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Posttraumatic Growth After Breast Cancer: Patient, Partner, and Couple Perspectives

From the Fox Chase Cancer Center, Philadelphia, PA (S.M., L.G.); the Memorial Sloan-Kettering Cancer Center, New York, NY (J.O.); the Graduate Center, City University of New York, New York, NY (G.W.); the Hospital of the University of Pennsylvania, Philadelphia, PA (K.F.); and Cooper Hospital-Camden, Camden, NJ (G.G.).

Address correspondence and reprint requests to Sharon Manne, PhD, Fox Chase Cancer Center, 333 Cottman Avenue, P1100, Philadelphia, PA 19111. E-mail: SL-Manne{at}fccc.edu

	ABSTRACT

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
OBJECTIVE: The purpose of this study was to evaluate posttraumatic growth among breast cancer patients and their significant others over a 1-year time span after diagnosis and to examine cognitive and emotional processes in posttraumatic growth.

METHODS: One hundred sixty-two women with breast cancer and their partners completed surveys assessing posttraumatic growth, cognitive and emotional processing, and marital satisfaction at 3 time points spaced 9 months apart.

RESULTS: Posttraumatic growth increased for both partners during this period. Patient posttraumatic growth was predicted by younger age, contemplating reasons for cancer, and more emotional expression at time 1. Partner posttraumatic growth was predicted by younger age, more intrusive thoughts, and greater use of positive reappraisal and emotional processing at time 1.

CONCLUSION: Posttraumatic growth is reported by patients and by significant others. Cognitive and emotional processes predict growth. Patient growth is associated with the significant other’s cognitive and emotional processing of breast cancer.

Key Words: posttraumatic growth, • breast cancer, • couples, • cognitive processing, • affective processing.

Abbreviations: PTGI = Posttraumatic Growth Inventory;; ECOG = Eastern Cooperative Oncology Group;; DAS = Dyadic Adjustment Scale;; CARES = Cancer Assessment Rehabilitation Evaluation Survey.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
Life events such as the diagnosis of early-stage breast cancer have the potential to be stressful and to evoke a wide range of psychological reactions (1). Patients deal with a number of negative experiences, including medical treatments and their side effects such as fatigue, pain, and hair loss; temporary and permanent changes in physical appearance; alterations in future life plans; and the threat of future disease recurrence. These experiences may evoke negative psychological reactions. Indeed, studies have reported that between 7% and 46% of women with early-stage breast cancer report clinically significant levels of depressive symptoms within the first 6 months of diagnosis, and between 32% and 45% of women report clinically significant anxiety (2,3). However, the struggle to deal with these experiences can also result in positive changes in views about oneself and one’s relationships. There have been a number of terms used to refer to positive psychological changes individuals may undergo, including identity reconstitution (4) and self-transformation (5). Tedeschi and Calhoun (6,7) have coined the most widely used term, posttraumatic growth, to refer to the spectrum of positive changes an individual may experience after a traumatic event.

Most research to date on posttraumatic growth has focused on quantifying the prevalence and domains of positive changes reported by survivors of traumatic events. The empirical literature has suggested that individuals who experience stressors such as myocardial infarction (8) and sexual assault (9) report positive changes after these experiences. Evidence suggests that posttraumatic growth is also relatively common among adults with cancer. The available data suggest that between 60% and 90% of cancer survivors (10–12) report positive changes. Positive effects reported by cancer patients have covered the gamut from existential changes such as vastly altered views about spirituality to behavioral changes such as improved health practices.

Relatively few scales have been validated to evaluate posttraumatic growth. The vast majority of studies of this phenomenon have used qualitative methods, typically interviewing patients to ask them about positive changes and coding responses into categories (eg, 5,12). Several instruments have been developed recently to quantify positive changes (eg, 13). One measure that has been empirically validated is the Posttraumatic Growth Inventory (PTGI; 7). The scale has 5 domains: change in relationships with others, realization of new possibilities, increased personal strength, spiritual changes, and changes in appreciation for life.

With the advent of positive psychology (eg, 14), the clinical and research communities have grown increasingly interested in this phenomenon. However, there are a number of unanswered questions. Among the most important questions is how prevalent positive changes are at the time of the onset of the traumatic event. Most data on the prevalence of growth among cancer patients have been collected far after the experience has occurred (15,16). This approach is adopted because it is hypothesized that growth takes place after an extended process of working through the experience. However, it is likely that people make positive changes during and immediately after a traumatic experience. Indeed, recent studies have shown that between 20% and 80% of people report positive changes shortly after a traumatic event (9). For a more complete understanding of the growth process, more information about growth during and shortly after the experience is necessary.

A second question relates to the longitudinal course of growth. The few studies that have examined positive changes after cancer treatment have not followed participants longitudinally (eg, 17). In their cross-sectional study of breast cancer survivors, Cordova et al. (17) reported that greater posttraumatic growth was associated with a longer time since diagnosis, suggesting that growth increases over time after an initial diagnosis of cancer. A longitudinal perspective can provide information to both researchers and clinicians about the natural trajectory of posttraumatic growth and its individual variability. A third question concerns predictors of the course of posttraumatic growth. Most of the focus in the cancer literature has been on clarifying the relationship between posttraumatic growth and distress (eg, 11). Less is known about factors that contribute to the course of growth. According to cognitive-affective-social processing theories of trauma (eg, 18–20), stressors will not elicit positive change; they must be perceived as sufficiently threatening to one’s life to challenge basic beliefs and elicit coping responses (21). Individuals who cope best with traumatic experiences actively contemplate and work through or process their experience using cognitive, affective, and interpersonal processing strategies. Three cognitive processes that have been identified are not suppressing intrusive memories about the experience so that memories can be processed (19,22), searching for a reason that the experience happened so that the person can assimilate this information into the processing, and attempting to find meaning in the experience (23). The affective and interpersonal processes that have been identified are attempts to understand emotional reactions on one’s own or by talking about emotions and thoughts with others (20,24). Attempts to share feelings and understand emotional reactions to the traumatic experience either through directly venting one’s emotions or processing one’s emotions are also thought to facilitate psychological growth (24). Cognitive-affective-social processing models suggest that the more an individual actively thinks about the circumstances and feelings and implications of the experience and tries to make sense of them, the more likely posttraumatic growth will occur (6). These theories propose that the timing of processing early in the experience is a key predictor of outcome. Early in an experience, intrusive thoughts that are allowed to occur and be actively processed rather than resisted or pushed down are likely to result in a better psychological outcome (18). Similarly, the search for cause and meaning, if not prolonged and ruminative, is also viewed as constructive (22). Previous work on posttraumatic growth in breast cancer survivors is consistent with cognitive-social processing models. Cordova et al. (17) examined the cross-sectional association between perceived threat of breast cancer and 1 indicator of social processing, the degree to which patients talked about the cancer experience in the past, with posttraumatic growth in their sample of breast cancer survivors. They found that perceived threat and previous talking about the cancer were associated with more growth.

A fourth unanswered question is whether growth is restricted to the person directly affected by the traumatic experience. Although the conceptualization of trauma has recently been expanded to include people who witness the event (25), the literature on posttraumatic growth has focused almost exclusively on people directly affected by the experience, with little attention to the fact that close family members may also make positive psychological changes after trauma. Early evidence suggests that these changes occur. In a recent cross-sectional study, Weiss (26) studied husbands of early-stage breast cancer survivors using the PTGI and found that husbands reported posttraumatic growth and positive benefits 3 or more years after diagnosis.

A fifth question is how growth unfolds in the context of a marital relationship. The literature on posttraumatic growth does not take a dyadic approach to understanding this phenomenon. Because couples typically face cancer together and their distress reactions are closely linked (27), it is important to look at the correspondence between couples’ positive changes. Few studies have examined positive psychological changes at the couple level. Weiss (26) recently compared breast cancer survivors’ and husbands’ posttraumatic growth and found that husbands evidenced lower levels of growth than survivors. Little is known about the correspondence between couples’ positive psychological changes over time and factors that predict differences between couples’ growth trajectories.

This study had 3 aims. The first aim was to characterize the longitudinal course of posttraumatic growth at the individual level for patients and partners over a 1-year time span after breast cancer diagnosis. We predicted that growth would increase significantly over time. The second aim was to evaluate the longitudinal associations between individual cognitive processing (intrusions, the search for meaning and reason for developing breast cancer, positive reappraisal) and affective-interpersonal processing (emotional expression and emotional processing) and the course of posttraumatic growth for patients and partners. Based on cognitive and affective-interpersonal processing theory, we hypothesized that early intrusions and a search for meaning and reason for the cancer that resolved (decreased over time) would predict an increase in posttraumatic growth over time, and that early positive reappraisal coping and emotional processing would predict an increase in posttraumatic growth for both partners. Our third aim was to take a couple-level perspective on the growth process. We compared couples’ levels of growth over the 1-year postdiagnosis period and examined predictors of discrepancies between couples’ growth trajectories. We had 2 predictions. First, we predicted that patients would evidence more posttraumatic growth than partners. Second, we predicted that partner cognitive and affective-interpersonal processing would influence patient growth. Specifically, we predicted that patients in relationships with partners who reported more cognitive (ie, more positive reappraisal, contemplating reasons for the cancer) and interpersonal processing (ie, more emotional expression) would report more growth. In our consideration of couples’ growth, we also took into account marital quality. We proposed that that couples who were in higher-quality relationships would evidence more couple-level growth. In all analyses, we took into account medical variables such as stage of disease, physical impairment, and time since diagnosis, because we proposed that objective indicators of the stressful life event could predict posttraumatic growth. To assess these aims, we studied women with early-stage breast cancer and their partners at 3 time points: shortly after surgery, and 9 and 18 months afterward.

	METHODS

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
Participants
The present analyses are part of a larger study of the effect of breast cancer on marital relationships (28,29). Participants were 162 women with breast cancer who had recently undergone surgery who were married or cohabitating and their significant others. The mean age of the patient participants was 49 years (range, 29–74 years), and of their partners, 51 years (range, 29–76 years). Median family income level as reported by patients was $85,000. Seventy-eight percent of patients and 82% percent of partners completed at least a high school degree. The majority of patients (91%) and partners (92%) were white. Ninety-eight percent of couples were married (the remaining were cohabiting). For married patients, the average length of the relationship was 22 years (range, 0.2–57 years; SD, 12.6). Among cohabiting patients, the average length of the relationship was 13 years (range, 5–22 years; SD, 6). Three couples were same-sex pairs.

Approximately 34% of the sample was diagnosed with stage 1 disease, 37% of the patients were diagnosed with stage 2 disease, 27% of the patients were diagnosed with stage 3A disease, and 3% were diagnosed with ductal carcinoma in situ. The majority of patients had undergone lumpectomy (68%) or modified radical mastectomy (19%). The average amount of time since diagnosis was 4 months (range, 1–10 months), and the median amount of time since diagnosis was 4 months. Thirteen percent of women were diagnosed within 2 months before completing the baseline survey, and 6% of women were diagnosed between 8 and 10 months before completing the baseline survey. After surgery, the majority of patients had radiation and chemotherapy and tamoxifen/raloxifene (N = 55; 34%), chemotherapy only (N = 32; 20%), chemotherapy plus tamoxifen/raloxifene (N = 32, 20%), or chemotherapy and radiation (N = 27; 17%). The remaining participants received surgery only (N = 2), radiation and hormonal therapy (N = 6), radiation only (N = 3), or tamoxifen/raloxifene only (N = 4). At the time of recruitment, 89% of patients (N = 144) were receiving chemotherapy, 8% were undergoing radiation therapy (N = 13), 1 patient was receiving hormone therapy, and 2 patients were not undergoing any treatment. In terms of Eastern Cooperative Oncology Group (ECOG) performance status at time 1, 54% had a rating of 0 (no symptoms, fully active, able to work), 46% had a rating of 1 (symptomatic, but not spending extra time in bed; able to do light work). At time 2 (9 months later), 63.3% of patients who were still participating in the study were on hormone therapy but had completed radiation or chemotherapy or both, 25% of patients were not on any form of treatment, and 3% of patients were still undergoing either chemotherapy or radiation therapy. Ninety-three percent had an ECOG performance status of 0. At time 3 (18 months later), of the patients who were still actively participating in the study, all had an ECOG performance rating of 0. Fifty-eight percent of patients were receiving hormone therapy, 6% of patients were still undergoing either chemotherapy or radiation, and 39% of patients completed treatment and were not receiving any form of therapy (including hormone therapy).

Procedure
Patients were approached for study participation from the outpatient clinics of oncologists practicing in 3 comprehensive cancer centers in the Northeastern United States or in several smaller community hospital oncology practices. Criteria for study inclusion were as follows: a) patient had a primary diagnosis of ductal carcinoma in situ or stage 1, 2, or 3a breast cancer; b) patient had a ECOG performance status at recruitment of 0 or 1; c) patient had breast cancer surgery; d) patient and partner were 18 years old or older; e) patient and partner able to give informed consent; f) patient and partner were English speaking; and g) patient was currently married or living with a significant other of either gender.

Four hundred patients were approached for study participation by a research assistant. Eligible patients were identified and approached either after an outpatient visit or by telephone contact. Participants were given a written informed consent and the study questionnaire to complete and return. All participants signed an informed consent form approved by the Institutional Review Board. One hundred sixty-two couples completed the baseline survey (41% acceptance). Two hundred forty couples refused the study. The most common reason for refusal provided was that the patient was too busy. The majority (62%) did not provide a reason. Comparisons were made between patient participants and refusers with regard to available data (age, ethnicity, cancer stage, performance status). Results indicated that study participants were significantly younger (mean, participants, 50.1 years, SD, 9.9; mean, refusers, 53.5 years, SD, 11.3; t[408] = 3.7; p < .001) and had lower performance status ratings on the ECOG scale (79% of refusers had a score of 0 [no symptoms]; 51% of participants had a score of 0 [no symptoms]; ² = 40.7; p < .001). There were no differences between participants and refusers in terms of ethnicity (white vs. nonwhite) or cancer stage. We were not able to compare partner refusers with participants because we did not have data available on partner refusers.

Patient and partner completed surveys immediately on consenting to the study (time 1) and at 9 months (time 2) and 18 months (time 3) after they consented to the study. Both partners returned surveys by mail.

Measures Administered to Both Partners
Posttraumatic Growth
The PTGI (7) is a 21-item scale that assesses positive change in the following areas: new possibilities (5 items: "I developed new interests"), relating to others (7 items: "A sense of closeness with others"), personal strength (4 items: "Knowing I can handle difficulties"), spiritual change (2 items: "I have a stronger religious faith"), and appreciation for life (3 items: "An appreciation for the value of my own life"). Items were rated on a 6-point Likert scale (0 = "This did not change as a result of my/my partner’s cancer," to 5 = "This changed to a very great degree as a result of my/my partner’s cancer"). Instructions for partners asked them to rate how much they changed as a result of their partner’s cancer. Sum scores were used in the analyses. Internal consistency for patient and partners for the PTGI total scale was 0.95, 0.96, and 0.96 for patients at times 1, 2, and 3, respectively, and 0.94, 0.97, and 0.91 for partners at times 1, 2, and 3, respectively.

Intrusion
The intrusion scale of the Impact of Events Scale (30) was used to assess intrusive ideation about breast cancer and its treatment. The intrusion scale consists of 7 weighted Likert items (1 = not at all, 3 = sometimes, 5 = often) that assess involuntary intrusive thoughts. Participants were asked to rate intrusive thoughts about cancer in the last week. Internal consistency for patients, as calculated by coefficient á, was 0.86, 0.88, and 0.86 at times 1, 2, and 3, respectively. Internal consistency for partners, as calculated by coefficient á, was 0.84, 0.89, and 0.85 at times 1, 2, and 3, respectively.

Search for Meaning and Reason for Cancer
Three items evaluated the degree to which the participants tried to find some meaning in the cancer experience ("How often have you tried to find some meaning in the cancer experience?": search for meaning), tried to understand why they or their partners were diagnosed with cancer ("How often have you tried to understand why you [your partner] was diagnosed with cancer?": search for cause), and how often they found themselves thinking about the reason for their or their partner’s cancer ("How often have you found yourself thinking about the reason for your [your partner’s] cancer?": contemplate reason). All items were rated on a 5-point Likert scale (1 = not at all, 5 = a great deal) and rated for processing in the past month.

Positive Reappraisal
Positive reappraisal was assessed using COPE subscale (31). This subscale has shown good internal consistency in other studies of women with breast cancer (32) but has not been administered to partners. Participants selected a stressor from a list of 5 stressors they experienced in the past month and provided ratings on dealing with the stressor. Internal consistency for the positive reappraisal scale for patients was 0.82, 0.81, and 0.82 at times 1, 2, and 3, respectively, and for partners, internal consistency was 0.78, 0.66, and 0.78 at times 1, 2, and 3, respectively.

Emotional Processing
The Emotional Processing scale (33) was used. This scale has 2 subscales: emotional expression (eg, "I took time to express my emotions") and emotional processing (eg, "I tried to figure out what my feelings meant"). The scale has been used with breast cancer patients (29), but not with partners. Internal consistency for the emotional processing subscale was 0.60, 0.62, and 0.58 for patients at times 1, 2, and 3, respectively, and 0.68, 0.65, and 0.66 for partners at times 1, 2, and 3, respectively. Internal consistency for the emotional expression subscale was 0.80, 0.86, and 0.78 for patients and 0.66, 0.63, and 0.68 for partners at times 1, 2, and 3, respectively.

Marital Satisfaction
Both partners completed the Dyadic Adjustment Scale (DAS) (34). The DAS is a widely used measure of satisfaction with intimate relationships composed of 32 items assessing consensus, satisfaction, cohesion, and affectional expression. Responses are made in different multiple-choice formats. Higher scores represent higher marital quality. Internal consistency for both patients and partners was 0.93 (time 1) and 0.94 (times 2, 3).

Measures Administered to Patient Only
Medical Variables
Data regarding the patient’s disease stage (1 to 3a), treatment status (chemotherapy or radiation, no treatment), time since diagnosis, and ECOG symptom ratings were obtained from the medical chart.

Physical Impairment
Physical impairment was assessed with the functional status subscale of the Cancer Rehabilitation Evaluation System (CARES) (35). Twenty-six items assessed patients’ functional disability caused by the cancer and its treatment (eg, "I have difficulty doing household chores"). Participants rated the degree they experienced each difficulty during the past month from 0 (not at all) to 4 (very much). Higher scores indicated greater impairment. Internal consistency for the CARES was 0.92, 0.92, and 0.90 at times 1, 2, and 3, respectively.

Outline of Analyses
The longitudinal data were analyzed using a growth curve models approach. Growth curve analyses are designed to understand rates of change in outcome variables over time. For example, in the present study, patient PTGI is 1 of the outcome variables. Growth curve analyses examine individual differences among patients in their baseline levels of PTGI and individual differences in the rates at which PTGI scores change over time. Individual differences in the rates of change are compared with the average rate of change for patients as a group. If there are no differences in individual rates of change over time, the model is analyzed as a simple repeated measures design. If there are differences in individual rates of change over time, the explanatory variables are assessed to determine whether they can account for these differences. Growth curve analyses require the use of mixed linear model approach, which is also referred to as a random effects or hierarchic linear model (36,37). The Statistical Analysis System (SAS) procedure mixed implements a MIXED linear model approach to the analysis of growth curve and repeated measures models.

We conducted analyses of individual growth (separate patient and partner models) and couple-level growth (2 models). The individual patient and partner growth curve models were developed using a 6-step hierarchic procedure. The first step of model building was to determine whether there were significant differences among patients (or partners) in their baseline PTGI scores (in the intercepts), the slopes describing the effects of the passage of time on growth, and the covariances between the intercepts and the slopes. If there were differences in patients’ (or partners’) initial PTGI scores or rates at which their PTGI scores changed over time or both, efforts to explain these differences were evaluated at each subsequent stage of model construction. The second step of model building was to examine the role of potential demographic predictors of posttraumatic growth. To keep the complexity of the models that were used in this analysis to a minimum, only demographic variables that were significantly correlated with PTGI scores at the 3 time points were included in the final model. Potential demographic candidates included age, ethnicity, education, and family income. The third step of model building (for the patient model only) involved examining the contribution of medical variables. To keep the complexity of the models used in this analysis to a minimum, only those medical variables that were significantly associated with PTGI scores at the 3 time points were included in the final model. The medical variables examined included patient ECOG score, time since diagnosis, cancer stage, treatment status at all time points (receiving chemotherapy or radiation/completed treatment), and physical impairment (CARES). The fourth step of model building was to assess the contribution of cognitive processes (intrusion, search for reason, search for meaning, contemplate reasons, positive reappraisal). The fifth step of model building involved examining the role of emotional processes (emotional processing, emotional expression). The final step of model building involved determining whether there were significant differences in the rates at which posttraumatic growth changed over time (ie, the slopes). To examine this possibility, we examined differences in trajectories over time. Using a growth curve modeling perspective, explanations of slope differences were evaluated using interaction terms of the time variable and cognitive and emotional processes. If the interaction term accounted for significant differences in slopes, then the variance component for the slopes should have become nonsignificant.

The 162 patients and partners who completed the first assessment formed the basis of the individual patient and partner growth curve analysis. Patients or partners who did not complete 1 or both of the follow-ups were included if they provided all time 1 information. There were 141 patients (21 dropouts or missing) and 135 partners (27 dropouts) with complete time 2 data and 120 patients (42 dropouts) and 115 partners (47 dropouts) with complete time 3 data. With mixed linear models, missing data on all variables can be estimated for the parameters for the participants with full data and missing data (38). The statistical program does not impute the data; rather, partial data (eg, time 1 and 2, no time 3) are used along with data from participants with all 3 time points to estimate the parameter. The ability to handle missing data in this manner is a characteristic of mixed linear models.

We considered 2 approaches to analyzing the couple-level data because there is no consensus regarding how to analyze couple-level data. The approaches that have been used are a mean score approach and a discrepancy score approach (39). The mean score approach entails averaging couples’ PTGI scores and all predictors. The discrepancy approach entails using the difference between patient and partner PTGI scores as the dependent variable. In a discrepancy score model, predictors remain at the individual level (eg, patient intrusions, partner intrusions). We selected the discrepancy approach to analyze couple-level data for 2 reasons. First, discrepancy scores are easier to interpret than mean scores. Mean scores reflect the couple as a whole. Once couples’ scores are averaged, it is difficult to determine whether the average score masks differences between women and their partners. For example, a high average could reflect high scores for both partners or a high score for either partner, which would contribute to difficulty interpreting results. With a discrepancy score approach, partner PTGI scores are subtracted from patient PTGI scores to yield discrepancy scores. Positive discrepancy scores indicate that the patient had a higher rate of growth than the partner, whereas negative discrepancy scores indicated that the partner had a higher rate of growth than the patient. The second reason we selected the discrepancy approach is that this approach is consistent with previous studies evaluating couples coping with illness, which have used the incongruity hypothesis (40). High absolute difference scores suggest an incongruity between patient and partner growth, and a greater incongruity in growth between partners could potentially strain the relationship. In the present study, the discrepancy model was built using the same steps as for the individual models (demographic, medical, cognitive, affective-social processes), with 1 exception: marital satisfaction was added into the couple model after demographic variables.

	RESULTS

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
Patient Posttraumatic Growth
Longitudinal Course of Patient Posttraumatic Growth Inventory
Descriptive statistics for all variables included in the model are shown in Table 1. As described, the first step of model building was to examine the longitudinal course of PTGI. Growth curve analyses determined whether there were significant differences among patients in their baseline PTGI scores (in the intercepts), the slopes describing the effects of the passage of time on growth, and the covariances between the intercepts and the slopes. Results of the first step of growth curve modeling indicated that there were no significant differences among the women in the rates at which PTGI changed over time (ie, no slope differences among the women). For all women, on average, there was a significant increase in PTGI over time (F = 8.63; p = .0037). The intraclass correlation of 0.66 indicated that there was a consistent pattern of change over time.

View larger version (12K): [in this window] [in a new window]   Figure 1. Plot of the interaction between Time x patient emotional expression predicting patient PTGI. *, 1 SD below the mean for patient emotional expression; , 1 SD above the mean for patient emotional expression.

Predictors of the Longitudinal Course of Partner Posttraumatic Growth Inventory
For partners, the hierarchic procedure of adding variables to the model was changed slightly. Although partner demographic variables were assessed, patient medical variables were not included in partner analyses. The results of step 2 of the model building procedure indicated that the only significant partner demographic variable was age, and therefore, only this predictor was included in the final model.

The second panel of Table 2 summarizes the final model. Younger partners were more likely to have higher PTGI scores (p = .0004). Among the cognitive variables added in step 3 of model building, 2 cognitive variables, intrusions and positive reappraisal, were significant predictors of partner growth. Partner intrusive thoughts were associated with increased growth over time (p = .023). Partner positive reappraisal was also associated with increased partner growth over time (p = .003). No emotional processes added in step 4 were significant. The final step of model building involved examining the contribution of interactions between time and cognitive and emotional processes in growth. The results revealed 2 significant interactions, shown in the second panel of Table 2. The first significant interaction was between time of assessment and partner positive reappraisal (p = .017), which is plotted in Figure 2A. The test for the significance of the slopes indicated that growth for partners who were 1 SD below the mean on positive reappraisal decreased significantly over time (t = –2.24; p = .03), whereas the decrease in growth over time for partners 1 SD above the mean was not significant (t = –0.89; p = .38). The second significant interaction was between the time of assessment and partner emotional processing (p = .02), which is plotted in Figure 2B. The test for the significance of the slopes indicated that partners who were 1 SD below the mean on emotional processing reported significantly lower growth over time (t = –2.13; p = .04). However, the decrease for partners who were 1 SD above the mean was not significant (t = –1.05; p = .29).

View larger version (11K): [in this window] [in a new window]   Figure 2. A: Plot of the interaction between time by partner positive reappraisal predicting partner PTGI. *, 1 SD below the mean for positive reappraisal. , 1 SD below the above for positive reappraisal. B: Plot of the interaction between time by partner emotional processing predicting partner PTGI. *, 1 SD below the mean for partner emotional processing. , 1 SD above the mean for partner emotional processing.

Predictors of Couples’ Growth
Both patient and partner characteristics were included in analyses (eg, patient intrusions, partner intrusions). Variables were entered into the model into the following order: patient variables, partner variables, significant interaction terms. It should be noted that, because marital satisfaction was included in this analysis, the sample size was 148 couples because of missing data on the DAS.

Before analyzing predictors of couple discrepancy scores, changes over time for each couple were graphed. These graphs indicated that the discrepancies for many couples decreased over time, whereas an approximately equal number of couples evidenced greater discrepancies over time. The remainder showed no change. These graphs suggested the possibility that there might not be a main effect for time. Indeed, the mixed model having only time as a main effect was not significant (t = 0.09; p = .76), although there were clear differences among the couples around this horizontal slope (z = 2.46; p = .007), confirming the graphical findings. Not surprisingly, the correlation between couple PTGI discrepancy at time 1 and changes in slopes was not significant (z = –0.22; p = .83). The reason for the low correlation is that, for many couples, initial discrepancies increased over time, whereas for other couples, initial discrepancies decreased. These findings suggested that a model that included interaction terms between time and patient and partner cognitive and emotional processing variables might be able to clarify discrepancy changes over time.

Among the demographic and medical predictors, only age and physical impairment were significantly associated with growth, and therefore, only these 2 variables were included in the final model. Variables were placed into the model in the following order: time, patient age, patient physical impairment, patient DAS, and patient cognitive and emotional processes, followed by partner variables (other than impairment) in the same order. Table 3 summarizes the results of the discrepancy score analysis. Only 1 patient cognitive or affective variable was a significant predictor of discrepancy. If a patient reported higher levels of contemplation about the causes of her cancer, her growth exceeded her partner’s growth. Among partner demographic variables, partner age was significant. As partner age increased, patient growth was greater than that of the partner. Because there was an interaction between partner emotional expression and time, we will reserve the discussion of the effect for partner emotional expression for the presentation of the interaction analyses.

View larger version (10K): [in this window] [in a new window]   Figure 3. A: Plot of the interaction between time by patient physical impairment predicting discrepancy between patient and partner PTGI. Higher scores on the discrepancy measure indicate patient PTGI is higher than partner PTGI. *, 1 SD below the mean for patient physical impairment. , 1 SD above the mean for patient physical impairment. B: Plot of the interaction between time by partner positive reappraisal predicting discrepancy between patient and partner PTGI. Higher scores on the discrepancy measure indicate patient PTGI is higher than partner PTGI. *, 1 SD below the mean for partner positive reappraisal. , 1 SD above the mean for partner positive reappraisal. C: Plot of the interaction between time by partner emotional expressiveness predicting discrepancy between patient and partner PTGI. Higher scores on the discrepancy measure indicate patient PTGI is higher than partner PTGI. *, 1 SD below the mean for partner emotional expressiveness. , 1 SD above the mean for partner emotional expressiveness.

	DISCUSSION

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
This study is the first attempt to use longitudinal design to examine posttraumatic growth after cancer among patients and their partners. The results revealed 3 key findings. First, shortly after diagnosis, patients and partners reported positive psychological changes, and posttraumatic growth increased for both patient and partner over the 1-year period they were followed. Second, cognitive and emotional processes contributed to increases inpatient psychological growth, but fewer variables predicted partner growth. Third, our findings for couple-level growth illustrated the importance of considering the dyadic context when attempting to understand patient and partner posttraumatic growth.

Patient Growth
Our analyses revealed that women with breast cancer reported positive changes in their lives relatively shortly after being diagnosed. Although the magnitude of growth was not as high as growth reported in studies of longer-term breast cancer survivors (17), women reported that they developed closer relationships with others, appreciated their lives more, recognized their positive qualities and strengths, and developed a better understanding of spiritual matters. These findings are consistent with those of other studies of women undergoing other traumatic events (eg, 9) and do not support the contention that growth happens only after an extended period after cancer diagnosis. In addition, there were gradual increases in all posttraumatic growth domains over the 1-year period we followed women. Increases in posttraumatic growth were seen in a sense of personal strength, the realization of new possibilities, and new appreciation of life and for relationships with others, which is consistent with findings reported by Cordova et al. (17).

The demographic and cognitive and emotional processes examined accounted for changes in patients’ growth trajectories over time. Younger age was the only demographic predictor of posttraumatic growth, which has not been reported in previous studies of breast cancer survivors (17,26). There are 2 potential explanations for this finding. First, a breast cancer diagnosis is less normative, more threatening, and more distressing for younger women (41). The greater threat may prompt more growth. Second, younger women may be more aware of and influenced by expectations to adopt a positive attitude and thus may evidence more growth.

Our results suggested that some cognitive processes were related to patient growth, whereas some cognitive processes were not related to growth. Women who contemplated more the potential reasons why they might have developed breast cancer had more growth over time. Engaging in more attempts to search for meaning in breast cancer was marginally associated with gains inpatient growth. These results are consistent with cognitive processing theory, which proposes that the more a person actively tries to make sense of an experience, the greater the chances for posttraumatic growth (6,23). However, other cognitive processes, including intrusions, searching for a cause for developing breast cancer, and positive reappraisal, were not associated with growth. Why were some indicators of cognitive processing related to growth whereas others were not? A likely explanation is that not all cognitive processes facilitate growth. Indeed, previous studies have not consistently reported associations between all cognitive processes and growth. Previous studies examining the role of intrusions have not consistently reported an association between intrusions and growth among breast cancer survivors (17). Searching for a cause of one’s breast cancer may lead to self-blame, which is associated with poorer adaptation to breast cancer (42). Patients discriminate between cognitive processes, and not all processes facilitate growth. Future studies of contributors to growth should carefully distinguish between cognitive processes.

In terms of emotional processing, we found that emotional expression (eg, expressing inner feelings) predicted growth, whereas emotional processing (eg, delving into the meaning of feelings) did not predict growth. Patients who evidenced above-average emotional expression about cancer over the 3 assessment time points maintained higher posttraumatic growth across time. In addition, the interaction between time and emotional expressiveness indicates that it is the sustained effort to express emotions over time that is crucial to subsequent growth. This finding is consistent with social processing models suggesting that emotional expression facilitates adaptation and growth after crisis (33), and with a large body of literature suggesting that affective expression and experiencing are critical components of therapeutic growth and change (43,44). How might emotional expression facilitate growth? First, through expression of negative emotions, one might desensitize oneself to negative feelings (45). The reduction in negative feelings may allow for more focus on positive feelings and benefits (46). Second, expression of feelings may facilitate growth through feedback about one’s personal strength and prompt consideration and recognition of ways cancer has changed one’s life (ie, "You are such a brave person!" enhances personal strength). Third, at least 1 domain of growth, relationships with others, could be directly affected by emotional expression: enhanced closeness in relationships can be a direct consequence of emotional self-disclosure (47). Supportive reactions to such expressions would directly reinforce the feeling that others are compassionate and would enhance closeness.

In contrast, emotional processing (eg, attempts to delve into the meaning of feelings) was not associated with posttraumatic growth. Our findings are consistent with the findings of Stanton et al. (33) suggesting that emotional processing is not predictive of adaptation. Persistent engagement in attempts to understand one’s emotions that begins shortly after diagnosis and continues for as long as 18 months may become a ruminative process, and rumination has been shown to contribute to distress reactions in previous studies (48,49). Our findings regarding emotional processing are particularly interesting when considered together with our results indicating that emotional expression and 1 dimension of self-searching (contemplating the reason for breast cancer) were associated with growth. Taken together, our results indicate that cognitive self-searching may facilitate growth more than emotional self-searching. There are at least 2 potential explanations for this pattern of results. First, these findings are consistent with the hypothesis that emotional expression about a stressful event that is accompanied by an attempt to make sense of the stressful event promotes posttraumatic growth (50). However, we did not evaluate the impact of engagement in both emotional expression and cognitive self-searching. Future studies should examine whether there is a greater combined impact of emotional expression with cognitive self-searching compared with emotional expression or cognitive self-searching alone. Second, it is possible that the findings are a reflection of the measurement methodology. Although our measure of intrusions was lengthy, single-item measures of searching for meaning, searching for cause, and contemplating reason were used. Our measures of emotional processing and emotional expression were also relatively brief, consisting of 4 items. Future studies should include more comprehensive measures of cognitive processes. In addition, future studies should carefully assess emotional and cognitive processes using qualitative methods to gather in-depth information about what happens when women delve into their emotions to try and understand them compared with what happens when women endeavor to understand the meaning and reason for their cancer.

Partner Growth
Partners also reported positive changes after the breast cancer diagnosis. Although the magnitude of partner growth was not as high as posttraumatic growth reported in other studies of husbands of breast cancer survivors (26), our findings indicate that posttraumatic growth is not limited to the person directly affected by the event, and that positive psychological changes may also extend to close family members. Our findings are consistent with newer conceptualizations of trauma suggesting that people who witness an event are also vulnerable to posttraumatic stress reactions (25) and are similar to results reported by Weiss (26) in her study of husbands of 3-year to 5-year breast cancer survivors. Gradual increases in all domains of growth over the period of 1 years were also noted for partners. The domains of growth evidencing the greatest gains were similar to those found for patients, with increased sense of personal strengths and new possibilities for life. Lower-magnitude gains were shown for appreciation of life, relationships with others, and spirituality. It is interesting and not surprising that partners reported less posttraumatic growth than patients. Because the direct threat to life and exposure to traumatic experiences such as chemotherapy and surgery are encountered directly by patients, the potential for growth is likely to be greater for patients than partners.

Other than age, predictors of partner growth differed from predictors of patient growth. Among the cognitive processes studied, intrusive thoughts, positive reappraisal, and emotional processing were all associated with more partner growth, but none of these variables was associated with patient growth. Our finding that intrusion is predictive of growth is consistent with cognitive processing models maintaining that intrusions are an indication that people are working to integrate the event into their world view (51–53). The effects of positive reappraisal depended both on the level of positive reappraisal and on time. Partners who reported below-average engagement in positive reappraisal reported significantly lower growth over time, whereas partners who reported above average engagement in positive reappraisal did not report a decline in their original levels of growth. These differences suggest that partners who work at finding the silver lining in the cancer experience may also find it easier to perceive positive changes in themselves and their relationships as a result of their partner having breast cancer. The effects of partner emotional processing also depended on the time of assessment. Partners who were below average in attempts to understand their feelings were more likely to report a significant decline in their growth over time. These findings are consistent with cognitive-affective processing theories suggesting that trying to understand and integrate one’s emotional reactions to a traumatic experience are likely to lead to posttraumatic growth. However, as with our findings for patients, not all cognitive and affective processing variables were associated with partner growth. In addition, as noted, the cognitive and affective variables predicting partner growth were completely different from the variables predicting patient growth. It is possible that the psychological processes underlying posttraumatic growth of individuals directly affected by a difficult life experience differ dramatically from those processes underlying posttraumatic growth of family members indirectly affected by the same life experience. However, as noted, it is also possible that our results reflect limits of our measures cognitive and emotional processing.

Couple Growth
One of the most interesting aspects of this study was the couple-level analyses. We had 5 key findings. First, patients who reported higher levels of contemplation about the reasons for their cancer evidenced more growth over time than their partners, which is consistent with the individual patient model results. Second, the effect of physical impairment on discrepancies between patient and partner growth was a function of both level of impairment and time. Over time, patients who reported less physical impairment reported more growth than their partners, whereas patient growth and partner growth were more similar if the patient reported more physical impairment. Because we did not find any effects for physical impairment on patient or partner growth in the individual-level models, the role of physical impairment should be re-examined in future studies. Third, the effect of partner positive reappraisal on discrepancies between patient and partner growth was also a function of time. There was an increasing level of congruence between patient and partner growth over time if the partner was above average in the use of positive reappraisal, whereas there was decreasing congruence between couples’ growth over time if the partner was below average in the use of positive reappraisal. Fourth, women whose partners were above average in their emotional expressiveness reported greater posttraumatic growth than their partners compared with women whose partners were below average in emotional expressiveness. These findings suggest that patient growth is not solely an individual activity. Patients report more growth when their partners discuss their own feelings. One explanation is that a more expressive partner sets the stage for open communication and more comfort for the patient to discuss her concerns, thereby promoting patient growth. Finally, it was surprising that marital quality did not predict couples’ growth. It is possible that marital quality is a consequence of growth rather than a predictor. It is also possible that marital quality is stable, particularly in the present sample of couples, in which the average relationship length was over 20 years. Thus, the variability in marital satisfaction might have been an issue. One caveat when considering the implications of these interactions is that the tests for the significance of slopes suggested that whereas there were significant differences between the 2 groups, individual slopes for both groups for all 3 interactions were not significant in any of the cases.

Limitations
Before closing, it is important to point out limitations. Most importantly, all measures were self-reported and thus subject to biases inherent with the self-report methods. Although patient PTGI ratings have been shown to be strongly correlated with partner ratings of the patient (26), our other measures are subject to this bias. Second, the construct of posttraumatic growth has been criticized. Psychoanalytic theorists propose that finding positive benefit is a defensive process (54). Asking people to judge changes in themselves and their lives after a negative life event may also be subject to the phenomenon of response shift. Response shift is an accommodative process whereby the person alters internal standards, values, and the meaning of quality of life (55). Evidence of response shift that is typically provided is that the quality of life of people with chronic illness is similar to that of healthy people (11). Posttraumatic growth could reflect an accommodative process whereby internal standards for judgments of quality of life change. A third limitation relates to the psychological domain that is being assessed by posttraumatic growth. The association between posttraumatic growth and other aspects of psychological distress and well-being has not been clarified. Although some studies have found that growth is not associated with distress or well-being (17), it is not clear whether posttraumatic growth truly reflects a positive psychological outcome. Positive psychological benefits could reflect societal pressure placed on breast cancer patients to think positively. Recent critiques of the positive psychology movement have suggested that the pressure to think positively is not always adaptive (14). A fourth limitation is the relatively high rate of study refusal. Although not surprising given that we asked both partners to complete surveys over a 1-year time span, the final sample may not be representative of the larger population of breast cancer patients. For example, patient participants were significantly younger and sicker than refusers. Our findings may also not generalize to individuals with other forms of cancer or to couples in which the patient is male. A fifth limitation regards the small number of same-sex couples in the study, and the fact that patients were female and most partners were male. Although the numbers of same-sex couples were too small to analyze separately, there may be differences with regard to the degree of communication and social processing of cancer between same-sex and opposite-sex couples. Previous research has suggested gender differences with regard to partner reaction and the effect of social support (56–58). More research is needed regarding potential differences in same-sex and opposite-sex couples’ reactions to cancer. Sixth, there was variability in our first assessment in the amount of time since initial diagnosis, and we were not able to evaluate the influence of amount of time since treatment was completed in our analyses. Both of these factors may have influenced the course of growth for couples. In addition, we did not measure personality constructs such as openness to experience, which may predict both the process of making positive changes and the cognitive, affective, and interpersonal processes underlying growth phenomena. Finally, although the interactions of time with impairment, partner positive reappraisal, and partner emotional processing accounted for some of the variability of the discrepancy scores over time, there was variability that was not accounted for. Future research should examine the role of other potential predictors of discrepancies in couples’ growth over time.

	CONCLUSION

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
These findings have clinical implications. Interventions that seek to facilitate patient growth would benefit from facilitating thoughtful self-searching about the reasons for their cancer and engagement in affective expression. If our insignificant findings regarding emotional processing and self-searching are replicated in other studies, patients who engage in persistent attempts to understand their emotional reactions may need to be redirected to other methods of dealing with breast cancer. Interventions seeking to facilitate partner growth (and couples’ growth) would benefit from a focus on positive reappraisal and conveying the importance of not pushing down or avoiding intrusive thoughts about their partner’s cancer. Interventions targeting couples might benefit from targeting partner emotional expressiveness. Overall, growth may be easier to facilitate in younger patients. Future research should use qualitative methods to evaluate why contemplating reasons for cancer contributed to growth, examine other potential predictors of growth such as optimism and acceptance, examine predictors of the separate domains of growth, and examine the link between posttraumatic growth and other psychological outcomes such as distress and well-being, using prospective analyses.

	ACKNOWLEDGMENTS

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION CONCLUSION ACKNOWLEDGMENTS REFERENCES

 
This study was supported by National Institutes of Health grant MH51246 and General Clinic Research Center grant RR00046, and by the Foundation of Hope for the Research and Treatment of Mental Illness.

Received for publication May 2, 2003.

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