Work Performance Among Informal Caregivers: A Review of the Literature

Abstract

Objectives: To examine the association between informal caregiving and caregiver work performance. Method: A systematized review of the literature. Results: We found that caregiving has an adverse impact on work performance: caregivers experience substantial work disruptions and negative work performance outcomes, and these findings were consistent across measures. Our synthesis suggests that caregivers miss a significant amount of work and have reductions in productivity due to their caregiving responsibilities. However, significant methodological limitations with the reviewed studies make systematic interpretations and causal determinations challenging. Discussion: Examining the effect of caregiving on work performance is critical to better understand the full impact of caregiving, especially as demand for caregivers increases as the population ages. This comprehensive review suggests that caregiving has a significant negative impact on work performance, although methodological challenges remain in this area of science. These findings should inform both public policy development and workplace benefits design.

Keywords

caregiving employment productivity work performance

Introduction

Informal caregivers, or family and friends who provide care or assistance to a loved one, are a primary source of support and assistance to family and community members as they age, become ill, or are otherwise unable to perform activities of daily living. Approximately 34.2 million Americans—nearly 15% of all adults in the United States—have been a caregiver to a family or friend aged 50 or older in the prior 12 months (National Alliance for Caregiving and AARP, 2015).

Being an informal caregiver is demanding and time consuming. Although our study focuses on caregivers of older adults, caregivers vary widely and care for a wide range of populations. There is a fair amount of heterogeneity in who the caregivers are and the intensity of care that is provided. Women, primarily wives and daughters, are more likely than men to be in caregiving roles (Henretta, Hill, Li, Soldo, & Wolf, 1997; McGarry, 1998; Pillemer & Suitor, 2006), and wives tend to provide more hours of care relative to other caregivers (Friedman, Shih, Langa, & Hurd, 2015). White family caregivers are also more often spouses than are family caregivers from other race-ethnic groups (Janevic & Connell, 2001), and individuals with dementia from minority race-ethnic groups tend to receive more intensive hours of care from their family caregivers compared to White older adults with dementia (Friedman et al., 2015).

Informal caregivers perform a wide range of tasks for care recipients, from arranging and attending medical appointments and assisting with health care decision making to dressing, bathing, and helping with shopping and other activities of daily living. Assisting with these activities requires a significant time commitment on the part of caregivers. Many caregivers provide more than 9 hr per week of unpaid care, and 23% provide more than 40 hr per week (National Alliance for Caregiving and AARP, 2015). The time spent providing care is often in addition to other employment demands: roughly 56% of caregivers are employed full time and work on average 34.7 hr per week (National Alliance for Caregiving and AARP, 2015).

The consequences of informal caregiving on caregivers’ formal employment have been the focus of much empirical investigation. Two recent systematic reviews of the literature focused extensively on the effect of caregiving on labor force participation, in terms of both the number of hours that caregivers supply and caregivers’ decisions to either seek employment or to stop working (Bauer & Sousa-Poza, 2015; Lilly, Laporte, & Coyte, 2007). Although these reviews generally identified a negative association between caregiving and employment, the effect sizes tended to be modest. Caregivers were only slightly more likely to be unemployed than noncaregivers. Lilly et al. (2007) did find, however, that caregivers were likely to work fewer hours than noncaregivers. Effect sizes were largest among specific populations, namely women who live with a care recipient and caregivers whose burden is especially high (Bauer & Sousa-Poza, 2015; Lilly et al., 2007). Findings from these review papers also show that even though most caregivers stay employed, they are likely to adjust their workloads (in terms of total hours worked) in response to the demands of caregiving. Both reviews note that causation is extremely difficult to assess in these studies, in part because people who choose to become caregivers may be inclined to leave the workforce independently of assuming the role of caregiver (Bauer & Sousa-Poza, 2015).

While these findings are important, they only reflect a small segment of the work experiences of caregivers. What is missing from existing reviews of this topic is an investigation that goes beyond work status and hours employed to look at the job productivity, quality of work, and missed days at work of the caregivers. All of these could be affected by caregiving responsibilities. For instance, caregiving responsibilities at home may affect work performance. There are several mechanisms through which caregiving can affect work performance: the caregiver may have difficulties focusing at work due to stress, preoccupation with caregiving demands, or lack of sleep, or they might need to interrupt work to manage caregiving responsibilities. No reviews to date have investigated work performance as measured by missed time or productivity among specifically within a population of caregivers who decide to stay in the workforce.

This topic is important for several reasons. Poor work performance during caregiving periods could affect a caregiver’s long-term earnings as well as future opportunities for promotions and raises. Moreover, the stress associated with balancing the demands of caregiving with work could have implications for working caregivers’ physical and mental health.

Many studies have focused on these important issues but they have not yet been reviewed in a single study. To fill this important gap in the literature, this article will use a literature review approach to examine the association between caregiving and work performance (i.e., missed time at work, productivity, and work quality) as well as caregiving characteristics associated with the relationship between caregiving and work performance.

Method

Search Strategy

This current study was part of a larger effort to identify the nondiscretionary costs and resource use among informal caregivers of older adults. While performing that systematic review, we identified a number of studies that focused on work performance among caregivers. Although we did not perform a full systematic review of work performance, we did use extensive systematic methods. By using systematic review methods, our current study exists in a middle ground between a narrative review, which do not require documentation of search methods, and systematic reviews. This sort of “systematized” review method has been used and discussed previously (Grant & Booth, 2009; Hacker, Anies, Folb, & Zallman, 2015).

We searched Ovid Medline (1990—November 13, 2015) and Ovid Medline In-Process & Other Non-Indexed Citations (1990—November 13, 2015) for studies examining costs and informal caregiving. A public health informationist with expertise in systematized review methods created a search for the following concepts: “older adults,” “informal caregivers,” and “costs and resource usage,” which included some employment outcomes including absenteeism. We include all of the specific search terms in Supplemental Appendix B. We then identified relevant studies from this initial search. Of the studies that we identified in the original search focusing on work performance, we performed reference mining through a title screen of the reference lists of the selected articles for additional studies. We also interviewed content experts for recommendations for additional studies. Once we had a final list of articles, we returned to Ovid Medline and used the “similar article” function to identify related studies published from November 2015 to November 2017.

Study Selection

For inclusion, studies had to be in English, focus on older adults, have quantitative findings, and focus on the relationship between informal caregiving and work performance. We included studies that focused on work performance in three categories: missed time at work, productivity, and “cross-cutting” measures that span those domains by combining aspects of missed work and productivity into a single measure. We excluded studies that focused on workforce participation, including entering or leaving the workforce or the total number of hours worked. As noted above, previous systematic reviews have already examined the relationship between caregiving and workforce participation (Bauer & Sousa-Poza, 2015; Lilly et al., 2007). Because our interest is in the observational relationship between caregiving and work performance, we also excluded studies that were part of an intervention study. In addition, studies were excluded if the focus was outside the scope of our study: if the focus was not on assessing impact on the caregiver, was on economic evaluation or opportunity cost assessment instead of on direct cost to the caregiver, or if it failed to distinguish between working in the home from working outside the home in its assessment of costs. Systematic reviews and purely qualitative and exploratory studies were also excluded. Finally, we excluded any non-United States studies.

Two reviewers evaluated all abstracts against these inclusion and exclusion criteria, with disagreements resolved through a third reviewer and through discussion. For each of the abstracts, we retrieved full-text articles and repeated the same approach. We did not use a specific definition of informal caregiving, although we did determine that the caregiver could not be providing care as part of an employment relationship.

Data Extraction

From each full-text article, we extracted key data including reference, sample, clinical condition of care recipient, data analysis methods, outcomes of interest, and findings. Two authors read each of the full-text articles and one author abstracted the data. The second author reviewed all data extracted. Disagreements were resolved by discussion and by consensus agreement between the two authors. All extracted data is in the Supplemental Appendix A. A summary table for all included studies describes the condition of the care recipient, analysis methods, sampling frame, outcome types, and publication year (Table 1). We then use a narrative review to describe the relationship between informal caregiving and three outcome types: missed work, productivity, and cross-cutting measures.

Table 1.

Details of Included Studies (n = 19).

Care recipient sample
General elderly	42.1%, 8 studies
Cancer	15.8%, 3 studies
Alzheimer’s disease and other dementias	15.8%, 3 studies
Functionally disabled elderly	5.3%, 1 study
Lupus	5.3%, 1 study
Orthopedics	5.3%, 1 study
Stroke	5.3%, 1 study
Post-acute home care	5.3%, 1 study
Outcomes
Missed work	73.6%, 14 studies
Productivity	42.1%, 8 studies
Cross-cutting measure	42.1%, 8 studies
Sampling frame
Convenience	36.8%, 7 studies
Nationally representative	52.6%, 10 studies
Other	10.5%, 2 studies
Analysis method
Self-reported effect of caregiving	73.7%, 14 studies
Cross-sectional comparison to comparison group	15.8%, 3 studies
Pre-post caregiving comparisons	10.5%, 2 studies
Year published
1984-1989	5.3%, 1study
1990-1995	36.8%, 7 studies
1996-2000	0%, 0 studies
2001-2005	10.5%, 2 studies
2006-2010	10.5%, 2 studies
2011-2015	15.8%, 3 studies
After 2015	21.1%, 4 studies

Results

Our database searches produced a total of 7,104 studies. Excluding duplicates, we screened 6,741 titles and abstracts. We identified 150 citations gathered from reference mining and expert consultation. After screening abstracts, we retrieved the full texts of 77 articles. We excluded 58 studies based on the restrictions mentioned in the methods section, so 19 studies remained for this analysis (See Appendix C).

Description of Included Studies

Table 1 shows the descriptive statistics of included studies. Nearly three quarters of the studies focused on caregiving for the general elderly (i.e., a general population of elderly care recipients without a specific condition), patients with cancer, or patients with Alzheimer’s disease or other forms of dementia. The remaining studies examined evidence on caregivers for functionally disabled elders, patients with lupus, orthopedic trauma, stroke, or post-acute home care.

The studies focused on various types of outcomes. The largest proportion (73.7%) included measures on missed work. 42.1% included measures on productivity; and 42.1% included cross-cutting measures that spanned performance, assessing missed work and productivity. Some measures included information about reliability and validity; others did not. Slightly more than half of the studies used a nationally representative sample or a local census, while 36.8% used a convenience sample of patients and/or caregivers. The remaining 10.5% of studies were based on a small sub-sample or proxy sample of a much larger nationally representative sample.

Nearly three quarters of the studies were cross-sectional and relied on respondents’ self-assessment of the impact caregiving had on their work performance. These typically asked caregivers to report on a variety of adverse work-related outcomes that are “due to caregiving.” Although these caregivers have no comparison group, they attempt to establish a “counter factual” (i.e., what would happen if they were not caregivers) by asking respondents which of the outcomes (e.g., days missed) are “due to caregiving.” Only three studies explicitly compared caregivers’ reports or outcomes to those of non-caregivers. Only two studies performed a pre- versus post-caregiving within-subject comparison on key outcomes, comparing reports for individuals before and after assuming caregiving responsibilities.

Missed Work

Around 14 studies focused on the relationship between caregiving and missed work. To assess missed time at work, researchers used a number of (self-reported) metrics, including the number of complete or partial missed days of work, the use of sick, vacation, or leave days, and other measures (e.g., “absenteeism”). We separated the 14 articles into the following four subgroups: general measure of missed work (7 studies), specifically enumerating days or hours lost (5 studies), use of sick days, vacation time, or leave time (4 studies), late or early arrival at work (3 studies), and a composite measure of missed work that combined several missed work metrics (1 study). The findings from these studies are described below and summarized in Table 2.

Table 2.

Missed Work, Summary Findings (n = 14 Studies).

Study	Caregiving context	Analysis method	Main findings
General measure of missed work
Al Sawah et al. (2017)	Lupus patients	Self-reported effect of caregiving	– Caregivers missed 12.8% of paid work time in past 7 days on average
Ganapathy et al. (2015)	Stroke	Self-reported effect of caregiving	– Mean absenteeism of 9%- The following were significant positive predictors of absenteeism: income < US$25,000, Income between US$25,000 and US$49,999, number of children under 18 years of age, lack of nursing home coverage for stroke survivor, and stroke survivor did not have other caregivers- Age was significantly and negatively associated with absenteeism
Krach and Brooks (1995)	General elderly	Self-reported effect of caregiving	– 48% missed work over 6-month period due to their own or family member’s illness
Mazanec, Daly, Douglas, and Lipson (2011)	Palliative care	Self-reported effect of caregiving	– 9.63% of caregivers reported loss of work in prior week
Mutschler (1994)	General elderly	Self-reported effect of caregiving	– The following were significantly related to the number of hours worked: hours of care weekly, household income < US$10,000, nonspouse caregiver cares for others besides elder, caregiver is spouse, male, non-White, caregiver has one of the following types of jobs: clerical, production/laborer, or executive/professional
Robison, Fortinsky, Kleppinger, Shugrue, and Porter (2009)	General elderly	Self-reported effect of caregiving	– Caregivers who missed work in the past year were less likely to be male, under age 61, and have a care recipient who has unmet needs for community long-term care services
Scharlach and Boyd (1989)	General elderly	Cross-sectional comparison to comparison group	– Caregivers took time off during a work day more frequently than non-caregivers (0.80 times vs. 0.48 times on average in the past 2 months)
Wolff, Spillman, Freedman, and Kasper (2016)	General elderly	Cross-sectional comparison to comparison group	– Caregivers who provided substantial help reported significantly higher rates of missed work (205) than those who gave some help (7%) and no help (3.5%)- Caregivers who provided substantial help reported significantly higher rates of absenteeism (2.1%) compared to those who provided some help (0.7%) and no help (0.2%)
Enumerating days or hours lost
Al Sawah et al. (2017)	Lupus patients	Self-reported effect of caregiving	– Caregivers missed 5.2 hr on average in past 7 days
Franklin, Ames, and King (1994)	Post-acute home care	Pre-post caregiving comparisons	From caregiving inception to 3 months later . . .
Franklin, Ames, and King (1994)	Post-acute home care	Pre-post caregiving comparisons	– Average workdays lost decreased from 8.53 to 4.83
Mazanec et al. (2011)	Palliative care	Self-reported effect of caregiving	– 17 hr lost in last week on average
Passik and Kirsh (2005)	Cancer patients receiving chemotherapy	Self-reported effect of caregiving	– 2.7 missed days of work over the course of one month
Scharlach and Boyd (1989)	General elderly	Cross-sectional comparison to comparison group	– Caregivers took more days off in the last 2 months (0.79 days for caregivers vs. 0.51 days for noncaregivers)
Leave or vacation time
Anastas, Gibeau, and Larson (1990)	General elderly	Self-reported effect of caregiving	– 64% used vacation time in the last year
Anastas, Gibeau, and Larson (1990)	General elderly		– 3% took leave of absence and 33% changed their work schedule
De Moor et al. (2017)	Cancer survivors	Cross-sectional comparison to comparison group	– 8% of caregivers took an extended leave from workAmong caregivers that took extended leave from work of at least 2 months:- 26% took paid leave only- 35% took unpaid leave only- 40% took paid and unpaid leave
Moore, Zhu, and Clipp (2001)	Community-dwelling male veterans	Self-reported effect of caregiving	– 39% used sick leave
Scharlach and Boyd (1989)	General elderly	Cross-sectional comparison to comparison group	– 11.4% took a personal leave at any point during caregiving
Late or early arrival at work
Moore et al. (2001)	Community-dwelling male veterans	Self-reported effect of caregiving	– 42% were late for work
National Alliance for Caregiving and AARP (2015)	General elderly	Self-reported effect of caregiving	– 49% went in to work late, left early, and/or took time off
Scharlach and Boyd (1989)	General elderly	Cross-sectional comparison to comparison group	In the last 2 months . . .
			– 15.1% extended a break
			– 16.1% arrived late for work
Composite measure of missed work
Mutschler (1994)	General elderly	Self-reported effect of caregiving	– 49% reported work constraints
Mutschler (1994)			– The following were significantly related to the probability of reporting work constraints: hours of care weekly, problem with cost of care, caregiver has primary responsibility, caregiver is spouse, work > 30 hr per week, and caregiver has a clerical job

General Measure of Missed Work

Seven articles reported the results of caregiving on general measures of missed work, including absenteeism, missing work in general, and determinants of missed work. Five of these articles focused on caregivers of a general elderly population. A study of the needs of working caregivers of older persons found that 48% of 760 working caregivers missed work over a 6-month period due to their own or a family member’s illness. However, the study is unclear about whether their own illness was related to caregiving (Krach & Brooks, 1995). Robison et al. surveyed 767 caregivers and conducted a regression analysis on the determinants of missed work due to caregiving (Robison, Fortinsky, Kleppinger, Shugrue, & Porter, 2009). This study measured missed work as a binary variable equal to 1 if caregivers reported using sick or vacation time in the past year for a reason related to caregiving, or 0 if they did not. The authors regressed the missed work variable on several caregiver and care recipient characteristics and found that women caregivers and caregivers under age 61 were less likely to miss work in the past year. Caregivers were also more likely to miss work if their care recipient reported having unmet needs for long-term services and supports. In a sample of 341 caregiving employees at a large California firm, Scharlach and Boyd (1989) found that relative to noncaregivers, caregivers took time off during a work day more frequently (0.80 times vs. 0.48 times on average in the past 2 months).

Using data from the National Study of Caregiving, Wolff and colleagues studied 656 employed caregivers to compare measures of missed work between caregivers who provided substantial help with care to caregivers who provided either some or no help with care (Wolff, Spillman, Freedman, & Kasper, 2016). The authors found that caregivers who provided more help reported significantly higher rates of missed work: 20% of those who provided substantial help reported missed work, 7% of those who provided some help, and 3.5% of those who provided no help.

The three remaining articles examined the effect of caregiving on caregivers taking care of specific populations including lupus, stroke, and palliative care patients. A national survey of 174 employed caregivers of patients with lupus found that these caregivers missed, on average, 12.8% of paid work time within the previous 7 days due to caregiving (Al Sawah et al., 2017). An Internet survey of 75 employed caregivers of stroke survivors with poststroke spasticity found an average absenteeism rate of 9% due to caregiving (Ganapathy et al., 2015). This study also identified several factors that are positively associated with absenteeism: income < US$25,000 (compared to an income of 40,000+), income between US$25,000 and US$40,000, more children under 18 years of age, lack of nursing home coverage for stroke survivor, and lack of other caregivers for the patient. Age was negatively associated with absenteeism, meaning that older caregivers were less frequently absent from work. A survey of 40 employed caregivers participating in an ongoing palliative care clinical trial found that within the last week, 9.63% of caregivers reported a loss in work time due to caregiving (Mazanec, Daly, Douglas, & Lipson, 2011).

Enumerating Days or Hours Lost

Five articles examined how caregiving affects the number of caregivers’ days or hours of work lost. Franklin and colleagues surveyed 236 employed female caregivers of elderly post-acute home care family members in Michigan (Franklin, Ames, & King, 1994). To examine whether work adaptation occurs for caregivers, the authors collected data at the point of caregiver role inception, and again 3 months later. They found that the average number of workdays lost decreased over this time period, from 8.53 days at inception to 4.83 days after 3 months. However, over half of this caregiver sample was no longer included in the study at the 3-month point because patients either died, were hospitalized or institutionalized, or recovered from their physical ailments and no longer needed care. For this reason, the decreases could be explained by a combination of attrition bias (i.e., the sicker patients needing more care were transferred to a different setting) and of patients recovering from their ailments.

Mazanec and colleagues (2011) found that caregivers of palliative care patients lost on average 17 hr of work within the prior week. During a month-long study of spousal care for patients receiving chemotherapy and experiencing significant fatigue, Passik and Kirsh (2005) found that their sample of 15 spousal caregivers working full-time missed an average of 2.7 work days over a month due to caregiving. The authors also found that spousal caregivers on average took an additional 1.29 sick days and 1.76 vacation days during the month of study due to caregiving. Scharlach and Boyd (1989) found that compared to noncaregivers, caregivers took more days off in the prior 2 months (0.79 days for caregivers vs. 0.51 days for noncaregivers). Finally, Al Sawah and colleagues (2017) found that caregivers of lupus patients missed 5.2 hr of work on average within the prior 7 days due to caregiving.

Leave or Vacation Time

Four articles examined the relationship between caregiving and leave or vacation time used by caregivers. In a national survey of 558 self-identified caregivers, Anastas and colleagues found that within the last year, the majority (64%) had used vacation time due to caregiving responsibilities (Anastas, Gibeau, & Larson, 1990). This study also found that as few as 3% took a leave of absence and as many as 33% changed their work schedule due to caregiving. A survey of 265 employed caregivers of elderly community-dwelling male veterans found that 39% of these caregivers used sick leave due to caregiving (Moore, Zhu, & Clipp, 2001). As a result of caregiving ever, 11.4% of caregivers took a personal leave (Scharlach & Boyd, 1989). De Moor and colleagues (2017) studied a nationally representative sample of caregivers of cancer survivors and found that 8% of caregivers took an extended leave (2 months or more) due to caregiving, typically using a combination of paid and unpaid leave.

Late Arrival to, or Early Departure From, Work

Three articles examined the extent to which caregivers arrived late to or left early from work. Moore and colleagues (2001) found that 42% of caregivers reported being late for work as a result of caregiving. The 2015 National Alliance for Caregiving (NAC) and AARP report found that 49% of working caregivers arrived late, left early, and/or took time off due to caregiving (National Alliance for Caregiving and AARP, 2015). Scharlach and Boyd (1989) found that within the prior 2 months, 15.1% of caregivers extended a break and 16.1% of caregivers arrived late for work due to caregiving.

Composite Measure of Missed Work

Mutschler (1994) created a composite missed work measure related to work constraints. Caregivers were considered to have work constraints if they worked fewer hours than desired, changed their work schedule, or took time off without pay due to caregiving. About 49% of caregivers reported at least one work constraint due to caregiving. The following were significantly related to the probability of caregivers reporting such constraints: weekly hours of care they provide, the costs of care, if the caregiver has primary responsibility for the patient, is the patient’s spouse, works > 30 hr per week, or has a clerical job.

Productivity

Regardless of whether caregivers’ workforce participation levels change, caregiving responsibilities may still impact productivity, which in turn may affect employment outcomes. We identified eight studies that focused on caregivers’ productivity at work. These studies used a variety of metrics to measure performance. Six studies estimated the extent to which caregiving affected productivity, one study examined care recipient symptoms that lead to productivity loss, and two studies examined the work outcomes that resulted from productivity loss. The studies are described here and summarized in Table 3.

Table 3.

Productivity, Summary Findings (n = 8 Studies).

Study	Caregiving context	Analysis method	Main findings
General measure of productivity
Al Sawah et al. (2017)	Lupus patients	Self-reported effect of caregiving	– 33.5% reduction in job effectiveness on average
Ganapathy et al. (2015)	Stroke	Self-reported effect of caregiving	– Mean presenteeism of 27% (SD = 26%)- Income < US$25,000 was significantly and negatively associated with presenteeism- Lack of nursing home coverage for stroke survivor significantly and positively associated with presenteeism- 8.8 hr of work lost due to restrictive productivity on average in past week
Mazanec, Daly, Douglas, and Lipson (2011)	Advanced cancer	Self-reported effect of caregiving	Within the last week . . .- 15.41% of caregivers reported an impairment while working- Caregivers had 22.88% overall work productivity loss
National Alliance for Caregiving and AARP (2015)	General elderly	Self-reported effect of caregiving	– 7% of caregivers received warning about performance/attendance
Passik and Kirsh (2005)	Cancer patients receiving chemotherapy	Self-reported effect of caregiving	– 32% felt they were less effective at work
Scharlach and Boyd (1989)	General elderly	Cross-sectional comparison to a comparison group	In the last 2 months . . .- 31.5% were too tired to work
Wolff, Spillman, Freedman, and Kasper (2016)	General elderly	Cross-sectional comparison to a comparison group	– Caregivers who provided substantial help reported significantly higher rates of presenteeism (7.9%) compared to those who provided some help (2.6%) and no help (2.7%)
Ziran, Barrette-Grischow, and Hull (2009)	Orthopedics	Pre-post caregiving comparisons	– Increase in mean level of employment burden- 16% reported some interference with employment before patient injury; 29% to 57% after injury

Of the six studies that examined the effect of caregiving on work productivity, two examined the effect of providing care for cancer patients. In one focused on caregivers of patients with advanced cancer, Mazanec et al. (2011) found that within the prior week, 15.4% of caregivers reported an impairment while working and 22.9% reported overall work productivity loss due to caregiving. Among spousal caregivers of cancer patients receiving chemotherapy, 32% felt they were less effective at work overall due to caregiving (Passik & Kirsh, 2005).

Three of the studies focused on general measures of productivity for caregivers of patients with particular conditions. Al Sawah and colleagues (2017) found that caregivers of lupus patients reported 33.5% reduction in “job effectiveness” (limited definition provided in study) on average due to caregiving. Caregivers of stroke survivors reported an average presenteeism due to caregiving (defined as working while sick or otherwise impaired) rate of 27% (Ganapathy et al., 2015). Ganapathy and colleagues also found that an annual income of less than US$25,000 was negatively associated with presenteeism, while a lack of nursing home coverage for stroke survivors was positively associated with presenteeism. Ziran and colleagues found that 16% of 57 employed caregivers providing care for orthopedic patients reported some interference with employment before a patient’s injury and 57% reported workplace interference after the injury (Ziran, Barrette-Grischow, & Hull, 2009). This was coupled with a significant increase in the mean level of self-assessed employment burden postinjury relative to the preinjury level.

In a study of caregivers of elderly patients without specific health conditions, Wolff and colleagues (2016) found that caregivers who provided substantial help reported significantly higher rates of presenteeism (7.9%) relative to those providing some help (2.6%) or no help (2.7%).

One study reported the prevalence of particular symptoms leading to caregivers’ productivity loss: Scharlach and Boyd (1989) found that 31.5% of caregivers studied were too tired to work productively in the prior 2 months due to caregiving.

Two studies examined outcomes of productivity loss. According to the National Alliance for Caregiving and AARP (2015) report on caregiving, 7% of caregivers received a warning about job performance/attendance since beginning caregiving duties (National Alliance for Caregiving and AARP, 2015). Ganapathy and colleagues (2015) found that caregivers of stroke survivors lost on average, 8.8 hr of work in the previous week because of reduced job productivity due to caregiving.

Cross-Cutting Measures

We identified eight studies that created “cross-cutting” measures that span multiple categories, including missed work or productivity (Table 4). Al Sawah and colleagues (2017) found that caregivers reported 27.4% overall work impairment, based on absenteeism and presenteesism, on average in the past week due to caregiving.

Table 4.

Cross-cutting measures, summary (n = 8 studies).

Study	Caregiving context	Analysis method	Main findings
Al Sawah et al. (2017)	Lupus patients	Self-reported effect of caregiving	− 27.4% work impairment on average
Anastas, Gibeau, and Larson (1990)	General elderly	Self-reported effect of caregiving	− 53% of caregivers reported no conflict, 39% reported a conflict, 8% considered quitting
Ganapathy et al. (2015)	Stroke	Self-reported effect of caregiving	− 32% average work restriction
			− Age was significantly and negatively associated with overall work restriction
			− Number of children < 18 and lack of nursing home coverage for stroke survivor were significantly and positively associated with overall work restriction
Longacre, Valdmanis, Handorf, and Fang (2017)	General elderly	Self-reported effect of caregiving	− 52.4% of employed caregivers reported that caregiving interfered with their job
Longacre, Valdmanis, Handorf, and Fang (2017)	General elderly		− Those reporting that caregiving interfered with their job were more highly educated, less likely to be the care recipient’s spouse and more likely to be their child or son/daughter in-law, more likely to care for someone with more than three ADLs, and provided more hours of care relative to those that reported that caregiving did not interfere with their job
McKinlay, Crawford, and Tennstedt (1995)	Functionally-disabled elderly	Self-reported effect of caregiving	− 20.3% experienced negative impact on job structure over 7-year period
McKinlay, Crawford, and Tennstedt (1995)	Functionally-disabled elderly		− Significant predictors of impact on job structure: in-home care hours, linkage care hours, married female as caregiver, age of caregiver, formal service hours
Scharlach, Sobel, and Roberts (1991)	General elderly	Self-reported effect of caregiving	− Work interference associated with the following caregiver factors: self-reported strain, likelihood of nursing home placement, likelihood of job turnover, social support, and job flexibility
Scharlach, Sobel, and Roberts (1991)	General elderly		− Work interference associated with the following care-recipient factors: self-care ability, cognitive impairment, and behavioral disturbances.
Stone and Short (1990)	General elderly	Self-reported effect of caregiving	− For every hour the care recipient can be left alone, the caregiver is 0.67% less likely to need work accommodations
			− Caregivers who care for elders with behavior problems are 17.94% more likely to need work accommodations
			− Primary caregivers are 19.40% more likely to need work accommodations than secondary caregivers
			− Female caregivers are 11.78% more likely to need work accommodations than male caregivers
			− White caregivers are 15.06% more likely to need work accommodations than non-White caregivers
			− Caregivers in fair or poor health are 14.96% more likely to need work accommodations than healthier caregivers
Wolff, Spillman, Freedman, and Kasper (2016)	General elderly	Cross-sectional comparison to a comparison group	− Caregivers who provided substantial help with care were over three times as likely to experience productivity loss (accounting for absenteeism and presenteeism) than caregivers who provided no help
Wolff, Spillman, Freedman, and Kasper (2016)	General elderly		− College or higher level of education and self-reported good health (relative to excellent health) were significantly associated with productivity loss

ADL: Activities of daily living.

Anastas and colleagues (1990) created a “conflict score” based on whether caregiving responsibilities conflicted with job demands or whether a caregiver had ever considered quitting a job because of caregiving responsibilities. They found that 53% of caregivers reported no conflict, 39% reported a conflict, and 8% had considered quitting due to caregiving responsibilities.

Ganapathy and colleagues (2015) found that caregivers of stroke survivors reported 32% average “work restrictions” due to caregiving, a measure that combines absenteeism and presenteeism. The authors also found that age was negatively associated with overall work restrictions, while the number of children under 18 and the lack of nursing home coverage for stroke survivors were positively associated with work restrictions. A national survey of 948 employed caregivers of general elderly patients found that 52.4% of employed caregivers reported that caregiving interfered with their job. These caregivers tended to be more highly educated, were less likely to be the care recipient’s spouse (and more likely to be their child or son/daughter in-law), more likely to care for someone requiring help with more than three activities of daily living, and provided more hours of care relative to those not reporting any job interference (Longacre, Valdmanis, Handorf, & Fang, 2017).

A survey of caregivers of functionally-disabled elderly patients in Massachusetts used a composite measure to rate the negative impact of caregiving on “job structure,” any job changes, number of hours worked, and/or work shift (McKinlay, Crawford, & Tennstedt, 1995). Over a 7-year study period, the authors found that 20.3% of all employed caregivers experienced a negative impact on their job structure due to caregiving. They also identified the following predictors of negative impact on job structure: a high number of in-home care hours, significant time spent arranging formal services for care recipient, a married female as caregiver, higher age of caregiver, and greater number of hours of formal care for care recipient.

Scharlach et al. created several structural equation models to examine the association between various factors and work interference due to caregiving (Scharlach, Sobel, & Roberts, 1991). They calculated work interference as a composite measure of survey responses related to change in work routine, foregone work opportunities, number of hours missed, and how much caregiving conflicted with a caregiver’s job. They found that work interference was associated with the following caregiver factors: self-reported strain, perceived likelihood of care recipient requiring nursing home placement, likelihood of job turnover, social support, and job flexibility. They also found that work interference was associated with the following care-recipient factors: self-care ability, cognitive impairment, and behavioral disturbances.

A nationally representative survey of 491 employed, nonspousal caregivers regressed caregiver and care recipient factors on work “accommodations” measured as caregivers reporting one or more of the following adjustments due to caregiving: rearranging schedules, reducing work hours, or taking time off without pay (Stone & Short, 1990). The authors found that the following caregiver characteristics were associated with an increased likelihood of needing work accommodations: being the primary caregiver, female, White, and in fair or poor health. They also found that for every hour a care recipient can be left alone, a caregiver has a smaller likelihood of needing work accommodations, and that caregivers who care for elders with behavioral problems are most likely to need work accommodations.

Finally, Wolff and colleagues (2016) studied caregiving-related work productivity loss among 656 employed caregivers from the National Study of Caregiving, a composite measure that accounts for absenteeism and presenteeism. Caregivers who provided substantial help with care experienced more productivity loss (9.6%) than caregivers who provided some help (3.3%) or caregivers who gave no help (2.9%). In multivariable models controlling for caregiver characteristics, it was found that caregivers providing substantial help were over three times more likely to experience productivity loss than caregivers who provided no help. Other characteristics significantly associated with productivity loss for caregivers included college or higher level of education and self-reported good health (compared to excellent health).

Conclusion

Previous literature reviews have found that caregiving has a relatively small impact on workforce participation, both in terms of decisions to enter or exit the workforce and the number of hours worked (Bauer & Sousa-Poza, 2015; Lilly et al., 2007). While these findings are important, they only reflect limited components of the work experiences of caregivers. Even if caregivers remain in the workforce, their daily employment experiences can still be significantly affected. Our review investigates the relationship between caregiving and work performance among caregivers who have decided to remain in the workforce while providing care. We found that caregivers experience substantial work disruptions and negative work performance outcomes, and these findings were consistent across a variety of outcomes. Taken together, the studies we reviewed suggest that caregivers miss a significant amount of work and have reductions in productivity due to their caregiving responsibilities.

Despite the apparent effects of caregiving on work performance outcomes, we found that these outcomes are sometimes hard to measure. From study to study, there was little consistency across the measures used to estimate work outcomes. For example, within the general measures of missed work, there were two specific categories: measures of “missed work” and “absenteeism.” These two measures were assessed over different periods of time and for different patient populations, making it difficult to create a succinct summary across the studies. Similar challenges were present for each category of work performance outcome.

The studies in our review are generally cross-sectional and rely on caregivers’ self-assessment of the impact of caregiving, making causal inference challenging. Randomized controlled trials are considered to be the gold standard for causal inference studies, but researchers cannot randomly assign caregiver status to an individual. Therefore, researchers are left with observational or quasiexperimental designs to better understand the impact of caregiving on work outcomes. Of the studies we reviewed, approximately three quarters used a cross-sectional design with no comparison group; 7% compared caregivers to noncaregivers using cross-sectional databases; and 14% compared longitudinal pre-post within subject comparisons. No studies compared changes in caregivers’ work outcomes from before until after they became caregivers to those of noncaregivers over time the same time period. This kind of “difference-in-difference” design is a much stronger design and more closely approximates causality. Given the limitations to the designs of existing studies included in this review, it is difficult to assess the extent to which employment outcomes are associated with caregiving as opposed to some other factor correlated with caregiving. The cross-sectional studies often attempted to get closer to causal inference by asking patients to report the extent to which negative work outcomes were “due to caregiving,” but these questions are still prone to recall bias and caregivers overestimating the true impact of caregiving.

Despite these methodological challenges, our findings suggest that caregiving has a negative impact on work performance. These findings have important implications for caregivers. Caregivers are already at significantly increased risk of financial instability due to money spent out of pocket on the recipient’s care (Rainville, Skufca, & Mehegan, 2016). As their job performance suffers, these caregivers might also be at increased risk of losing their jobs or receiving lower pay due to poor performance. As noted in the introduction, working caregivers could experience escalated levels of stress, with implications for their own physical and mental health. Poor work performance and its implications for salary and promotion may also affect a caregiver’s ability to retire when desired, which is significant as over 50% of caregivers of the elderly are over 55 years old (National Academies of Sciences, Engineering, & Medicine, Health and Medicine Division, Board on Health Care Services, Committee on Family Caregiving for Older Adults, 2016). Policy-related supports could help caregivers meet the demands of their jobs and reduce the likelihood of serious negative work-related outcomes. These may be varied and could include providing increased caregiver financial support, family leave, access to respite care and telecommuting options. The federal Lifespan Respite Care Program (LRCP) provides grants to states to support respite care (Administration for Community Living, n.d.). The LRCP is currently funded at approximately US$2.5 million annually, a significantly lower amount than the US$30 million to US$95 million authorized by the original legislation. Also, increased funding for the National Family Caregiver Support Program (NFCSP) would allow states to provide counseling, training, and additional supplemental services including home modifications, transportation and assistive technology. Furthermore, some caregivers may want to take time off from work by using extended family medical leave. The Family and Medical Leave Act (FMLA) allows employees of qualified employers to take up to 12 weeks of unpaid leave to care for a sick spouse, child, or parent. FMLA provides a federal minimum standard for employee medical leave, but some states have expanded family medical leave to include paid leave and additional categories of employers (Department of Labor, n.d.). Recently, private employers such as Deloitte LLP have expanded family leave benefits, allowing employees to take up to 16 fully paid weeks off to care for a family member. Many employers are also expanding technology platforms and increasing telecommuting options for employees. All of these public and private policies could lessen negative work-related outcomes for caregivers (Klerman, Daley, & Pozniak, 2012).

While many key caregiving responsibilities—coordinating care, making treatment decisions, overseeing the use of medical equipment, and helping with daily tasks such as eating and bathing—put caregivers into regular contact with physicians, nurses, pharmacists, and other providers, caregivers themselves often do not enter into effective partnerships with health care providers because of time, reimbursement, and information limitations. These limitations often make caregiving much more difficult and likely increase the burden on caregivers’ employment.

The National Academies of Sciences, Engineering, & Medicine et al. (2016) recently convened an expert panel aimed at addressing the barriers to effective caregiving. The panel concluded that health care providers could improve their ability to identify and assess the competency of caregivers. The panel suggests identifying primary caregiving within a patient’s medical record and then having providers use validated tools for assessing caregiver skills, needs, and risk to their health, employment, and overall well-being as a starting point. Then, interventions could be triggered based on caregivers’ needs. However, no financial incentives exist for providers to more systematically identify and assess caregivers at risk. One solution would be to provide a change of payment policies that would create incentive to include caregivers (National Academies of Sciences, Engineering, & Medicine et al., 2016). Once caregivers are identified and assessed, supports could be identified to help caregivers to provide care and also to better meet their employment responsibilities. This may include the development programs to help caregivers more efficiently participate in coordination of the care for their patients.

This study has limitations. The final review ended in November 2015, which means newer studies may have not been identified. However, we did use various methods to identify studies from November 2015 to the end of 2017, described in the methods section. Although we used methods consistent with systematic reviews, we only searched one data source. However, the referencing mining approach reduced the probability of missing key studies.

A large body of research investigates how caregiving influences health outcomes. Little research has examined the influence of caregiving on the employment of the caregiver. This is critical with the expected increase in the number of older adults needing care in the future as the current population ages. This comprehensive review suggests that caregiving has a significant negative impact on work performance, although future work is needed to address methodological challenges in this area of science.

Supplemental Material

Appendix_A_9-26-2018 – Supplemental Material for Work Performance Among Informal Caregivers: A Review of the Literature

Supplemental Material, Appendix_A_9-26-2018 for Work Performance Among Informal Caregivers: A Review of the Literature by Grant R. Martsolf, Ryan Kandrack, Juleen Rodakowski, Esther M. Friedman, Scott Beach, Barbara Folb and A. Everette James in Journal of Aging and Health

Supplemental Material

Appendix_B_Search_terms – Supplemental Material for Work Performance Among Informal Caregivers: A Review of the Literature

Supplemental Material, Appendix_B_Search_terms for Work Performance Among Informal Caregivers: A Review of the Literature by Grant R. Martsolf, Ryan Kandrack, Juleen Rodakowski, Esther M. Friedman, Scott Beach, Barbara Folb and A. Everette James in Journal of Aging and Health

Supplemental Material

Appendix_C – Supplemental Material for Work Performance Among Informal Caregivers: A Review of the Literature

Supplemental Material, Appendix_C for Work Performance Among Informal Caregivers: A Review of the Literature by Grant R. Martsolf, Ryan Kandrack, Juleen Rodakowski, Esther M. Friedman, Scott Beach, Barbara Folb and A. Everette James in Journal of Aging and Health

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Stern Family Foundation and the Emily Kelly Roseburgh Memorial Fund of The Pittsburgh Foundation.

Supplemental Material

Supplemental material for this article is available online.

ORCID iDs

Grant R. Martsolf

Barbara Folb

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