefly below), resources (e.g. social support, respite care opportunities), and characteristics of the care recipient’s illness (in particular, the severity of disability). The existing measures are generally rather long compared to epidemiological standards though here we did focus on the shorter measurement options. There is a need for a short measure of caregiving experiences that is appropriate for population-level studies.
Measuring perceived stress from caregiving. There is a proliferation of measures for capturing distress from caregiving. Many of the measures tap similar constructs, and to our knowledge, the measures have not been compared head to head in the same study. Several reviews of measures of caregiving distress have been conducted, including one by Vitaliano & Young (1991) that focused on measures for caregivers of dementia patients, another by Deeken et al (2003) that included measures for caregivers of chronically ill patients more broadly, and a report by the Family Caregiver Alliance that focused on clinically relevant measures. Few of these scales have been translated into other languages. Below we highlight several measures that capture the psychological response to caregiving.
One scale used to capture the psychological, subjective response to caregiving is the Zarit Caregiver Burden Scale – short form (Zarit, Reever, & Bach-Peterson, 1980; Bedard et al., 2001). This 12-item measure captures perceptions of stress related to caregiving and their role as caregivers. High scores on this scale have been associated with health-related quality of life (Hughes et al., 1999), fatigue (Osaki et al., 2016), anxiety and depressive symptoms (Grunfeld et al., 2004), general mental health (McLennon, Habermann, & Rice, 2010), and lower health-promoting behaviors (Sisk, 2000) in a range of caregiver samples. Example items are: As a caregiver do you feel... (1) Stressed between caregiving and trying to meet other responsibilities (work/ family)? (2) Angry when you are around your care recipient? (3) That you have lost control of your life since you began providing care for your care recipient?
Another measure of caregiver distress that has been used is the Given’s Caregiver Reaction Assessment Scale (Given et al., 1992). The development of this 24-item measure was guided by the goal of capturing how caregiving had affected caregivers’ health, daily schedule, finances, changes in their life and self-worth from caregiving, and perceived support from others. Factor analysis identified five dimensions of caregiver reactions that are captured with this scale, including both positive and negative reactions: the impact of caregiving on disrupted schedule, financial problems, lack of family support, health problems and the impact of caregiving on self-esteem (Nijboera et al., 1999). Example items: Caring for my care recipient is important to me; I enjoy caring for my care recipient; I resent having to care for my care recipient. The positive items are a unique and important aspect of this scale, though may not capture all aspects of positive experiences related to caregiving (Persson et al., 2008). This scale has primarily been used to describe populations of caregivers, and less frequently to associate with or predict health outcomes.
A need in this field is to examine these measures more closely, to evaluate and compare the reliability and validity of these measures (i.e. content validity, internal consistency reliability, factor analyses/ construct validity, and criterion-validity). It is also important, though beyond the scope of this summary to examine whether these scales been used in randomized controlled trials and shown to be influenced by caregiver interventions.
How distressed a caregiver is by the demands of the caregiving role is influenced by many factors, including contextual, demographic, biological, psychological, and social components. The lack of group differences in health outcomes between caregivers and controls in some studies may be because not all caregivers are vulnerable to the potential negative effects of caregiving. Vulnerabilities are characteristics that interact with stress exposures and place someone at greater risk of being overwhelmed or distressed by the demands of caregiving, and thus at risk of poorer outcomes. Researchers have identified demographic, biological, personality, and contextual factors that place caregivers at greater risk of health decline. These factors can not be fully described in this brief summary, though those examining the impact of caregiving on health need to think carefully about measuring moderators and including them in analytic plans. Some of these vulnerability factors are co-morbidities of the caregiver such as metabolic syndrome, care recipient disease type and severity, and gender (Dyck, Short, & Vitaliano, 1999; Fredman, Cauley, et al., 2010; Fredman, Doros, Cauley, Hillier, & Hochberg, 2010).
This summary was prepared by Alexandra Crosswell, PhD and Elissa Epel, PhD, and reviewed by Lisa Fredman, PhD, and Peter Vitaliano, PhD. If you have any comments on these measures, email Alexandra.Crosswell@ucsf.edu. Version date: August 2018
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