Resiliency Factors associated with quality of life in primary caregivers of patients admitted to the neuroscience intensive care unit

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Resiliency Factors associated with Quality of Life in Primary Caregivers of Patients

admitted to the Neuroscience Intensive Care Unit

Department of Developmental Psychology

April 6

th

₂₀₁₇

Tessa Heinhuis

Student ID: 10319891

University of Amsterdam

Master’s thesis

Supervisor: dr. Bianca Boyer

External supervisors: dr. Ana-Maria Vranceanu, PhD & dr. Emily Zale, PhD

Second supervisor: Maien Sachisthal

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TABLE OF CONTENTS

Abstract

Introduction

Theoretical Constructs

Promoting Quality of Life

The Current Study

Research Question

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Materials and Methods

Participants

Procedure

Measurements

Statistical Analyses

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Results

Descriptives

Relations between caregivers’ own resilience factors and Quality of Life

Relations between patients’ resiliency and caregiver’ QoL

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Discussion

Limitations and Future Directions

Implications and Conclusions

References

Appendix

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ABSTRACT

Purpose: The purpose of this study is to examine the associations of caregivers’ Quality of Life (QoL)

(physical, psychological, social and environmental) with their own and their patients’ psychosocial resiliency factors (mindfulness, coping, self-efficacy, social support) and patients’ QoL, within two weeks after the patients’ admission to the neuroscience intensive care unit (Neuro-ICU), in order to effectively help future caregivers through psychosocial interventions.

Methods: Fifty-six dyads of caregivers (total N = 63) and patients (total N = 56) participated in this prospective

study and self-reported demographics and measures of four separate QoL domains (WHOQOL-BREF), mindfulness (CAMS-R), coping (MOCS-A), intimate bonds (IBM) and self-efficacy (patients: GSE; caregivers: CSES-R) during hospitalization.

Results: Caregivers’ mindfulness, coping and self-efficacy were significantly associated with at least one of their

own QoL domains, though there were no cross-over effects: patients’ resiliency skills were not related to caregivers’ QoL.

Conclusions: For each QoL domain of the caregivers, at least one resiliency skill was of predictive value, with

mindfulness being the strongest predictor for caregiver QoL.. These findings emphasize the importance of resiliency focused interventions for caregivers, to enhance these skills to improve overall QoL in these vulnerable populations.

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INTRODUCTION

Every year, more than 5 million Americans are admitted to intensive care units (ICUs) and need

subsequent emotional and functional support as they embark on the journey of recovery (Gunderson, Walter, Ruskin, Ding & Moore, 2016; Iwashyna, 2010). As a consequence, yearly millions of people become informal caregivers, who are unpaid individuals (e.g., spouse or romantic partner, family member, friend, neighbor) involved in assisting with activities of daily living and/or medical tasks (National Alliance of Caregiving, 2005). Because of the often sudden nature of the ICU admission and the high risk of medical consequences and long-lasting effects, many informal caregivers have little time to prepare for their new role (Ågård, Egerod, Tønnesen & Lomborg, 2015), and may become overwhelmed by adding the task of care giving to their own work and family responsibilities (van den Born-Van Zanten, Vink, Dongelmans, Dettling-Ihnenfeldt, Vink & Van der Schaaf, 2016). Technological and medical improvements have increased the proportion of patients who recover from critical illness and thus are discharged from ICUs (Gunderson, Walter, Ruskin, Ding & Moore, 2016), which, in turn, creates an increasing need for more informal caregivers. Indeed, the unpaid work provided by informal caregivers is estimated at hundreds of billions of dollars annually in the U.S. only, since caregivers replace paid nurses and medical staff (Schulz & Sherwood, 2008).

A substantial proportion (40%) of patients admitted to Neuroscience Intensive Care Units (Neuro-ICUs) evince neurological damage that leads to physical, cognitive and behavioral challenges (Greenwood, 2001). As such, informal caregivers to Neuro-ICU patients may face unique care giving challenges, and multiple studies have demonstrated that these informal caregivers experience psychological distress associated with admission to the Neuro-ICU admittance of their loved one (Shaffer, Riklin, Jacobs, Rosand & Vranceanu, 2016; Wartella, Auerbach & Ward, 2009). This stress is often followed by clinically significant psychiatric

symptoms, such as anxiety or depression, probable to continue from hospital admission through months or even years later (Ayerbe, Ayis, Wolfe & Rudd, 2013; Gillen, Tennen, Affleck & Steinpreis, 1998). Caregivers’

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psychiatric symptoms increase their own risk for disease (Lee, Colditz, Berkman & Kawachi, 2003) and even mortality (Schulz & Beach, 1999).

Theoretical Constructs

The multiple challenges that informal caregivers face because of their increased stress and psychiatric symptoms, including seeing their loved one in sick health, shifting of roles, responsibilities and obligations, and having to adapt to new life perspectives and future goals (McCullagh, Brigstocke, Donaldson & Kalra, 2005), can adversely impact their own Quality of Life (QoL). QoL is a multi-dimensional construct that broadly refers to an individual’s perceptions of their status in relation to their goals, expectations, cultural values and standards. Decreased QoL is common in ICU caregivers (Johnson, Chaboyer, Foster & Van Der Vooren, 2001).

QoL can be measured across multiple domains, the most central and most reported domains including health, both physical (e.g. energy and fatigue, mobility) and psychological (e.g. self-esteem, positive and negative feelings), social relationships (e.g., receiving emotional, physical and financial support) and environment (e.g., access to financial resources, living in satisfactory neighborhoods, safety) (Opara & Jaracz, 2010), hence in this research when we mention QoL, we are discussing these four specific domains. Patients reporting low QoL are associated with increased experienced strain of their caregivers and the QoL of the patient influences the QoL of their primary caregiver (McPeake et al., 2016). There is also evidence that caregiver burden (i.e., ‘the extent to which caregivers distinguish that their emotional or physical health, social life and financial condition are suffering as a consequence of caring for their loved one; Johnson, Chaboyer, Foster & Van Der Vooren, 2001) negatively affects the caregivers’ overall health-related QoL (Bell, Araki & Neumann, 2001). Among caregivers, low QoL has been shown to negatively impact caregiver mental and physical health, and it may also have indirect negative effects on patients (Beach, Schulz, Williamson, Miller, Weiner & Lance, 2005).

QoL is positively influenced by resiliency (Ristevska-Dimitrovska, Filov, Rajchanovska, Stefanovski &

Dejanova, 2015); the ability to adapt effectively to negative or stressful circumstances in life. Resiliency is a multi-dimensional construct that includes biological, social and psychological processes (Bonanno, Galea,

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Bucciarelli & Vlahov, 2007). Theoretical conceptualizations of resiliency and numerous empirical

observations indicate that resiliency may be protective against the development of psychiatric symptoms while faced with adversity (Shaffer, Riklin, Stagl, Rosand & Vranceanu, 2016), perhaps because resiliency is associated with adaptive thinking patterns and the ability to access resources needed to reduce negative outcomes (Wilson, Meyer, Antebi-Gruszka, Boone, Cook & Cherenack, 2016). Several theoretical frameworks have been used to conceptualize resiliency (Wilson et al. 2016, Fergus & Zimmerman, 2005; Bonanno, Galea, Bucciarelli & Vlahov, 2007). These models are unified by several elements, and, in one of the most central models, the compensatory model, resiliency is associated with positive outcomes regardless of

the severity of the stressor (Wilson et al., 2016; Masten, 2001).

Several resiliency constructs depicted in preceding research include: mindfulness (living in the moment

with open attention and observing your stressful thoughts from a distance without judging them, the ability to purposefully direct and maintain attention in a non-judgmental manner; Brown & Ryan, 2003), coping

(consciously and adaptively focusing on your own efforts to deal with personal or interpersonal conflict; Steinhardt & Dolbier, 2008), social support (the possibility to engage in interpersonal interactions providing

emotional, tangible, informational resources and companionship and the feeling someone is cared for and has loving assistance available; Horton & Wallander, 2001) and self-efficacy (a person’s perception of his or her own

capacity to reach goals, a judgment regarding how people can control their behavior to face life’s challenges; Wilson et al., 2016). These resiliency constructs have positive associations with numerous health outcomes (Tugade, Fredrickson & Feldman Barett, 2004). Moreover, former research indicates that, among caregivers of patients with brain injuries, resiliency constructs are strong predictors of QoL, perhaps by increasing use of positive emotions to cope with stress (Kitter & Sharman, 2015).

Promoting Quality of Life

Given the major burdens that can be placed on informal caregivers of Neuro-ICU patients and the possible contribution of resiliency in improving their QoL, it is important to identify specific factors that may promote or maintain their QoL. Not all caregivers report low QoL after the initial adjustment post

Neuro-7

ICU, some are able to adjust and return to baseline psychosocial wellbeing right after the hospitalization of their loved one. A previous literature review noted that 36% of informal caregivers experienced negative changes in their QoL (van Beusekom, Bakhshi-Raiez, De Keizer, Dongelmans & van der Schaaf, 2016) and, besides that, 12.2% of caregivers at hospital discharge and 15.6% of caregivers at 6 months after discharge were classified as having symptoms consistent with severe depression (Douglas and Daly, 2003). Because of this, it is important to identify modifiable factors, such as resiliency variables, that are associated with

improved caregiver QoL, since 1) caregivers with low QoL will most likely continue to have even lower QoL as they embark on care giving after discharge; 2) caregivers with poor QoL are not going to be able to provide high quality of care for the patient, and this will impact the patient’s recovery; 3) poor QoL is a risk factor for morbidity and mortality. Examining caregivers’ QoL at the time of hospitalization of their loved one and relating this to resiliency skills that are used would allow us 1) to identify caregivers with low QoL early in the recovery process of their loved one and 2) to develop brief resiliency skills based interventions (e.g.

mindfulness sessions, coping or self-efficacy training, social support groups) to promote caregiver QoL. Previous research on caregivers’ QoL of ICU patients has typically been conducted months after the hospitalization (Berg and Upchurch, 2007) and focused on variables that negatively affect QoL (e.g.,

depression, anxiety or severe distress; Ristevska-Dimitrovska et al., 2015). Given that resiliency is associated with improved QoL (Talepasand, Pooragha & Kazemi, 2013) and that many resiliency factors can be promoted via psychosocial interventions (Luthar & Cicchetti, 2000), an important next step in this line of research is to examine associations between resiliency factors and QoL among informal caregivers of patients recently admitted to the Neuro-ICU.

The Current Study

To fill this gap in the literature, the purpose of this cross-sectional study was to test associations between multiple factors of resiliency (i.e., mindfulness, coping, self-efficacy and social support) and specific domains of QoL among informal caregivers at the time of patient admission to the Neuro-ICU. Specifically, we sought to test whether one’s own resiliency skills would be associated with physical, psychological,

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environmental, and social QoL. Previous studies found that QoL of life of caregivers and patients diagnosed with cancer were interrelated and identified that patient and caregiver factors often interact (Berg and Upchurch ,2007; Garcia, Kenny and Ledermann, 2015), even though most prior research assessing QoL has only looked at patients factors (McPeake et al., 2016). Both psychological resilience and lower QoL following illness are interconnected within patient-caregiver dyads (Berg & Upchurch, 2007; Hodges, Humphris & MacFarlane, 2005), but it is not clear yet if this also accounts for dyads recently after the patient was admitted to a Neuro-ICU. As such, when accounting for QoL in caregivers, it is important to assess both own and patient’s resiliency skills (Hodges, Humphris & MacFarlane, 2005).

In this study, several control variables are used to obtain a better insight in the relations between resiliency skills and QoL of caregivers of Neuro-ICU patients. Although gender, age, sex, education level, marital status and employment status of caregivers are not the core factors in this study, it is of importance to understand them to be able to remove their effects from the relation between caregivers’ resiliency skills and caregivers’ QoL. These control variables explain part of the variance between caregiver QoL and resiliency skills of both caregivers and patients, which is what we want to control for.

Age is an important control variable, since it is often negatively significantly related to QoL

(Quintana, Arostegui, Oribe, López de Tejada, Barrios & Garay, 2005). Age is coded as a continuous variable, so there are no separate groups. Also meaningful to this study is the control variable gender, since previous research indicated that women in general feel happier than men and have better QoL than men (Alesina, Di Tella & MacCulloch, 2004). One more variable that has to be controlled for in this study is race, since it has been found that African-American and Hispanic report lower QoL than non-Hispanic white participants (Quittner et al., 2010). Also, prior research has found that men with (a history of) prostate cancer with less education experience worse QoL (Knight et al., 2007). Besides that, employment status of the last 12 months is an important control variable, since unemployment or a history of unemployment predicts lower QoL (Ulfarsson, Nilsson, Blomstrand & Nilsson, 2014). Finally, marital status can be of influence for QoL, because it has been concluded in another study that in general, not being married has a negative effect on QoL (Blanchflower & Oswald, 2004).

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Research Question

Since there’s evidence that the higher the level of resiliency is, the better it improves a person’s global QoL (Opara & Jaracz, 2010), we hypothesized that at least one of the four different caregiver resiliency factors would evince unique, positive associations with caregiver QoL, after accounting for all control variables; non-modifiable caregiver (age, gender, sex, marital status, education level and employment) and patient (intubation status and type of diagnosis) factors. We assume that each of the four QoL domains has significant associations with mindfulness, self-efficacy, coping or social support.

Besides that, improved resiliency skills of patients, such as coping, can decrease the experienced burden of caregivers (Bergquist, Klunk, Krishnan, Milburn & Smigielski, 2015) and psychological resilience following illness is significantly related between patients and their caregivers (Shaffer, Riklin, Jacobs, Rosand & Vranceanu, 2016). Moreover, low mindfulness of patients is related to high depressive symptoms in caregivers (Shaffer, Riklin, Jacobs, Rosand & Vranceanu, 2016) and therefore we hypothesized that patients’ resiliency skills can be of predictive value for caregivers’ QoL.

The main research question of this study is, hence, if resiliency skills of caregivers are positively related to QoL of caregivers of patients recently admitted to the Neuro-ICU, at the time of hospitalization. Thus, following previous literature on resiliency and QoL, the key hypothesis is, more specifically, that there is a positive and significant relation between caregivers’ physical, psychological, social and environmental QoL and either mindfulness, self-efficacy, coping or social support of caregivers, above-and-beyond non-modifiable caregiver and patient factors. Secondly, it is explicitly hypothesized that either patients’

mindfulness, self-efficacy, coping and social support is significantly related to each of the QoL domains of their caregivers.

MATERIALS AND METHODS Participants

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Patients admitted to the Neuro-ICU of a large, urban hospital in Boston (MA) and their informal primary caregivers were recruited between March 2015 and December 2016. Patients and caregivers were approached during their inpatient hospitalization and screened for inclusion/exclusion criteria. Inclusion criteria for the patient and informal primary caregivers were: 1) age 18 years or older and 2) English fluency and literacy. Only the patient’s single primary caregiver was eligible to enroll. Patients had to have been admitted to the Neuro-ICU within two weeks of admission and medically cleared for participation by medical staff. Caregivers were identified by the patient as the person who would be the primary source of informal care after hospital discharge. Patients who were identified as non-eligible by medical staff, due to any medical (i.e. critical illness) or cognitive (i.e. patient suffering from dementia) issues were not able to consent and therefore were not asked to participate in the study. A total of 83 patient-caregiver dyads enrolled and completed questionnaires about resiliency and QoL.

Procedure

This was a cross-sectional study of baseline data collected in the course of a larger prospective study of dyads of patients admitted to the Neuro-ICU and their informal primary caregivers. Patients and caregivers were approached and screened in their hospital room during the inpatient hospitalization. Dyads who agreed to participate in the study were provided with packets of questionnaires to complete during their hospital stay. Enrollment, inclusionary criteria review and self-report questionnaire completion occurred at the bedside in the single-patient Neuro-ICU rooms. Electronic medical records were also reviewed by trained staff to record the disease severity and impairment for each patient, as well as the reason for admission to the ICU and discharge status. In some cases the patient was not able to complete the questionnaires, so only the caregiver provided data (N=63), and in other cases patients were able to participate but they had no primary caregiver present, so they enrolled in the study without a caregiver (N=56).

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Demographics. Demographic characteristics, including age, gender, race/ethnicity, marital status,

education, and primary employment status were assessed via self-report.

QoL. The World Health Organization Quality of Life BREF (WHOQOL-BREF; Skevington, Lotfy

& O’Connell, 2004) is a 26-item self-report questionnaire, which measures QoL across the following

domains: physical health (e.g. activities of daily living, energy and fatigue, work capacity), psychological health (e.g. negative and positive feelings, self-esteem, bodily image and appearance), social relationships (e.g. personal relationships, support and sexual activity) and environment (e.g. physical safety and security, health and social care, home environment, opportunities for recreation). The WHOQOL-BREF is a widely used, reliable, and valid measure of QoL (Skevington, Lotfy & O’Connell, 2004). All items are rated on a 5-point Likert scale (1 indicating a low score and 5 representing a high score), and domain scores are calculated according to published scoring recommendations, with high scores indicating higher quality of life. Each domain score has a range of 4-20.

Caregiver Self-Efficacy. The Revised Caregiver Self-Efficacy Scale (CSES-R; Steffen, McKibbin, Zeiss,

Gallagher-Thompson & Bandura, 2002), is a reliable and valid measure of the extent to which caregivers hold confidence in their abilities to perform care giving duties (Steffen, McKibbin, Zeiss, Gallagher-Thompson & Bandura, 2002). The measurement consists of 15 items, each rated on a 0-100 scale, with response anchors at 0 (0% confidence means that you cannot do it at all), 50 (50% confidence means that if you gave it your best effort, there is a 50% chance that you might succeed), and 100 (100% confidence means that you are

convinced you can do it). The CSES-R measures 3 domains of care giving self-efficacy: Obtaining Respite, Responding to Disruptive Patient Behaviors, and Controlling Upsetting Thoughts. The total care giving self-efficacy score is the average of all items and ranges from 0 to 1500, with higher scores indicating better perceived ability to provide assistance and guidance to a loved one in need.

Patient self-efficacy. Only patients completed the General Self-Efficacy Scale (GSES; Chen, Gully &

Eden, 2001) to assess a general sense of perceived self-efficacy and the coping skills used with daily hassles as well as adapting correctly after stressful life events. The 10 items (e.g. “I am confident that I could deal efficiently with unexpected events”) are scored on a 4-point Likert scale with responses ranging from 1 (“not

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at all true”) to 4 (“exactly true”). The total score of this test has a range from 10 to 40, with higher scores indicating a higher believe that one’s own actions are responsible for successful outcomes. In samples from 23 nations to test the reliability, Cronbach’s alphas ranged from .76 to .90, with the greater part in the high .80s (Chen, Gully & Eden, 2001). Criterion-related validity is documented in numerous correlation studies where positive coefficients were found with favorable emotions, optimism, and work satisfaction. Negative coefficients were found with depression, anxiety, stress, burnout, and health complaints (Luszczynska, Scholz & Schwarzer, 2005).

Mindfulness. The Cognitive and Affective Mindfulness Scale-Revised (CAMS-R; Feldman, Hayes,

Kumar, Greeson & Laurenceau, 2007) was used to assess typical use of mindfulness skills (e.g., acceptance of things you can’t change, staying in the present) in everyday life. The 12 items are rated on a four-point Likert scale, with responses ranging from 1 (“rarely/not at all”) to 4 (“almost always”), and summed to represent a total mindfulness score, with scores ranging from 12 to 48. Higher scores indicate more mindfulness skills used on a daily basis. Validity was found to be acceptable to good in the R (0.66). The overall CAMS-R demonstrated acceptable levels of internal consistency (Feldman, Hayes, Kumar, Greeson & Laurenceau, 2007).

Intimate Bond Measure. The Intimate Bond Measure (IBM; Wilhelm & Parker, 1988) measures two key

underlying dimensions; care and control, between partners in an intimate relationship, and in general indicates the way both participants experience social support. The IBM consists of 24 items with 2 subscales: 12 items for the care dimension and 12 items for the control dimension, all being scored on a 4-point Likert scale with responses ranging from 0 (“not at all”) to 3 (“very true”). The total score is ranging from 0 to 36, with higher scores demonstrating higher perceived care and lower partner controlling. This instrument has been validated among other populations of patients and their caregivers (Fisher, Tran, Biggs & Tran, 2014).

Perceived Coping Abilities. The Measure of Coping Status-A (MOCS-A; Antoni et al., 2006) is a reliable

and valid measure of perceived ability to use coping strategies, including relaxation, awareness of stress, assertiveness, and disputing maladaptive thoughts. The MOCS-A consists of 13 items that are scored using a 5-point Likert scale, with responses ranging from 0 (“I cannot do this at all”) to 4 (“I can do this extremely

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well”). Total scores range from 0 to 52, with higher scores indicating higher levels of perceived coping

abilities. This instrument has been proven to be reliable and has been validated among other medically ill populations (Antoni et al., 2006).

Statistical Analyses

All 8 hierarchical analyses were completed using SPSS version 20 (2011; IBM Corp, Armonk, NY), and to reduce the occurrence of a type 1 error, the incorrect rejection of a true null hypothesis, an alpha level of .05/8 = .006 was used to determine statistical significance. Caregivers’ and patients’ characteristics were summarized by measures of central tendency (e.g. proportion, mean).

Regarding the main hypothesis, that at least one of the caregivers’ resiliency skills is significantly related with caregiver QoL above-and-beyond non-modifiable caregiver and patient factors, a hierarchical linear regression was used to test associations between caregiver resiliency factors and caregiver QoL domains and to assess whether variables other than resiliency skills have an effect on caregiver’ QoL. Non-modifiable caregiver factors (e.g. age, gender) were entered at Step 1 and non-modifiable patient factors (i.e. intubation and diagnosis) were entered at Step 2, to understand the possible predictive value of these control variables. Resiliency factors of caregivers, the independent variables, were entered at Step 3.

Regarding the second hypothesis, that is, patients’ resiliency factors are of predictive value for caregivers’ QoL, another hierarchical regression was run. Non-modifiable patient demographics and

characteristics (e.g. age, gender) were entered at Step 1 and patient factors (i.e. intubation and diagnosis) were entered at Step 2. At Step 3, patients’ resiliency skills, the independent variables, were added to the model. The reason for this order is to get a clear insight of the different variables and their effects on caregiver QoL. Separate models were conducted for each caregiver’ QoL domain (Physical Health, Psychological, Social Relationships and Environment), with every domain being the dependent variable. For each hierarchical regression model, the change in R2 _{was used to examine the relative contribution of resiliency factors in} addition to the non-modifiable patient and caregiver factors.

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RESULTS

Descriptives

Of the 132 eligible patients who were approached, 100 patients and 110 of their primary caregivers consented to participate. There were 83 full patient-caregiver dyads. Of all the complete dyads who were enrolled in this broader study (N = 83), a total N of 63 caregivers and a total N of 56 patients provided responses to all questionnaires related to the research questions in this study. The samples comprised primarily middle-aged, white, highly educated and married participants. Caregivers and patients reported significant comparable levels of resiliency skills and QoL (Table 1).

Table 1. Summary of variable descriptives.

Characteristics Caregivers

(N = 63) Patients* (N = 63)

Mean age (SD) in years Minimum Maximum 52.4 (13.6) 18.0 84.0 53.1 (17.1) 21.0 88.0 Sex, n (%) Women 39 (61.9) 29 (46.0) Race/ ethnicity, n (%) White Black/ African-American Asian Multiracial Other 55 (87.3) 1 (1.6) 2 (3.2) 3 (4.8) 2 (3.2) 50 (79.4) 2 (3.2) 3 (4.8) 3 (4.8) 3 (4.8) Marital status, n (%)

Married, living with partner Single, never married Separated/ divorced Widowed 54 (84.4) 6 (9.4) 3 (4.7) 0 (0) 43 (68.2) 10 (15.9) 3 (4.8) 5 (7.9) Education, n (%)

Less than high school (< 12 years) Completed high school (12 years) Some college (< 16 years) Completed college (16 years)

Graduate/ professional degree (>16 years)

2 (3.2) 8 (12.7) 15 (23.8) 17 (27) 21 (33.3) 2 (3.2) 10 (15.9) 15 (23.8) 24 (38.1) 10 (15.9) Employment (last 12 months)

Full-time

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Homemaker

School full- or part time Unemployed Retired Other 4 (6.3) 2 (3.2) 1 (1.6) 9 (14.3) 5 (7.9) 3 (4.8) 2 (3.2) 2 (3.2) 17 (27) 3 (4.8) Diagnosis, n (%) Stroke Tumor TBI Other 24 (38.1) 13 (20.6) 9 (14.3) 17 (27) Intubation, n (%) Yes 51 (81) Resiliency factors Mindfulness Coping Social support Self-efficacy QoL factors Physical QoL Psychological QoL Social QoL Environmental QoL M (SD) 33.794 (5.1) 31.952 (8.8) 38.635 (7.6) 1245.777 (239.0) 13.342 (1.6) 14.381 (1.9) 16.254 (2.7) 16.929 (2.4) M (SD) 34.140 (5.6) 32.053 (9.2) 40.127 (10.8) 33.050 (5.4) 12.630 (2.1) 13.839 (2.3) 15.655 (3.3) 16.181 (2.9)

* Missing values: age = 4 (6.3%), sex = 2 (3.2%), race/ethnicity = 2 (3.2%), marital status = 2 (3.2%), education = 2 (3.2%), employment = 2 (3.2%), QoL domains: 5

Abbreviations: SD: standard deviation, TBI: traumatic brain injury

Relations between caregivers’ own resilience factors and Quality of Life

Tables 3-6 show the results of the hierarchical regressions performed to test the main hypothesis; that at least one of the resiliency factors of caregivers is significantly related to the four caregiver QoL

domains, after accounting for the control variables. Four separate hierarchical regressions were performed for the four dependent variables (physical, psychological, social and environmental QoL of caregivers). In the first step of the model, caregiver demographics were entered, which did not illustrate a significant relationship with physical QoL (R2 _{= .090, F (6,56) = .926, p > .05), psychological QoL (R}2 _{= .137, F (6, 56) =1.483,}

p > .05), social QoL (R2 _{=.137, F (6 ,56) = 1.485, p > .05) and environmental QoL (R}2 _{= .117, F (6, 56) =} 1.234, p > .05). In Step 2 patient factors (intubation and diagnosis) were entered in the analysis to test their

association with caregivers’ QoL, but the model stayed insignificant concerning physical QoL (R2 = .133, F (8, 54) = 1.034, p > .05), psychological QoL (R2 = .159, F (8, 54) = 1.273, p > .05), social QoL (R2 = .184, F (8,

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54) = 1.518, p > .05) and environmental QoL (R2 _{= .129, F (8, 54) = .995, p > .05). It can be seen that the} control variables are not of significant predictive value for QoL. This means that, overall; any increase in the independent variables was not related to any increase or decrease in the control variables, and vice versa.

Regarding physical QoL, in Step 3, resiliency skills of caregivers were entered and these variables accounted for a significant amount of variance in physical QoL of caregivers: R2 = .486, F (12, 50) = 3.941, p < .001, after accounting for caregivers’ demographics and patient factors. The ∆R2 was .353 (p < .001), which means the addition of caregiver resiliency factors accounted for 35,3% more of the variance in physical QoL. The analysis showed that only mindfulness did significantly predict physical QoL of caregivers (β = .405, p

< .05) (Table 3).

Table 3. Results of the hierarchical regression analysis (dependent: caregiver physical health QoL; independent: caregiver resiliency skills).

B (SE) β p R2 Predictors Step 1 Constant Age Sex Race/ethnicity Marital status Education Employment 11.690 (1.547) .005 (.018) .836 (.448) .133 (.25) .258 (.36) .023 (.188) -.004 (.008) .037 .247 .075 .094 .016 -.064 .000 .798 .067 .597 .476 .903 .637 .090 Step 2 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation 12.316 (1.587) -.006 .947 (.451) .208 (.254) .286 (.359) .118 (.197) -.004 (.008) -.061 (.096) -.774 (.609) -.052 .280 .118 .104 .082 -.072 -.087 -.185 .000 .737 .040 .417 .429 .550 .592 .526 .209 .133 Step 3 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation Caregiver coping Caregiver mindfulness Caregiver self-efficacy Caregiver social support

5.614 (2.484) .011 (.016) .594 (.378) .241 (.204) -.161 (.317) .021 (.167) -.003 (.007) -.045 (.077) -.597 (.501) .041 (.036) .131 (.056) .001 (.001) -.015 (.025) .093 .176 .137 -.059 .015 -.055 -.064 -.143 .217 .405 .130 .-070 .028 .479 .123 .243 .614 .901 .613 .562 .239 .265 .022 .266 .544 .486

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For caregivers’ psychological QoL, when adding resiliency skills in Step 3, the model significantly improved (R2 _{= .694, F (12, 50) = 9.459, p < .001), after accounting for caregivers’ demographics and patient} factors. With a ∆R2 _{of .536 (p < .001), 53,6% of the variance can be explained by the added predictors in step} 3. More specifically, the analysis showed that mindfulness did significantly predict value of psychological QoL of caregivers (

β

= .487, p < .01), as well as did coping (

β

= .323, p < .05) (Table 4).

Table 4. Results of the hierarchical regression analysis (dependent: caregiver psychological QoL; independent: caregiver resiliency skills).

B (SE) β p R2 Predictors Step 1 Constant Age Sex Race/ethnicity Marital status Education Employment 15.544 (1.773) .013 (.020) .399 (.514) -.587 (.286) .512 (.413) .331 (.215) .005 (.010) .090 .100 -.283 .159 .195 .073 .000 .528 .440 .045 .220 .120 .578 .137 Step 2 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation 16.019 (1.840) .006 (.022) .476 (.523) -.559 (.294) .531 (.416) .413 (.229) .005 (.010) .035 (.111) -.831 (.706) .041 .120 -.270 .165 .244 .070 .043 -.169 .000 .788 .367 .063 .207 .076 .597 .752 .245 .159 Step 3 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation Caregiver coping Caregiver mindfulness Caregiver self-efficacy Caregiver social support

6.214 (2.255) .033 (.014) -.098 (.343) -.532 (.185) -.091 (.288) .258 (.151) .007 (.006) .064 (.070) -.455 (.454) .072 (.033) .185 (.051) .001 (.001) -.004 (.023) .233 -.025 -.257 -.028 .152 .092 .078 -.092 .323 .487 .068 -.014 .008 .024 .777 .006 .752 .094 .277 .361 .322 .034 .001 .446 .874 .694

For social QoL as the dependent variable, in Step 3 of the analysis, resiliency skills were added and these variables were a significant predictor for social QoL of caregivers: R2 _{= .621, F (12, 50) = 6.840, p} < .001. The ∆R2 _{was .438 (p < .001), so 43.8% of the variance in social QoL can be explained by adding the}

18

resiliency factors of the caregivers. The analysis showed that coping (

β

= .432, p < .05) and self-efficacy (β

= .418, p < .05) significantly predicted social QoL of caregivers (Table 5).

Table 5. Results of the hierarchical regression analysis (dependent: caregiver social QoL; independent: caregiver resiliency skills).

B (SE) β p R2 Predictors Step 1 Constant Age Sex Race/ethnicity Marital status Education Employment 20.532 (2.464) .027 (.028) .225 (.714) -.963 (.398) .770 (.574) -.300 (.299) -.004 (.013) .134 .041 -.334 .172 -.127 -.041 .000 .345 .754 .019 .185 .320 .753 .137 Step 2 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation 21.589 (2.519) .010 (.030) .401 (.716) -.877 (.403) .813 (.569) -.124 (.313) -.005 (.013) .012 (.152) -1.651 (.967) .051 .073 -.305 .181 -.053 -.048 .011 -.241 .000 .733 .577 .034 .159 .693 .714 .936 .093 .184 Step 3 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation Caregiver coping Caregiver mindfulness Caregiver self-efficacy Caregiver social support

5.589 (3.487) .058 (.022) -.616 (.531) -.770 (.286) -.155 (.445) .003 (.234) -.010 (.009) .074 (.108) -1.301 (.703) .133 (.051) .022 (.078) .005 (.001) .068 (.035) .292 -.111 -.268 -.035 .001 -.102 .064 -.190 .432 .041 .418 .189 .115 .012 .251 .010 .729 .990 .276 .498 .070 .012 .783 .000 .061 .621

In the fourth analysis, in Step 3, resiliency skills were added and these variables were a significant predictor for environmental QoL of caregivers: R2 _{= .493, F (12, 50) = 4.047, p < .01. ΔR}2 _{was .364 (p} < .001), so 36.4% of the variance in environmental QoL can be explained by the added predictors in Step 3. The analysis showed that only self-efficacy significantly predicted values of environmental QoL of caregivers (

β

= .409, p < .01) (Table 6).

19

Table 6. Results of the hierarchical regression analysis (dependent: caregiver environmental QoL; independent: caregiver resiliency skills).

B (SE) β p R2 Predictors Step 1 Constant Age Sex Race/ethnicity Marital status Education Employment 17.791 (2.191) .038 (.025) .194 (.635) -.676 (.354) .521 (.510) .222 (.266) -.006 (.012) .215 .040 -.267 .132 .107 -.069 .000 .137 .762 .061 .312 .406 .603 .117 Step 2 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation 17.942 (2.287) .037 (.027) .209 (.650) -.699 (.366) .525 (.517) .260 (.284) -.006 (.012) .102 (.138) -.536 (.878) .211 .043 -.277 .133 .126 -.068 .101 -.089 .000 .178 .749 .061 .314 .363 .614 .463 .544 .129 Step 3 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation Caregiver coping Caregiver mindfulness Caregiver self-efficacy Caregiver social support

6.833 (3.546) .069 (.023) -.417 (.540) -.593 (.291) -.308 (.453) .292 (.238) -.009 (.010) .137 (.110) -.412 (.715) .091 (.052) .054 (.079) .004 (.001) -.005 (.036) .398 -.086 -.234 -.078 .141 -.099 .136 -.069 .337 .115 .409 -.015 .060 .003 .444 .047 .500 .226 .363 .218 .567 .085 .502 .001 .894 .493

The main hypothesis predicted that at least one of the resiliency skills of caregivers was related to their own physical, psychological, social and environmental QoL, after accounting for control variables. Reviewing the results, all QoL domains were significantly related with at least one of the resiliency skills of caregivers, above-and-beyond caregiver demographics and patient factors and therefore, the main hypothesis can be accepted. This analysis showed that, for caregivers, mindfulness was significantly of predictive value for physical QoL and psychological QoL. Coping was of significant value for predicting psychological and social QoL and self-efficacy was effective regarding social and environmental QoL. Only social support was not of predictive value for either one of the QoL domains.

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Relations between patients’ resiliency and caregivers’ QoL

To test the second hypothesis, that patients’ resiliency skills are of predictive value for caregivers’ QoL, after controlling for patient demographics and intubation and diagnosis, none of the four tested resiliency skills of patients were of significant predictive value for either one of the QoL domains of caregivers. This hypothesis can therefore not be accepted (Tables 7-10, Appendix).

DISCUSSION

As admission to a Neuro-ICU can produce significant turmoil in the lives of both patients and their primary caregivers, the objective of this study was to assess whether resiliency skills are positively related to caregivers’ QoL, so to hold implication for psychosocial interventions targeting resiliency among this vulnerable population. The results of this study provide the first evidence that improving caregivers’ own mindfulness, self-efficacy and coping skills could increase their QoL following hospitalization of their loved one. Compared to other resiliency skills, self-efficacy, social support and coping, mindfulness was of more predictive value for caregivers’ QoL, which could be of worth when designing interventions to target caregiver QoL. However, this early in the recovery process, there was no cross-over of patients’ own psychosocial resiliency factors relating to one’s caregiver’s QoL. Findings reinforce the importance of addressing resiliency intervention programs specifically to caregivers of patients with acute neurological illnesses recently after hospital admission.

Findings specify that caregivers’ mindfulness, coping and self-efficacy were of predictive value for caregivers’ QoL. These results are consistent with prior research done in other medical populations: brief psychological interventions such as mindfulness-based programs that teach resiliency have been found to improve QoL in patients with cancer or HIV and their caregivers (Antoni et al., 2006; Jensen et al., 2013; Ristevska-Dimitrovska et al., 2015; Manne et al., 2015). Unexpectedly, we didn’t find any significant relation between social support and caregivers’ QoL. Previous studies indicate that seeking social support is associated with overall better mental health for both patients and caregivers (Shaffer, Riklin, Stagl, Rosand & Vranceanu, 2016), but this does not seem to account for QoL in dyads shortly after Neuro-ICU admission. Although not

21

tested in this study, it may be that social support becomes more important as the recovery process continues, and this should be examined in future research.

Patients’ resiliency skills were not interrelated with caregivers’ QoL. Previous studies showed that patients and caregivers adjust together to medical illness and that psychosocial resilience after illness is significantly interrelated within patient-caregiver dyads (Berg & Upchurch, 2007; Hodges, Humphris & MacFarlane, 2005), but it could be that this does not account for dyads within two weeks after admission in the Neuro-ICU. Indeed, these results are comparable with a previous study conducted in a Neuro-ICU recently after patient admission, which indicated that patients’ resiliency skills were not associated with their caregivers’ mental health and emotions and vice versa (Shaffer et al., 2016). It may be that patients’ resiliency skills become more interrelated with caregivers’ QoL as time passes, which would be critical to investigate in a long-term study in which dyads are followed-up with weeks or months after hospital discharge. Since, within two weeks of hospital admission, only one’s own resiliency skills are significantly related to caregivers’ QoL, these findings suggest the importance of developing intervention programs targeting resiliency skills

particularly for caregivers of ICU patients. Attention to patients’ QoL has become a standard of clinical care for many illnesses, though this study indicates that assessing caregivers’ QoL as well should be a priority during hospitalization, given that these persons contribute heavily to the patients’ recovery.

Limitations and Future Directions

Data were cross-sectional and because of that, causality cannot be ascertained. Besides that, directionality cannot be confirmed from these analyses. It’s impossible to conclude that some participants have a high QoL because of their high resiliency skills; as it could also be accurate that positive QoL is influenced by other variables for which we can’t account. An additional restriction may be a possible risk of selection bias regarding our results on determinants of caregivers’ QoL, because we did not include ‘sicker’ patients, who were not able to speak due to intubation or other medical conditions, which could be relevant to the outcomes of interest. Consequently, we have to interpret the findings of this study with discretion.

22

Another limitation is that all dyads come from only one Neuro-ICU at a single, urban US hospital, which is located in an area with a relatively high socioeconomic status. QoL outcomes may differ widely depending on the local environment (Hwang et al., 2014) and previous literature indicates that in stroke survivor-caregiver dyads, better QoL was reported in urban areas than those living in rural areas (Savini et al., 2014).

In addition, since we enrolled patients and caregivers whilst they were in the Neuro-ICU, it could be possible that QoL and resiliency factors are likely to show stronger correlations as time since hospitalization progresses (Hodges, Humphris & Macfarlane, 2005). Particularly in the very early stages of care giving, negative effects may not occur and QoL is therefore not (yet) effected (Schulz & Sherwood, 2008). It could be that care giving at this early stage has positive effects on the QoL of caregivers regardless of their resiliency skills; the taking care makes caregivers possibly feel good about themselves and it gives meaning to their lives. Recent findings suggest that supporting or helping others may just be as beneficial to health as receiving care (Schulz & Sherwood, 2008).

Also, no information on the caregivers’ previous QoL before the hospitalization of their loved one has been collected. Other literature with stroke survivor-caregiver dyads suggests that QoL is influenced by the pre-existing situation, characteristics of individuals as well as the characteristics of their relationship, prior to hospitalization (Savini et al., 2014). We therefore cannot examine the difference between QoL factors of the caregivers before the admission of their patient to the Neuro-ICU.

An additional factor that can influence caregivers’ QoL is the time point of this research, since literature has shown that decreased QoL in caregivers, especially psychological QoL, is associated with the number of hours spent in care giving, but since this study has been conducted in the hospital where nurses primarily take care of a patient, caregivers’ strain might not be comparable to their strain months after discharge. Their QoL may decrease significantly over the next few weeks because their increased hours of care giving results in lower participation in social activities, as well as increased irritation and depression symptoms (Lurbe-Puerto, Leandro & Baumann, 2012). This study did not use a longitudinal design, which could be a factor why these findings differ from other studies with comparable populations. This study was

23

conducted in hospital settings shortly after a patient has been admitted to the Neuro-ICU, hence these results cannot be generalized to the situations after discharge or the rehabilitation phases. Finally, this study relies on self-report, which is found to be prone to response bias and dishonest reporting (van den Born-Van Zanten, Vink, Dongelmans, Dettling-Ihnenfeldt & van der Schaaf, 2016).

Implications and Conclusions

Up until now, the QoL of close family members and friends of ICU patients is rarely acknowledged, despite their great contribution to the patients’ recovery process. Research in Neuro-ICU caregivers recently after hospital admission is particularly scarce and this is one of the first studies to explore possible

mechanisms by which resilience may impact QoL among Neuro-ICU caregivers. This study advances our understanding of how resilient caregivers handle, through mindfulness, self-efficacy and coping, severe stressors, such as a loved one being hospitalized because of an acute neurological illness.

In conclusion, caregiver psychosocial interventions designed to enhance caregivers’ resiliency through mindfulness, self-efficacy or coping training may prove an effective way to prevent low QoL outcomes in ICU caregivers. Within 2 weeks of hospital admission, resiliency has its clear role in QoL and upcoming studies should track long-term associations between patient and caregiver resiliency skills and QoL and should test the extent to which resiliency skills successfully attenuate the burden of the Neuro-ICU experience. Understanding how psychosocial resiliency factors can attribute to long-term improved QoL in caregivers will be fundamental in building targeted interventions effective in preventing poor health outcomes of caregivers of ICU patients.

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APPENDIX

Tables

Table 7. Results of the hierarchical regression analysis (dependent: caregiver physical QoL; independent: patient resiliency skills; control variables: patient demographics and patient factors).

B (SE) β p R2 Predictors Step 1 Constant Age Sex Race/ethnicity Marital status Education Employment 13.388 (1.231) .012 (.017) -1.110 (.486) -.084 (.183) .038 (.287) .163 (.231) -.008 (.011) .119 -.321 -.067 .021 .098 -.105 .000 .475 .027 .649 .896 .483 .456 .140 Step 2 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation 14.275 (1.476) .011 (.017) -1.207 (.499) -.089 (.187) -.073 (.304) .178 (.236) -.006 (.012) .019 (.114) -.872 (.732) .107 -.349 -.071 -.042 .107 -.085 .026 -.189 .000 .524 .020 .636 .811 .455 .576 .869 .240 .167 Step 3 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation Patient coping Patient mindfulness Patient self-efficacy Patient social support

9.949 (2.357) -.001 (.019) -1.373 (.546) .030 (.194) -.124 (.320) .328 (.258) -.003 (.012) -.016 (.124) -1.419 (.851) -.036 (.040) .100 (.058) .053 (.059) .013 (.027) -.006 -.397 .024 -.071 .197 -.037 -.023 -.308 -.191 .322 .154 .082 .000 .976 .016 .876 .700 .211 .815 .896 .103 .374 .093 .372 .625 .273

Table 8. Results of the hierarchical regression analysis (dependent: caregiver psychological QoL; independent: patient resiliency skills; control variables: patient demographics and patient factors).

B (SE) β p R2 Predictors Step 1 Constant Age Sex Race/ethnicity Marital status Education Employment 13.994 (1.426) .008 (.019) -.506 (.563) -.175 (.212) .224 (.332) .326 (.268) .012 (.012) .068 -.130 -.124 .113 .174 .142 .000 .691 .373 .412 .503 .230 .330 .097 Step 2 Constant 14.438 (1.730) .000 .104

30

Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation .007 (.020) -.568 (.585) -.174 (.219) .158 (.357) .329 (.277) .013 (.014) .026 (.133) -.505 (.858) .064 -.146 -.123 .080 .175 .146 .032 -.097 .713 .336 .431 .660 .241 .356 .844 .559 Step 3 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation Patient coping Patient mindfulness Patient self-efficacy Patient social support

11.399 (2.851) .001 (.023) -.962 (.661) -.078 (.235) .002 (.387) .383 (.312) .012 (.015) .058 (.150) -1.017 (1.030) -.034 (.049) .006 (.070) .105 (.072) .019 (.032) .010 -.246 -.055 .001 .204 .138 .071 -.196 -.158 .017 .268 .108 .000 .961 .153 .741 .996 .227 .422 .702 .329 .491 .933 .149 .550 .167

Table 9. Results of the hierarchical regression analysis (dependent: caregiver social QoL; independent: patient resiliency skills; control variables: patient demographics and patient factors).

B (SE) β p R2 Predictors Step 1 Constant Age Sex Race/ethnicity Marital status Education Employment 17.890 (2.074) .015 (.028) -.414 (.819) -.453 (.308) .447 (.483) -.082 (.390) .003 (.018) .090 -.073 -.220 .155 -.030 .020 .000 .598 .616 .148 .360 .835 .890 .090 Step 2 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation 19.991 (2.453) .012 (.028) -.610 (.829) -.475 (.310) .210 (.506) -.036 (.392) .007 (019) .003 (.189) -1.893 (1.216) .070 -.108 -.231 .073 -.013 .059 .070 .002 .000 .681 .466 .132 .679 .927 .701 .989 .127 .142

31

Step 3 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation Patient coping Patient mindfulness Patient self-efficacy Patient social support

16.707 (3.965) .032 (.032) -.560 (.919) -.527 (.326) .095 (.539) -.215 (.434) .000 (.020) .092 (.208) -2.666 (1.432) .083 (.068) .024 (.098) -.068 (.100) .055 (.045) .192 -.099 -.256 .033 -.079 -.003 .078 -.353 .268 .048 -.119 .212 .000 .329 .546 .114 .860 .622 .987 .662 .070 .227 .806 .499 .222 .234

Table 10. Results of the hierarchical regression analysis (dependent: caregiver enivronmental QoL; independent: patient resiliency skills; control variables: patient demographics and patient factors).

B (SE) β p R2 Predictors Step 1 Constant Age Sex Race/ethnicity Marital status Education Employment 16.999 (1.776) -.004 (.024) -.514 (.702) -.110 (.264) .357 (.414) .267 (.334) .002 (.016) -.028 -.108 -.064 .148 .117 .019 .000 .872 .467 .680 .393 .428 .900 .052 Step 2 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation 17.461 (2.151) -.004 (.025) -.619 (.727) -.096 (.272) .257 (.444) .257 (.344) .001 (.017) .077 (.166) -.729 (1.067) -.027 -.130 -.056 .106 .112 .010 .078 -.115 .000 .879 .400 .725 .565 .459 .952 .644 .498 .063 Step 3 Constant Age Sex Race/ethnicity Marital status Education Employment Patient diagnosis Patient intubation Patient coping Patient mindfulness Patient self-efficacy Patient social support

11.855 (3.479) -.002 (.028) -.912 (.806) -.013 (.286) .095 (.473) .246 (.381) -.003 (.018) .127 (.183) -1.485 (1.257) .008 (.059) .039 (.086) .088 (.087) .034 (.039) -.017 -.192 -.007 .039 .108 -.028 .129 -.235 .031 .092 .184 .157 .001 .935 .265 .964 .841 .523 .868 .490 .244 .894 .651 .319 .386 .162