Running Head: Spouses of Cardiac Patients
Address correspondence to:
Kerstin Schröder, Freie Universität Berlin, Studiengang Psychologie, Gesundheitspsychologie (WE 10), Habelschwerdter Allee 45, 14195 Berlin, Germany
(Fax: +49/30/838-5634; E-Mail: kschreod@zedat.fu-berlin.de)
Recovery from surgery can be facilitated by personal and social resources, such as optimistic self-beliefs and social support. Moreover, the existence of a social network and the behavior of its members can also have a positive effect. Patients (N = 381; 302 men, 79 women) undergoing heart surgery were surveyed once before and twice after their surgery. In addition, 114 social network members (18 men, 96 women), most of them spouses, reported about their own perceived resources at Time 1. It turned out that characteristics of spouses were related to patient characteristics. Recovery from surgery at Time 2 and readjustment to normal life after half a year (Time 3) could be partly predicted by spouses' perceived social support and optimistic self-beliefs (Time 1).
Keywords: quality of life, self-efficacy, social support, spouse, surgery, recovery
Readjustment after stressful life events depends to a certain extent on how social network members respond and provide support for one another. Recovery from surgery, for example, is not entirely determined by physical attributes, medical treatment and personality characteristics of the patients themselves, but can also be influenced by characteristics of their loved ones. It has been demonstrated that social support may facilitate recovery. Some studies have focused on the mere existence of social networks, whereas others have examined perceived or actually received social support (Fontana, Kerns, Rosenberg, & Colonese, 1989; King, Reis, Porter, & Norsen, 1993; Kulik & Mahler, 1989, 1993, Maes & Bruggemans, 1990; Maes, Leventhal, & de Ridder, 1996). The present study, using a longitudinal approach, takes a different perspective by exploring characteristics of spouses, in comparison to patients' characteristics, in terms of possible spousal impact on post-surgical patient adjustment. Previous studies have pointed to the crucial role that close network members may play after cardiac surgery, although the empirical evidence is inconsistent (Croog & Fitzgerald, 1978; Helgeson, 1993a, 1993b, 1993c; Waltz, 1986; Waltz & Badura, 1988).
Social support from others has been found to assist coping and to exert beneficial effects on various health outcomes for patients (Schwarzer & Leppin, 1989, 1991; Veiel & Baumann, 1992). Social support has been defined in various ways, for example as "resources provided by others" (Cohen & Syme, 1985), as "coping assistance" (Thoits, 1986), as "a resource for coping" (Endler & Parker, 1990), and as an exchange of resources "perceived by the provider or the recipient to be intended to enhance the well-being of the recipient" (Shumaker & Brownell, 1984, p. 13). Several types of social support have been investigated, such as instrumental support (e.g., assist with a problem), tangible support (e.g., donate goods), informational support (e.g., give advice), emotional support (e.g., give reassurance), among others. The definition and measurement problems involved in studying the social support construct, however, have remained debatable issues (Dunkel-Schetter & Bennett, 1990; Endler & Parker, 1990; Kessler, 1992; Pierce, Sarason, & Sarason, 1996; Sarason, Sarason, & Pierce, 1995; Schwarzer, Dunkel-Schetter, & Kemeny, 1994; Turner, 1992; Vaux, 1992).
Social support has been found beneficial in patients' recovery from heart surgery. Kulik and Mahler (1989) have studied men who had undergone coronary artery bypass graft surgery (CABG). Those who received many hospital visits by their spouses were, on average, released earlier from the hospital than those who received few visits. In a longitudinal study, the same authors also found that emotional support from their spouses had positive effects on patients after surgery (Kulik & Mahler, 1993). Similar results were obtained by other researchers (Fontana et al., 1989; King et al., 1993). Marital satisfaction was related to patients' well-being in a study by Waltz (1986). The only effective dependent variable was, however, negative affect. Helgeson (1993a) has found that patients' perceived availability of information support was a good predictor of recovery. Negative marital interaction predicted poor adjustment, and spousal disclosure predicted patients' life satisfaction. In a different analysis (Helgeson, 1993b) she found that social support never predicted any of the adjustment variables, but that the shift in household responsibilities from patient to spouse had a negative impact on later patient adjustment.
A conceptual issue is whether social support should be understood as an ongoing process of social coping, or rather as a potential resource factor that might facilitate adjustment to adverse conditions. Endler and Parker (1990), and Parker and Endler (1992) argue that social support should not be conceived of as a distinct coping dimension, but rather as a social resource or a set of social resources that may be available for a number of different coping strategies. They suggest that social support should be excluded from the category of "coping strategies" and should be added to the category of "coping resources." Moreover, they note that support seeking is not merely a subcategory of avoidant coping. On theoretical and empirical grounds they suggest that coping can be subdivided into task-oriented, emotion-oriented, and avoidant coping. The latter is reflected by either engaging in a substitute task (distraction) or by seeking out other people (social diversion), both being ways to avoid further stress (Endler & Parker, 1990; Parker & Endler, 1992, 1996). The authors acknowledge that a social network can be a resource, but they deny that seeking social support represents an active or instrumental way of coping, as many other authors have suggested (Carver, Scheier, & Weintraub, 1989; Hobfoll, Freedy, Green, & Solomon, 1996).
Endler and Parker (1990) emphasize that social support is not a specific coping mechanism, but rather "an important resource and moderator of coping activities" (p. 34). Thus, social support, a moderator, impacts the various coping dimensions "with respect to task-oriented coping, social support as problem-oriented and as related to seeking information, with emotion-oriented coping, social support provides emotional support and emotional regulation. Similarly, with avoidance strategies, social support may provide opportunities for diversion activities and escape" (Endler & Parker, 1990, pp. 34-35). In sum, the social support mechanism augments and assists coping styles in responding to and dealing with stress.
In the present study, social support is understood as a resource factor for both patients and for their spouses. Perceiving the availability of help or support in case of need can be a stabilizing factor that may facilitate social interaction among patients and partners and, thus, improve readjustment to stress. Both sets of variables, patients' and partners' perceived support, may reflect reciprocity within supportive social encounters. High levels of mutual support in both patients and spouses can provide an index of a well-functioning couple. Thus, it is of interest how these two support characteristics of both patients and their partners are interrelated and to what degree they independently contribute to the prediction of later readjustment to the patients' surgery.
In addition to social support, it is expected that coping competence of both patients and their partners may play an important role in the readjustment process. It has been found that optimistic beliefs in one's competence (perceived self-efficacy) facilitates all kinds of difficult behaviors, including rehabilitation. Perceived self-efficacy pertains to personal action control or agency and reflects the belief of being able to master challenging demands by means of adaptive action. It can also be regarded as an optimistic view of one's own capacity to deal with stress (Bandura, 1992). Patients with high efficacy beliefs are better able to control pain than those with low self-efficacy (Altmaier, Russell, Kao, Lehmann, & Weinstein, 1993; Litt, 1988; Manning & Wright, 1983). Self-efficacy has been shown to positively affect blood pressure, heart rate and serum catecholamine levels in coping with challenging or threatening situations (Bandura, Cioffi, Taylor, & Brouillard, 1988; Bandura, Reese, & Adams, 1982; Bandura, Taylor, Williams, Mefford, & Barchas, 1985). Cognitive-behavioral treatment of patients with rheumatoid arthritis enhanced their efficacy beliefs, reduced pain and joint inflammation, and improved psychosocial functioning (Holman & Lorig, 1992; O'Leary, Shoor, Lorig, & Holman, 1988; Smith, Dobbins, & Wallston, 1991; Smith & Wallston, 1992). Optimistic self-beliefs have turned out to be influential in the rehabilitation of chronic obstructive pulmonary disease patients (Kaplan, Atkins, & Reinsch, 1984; Toshima, Kaplan, & Ries, 1992). Recovery of cardiovascular function in postcoronary patients is similarly enhanced by beliefs in one's physical and cardiac efficacy (Ewart, 1992; C. B. Taylor, Bandura, Ewart, Miller, & DeBusk, 1985). Others have found that perceived self-efficacy or a sense of agency promoted later psychosocial adjustment of heart patients (S. E. Taylor, Helgeson, Reed, & Skokan, 1991; Waltz, & Badura, 1988)
Obviously, perceived self-efficacy predicts the degree of therapeutic change in a variety of settings (Bandura, 1992). Dispositional optimism (Scheier & Carver, 1985) as a theoretical construct similar to self-efficacy has also been found beneficial, for example, among both cancer patients (Carver et al., 1993; Friedman et al., 1992) and heart patients (Fitzgerald, Tennen, Affleck, & Pransky, 1993; Scheier et al., 1989). (For a general review of the relationship between optimism and health, see Bandura, 1992; Peterson & Bossio, 1991; Scheier & Carver, 1992; Schwarzer, 1994.)
There appears to be no reported research on the effects of spouses' self-efficacy on patients' readjustment. High self-efficacious spouses could serve as coping models for patients, which would be reflected in a positive association between the spouses' self-efficacy and their partners' recovery. However, an ill individual observing a highly self-efficacious spouse could possibly feel depressed due to an unfavorable social comparison (patient versus spouse) which would thus be reflected by a negative relationship between patient and spouse self-efficacy scores.
The aim of the present study is to explore the possible influence of both patients' and partners' resource factors on recovery from surgery. Personal and social resources emanating from both partners are seen as relatively stable factors that may influence the way that patients cope with adversity. The first goal is to examine whether spousal presurgery characteristics are related to immediate patient postsurgery and six-month follow-up characteristics. Second, patient and spouse characteristics are evaluated for a joint prediction of adjustment indicators for Times 2 and 3.
The study used a longitudinal design with three trials, once just before the surgery, about one week after surgery, and again half a year later. Patients were contacted upon arrival at the cardiac surgery ward of the Charité Hospital Berlin and were asked to participate in the study. They were briefed very generally about the research, the purpose of which was declared as an "investigation on the effects of severe cardiac disease and surgery on the quality of life." The patients were assured that the data would be computerized anonymously and that participation was voluntary. They received a questionnaire to be placed as soon as possible into a box that was available on the ward for that purpose (Wave 1). At the same time, they also received a second questionnaire for their spouse or intimate partner, which was also returned to the box, usually at the same time.
Patients were approached for the interview not earlier then five days and not later than 10 days after surgery (Wave 2). In those cases where patients were unable to be interviewed (e.g., due to poor physical condition), further attempts to obtain interview data were made in the subsequent days until discharge from hospital. The postsurgery interview took about half an hour. It included oral questions about physical and mental well-being, and activities such as sitting up in bed and ambulating.
Finally, patients received a questionnaire by mail half a year later, that was designed to assess self-reported quality of life (Wave 3).
Those who had responded to the presurgery questionnaire represented the initial sample of 381 patients (302 men, 79 women).The present analyses were based on the longitudinal subsample of 248 patients (193 men, 55 women) who had completed the postsurgery interview in addition. The attrition rate was 35.5% for the following reasons: 19.4% (n = 74) were transferred to different hospitals early after surgery, 5.8% (n = 22) passed away, 5.5% (n = 21) did not undergo surgery, and 4.5% (n = 17) were unwilling to be interviewed.
Within this longitudinal sample there were 193 men with a mean age of 59.1 years (SD = 10) and 55 women with a mean age of 57.4 years (SD = 11.7). Coronary artery bypass surgery was performed on 152 of the 193 men and on 26 of the 55 women. The others underwent different kinds of heart surgery, with most patients having been scheduled for cardiac valve substitution, heart transplantation, removal of heart tumors, or aneurysm resection. More men (n = 159, 82.46%) than women (n = 19, 34.5%) had a life partner. A myocardial infarct had been experienced by 35% of the patients, two infarcts by 6.4%. Of the men, 48.1% were retired or jobless, of the women 26.1%.
The sample of close social network members that were available for the study consisted of 114 persons, 18 men with a mean age of 53.39 years (SD = 9.79) and 96 women with a mean age of 51.05 years (SD = 12.48). There was no significant age difference between the male and female network members (F[1,113] = 0.56, p = .45). Most of the significant others were spouses; only five were sons or daughters, and two were close friends.
The first two of the following instruments, measuring self-efficacy and social support, were administered to both patients and their partners at Time 1. To assess a personal resource factor, a German version of the Generalized Self-Efficacy scale was used (Schwarzer & Jerusalem, 1995). This ten-item inventory was designed to assess optimistic self-beliefs that do not reflect situation-specific perceived self-efficacy (Bandura, 1992), but rather a dispositional and general personality dimension (Schwarzer, 1993, 1994). Sample items are: "I can always manage to solve difficult problems if I try hard enough," and "I can remain calm when facing difficulties because I can rely on my coping abilities." Responses were made on a four-point Likert scale, ranging from 1 (not at all true) to 4 (exactly true). The internal consistency for this inventory was Cronbach's alpha was .82 for patients and also .82 for their relatives.
To assess a social resource, the social support scale by Donald and Ware (1982, 1984) was used in its German adaptation by Bullinger and Kirchberger (Kirchberger, 1991; Westhoff, 1993). This inventory, which comprises of 19 items that aim at the perceived availability of instrumental, emotional and informational support, is particularly suited for patients. Sample items are: "Is there anyone (a) who would help if you were ill in bed," (instrumental), (b) "who would hug you," (emotional), and (c) "whose advice is really important?" (informational). Responses were made on a five-point Likert scale ranging from 1 (never) to 5 (always). The internal consistency for the 19-item scale was Cronbach's alpha = .96 for patients and .95 .for their relatives.
Postsurgery activity levels were measured by interview questions: The one of prime interest here was a single item assessing when patients sat up in bed for the first time after surgery. Small numbers pertain to a shorter time period, thus indicating a higher activity level that may suggest earlier recovery. The patients were also asked whether they had already made plans for their future, such as going on a vacation.
For the present analysis, ten items assessing quality of life were examined individually as dependent variables. Three items were designed to assess the possible impairment by ill health of daily functioning, good mood, and overall life satisfaction. Patients rated perceived impairment on a five-point scale ranging from most severely to not at all. Seven items were taken from the Munich Life Quality Dimensions List (Heinisch, Ludwig, & Bullinger, 1991). They refer to satisfaction with: marital or intimate partner, family life, overall health, mental condition, medical treatment, contacts with friends or acquaintances, and self-esteem. Responses were made on a five-point Likert scale anchored at very dissatisfied, rather dissatisfied, neither/nor, rather satisfied, and very satisfied.
Descriptive statistics of the variables involved are presented in Tables 1 and 2. Table 1 contains the means, standard deviations, and subsample sizes of the patients, Table 2 those of the spouses. Gender differences were found for half of the patients' variables. Male patients were more self-efficacious than their female counterparts at both Times 1 and 3. They also had significantly higher scores for perceived social support. As far as recovery at Time 2 is concerned, men tried to sit up in bed earlier than women did, but did not make more plans for a vacation. Of the ten life quality items measured at Time 3, female patients reported more satisfaction with intimate relationships, with family life, and with their mental condition than men. In all other cases, there were no differences between men and women patients (Table 2).
In the sample of partners, men and women did not differ in self-efficacy, but women reported higher levels of social support than men (Table 2). Although there were significant gender differences in half of the 18 variables under study, one must consider that the corresponding effect sizes did not exceed eta 2 = .07; therefore, not more than 7% of the variance was accounted for by the gender factor.
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Social support and self-efficacy, measured at Time 1, are seen here as coping resources that might be related to recovery approximately five days after surgery at Time 2 and to adjustment at Time 3, half a year after surgery. Table 3 summarizes all correlations of these two resources for both patients and partners with various adjustment indicators.
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First, social support, as perceived by the patients, was positively and significantly related to six quality of life items. The strongest associations were found for satisfaction with intimate relationships (.55) and with family life (.51). Moreover, self-efficacy of patients was associated significantly with seven quality of life indicators, in particular satisfaction with self-esteem (.39), mental condition (.29), and family life (.28). These associations were expected and, thus, can be seen as a partial validation of the various social support and self-efficacy measures.
However, no theoretical expectations were formulated for the relationships between spousal variables at Time 1 with patient variables at later points in time. It came as a surprise that the obtained empirical associations were even stronger for the lagged association than for the cross-sectional one. Six of the ten life quality indicators and the two Time 2 recovery indicators were significantly related to social support as perceived by the spouse. Again, satisfaction with one's intimate relationship (.50) and with one's family life (.49) were the variables most closely related to partners' support. Furthermore, patients' satisfaction with overall health (.43) and daily functioning (.36) could be significantly predicted by the characteristics of the spouses. Partners' self-efficacy at Time 1 was related to four quality of life indicators at Time 3, namely satisfaction with mental condition (.32), medical treatment (.35), social contacts (.34), and self-esteem (.34).
It is of further note that Table 3 also provides valuable psychometric information. The stability of patients' perceived social support for the half-year period from Time 1 to Time 3 was r = .81, and that of perceived self-efficacy was r = .67, suggesting that these constructs can possibly be conceptualized as personality dispositions. Moreover, partners' self-efficacy was related to patients' self-efficacy (Time 3) r = .35, and partners' social support was related to patients' social support (Time 3) r = .29. Thus, for close interpersonal relationships there is a tendency to share a number of traits.
To examine the joint effects of patients' and their partners' initial resources on later patient adjustment, hierarchical regression analyses were computed. At the first step, the two patient characteristics (self-efficacy and support) were entered; at the second step the two partner characteristics (self-efficacy and support). This was done to determine whether spousal variables exert an additional influence after patient predictors have already been considered. Thus, this is a conservative approach that favors patient variables. If, however, partner variables account for additional variance, this would support the present research hypotheses.
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Table 4 reports the multiple correlation (R), the explained variance (R2), the F test and the p value for all dependent variables. For each dependent variable the standardized partial regression coefficients (betas) for the two predictors at Step 1, and the four predictors at Step 2 are provided.
For the dependent variable "sitting up in bed for the first time," measured about a week after surgery, the two patient predictors, social support and self-efficacy, accounted for 5% of the variance for Step 1. Adding the two partner variables at Step 2 increased the explained variance by 11 to 16%. Partners' perceived social support was most influential (beta = -.31). The negative sign pertains to the inverse nature of the dependent variable since low values indicate good recovery. That is, the more support a partner perceives, the earlier patients try to sit up in bed following surgery. Making vacation plans was associated with the same pattern. There was a gain in prediction of 9%. It is noteworthy that the patients' social support is completely irrelevant for these two recovery indicators after surgery, i.e., sitting up and vacation plans, whereas partners' perceived social support appears to be the best predictor.
For all ten Quality of Life measures (patients, Time 3) there was a significant increment in explained variance when partners' resources where added to patients' resources. The F values, testing the significance of the regression, sometimes became lower, simply because the number of predictors was doubled at Step 2, but the R2 , indicating explained variance, was increased. In four cases, partners' support was the most influential variable, accounting for more variance than the partners' self-efficacy and both patients' resource variables. For the other six cases there were mixed patterns. Item 1 of Quality of Life assessed the possible impairment of daily functioning by ill health. The two patient predictors, social support and self-efficacy, accounted for 4% of the variance at Step 1. Adding the two partner variables at Step 2 increased the explained variance by 13 to 17%. Partners' perceived social support was most influential (beta = .39). The second Quality of Life question asked whether good mood could be impaired by ill health. There was only a slight gain of 3% of variance at Step 2, but again partners' social support had the highest beta value. The third Quality of Life item pertained to overall life satisfaction. Here, six percentage points were gained, and patients' support (.23) and partners' support (.25) were approximately equally important. Satisfaction with the marital or intimate partner was also influenced by patients' support (.51) and partners' support (.33), with more variance explained (51%) than for any other recovery indicator. Item 5, referring to family life, was also explained significantly (48%) by the four resource variables in the present predictor set, again with patients' support (.48) and partners' support (.33) being the high impact predictors. Item 6, asking for satisfaction with one's overall health, was primarily predicted by partners' support (.38) with 21% of its variance accounted for, including a gain from Step 1 to Step 2 of 12%. Quality of Life item 7, pertaining to the patients' satisfaction with his or her mental condition, was not very well predicted (18%), but partners' self-efficacy (.28) did make a contribution. Quality of Life item 8, asking for the patient's satisfaction with medical treatment, was only predicted by the two patients' resource variables (27%). Adding the partners' predictors resulted only in a negligible gain of 1%. Quality of Life item 9 (satisfaction with contacts with friends or acquaintances) made a difference of 18%, mainly due to the strong impact of partners' self-efficacy (.48). Finally, Quality of Life item 10, asking for satisfaction with one's self-esteem, was predicted primarily by the two patients' resource variables.
Social and psychological factors are influential in the process of recovery from illness in addition to physical or medical factors. Coping resources such as optimistic self-beliefs and social support played an important role in the present study on heart patients who underwent surgery. The research design included three points in time, with surgery as the critical life event occurring shortly after the first data collection. The most conspicuous aspect that makes this study distinct from others is that self-report data from the spouses of the patients were also collected. The main focus of the present analyses was to examine the predictive power of Time 1 presurgery partner variables on Time 3 (six months postsurgery) patient variables.
This was done by comparing two key resource factors, perceived social support and perceived self-efficacy, for the two groups (patients and partners). It was expected that patients' perceived resources at Time 1 would predict their recovery at Time 2 (within a week following surgery), and readjustment at Time 3. There is empirical evidence from previous research, indicating that such a prediction for the patient sample is feasible (Croog & Fitzgerald, 1978; Helgeson, 1993a, 1993b, 1993c; Waltz, 1986; Waltz & Badura, 1988). Correlation analyses of the present data confirm this evidence. Moreover, it was predicted that the spousal self-report data on their own social support and self-efficacy would also predict patient outcome variables. This was indeed the case, and the more surprising fact was that sometimes the spouses' characteristics were even better predictors of patients' readjustment than the characteristics of the patients themselves.
This obviously has to do with the nature of the social support construct. Support is, to a large extent, based on reciprocity. In studying couples, the subjective perceptions of both sides of a dyad represent valuable indicators of the ongoing transaction between the persons involved, and it may be possible that one of the two perspectives is more objective than the other. In the present sample, most of the spouses were women (since most of the patients were men). Women have the reputation of being more expert at interpersonal relationships and of possessing better social skills than men (McClelland, 1957). Womens' perceived social support may a better indication of a well-functioning or malfunctioning intimate relationship than the nature of the support as perceived by their husbands. A woman who believes that she is well-supported might have a positive and optimistic view of the relationship which, in turn, may facilitate interactions that promote better readjustment of the patients. Also, a woman who believes that she is receiving poor support might feel no need for reciprocity and, thus, does not invest that much time and effort in both the relationship in general and in her husband's recovery in particular.
The assumption that self-efficacy as perceived by social network members (partners) might influence patients' recovery may not sound intuitively obvious. However, the present data support this assumption. The core of self-efficacy is optimism (Bandura, 1992). Individuals who believe that they can make a difference and influence others are more active and supportive than those who are not. There is a positive correlation between self-efficacy and social support, probably based on the degree of optimism that is inherent in both variables. Individuals who have optimistic self-beliefs also believe that they would receive support in times of need and that they have the social skills to mobilize support whenever they wish. Moreover, the existence of a self-efficacious partner may be extremely valuable by indicating that there is indeed a powerful other who can make good things happen. Optimistic partners who see themselves as active agents of their own life can be resourceful support persons who help to improve a patient's readjustment after his or her cardiac surgery.
Although it would be obviously better to actually observe couples' interactions over an extended time period and to collect subjective data as well, the present, more modest approach has provided supportive data that point to the indirect effect of spousal characteristics on the subsequent readjustment of patients.
Pierce et al. (1996) have focused on the importance of social support for coping. They have noted that social support influences how one copes with stressful life events, and how social support may affect their prevention. "Because life events, stress coping efforts, and supportive relationships may have an impact on health and well-being over time, longitudinal designs are needed to permit evaluation of specific mechanisms" (Pierce et al., 1996, p. 447). Thus, this present study used a longitudinal design, permitting us to make predictions at Time 3 from data collected at Time 1. Bandura (1992) has noted that a socially oriented approach is necessary for both enhancing and maintaining physical well-being. He proposes self-regulatory skills as a means of promoting both physical and mental health. However, we suggest that these skills should be supplemented by social support systems.
Cohen and Herbert (1996) note that stress, depression, and negative affect amongst other factors "can influence both cellular and humoral indicators of immune system and status"(p. 113). Endler (1993), in discussing his interactional model of stress, anxiety, and coping, notes the intimate interrelationships in biological, psychological, and social factors with respect to health and illness. The present study has theoretical as well as practical implications with respect to the role of these three factors regarding both health and illness.
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The authors are grateful to Professor Dr. Wolfgang Konertz, Department of Cardiac Surgery, Charite Hospital Berlin, for access to the sample, and to Gerda Schmitz for her valuable assistance in the present data analysis. This study was supported, in part, by a Social Sciences and Humanities Research Council of Canada grant (No. 410-94-1473) to Norman S. Endler.
Table 1
Scale Statistics for Patients at Time 1
Men Women
Variable M s n M s n F p eta2
Self-efficac 30.33 4.25 290 28.41 4.89 74 11.27 .00 .03
y1
Self-efficac 30.09 4.18 155 28.48 3.61 45 5.42 .02 .03
y3
Support 1 86.82 10.98 292 78.46 17.43 73 25.99 .00 .07
Support 3 87.07 10.03 158 79.62 14.84 43 14.90 .00 .07
Sitting Up 1.59 1.14 192 2.02 1.21 54 5.84 .02 .02
Vacation 0.58 0.73 192 0.50 0.50 54 0.61 .43 .00
Plan
LifeQual 1 2.08 0.84 159 2.13 0.83 42 0.11 .74 .00
LifeQual 2 1.76 0.85 159 1.96 0.95 45 1.69 .19 .01
LifeQual 3 1.63 0.86 159 1.60 0.76 43 0.02 .88 .00
LifeQual 4 1.49 0.76 153 1.97 1.00 34 9.80 .00 .05
LifeQual 5 1.45 0.72 156 1.79 0.83 43 7.08 .01 .03
LifeQual 6 2.23 0.96 158 2.09 0.74 44 0.84 .36 .00
LifeQual 7 1.57 0.64 160 1.98 0.89 45 11.90 .00 .06
LifeQual 8 1.57 0.71 158 1.73 0.82 44 1.52 .22 .01
LifeQual 9 1.84 1.68 160 1.73 0.73 44 0.20 .65 .00
LifeQual 10 1.85 0.80 158 2.09 0.84 43 2.93 .09 .01
Note. Self-efficacy 1 = Self-efficacy at Time 1; Self-efficacy 3 = Self-efficacy at Time 3; Support 1 = Support at Time 1; Support 3 = Support at Time 3; LifeQual 1 = Impairment in daily functioning by ill health; LifeQual 2 = Mood impairment by ill health; LifeQual 3 = Dissatisfaction by ill health; LifeQual 4 = Satisfaction with intimate relationship; LifeQual 5 = Satisfaction with family life; LifeQual 6 = Satisfaction with overall health; LifeQual 7 = Satisfaction with mental condition; LifeQual 8 = Satisfaction with medical treatment; LifeQual 9 = Satisfaction with social contacts; LifeQual 10 = Satisfaction with self-esteem.
Table 2
Scale Statistics for Partners at Time 1
Men Women
Variable M s n M s n F p eta2
Self-efficacy 29.86 3.75 18 30.44 4.37 99 0.27 .60 .00
Support 81.43 13.76 18 88.08 9.39 97 6.51 .01 .05
Table 3
Correlations of Patients' or Partners' Resources With Later Adjustment of Patients
Patients Partners
Dependent Support Self- Support Self-
Efficacy Efficacy
Sitting up -.13 -.07 -.31** .10
Vacation plans .10 .12 .31** .19
LifeQual 1 .15* .13 .36** .07
LifeQual 2 .19** .18* .28* .14
LifeQual 3 .06 .08 .27* .06
LifeQual 4 .55** .18* .50** .18
LifeQual 5 .51** .28** .49** .24
LifeQual 6 .11 .19** .43** .04
LifeQual 7 .17* .29** .09 .32*
LifeQual 8 .07 .23** .12 .35**
LifeQual 9 .07 .03 .02 .34**
LifeQual 10 .16* .39** .05 .34**
Support 3 .81** .18* .29* .12
Self-efficacy 3 .27** .67** .19 .35**
Note. Self-efficacy 3 = Self-efficacy at Time 3; Support 3 = Support at Time 3; LifeQual 1 = Impairment in daily functioning by ill health; LifeQual 2 = Mood impairment by ill health; LifeQual 3 = Dissatisfaction by ill health; LifeQual 4 = Satisfaction with intimate relationship; LifeQual 5 = Satisfaction with family life; LifeQual 6 = Satisfaction with overall health; LifeQual 7 = Satisfaction with mental condition; LifeQual 8 = Satisfaction with medical treatment; LifeQual 9 = Satisfaction with social contacts; LifeQual 10 = Satisfaction with self-esteem.
Table 4
Hierarchical Regression Analyses with Patient and Partner Variables at Time 1, Predicting Time 3 Patient Variables
Dependent n Step Patient Patient Partner Partner R R2 F p
Variable Support Self-Effica Support Self-Effica
beta cy beta cy
beta beta
Sitting up 74 1 -.11 -.17 .23 .05 1.98 .15
2 -.01 -.20 -.31 .23 .40 .16 3.35 .01
Vacation plans 73 1 .04 .17 .19 .03 1.26 .29
2 -.03 .08 .29 .08 .35 .12 2.30 .07
LifeQual 1 60 1 .17 .07 .21 .04 1.26 .29
2 .07 .01 .39 -.10 .41 .17 2.85 .03
LifeQual 2 60 1 .21 .21 .34 .12 3.82 .03
2 .17 .16 .19 -.02 .39 .15 2.42 .06
LifeQual 3 60 1 .30 .07 .33 .11 3.58 .03
2 .23 .06 .25 -.13 .42 .17 2.87 .03
LifeQual 4 59 1 .60 .09 .64 .41 19.31 .00
2 .51 -.03 .33 .09 .71 .51 14.09 .00
LifeQual 5 58 1 .56 .12 .62 .38 16.87 .00
2 .48 .00 .33 .10 .70 .48 12.43 .00
LifeQual 6 59 1 .22 .14 .30 .09 2.77 .07
2 .13 .06 .38 -.06 .46 .21 3.67 .01
LifeQual 7 60 1 .23 .18 .34 .11 3.67 .03
2 .28 .07 -.08 .28 .42 .18 2.99 .03
LifeQual 8 60 1 .25 .38 .52 .27 10.64 .00
2 .25 .34 .05 .06 .53 .28 5.29 .00
LifeQual 9 60 1 .16 .00 .16 .03 .78 .46
2 .26 -.19 -.11 .48 .46 .21 3.73 .01
LifeQual 10 60 1 .16 .43 .51 .26 10.01 .00
2 .23 .40 -.19 .17 .55 .31 6.08 .00
Support Time 3 58 1 .91 -.13 .87 .76 86.23 .00
2 .90 -.20 .10 .08 .88 .77 45.17 .00
Self-efficacy 59 1 .16 .68 .75 .57 36.51 .00
Time 3
2 .19 .67 -.12 .08 .76 .58 18.71 .00
Note: LifeQual 1 = Impairment in daily functioning by ill health; LifeQual 2 = Mood impairment by ill health; LifeQual 3 = Dissatisfaction by ill health; LifeQual 4 = Satisfaction with intimate relationship; LifeQual 5 = Satisfaction with family life; LifeQual 6 = Satisfaction with overall health; LifeQual 7 = Satisfaction with mental condition; LifeQual 8 = Satisfaction with medical treatment; LifeQual 9 = Satisfaction with social contacts; LifeQual 10 = Satisfaction with self-esteem.