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Protective buffering refers to hiding cancer-related thoughts and concerns from one’s spouse or partner. This study sought to examine the intra- and inter-personal consequences of protective buffering and motivations for such (desire to shield partner from distress, desire to shield self from distress).
Eighty hematopoietic stem cell transplant patients and their spousal caregivers/ partners completed measures designed to assess protective buffering and relationship satisfaction at two time points: prior to the transplant (T1) and 50 days post-transplant (T2). Overall mental health was also assessed at T2.
There was moderate agreement between one dyad member’s reported buffering of his/ her partner, and the partner’s perception of the extent to which s/he felt buffered. Caregivers buffered patients more than patients buffered caregivers, especially at T2. The more participants buffered their partners at T2, and the more they felt buffered, the lower their concurrent relationship satisfaction and the poorer their mental health. The latter effect was particularly true for patients who buffered, and patients who felt buffered. With respect to motivations, patients who buffered primarily to protect their partner at T1 reported increases in relationship satisfaction over time, but when they did so at T2, their caregiver reported concurrent decreases in relationship satisfaction.
Protective buffering is costly, in that those who buffer and those who feel buffered report adverse psychosocial outcomes. In addition, buffering enacted by patients with an intention to help may prove counterproductive, ultimately hurting the object of such protection.
Coping is typically thought of in terms of individual-level strategies, such as active coping, planning, positive reframing, acceptance, and behavioral disengagement.1 But coping also has dyadic-level implications.2 Relationship-focused coping strategies are ways of coping designed to maintain, preserve, and protect social relationships during times of stress (e.g., a family coping in the aftermath of a destructive hurricane, a couple coping in the face of a woman’s breast cancer diagnosis and treatment).
In the present study, we focus on a particular relationship-focused coping strategy, that of protective buffering (PB). Originally conceived of with respect to couples dealing with a myocardial infarction,2 PB as applied to the cancer setting is defined as “hiding one’s concerns, denying one’s worries, concealing discouraging information, preventing the patient from thinking about the cancer, and yielding in order to avoid disagreement” (p. 275).3 Two hypothetical examples are as follows. A patient might be experiencing certain symptoms, perhaps worsening symptoms, but so as not to worry his/ her caregiving partner, hesitate to mention those symptoms. Alternatively, the caregiver might fear that his/ her ill partner will die but, so as not to further burden that individual, refrain from expressing those fears.
What are the consequences of PB? Does it in fact confer protective effects? In attempting to answer this question, we consider both intra- and inter-personal effects of PB and, in so doing, draw on nomenclature from social psychology and dyadic analysis.4 In any dyad, one member can be designated as the “actor”, who behaves in some way toward the other member of the dyad, designated the “partner”. Importantly, the designation is purely arbitrary, as both members of the dyad play both roles. Intrapersonal effects refer to the effects of an actor’s behavior on his or her own outcomes, e.g., the effects of a husband’s behavior on his own affective state. Interpersonal effects refer to the effects of an actor’s behavior on outcomes in the partner and vice versa, e.g., the effects of a husband’s behavior on his wife’s affective state.
Research on PB has indeed yielded both intra- and inter-personal effects, i.e., effects on the one who engages in buffering (the actor) and effects on the one who is the object of such buffering (the partner). Regarding intrapersonal effects, buffering enacted by patients has been associated with negative outcomes among patients: increased distress5, 6 and decreased self-efficacy.7 Similarly, buffering enacted by partners has been associated with negative outcomes among partners: increased distress2, 6, 8 and decreased self-efficacy.9 Regarding interpersonal effects, buffering enacted by patients has been associated with increased distress among partners,2 and buffering enacted by partners has been associated with increased distress8, 9 and decreased relationship quality3 among patients; it has also been associated with a positive outcome among patients, namely, increased self-efficacy to recover from a myocardial infarction.7
Methodological approaches to the study of PB have differed to some extent. Researchers have administered slightly different versions of the scale originally constructed by Coyne & Smith,2 then modified by Suls et al.6 Only a subset of studies has assessed buffering as enacted by both dyad members. An even smaller subset has assessed received buffering – the extent to which an individual feels buffered by his/ her partner, and this has only been done with respect to patient perceptions.3, 9, 10 Analyses generally have not taken into account the interdependent nature of the dyadic data, with notable exceptions.8, 11 In addition, few study designs have afforded examination of either change in PB over time or the effects of PB at one point in time on outcomes at a later point in time, again with notable exceptions.6, 8, 12 Lastly, just one published study has employed a behavioral or objective measure of PB.13
In yet another methodological twist, Trost,14 in an unpublished dissertation, added two items to the PB scale. The items were designed to assess motivation to protect. At first blush, PB appears to be a purely prosocial act, intended to shield one’s partner. However, buffering theoretically also affords self-protection. In withholding concerns and worries, and yielding during arguments, one minimizes negative emotional experience and avoids conflict. One also avoids the personal negative feelings of having upset the other. Using a sample of 60 myocardial infarction patients and spouses, Trost14 found increased distress among spouses when patients reported greater intentions to protect themselves relative to their spouses.
Buffering may be especially likely to occur in situations in which treatment is a last resort and/ or poses grave medical risks, as is the case with hematopoietic stem cell transplantation (HSCT), one of the most aggressive forms of cancer treatment. With HSCT, patients receive chemotherapy, sometimes combined with total body irradiation. The patient is then “rescued” and their disease is combated with infusion of either their own stored immune stem cells (autologous), or stem cells from an immune-matched related or unrelated donor (allogeneic). Complete immune recovery can take many months and requires social isolation to protect against germs and a complex medication regimen for disease prophylaxis, infections and symptom control. Patients are not allowed to return to work or school for 6–12 months post-transplant. Early and late medical sequelae are well-established and include: infection, acute and chronic graft-versus-host disease, pulmonary complications, neurological complications, infertility, secondary malignancy, relapse and even death.15, 16 Psychosocial sequelae have also been documented: decreased mental health, anxiety, depression, fatigue, sleep difficulties, sexual dysfunction, and concerns ranging from the pragmatic (financial) to the existential.17–19 Spouses/ partners are also impacted by the treatment. They are required to take on an extensive caregiving role,20, 21 including responsibility for medical care tasks and amplification of routine household tasks (e.g., cleaning to minimize exposure to germs). Psychosocial sequelae among caregivers include decreased mental health, decreased relationship satisfaction, sexual difficulties, decreased social support, increased negative affect, increased loneliness, and decreased spiritual well-being.18, 22 Recognizing these challenges and the natural inclination to protect both oneself and one’s partner from emotional upheaval during the survival challenges and practical demands of HSCT, we determined a need to examine the impact of PB in this population.
Several questions drove the present investigation: Does PB among HSCT patients and spouses change over time?; Who buffers more, patients or spouses?; Are PB reports accurate, i.e., does PB enacted by one dyad member correspond to that received by the other?; Does PB have intra- and inter-personal costs, and do these costs differ when one considers the intentionality behind PB (desire to protect partner, desire to protect self)? Accordingly, our goals were three-fold: (1) To examine the course of PB among both patients and caregivers, as couples move from preparing for the transplant to recovering from the transplant; (2) To examine the degree of concordance and interdependence among couples with respect to PB (i.e., the extent to which one partner’s buffering is associated with the other partner’s buffering, and the extent to which one partner’s buffering is associated with the other partner’s perception of being buffered); (3) To examine the prospective and concurrent intra- and inter-personal consequences of PB on functioning at a point of high stress and demand, namely, day 50 post-transplant, when couples have recently transitioned from inpatient to outpatient care. We predicted that PB would increase over time, as patients faced post-HSCT sequelae and partners faced heightened caregiving duties that nurses had previously performed. We also predicted that partners would buffer patients more than patients would buffer partners, due to the inherent “protective” nature of the caregiver role. Furthermore, PB was expected to be associated with deleterious intra- and inter-personal consequences. Analyses regarding concordance and motivation to protect were exploratory.
Patients and caregivers were recruited from the Seattle Cancer Care Alliance, an affiliation of the Fred Hutchinson Cancer Research Center and the University of Washington. The study coordinator reviewed a list of incoming patients, those with an imminent HSCT. These patients were screened for eligibility and, if deemed eligible based on medical record and initial social work intake, scheduled for a face-to-face consent meeting. The social work note was utilized to determine whether or not patients were partnered, and whether or not the partner planned to remain in Seattle for the transplant and ensuing recovery period.
Eligible patients were at least 21 years old, English speaking and comprehending, scheduled to receive their first HSCT, and married or in a committed, cohabiting, heterosexual or homosexual relationship. Eligible partners were at least 21 years old, English speaking and comprehending, and planning to be present at the transplant site for at least two months (couples typically relocate to a transplant center for 2–4 months during the acute procedures). Informed consent was obtained from all participants.
The design of the study was prospective and longitudinal, with assessments prior to the transplant (T1) and approximately 50 days post-transplant (T2). T1 questionnaires were administered, on average, 23.00 days pre-transplant (SD = 23.62, median = 14.00). T2 questionnaires were administered, on average, 52.05 days post-transplant (SD = 4.53).
The distribution was more varied for the T1 administration, simply because the transplant team can only estimate the likely date of transplant and many medical events may intercede that would not have been known to the researcher or patient at the point of assessment (e.g., a transplant day might be adjusted as the workup indicates necessary). All questionnaires were completed in a conference room of the Seattle Cancer Care Alliance.
Study procedures were approved by the Fred Hutchinson Cancer Research Center Institutional Review Board. Self-report measures are described in turn.
This measure, administered at both time points, consists of three sections. First, respondents rate the extent to which, in communicating with their partner during the past month, they: denied or hid their anger; denied or hid their worries; avoided disagreeing with their partner; gave in more during arguments with their partner; acted more positive than they felt; avoided talking about things; and withheld potentially upsetting information.6, 14 The first six items follow Suls et al.6 and the seventh, Trost.14 Items are rated on a 1–5 scale, with higher values indicative of greater buffering. The second section assesses motivation to protect, following Trost:14 “In doing these things [the previously rated items], (1) to what extent did you try to protect your partner from feeling bad or distressed, and (2) to what extent did you try to protect yourself from feeling bad or distressed?” The third section assesses received buffering. Respondents make a second set of ratings for the items listed above (e.g., “avoided talking about things”), this time with respect to how their partner behaved toward them. Internal consistencies for the present sample were strong: Cronbach’s coefficient α = .80 and .85 for patient-reported buffering of caregiver (at T1 and T2, respectively); .84 and .86 for caregiver-reported buffering of patient; .87 and .86 for patient-reported received buffering; and .80 and .86 for caregiver-reported received buffering.
The DAS was administered at both time points. It is a widely used measure of adjustment in spousal or committed relationships, arguably the gold standard and sensitive to change.23 We administered the 10-item satisfaction subscale. Exemplar items include, “How often do you and your partner quarrel?” and “How often do you discuss or have you considered divorce, separation, or terminating your relationship?” Response formats vary (using 0–5, 0–4 and 0–6 rating scales). Individual items are summed to create a satisfaction aggregate; theoretical range = 0–50, with higher numbers indicative of greater satisfaction. Cronbach’s coefficient α for the present sample = .74 and .76 for patients and .84 and .81 for caregivers (at T1 and T2, respectively).
The SF-36 was administered only at T2, to minimize responder burden. It is a widely-used measure of quality of life, with well-established psychometric properties.24 Thirty-six items assess eight dimensions of function: physical functioning (10 items), social functioning (2 items), bodily pain (2 items), vitality (4 items), role-physical, the extent to which work or other activities are impacted by physical problems (4 items), role-emotional, the extent to which work or other activities are impacted my emotional problems (3 items), mental health (5 items), and general health (5 items). Exemplar items include, “During the past 4 weeks, to what extent has your physical health or emotional problems interfered with your normal social activities with family, friends, neighbors or groups?” (social functioning) and “During the past 4 weeks, how much have you cut down on the amount of time spent on work or other activities as a result of your physical health?” (role-physical). Response formats vary. Internal consistency (Cronbach’s coefficient alpha) values for patients and caregivers, respectively, in the present sample were: .90 and .93 for physical functioning; .77 and .89 for social functioning; .90 and .84 for bodily pain; .87 and .84 for vitality; .91 and .91 for role-physical; .94 and .87 for role-emotional; .85 and .82 for mental health; and .74 and .76 for general health. In addition to the eight subscales, two summary standardized T scores can be calculated: a mental component summary (MCS) and a physical component summary (PCS). All eight subscales contribute to both summary scores, with the MCS most heavily weighted by the mental health, social functioning, and role emotional subscales, and the PCS most heavily weighted by the physical functioning, role physical, and bodily pain subscales. We focus here on MCS scores as an outcome variable.
Statistical analyses were performed with Statistical Package for the Social Sciences 17.0. Bivariate correlations were used to examine associations among the major study variables: predictors, outcomes and potential covariates. Repeated measures ANOVAs were conducted to examine changes over time among patients and caregivers with respect to buffering, received buffering, and motivation to protect. To account for and model the natural interdependence that exists among couples, we employed the Actor-Partner Interdependence Model.4 This procedure estimates two effects, actor effects and partner effects. The actor effect represents the association between a predictor and an outcome within an individual (e.g., patient’s buffering and patient’s relationship satisfaction); the partner effect represents the association between a predictor and an outcome across dyad members (e.g., patient’s buffering and caregiver’s relationship satisfaction). Cross product terms are added to test for interactions. Because the dyad is the unit of analysis, models include only those couples for whom both parties are represented. With power set at .80, 36 dyads are needed to detect interdependence.25 Our sample size exceeded this requirement.
Three sets of linear mixed models were run for each of two dependent variables at T2: relationship satisfaction (DAS) and overall mental health (MCS). In one set of models, the predictor was concurrent buffering (the extent to which an individual buffered his/ her partner). In the second set of models, the predictor was concurrent received buffering (the extent to which an individual felt buffered by his/her partner). In the third set of models, the predictor was concurrent motivation to protect. Difference scores were created by subtracting scores for “desire to protect self” from scores for “desire to protect partner”, with positively signed difference scores indicative of greater intention to protect partner versus self, and negatively signed difference scores indicative of greater intention to protect self versus partner. A final set of models was run to examine prospective predictors of relationship satisfaction at T2: one with buffering at T1 as the predictor, a second with received buffering at T1 as the predictor, and a third with motivation to protect at T1 as the predictor, each controlling for relationship satisfaction at T1.
All models were run both with and without controlling for patient age, spouse age, and length of relationship (based on bivariate associations noted in the following section). Those without covariates are reported here. None of the covariates was associated with outcomes in concurrent or prospective analyses, and none of the associations involving PB was altered in any significant way by the addition of the covariates to the predictive equation.
Figure 1 provides an overview of patient flow from initial screening to eligibility determination to enrollment. Among eligible couples for whom both dyad members attended a face-to-face consent meeting (n = 115), 87 agreed to participate, resulting in a 76% agreement rate. Patients who agreed to participate did not differ from those who declined with respect to age, gender, ethnicity or race, all P values > .05.
Eighty dyads completed pre-transplant (T1) questionnaires. Among the 80, 63 caregivers (79%) and 60 patients (75%) completed T2 questionnaires. Reasons for non-completion were as follows: 3 patients expired prior to T2; 3 patients were discharged directly home following transplant, due to a poor prognosis; 5 patients relapsed and/or were re-admitted to the hospital prior to T2; one patient was receiving an infusion at the time of the T2 appointment (when the caregiver completed questionnaires); and 8 voluntarily withdrew from the study prior to T2. Reasons for withdrawal included: caregiver out of town/ unavailable (n = 1), caregiver illness (n = 1), overwhelmed/ too much going on (n = 4), and no explanation (n = 2). Because the sample size for patients and caregivers at T2 was unbalanced (60 and 63), and the dyad was the unit of analysis, data for the 3 caregivers were excluded.
Table 1 displays pre-transplant characteristics of a) the accrued sample and b) the subsample of “completers”, those surviving to and participating at T2. Participants were, on average, 56 years old, ranging in age from 26–78. Approximately two-thirds of patients were male, hence two-thirds of caregivers were female (all couples were heterosexual). The majority was Caucasian. Educational status and income were well-distributed. Ninety-four percent of couples were married at the time of enrollment. Similar to the wide range in age, couples had been together for varying periods of time (on average, 25 years). With respect to clinical characteristics of patients, the most common diagnosis was acute leukemia, followed by myelodysplasia. Most transplants were allogeneic in type (61% unrelated), and a significant percentage were non-myeloablative, meaning that the conditioning or preparatory regimen was substantially less intense. Importantly, the 60 patients who provided data at both time points did not differ appreciably from the 20 patients who provided data solely at T1; the same was true of caregivers, Ps > .05.
Table 2 displays correlations among study variables. We commence with correlations among the buffering variables. Patients and caregivers demonstrated some degree of interdependence with respect to buffering (r = .44, P < .001 at T1; r = .23, P = .075 at T2) and received buffering, but only at T2 (r = .08, P > .05 at T1; r = .29, P = .023 at T2). In other words, if a given participant buffered his/ her partner, the partner reported doing the same, and if a given participant felt buffered, so too did his/ her partner, at least at T2. Also of interest was the concordance between one dyad member’s buffering of his/ her partner and the other dyad member’s received buffering. Results indicated moderate concordance: r = .26, P = .019 and r = .28, P = .031 for patient-reported buffering of caregiver and caregiver-reported received buffering at T1 and T2, respectively; and r = .38, P < .001 and r = .31, P = .016 for caregiver-reported buffering of patient and patient-reported received buffering at T1 and T2, respectively. These relations provide evidence for the validity of PB reports. Looking at within-person correlations, those who believed they were doing a lot of buffering also felt they were being buffered by their partner (r = .63, P < .001 for patients at T1; r = .73, P < .001 for patients at T2; r = .56, P < .001 for caregivers at T1; and r = .66, P < .001 for caregivers at T2). In addition, among both patients and caregivers, buffering and received buffering were associated with the two motivation to protect variables (all Ps < .01). With respect to demographic characteristics, patient age was inversely related to caregiver-reported buffering and received buffering, such that caregivers were more likely to buffer younger patients, and more likely to feel buffered by younger patients. Of note, this was only true at T1 (r = −.26, P = .023 for buffering and age, and r = −.24, P = .033 for received buffering and age), not T2 (Ps > .05). Length of relationship was inversely associated with caregiver-reported desire to protect self at T2 (r = −.30, P = .018), such that caregivers in longer relationships were less likely to buffer for self-protective reasons. Interestingly, patient physical functioning (PCS) was not associated with any variables.
Table 3 displays descriptive statistics of the predictor variables: buffering, received buffering and motivation to protect. A 2 (role: patient, caregiver) X 2 (time: T1, T2) mixed analysis of variance (ANOVA) on buffering scores revealed two significant effects. First, a main effect of role indicated that caregivers reported doing more buffering than patients (Ms = 2.84 and 2.35), F(1, 118) = 15.04, P < .0001, ηp2 = .11. This effect was qualified by a role x time interaction, F(1, 118) = 5.26, P = .024, ηp2 = .04. Follow-up tests showed that the simple effect of role was stronger at T2, t(118) = 7.05, P < .0001, ηp2 = .30, than at T1, t(118) = 3.80, P < .0001, ηp2 = .11. In short, caregivers reported engaging in more buffering than patients, and this was especially true at T2. A comparable analysis was conducted on received buffering scores. None of the effects reached significance (all Ps > .05).
We examined motivation to protect using a 2 (role: patient, caregiver) x 2 (target of protection: self, other) x 2 (time: T1, T2) ANOVA, with the first factor treated as a between-subjects factor and the last two factors treated as within-subjects factors. A main effect of target indicated that participants were more motivated to protect their partner (M = 3.63) than themselves (M = 2.56), F(1, 116) = 120.65, P < .0001, ηp2 = .51. This effect was qualified by a role x target interaction, F(1, 116) = 11.38, P = .001, ηp2 = .09. Follow-up tests showed that while both dyad members expressed greater interest in protecting their partner than in protecting themselves, this was more true for caregivers, t(116) = 14.52, P < .0001, ηp2 = .65, than for patients, t(116) = 7.70, P < .0001, ηp2 = .34.
Table 4 displays results from the Actor-Partner Interdependence Model analyses, using concurrent predictors at T2. Inspection of the top portion shows that the main effect of actor was significant for both outcomes when buffering was used as the predictor. Independent of whether they were patients or caregivers, the more participants buffered their partner, the less satisfied they were with their relationship and the poorer was their mental health. The last effect was qualified by a role x actor interaction. Figure 2 displays predicted MCS scores for participants scoring 1 SD above or below the mean on buffering (as per Aiken & West26). As seen in the figure, the slope is negative for both dyad members, but is steeper for patients (b = −10.58, P < .0001) than for caregivers (b = −5.18, P < .0001). In short, buffering was associated with negative intrapersonal outcomes, and for mental health, this was especially true for patients.
Results for received buffering were similar (see middle portion of Table 4). Significant main effects of actor emerged for both outcomes: Independent of whether they were patients or caregivers, the more participants felt buffered by their partner, the less satisfied they were with their relationship and the poorer was their mental health. Once again, the last effect was qualified by a role x actor interaction. The form of the interaction matched that found with buffering: The slope relating received buffering to mental health was steeper for patients (b = −9.25, P < .0001) than for caregivers (b = −4.03, P = .006).
The bottom portion of Table 4 shows results for the motivation to protect index (motivation to protect partner minus motivation to protect self difference scores). None of the main effects reached significance, but several interactions did (or were marginally significant). Because the pattern was similar for both outcomes, we discuss them together, referring to the simple slope values presented in Figure 3. As can be seen, high patient motivation index scores predicted poorer partner outcomes. Patients who were especially motivated to protect their caregivers rather than themselves had caregivers who were relatively dissatisfied with their relationship and worse off in terms of overall mental health.
In a final set of models, the PB variables at T1 were used to predict relationship satisfaction at T2, controlling for relationship satisfaction at T1. When buffering at T1 was used as a predictor, only a main effect of the covariate, relationship satisfaction at T1, emerged, such that greater satisfaction at T1 was associated with greater satisfaction at T2 (b = 0.77, P < .0001). The same was true when received buffering at T1 was used as a predictor (b = 0.79, P < .0001). However, when the motivation to protect index was examined, an actor x role interaction emerged as well (b = −.58, P = .001). Figure 4 shows the nature of this interaction. As can be seen, the motivation index was positively related to relationship satisfaction among patients: The more highly motivated patients were to protect their partners relative to themselves (prior to the transplant), the greater was their adjusted post-transplant relationship satisfaction (b = .60, P < .05). In contrast, the motivation index was inversely related to relationship satisfaction among caregivers: The more highly motivated caregivers were to protect their partners relative to themselves (prior to the transplant), the lower was their adjusted post-transplant relationship satisfaction (b = −.50, P = 0.01). Additional analyses showed that the simple effect of role was significant when the motivation index was low (b = .63, P < .05) and high (b = −.83, P < .01).
Couples facing stress frequently turn to one another for support. The manner in which this support is communicated and experienced predicts various health outcomes.27, 28 In this study, we examined how PB — a form of social support in which one dyad member attempts to minimize the stress of the situation for the other — predicts the way couples cope when one partner is undergoing treatment for cancer.
Caregivers buffered patients more than patients buffered caregivers, especially at T2, day 50 post-transplant. This is hardly surprising. Caregiving responsibilities are exceedingly high during the acute recovery period. The patient’s immunosuppressed state necessitates not just medical care tasks and accompaniment to healthcare visits, but meal preparation with safety in mind, and rigorous and constant housecleaning to prevent exposure to germs. Likewise, patients are of necessity focused on their own physical recovery, so it is understandable that they would do less PB than caregivers. At the same time, patients did report doing some degree of buffering on their own, suggesting that they are trying to reduce stress for their caregivers.
Caregivers buffered with a greater prosocial orientation than did patients. In other words, they buffered with a stronger desire to protect their partner from feeling bad than themselves from feeling bad. Again, this makes perfect sense given the nature of the caregiving role. Conversely, it is no doubt adaptive for patients to be less partner-focused during a period of such acute stress – recovery from a major medical procedure with threat to survival and multiple known sequelae as is the case with HSCT.29
We found moderate agreement between one dyad member’s reported buffering of his/ her partner, and the partner’s perception of the extent to which s/he felt buffered. This suggests that PB judgments were relatively accurate. As noted in the introduction, few studies have been designed in such a way as to assess received buffering. Hagedoorn and colleagues3 measured partner-reported buffering of patient and patient-reported received buffering in a sample of 68 couples coping with cancer. Their correlation (r = .32) was remarkably similar to ours. Interestingly, the moderate level of agreement in our sample at the dyadic level did not translate into a role effect for received buffering at an aggregate level. In other words, caregivers reported doing more buffering than patients, but on average, patients did not report feeling more buffered than did caregivers.
Actor-Partner Interdependence Model analyses replicated actor effects as reported by other researchers.2, 5–9 For patients and caregivers alike, the more participants buffered their partner (and felt buffered by their partner), the less satisfied they were with their relationship and the poorer was their mental health. The findings for mental health, moreover, were qualified by a role x actor interaction. Although buffering was linked to poor mental health among both dyad members, this was especially true for patients. Interestingly, no partner effects were obtained, suggesting that PB creates consistent intrapersonal costs while providing few (if any) interpersonal benefits.
A different set of results emerged when examining motivations to buffer. Concurrent analyses of T2 outcomes yielded intra- and inter-personal effects for patients but not caregivers. The more motivated patients were to protect their partner relative to themselves, the less satisfied their caregivers were with their relationship, and the poorer was the mental health for both parties. Prospective analyses yielded a different pattern. No partner effects were found prospectively, but patients who were highly motivated to protect their partner relative to themselves experienced increases in their own relationship satisfaction over time, whereas caregivers who were highly motivated to protect their partner relative to themselves experienced decreases in their own relationship satisfaction over time. (Stated conversely, caregivers who were highly motivated to protect themselves relative to their partner experienced increases in their own relationship satisfaction over time.)
Why might this be the case? We know, from the broader and even HSCT-specific caregiving literatures, that caregiving exacts a significant toll on the one who cares: burden, fatigue, lack of sleep, depression, anxiety and physical impairment.18, 22, 30 Though certainly easier said than done, caregivers are frequently urged by loved ones and clinicians alike to take breaks and, in essence, to take care of themselves. It is intriguing to speculate about the mechanisms by which a more egoistic (self-protective) motivation might result in enhanced relationship satisfaction. It is likely that a greater motivation to buffer oneself from distress is associated with other self-protective behaviors. Perhaps the more egocentrically-motivated caregivers spent more time exercising or took more breaks. Perhaps they, subtly or otherwise, expected more of their patients in terms of self-care, thereby causing less of a strain and demand on themselves, resulting in a more positive affective state, a more positive perception of their patient and ultimately, greater relationship satisfaction. Our findings bolster the notion that caregivers should indeed think of themselves.
Regarding the inverse relationships between patient PB and caregiver outcomes, it is difficult to know which way the causal arrow flows. Do caregivers truly suffer as a result of patients’ protective intentions? Or, is it that patients feel the need to protect unhealthy partners? A mentally unhealthy or dissatisfied partner requires more attention, care and protection. A mentally unhealthy or dissatisfied partner is also less likely to provide social support, and may in fact serve as a social constraint to the patient, thereby inhibiting disclosure of cancer-related thoughts and feelings.31 Social constraints on disclosure are defined as “both objective social conditions and individuals’ construal of those conditions that lead individuals to refrain from or modify their disclosure of stress- and trauma-related thoughts, feelings, or concerns” (p. 315).31 Such constraints have been found to be associated with inadequate cognitive processing of, and maladjustment to, a stressor or traumatic event.32–34
In addition to our inability, with this associational study, to determine causality or direction of effect, other limitations must be considered. Outcomes were measured via self-report, not diagnostic interview, thereby assessing subclinical levels of relationship distress and mental functioning. Buffering was also measured via self- and partner-report. The most elegantly designed studies will include a behavioral indicator of the construct. Do subjective and objective indicators of PB correspond? In addition, it would be interesting to assess patient perceptions of caregiver motivations to protect and vice versa, and to examine the behavioral manifestations of prosocial versus self-protective motivations. Does buffering to minimize the experience of distress for oneself “look” different from buffering to minimize the experience of distress for one’s partner, in terms of what is said or not said, facial expressivity, and tone of voice?
Further longitudinal work is needed to fully comprehend the extent to which patients and caregivers engage in PB. Does PB decrease in the months to follow, as patients recover? Does caregiver PB elevate if the patient’s medical condition worsens? If in fact caregivers are engaging in PB on a chronic basis, it will be important to examine the physiological consequences of such. To recall, one of the items on the PB scale is “Acted more positive than I felt”. Expressive suppression, defined as the “conscious inhibition of one’s own emotional expressive behavior while emotionally aroused” (p. 970),35 may lie at the heart of PB, and is known to be physiologically effortful.35–37
Given that PB poses deleterious effects for those who engage in this behavior, it seems important to intervene on this front. But is buffering amenable to intervention? At the very least, clinicians will want to foster open communication among these couples. Indeed, at least one couples-based coping training intervention has yielded promising results in terms of facilitating communication among dyads in which one member has cancer.38 Either alternatively or in addition to a couples-oriented treatment, patients and caregivers may benefit simply from opportunities to express their thoughts and feelings – perhaps individually to a counselor or via journaling.39, 40 In a randomized written emotional expression trial, Zakowski and colleagues found heightened benefit of expression among socially constrained cancer patients – those whose cancer-related disclosures had been discouraged by significant others.41 Because PB inherently involves limited disclosure, an outlet for emotional expression might be particularly helpful for patients and caregivers in relationships characterized by the use of PB and, ultimately, beneficial for the dyad as a whole.
Supported by grant R21 CA 112477 from the National Cancer Institute, awarded to the first author.
Thanks to Study Coordinator Heather Lucas, staff at the Seattle Cancer Care Alliance, and the couples who kindly participated.
No financial disclosures.