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. Author manuscript; available in PMC: 2025 May 1.
Published in final edited form as: Clin Gerontol. 2020 Jun 28;47(3):484–493. doi: 10.1080/07317115.2020.1783042

Sleep Disturbance, Mental Health Symptoms, and Quality of Life: A Structural Equation Model Assessing Aspects of Caregiver Burden

Scott G Ravyts 1, Joseph M Dzierzewski 1
PMCID: PMC7767889  NIHMSID: NIHMS1646024  PMID: 32597344

Abstract

Objectives:

The present study sought to examine the association between sleep disturbance, mental health symptoms, and quality of life among informal caregivers. The study also aimed to assess whether greater caregiver demands (i.e., hours spent providing care per week) altered the associations between these physical and mental health outcomes.

Methods:

530 informal caregivers participated in an online study of sleep and health across the lifespan. Sleep disturbance was assessed via the Insomnia Severity Index and RU-SATED. Mental health was measured using the PHQ-2, GAD-2, and the PANAS. Quality of life was assessed via the Satisfaction with Life Scale.

Results:

Results revealed an indirect association between sleep disturbance and quality of life via increased mental health symptoms (β = −.21, p =.001). This indirect association was moderated by caregiver demands (β =.33, p =.002), with higher caregiving demands increasing the association between sleep disturbance and quality of life.

Conclusions:

Findings highlight the adverse outcomes associated with sleep disturbance among caregivers and suggest that higher caregiving demands increases the effect of sleep disturbance on quality of life.

Clinical Implications:

Increased caregiving is associated with adverse physical and mental health consequences. Assessing and treating sleep disturbance among caregivers is needed and may lead to improvements in mental health and quality of life.

Keywords: Caregiving, sleep, insomnia, depression, anxiety, quality of life

Introduction

An estimated 43.5 million people in United States provide informal care to a relative, which has been defined as ongoing, unpaid care to assist with activities of daily living or instrumental activities of daily living (National Alliance for Caregiving [NAC] & American Association of Retired People [AARP], 2015). On average, caregivers spend 24.4 hours per week providing care, with 23% of individuals providing over 40 hours per week of care (NAC & AARP, 2015). Caregivers are an invaluable source of support for care recipients and serve as an integral component of the health care system in the United States. However, caregiving is associated with a range of adverse physical, social, and emotional consequences leading to caregiver burden and lower quality of life (Adelman, Tmanova, Delgado, Dion, & Lachs, 2014).

Sleep among caregivers

Poor sleep is one common aspect of caregiver burden. A recent critical review of 22 empirical studies found that up to 76% of caregivers report poor sleep quality, with their sleep characterized by short sleep duration and frequent nighttime awakenings (Byun, Lerdal, Gay, & Lee, 2016). Compared to non-caregivers, caregivers’ sleep appears to be both objectively and subjectively worse (Rowe, McCrae, Campbell, Benito, & Cheng, 2008; Sakurai, Onishi, & Hirai, 2015). While most research has been predominately focused on caregivers tending to individuals with either dementia or cancer, poor sleep has been reported among individuals providing care for a range of chronic illnesses (Byun et al., 2016). Yet, despite knowledge regarding the prevalence of poor sleep among caregivers, less is known about how sleep in this population is associated with other aspects of caregiver burden. That is, while both mental health and quality of life are known to be negatively affected by caregiving, research regarding the influence of poor sleep on these factors remains limited.

The dysregulation model of sleep posits that sleep disturbance exacerbates mental health symptoms by impairing emotional regulation and altering the body’s circadian rhythms (Palagini, Bastien, Marazziti, Ellis, & Riemann, 2019). This model is supported empirically by longitudinal studies which found that sleep problems predict future mental health dysfunction (Alvaro, Roberts, & Harris, 2013). The chronic adverse effect of sleep disturbance on mental health may also lead to decreased quality of life. That is, mental health symptoms may act as a mechanism through which poor sleep decreases the quality of life. While this mediating effect has previously been demonstrated in other samples (Yuan et al., 2020; Zhi et al., 2016), it remains untested among caregivers. This gap in the literature is notable given that caregiving responsibilities are known to adversely impact sleep, mental health, and quality of life (Adelman et al., 2014). These effects may be particularly pronounced among caregivers who spend a greater number of hours per day providing care (Chang, Chiou, & Chen, 2010). Taken together, these findings suggest that an association between sleep disturbance and quality of life via increased mental health symptoms, if present, may be more pronounced among individuals with greater caregiver demands.

Sleep and mental health symptoms among caregivers

Mental health symptoms are another common aspect of caregiver burden and are often comorbid with sleep disturbance (Liu et al., 2017). Consistent with the general population, evidence suggests that caregivers experiencing sub-optimal sleep are more likely to experience more mental health symptoms. For example, female veterans with self-identified sleep problems due to caregiving for an adult report significantly more symptoms of depression and anxiety than individuals with sleep problems due to caring for an infant or child or to all other respondents (Song et al., 2018). Sleep disturbance is believed to be a strong and reliable predictor of mental health symptoms with one study finding that caregiver sleep problems, comprised of sleep quality, sleep efficiency, and daytime dysfunction accounted for over 60% of the variance in caregiver depression (Carter & Chang, 2000).

Mental health and quality of life among caregivers

Caregivers with poorer mental health are more likely to report having a lower quality of life, defined as the degree to which a person derives satisfaction from life. For example, one study examining caregivers of women with cancer found that depressive symptoms were negatively correlated with quality of life and that individuals with depression were more likely to have a lower quality of life (Heidari Gorji et al., 2012). Similarly, among caregivers of individuals with mental illness, having more anxiety or depressive symptoms was associated with lower quality of life across several different domains (Jeyagurunathan et al., 2017). Changes in the quality and pattern of caregivers’ sleep may lead to detrimental mental health effects and subsequent declines in quality of life.

Sleep disturbance, mental health, and quality of life

While the bivariate associations between sleep disturbance, mental health, and quality of life among caregivers have been examined, research examining the associations among all three factors together remains limited. However, preliminary evidence suggests that these factors are interconnected. For example, a study examining caregivers of individuals with Alzheimer’s and Parkinson’s disease found that poor sleep quality was associated with depressive symptoms and correlated with quality of life (Cupidi et al., 2012). Similarly, among caregivers of cancer patients, sleep, depression, and anxiety were all associated with quality of life (Cuthbert, King-Shier, Ruether, Tapp, & Culos-Reed, 2016). Further research is needed to examine whether mental health acts as a mechanism through which sleep influences the quality of life in caregivers. Additionally, the influence of caregiver demands (i.e., hours of care provided) on all three of these factors has been overlooked. As a result, it is unknown whether the association between sleep, mental health, and quality of life generalizes to all caregivers or if it is only pronounced among individuals with high caregiver demands.

Present study

A better understanding of the adverse physical and psychological consequences associated with caregiving, and the associations between these outcomes, is needed to inform future interventions. Knowledge regarding these symptoms may not only be critical in reducing caregiver burden and improving caregiver health but may also lead to better care for care recipients. The purpose of the present study is to examine the association between sleep disturbance, mental health, and quality of life among a diverse sample of informal caregivers. Building on the existing literature (Yuan et al., 2020; Zhi et al., 2016), greater sleep disturbance was hypothesized to be associated with lower quality of life both directly and via increased mental health symptoms. In addition, the aforementioned direct and indirect relationships between sleep disturbance, mental health symptoms, and quality of life were hypothesized to be stronger among caregivers who provide more hours of informal care per week. Knowledge gained from the present study could highlight sleep as an important, but overlooked, factor as it relates to well-being among caregivers. Additionally, the present study contributes to the growing literature examining how greater caregiving demands are associated with different facets of caregiver burden.

Methods

Data included in the present study came from a larger, IRB approved online study examining sleep and health across the lifespan. Data collection was completed via Amazon’s Mechanical Turk (MTurk), a crowdsourcing online platform where individuals are compensated for the completion of a variety of tasks and services. Individuals self-selected to participate in the study. All participants were required to provide informed consent prior to completing the questionnaire. Data collected via MTurk has significantly increased in recent years and been found to be as reliable as those acquired via traditional methods, with several studies supporting a correspondence between the behavior of MTurk participants and behavior offline (Buhrmester, Kwang, & Gosling, 2011; Mason & Suri, 2012).

Aside from residing within the United States, inclusion criteria for the parent study were minimal and were based solely on recruiting an equal number of men and women across the lifespan. Participants could only complete the study one time. In order to be included in the present study, participants had to self-identify being as an informal caregiver providing care to an individual due to a physical, psychological, cognitive, developmental, or age-related impairments. Participants who only reported providing care in the context of child rearing were not included due to evidence suggesting that this type of caregiving differs from that of providing care to an individual with impairments (e.g., Song et al., 2018). No age restriction was placed for inclusion in the present analyses.

Two safeguards were implemented to minimize potential threats to validity sometimes associated with online data collection. First, an instructional manipulation check asked participants to respond to an item by selecting a specific response. Secondly, to ensure consistency in participants’ responses, a question inquiring about participants’ age at the beginning of the survey was cross-validated with a question about their birthdate at the end of the survey. Only participants who passed both the instructional validity check and the consistency check were included in the present study. Consistent with prior MTurk research (e.g., Buhrmester et al., 2011), participants were compensated 0.50 USD for being in the study. Compensation amounts have not been shown to affect the quality of data collected via this platform (Buhrmester et al., 2011).

Of the 4298 participants included in the parent study, 15.26% (N = 656) reported being a caregiver. Of those who identified as caregivers, 82.31% (N = 540) passed the consistency validation check and an additional 98.70% (N = 533) of those passed the instructional validation check.

Measures

Sleep disturbance

Sleep was assessed using two scales, a recently developed sleep health scale (RU SATED; Buysse, 2014) and the Insomnia Severity Index (ISI; Bastien, Vallières, & Morin, 2001). These scales were chosen in an attempt to capture how sleep may be influenced by caregiving. RU SATED contains six items, with each item measuring one aspect of sleep heath: sleep regularity, satisfaction, timing, duration, efficiency, and alertness during the day. Items are each rated on 3-point Likert scale from 0 (rarely/never) to 2 (usually/always), with higher scores indicating better sleep health. Preliminary psychometric evaluations suggest that the scale is an empirically reliable measure of sleep health (Ravyts, Dzierzewski, Perez, Donovan, & Dautovich, 2019). Cronbach’s alpha for RU SATED in the current sample was.57.

The ISI is a 7-item measure which assesses the nature, severity, and impact of insomnia. Scores on the ISI range from 0 to 28 with higher scores representing greater insomnia severity. The ISI is a widely used measure which has shown to be psychometrically sound and reliable among both clinical and non-clinical sleep populations (Bastien et al., 2001; Morin, Belleville, Bélanger, & Ivers, 2011). Cronbach’s alpha for ISI in this study was.86.

Mental health symptoms

Mental health symptoms were assessed using the GAD-2, PHQ-2, and negative affect items from the Positive and Negative Affect Schedule (PANAS). The PHQ-2 is a 2-item measure of depressive symptoms over the last 2 weeks measured on a 4-point Likert scale from 0 (not at all) to 3 (nearly every day) with higher scores indicating more depressive symptoms (Kroenke, Spitzer, & Williams, 2003). Similarly, the GAD-2 is a 2-item measure of anxiety symptoms over the past 2 weeks rated on a 4-point Likert scale from 0 (not at all) to 3 (nearly every day) with higher scores indicating more anxiety symptoms (Kroenke, Spitzer, Williams, Monahan, & Löwe, 2007). Finally, affect was measured using the negative affect subscale of the PANAS (Watson, Clark, & Tellegen, 1988). Items are rated on a 5-point Likert scale from 1 (very slightly or not at all) to 5 (extremely) with higher scores indicating more negative affect over the past week. Cronbach’s alpha for the PHQ-2, GAD-2, and the negative affect subscale of the PANAS in the current sample were.85,.86, and.91, respectively.

Quality of life

Quality of life was assessed via the Satisfaction with Life Scale (SWLS; Diener, Emmons, Larsen, & Griffin, 1985). The SWLS is a valid and psychometrically sound measure that has been widely used among health-related quality of life research (Pavot & Diener, 2008). Statements on this 5-item measure are rated on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree) with higher scores indicating greater life satisfaction. Cronbach’s alpha for the SWLS in the current sample was.89.

Caregiver demands.

Caregiving demands were assessed via the self-reported average number of hours of care provided per week. Low caregiver demand was operationalized as less than 20 hours of care per week, while high caregiver demand was operationalized as 20 or more hours of care provided per week. This cutoff was chosen in order to approximate the average number of hours reported by caregivers in the United States (NAC & AARP, 2015).

Data analysis

Analyses were conducted using SPSS v.26 and AMOS v.23 (Arbuckle, 2014). A structural equation model (SEM) was used to evaluate the direct and indirect relationships among sleep disturbance, mental health symptoms, and quality of life among caregivers. Specifically, sleep disturbance was conceptualized as a latent variable represented by the ISI and RU SATED. Mental health was conceptualized as a latent variable comprised of the PHQ-2, GAD-2, and the negative affect subscale from the PANAS. Finally, quality of life was assessed as a manifest variable using the SWLS. The indirect effect of sleep disturbance on quality of life was assessed using 2,000 bootstrapped samples and a 95% bias-corrected confidence interval.

In order to determine whether the SEM differed for participants who provided more hours of caregiving, an invariance test was run as a function of the number of weekly hours of care provided. This invariance analysis examined the overall model fit between individuals with high and low caregiver demands, as well as the direct associations among the latent variables for these two groups. Finally, a multi-group moderated mediation analysis using an estimand in AMOS was used to specifically examine whether the indirect effect of sleep disturbance on quality of life was moderated by the number of hours provided (Gaskin, 2016). For both of these analyses, caregivers were dichotomized as either having a low caregiving demand (<20 hours per week) or high caregiving demand (≥20 hours per week).

Prior to running the SEM, data was assessed for the presence of multivariate outliers via the square distance of Malahanobis (D2). Normality was assessed via univariate and multivariate coefficients of skewness and kurtosis. Missing data was minimal (N = 3) but included participants without any data pertaining to sleep and thus was deleted list-wise.

Goodness of fit for the SEM was established using previously recommended guidelines including: a non-significant chi-square test, a root mean squared error of approximation (RMSEA) of.08 or less (Tabachnick & Fidell, 2001), and a comparative fit index (CFI), goodness of fit index (GFI), adjusted goodness of fit index (AGFI), normed fit index (NFI), incremental fit index (IFI), and Tucker–Lewis index (TLI) of.90 or greater indicating adequate model fit and.95 or greater indicating good fit (Bentler, 1990; Byrne, 1994).

Results

Descriptive statistics

The final analytical sample included 530 informal caregivers. Participants were predominately middle-aged (M = 46.11, SD = 16.36) and White (78.11%). On average, participants reported providing 17.62 hours a care per week (SD = 12.89), and being an informal caregiver for 6.85 years (SD = 5.69). Nearly two thirds of the sample reported providing care for an age-related condition, with top reasons for care including age-related declines in health (42.45%), physical illness (36.03%), memory/cognitive disorder (24.15%), psychological disorder (16.79%), or a developmental disorder (15.66%). A subset of participants reported providing care for more than one reason with 18.68% of the sample endorsing two reasons for providing care and 6.7% of the sample endorsing three or more reasons. Participants were the most likely to report providing care for a parent (38.11%), child (31.32%), or spouse (21.13%).

Insomnia symptoms fell within the subthreshold range on average, with 29.40% of participants’ scores on the ISI falling within the clinical range. A significant number of participants scored above the recommended clinical cutoff on either the PHQ-2 (35.47%) or the GAD-2 (39.81%), suggesting the presence of potentially clinically relevant mental health symptoms. Participants’ quality of life fell within the average range (M = 19.83, SD = 7.96), with 14.34% and 12.64% of participants with scores falling within the dissatisfied and extremely dissatisfied range, respectively. Complete demographic and clinical characteristics are presented in Table 1.

Table 1.

Participant demographic and clinical characteristics.

Mean (Std. Deviation)
Demographic Characteristics
Age 46.11 (16.36)
Sex (%)
 Male 41.70%
 Female 51.10%
 Non-Binary 7.20%
Racea (%)
 White 78.11%
 Black 11.13%
 Asian-American 7.17%
 Latino/Hispanic 4.90%
 Native American 4.30%
 Pacific Islander 0.75%
 Other Race 1.32%
Sleep Characteristics
 ISI 10.71 (6.60)
 RU SATED 6.92 (2.55)
Mental Health Characteristics
 PHQ-2 2.04 (1.95)
 GAD-2 2.23 (1.99)
 PANAS-NA 11.41 (5.37)
Quality of Life
 SWLS 19.84 (7.96)
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a

Participants were allowed to identify more than one race. ISI = Insomnia Severity Index, PHQ-2 = Patient Health Questionnaire-2, GAD-2 = Generalized Anxiety Disorder-2 scale, PANAS-NA = Positive and Negative Affective Schedule – Negative Affect Subscale, SWLS = Satisfaction with Life Scale.

Nearly a third of the sample (N = 200) reported providing 20 or more hours of care per week on average. Differences based on the average number of hours of care provided per week were present for quality of life, t(528) = 3.25, p = .001. Specifically, participants providing 20 or more hours of care reported lower quality of life (M = 18.40 SD = 8.21) compared to those providing less care (M = 20.671, SD = 7.68). Difference in the two groups was also noted regarding insomnia symptoms, t(528) = − 2.57, p = .01, and sleep health, t (528) = 2.11, p = .03, with participants providing more care reporting more insomnia symptoms (M = 11.65, SD = 6.30) and poorer sleep health (M = 6.62, SD = 2.61) compared to participants providing less care (M = 10.14, SD = 6.99; M = 7.11, SD = 2.49). In contrast, no differences in the mental health symptoms of these two groups were present (ps >.05).

Measurement model

Regarding fit for the measurement model, the chi-squared test was statistically significant, χ2(14, N = 530) = 29.11, p = .01, potentially suggestive of poor model fit. However, the statistical significance of chi-squared tests is known to be sensitive to large sample sizes (Tabachnick & Fidell, 2001). In contrast, the GFI (.982), AGFI (.945), NFI (.982), RFI (.961), IFI (.990), TLI (.979), and RMSEA (.045) all fell within the adequate to good range. Taken together, these indices suggest that the measurement model fit the data adequately, and thus no modifications were conducted to improve the model. All manifest variables loaded highly (all beta-weights >.64 and all p-values <.001) onto their latent constructs.

Structural model

The structural model revealed that sleep disturbance did not have a direct effect on the quality of life (β = − .08, p = .11). However, sleep disturbance did have a significant indirect effect on the quality of life via mental health symptoms (β = − .21, p = .001). That is, sleep disturbance was positively associated with mental health symptoms (β = .59, p = .001) and mental health symptoms were, in turn, negatively associated with quality of life (β = − .36, p = .001). As a whole, the model accounted for 35.1% of the variance in mental health symptoms and 17.00% of the variance in quality of life. The complete SEM is presented in Figure 1.

Figure 1.

Figure 1.

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Structural equation model. Latent variables are represented by circles and manifest variables are presented by rectangles; values next to each arrow represents the value of the standardized regression weights; *** p<.001

Invariance test

The invariance analyses evaluated the difference between an unconstrained model, which assumes that the groups are yielding different values of the parameters when the model is applied to the data, and a set of constrained models, which assume that the groups are yielding equivalent values of given sets of parameters when the model is applied to the data. When contrasted to the unconstrained model, the chi-square difference test for the measurement weights model yielded a statistically significant value, χ2 (5, N = 530) = 17.42, p = .004. This finding indicates the presence of non-invariance across the two groups with respect to the pattern coefficients associating the indicator variables to their factors. Post-hoc comparisons revealed that only the path between mental health symptoms and quality of life was non-invariant across the two groups (z = − 3.70, p < .01), with the association being significantly stronger among the high caregiver demand group (β = − 1.14) than the low caregiver group (β = − .43).

Finally, the test of moderated mediation indicated that the indirect effect of sleep disturbance on quality of life was moderated by the number of hours of care provided (β = .33 p = .002). Specifically, the indirect effect of sleep disturbance on quality of life was stronger among participants who provided twenty or more hours of care than individuals who provided less than 20 hours of care.

Discussion

The purpose of the present study was to examine the association between sleep disturbance, mental health symptoms, and quality of life among a sample of informal caregivers. Contrary to our hypothesis, we found no evidence for a direct effect of sleep disturbance on quality of life. However, support for a negative indirect effect of sleep disturbance on quality of life via increased mental health symptoms was found. Findings from the present study also indicated that this indirect effect is stronger among caregivers who provide more weekly hours of care. Finally, results demonstrated that the negative association between mental health symptoms and quality of life is significantly stronger among caregivers who provide more hours of care.

The lack of an association between sleep disturbance and quality of life in the present study is inconsistent with prior studies which found robust associations found between sleep and quality of life among non-clinical samples (Baldwin et al., 2010; Marques, Meia-Via, da Silva, & Gomes, 2017). One possible explanation for these discrepant findings may be the fact that prior work has generally focused on one or more facets of quality of life (e.g., physical, psychological, or social quality of life). Thus, the direct effect of sleep may not be captured by a more general assessment of quality of life. Another possibility is that the association between sleep disturbance and quality of life found in previous research was driven by increased mental health symptoms which were not controlled for. Finally, the association between sleep disturbance and quality of life may be more pronounced among certain caregiving populations (e.g., dementia, cancer).

Several factors may explain how sleep disturbance is linked to lower quality of life via adverse mental health symptoms. Caregivers living with their care recipient report spending time attending to their loved one’s needs at night, anticipating possible needs, or having their sleep interrupted by the care recipients’ nighttime behavior (Arber & Venn, 2011). Even caregivers who do not live in the same household as their care recipient report similar levels of sleep disturbance (Simpson & Carter, 2015). Over time, sleep disturbance may lead to changes in sleep regularity or in the development of compensatory factors (e.g., increased caffeine use, daytime napping), which may maintain future sleep disturbance and promote poorer mental health (McCurry, Song, & Martin, 2015). Inconsistency in the quality and duration of sleep from day-to-day has been shown to be associated with increased mental health symptoms, with nights characterized by poorer sleep predicting negative affect among caregivers the next day (McCrae et al., 2016). Given the average number of years spent providing care, disrupted sleep and its adverse effect on mental health may be associated with decreased quality of life.

The moderating effect of caregiving demands on the association between sleep disturbance and quality of life contributes to the growing literature suggesting that increased caregiving demands are linked with pertinent adverse consequences. For example, a recent longitudinal study found a dose–response relationship between caregiving and sleep disturbance (Sacco, Leineweber, & Platts, 2018). Similarly, providing over 20 hours of care is associated with increased depression and psychological distress (Burton, Zdaniuk, Schulz, Jackson, & Hirsch, 2003; Hirst, 2005). Results from the present study suggest that while individuals with higher caregiving demands might not differ in terms of mental health symptoms, their sleep and quality of life are lower than their peers which may be partly attributed to stronger relationships among symptoms of caregiver burden.

Implications

The present findings reiterate the adverse consequences of poor sleep among caregivers and highlight the potential benefit of interventions which seek to improve caregivers’ sleep. Interventions targeting caregivers’ sleep have shown some preliminary success. For example, one study which implemented a brief behavioral sleep intervention among caregivers of individuals with cancer found that participants in the treatment condition displayed improved sleep quality and decreased depressive symptoms compared to participants in a control group (Carter, 2006). Despite evidence suggesting that sleep among caregivers is modifiable and may be associated with positive mental health consequences, most existing interventions for caregiver burden do not explicitly target sleep (Adelman et al., 2014).

Our finding that increased caregiving demands is associated with poorer sleep and decreased quality of life suggests that respite care maybe another useful intervention. Caregivers who use respite care, such as adult day services, have been shown to report lower levels of caregiver burden and stress (Fields, Anderson, & Dabelko-Schoeny, 2014). Such services may also help to address care recipient sleep which may translate to sleep improvements among caregivers (Martin et al., 2017).

Limitations and future directions

The present study is not without limitations. First, the cross-sectional design of the present study precluded the examination of temporal associations between sleep disturbance, mental health symptoms, and quality of life. Furthermore, while the SEM provides initial support for the indirect effect of sleep disturbance on quality of life, alternative associations may also exist. Secondly, the assessment of the quality of life was limited to a single measure focusing on the overall quality of life. Future studies would benefit from examining the influence of caregivers’ sleep and mental health on multiple facets of quality of life (e.g., physical health, psychological, social). The relatively low internal consistency of RU SATED in the present sample is also noteworthy. Though a strength of the study was the ability to examine a heterogeneous sample of caregivers, the associations between sleep disturbance, mental health symptoms, and quality of life may vary for specific caregiving populations. Moreover, given that the current sample was predominately non-Hispanic White, the current findings may not generalize to more racially diverse caregiver samples. Finally, additional research should continue to explore other factors which may better account for caregivers’ quality of life.

Conclusions

Collectively, the present study provides initial evidence for an indirect effect of sleep disturbance on quality of life via increased mental health symptoms. Our findings also suggest that this effect becomes exacerbated among caregivers who provide more hours of care. Taken together, these findings suggest that interventions which seek to improve caregivers’ sleep may be beneficial and warrant further examination.

Clinical implications.

  • Sleep disturbance among informal caregivers is common and associated with adverse consequences suggesting that interventions targeting sleep disturbance in caregivers are warranted.

  • Patients with greater caregiving demands would benefit from increased screening for concerns related to sleep and mental health.

Acknowledgments

Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Number K23AG049955 (PI: Dzierzewski).

Funding

This work was supported by the National Institute on Aging of the National Institutes of Health [K23AG049955].

Footnotes

Disclosure statement

The authors have no conflict of interests to disclose.

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