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. Author manuscript; available in PMC: 2023 Apr 1.
Published in final edited form as: Health Psychol. 2021 Sep 9;41(4):268–277. doi: 10.1037/hea0001102

Emotional distress in Neuro-ICU survivor-caregiver dyads: The Recovering Together randomized clinical trial

Sarah M Bannon 1, Talea Cornelius 2, Melissa V Gates 1, Ethan Lester 1, Ryan A Mace 1, Paula Popok 1, Eric A Macklin 3, Jonathan Rosand 4,5, Ana-Maria Vranceanu 1
PMCID: PMC8904645  NIHMSID: NIHMS1738276  PMID: 34498896

Abstract

Objective:

Emotional distress is common in both survivors and their informal caregivers following admission to a Neuroscience Intensive Care unit (Neuro-ICU) and can negatively affect their individual recovery and quality of life. Neuro-ICU survivor-caregiver dyads can influence each other’s emotional distress over time, but whether such influence emerges during dyadic treatment remains unknown. The present study involved secondary data analysis of Neuro-ICU dyads enrolled in a randomized clinical trial of a dyadic resiliency intervention, Recovering Together (RT), versus a health education attention placebo control to test dyadic similarities in emotional distress before and after treatment.

Methods:

Data were collected from 58 dyads following Neuro-ICU admission. Emotional distress (depression, anxiety, and post-traumatic stress) was assessed at baseline, 6 weeks (post-intervention), and 12 weeks later. Nonindependence within survivor-caregiver dyads was examined (i.e., correlations between cross-sectional symptoms and changes in symptoms over time); mutual influence of emotional functioning over time (i.e., “partner effects”) was examined using cross-lagged path analyses.

Results:

There were strong, positive cross-sectional correlations between survivor and caregiver distress at post-intervention and follow-up, and between changes in survivor and caregiver distress from baseline to post-intervention and post-intervention to follow-up. There were no partner effects.

Conclusions:

Neuro-ICU survivors and their informal caregivers show similar changes in emotional distress after treatment. These findings highlight the potential benefits of intervening on both survivor and caregiver distress following Neuro-ICU admission.

Keywords: Dyads, Depression, Anxiety, Post traumatic Stress, Intervention

Admission to a Neuroscience Intensive Care unit (Neuro-ICU) is a life altering event for both survivors and their informal caregivers (i.e., a partner, relative, or friend who provides unpaid assistance to an adult with a chronic health condition) (National Alliance for Caregiving., 2015). Although some survivors and caregivers are resilient when navigating the acute neurological injury (ANI) and hospitalization, approximately 20–50% develop emotional distress (e.g., depression, anxiety, and post-traumatic stress [PTS]). Addressing early emotional distress is critical because it tends to become chronic (Bannon et al., 2020; LaBuzetta et al., 2019; Shaffer et al., 2016; Vranceanu, 2019; 2020) and can negatively influence subsequent survivor and caregiver morbidity, mortality, and quality of life (Beach et al., 2005; Ji et al., 2012; Lee et al., 2003; Presciutti et al., 2020; Schulz & Beach, 1999; Turner-Stokes & Hassan, 2002).

After major medical events, there is robust evidence that patterns of emotional distress are correlated between dyads (i.e., pairs) of survivors and their informal caregivers (Badr et al., 2019; Cook & Kenny, 2005; Kershaw et al., 2015; Cook & Kenny, 2005). Several theoretical models (e.g., interdependence theory; dyadic coping and illness management theories; family resilience models) acknowledge the dyadic relationship as a care-partnership across the illness continuum (Falconier & Kuhn, 2019; Lange & Rusbult, 2012; Lyons & Lee, 2018; Patterson, 2002). These models suggest that survivors and caregivers influence one anothers’ emotional distress though their shared experience of medical events, mutual influence in their appraisal of the illness through daily interactions, mutual participation in medical decision-making and care-tasks (e.g., symptom management, medication adherence), and experience of relationship changes (e.g., decreased intimacy, conflict and strain) that can increase emotional distress for both dyad members (Badr et al., 2019). In fact, there is robust evidence for non-independence of mental and physical health outcomes within survivor-caregiver dyads across a wide range of health conditions (Chung et al., 2009; Hoeffding et al., 2017; Jacobs et al., 2017; Kershaw et al., 2015; Lin et al., 2020), including Neuro-ICU dyads after discharge (Meyers et al., 2020a; 2020b; 2020c; Shaffer et al., 2016)

Shared patterns of emotional distress within dyads (i.e., non-independence) can be examined in multiple ways, including: (1) correlated symptoms (i.e., cross-sectional similarities in survivor-caregiver dyads), (2) correlated changes in symptoms, and (3) interdependence, or mutual influence of one anothers’ emotional functioning over time (i.e., “partner effects,” or how survivor level of distress at one time point influences caregiver level of distress at a future time point and vice versa) (Cook & Kenny, 2005). Longitudinal observational studies of Neuro-ICU dyads indicate non-independence in emotional distress between survivors and caregivers from hospitalization through 6 months post-discharge. For example, symptoms of depression, anxiety and PTS are correlated within survivor-caregiver dyads during hospitalization (Shaffer et al., 2016) as well as 3- and 6-months post-discharge (Meyers et al., 2020a; 2020b; 2020c). In addition, partners’ PTS at 3 months post-discharge was associated with one’s own PTS at 6 months post-discharge (i.e., “partner effects” or interdependence) (Meyers et al., 2020c).

Dyadic psychosocial interventions that address survivors and their informal caregivers needs simultaneously may enhance survivor, caregiver, and dyadic relationship factors that impact illness outcomes (Badr et al., 2019) and are increasingly common (Shaffer et al., 2020). Some studies have examined non-independence to understand whether dyads respond similarly to psychosocial interventions. For example, dyads’ weight loss trajectories are non-independent, such that partners change in similar ways during the course of weight-loss interventions (Cornelius et al., 2016). While these findings highlight the potential for dyads to change together during psychosocial interventions, no prior studies have examined similarities and partner influence in outcomes following psychosocial interventions for Neuro-ICU survivor-caregiver dyads. Given that observational longitudinal research indicates non-independence of emotional distress between Neuro-ICU dyads’ levels over time, it is important to explore these relationships in the context of psychosocial interventions. Findings can help identify whether dyads who receive treatment together also change together, and whether one member of the dyad can influence resiliency for one or both dyad members over time.

Recovering Together (RT), a dyadic intervention that accounts for the non-independence of survivors and caregivers by engaging them together in resiliency and interpersonal communication skills, was iteratively developed with the goal of preventing chronic emotional distress in both dyad members (Bannon et al., 2020; McCurley et al., 2019; Meyers et al., 2020d). In a single-blind, pilot randomized clinical trial (RCT), we found that participation in RT was associated with clinically and statistically significant improvement in depression, anxiety and PTS beyond an attention placebo control matched for dose and time for both survivors and caregivers (Vranceanu et al., 2020).

Consistent with prior studies that examine dyadic dynamics in the context of dyadic RCTs (Badr et al., 2019; Ellis et al., 2017; Song et al., 2016), the present study investigated whether Neuro-ICU survivor-caregiver dyads who participated in the Recovering Together pilot RCT (Vranceanu et al., 2020) exhibited non-independence in their emotional distress outcomes. Of note, the primary RCT outcomes concerned survivor and caregiver outcomes independently, without accounting for dyadic effects. The present study, presents a novel statistical examination of dyadic effects that coupld contribute to the outcomes observed for survivors and caregivers, and had the goal of informing a more fine-grained analysis of dyadic effects in a subsequent fully-powered RCT. The study hypothesized that survivor and caregivers would exhibit non-independence as evidenced by: (1) correlated cross-sectional emotional distress symptoms, (2) correlated changes in symptoms, and (3) interdependence (i.e., “partner effects,” or mutual influence). It was additionally expected that each dyad member’s own distress at a previous timepoint would be positively associated with their own subsequent levels of emotional distress (i.e., “actor effects”).

Method

The present study involved secondary data analysis of the Recovering Together (RT) RCT (ClinicalTrials.gov Identifier: NCT03694678) (Vranceanu et al., 2020). Trial procedures including study design, recruitment and randomization procedures, and descriptions of the intervention and control conditions have been previously reported elsewhere (Vranceanu et al., 2020). The study was approved by the Massachusetts General Hospitaal Institutional Review Board.

Participants

Participants were 58 dyads of Neuro-ICU admitted survivors and their informal caregivers enrolled in the RT RCT. Participants were recruited through direct referrals from the nursing team in the MGH Neuro-ICU between January 2019 and December 2019. The nursing team served as a liaison between dyads and the research team as they introduced the study to potentially eligible dyads and connected them to the research team. Then, the research team met with dyads at their bedside and described the study with recruitment materials (including a recruitment video of two dyads who successfully completed a prior feasibility study). Eligible dyads included survivors: (1) aged 18 or older, (2) cleared for participation by the medical team (i.e., intact medical decision-making, medical condition not expected to deteriorate), (3) cognitively intact based on a Mini Mental Staus Exam score >26, (4) had a caregiver willing to participate, (5) had access to an internet-enabled device (e.g., smartphones, tablets, computers), (6) were willing to participate in 2 in-person and 4 live-video sessions together, and (7) English speaking. Additional inclusion criteria for dyads was endorsement of clinically significant emotional distress by either survivor or caregiver (depression, anxiety, or PTS; HADS-D or HADS-A >=7; PTS per DSM-V criteria) (Vranceanu et al., 2020).

Demographic information has been previously published (Vranceanu et al., 2020). Briefly, survivors were 36% female (n = 21), had an average age of 49.7 years (SD = 16.4), and a majority completed a graduate or professional degree (35%). Informal caregivers were predominantly female (67%, n = 39), and had an average age of 52.3 years (SD=14.5). Informal caregivers were most frequently spouses/partners (79%, n = 46), followed by parents (12%, n = 7) and siblings (3%, n = 2). Emotional distress in survivors and caregivers at each time point is presented in Table 1. Program acceptability was excellent with 86% (n = 50) of dyads completing 4 out of 6 sessions. Full information on feasibility outcomes, including feasibility of randomization and data collection, was reported in Vranceanu et al. (2020). A total of 58 dyads (29 dyads/condition) were enrolled in the study. Twenty-five survivors and 28 caregivers in the RT condition and 19 survivors and 25 caregivers in the health education control condition completed measures at all time points.

Table 1.

Survivor and caregiver characteristics of emotional distress across time points.

Baseline Post-Intervention 3-month Follow-up
Survivor Outcome
n, M(SD), Range n, M(SD), Range n, M(SD), Range
Depression (HADS)
RT 29, 8.7 (4.2), 2.0–16.0 27, 4.0 (4.1), 0–16.0 26, 3.7 (3.3), 0–11.0
CONTROL 29, 7.1 (4.0), 1.0–18.0 25, 7.2 (3.7), 0–14.0 23, 7.7 (5.0), 0–16.0
OVERALL 58, 7.9 (4.1), 1.0–18.0 52, 5.6 (5.6), 0–16.0 49, 5.7 (4.2), 0–16.0
Anxiety (HADS)
RT 29, 11.1 (4.7), 3.0–20.0 27, 3.3 (4.1), 0–19.0 26, 4.7 (4.8), 0–17.0
CONTROL 29, 6.3 (4.0), 0–17.0 26, 8.5 (5.2), 0–20.0 23, 8.9 (6.0), 0–21.0
OVERALL 58, 8.7 (5.0), 0.0–20.0 53, 5.9 (4.7), 0–20.0 49, 6.8 (5.4), 0–21.0
Post-traumatic Stress (PCL-C)
RT 29, 41.6 (12.9), 18.0–64.0 27, 26.4 (10.8), 17.0–66.0 26, 28.2 (10.1), 17.0–52.0
CONTROL 29, 29.3 (12.1), 18.0–63.0 26, 34.6 (12.1), 17.0–58.0 23, 41.7 (16.0), 17.0–70.0
OVERALL 58, 35.4 (13.9), 18.0–64.0 53, 30.5 (11.5), 17.0–66.0 49. 35.0 (13.1), 17.0–70.0
Baseline Post-Intervention 3-month Follow-up
Caregiver Outcome
n, M(SD), Range n, M(SD), Range n, M(SD), Range
Depression (HADS)
RT 29, 7.8 (2.7), 3.0–15.0 29, 3.3 (3.4), 0–12.0 26, 2.4 (2.6), 0–11.0
CONTROL 29, 4.8 (3.8), 0–12.0 29, 6.1 (5.4), 0–16.0 26, 7.3 (5.3), 0–21.0
OVERALL 58, 6.3 (3.6), 0–15.0 58, 4.7 (4.4), 0–16.0 52, 4.9 (4.0), 0–21.0
Anxiety (HADS)
RT 29, 13.2 (3.9), 4.0–20.0 29, 6.0 (3.8) 0–16.0 26, 5.3 (3.8), 0–16.0
CONTROL 29, 7.0 (4.7), 0–17.0 29, 8.1 (6.1), 0–21.0 26, 9.6 (5.0), 0–17.0
OVERALL 58, 10.1 (5.3), 0–20.0 58, 7.1 (5.0), 0–21.0 52, 7.5 (4.4), 0–17.0
Post-traumatic Stress (PCL-C)
RT 29, 43.2 (10.7), 26.0–61.0 29, 30.3 (9.8), 24.0–65.0 26, 27.3 (7.7), 17.0–47.0
CONTROL 29, 29.4 (12.0), 17.0–62.0 29, 35.9 (16.6), 17.0–77.0 26, 37.7 (16.1), 17.0–67.0
OVERALL 58, 36.3 (11.4), 17.0–62.0 58, 33.1 (13.2), 17.0–77.0 52, 32.5 (11.9), 17.0–67.0
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Overview of Treatment Randomization and Intervention Conditions

Dyads were randomly assigned to one of two intervention conditions using a computer-generated randomization sequence (permuted blocks of size 2 and 4 and 1:1 allocation; 29 dyads in each condition). Treatment assignments were implemented using the REDCap (Harris et al., 2009) data collection platform. All study team members (besides the study statistician) were blind to the allocation algorithm. Both the RT and control conditions entailed two in-person dyadic visits in the Neuro-ICU at bedside, and four dyadic virtual visits after discharge to rehab or home. RT and control conditions are described below briefly and more details on session content has been previously reported (Vranceanu et al., 2020).

The Recovering Together (RT) intervention condition (Bannon et al., 2020; McCurley et al., 2019; Meyers et al., 2020a; Vranceanu et al., 2020) is a 6-session skills-based dyadic intervention that targets the prevention of chronic emotional distress for survivor-caaregiver dyads. RT is informed by prominent dyadic theoretical models of adaptation to stress, including the dyadic longitudinal model and dyadic coping models of illness management, as well as individual, dyadic, and family resiliency frameworks (Falconier & Kuhn, 2019; Lyons & Lee, 2018; Patterson, 2002). RT draws content from several evidence-based therapies (e.g., cognitive behavioral therapy, dialectical behavioral therapy, trauma-informed therapies) and includes training in skills linked to resiliency after significant adversity and trauma (e.g., mindfulness, dialectics, cognitive restructuring, interpersonal effectiveness) to address the stressors experienced by both dyad members during and after hospitalization (Bannon et al., 2020; McCurley et al., 2019; Meyers et al., 2020a; Vranceanu et al., 2020). The first 2 sessions of RT are delivered to all dyads at bedside, and include skills for distress tolerance such as mindfulness, dialectics, diaphragmatic breathing, and self-care. The following 4 sessions are delivered over live video after discharge and tailored to the dyads’ unique stressors and needs. Sessions after discharge include continued practice of distress tolerance skills, with additional topics and skills practice designed to promote dyadic adjustment and positive interpersonal communication. Session content is further described in Supplemental Table 1. Survivors and caregivers participate in all sessions together and practice skills between sessions together.

The health education control condition mimicks the dose and duration of RT and provides educational information without teaching resiliency skills. Topics include: education on common experiences after acute neurological illness injury, the importance of self-care behaviors (diet, exercise, sleep), adjusting to life after hospital discharge, adherence to medical regimens, changing relationships, and navigating fears of recurrence.

Measures

Demographics and clinical variables were collected at baseline for all study participants. Measures of self-reported emotional distress were collected at the time of study enrollment, post-intervention (within 7 weeks of enrollment), and again at 3-month follow-up (12–14 weeks after enrollment).

Depression and Anxiety

The 14-item Hospital Depression and Anxiety Scale (HADS; Bjelland et al., 2002) is a widely used, reliable, and valid measure for symptoms of depression and anxiety. Items are scored on on a 4-point Likert scale, with higher scores indicating higher symptom severity. Depression and Anxiety scores are calculated separately by summing the 7 items for the respective subscales. Subscale total scores range from 0 to 28, with scores of 7 or greater representing clinically significant symptoms of anxiety or depression (Hansson et al., 2009). In the current sample, internal consistency reliability at baseline was good for survivors (α =.86) and excellent for caregivers (α =.92) for the HADS-A. Internal consistency reliability was also good for the HADS-D (α = .86 for survivors; α=.82 for caregivers).

Post-traumatic Stress

The 17-item PTSD Checklist-Civilian Version (PCL-C; Weathers et al., 1993) assesses PTS symptom severity on a 5-point Likert scale, with higher scores suggesting worse symptom severity. Total severity scores are generated by summing all items, and total scores range from 17 to 85. Clinically significant symptoms are determined using an algorithm based on Diagnostic and Statistical Manual for Mental Disorders (DSM; Blanchard et al., 1996) requiring criteria B-D being met with symptoms endorsement the moderate or above range. Internal reliability was excellent (α = .91 for survivors; α=.92 for caregivers).

Statistical Analyses

First, non-independence of dyads’ emotional distress was examined in the cross-sectional correlations of emotional distress scores within-dyads at each timepoint and correlations between dyad members’ changes in distress over time (baseline to post-intervention, post-intervention to follow-up). This analysis tested whether patients and caregivers emotional distress was similar at any given timepoint and whether changes in distress were similar within dyads.

Next, cross-lagged panel path models were conducted to examine stability (i.e., “actor effects”) and mutual influence (i.e., “partner effects”) in emotional distress over time using MPlus v. 6.1 (Muthén & Muthén, 2007). This analysis tests how “stable” an actor is in terms of distress over time and whether this outcome changes based on a partner’s prior distress. For each outcome (symptoms of depression, anxiety, and PTS), a fully unrestricted model with no covariates other than condition (intervention or control) was calculated using maximum likelihood estimation and robust residuals (MRL). MRL uses all data available to estimate models, which has advantages over listwise deletion (Little & Rubin, 2019). To test for effect modification (i.e., to see whether associations differed by patient v. caregiver role), the fully unrestricted model was then compared to a model restricting all effects as equal over time and across role (survivor or caregiver), and coefficients for intervention at post-intervention and follow-up were allowed to differ from baseline. Variances and covariances were also restricted (baseline variance and covariance were allowed to differ from post-intervention and follow-up). Changes in fit as model restrictions were added were tested statistically using nested Chi-square analyses, adjusting for scaling correction. We did not evaluate fit using specific cutoff criteria due to the lack of consensus on rules of thumb” cutoffs for conventional fit indices (Hu & Bentler, 1999). Instead, if the model fit was significantly worse (p < .05), differences were systematically investigated. Adequacy of fit for the selected model was reported using chi-square statistics, however, chi-square indices of model fit have high rate of false positives in small sample sizes (Kenny et al., 2015). Thus. despite shortcomings of other fit indices in small samples (Kenny et al., 2015), Comparative Fit Index [CFI], Tucker-Lewis index (TLI), Root Mean Square Error of Approximation [RMSEA], and Standardized Root Mean Square Residual (SRMR) were also reported. Sensitivity analyses examining sources of misspecification were estimated (Kenny et al., 2015).

All models controlled for intervention condition (1 = RT active intervention; 0 = control). Sensitivity analyses included additional covariates: survivor and caregiver gender (1 = male; 0 = female), survivor intubation status (1 = intubated; 0 = not intubated), and caregiver relationship to survivor (1 = spouse/partner; 0 = other). These covariates were selected a priori based on prior work demonstrating their association with emotional distress outcomes for Neuro-ICU survivor-caregiver dyads after discharge (Meyers et al., 2020a; 2020b; 2020c). Statistical significance inferred using standard criteria (α = .05, two-tailed).

Results

Correlations Between Survivor and Caregiver Emotional Distress at Three Time Points

Correlations between survivor and caregiver emotional distress (depression, anxiety, and PTS symptoms) at each wave are presented in Table 2. At baseline, survivor and caregivers’ levels of PTS were significantly correlated (r = .38, p < .05). Baseline levels of depression and anxiety were not significantly correlated within-dyads (ps > .05) Post-intervention levels of depression (r = .56, p < .01), anxiety (r = .27, p < .01), and PTS were all significantly correlated within-dyad (r =.48, p < .01). Correlations were of similar magnitude at the 3-month follow-up assessment (rs ranged from .34 to .37, ps < .05).

Table 2.

Correlations between survivor and caregiver emotional distress at each time point.

Survivor Depression Caregiver Depression
Baseline Post-intervention Follow-up Baseline Post-intervention Follow-up
Survivor Depression Baseline 1.00
Post-intervention 0.09 1.00
Follow-up 0.13 0.54** 1.00
Caregiver Depression Baseline 0.25 −0.03 −0.19 1.00
Post-intervention −0.11 0.56** 0.40** 0.20 1.00
Follow-up −0.09 0.45 0.37* 0.27 0.68** 1.00
Survivor Anxiety Caregiver Anxiety
Baseline Post-intervention Follow-up Baseline Post-intervention Follow-up
Survivor Anxiety Baseline 1.00
Post-intervention −0.05 1.00
Follow-up 0.08 0.64** 1.00
Caregiver Anxiety Baseline 0.20 −0.42** −0.38** 1.00
Post-intervention −0.11 0.27** 0.25 0.06 1.00
Follow-up −0.29 0.32* 0.34* 0.05 0.51** 1.00
Survivor PTS Caregiver PTS
Baseline Post-intervention Follow-up Baseline Post-intervention Follow-up
Survivor PTS Baseline 1.00
Post-intervention 0.20 1.00
Follow-up 0.24 0.50** 1.00
Caregiver PTS Baseline 0.38** −0.04 −0.19 1.00
Post-intervention 0.06 0.48** 0.18 0.38** 1.00
Follow-up −0.01 0.49** 0.34* 0.32* 0.71** 1.00
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*

p < .05;

**

p < .01.

Correlations Between Changes in Emotional Distress Symptoms

Correlations between changes in emotional distress within-dyads from baseline to post-intervention and from post-intervention to follow-up are presented in Table 3. Correlations between survivor and caregiver emotional distress from baseline to post-intervention were consistently strong (Cohen, 1988) and positive (rs ranged from .56 to .62, ps < .01). Survivor and caregiver changes in emotional distress from post-intervention to 3-month follow-up were not significantly correlated.

Table 3.

Correlations between changes in survivor and caregiver emotional distress.

Survivor Depression Caregiver Depression
Baseline to Post-intervention Post-intervention to Follow-up Baseline to Post-intervention Post-intervention to Follow-up
Survivor Depression Baseline to Post-intervention 1.00
Post-intervention to Follow-up −0.32* 1.00
Caregiver Depression Baseline to Post-intervention 0.56** 0.02 1.00
Post-intervention to Follow-up −0.23 0.16 −0.41** 1.00
Survivor Anxiety Caregiver Anxiety
Baseline to Post-intervention Post-intervention to Follow-up Baseline to Post-intervention Post-intervention to Follow-up
Survivor Anxiety Baseline to Post-intervention 1.00
Post-intervention to Follow-up −0.36* 1.00
Caregiver Anxiety Baseline to Post-intervention 0.61** −0.10 1.00
Post-intervention to Follow-up −0.02 0.15 −0.40** 1.00
Survivor PTS Caregiver PTS
Baseline to Post-intervention Post-intervention to Follow-up Baseline to Post-intervention Post-intervention to Follow-up
Survivor PTS Baseline to Post-intervention 1.00
Post-intervention to Follow-up −0.33* 1.00
Caregiver PTS Baseline to Post-intervention 0.62** 0.00 1.00
Post-intervention to Follow-up −0.02 0.26 −0.34* 1.00
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*

p < .05;

**

p < .01.

Stability and Influence in Emotional Distress

Depression

The unrestricted and fully restricted models were not significantly different, χ2(15) = 24.83, p = .052. The selected model (Figure 1) demonstrated acceptable fit, χ2(19) = 41.06, p = .002; CFI = 0.79; TLI = .64; RMSEA = 0.14, 90% CI: 0.08, 0.20, SRMR = 0.13.

Figure 1.

Figure 1.

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Fully restricted cross panel analysis of depression across study time points.

Note: X2(19) = 41.06, p = .002; CFI = 0.79; TLI= 0.64; RMSEA = 0.14, 90% CI 0.08, 0.20; SRMR= 0.13.

One’s own prior depression was significantly associated with depression at post-intervention and follow-up, B = 0.42, se = 0.08, p < .001 (“actor effect,” or stability); whereas one’s partner’s prior depression was not, B = 0.05, se = 0.07, p = .51 (“partner effect,” or influence). The residual covariance between survivor and caregiver depression was positive and significant at post-intervention and follow-up, p < .001 (but not baseline, p = .23). Including covariates did not alter these conclusions.

Fit indices indicated a path between caregiver depression at baseline and follow-up; for consistency, this was added for survivors as well. The resulting model fit the data such that the chi-square was now nonsignificant, χ2(18) = 28.15, p = .06; CFI = 0.91;TLI = 0.88; RMSEA = 0.10, 90% CI: 0.00, 0.16, SRMR = 0.13. No substantive conclusions were altered.

Anxiety

The unrestricted and fully restricted models were not significantly different, χ2(15) = 16.84, p = .33. The selected model (Figure 2) demonstrated acceptable fit, χ2(19) = 29.66, p = .056; CFI = 0.89; RMSEA = 0.10, 90% CI: 0.00, 0.16.

Figure 2.

Figure 2.

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Fully restricted cross panel analysis of anxiety across study time points.

Note: X2(19) = 29.66, p = .056; CFI = 0.89; TLI= .88; RMSEA= 0.10, 90% CI 0.00, 0.16; SRMR= 0.13.

One’s own prior anxiety was significantly associated with anxiety at post-intervention and follow-up, B = 0.36, se = 0.07, p < .001; one’s partner’s prior anxiety was not significantly associated with one’s own anxiety over time, B = −0.06, se = 0.06, p = .30. The residual covariance between survivor and caregiver anxiety was positive and significant at post-intervention and follow-up, p = .009 (but not baseline, p = .23). Including covariates did not significantly alter these conclusions.

Fit indices suggested a potential path between one’s own anxiety at baseline predicting anxiety at follow-up in survivors and in caregivers. A model including these paths provided excellent fit, χ2(18) = 17.05, p = .52; CFI = 1.00; TLI= 0.79; RMSEA = 0.00, 90% CI 0.00, 0.11, SRMR=0.13; and did not alter any substantive conclusions.

PTS

The unrestricted and fully restricted models were not significantly different, χ2(15) = 18.39, p = .24. The selected model (Figure 3) demonstrated acceptable fit, χ2(19) = 42.23, p = .002; CFI = 0.81; TLI=0.79 RMSEA = 0.14, 90% CI: 0.08, 0.20, SRMR= 0.13

Figure 3.

Figure 3.

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Fully restricted cross panel analysis of PTS across study time points.

Note:X2(19) = 42.23, p = .002; CFI = 0.81; TLI= 0.79; RMSEA = 0.14, 90% CI 0.08, 0.20; SRMR= 0.13.

One’s own prior PTS symptoms was significantly associated with PTS at post-intervention and follow-up, B = 0.52, se = 0.08, p < .001. One’s partner’s prior PTS was not significantly associated with one’s own PTS over time, B = 0.01, se = 0.06, p = .92. The residual covariance between survivor and caregiver PTS was positive and significant at post-intervention and follow-up, p = .007 (but not baseline, p = .34). Including covariates did not alter these conclusions.

Fit indices suggested a potential path between one’s own PTS symptoms at baseline predicting PTS symptoms at follow-up in survivors and in caregivers. A model including these paths provided excellent fit, χ2(18) = 18.80, p = .40, CFI = 0.99, RMSEA = 0.03, 90% CI 0.00, 0.12, and did not alter any substantive conclusions.

Discussion

The present study utilized a secondary data analysis to explore similarities between Neuro-ICU survivor-caregiver dyads in emotional distress outcomes in the context of their participation in an RCT of two dyadic psychosocial interventions. Consistent with the overarching study hypotheses, there was evidence for non-independence of survivor and caregivers’ emotional distress at baseline (PTS) and at post-intervention and follow-up (depression, anxiety, PTS). Changes in emotional distress over the course of dyadic psychosocial treatment and through the 3-month follow up were also correlated within dyads. Contrary to study hypotheses, there was no evidence for the interdependence (i.e., “partner effects”) of dyad members’ levels of emotional distress on each others’ subsequent emotional distress.

Correlations between cross-sectional emotional distress and changes in levels of emotional distress, as well as the positive residual covariances of dyads’ emotional distress after treatment (post-intervention and follow-up), provide evidence that Neuro-ICU survivors and caregivers respond in similar ways to psychosocial interventions. This pattern was observed across emotional distress target outcomes (depression, anxiety, PTS). These findings are supported by robust literature which indicates that adjustment to illness is a dyadic process (Badr et al., 2019; Karademas, 2021), and could be related to shared treatment exposure, shared environmental exposure in the hospital and after discharge, or both. After the onset of chronic illnesses, patient-caregiver dyads engage in discussions about the illness, which can contribute to their shared ways of understanding and managing the illness (Karademas, 2021). Participation in a dyadic intervention allows partners to discuss topics related to the acute neurological illness, which can impact their appraisal of the illness and related stressors. As a result, this may create similarities in emotional distress patterns over time (Karademas, 2021).

Although this study did not provide evidence for interdependence (i.e., “partner effects,” or mutual influence) of emotional distress, it is possible that intervention effects were strong enough that dyadic markers of influence could not be detected. Stated otherwise, the added, indirect influence of a partner’s emotional state on one’s own emotional distress over time may have been washed-out by the large direct influence of the intervention on survivors and caregivers who completed it together (Kenny & Ledermann, 2010). Future studies should investigate potential mechanisms of change at both the individual level (e.g., do changes in individual-level coping behaviors exhibit patterns of influence between partners) as well as dyad-level mechanisms (e.g., developing dyadic coping strategies together). Studies should also examine interdependence in larger samples with greater power to be able to detect partner effects. Increasing research in this area is critical for Neuro-ICU dyads – where one dyad member may have cognitive, physical, health, or other practical complications that preclude participation – making it necessary to understand whether both partners could experience benefits from only one dyad member receiving treatment (Gorin et al., 2008; 2018).

These findings have a number of research implications. Despite the rich theoretical and empirical literature (Badr et al., 2019; Falconier & Kuhn, 2019; Karademas, 2021; Lange & Rusbult, 2012; Lyons & Lee, 2018; Patterson, 2002) demonstrating dyad members’ shared adjustment to illness over time, very few studies have examined outcomes of dyadic RCTs in medical populations using statistical approaches that examine dyad members simultaneously. Incorporating such approaches illuminates patterns of interdependence between survivors and caregivers in relation to intervention outcomes, which can be used to determine whether to intervene on surivors and caregivers separately or in tandem, and to refine intervention approaches and procedures. Recent reviews (Badr et al., 2019) on best practices for dyadic interventions emphasizes the need for screening for both survivor and caregive distress as a first step in providing comprehensive care, and considering survivor, caregiver, and relationship needs in formulating supportive care protocols. The pattern of results in the present study illustrate the benefits of this dyadic treatment conceptualization, and suggest that if one dyad member benefits from treatment, the other dyad member benefits similarly. The present study examined emotional distress outcomes in separate statistical models based on statistical guidelines for dyadic analyses (Kenny et al., 2020), consistency with our prior work (Vranceanu et al., 2020), and prior literature (Hwang et al., 2014; Schöttke & Giabbiconi, 2015; Stein et al., 2018). However, future studies should consider latent variable analyses to examine dyadic factors that may contribute to emotional distress outcomes more broadly.

Our findings also have clinical implications. Practitioners could try leveraging the dyad’s potential strengths (e.g., relationship satisfaction, open communication ability to cope and problem-solve together) to enhance resilience. Further, they could address any vulnerabilities (e.g., challenges with individual emotion regulation, differing coping styles or appraisal of the illness, communication skills deficits) with education and strategies linked to positive dyadic adjustment to stressors (e.g., collaborative dyadic coping, open discussion of stressors, supportive coping) (Falconier & Kuhn, 2019). Future studies involving a more fine-grained analysis of Neuro-ICU dyads’ dynamics of emotional distress following discharge can be used to understand how survivors and caregivers recover together and therefore enhance interventions for survivor-caregiver dyads by capitalizing on shared dynamics.

There were a number of limitations in this study. First, sample size was determined for the primary outcomes of the RT RCT (Vranceanu et al., 2020) which included feasibility, acceptability, credibility, and preliminary effects for survivors and caregivers separately, and the study was not sufficiently powered to fully examine dyadic effects. In addition, participant self-selection may have influenced the initial presentation of dyads enrolled in the RT RCT. However, the refusal rate of eligible dyads was low (24%) and the study team made efforts to minimize selection bias by building rapport during the initial screening and offering a flexible approach to enrollment. This study relied on self-report assessments of emotional distress; therefore, it is also possible that response bias impacted the findings. This analysis was an early test of the hypotheses that survivor and caregiver outcomes would exhibit non-independence in emotional distress outcomes over the course of the intervention trial and the small sample size prevented an exploration of treatment outcomes stratified by condition. In addition, the small sample size precluded our ability to explore potential mechanisms of change in the active intervention condition (e.g., individual coping techniques, relationship building) and adjust for potential bias in secondary analyses of dyadic effects. Further, RCTs that are fully powered to investigate dyadic effects are needed in order to examine interrelations between individual and dyadic adjustment to illness, consistent with theoretical frameworks (Falconier & Kuhn, 2019). Further, the Recovering Together RCT (Vranceanu et al., 2020) did not include an assessment of dyads’ contextual factors (e.g., age of survivors and caregivers, relationship type and length, additional caregiving roles) that may have impacted outcomes after discharge, and should be considered in future studies.

Conclusion

Neuro-ICU survivors and their informal caregivers exhibit similarities in their levels of emotional distress (depression, anxiety, PTS) after participation in a dyadic intervention and change in similar ways over time. These findings suggest that, if one dyad member benefits from treatment, the other dyad member benefits similarly, highlighting the potential of dyadic treatment approaches to harness social factors and ameliorate survivor and caregiver distress following Neuro-ICU admission.

Supplementary Material

Supplemental Material

Acknowledgements

We acknowledge Victoria A. Grunberg, M.S. for her assistance reviewing of the manuscript.

We declare no conflicts of interest. This work was supported by National Institute of Nursing Research (NNIR) under 5R21 grant (NR017979).

Footnotes

Trial registration: ClinicalTrials.gov identifier: NCT03694678

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