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. Author manuscript; available in PMC: 2021 Nov 14.
Published in final edited form as: Rehabil Psychol. 2020 May 14;65(4):432–442. doi: 10.1037/rep0000327

Do Emotional Distress and Functional Problems in Persons With Traumatic Brain Injury Contribute to Perceived Sleep-Related Impairment in Caregivers?

Anna L Kratz 1, Nicholas R Boileau 2, Angelle M Sander 3, Risa Nakase-Richardson 4, Robin A Hanks 5, Jill P Massengale 6, Jennifer A Miner 7, Noelle E Carlozzi 8
PMCID: PMC7665992  NIHMSID: NIHMS1638032  PMID: 32406737

Abstract

Objective:

The goal of this study was to examine the association between characteristics of persons with traumatic brain injury (PwTBI) and perceived sleep-related impairment of the caregivers.

Method:

Fifty-two dyads (n = 23 civilians, n = 29 service members/veterans [SMVs]) were enrolled. Caregivers completed the Patient-Reported Outcomes Measurement Information System Sleep-Related Impairment computer adaptive test, and PwTBI completed Quality of Life in Neurological Disorders measures of depression, anxiety, anger, cognitive functioning, and upper and lower extremity functioning. Hierarchical linear regression models, stratified by civilian/SMV group, were employed to assess prediction of caregiver-perceived sleep-related impairment from emotional distress of the PwTBI (anxiety, depressed mood, and anger) and perceived functional status of the PwTBI (cognitive, upper extremity, lower extremity functioning).

Results:

Compared with caregivers of civilians, caregivers of SMVs reported higher perceived sleep-related impairment. Regression results showed that characteristics of the PwTBI accounted for moderate amounts of variance in the sleep-related impairment of caregivers of both civilians and SMVs. Within-group analyses showed that the strongest predictor of sleep-related impairment of caregivers of civilians was self-reported cognitive function of the PwTBI (β = −0.82, p = .08); the strongest predictor of sleep-related impairment of caregivers of SMVs was self-reported anger of the PwTBI (β = 0.54, p = .07).

Conclusions:

In both caregivers of civilians and SMVs with TBI, characteristics of the PwTBI were related to perceived caregiver sleep-related impairment. These preliminary data can inform future research with larger samples that examine the impact of multiple characteristics of the caregiver and care recipient on caregiver sleep. Findings highlight the potential importance of considering the dynamics of the dyad in rehabilitation programming not only for the PwTBI but for caregivers as well.

Keywords: caregivers, traumatic brain injury, military, sleep

Introduction

Caregivers of individuals with moderate to severe traumatic brain injury (TBI) often undergo considerable physical and emotional stress (Brooks, Campsie, Symington, Beattie, & McKinlay, 1986; Brooks, Campsie, Symington, Beattie, & McKinlay, 1987; Gillen, Tennen, Affleck, & Steinpreis, 1998; Kreutzer, Gervasio, & Camplair, 1994b; Kreutzer et al., 2009; Livingston, Brooks, & Bond, 1985; Marsh, Kersel, Havill, & Sleigh, 2002; Ponsford & Schönberger, 2010; Winstanley, Simpson, Tate, & Myles, 2006). One notable area of concern reported by caregivers is sleep disturbance (Arango-Lasprilla et al., 2010; Carlozzi, Massengale, et al., 2018; Comerci et al., 2015; Jumisko, Lexell, & Söderberg, 2007; Marsh, Kersel, Havill, & Sleigh, 1998; Marsh et al., 2002). Sleep disturbance has been ranked as one of the most significant problems in caregivers of individuals with TBI, with an estimated occurrence in 50–60% of caregivers (Arango-Lasprilla et al., 2011; Carlozzi et al., 2016; Carlozzi et al., 2015; Knight, Devereux, & Godfrey, 1998; Marsh et al., 1998; Marsh et al., 2002; McPherson, Pentland, & McNaughton, 2000; Montgomery & Dennis, 2003; Morin, Culbert, & Schwartz, 1994; Saban et al., 2016). While there have been no recent investigations of the use of medication to facilitate sleep in caregivers of individuals with TBI, early studies found that many caregivers turned to medication to aid sleep (Kreutzer, Marwitz, & Kepler, 1992; Panting & Merry, 1972). Chronic sleep problems are associated with several negative health outcomes including increased risk for obesity, cardiovascular disease (including stroke), prolonged recovery times from illness, and worsening of mood disorders (Depner, Stothard, & Wright, 2014; Duss et al., 2018; Farrell & Richards, 2017; Hsu, Huang, Huang, Chiang, & Leu, 2012; Javaheri & Redline, 2017; Jun & Polotsky, 2009; Lévy, Bonsignore, & Eckel, 2009; Li et al., 2014; McCurry, Song, & Martin, 2015; Mullington, Haack, Toth, Serrador, & Meier-Ewert, 2009; Potter et al., 2016; Sofi et al., 2014; Van Cauter, Spiegel, Tasali, & Leproult, 2008; Wells, Dywan, & Dumas, 2005; Wickwire, Shaya, & Scharf, 2016).

Fortunately, sleep disturbances, such as poor sleep quality, and sleep disorders, such as obstructive sleep apnea and insomnia, are readily treatable (Morin et al., 1994), and treatments can result in significant downstream improvements in associated physical and mental health (Montgomery & Dennis, 2003; Morin et al., 1994). Because caregiver well-being is directly related to the well-being and successful rehabilitation of the person with TBI (PwTBI; Anderson et al., 2001; Holland & Schmidt, 2015; Kreutzer, Marwitz, Godwin, & Arango-Lasprilla, 2010; Ramkumar & Elliott, 2010; Sander et al., 2002; Sander, Maestas, Sherer, Malec, & Nakase-Richardson, 2012; Schönberger, Ponsford, Olver, & Ponsford, 2010; Smith & Schwirian, 1998; Temple, Struchen, & Pappadis, 2016; Vangel, Rapport, & Hanks, 2011; Verhaeghe, Defloor, & Grypdonck, 2005), improvements in caregiver sleep could ostensibly result in better health-related quality of life for the care recipient with TBI as well.

The current literature lacks critical information on factors that contribute to poor sleep in caregivers of individuals with TBI. Better understanding of contributors to poor sleep in caregivers is necessary to inform the development and application of targeted and individualized interventions. A recent article emphasized the need to identify effective sleep treatments that address the unique challenges presented by the caregiving context (McCurry et al., 2015). One neglected area of inquiry is the impact that care-recipient characteristics have on caregiver sleep. Studies typically focus on the individual with the sleep problem in identifying both contributors to poor sleep and effective sleep interventions. Likewise, currently available sleep interventions, such as administration of a sleep medication, application of a continuous positive airway pressure machine, or a behavioral intervention for sleep (e.g., cognitive–behavioral therapy for insomnia), are focused solely on the person with the sleep disturbance. In the caregiving context, however, the impact of the care recipient on the caregiver’s sleep warrants consideration. The combination of round-the-clock responsibilities, stress, and caregiver burden may contribute to caregiver sleep disturbance. Changes associated with having a TBI, such as emotional distress, impulsivity, and disinhibition, are often reported as most stressful to caregivers (Griffin et al., 2017; Kinsella, Packer, & Olver, 1991; Kreutzer, Gervasio, & Camplair, 1994a; Marsh et al., 1998; Norup, Welling, Qvist, Siert, & Mortensen, 2012; Oddy, Humphrey, & Uttley, 1978; Ponsford, Olver, Ponsford, & Nelms, 2003). These difficulties are also likely to contribute to caregivers’ sleep disturbance as they may be concerned about what may happen if they are not awake to monitor the person’s behavior. Furthermore, over 50% of individuals with TBI experience sleep disturbances themselves (Marsh et al., 1998; Marsh et al., 2002), and rates of sleep disorders (Castriotta & Murthy, 2011; Mathias & Alvaro, 2012), including OSA, may be up to 12 times higher in these individuals than in the general population (Holcomb et al., 2016; Mathias & Alvaro, 2012; Webster, Bell, Hussey, Natale, & Lakshminarayan, 2001). Such sleep difficulties may place caregivers at increased risk for sleep disruption as they may need to provide 24-hr care or are simply awakened by the disruptive sleep of the PwTBI.

Despite the likely impact of characteristics of the PwTBI on caregiver sleep, this association has, to our knowledge, remained unexamined. This is particularly unfortunate given that sleep interventions for caregivers may need to address factors specific to the caregiving role or to the care recipient in order to be effective. Thus, information on how the characteristics of the care recipient affect the caregiver’s sleep are sorely needed.

The aim of this study was to examine the combined and independent contributions of anxiety, depressed mood, and anger (collectively “emotional distress”) as well as cognitive functioning, upper extremity functioning, and lower extremity functioning (collectively “functional status”) in the PwTBI to the level of perceived sleep-related impairment in their caregiver. We conducted this cross-sectional study in a sample of caregivers of civilians or service members/veterans (SMVs) with TBI. Based on our previous findings that military caregivers report higher sleep disturbance than caregivers of civilians with TBI (Carlozzi, Ianni, et al., 2019), we expected to find that caregivers of SMVs would report significantly higher perceived sleep-related impairment. We hypothesized that the sets of variables reflecting emotional distress and functional problems in the PwTBI would each contribute significantly to perceived sleep-related impairment in both caregivers of civilians and SMVs with TBI.

Method

Study Participants

The current study included 52 caregiver/care-recipient dyads (23 civilian and 29 SMV dyads) who were recruited as part of a larger study designed to evaluate health-related quality of life (HRQOL) for caregivers of PwTBI. This is a secondary analysis of data from caregivers who were recruited to participate in a multiphase project designed to develop and validate new measures of HRQOL for caregivers of civilians and SMVs with TBI (Carlozzi, Kallen, et al., 2018); for this particular data set, care recipients of caregivers who were enrolled in the larger study were recruited in order to gather data from caregiving dyads. To enroll, both the caregiver and the PwTBI had to be willing to participate. Caregivers had to be at least 18 years old, able to read and understand English, and caring for an individual with a medically documented TBI. Caregivers had to be providing some form of care (physical assistance, emotional support, or financial assistance) to the PwTBI. Professional (i.e., paid) caregivers were not eligible for this study. PwTBI had to be ≥ 1 year postinjury to maximize sample homogeneity (Burns, Marino, Flanders, & Flett, 2012; Dikmen et al., 2009; Dikmen, Machamer, Winn, & Temkin, 1995; Dikmen, Mclean, & Temkin, 1986; Dikmen, Reitan, & Temkin, 1983; Ditunno, Stover, Freed, & Ahn, 1992; Jørgensen et al., 1995a, 1995b; Waters, Adkins, Yakura, & Sie, 1993, 1994; Waters, Adkins, Yakura, & Sie, 1998; Waters, Yakura, Adkins, & Sie, 1992). Civilians with TBI had to have medical record documentation supporting a complicated mild, moderate, or severe TBI according to TBI Model System inclusion criteria (Corrigan et al., 2012), whereas SMVs with TBI had to have medical record documentation to support a TBI diagnosis. Injury severity, classified according to military or Veterans Affairs definitions for mild, moderate, severe, or penetrating TBI, was available for only one SMV case (see Carlozzi et al., 2016). PwTBI must have sustained their TBI at age 16 or older, be at least 18 years old at the time of the study, be able to read and understand English, and be capable of providing informed consent. In instances where capacity to provide consent was questionable, the PwTBI had to receive a score of at least 25 on The Orientation Log (O-Log; Novack, 2000) and be able to accurately paraphrase the purpose of the study and their rights after they were explained to them. PwTBI with O-Log scores < 25 (out of a possible 30) were ineligible. All study activities were conducted in accordance with and with approval from local institutional review boards, and written informed consent was obtained for both members of the dyad prior to their participation in this study.

Measures

Demographics.

Demographic data including civilian or SMV status, age, gender, race, ethnicity, and education was collected via self-report on AssessmentCenter.net (Gershon, Rothrock, Hanrahan, Bass, & Cella, 2010), an online data collection platform. Medical record data for the PwTBI was included in the data set when available.

Caregiver measures.

Patient-Reported Outcomes Measurement Information System (PROMIS).

Caregivers completed the PROMIS (Cella et al., 2010) Sleep-Related Impairment computer adaptive test (CAT), which measures perceived alertness, sleepiness, and tiredness during normal waking hours over the past 7 days. Items are rated on a 5-point Likert-type scale ranging from 1 (not at all) to 5 (very much). Scores are on a T metric (M = 50, SD = 10); higher scores indicate more distress. Previous work supports the reliability and validity of this measure (Carlozzi, Boileau, et al., in press).

Mayo-Portland Adaptability Inventory-Fourth Edition (MPAI-4).

Caregivers also completed the MPAI-4 (Malec et al., 2003), a 35-item measure designed to evaluate caregiver perceptions of the functional ability of the person with TBI. Scores are on a T metric (M = 50, SD = 10); higher scores indicate lower functioning (Malec, 2005). Relative to other people with brain injury, score interpretation is as follows: T scores > 60 indicate severe limitations in functioning, T scores between 50 and 60 are in the moderate to severe range, T scores between 40 and 50 are considered mild to moderate, T scores between 30 and 40 indicate mild limitations, and T scores < 30 indicate good functioning (Malec et al., 2003). The MPAI-4 takes 5–10 min to complete. Previous studies support the reliability and validity of this measure (Bohac, Malec, & Moessner, 1997; Fortune et al., 2015; Kean, Malec, Altman, & Swick, 2011; Malec, Kean, Altman, & Swick, 2012; Wilde et al., 2010).

Care recipient measures.

PROMIS.

PwTBI completed the PROMIS (Cella et al., 2010) Anger CAT, which measures angry mood, negative social cognitions, and efforts to control temper during the past 7 days. Items are rated on a 5-point Likert-type scale ranging from 1 (never) to 5 (always). Scores are on a T metric (M = 50, SD = 10); higher scores indicate more distress. Reliability and validity of this measure is supported in clinical populations (Bajaj et al., 2011; Bartlett et al., 2015; Carlozzi, Goodnight, et al., 2019; Schalet et al., 2016; Stone, Broderick, Junghaenel, Schneider, & Schwartz, 2016; Tulsky et al., 2016).

Quality of Life in Neurological Disorders (Neuro-QoL).

PwTBI completed the Neuro-QoL (Cella et al., 2012; Cella et al., 2011) Anxiety CAT, which measures feelings of fear or helplessness, the Neuro-QoL Depression CAT, which measures feelings of hopelessness and negative mood, the Neuro-QoL Cognitive Function CAT, which measures perceived difficulty with thinking and memory, the Neuro-QoL Lower Extremities Function CAT, which measures balance and endurance, and the Neuro-QoL Upper Extremities Function CAT, which measures ability to perform activities of daily living. Items are rated on a 5-point Likert-type scale ranging from 1 (never/without any difficulty/no difficulty) to 5 (always/unable to do/cannot do). Scores are on a T metric (M = 50, SD = 10). Higher scores on negative affect measures (i.e., anxiety, depression) indicate more distress; higher scores on measures of function (i.e., cognitive function and upper/lower extremities function) indicate better functioning. Reliability and validity of these measures are supported in clinical populations (Amtmann, Bamer, Kim, Chung, & Salem, 2018; Carlozzi, Goodnight, et al., 2019; Kozlowski, Cella, Nitsch, & Heinemann, 2016; Miller et al., 2016; Nowinski et al., 2016; Tulsky et al., 2016; Victorson et al., 2014).

Analysis Plan

Statistical analyses were performed using SAS 9.4 software (SAS Institute Inc., Cary, NC). The study was adequately powered to test statistical significance (critical α = .05) in univariate analyses (e.g., t tests), where the purpose was to characterize differences between the civilian/SMV groups on a single variable at a time. However, the sample was underpowered to detect effects in multivariate analyses examining associations between characteristics of the PwTBI and caregiver sleep (e.g., regression models); therefore, effect sizes were prioritized, as described next, for multivariate analyses.

Descriptive statistics for demographic and key study variables were calculated. Comparisons between the civilian and SMV subsamples were examined using independent t tests (for continuous variables) and chi-squared tests (for categorical variables; Fisher’s Exact when expected cell counts were < 5). Hierarchical linear regression models were used to determine the amount of variance in caregiver sleep-related impairment that could be explained by the emotional distress of the PwTBI (anxiety, depressed mood, and anger) and the perceived functional status of the PwTBI (cognitive function, upper extremities function, and lower extremities function). Given the substantial differences between those caring for civilians versus SMVs with TBI and the inability to control for all these differences due to limited sample size, regression results were stratified by group (civilian/SMV status). Caregiver age and gender (for civilian models only) were entered in Step 1. Change in R2 (proportion of variance) estimates for sets of variables are dependent on order of entry into the model. To obtain estimates for the proportion of variance in caregiver sleep-related impairment over and above the effects of the other sets of predictors, models were first run entering emotional distress predictors in Step 2 and functional status predictors in Step 3. Next, the order of entry for emotional distress and functional status predictors was reversed. The two models resulted in identical results for independent effects of predictors, and only the R2 and model change (ΔR2) statistics changed based on order of entry. Adjusted R2 and ΔR2 (change) were examined to determine contributions of sets of variables to caregiver sleep-related impairment, and β (standardized regression coefficient) was examined to determine contribution of independent predictor variables in the models. To assess collinearity, variance inflation factor (VIF) was calculated after the final step of each model; there is no consensus about which level of VIF constitutes serious problems with multicollinearity, with criteria ranging from VIF > 5 to VIF > 10 indicating high collinearity (Hair, Anderson, Tatham, & Black, 1995; Sheather, 2009). Here, we adopt the criteria that VIF < 5 is acceptable. Given the small subsample sizes of the stratified civilian- and SMV-specific analyses, effect sizes were prioritized over statistical significance in the regression analyses. Specifically, moderate or large effects, indicated by standardized betas for independent predictors of at least 0.50 (moderate effect) or 0.80 (large effect) and R2 values of at least 0.25 (moderate effect) or 0.64 (large effect; Ferguson, 2009), were examined.

Results

Preliminary Results

The preliminary results are shown in Table 1. A total of 52 dyads (n = 23 civilians, n = 29 SMVs) participated in the current study. The civilian caregiver sample consisted of 69.6% women, whereas the SMV sample had only female caregivers (p = .001). Caregivers of civilians were on average 20 years older than their SMV counterparts (p < .0001). Most of the full sample was non-Hispanic and White and had attained at least a high school education. Caregivers of SMVs were more likely to be the spouse (93.1%) of the care recipient, while caregivers of civilians were more likely to include other relationships (p = .001). Demographics of these subsamples are largely consistent with the demographic characteristics of the populations they are meant to represent. Pre-9/11 military caregivers are more like caregivers of civilian TBI, with a higher proportion being the parent of the person with TBI; in contrast, post-9/11 military caregivers are different from civilian caregivers in that they are predominantly a spouse caregiver and under the age of 30 years (Ramchand et al., 2014). Compared with civilian caregivers, military caregivers are more likely to be caring for a person with mental health and/or substance abuse issues, provide emotional rather than physical support, and show evidence of greater stress and burden, as evidenced by approximately 3 times the amount of missed worked compared with civilian caregivers (Ramchand et al., 2014).

Table 1.

Descriptive Statistics for Demographic and Key Study Variables for Civilian and SMV Subgroups and the Total Sample

Variable Civilian (n = 23) SMV (n = 29) Total (n = 52) p
Caregiver demographics
 Gender (female, %) 69.6 100.0 86.5 .001
 Age, M (SD) 55.1 (14.1) 34.2 (6.6) 43.4 (14.8) <0001
 Race (%) .46
  White 91.3 89.7 90.4
  Black 4.4 0.0 1.9
  Other 4.4 10.3 7.7
 Ethnicity (%) .31
  Non-Hispanic 87.0 96.6 92.3
  Hispanic 13.0 3.4 7.7
 Highest education (%) .11
  Less than HS 4.4 0.0 1.9
  HS/GED 17.4 3.5 9.6
  More than HS 78.3 96.5 88.5
 Marital status (%) .18
  Never married 4.4 0.0 1.9
  Married 78.3 96.5 88.5
  Divorced 8.7 3.5 5.8
  Widowed 8.7 0.0 3.9
 Relationship to person with TBI (%) .001
  Spouse 47.8 93.1 73.1
  Parent 34.8 3.5 17.3
  Child/other family member 13.0 3.5 7.7
  Other 4.4 0.0 1.9
 Years in caregiver role 5.3 (4.6) 6.9 (2.6) 6.2 (3.7) .16
 MPAI-4 rating of person with TBI, M (SD) 43.4 (12.2) 62.0 (9.0) 54.4 (13.8) <0001
Person with TBI demographics
 Gender (female, %) 30.4 0.0 13.5 .002
 Age, M (SD) 43.3 (19.3) 35.6 (8.1) 39.0 (14.6) .08
 Time since injury in years, M (SD) 5.1 (4.5) N/Aa 5.0 (4.4) —
 TBI severity (%) <0001
  Complicated mild 30.4 0.0 13.5
  Moderate 26.1 0.0 11.5
  Severe 43.5 3.5 21.2
  Missing 0.0 96.5a 53.8
 Cause of injury (%) .0003
  Motor vehicle accident 65.2 31.0 46.2
  Fall 8.7 6.9 7.7
  Violence related 0.0 3.5 1.9
  Struck/thrown against object 0.0 44.8 25.0
  Missing 0.0 10.3 5.8
  Other 26.1 3.5 13.5
 Previous TBI (yes, %) 13.0 51.7 34.6 .0036
 PROMIS Anger, M (SD) 48.9 (12.8) 68.8 (9.1) 60.6 (14.5) <0001
 Neuro-QoL Anxiety, M (SD) 47.7 (10.6) 60.7 (6.7) 55.3 (10.6) <0001
 Neuro-QoL Depression, M (SD) 48.6 (9.0) 58.4 (7.1) 54.3 (9.3) <0001
 Neuro-QoL Cognitive Function, M (SD) 44.6 (9.5) 31.9 (5.5) 37.1 (9.7) <0001
 Neuro-QoL Upper Extremities Function, M (SD) 48.8 (8.0) 40.5 (8.2) 44.1 (9.1) .0005
 Neuro-QoL Lower Extremities Function, M (SD) 49.7 (8.8) 41.6 (7.0) 45.0 (8.9) .0004
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Note. SMV = service member/veteran; TBI = traumatic brain injury; HS = high school; GED = General Educational Development; MPAI-4 = Mayo-Portland Adaptability Inventory fourth edition; PROMIS = Patient-Reported Outcomes Measurement Information System; Neuro-QoL = Quality of Life in Neurological Disease. MPAI scores were missing for three civilian cases.

a

Medical records confirming time and severity of injury were not collected for the military sample with the exception of 3.5% of cases who personally provided medical records to the study team.

Caregiver ratings of the functioning of the PwTBI (MPAI T scores) show significantly higher functional impairment in the SMV group, where the average score is in the severely impaired range. In contrast, MPAI scores in the civilian group were, on average, in the mild-moderate impairment range. In the civilian subgroup, there was good representation of mild/complicated, moderate, and severe TBI; most of the data on injury severity in the SMV group was missing. Therefore, it is difficult to characterize the TBI severity in this subgroup or make comparisons between the groups. Prior (repeated) head injuries were more frequently reported in the SMV group (51.7%) compared to the civilian group (13.0%; p = .004).

In prior research, patient-reported outcome scores of one standard deviation from the mean have been considered to represent moderate to severe symptoms (mean T score ≥ 60 for measures where higher scores are negative or ≤ 40 for measures where higher scores are positive; Cella et al., 2014; Cook, Victorson, Cella, Schalet, & Miller, 2015; Nagaraja et al., 2018). Caregiver sleep-related impairment averaged 58.8 (SD = 12.5) for the full sample, which does not indicate impairment; however, there were significant differences between caregivers of civilians (M = 50.6, SD = 11.8) and caregivers of SMVs (M = 65.3, SD = 8.7; p < .0001), with the scores of SMV caregivers being in the impaired range.

For the PwTBI, the SMV group had significantly worse scores on all emotional (anger, anxiety, depression) and functional (cognition, upper extremities function, lower extremities function) measures. For both PROMIS Anger and Neuro-QoL Cognitive Function, the full sample scored beyond the threshold for impairment (i.e., 1 standard deviation above/below the mean); the military sample had means in the impaired range for PROMIS Anger, Neuro-QoL Anxiety, and Neuro-QoL Cognitive Function.

Regression Analysis Results

In the civilian sample, the regression model accounted for 32.5% of the variance in caregiver-perceived sleep-related impairment. Regardless of the step in which it was entered, the emotional distress of the PwTBI resulted in small, nonstatistically significant changes in variance accounted for in caregiver sleep-related impairment (see Table 2). In contrast, when entered either before (Step 2) or after (Step 3) emotional distress, functional status of the PwTBI accounted for moderate increases of 20–28% of variance in caregiver sleep-related impairment. In terms of the contribution of individual variables, cognitive functioning of the PwTBI demonstrated a large (β = −0.82, p = .08) and upper extremity functioning of the PwTBI demonstrated a moderate (β = 0.61, p = .61) independent effect on sleep-related impairment for civilian caregivers. All other variables, including age and gender, demonstrated small effects on caregiver-perceived sleep-related impairment.

Table 2.

Hierarchical Linear Regression Predicting Sleep-Related Impairment in Caregivers of Civilians From Variables Reflecting Emotional Distress and Functional Status of the Care Recipient With TBI

Step Predictor β [95% CI] p VIF ΔR2
1 Gender 0.19 [−9.74, 19.46] .48 1.52 0.01
Age −0.09 [−0.67, 0.50] .77 2.22
2/3 Neuro-QoL Anxiety −0.29 [−0.49, 1.27] .52 3.87 0.11/0.03
Neuro-QoL Depression 0.25 [−0.86, 1.52] .56 3.71
PROMIS Anger −0.02 [−0.73, 0.69] .95 2.67
3/2 Neuro-QoL Cognitive Functiona −0.82 [−2.18, 0.16] .08 4.00 0.20/0.28
Neuro-QoL Upper Extremitiesa 0.61 [−0.86, 1.40] .61 2.63
Neuro-QoL Lower Extremitiesa 0.36 [−0.49, 1.27] .36 1.94
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Note. N = 23. TBI = traumatic brain injury; β = standardized beta coefficient; 95% CI = 95% confidence interval of the standardized beta coefficient; VIF = variance inflation factor; ΔR2 = change in R2 between models; Neuro-QoL = Quality of Life in Neurological Disease; PROMIS = Patient-Reported Outcomes Measurement Information System.

a

Measure is reverse scored so that higher scores indicate better health.

In the SMV sample, the regression model accounted for 26.3% of the variance in caregiver-perceived sleep-related impairment. Regardless of the step in which it was entered, the functional status of the PwTBI resulted in very small changes in variance accounted for (ΔR2 0–10%) in caregiver sleep-related impairment (see Table 3). In contrast, when entered in Step 3, emotional distress resulted in a 24% increase in the amount of variance accounted for in caregiver sleep-related impairment. In terms of individual variables, anger levels of the PwTBI demonstrated a moderate independent effect (β = 0.54, p = .07) on caregiver sleep-related impairment. All other individual variables, including the demographic variable, age, demonstrated small effects on caregiver sleep-related impairment.

Table 3.

Hierarchical Linear Regression Predicting Sleep-Related Impairment in Caregivers of SMVs From Variables Reflecting Emotional Distress and Functional Status of the Care Recipient With TBI

Step Predictor β [95% CI] p VIF ΔR2
1 Age 0.05 [−0.52, 0.64] .83 1.29 0.01
2/3 Neuro-QoL Anxiety −0.17 [−1.00, 0.55] .56 2.29 0.15/0.24
Neuro-QoL Depression 0.24 [−0.35, 0.96] .35 1.86
PROMIS Anger 0.54 [−0.06, 1.04] .07 2.42
3/2 Neuro-QoL Cognitive Functiona 0.33 [−0.25, 1.27] .18 1.56 0.10/0.00
Neuro-QoL Upper Extremitiesa −0.08 [−0.61, 0.43] .73 1.53
Neuro-QoL Lower Extremitiesa 0.15 [−0.43, 0.79] .52 1.68
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Note. N = 29. SMV = service member/veteran; TBI = traumatic brain injury; β = standardized coefficient; 95% CI = 95% confidence interval of the standardized beta coefficient; VIF = variance inflation factor; ΔR2 = change in R2 between models; Neuro-QoL = Quality of Life in Neurological Disease; PROMIS = Patient-Reported Outcomes Measurement Information System.

a

Measure is reverse scored so that higher scores indicate better health.

Discussion

This study examined the effects of characteristics of the PwTBI (care recipient) on the perceived sleep-related impairment of the caregiver. Caregivers of SMVs reported much higher levels of perceived sleep-related impairment compared to caregivers of civilians. Means for caregivers of SMVs were approximately 1.5 standard deviations higher than for civilian caregivers, constituting a clinically significant difference between the groups. This finding precipitated further group-specific, stratified analyses that showed several interesting findings within groups of civilian and SMV caregivers.

The relative contribution of care-recipient emotional distress versus functional status to caregiver sleep-related impairment was examined within the civilian and SMV subsamples. For the sample of caregivers of civilians, the functional status of the PwTBI was more consequential to caregiver sleep-related impairment than the emotional distress of the PwTBI; cognitive functioning of the PwTBI also had a large independent effect on sleep-related impairment for caregivers of civilians versus SMVs. In contrast, in the sample of caregivers of SMVs, the emotional distress of the PwTBI was more consequential to caregiver sleep-related impairment than the functional status of the PwTBI relative to their civilian counterparts; specifically, the care-recipients’ level of anger demonstrated a moderate independent association with perceived sleep-related impairment for military caregivers.

While these findings indicate that the caregiver role may be experienced differently by those caring for civilians versus SMVs, these findings may reflect important differences other than civilian/SMV status in these subsamples. It should be noted that the civilian and SMV groups were quite different in terms of caregiver age, gender ratios, and relationship to the person with TBI; how these groups differ in terms of the severity of the injury in the person with TBI is not clear due to difficulties in obtaining thorough diagnosis information for the SMV subsample. According to the caregiver report (i.e., MPAI scores), those PwTBI in the SMV subgroup were significantly more impaired compared with the civilians. The impact of severity of TBI and of both global functional impairments and more focal impairments of the PwTBI on caregiver sleep bears further examination. Different patterns of impairment in the PwTBI call for different types of caregiving; the possibility that provision of care in different domains (e.g., financial, emotional, physical assistance, activities of daily living) may have different effects on the caregiver, and specifically on caregiver sleep, warrants further examination. It should be noted that while these differences in group demographics make it difficult to ascertain the reasons why different care-recipient characteristics are related to caregiver sleep within each subsample, these subsamples do largely reflect observed differences in the demographics of the subpopulations of civilian and SMV caregivers (Ramchand et al., 2014).

Differences in the required inclusion criteria for the PwTBI between the groups may have played a role in the findings. For the civilian sample, individuals with uncomplicated mild TBI where excluded, while they were included for the SMV sample. The decision to include those with uncomplicated mild TBI in the SMV group was made due to existing prevalence rates for mild TBI in the military (i.e., ~80%; Defense & Veterans Brain Injury Center, 2015). Despite the inclusion of uncomplicated mild TBI in the military subsample, the SMVs with TBI endorsed significantly higher cognitive impairment and more emotional distress on the PROMIS and Neuro-QoL measures. These differences in self-report correspond with the caregivers’ rating of SMVs as more functionally impaired compared with the civilian subgroup. Additional studies are needed to further examine these findings in a sample that allows for consideration of the impact of factors such as TBI severity and care-recipient level of function (both global impairment and focal impairments), as measured by proxy report and/or objective assessments, to provide an optimally reliable assay of level of dependence on the caregiver.

The impact of other factors, such as distinct models of care in civilian versus military health care systems on caregiver sleep, also warrants examination in future studies. For example, rehabilitation of the person with TBI may focus differentially on physical, cognitive, and emotional functioning, and caregivers may experience different quality and quantity of interactions with health care providers and may receive different levels of support across military and civilian health care systems.

The findings have implications for caregiver support programming and clinical care. The higher incidence of sleep problems in the SMV sample may inform the nature of informational and navigational supports in the Department of Veterans Affairs Caregiver Support Program (Collins & Kennedy, 2008). Identifying caregivers at higher risk for sleep-related problems can help inform screening of caregivers in greater need of sleep-related health services earlier in the caregiving process. Screening and evaluation of sleep problems among caregivers should consider the impact that the care recipient has on the caregiver, with efforts to address effects of the behaviors of both members of the caregiving dyad in sleep-focused interventions.

This study provides preliminary evidence as to the association between emotional, cognitive, and physical factors in a PwTBI and the sleep of their caregiver. Several study limitations warrant careful interpretation of the current findings and replication and extension in future studies. First, this study examined self-reported sleep-related impairment and did not include any objective assessments of sleep. Future work is needed to determine if a similar pattern of findings would result from using more objective measures of sleep (e.g., polysomnography, actigraphy). In addition, we did not include any assessments of sleep in the PwTBI, which is unfortunate given that the previous research would indicate that caregiver sleep should impact care-recipient sleep, and vice versa (Verhaeghe et al., 2005). Our sample was comprised primarily of White female caregivers, which does not allow for comparisons based on gender, race, and relationship type. These factors limit the generalizability of our findings to the broader caregiver population. While we would assume that the majority of these caregiver/care-recipient dyads were cohabiting and sleeping in the same room (given that the majority of caregivers were the spouse of the person with the TBI), we did not formally assess living/sleeping situation. Future work is needed to better understand the impact that living situation has on sleep among these dyads. Furthermore, the small sample size precluded our ability to conduct detailed examination of these two subsamples. Our within-group findings were conducted post hoc, and effect size was prioritized over statistical significance, which could have introduced bias. Therefore, these results should be interpreted with caution. We also did not include identical assessments for each member of the dyad, which precluded the examination of within-dyad associations.

Another notable limitation is that we did not examine characteristics of the caregivers that may be influential to sleep, including their own emotional distress and functional status. Our earlier work has shown that caregiver sleep is strongly related to both emotional and physical health for the caregiver (Carlozzi, Ianni, et al., 2019). Similarly, there were several characteristics related to the PwTBI that were not examined and warrant further explanation (including injury severity, as well as number of sustained TBIs). Because this study was limited by the small sample, we could not account for all these caregiver and PwTBI factors in the models. Therefore, it is important that future work examines the role of additional caregiver and PwTBI factors as potential mechanisms of the impact of care recipient on caregiver sleep. These mechanisms may reflect fairly direct links, such as stress-related physiological changes in the caregiver that could impact their sleep quality.

Regardless of the limitations of this study, these findings highlight the importance of examining caregiver sleep in the context of the caregiver/care-recipient dyad and would suggest that there are important characteristics of the PwTBI that have a significant impact on caregiver sleep. This finding is consistent with work in other caregiving populations that has demonstrated a reciprocal relationship between both members of the caregiver dyad (Hamidou et al., 2017; Kotronoulas, Wengström, & Kearney, 2013; Pakenham, Dadds, & Lennon, 2002). This preliminary work informs future work aimed at improving caregiver sleep that needs to be personalized to consider the important contextual effects of the characteristics of the PwTBI.

Impact and Implications.

Characteristics of care recipients with traumatic brain injury (TBI) may have a substantial impact on caregiver sleep. Successful interventions to improve sleep in caregivers may need to address factors that are specific to the caregiver (e.g., emotional distress, health behaviors) as well as specific to the care recipient with TBI (e.g., functional limitations, emotional distress).

Acknowledgments

This article was supported by Grant R01NR013658 (PI: Noelle E. Carlozzi) from the National Institutes of Health, National Institute of Nursing Research. In addition, funding from the National Center for Advancing Translational Sciences (UL1TR000433) provided support for data collection. Anna L. Kratz’s contribution to this article was supported in part by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (K01AR064275). We thank the investigators and research associates/coordinators who worked on the study, the study participants, and the organizations that supported recruitment efforts.

Contributor Information

Anna L. Kratz, University of Michigan.

Nicholas R. Boileau, University of Michigan.

Angelle M. Sander, Baylor College of Medicine and TIRR Memorial Hermann, Houston, Texas

Risa Nakase-Richardson, James A. Haley Veterans’ Hospital, Tampa, Florida, and University of South Florida.

Robin A. Hanks, Rehabilitation Institute of Michigan, Detroit, Michigan, and Wayne State University

Jill P. Massengale, James A. Haley Veterans’ Hospital, Tampa, Florida

Jennifer A. Miner, University of Michigan

Noelle E. Carlozzi, University of Michigan

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