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Behavioral Medicine Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/vbmd20
The Relationship between Psychosocial Factors and Breast Cancer: Some Unexpected Results a
b
c
Dr. Jeffrey R. Edwards PhD , Dr. Cary L. Cooper PhD , Dr. S. Gail Pearl PhD , Dr. Ellen S. d
e
de Paredes MD , Dr. Tom O'Leary MD & Dr. Morton C. Wilhelm MD
f g
a
Darden Graduate School of Business Administration , University of Virginia , Charlottesville, USA b
University of Manchester Institute of Science and Technology , Manchester, England
c
Darden School
d
Department of Radiology , University of Virginia , USA
e
University of Virginia Health Sciences Center , USA
f
Cancer Center
g
Department of Surgery , University of Virginia Health Sciences Center , USA Published online: 09 Jul 2010.
To cite this article: Dr. Jeffrey R. Edwards PhD , Dr. Cary L. Cooper PhD , Dr. S. Gail Pearl PhD , Dr. Ellen S. de Paredes MD , Dr. Tom O'Leary MD & Dr. Morton C. Wilhelm MD (1990) The Relationship between Psychosocial Factors and Breast Cancer: Some Unexpected Results, Behavioral Medicine, 16:1, 5-14, DOI: 10.1080/08964289.1990.9934586 To link to this article: http://dx.doi.org/10.1080/08964289.1990.9934586
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The Relationship Between Psychosocial Factors and Breast Cancer: Some Unexpected Results
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Jeffrey R. Edwards, PhD, Cary L. Cooper, PhD, S. Gail Pearl, PhD, Ellen S. de Paredes, MD, Tom O’Leary, MD, and Morton C. Wilhelm, MD
A growing body of research suggests a link bet ween psychosocial factors and breast cancer. Research in this area often contains methodological problem, however, such as small sample size, inadequate comparkon groups, omission of important control variables, inclusion of on& a few psychosocial variables, and failure to anabze moderating effects. To overcome these problem, the present study examined the link between breast cancer and multiple psychosocial variables (life events, coping, Type A behavior pattern, availability of social support) among I,052 women with and without breast cancer. After controlling for hktoty of breast cancer and age, we found very few significant relationships between psychosocial variables and breast cancer. Furthermore, the relationship between life events and breast cancer was not moderated by coping, Type A, or availability of social support. Methodological and substantive reasons for these findings are dkcused.
Over the past two decades, many studies have examined the link between psychosocial stress and cancer.’ These studies have implicated a wide range of psychological precursors to cancer, such as depression,‘ and a distant relationship between patients and their parent^."^ Other studies also suggest that survival from cancer may involve psychological factors such as maintaining a fighting spirit.’ In recent years, there has been an increased interest in psychological precursors of breast cancer.’.6 This increased interest is due. in part, to the absence of any known environmental precursors or other substantive factors and to the continuing rise of breast cancer in many countries throughout the world. Most of the studies linking psychosocial stress and breast cancer have concentrated on personality predispositions’ or the presence of adverse life events preceding symptomatology.’ In many of these studies, it was found that women with breast cancer had previously experienced significantly more events involving loss and illness than had comparison The predominant personality characteristic of women with cancer, the studies indicated, was the tendency to suppress anger and emotions.”.” Few studies examined survival from breast cancer, though one investigation in-
A link between antecedent psychosocial stress and cancer has been recognized for centuries. Ganen’s secondcentury AD work on tumors, De Tumoribus, observed a higher incidence of cancer in “melancholic” than in “sanguine” women. In 1893, Herbert Snow reported in his book Cancer and the Cancer Process that, of 250 successive cancer patients he had studied at the London Cancer Hospital, 156 (62%) had significant life stress, or what he termed “immediate antecedent trouble,” prior to the cancer. This was the first time a quasi-scientific link was posited connecting stress with cancer.
D r Edwards is an assistant professor at the Darden Graduate School of Business Administration at the University of Virginia, Charlottesville; D r Cooper is a professor at the Universit-v of Manchester Institute of Science and Technology in Manchester, England; D r Pearl is a research associate at the Darden School; D r Paredes is an assistant professor in the department of radiology at the University of Virginia; D r O’Leary is clinical assistant professor and director of programs at the University of Virginia Health Sciences Center; and D r Wilhelm. associate clinical director of the Cancer Center, is also a professor in the department of surgery at the University of Virginia Health Sciences Center.
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PSYCHOSOCIAL FACTORS AND BREAST CANCER
dicated that those who survived the longest showed more anxiety, guilt, and depression, perhaps indicating that survivors may be more capable of expressing pent-up emotions. Although these investigations have contributed significantly to the body of knowledge in the field, most have been retrospective in design,'] involved small sample sizes,I4 used inappropriate or no control groups," and have not controlled for age, an important factor since breast cancer patients are skewed at the top end of the age distribution.6 Furthermore, only a few studies have explored various psychosocial factors simultaneously.'6 To provide more reliable and comprehensive information regarding the contribution of psychosocial factors to breast cancer, we must attempt to minimize these methodological weaknesses. This research attempted to minimize some of the methodological problems that characterized many earlier studies of stress and breast cancer. Specifically, the present study used data from a large sample of four different diagnostic groups, incorporated a quasi-prospective design, included relevant control variables, and incorporated multivariate techniques to examine simultaneously the contribution of psychosocial factors in the prediction of breast cancer.
METHOD Sample
The sample for this investigation consisted of 1,052 women who received a breast examination and mammography at the University of Virginia Medical Center during the summer of 1987. The majority of these women came to the center for a routine examination, though some were referred by their physicians after a lump was detected. Because each woman completed the questionnaire before her appointment, no woman knew about her actual diagnostic status until after the questionnaire data had been collected. Nearly 1,200 women were asked to participate in the study; of these, approximately 90% agreed. Deleting cases with missing data yielded a final sample of 1,052. The sample ranged in age from 18 to 85 years, with an average age of 53. More than half (64010) were employed, and 61% were married. Of those who were employed, approximately one half were either clerical (22.4%) or service (27.2%) workers, with most of the remainder (37.5%) in professional, technical, or managerial jobs.
questionnaire before receiving any information about their diagnosis, thereby reducing potential effects of diagnostic status on questionnaire responses. The questionnaire contained five major sections: 1. Demographic Data-age, marital status, occupation, number of children, medical history, cigarette smoking, alcohol consumption, and oral contraceptive use. 2. Life Events-a 42-item life events scale that was generated for a sample of the women in the United Kingdom'' and has been used in previous research into stress and breast cancer." Respondents were asked to indicate which events had occurred in the past 2 years and to rate the severity of these events in terms of degree of upset on a 10-point Likert-type scale. 3. Coping-a 38-item version of the Ways of Coping Checklist (WCCL)," which has demonstrated adequate psychometric proper tie^'^ and has been used extensively in stress and coping Respondents were asked to recall a stressful situation or event and to indicate, using a yes/no response format, whether they had used each coping strategy. 4. Type A Behavior Pattern-the Bortner Type A Scale,%which consists of 14 bipolar adjectives (eg, never rushed v always feel rushed, not competitive v very competitive, etc). Each response was rated on an 11-point scale centered at zero and ascending to 5 in both directions. The Bortner scale is moderately correlated with the Structured Intervie@ and the Jenkins Activity Surve?' and has been prospectively associated with coronary heart disease.% 5. Availability of Social Support-questions regarding the number of persons to whom the respondent could turn in response to a personal problem or crisis and their relationship to the respondent (ie, mother, father, husband, son, daughter, relative, friend).
Questionnaire data were supplemented by clinical diagnoses resulting from breast examination, mammography, and biopsy. Based on these diagnoses, we classified patients as having normal breasts ( n = 397), benign breast abnormalities (eg, fibroadenoma, fibroadenosis) ( n = 505), precancerous growths (eg, hyperplasia) ( n = 71). or breast cancer ( n = 79). This classification served as the dependent variable for later analyses. RESULTS
Measures
Characteristics of Diagnostic Groups
Upon arrival at the center, each woman was asked to complete a questionnaire while she waited for her appointment. This ensured that all patients completed the
Our first step was to examine differences between diagnostic groups on measures of demographic function, health-related behaviors, and medical history (see Table
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later analyses to focus on the relationship between psychosocial factors and the development of new breast cancer, thereby reducing the likelihood of detecting spurious relationships (eg, preexisting cancer contributing to the experience of life events). Second, it partialled history of cancer from illness-related life events, so that findings concerning these events focused specifically on illness other than cancer. Because of the specific focus of the present study on breast cancer, however, controlling for all types of cancer was considered overly restrictive. We used questionnaire information to distinguish breast cancer from other forms and created a dummy variable specifically indicating history of breast cancer. (we repeated the analyses, controlling for history of any form of cancer. Results did not differ substantively.)
1). Analyses of continuous variables (eg, age) involved simple one-way ANOVAs, whereas analyses of dichotomous variables (eg, marital status) involved contingency table analysis (ie, chi-square). As indicated in Table 1, the only significant difference found between the four diagnostic groups was previous history of cancer, indicating that the breast cancer group was significantly more likely to report a previous cancer diagnosis than the remaining three groups. The failure to find a significant difference for age was quite surprising in view of the positive relationship between age and prevalence of cancer found in most studies.6 Given the significant diagnostic group differences in history of cancer, this variable was statistically controlled in later analyses. This served two purposes. First, it allowed
~~
TABLE 1 Demographic Variables
Item (number) Age (years) Cigaretteslday Drinkdweek Number of children Age at first pregnancy
Cancer
Precancer
Cyst
Normal
M
M
M
M
F
55.7 4.7 2.2 2.7 22.9
53.4 3.5 1.6 2.3 22.2
53.1 3.4 I .7 2.7 22.5
52.9 3.0 1.3 2.7 22.3
1.17 0.90 1.80 1.25 0.32
Cancer
Precancer
cyst
Normal
Item
To
To
070
To
XI
Used oral contraceptive Work full time Ovary removed Marital status Single Married Divorced Separated Widowed Had cancer Mother had cancer Sister had cancer Aunt had cancer Maternal grandmother had cancer Paternal grandmother had cancer
46
48
84
87
26
16
43 85 25
45 89 25
2.49 2.60 2.49
8 66
71
7 1
15 1
9 64 12
18 44 19 14 22 14
12 18 18 14 28 10
8 64 10 4 15 18 14 14 18 II
3 13 19 12 13 19 9
12.43 28.09. 4.66 0.04 4.41 I .60
8
10
9
7
1.16
*p
1
< .01.
Spring 1990
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PSYCHOSOCIAL FACTORS AND BREAST CANCER
In addition to controlling for history of breast cancer, we also controlled for age in later analyses. Although the differences between diagnostic groups in terms of age failed to reach significance, the importance of controlling for age has been emphasized in the literature.‘ The admittedly modest association between age and diagnostic classification was eliminated by controlling for age, which still left ample degrees of freedom for examining relationships involving psychosocial variables.
are therefore presented here.) As indicated by the factor loadings, the resulting structure was simple and highly interpretable, with each item loading essentially on one and only one factor. Using .30 as a cutoff criterion for the factor loadings, we found that 27 of the original 42 items loaded on one of the eight factors. Based on items with the highest loadings, we labeled these factors Job Security (4 items), Moving (4 items), Farmly Illness (4 items), Birth (2 items), Self Illness (3 items), Financial Difficulty (4 items), Marriage (2 items), and Separation (4 items). Reliability estimates for these scales ranged from S O to .74 (see Table 2), with three of the eight scales having reliabilities greater than or equal to .70. This suggests that three of these scales were acceptable for research purposes, whereas the remaining five were marginally acceptable.>
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Dimensionality and Psychometric Properties of Measures We conducted factor analyses with oblique rotation on the life events, coping, and Type A measures. The primary purpose of these analyses was to identify natural groupings of items in order to form subscales for later analyses. For each analysis, we used both a scree test” and factor interpretability as criteria for determining the number of factors to retain. The reliability of the resulting subscales was estimated using Cronbach’s alpha$’ results of these analyses for each set of measures are described below.
Coping Factor analysis of the coping items yielded a four-factor solution, accounting for 27% of the common variance. The factor loadings again revealed a simple structure, though the magnitudes of the loadings were rather low (none greater than .a), making factor interpretation somewhat difficult. Thirty-four of the original 38 items had loadings of at least .30. Based on items with the highest loadings, we labeled these factors Maladaptive (14 items), DeniaVAvoidance (9 items), Seek Social Support (7 items), and Venting (4 items). Reliability estimates for the resulting scales
Lijie Events Factor analysis of the life event items yielded an eightfactor solution, accounting for 31Vo of the common variance. (When we conducted analyses for both event occurrence and event severity data, we found no substantive differences. Only those results pertaining to the severity data
TABLE 2 Means, Standard Deviations, Correlations. and Reliabilitiesi for All Scales ~~
Scales Job Security (JS) Moving (M) Family Illness (FI) Birth (B) Self Illness (SI) Financial Difficulty (FD) Marriage (M) Separation (S) Maladaptive (MD) DeniaVAvoidance ( D A ) Social Support (SS) Venting (V) Time Urgency (TU) Ambition ( A ) Loner ( L )
M
SD
JS
2. I 1.7 6.2 .2 4.0 2.4 .2 I .6 4.2 3.7 1.5 .9 36.9 29.6 12.0
4.9 4.5 9.3 1.6 7.0 5.5 I .4 4.9 4.9 2.4 I .5 1.1 12.5 7.4 5. I
(.63) .I9
M
~70) .I4 .06 .03 .I4 .08 .I7 .I7 .I0 .I4 .I4 .I4 .06
.to .04 .08 .32 .I2 .25 .I8
.04 .I6
.I5 .I9
.I5 -
.05
~
.04
FI
(.72) .I0 .I4 .I4 .06 .09
B
( .74)
.I0 .I4 .22 .I3
.I5
.04
(.67) .25 .04 .I4 .22 .I0 .03 .06 .04
.01 .02
.01 .06
.09 .01 .06 .05
.07
.II .I5 .II .01 - .02
SI
-
tReliabilities are given o n [he diagonal.
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EDWARDS ET AL
ranged from .53 to .80, with two of the four scales having reliabilities greater than or equal to .70 (see Table 2). Overall, these estimates were somewhat higher than those obtained for the life events scales, though the maladaptive and denial scales fared considerably better than the seek social support and venting scales.
Type A Behavior Pattern
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Factor analysis of the Bortner items yielded a threefactor solution, accounting for 34% of the common variance. Again, the factor loadings revealed a simple structure, though the first two factors were more interpretable than the third. Twelve of the original 14 items had loadings of at least .30. Based on items with the highest loadings, we labeled these factors Time Urgency (6 items), Ambition (4 items), and Loner (2 items). Reliability estimates for the resulting scales were .78 for time urgency, .65 for ambition, and .46 for loner, indicating that the loner scale was quite unreliable (see Table 2). Its inclusion in later analyses was therefore viewed as exploratory, and associated results should be viewed with caution. Multinominal Logit Analyses
We conducted a series of multinominal logit analysesw3z to assess whether life events, coping, and the Type A be-
havior pattern were related to clinical diagnoses. Like discriminant analysis, logit is appropriate for assessing the relationship between a set of continuous independent variables and a categorical dependent variable. Unlike discriminant analysis, however, logit provides estimates for specific independent variables rather than a composite linear function of the independent variables (ie, a discriminant function).33As a result, logit provides a clearer interpretation of the effects of specific independent variables, which was the primary focus of the present study. In addition, logit is less sensitive to departure from normality than discriminant analysis,” which was characteristic of several independent variables used in this study, particularly those derived from the life events scale. For these reasons, we selected logit for the present study. For each analysis, history of breast cancer was entered into the model first, age was entered second, and the set of psychosocial variables under consideration (ie, life events, coping, Type A, avadability of social support) was entered third. The significance of variables, both individually and taken as sets, was determined using the Wald test, 32 which is analogous to the F ratio corresponding to a set of restrictions in multiple regression analy~is.~’ Figures in Table 2 show means, standard deviations, interscale correlations, and reliabilities for the eight life events scales, four coping scales, and three Type A scales used as independent variables.
(.@)
.12 .28 .26 .15 .03 .28 .07
(.SO) .26 .06 .05
.02
.08
.04
.02 .01
.01
.01
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(.59)
.26 .I3 .I3 .20 .09
.13 .01
(.go) (.75) .27
(.55)
.40
.20
.43 .24 .47 .14 - .01
- .01 - .07
.06
.02
.04
(.53) .I2
.06 - .28
.04 .08
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Life Events Logit results for the eight life events scales are shown in Table 3. Our initial analyses used event severity rather than event occurrence, based on the assumption that the patient’s appraisal of the event would substantially influence experienced stressM6’” and on the modest but consistent superiority of weighted v unweighted life events in the prediction of ~ymptomatology.~~”~ The eight life events scales as a set did not contribute significantly to the prediction of diagnostic classification when we controlled for age and history of breast cancer (p > .lo). Nonetheless, tests of individual predictors indicated that selfillness and birth were marginally significant as independent predictors of diagnostic classification (p < .lo). Inspection of coefficients revealed that, for self-illness, patients in the cancer group scored higher than those in the precancer, cyst, and normal groups, indicating that events such as hospitalization, operation, and illness were rated as more upsetting by patients with cancer. For birth, patients in the precancer group scored lower than patients in the cyst and normal groups (no patients in the cancer group reported a birth event), indicating that pregnancy and birth were rated as less upsetting by patients with precancerous abnormalities. Because these predictors were only marginally significant, and because the life event variables as a set were not significant, these findings should be considered highly tentative. The lack of significant relationships found in the above analyses was unexpected and, in fact, deviated from earlier research into the relationship between stress and breast cancer.’.6 We therefore conducted a series of follow-up analyses to explore several potential reasons for this deviation. One potential reason is that the event severity ratings may have simply added noise to the data rather than contributing substantive information, so we repeated the logit analyses, this time using event occurrence rather than event seventy. Results again indicated that the life event variables as a set did not contribute significantly to the prediction of diagnostic classification, though self-illness and birth were again rnargjnally significant. The coefficients for these variables indicated the same general pattern of intergroup differences. In addition, total event occurence became marginally significant, with the cancer and precancer groups reporting slightly more life events than the remaining two groups. Thus, except for minor variations, the results for event occurrence were the same as those for event seventy. A second potential reason why so few significant relationships were found is that too many diagnostic groups were used, thereby creating distinctions with little sub-
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TABLE 3 Relationship Between Life Events and Diagnostic Classificationt
Source Had breast cancer Age Life Events
Job Security Moved Family Illness Birth Self Illness
Financial Difficulty Marriage Separation
x= 30.50* 1.67 28.61 5.46 1.16 5.10 7.72 7.06 1.78 0.24
0.50
‘p < . O l . tDashed lines indicate that the predictors were analyzed hierarchically.
stantive meaning. It could be argued that, from a clinical standpoint, the normal and cyst groups were essentially the same in that neither group demonstrated symptoms of cancer. Because of this, we collapsed the normal and cyst groups and repeated the analysis for both event severity and occurrence data. For event severity, the effects of total life events, self-illness, and birth now reached significance (p < .05), with the cancer and precancer groups reporting greater upset from life events than the combined normal/cyst group. In addition, family illness became marginally significant, with the cancer and precancer groups reporting more upset from family illness than the combined normal/cyst group. For event occurrence, the effect for self-illness became significant (p < .05), and the effect for birth remained marginally significant. The effects for total life events and job security also became marginally significant, with the cancer and precancer groups reporting more total life events and more events that threatened job security than the combined normal/ cyst group. Although these analyses yielded some significant findings, it should be noted that significance was achieved because the three-group analyses required a lower critical chi-square than the four-group analyses, not because the magnitude of the effect had increased. The
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more major home renovation than the remaining three groups. The pattern for retirement was more complex, with the normal group scoring highest, followed by the precancer, cyst, and cancer groups. Three life events revealed marginally significant differences, and agab the pattern of group differences was varied. Specifically, the precancer group reported a greater increase in responsibility for elderly and sick persons and more illness of family members than the remaining three groups, whereas the cyst and normal groups reported more births than the cancer and precancer groups. Results from the severity data differed rather markedly from those obtained from the occurrence data. For example, of the five variables that were significant for event occurrence, only one (threat of job loss) was significant for event severity, though two (major home renovation and retirement) were marginally significant. For these variables, the pattern of results for event severity was basically the same as for event occurrence. Furthermore, none of the variables that were marginally significant for event occurrence (including total life events) were marginally significant for event seventy. Three variables that were not marginally significant for event occurrence, however, were marginally significant for event severity. Specifically, the precancer group indicated that increased debt and difficulty with children were more upsetting than the remaining three groups, whereas the cyst and normal groups indicated that selling a house was more upsetting to them than to the cancer and precancer groups.
practical importance of significance achieved through such a procedure is rather dubious. A third potential reason why so few significant relationships were found is that the life event items may have been combined inappropriately when the subscales were formed, thereby concealing important information. We therefore conducted a second series of follow-up analyses, first on an overall index created by summing all life event items, then on each individual life event. We conducted these analyses on both event occurrence and event severity data (see Table 4).* As before, all analyses controlled for age and history of breast cancer. Results for total event occurrence were marginally significant, with patients in the precancer group reporting slightly more life events than those in the cancer group, who in turn reported more events than patients in the cyst and normal groups. Of the 42 individual life events examined, 5 revealed significant differences, though the pattern of group differences varied greatly. For example, the cancer and precancer groups reported more change in the nature of work and greater threat of job loss than the cyst and norma! groups. The cancer group, however, reported more surgery than the remaining three groups, and the precancer group reported *The overall indices created by summing all Occurrence and seventy events demonstrated acceptable reliabilities of .72 and .75, respectively. An obwous problem with analyzing individual life events. however, is that the reliability of individual items cannot be estimated. It is, therefore, difficult to attribute lack of significance to attenuation due to unreliability or to the true absence of an effect. Hence, the results concerning indi..idual life events should be interpreted with this caveat in mind.
TABLE 4 Follow-Up Analyses of Life Eventst
Item ( n u m b e r )
Cancer
Precancer
cyst
Normal
vo
vo
vo
Q70
11
22 22
9 13
9
8.90*
11
8.74*
2 44
6 6 22
4 4 19
I 8
9.90* 9.29'
19
10.00*
0.37
0.36
0.28
0.08
7.94'
x=
Occurrence M a j o r renovation C h a n g e in n a t u r e of work Threat of j o b loss Retired
Surgery Severity (M) Threat of j o b loss
18 7
* p < .05. * p < .01. tAll analyses controlled for history of breast cancer and age.
Spring 1990
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PSYCHOSOCIAL FACTORS AND BREAST CANCER
The above analyses imply several relationships that were not evident in the analyses of the eight life events scales. These relationships should be interpreted with caution, however, in that the large number of statistical tests conducted drastically increased the probability of a Type I error. For example, if the alpha for 42 independent tests is set at .05, then the probability of finding at least one significant effect, assuming no significant relationships actually exist, is approximately .88. If the tests are not independent (as in the case of the 42 life event indices), then this probability is somewhat lower but still much larger than the intended alpha of .05. Using the Bonferroni technique to correct for this would result in an alpha of .05/42, or .0012. If we adopted this more conservative approach, then none of the relationships reported in Table 4 would be considered significant.
Coping Logit results for the four coping scales indicated that neither the coping variable as a set nor the individual predictors were significant. We again conducted a series of follow-up analyses on the individual coping items, as we had with the life event data. None of these analyses reached significance.
Type A Behavior Pattern As with the coping scales, logit results for the three Type A scales indicated that neither the Type A variables as a set nor the individual predictors were significant. A series of follow-up analyses on individual items did not reveal any significant relationships.
Availability of Social Support As with the coping and Type A scales, logit results for the seven availability of social support indices revealed that neither the variables as a set nor the individual predictors were significant. N o significant relationships were found in follow-up analyses.
Moderating Effects of Coping, Tvpe A , and Availability of Social Support We examined coping, Type A, and availability of social support as moderators of the relationship between stressful life events and diagnostic classification. These effects were examined by hierarchically entering the product of life events and the moderator variable under consideration into the model, after controlling for life events and the moderator variable."' As before, these analyses also controlled for history of breast cancer and age. Because of
12
the potentially large number of interactions, we first tested the moderating effects of the coping, Type A, and availability of social support subscales on the relationship between total life events (both occurrence and seventy) and diagnostic classification. If significant moderating effects were found, then furtner analyses of separate life events scales would reveal the particular events involved in these effects. None of the interactions between total event seventy and the coping, Type A, and availability of social support subscales reached significance. Because of this, we conducted no further analyses involving the separate life events scales.
DISCUSSION This study detected very few significant relationships between psychosocial variables and diagnostic classification. Analyses of life events subscales revealed marginally significant effects for self-illness and birth. Analyses of individual life events revealed additional relationships, but the large number of statistical tests conducted warrants caution in the interpretation of these results. No significant effects were found for coping, Type A, or availability of social support, nor did these variables moderate the relationship between total life events and diagnostic classification. Before concluding that the above findings indicate no relationship between psychosocial factors and breast cancer, it is necessary to consider methodological problems that may have inflated Type I1 error, thereby preventing the detection of relationships that, in fact, exist. One potential problem typically considered is inadequate statistical power." This, however, was an unlikely explanation in the present investigation, given the substantial sample size. Another potential problem is restricted range of variables included in analyses, but descriptive statistics indicated that, with few exceptions, responses were obtained throughout the entire potential range for each variable. A third potential problem is unreliability of measures included in analyses. Though no estimate of reliability was available for the criterion measure (ie, diagnostic classification), the clinical rigor taken to derive this measure suggests that it contained very tittle error. On the other hand, several predictor variables yielded rather low reliability estimates, suggesting that they contained substantial amounts of error variance. Even scales with high reliabilities, such as maladaptive coping (alpha = .80), time urgency (alpha = .78), and total event severity (alpha = .78), did not exhibit significant associations with diagnostic classification. These methodological reasons for a lack
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of significant effects can therefore apparently be ruled out in the present study. In light of the preceding discussion, we must tentatively conclude that the psychosocial variables included in this investigation were simply not related to the incidence of breast cancer. This conclusion is underscored by the fact that the only life events subscales that reached even marginal significance (self-illness and birth) may reflect physiological rather than psychosocial correlates of breast cancer. Nonetheless, it should be emphasized that the conclusions of this study are valid only for the measures and sample involved. For example, although the measures of acute life events were generally unrelated to breast cancer, it is nonetheless plausible that significant relationships may exist for either chronic situations or daily hassle^.^^.^^ In addition, although the sample used in this investigation was quite large, it was drawn exclusively from a restricted geographical region. Therefore, the generalizability of these findings to other samples awaits empirical verification. Furthermore, controlling for other known breast cancer risk factors (eg, deviation from ideal body weight, history of breast feeding, estrogen in addition to birth control pill, etc) may have altered the results of our study. When compared with work conducted in the United Kingdom concerning the link between psychosocial factors and breast cancer," the results of the present study show some similarities as well as some qualitative differences. First, both studies confirmed that only a handful of major life events, rather than all adverse events, are implicated in breast cancer. Second, both studies suggest that self-illness events (eg, the occurrence of illness, hospitalization, and surgery) that involved illnesses other than breast cancer were related to subsequent breast cancer diagnosis. Third, both studies found that Type A behavior, a variety of coping strategies, and the availability of social support were not significant predictors of breast cancer. Since many of these measures have been derived in the context of cardiovascular and mental health research, they may not be appropriate measures for cancer research. Fourth, both studies indicate that loss-related events were related to breast cancer. However, in the United Kingdom study, these events referred to death of a husband or close friend, whereas in the United States study, these events referred to threatened loss of a job. One explanation for this divergence is that fewer psychological or bereavement counseling facilities are available in the United Kingdom than in the United States, suggesting that women in the United States who experience the death of a husband or close friend are able to seek appropriate counseling support more readily than British wom-
Spring 1990
en. This may help minimize the impact of loss-related events involving interpersonal relationships, thereby buffering their effects on immune system re~ponse.~' In conclusion, the results of this study indicate that life ebents, coping, Type A behavior pattern, and the availability of social support are largely unrelated to the incidence of breast cancer. Given the inconsistency of these results with earlier studies,' we need much more research to verify the connection between psychosocial factors and breast cancer, to identify possible moderating factors (eg, personality, coping strategies, social support), and to fully understand the psychophysiology of the disease process.
INDEX TERMS stress. Type A behavior. coping, social support, bread cancer
NOTE Address correspondence to Jeffrey R. Edwards, PhD, The Darden School, University of Virginia, Charlottesville, VA 22W6-6550.
REFERENCES 1. Cooper CL. Stress ond Eremt Concer. New York: John Wiley &
Sons; 1988. 2. Shekelle RB. Raynor WJ, Ostfeld AM, et al. Psychological depression and 17-year risk of death from cancer. Psychosom Med. 1981;43:117. 3. Thomas CB, Greenstreet RL. Psychobiological characteristics in youth as predictors of five disease states: Suicide, mental illness, hypertension, coronary heart disease and tumor. Hopkins Medico/ Journal. 1973;132:16. 4. Duszynski KR. Shaffer JW, Thomas CB. Neoplasm and traumatic events in childhood. Arch Gm Psychiotrv 1981;38:327. 5 . Derogatis LR, Abeloff MD. Melisaratos N. Psychological coping mechanisms and survival time in metastatic breast cancer. J JAMA. 1979;242:1504. 6. Cooper CL, Cooper RD, Faragher B. Psychosocial stress a.. a precursor to breast cancer: A review. Current Psychologicol Research Reviews. 1986;s:268-280. 7. Coppens A, Metcalfe M. Cancer and extroversion. Er Med J 1%3;20: 18-19. 8. Muslin HL. Gyarfas K, Pieper WJ. Separation experience and cancer of the breast. Annuol New York Acodemy ofscience Journo/. 1%9; 125:802-806. 9. Bageley C. Control of events. remote stress, and emergence of breast cancer. Am J Clin Psychology 1979.6:213-220. 10. Cheang A. Cooper CL. Psychosocial factors in breast cancer. Stress Medicine. 1985;1 :61-66. 11. Greer S, Morris T. Psychological attributes 01' women who develop breast cancer: A controlled study. J Psychosom Rcs. 1975; 19:147-153. 12. Wirsching M, Stierlin H. Hoffmann F, Weber G , Wirsching B. Psychological identification of breast cancer patients before biopsy. J Psychosom Res. 1982;26:1-1 1 . 13. Funch DP, Marshall J . The role of stress, social support, and age in survival from breast cancer. J Psychosom Res. 1982;27:77-83.
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PSYCHOSOCIAL FACTORS A N D BREAST CANCER
14. Becker H. Psychodynamic aspects of breast cancer: Differences in younger and older patients. Psychother Psychosom. 1978;32: 287-2%. IS. Snell L. Graham S. Social trauma as related to cancer of the breast. Br J Cancer. 1971;25:721-729. 16. Priestman TJ, Priestman SG, Bradshaw C. Stress and breast cancer. Br J Cancer. 1985;51:493-498. 17. Cooper CL, Cooper RD, Faragher B. A prospective study of the relationship between breast cancer and life events, Type A behaviour, social support and coping skills. Stress Medicine. 1986;2: 27 1-277.
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18. Folkman S, Lazarus RS. An analysis of coping in a middle-aged community sample. J Health Soc Behav. 1980;21:219-239. 19. Vitaliano PP. Russo J, Carr JE, Maiuro RD, Becker J. The ways of coping checklist: Revision and psychometric properties. Multivariate Behavioral Research. 1985;20:3-26. 20. Aldwin CM, Revenson TA. Does coping help? A reexamination of the relation between coping and mental health. J Pen SOCPsychol. 1987;53:337-348. 21. Coyne JC. Aldwin C. Lazarus RS. Depression and coping in stressful episodes. J Abnorm Psychol. 1981;90:439-447. 22. Folkman S, Lazarus RS. I f it changes, it must be a process: A study of emotion and coping during three stages of a college examination. J Pen Soc Psychol. 1985;48:150-170. 23. Folkman S. Lazarus RS, Gruen RJ, DeLongis A. Appraisal, coping, health status. and psychological symptoms. J pers SOCPsycho/. 1986;50:571-579. 24. Bortner RW. A short rating scale as a potential measure of pattern A behavior. J Chron Dis. 1%9;22:87-91. 25. Johnston DW. Shaper AG. Type A behavior in British men: Reliability and intercorrelation of two measures. J Chron Db. 1983; 36:203-207. 26. French-Belgian Collaborative Group. Ischemic h e m disease and psychological patterns. Adv Curdiol. 1982;29:25-31. 27. Cattell RB. The scree test for the number of factors. Multivariate Behavioral Research. 1966; I :94-976. 28. Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika. 1951;16:297-334. 29. Nunnally JC. Psychometric Theory. New York: McGraw-Hill Book Company; 1978.
30. Aldrich JH, Nelson FD. Linear Probability. Logit. and Probit Modek. Beverly Hills: Sage; 1984. 31. Pindyck RS, Rubinfeld DL. Econometric Modek and Economic Forecasts. New York: McGraw-Hill Book Company; 1981. 32. Steinberg D. Interpretation and diagnostics of the multinomial and logistic regression. Proceedings, 12th Annual SAS User’s Group fnternational Conference. Cary, NC: SAS Institute, Inc; 1987. 33. Dillon WR, Goldstein M. Multivariate Analysis: Methods and Applications. New York: John Wiley & Sons; 1984. 34. Press SJ, Wilson S. Choosing between logistic regression and discriminant analysis. J A m Statistical Association. 1978;73:69!705. 35. Neter J . Wasserman W. Applied Linear Statistical Modek. Homewood. 1L: Irwin; 1974. 36. Lazarus RS. Psychological Stress and the Coping Process. New York: McGraw-Hill Book Company; 1966. 37. Lazarus RS, Folkman S. Stress, Coping, and Adaptation. New York: Springer; 1984. 38. Cooper CL, Cooper RD. Faragher B. Stress and life event methodology. Stress Medicine. 1985;I :287-289. 39. Thoits PA. Dimensions of life events that influence psychological distress: An evaluation and synthesis of the literature. In: Kaplan HB ed: Psychological Stress: Trends in Theory and Research. New York: Academic Press; 1983; 33-103. 40. Cohen J. Partialed products are interactions: Partialed powers are curve components. Psychol Bull. 1978;85:858-866. 41. Cohen J. Statistical Power Analysis for the Behavioral Sciences. New York: Academic Press; 1977. 42. Burks N, Martin B. Everyday problems and life change events: Ongoing versus acute sources of stress. J Human Stress. 1985;I 1 (Spring):27-35. 43. Kanner AD, Coyne JC, Schaefer C. Lazarus RS. Comparison of two modes of stress measurement: Daily hassles and uplifts versus major life events. J Behav Med. 1981;4:1-39. 44. Cooper CL, Faragher B, Cooper RD. Incidence and perceptions of psychosocial stress: The relationship to breast cancer. Psycho/ Med. In press. 45. Morris T, Greer S, Pettingale KW. Watson M. Patterns of expression of anger and their psychological correlates in women with breast cancer. J Psychosom Res. 1981;25: I 11-1 17.
The National AIDS Information Clearinghouse 1-800-458-523 1 FAX: 1-301-738-6616 Call us. We’re your centralized resource for information on HIVIAIDS programs, services, and materials. A srnrice ol‘ I l i e U . S . L)elxirlment of Hralth and t Iiimiiii S e n k r s I’itbIic tlrallh Srnrice C:cnters lor I>israseControl
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Behavioral Medicine
Behavioral Medicine Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/vbmd20
The Relationship between Psychosocial Factors and Breast Cancer: Some Unexpected Results a
b
c
Dr. Jeffrey R. Edwards PhD , Dr. Cary L. Cooper PhD , Dr. S. Gail Pearl PhD , Dr. Ellen S. d
e
de Paredes MD , Dr. Tom O'Leary MD & Dr. Morton C. Wilhelm MD
f g
a
Darden Graduate School of Business Administration , University of Virginia , Charlottesville, USA b
University of Manchester Institute of Science and Technology , Manchester, England
c
Darden School
d
Department of Radiology , University of Virginia , USA
e
University of Virginia Health Sciences Center , USA
f
Cancer Center
g
Department of Surgery , University of Virginia Health Sciences Center , USA Published online: 09 Jul 2010.
To cite this article: Dr. Jeffrey R. Edwards PhD , Dr. Cary L. Cooper PhD , Dr. S. Gail Pearl PhD , Dr. Ellen S. de Paredes MD , Dr. Tom O'Leary MD & Dr. Morton C. Wilhelm MD (1990) The Relationship between Psychosocial Factors and Breast Cancer: Some Unexpected Results, Behavioral Medicine, 16:1, 5-14, DOI: 10.1080/08964289.1990.9934586 To link to this article: http://dx.doi.org/10.1080/08964289.1990.9934586
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The Relationship Between Psychosocial Factors and Breast Cancer: Some Unexpected Results
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Jeffrey R. Edwards, PhD, Cary L. Cooper, PhD, S. Gail Pearl, PhD, Ellen S. de Paredes, MD, Tom O’Leary, MD, and Morton C. Wilhelm, MD
A growing body of research suggests a link bet ween psychosocial factors and breast cancer. Research in this area often contains methodological problem, however, such as small sample size, inadequate comparkon groups, omission of important control variables, inclusion of on& a few psychosocial variables, and failure to anabze moderating effects. To overcome these problem, the present study examined the link between breast cancer and multiple psychosocial variables (life events, coping, Type A behavior pattern, availability of social support) among I,052 women with and without breast cancer. After controlling for hktoty of breast cancer and age, we found very few significant relationships between psychosocial variables and breast cancer. Furthermore, the relationship between life events and breast cancer was not moderated by coping, Type A, or availability of social support. Methodological and substantive reasons for these findings are dkcused.
Over the past two decades, many studies have examined the link between psychosocial stress and cancer.’ These studies have implicated a wide range of psychological precursors to cancer, such as depression,‘ and a distant relationship between patients and their parent^."^ Other studies also suggest that survival from cancer may involve psychological factors such as maintaining a fighting spirit.’ In recent years, there has been an increased interest in psychological precursors of breast cancer.’.6 This increased interest is due. in part, to the absence of any known environmental precursors or other substantive factors and to the continuing rise of breast cancer in many countries throughout the world. Most of the studies linking psychosocial stress and breast cancer have concentrated on personality predispositions’ or the presence of adverse life events preceding symptomatology.’ In many of these studies, it was found that women with breast cancer had previously experienced significantly more events involving loss and illness than had comparison The predominant personality characteristic of women with cancer, the studies indicated, was the tendency to suppress anger and emotions.”.” Few studies examined survival from breast cancer, though one investigation in-
A link between antecedent psychosocial stress and cancer has been recognized for centuries. Ganen’s secondcentury AD work on tumors, De Tumoribus, observed a higher incidence of cancer in “melancholic” than in “sanguine” women. In 1893, Herbert Snow reported in his book Cancer and the Cancer Process that, of 250 successive cancer patients he had studied at the London Cancer Hospital, 156 (62%) had significant life stress, or what he termed “immediate antecedent trouble,” prior to the cancer. This was the first time a quasi-scientific link was posited connecting stress with cancer.
D r Edwards is an assistant professor at the Darden Graduate School of Business Administration at the University of Virginia, Charlottesville; D r Cooper is a professor at the Universit-v of Manchester Institute of Science and Technology in Manchester, England; D r Pearl is a research associate at the Darden School; D r Paredes is an assistant professor in the department of radiology at the University of Virginia; D r O’Leary is clinical assistant professor and director of programs at the University of Virginia Health Sciences Center; and D r Wilhelm. associate clinical director of the Cancer Center, is also a professor in the department of surgery at the University of Virginia Health Sciences Center.
5
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PSYCHOSOCIAL FACTORS AND BREAST CANCER
dicated that those who survived the longest showed more anxiety, guilt, and depression, perhaps indicating that survivors may be more capable of expressing pent-up emotions. Although these investigations have contributed significantly to the body of knowledge in the field, most have been retrospective in design,'] involved small sample sizes,I4 used inappropriate or no control groups," and have not controlled for age, an important factor since breast cancer patients are skewed at the top end of the age distribution.6 Furthermore, only a few studies have explored various psychosocial factors simultaneously.'6 To provide more reliable and comprehensive information regarding the contribution of psychosocial factors to breast cancer, we must attempt to minimize these methodological weaknesses. This research attempted to minimize some of the methodological problems that characterized many earlier studies of stress and breast cancer. Specifically, the present study used data from a large sample of four different diagnostic groups, incorporated a quasi-prospective design, included relevant control variables, and incorporated multivariate techniques to examine simultaneously the contribution of psychosocial factors in the prediction of breast cancer.
METHOD Sample
The sample for this investigation consisted of 1,052 women who received a breast examination and mammography at the University of Virginia Medical Center during the summer of 1987. The majority of these women came to the center for a routine examination, though some were referred by their physicians after a lump was detected. Because each woman completed the questionnaire before her appointment, no woman knew about her actual diagnostic status until after the questionnaire data had been collected. Nearly 1,200 women were asked to participate in the study; of these, approximately 90% agreed. Deleting cases with missing data yielded a final sample of 1,052. The sample ranged in age from 18 to 85 years, with an average age of 53. More than half (64010) were employed, and 61% were married. Of those who were employed, approximately one half were either clerical (22.4%) or service (27.2%) workers, with most of the remainder (37.5%) in professional, technical, or managerial jobs.
questionnaire before receiving any information about their diagnosis, thereby reducing potential effects of diagnostic status on questionnaire responses. The questionnaire contained five major sections: 1. Demographic Data-age, marital status, occupation, number of children, medical history, cigarette smoking, alcohol consumption, and oral contraceptive use. 2. Life Events-a 42-item life events scale that was generated for a sample of the women in the United Kingdom'' and has been used in previous research into stress and breast cancer." Respondents were asked to indicate which events had occurred in the past 2 years and to rate the severity of these events in terms of degree of upset on a 10-point Likert-type scale. 3. Coping-a 38-item version of the Ways of Coping Checklist (WCCL)," which has demonstrated adequate psychometric proper tie^'^ and has been used extensively in stress and coping Respondents were asked to recall a stressful situation or event and to indicate, using a yes/no response format, whether they had used each coping strategy. 4. Type A Behavior Pattern-the Bortner Type A Scale,%which consists of 14 bipolar adjectives (eg, never rushed v always feel rushed, not competitive v very competitive, etc). Each response was rated on an 11-point scale centered at zero and ascending to 5 in both directions. The Bortner scale is moderately correlated with the Structured Intervie@ and the Jenkins Activity Surve?' and has been prospectively associated with coronary heart disease.% 5. Availability of Social Support-questions regarding the number of persons to whom the respondent could turn in response to a personal problem or crisis and their relationship to the respondent (ie, mother, father, husband, son, daughter, relative, friend).
Questionnaire data were supplemented by clinical diagnoses resulting from breast examination, mammography, and biopsy. Based on these diagnoses, we classified patients as having normal breasts ( n = 397), benign breast abnormalities (eg, fibroadenoma, fibroadenosis) ( n = 505), precancerous growths (eg, hyperplasia) ( n = 71). or breast cancer ( n = 79). This classification served as the dependent variable for later analyses. RESULTS
Measures
Characteristics of Diagnostic Groups
Upon arrival at the center, each woman was asked to complete a questionnaire while she waited for her appointment. This ensured that all patients completed the
Our first step was to examine differences between diagnostic groups on measures of demographic function, health-related behaviors, and medical history (see Table
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later analyses to focus on the relationship between psychosocial factors and the development of new breast cancer, thereby reducing the likelihood of detecting spurious relationships (eg, preexisting cancer contributing to the experience of life events). Second, it partialled history of cancer from illness-related life events, so that findings concerning these events focused specifically on illness other than cancer. Because of the specific focus of the present study on breast cancer, however, controlling for all types of cancer was considered overly restrictive. We used questionnaire information to distinguish breast cancer from other forms and created a dummy variable specifically indicating history of breast cancer. (we repeated the analyses, controlling for history of any form of cancer. Results did not differ substantively.)
1). Analyses of continuous variables (eg, age) involved simple one-way ANOVAs, whereas analyses of dichotomous variables (eg, marital status) involved contingency table analysis (ie, chi-square). As indicated in Table 1, the only significant difference found between the four diagnostic groups was previous history of cancer, indicating that the breast cancer group was significantly more likely to report a previous cancer diagnosis than the remaining three groups. The failure to find a significant difference for age was quite surprising in view of the positive relationship between age and prevalence of cancer found in most studies.6 Given the significant diagnostic group differences in history of cancer, this variable was statistically controlled in later analyses. This served two purposes. First, it allowed
~~
TABLE 1 Demographic Variables
Item (number) Age (years) Cigaretteslday Drinkdweek Number of children Age at first pregnancy
Cancer
Precancer
Cyst
Normal
M
M
M
M
F
55.7 4.7 2.2 2.7 22.9
53.4 3.5 1.6 2.3 22.2
53.1 3.4 I .7 2.7 22.5
52.9 3.0 1.3 2.7 22.3
1.17 0.90 1.80 1.25 0.32
Cancer
Precancer
cyst
Normal
Item
To
To
070
To
XI
Used oral contraceptive Work full time Ovary removed Marital status Single Married Divorced Separated Widowed Had cancer Mother had cancer Sister had cancer Aunt had cancer Maternal grandmother had cancer Paternal grandmother had cancer
46
48
84
87
26
16
43 85 25
45 89 25
2.49 2.60 2.49
8 66
71
7 1
15 1
9 64 12
18 44 19 14 22 14
12 18 18 14 28 10
8 64 10 4 15 18 14 14 18 II
3 13 19 12 13 19 9
12.43 28.09. 4.66 0.04 4.41 I .60
8
10
9
7
1.16
*p
1
< .01.
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PSYCHOSOCIAL FACTORS AND BREAST CANCER
In addition to controlling for history of breast cancer, we also controlled for age in later analyses. Although the differences between diagnostic groups in terms of age failed to reach significance, the importance of controlling for age has been emphasized in the literature.‘ The admittedly modest association between age and diagnostic classification was eliminated by controlling for age, which still left ample degrees of freedom for examining relationships involving psychosocial variables.
are therefore presented here.) As indicated by the factor loadings, the resulting structure was simple and highly interpretable, with each item loading essentially on one and only one factor. Using .30 as a cutoff criterion for the factor loadings, we found that 27 of the original 42 items loaded on one of the eight factors. Based on items with the highest loadings, we labeled these factors Job Security (4 items), Moving (4 items), Farmly Illness (4 items), Birth (2 items), Self Illness (3 items), Financial Difficulty (4 items), Marriage (2 items), and Separation (4 items). Reliability estimates for these scales ranged from S O to .74 (see Table 2), with three of the eight scales having reliabilities greater than or equal to .70. This suggests that three of these scales were acceptable for research purposes, whereas the remaining five were marginally acceptable.>
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Dimensionality and Psychometric Properties of Measures We conducted factor analyses with oblique rotation on the life events, coping, and Type A measures. The primary purpose of these analyses was to identify natural groupings of items in order to form subscales for later analyses. For each analysis, we used both a scree test” and factor interpretability as criteria for determining the number of factors to retain. The reliability of the resulting subscales was estimated using Cronbach’s alpha$’ results of these analyses for each set of measures are described below.
Coping Factor analysis of the coping items yielded a four-factor solution, accounting for 27% of the common variance. The factor loadings again revealed a simple structure, though the magnitudes of the loadings were rather low (none greater than .a), making factor interpretation somewhat difficult. Thirty-four of the original 38 items had loadings of at least .30. Based on items with the highest loadings, we labeled these factors Maladaptive (14 items), DeniaVAvoidance (9 items), Seek Social Support (7 items), and Venting (4 items). Reliability estimates for the resulting scales
Lijie Events Factor analysis of the life event items yielded an eightfactor solution, accounting for 31Vo of the common variance. (When we conducted analyses for both event occurrence and event severity data, we found no substantive differences. Only those results pertaining to the severity data
TABLE 2 Means, Standard Deviations, Correlations. and Reliabilitiesi for All Scales ~~
Scales Job Security (JS) Moving (M) Family Illness (FI) Birth (B) Self Illness (SI) Financial Difficulty (FD) Marriage (M) Separation (S) Maladaptive (MD) DeniaVAvoidance ( D A ) Social Support (SS) Venting (V) Time Urgency (TU) Ambition ( A ) Loner ( L )
M
SD
JS
2. I 1.7 6.2 .2 4.0 2.4 .2 I .6 4.2 3.7 1.5 .9 36.9 29.6 12.0
4.9 4.5 9.3 1.6 7.0 5.5 I .4 4.9 4.9 2.4 I .5 1.1 12.5 7.4 5. I
(.63) .I9
M
~70) .I4 .06 .03 .I4 .08 .I7 .I7 .I0 .I4 .I4 .I4 .06
.to .04 .08 .32 .I2 .25 .I8
.04 .I6
.I5 .I9
.I5 -
.05
~
.04
FI
(.72) .I0 .I4 .I4 .06 .09
B
( .74)
.I0 .I4 .22 .I3
.I5
.04
(.67) .25 .04 .I4 .22 .I0 .03 .06 .04
.01 .02
.01 .06
.09 .01 .06 .05
.07
.II .I5 .II .01 - .02
SI
-
tReliabilities are given o n [he diagonal.
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EDWARDS ET AL
ranged from .53 to .80, with two of the four scales having reliabilities greater than or equal to .70 (see Table 2). Overall, these estimates were somewhat higher than those obtained for the life events scales, though the maladaptive and denial scales fared considerably better than the seek social support and venting scales.
Type A Behavior Pattern
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Factor analysis of the Bortner items yielded a threefactor solution, accounting for 34% of the common variance. Again, the factor loadings revealed a simple structure, though the first two factors were more interpretable than the third. Twelve of the original 14 items had loadings of at least .30. Based on items with the highest loadings, we labeled these factors Time Urgency (6 items), Ambition (4 items), and Loner (2 items). Reliability estimates for the resulting scales were .78 for time urgency, .65 for ambition, and .46 for loner, indicating that the loner scale was quite unreliable (see Table 2). Its inclusion in later analyses was therefore viewed as exploratory, and associated results should be viewed with caution. Multinominal Logit Analyses
We conducted a series of multinominal logit analysesw3z to assess whether life events, coping, and the Type A be-
havior pattern were related to clinical diagnoses. Like discriminant analysis, logit is appropriate for assessing the relationship between a set of continuous independent variables and a categorical dependent variable. Unlike discriminant analysis, however, logit provides estimates for specific independent variables rather than a composite linear function of the independent variables (ie, a discriminant function).33As a result, logit provides a clearer interpretation of the effects of specific independent variables, which was the primary focus of the present study. In addition, logit is less sensitive to departure from normality than discriminant analysis,” which was characteristic of several independent variables used in this study, particularly those derived from the life events scale. For these reasons, we selected logit for the present study. For each analysis, history of breast cancer was entered into the model first, age was entered second, and the set of psychosocial variables under consideration (ie, life events, coping, Type A, avadability of social support) was entered third. The significance of variables, both individually and taken as sets, was determined using the Wald test, 32 which is analogous to the F ratio corresponding to a set of restrictions in multiple regression analy~is.~’ Figures in Table 2 show means, standard deviations, interscale correlations, and reliabilities for the eight life events scales, four coping scales, and three Type A scales used as independent variables.
(.@)
.12 .28 .26 .15 .03 .28 .07
(.SO) .26 .06 .05
.02
.08
.04
.02 .01
.01
.01
Spring 1990
(.59)
.26 .I3 .I3 .20 .09
.13 .01
(.go) (.75) .27
(.55)
.40
.20
.43 .24 .47 .14 - .01
- .01 - .07
.06
.02
.04
(.53) .I2
.06 - .28
.04 .08
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Life Events Logit results for the eight life events scales are shown in Table 3. Our initial analyses used event severity rather than event occurrence, based on the assumption that the patient’s appraisal of the event would substantially influence experienced stressM6’” and on the modest but consistent superiority of weighted v unweighted life events in the prediction of ~ymptomatology.~~”~ The eight life events scales as a set did not contribute significantly to the prediction of diagnostic classification when we controlled for age and history of breast cancer (p > .lo). Nonetheless, tests of individual predictors indicated that selfillness and birth were marginally significant as independent predictors of diagnostic classification (p < .lo). Inspection of coefficients revealed that, for self-illness, patients in the cancer group scored higher than those in the precancer, cyst, and normal groups, indicating that events such as hospitalization, operation, and illness were rated as more upsetting by patients with cancer. For birth, patients in the precancer group scored lower than patients in the cyst and normal groups (no patients in the cancer group reported a birth event), indicating that pregnancy and birth were rated as less upsetting by patients with precancerous abnormalities. Because these predictors were only marginally significant, and because the life event variables as a set were not significant, these findings should be considered highly tentative. The lack of significant relationships found in the above analyses was unexpected and, in fact, deviated from earlier research into the relationship between stress and breast cancer.’.6 We therefore conducted a series of follow-up analyses to explore several potential reasons for this deviation. One potential reason is that the event severity ratings may have simply added noise to the data rather than contributing substantive information, so we repeated the logit analyses, this time using event occurrence rather than event seventy. Results again indicated that the life event variables as a set did not contribute significantly to the prediction of diagnostic classification, though self-illness and birth were again rnargjnally significant. The coefficients for these variables indicated the same general pattern of intergroup differences. In addition, total event occurence became marginally significant, with the cancer and precancer groups reporting slightly more life events than the remaining two groups. Thus, except for minor variations, the results for event occurrence were the same as those for event seventy. A second potential reason why so few significant relationships were found is that too many diagnostic groups were used, thereby creating distinctions with little sub-
10
TABLE 3 Relationship Between Life Events and Diagnostic Classificationt
Source Had breast cancer Age Life Events
Job Security Moved Family Illness Birth Self Illness
Financial Difficulty Marriage Separation
x= 30.50* 1.67 28.61 5.46 1.16 5.10 7.72 7.06 1.78 0.24
0.50
‘p < . O l . tDashed lines indicate that the predictors were analyzed hierarchically.
stantive meaning. It could be argued that, from a clinical standpoint, the normal and cyst groups were essentially the same in that neither group demonstrated symptoms of cancer. Because of this, we collapsed the normal and cyst groups and repeated the analysis for both event severity and occurrence data. For event severity, the effects of total life events, self-illness, and birth now reached significance (p < .05), with the cancer and precancer groups reporting greater upset from life events than the combined normal/cyst group. In addition, family illness became marginally significant, with the cancer and precancer groups reporting more upset from family illness than the combined normal/cyst group. For event occurrence, the effect for self-illness became significant (p < .05), and the effect for birth remained marginally significant. The effects for total life events and job security also became marginally significant, with the cancer and precancer groups reporting more total life events and more events that threatened job security than the combined normal/ cyst group. Although these analyses yielded some significant findings, it should be noted that significance was achieved because the three-group analyses required a lower critical chi-square than the four-group analyses, not because the magnitude of the effect had increased. The
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more major home renovation than the remaining three groups. The pattern for retirement was more complex, with the normal group scoring highest, followed by the precancer, cyst, and cancer groups. Three life events revealed marginally significant differences, and agab the pattern of group differences was varied. Specifically, the precancer group reported a greater increase in responsibility for elderly and sick persons and more illness of family members than the remaining three groups, whereas the cyst and normal groups reported more births than the cancer and precancer groups. Results from the severity data differed rather markedly from those obtained from the occurrence data. For example, of the five variables that were significant for event occurrence, only one (threat of job loss) was significant for event severity, though two (major home renovation and retirement) were marginally significant. For these variables, the pattern of results for event severity was basically the same as for event occurrence. Furthermore, none of the variables that were marginally significant for event occurrence (including total life events) were marginally significant for event seventy. Three variables that were not marginally significant for event occurrence, however, were marginally significant for event severity. Specifically, the precancer group indicated that increased debt and difficulty with children were more upsetting than the remaining three groups, whereas the cyst and normal groups indicated that selling a house was more upsetting to them than to the cancer and precancer groups.
practical importance of significance achieved through such a procedure is rather dubious. A third potential reason why so few significant relationships were found is that the life event items may have been combined inappropriately when the subscales were formed, thereby concealing important information. We therefore conducted a second series of follow-up analyses, first on an overall index created by summing all life event items, then on each individual life event. We conducted these analyses on both event occurrence and event severity data (see Table 4).* As before, all analyses controlled for age and history of breast cancer. Results for total event occurrence were marginally significant, with patients in the precancer group reporting slightly more life events than those in the cancer group, who in turn reported more events than patients in the cyst and normal groups. Of the 42 individual life events examined, 5 revealed significant differences, though the pattern of group differences varied greatly. For example, the cancer and precancer groups reported more change in the nature of work and greater threat of job loss than the cyst and norma! groups. The cancer group, however, reported more surgery than the remaining three groups, and the precancer group reported *The overall indices created by summing all Occurrence and seventy events demonstrated acceptable reliabilities of .72 and .75, respectively. An obwous problem with analyzing individual life events. however, is that the reliability of individual items cannot be estimated. It is, therefore, difficult to attribute lack of significance to attenuation due to unreliability or to the true absence of an effect. Hence, the results concerning indi..idual life events should be interpreted with this caveat in mind.
TABLE 4 Follow-Up Analyses of Life Eventst
Item ( n u m b e r )
Cancer
Precancer
cyst
Normal
vo
vo
vo
Q70
11
22 22
9 13
9
8.90*
11
8.74*
2 44
6 6 22
4 4 19
I 8
9.90* 9.29'
19
10.00*
0.37
0.36
0.28
0.08
7.94'
x=
Occurrence M a j o r renovation C h a n g e in n a t u r e of work Threat of j o b loss Retired
Surgery Severity (M) Threat of j o b loss
18 7
* p < .05. * p < .01. tAll analyses controlled for history of breast cancer and age.
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PSYCHOSOCIAL FACTORS AND BREAST CANCER
The above analyses imply several relationships that were not evident in the analyses of the eight life events scales. These relationships should be interpreted with caution, however, in that the large number of statistical tests conducted drastically increased the probability of a Type I error. For example, if the alpha for 42 independent tests is set at .05, then the probability of finding at least one significant effect, assuming no significant relationships actually exist, is approximately .88. If the tests are not independent (as in the case of the 42 life event indices), then this probability is somewhat lower but still much larger than the intended alpha of .05. Using the Bonferroni technique to correct for this would result in an alpha of .05/42, or .0012. If we adopted this more conservative approach, then none of the relationships reported in Table 4 would be considered significant.
Coping Logit results for the four coping scales indicated that neither the coping variable as a set nor the individual predictors were significant. We again conducted a series of follow-up analyses on the individual coping items, as we had with the life event data. None of these analyses reached significance.
Type A Behavior Pattern As with the coping scales, logit results for the three Type A scales indicated that neither the Type A variables as a set nor the individual predictors were significant. A series of follow-up analyses on individual items did not reveal any significant relationships.
Availability of Social Support As with the coping and Type A scales, logit results for the seven availability of social support indices revealed that neither the variables as a set nor the individual predictors were significant. N o significant relationships were found in follow-up analyses.
Moderating Effects of Coping, Tvpe A , and Availability of Social Support We examined coping, Type A, and availability of social support as moderators of the relationship between stressful life events and diagnostic classification. These effects were examined by hierarchically entering the product of life events and the moderator variable under consideration into the model, after controlling for life events and the moderator variable."' As before, these analyses also controlled for history of breast cancer and age. Because of
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the potentially large number of interactions, we first tested the moderating effects of the coping, Type A, and availability of social support subscales on the relationship between total life events (both occurrence and seventy) and diagnostic classification. If significant moderating effects were found, then furtner analyses of separate life events scales would reveal the particular events involved in these effects. None of the interactions between total event seventy and the coping, Type A, and availability of social support subscales reached significance. Because of this, we conducted no further analyses involving the separate life events scales.
DISCUSSION This study detected very few significant relationships between psychosocial variables and diagnostic classification. Analyses of life events subscales revealed marginally significant effects for self-illness and birth. Analyses of individual life events revealed additional relationships, but the large number of statistical tests conducted warrants caution in the interpretation of these results. No significant effects were found for coping, Type A, or availability of social support, nor did these variables moderate the relationship between total life events and diagnostic classification. Before concluding that the above findings indicate no relationship between psychosocial factors and breast cancer, it is necessary to consider methodological problems that may have inflated Type I1 error, thereby preventing the detection of relationships that, in fact, exist. One potential problem typically considered is inadequate statistical power." This, however, was an unlikely explanation in the present investigation, given the substantial sample size. Another potential problem is restricted range of variables included in analyses, but descriptive statistics indicated that, with few exceptions, responses were obtained throughout the entire potential range for each variable. A third potential problem is unreliability of measures included in analyses. Though no estimate of reliability was available for the criterion measure (ie, diagnostic classification), the clinical rigor taken to derive this measure suggests that it contained very tittle error. On the other hand, several predictor variables yielded rather low reliability estimates, suggesting that they contained substantial amounts of error variance. Even scales with high reliabilities, such as maladaptive coping (alpha = .80), time urgency (alpha = .78), and total event severity (alpha = .78), did not exhibit significant associations with diagnostic classification. These methodological reasons for a lack
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of significant effects can therefore apparently be ruled out in the present study. In light of the preceding discussion, we must tentatively conclude that the psychosocial variables included in this investigation were simply not related to the incidence of breast cancer. This conclusion is underscored by the fact that the only life events subscales that reached even marginal significance (self-illness and birth) may reflect physiological rather than psychosocial correlates of breast cancer. Nonetheless, it should be emphasized that the conclusions of this study are valid only for the measures and sample involved. For example, although the measures of acute life events were generally unrelated to breast cancer, it is nonetheless plausible that significant relationships may exist for either chronic situations or daily hassle^.^^.^^ In addition, although the sample used in this investigation was quite large, it was drawn exclusively from a restricted geographical region. Therefore, the generalizability of these findings to other samples awaits empirical verification. Furthermore, controlling for other known breast cancer risk factors (eg, deviation from ideal body weight, history of breast feeding, estrogen in addition to birth control pill, etc) may have altered the results of our study. When compared with work conducted in the United Kingdom concerning the link between psychosocial factors and breast cancer," the results of the present study show some similarities as well as some qualitative differences. First, both studies confirmed that only a handful of major life events, rather than all adverse events, are implicated in breast cancer. Second, both studies suggest that self-illness events (eg, the occurrence of illness, hospitalization, and surgery) that involved illnesses other than breast cancer were related to subsequent breast cancer diagnosis. Third, both studies found that Type A behavior, a variety of coping strategies, and the availability of social support were not significant predictors of breast cancer. Since many of these measures have been derived in the context of cardiovascular and mental health research, they may not be appropriate measures for cancer research. Fourth, both studies indicate that loss-related events were related to breast cancer. However, in the United Kingdom study, these events referred to death of a husband or close friend, whereas in the United States study, these events referred to threatened loss of a job. One explanation for this divergence is that fewer psychological or bereavement counseling facilities are available in the United Kingdom than in the United States, suggesting that women in the United States who experience the death of a husband or close friend are able to seek appropriate counseling support more readily than British wom-
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en. This may help minimize the impact of loss-related events involving interpersonal relationships, thereby buffering their effects on immune system re~ponse.~' In conclusion, the results of this study indicate that life ebents, coping, Type A behavior pattern, and the availability of social support are largely unrelated to the incidence of breast cancer. Given the inconsistency of these results with earlier studies,' we need much more research to verify the connection between psychosocial factors and breast cancer, to identify possible moderating factors (eg, personality, coping strategies, social support), and to fully understand the psychophysiology of the disease process.
INDEX TERMS stress. Type A behavior. coping, social support, bread cancer
NOTE Address correspondence to Jeffrey R. Edwards, PhD, The Darden School, University of Virginia, Charlottesville, VA 22W6-6550.
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The National AIDS Information Clearinghouse 1-800-458-523 1 FAX: 1-301-738-6616 Call us. We’re your centralized resource for information on HIVIAIDS programs, services, and materials. A srnrice ol‘ I l i e U . S . L)elxirlment of Hralth and t Iiimiiii S e n k r s I’itbIic tlrallh Srnrice C:cnters lor I>israseControl
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