J Clin Epidemic-d Vol. 45. No. 9, pp. 941-950. 1992 Printed in Great Britain. All rights reserved

0895-4356/92$5.00+ 0.00 Copyright 0 1992Pergamon Press Ltd

DECISION MAKING DURING SERIOUS ILLNESS: WHAT ROLE DO PATIENTS REALLY WANT TO PLAY? LESLEY F. DEGNER’.* and

JEFFREY

A.

SLOAN'

’School of Nursing, University of Manitoba, Winnipeg, Manitoba and *Manitoba Nursing Research Institute, Winnipeg, Manitoba, Canada (Received

in revised form

6 April

1992)

Abstract-Two surveys were conducted to determine what roles people actually want to assume in selecting cancer treatments. 436 newly diagnosed cancer patients and 482 members of the general public participated. Preferences were elicited using two card sort procedures, each of which described five potential roles in decision making. Findings suggested that the impact of being diagnosed with a life-threatening illness may influence preferences to participate. The majority (59%) of patients wanted physicians to make treatment decisions on their behalf, but 64% of the public thought they would want to select their own treatment if they developed cancer. Most patients (51%) and members of the public (46%) wanted their physician and family to share responsibility for decision making if they were too ill to participate. Sociodemographic variables accounted for only 15% of variance in preferences. These variables are not particularly useful in making-predictions about which groups want more or less active roles in medical decision making.

Patient participation Medical oncology Neoplasms Patient advocacy

INTRODUCTION

What role patients should assume in medical decision making is an issue that has stimulated

much debate. A wide variety of opinions exist, ranging from the view that patients should assume at least some responsibility for selecting their own treatment, to the position that it is unwise to encourage such participation because patients do not have the specialized knowledge required to make treatment decisions. We decided to ask patients what degree of responsibility they actually wanted to assume in medical decision making. While previous studies have attempted to determine patient preferences about participating in treatment *All correspondence should be addressed to: Dr L. Degner, St Boniface General Hospital Research Center, 351 Tache Avenue, Winnipeg, Manitoba, Canada R2H 2A6 [Tel. (204) 235-34821.

Decision making

Social psychology

decision making, those investigations were limited in several respects: preferences to participate were measured as a dichotomous rather than continuous variable [1,2]; study participants were asked to project themselves into an illness situation rather than using a current illness as the reference point [3,4]; or no attempt was made to control the stage of illness at which the measurement of preferences was conducted [ 1,2, 51. None of the existing studies were conducted with newly diagnosed cancer patients. People facing serious illnesses such as cancer have a more significant stake in treatment decisions than patients facing many other diseases because of the toxicity, changes in body image, and lifestyle disruptions that can occur as a result of the disease and its treatment. This paper reports the findings of two surveys. The first examined preferences of newly diagnosed

942

LE.WEYF. DEGNERand JEFFREY A.

cancer patients about roles in treatment decision making, while the second obtained an estimate of these preferences in a general population. The purpose of the studies was to determine the prevalence of differing preferences about roles in treatment decision making in the context of cancer, whether these preferences differed when people anticipate having cancer vs are actually diagnosed with cancer, and which demographic and disease/treatment factors were the most important predictors of these preferences. METHODS

Survey of cancer patients

A survey was conducted between 1 January and 30 June 1988, in the two tertiary referral clinics for cancer patients in the province of Manitoba. Manitoba is a province of one million people, and the clinics are located in Winnipeg, a city with a population of 630,000. The province of Manitoba provides comprehensive, universal coverage of health care costs without deductibles or user charges. A consecutive sample of every patient over 18 years of age and within 6 months of an initial diagnosis of cancer was approached. Only those who were too ill to participate or gave evidence of mental confusion in their interactions with health care professionals or the research nurses were excluded. Patients treated by all 24 oncologists practising at the two sites were recruited for this study. Demographic and disease/treatment information was obtained from the patient’s chart and through direct questioning of the patient. Two types of variables were recorded: those suggested in the literature as being predictive of patient preferences (age and educational level); and those suggested by clinicians as potential predictors of patient preferences (gender, urban/ rural residence, type and stage of disease, type of treatment, and whether or not the patient had agreed to enter an experimental treatment protocol). Two measures were used. The first was developed to elicit consumer preferences about roles in treatment decision making. The rationale for developing the measure emerged from an extensive field study of factors influencing how treatment decisions are made for patients with life-threatening illnesses. That study was conducted over a 4-year period in 14 different health care settings in Manitoba [6], and led to description of the variable “control over the

SLOAN

design of therapy”, or who actually selected the treatment options after consideration of potential risks and benefits. Four patterns of control were observed in health care practice: providercontrolled, patient-controlled, family-controlled, and jointly-controlled decision making. Since some patients seemed to have preferences about which pattern of control was best for them, a hypothesis was developed that consumers of health care could have systematic preferences about the degree of control they wanted in treatment decision making, ranging from no control to complete control. Preliminary support for this hypothesis was obtained in a pilot study [5], suggesting that preferences to make treatment decisions did have a rank order. The new measure of preferences to participate was a card sort that had two sets of five cards each. Each card described a different role in decision making and was illustrated with a cartoon. The first set of five cards (patient/ physician dimension) illustrated roles that the patient and physician could assume, ranging from the patient selecting his own treatment through a collaborative model to a scenario where the physician alone made the decision (see Fig. 1). The second set of five cards (family/physician dimension) was designed to indicate whom the patient would want to make treatment decisions on his behalf if he became too ill to participate. These options ranged from the patient’s family making the decision alone, through a collaborative model where the family and physician jointly decided, to a scenario where the physician made the decision alone. Patients completed the card sorts one at a time, comparing each card with every other card in subsets of two until their entire preference order across the set of five cards was unfolded. This method permitted subjects to make mistakes, or to be intransitive in their preference orders. The method was superior to the “pick one” approach of previous studies because patients had more opportunity to consider and weigh their alternative roles in decision making. Considering two options at a time is also a simpler task than arranging a series of altematives in order [7]. The task proved to be an interesting one for subjects, even for those with relatively low levels of education. The second measure, the symptom distress scale [8], was selected to test the clinical hypothesis that patients are less willing to assume decisional responsibility as their level of distress

943

Decisional Preferences

increases. The scale consists of 13 symptoms identified by patients as distressing, and each symptom is described by a card in a Spoint Likert format ranging from 1 (normal or no distress) to 5 (severe distress). This scale was developed in a population of ambulatory cancer patients, with reliability levels as assessed by Cronbach’s alpha ranging from 0.79 to 0.83 in previous research [9], and 0.80 in this sample. The symptom distress scale was recently adopted by the Southwestern Oncology Group as a measure of quality of life in Phase III clinical trials [lo].

Survey of householders

The 1989 Winnipeg Area Study was the seventh in an annual series of surveys that use the City of Winnipeg tax assessment list to draw a systematic random sample of 752 households. In-person interviews were conducted with householders over 18 years of age and interviews were randomly predesignated as male or female to ensure that gender balance was achieved in selecting householders. Data collection occurred between February and April of 1989 using 32 trained interviewers. The response

ACTIVE ROLE

PASSIVE ROLE >

-n

I PfGERTK4TVfDOCTORANDI SHAPE ESFONSIBILINFORL.ECIDING WHICH TfENlENTIS EST FORFE,

Fig. 1. Statements on the role preferences card sort.

944

LFSLEYF. DEGNERand JEFFREY A. SLOAN

rate of 72% for the 1989 survey was comparable to that of previous years. Details about the 1989 Winnipeg Area Study are published elsewhere [ 111. In addition to the standard demographic information collected each year in the survey, three questions were included in the omnibus section of the questionnaire where researchers can purchase space. The first was, “Please tell me if you have ever had cancer? (Yes/No)” Only those who had not had cancer were then asked to complete the same two card sorts as had the cancer patients. Householders were asked to project what their role preferences would be if they developed cancer. Statistical analysis

Data from the patient card sorts were analyzed using unfolding theory [ 121. This scaling method is based on the theory of preferential choice. Individual preference orders are “unfolded” to determine whether they are consistent with the existence of an underlying psychological dimension, providing a direct test of the hypothesis that participants had systematic preferences about the degree of control they wanted in treatment decision making, ranging from no control to complete control. Preference orders fell on the dimension if they were in a sequence that captured the hypothetical rank order of the decisional roles and the midpoints between them. For example, the person who had the most extreme desire to keep control would have arranged the vignettes in Fig. 1 in the order ABCDE, and would have received an ordinal score of 1. The person with the next most extreme score would have the preference order BACDE, having crossed the midpoint between A and B, and would have an ordinal score of 2; and so on using the model detailed in Coombs [12]. The combination of 5 decisional roles and their midpoints produces a dimension with 11 possible transitive preference orders, thus generating the ordinal score range from 1 to 11. The preference orders of 282/428 (66%) patients and 27 l/482 (56%) householders unfolded onto the psychological dimension of preferences about keeping, sharing, or giving away control over decision making to the physician. In addition, preference orders of 2671423 (61%) patients and 2841473 (60%) householders unfolded onto the psychological dimension about physician-family preferences.

A maximum of only 13% of the preference orders could have fallen on either dimension or by chance alone, suggesting that both cancer patients and householders had systematic preferences along these psychological dimensions. Respondents whose preference orders did not fall on either dimension could be assigned a categorical value for their preference by using the role they had selected as their first choice. The distributions of cancer patients by ordinal score (n = 282) and by categorical preference (n = 428) were virtually identical on the physician-patient dimension (x2 = 0.03, p = 0.999), and as a result both the ordinal and categorical scores were used in the subsequent analyses. However, distributions for householders on the patient-physician dimension and for both samples on the patient-family dimension were not identical for ordinal score and categorical preferences. The smaller samples (see Table 3) whose preference orders fell on the hypothetical dimension were used in estimating the preference distributions because these preference orders were scaled data. Distributions of preferences for subsamples were compared using chi-square. Rank order correlations were used to determine the relationship of respondents’ ordinal preference scores with other interval and continuous variables. The relative importance of demographic and disease/treatment variables in predicting preferences was examined using logistic regression [ 131 in the form of the proportional odds model proposed by McCullagh [14] when discussing regression models for ordinal data. These results were cross validated by assuming an interval level for the role preferences variable and using stepwise linear regression. Results were congruent across the three models, and only the results of the logistic regression are reported here. Finally, because the two samples showed marked discrepancies in their respective age distributions and age proved to be the only variable that had a significant impact on preferences, subsequent analysis was undertaken to determine the extent of this confounding covariate effect. ANCOVA was used to adjust the age effect as a continuous variable on the interval level preference scores. In addition, the impact of age as a categorical variable was examined using contingency tables of preference distributions across a dichotomous age cohort with categories of greater and less than 50 years of age.

Decisional Preferences

945

Table 1. Demographic variables Variables Age Gender Male Female Education Junior high or less High school > High school

Cancer patients (n = 436)

Householders (n = 482)

p Value

59

42

0.008

52% 48%

45% 55%

0.034

33% 43% 24%

9% 37% 54%

0.000

Table 2. Cancers by site (excluding malignant neoplasms of the skin) Cancer patient sample

Sites Oral cavity, pharynx (ICDA 140-149) Respiratory system (ICDA 161-165) Breast (ICDA 174-175) Genitourinary (female) (ICDA 179-184, 188, 189) Genitourinary (male) (ICDA 185-189) Lymphatic, hematopoetic (ICDA 200-208) Digestive organs (ICDA 150-159) Other Total

Percent sample

13

162

8.0

98

137

13.3

62

652

9.5

52

797

6.5

69

717

9.6

40

387

10.3

31

1118

2.8

71 436

449 5019

15.8 8.7

RESULTS

Subjects

A total of 436 newly diagnosed patients and 482 members of the general public participated in the two surveys (see Table 1). The patients were an average of 75 days post-diagnosis (SD = 41.8), with a mean age of 59 years (SD = 13.9). The householders had a mean age of 42 years (SD = 16.4). There were more females among the householders (55%) than among the cancer patients (48%). Only 9% of householders had less than grade 10 education compared with 33% of the cancer patients. The sample of 436 cancer patients represented 8.7% of patients who were diagnosed in Manitoba in 1988 (see Table 2). The most frequent sites of cancer for the sample were the respiratory and lymphatic/hematopoetic systems. The sample was underrepresented with patients diagnosed as having cancers of the digestive organs (2.8%) compared to the incidence in Manitoba in 1988 (22% of total cases). Preference

Incidence in Manitoba in 1988

distributions

The findings revealed different distributions of preferences about roles in treatment decision

making according to whether or not the respondent had cancer (see Table 3). The majority of newly diagnosed patients (59O/,) preferred that physicians make treatment decisions on their behalf. The most popular first choice of patients was the statement, “I prefer that my doctor Table 3. Distributions of preferences

Sample Cancer patients (n = 428) 50yr Householders (n = 271) c50yr >50yr

Cancer patients (n = 267) i50yr >50yr Householders (n = 284) i50yr >50vr

Active role (%)

Collaborative role (%)

Passive role (%)

12

29

59

21 10

37 27

42 64

64

27

9

69 53

24 33

7 14

Family dominant (%)

Physician-family share (%)

Physician dominant (%)

10

51

39

21 8

44

39

35 52

40

46

14

43 34

46 46

11 20

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941

Decisional Preferences

Preferences illicited by each card sort were to their family. HOWstrongly correlated in cancer patients (r = 0.72, ever, both groups agreed that they wanted p = 0.000) and in householders (0.54, the physician and family to collaborate in making treatment decisions if they became too p = O.OOO),with those who preferred to assume more control also preferring that their family ill to participate. Differences between cancer patient and householder distributions on the assume more control. Two variables were family/physician dimension are illustrated in related to preferences about decisional control if the respondents were too ill to participate. Fig. 3. Younger cancer patients preferred more family Distributions by age are displayed in Table 3. Younger people were more likely to prefer an involvement in decision making as did younger householders. Women with cancer also preactive role in treatment decision making, both for themselves and for their family if they ferred more family involvement in decision became too ill to participate. However, the making, particularly women with cancers of differences in distributions by age groups were the reproductive system, but a gender effect not as striking as the differences between the was not present in the householders. There were no differences in the distribution of these two samples. preferences by educational level in either cancer Univariate results patients or householders. The clinical hypothesis that patients who are The univariate analysis revealed that three more ill prefer less control in cancer treatment variables were related to preferences about keeping, sharing, or giving away control to the decision making was not supported. Neither physician: age, education, and gender. Age was symptom distress levels nor stage of disease were related to patients’ role preferences. Howcorrelated with role preference scores in both the cancer patients and householders, with older ever, only 62% of patients could be classified as patients preferring less control. There were having either early or advanced disease from the differences in role preferences by educational medical record at the time the patients were level in cancer patients, with more highly edu- tested. cated patients preferring more control. There There was a non-significant trend for more was a non-significant trend for more highly rural patients to give away control to their physician. The distribution of patients from educated householders to prefer more control. There was also a trend for women to prefer Winnipeg (58%) compared to rural areas (42%) more control than men in the cancer patient was similar to that of the provincial population. sample but not among the householders. The Since 85% of patients were not offered expersource of the gender effect in cancer patients imental treatment protocols, the sample size was was explored in subsequent analyses. Because insufficient to determine whether there were women with breast cancer have lobbied for differences between those who accepted (n = 44) legislation to ensure that treatment alternatives or refused (n = 13) experimental therapy. There are disclosed by physicians [15], women with were no differences in preferences according to reproductive cancers were hypothesized to be whether patients had received single vs multiple potentially different with respect to their role modalities of treatment. preferences than other women. Women with Predictors of preferences reproductive cancers were found to prefer more control than men with reproductive cancers, Results of the logistic regression (see Table 4) while a gender effect was not evident in patients revealed that age was the most important prewith other types of cancer. dictor of preferences about keeping, sharing or decisional

responsibility

Table 4. Predictor variables for role oreferences Cancer patients

x2 Aae Male, reproductive cancer Female, reproductive cancer Education

19.55 7.05 3.07 2.38

Householders

P

R

x2

P

R

0.000 0.008 0.080 0.123

0.15 0.02 0.04 0.02

7.48

0.006

0.11

Total R* for the cancer patient model = 14.8%

Total R2 for the householder model = 6.9%

948

LESLEYF. DEGNERand JEFFREYA. SLOAN

giving away control to the physician in both the bility to the physician is in marked contrast to cancer patients and householders, with older the findings of previous studies. Both Blanchard subjects preferring less control. Being a male et al. [l] and Cassileth et al. [2] used a two-item with cancer of the reproductive system was indicator of role preferences, and found that also a significant predictor of a passive role approximately two-thirds of patients picked the preference. The variables of education and statement, “I prefer to participate in decisions being a female with reproductive cancer entered about my medical care and treatment” in the model for cancer patients, but not at a preference to the statement, “I prefer to leave significant level. The fact that age and education decisions about my medical care and treatment are correlated likely accounted for education up to my doctor.” Cassileth et d’s [2] sample being significant in the univariate results but not consisted of 256 cancer patients who were in when included in the logistic regression. Only hospital or being seen in an ambulatory center, 14.8% of the variance in patient role preferences while Blanchard et d’s [ 1] sample consisted of and 6.9% in householder preferences were 439 hospitalized patients with cancer. Patients accounted for by the predictor variables. No in both studies were at various stages of their model emerged to predict cancer patient or disease and treatment. If the statement chosen householder preferences on the family/physician by two-thirds of patients in these previous dimension. ANCOVA results showed that the studies is considered to indicate either an active effect of age on preferences for the patient/ or collaborative role preference (see Fig. I), then physician dimension (F = 25.46, df= 1,549, approximately 25% more of the American p < 0.0001) was dominated by the effect of the patients preferred these roles than did the cancer presence or absence of cancer (F= 162.84, patients in our sample. df = 1,549, p < 0.0001). This was also true for There are at least three possible explanations the effect of age on preferences for the family/ for this finding. First, differences in the physician dimension (F = 10.01, df = 1,547, measurement technique may have influenced the p = 0.0016) when compared to the effect of results. In our study, patients considered five the presence or absence of cancer (F= 57.09,different roles in cancer treatment decision making, and compared them in subsets of two df= 1,547, p = 0.0001). in every possible combination. In the studies of Blanchard et al. [l] and Cassileth et al. [2], a “pick one” technique was applied to only two DISCUSSION alternatives. Since most patients in our study The two striking findings of this study were wanted the physician to make the decision but the high proportion of cancer patients who only after “seriously considering my opinion”, wanted to leave treatment decision to their at least some of these patients might have picked the statement, “I prefer to participate in physicians, and the marked difference between cancer patient and public preferences. The decisions about my medical care and treatment”. For some patients, participation could cancer patient sample represented more than 10% of patients newly diagnosed in the province mean providing information that is essential for during 1988 if patients with cancers of the the physician to make the best decision. A recent study of 288 patients treated in a digestive organs are excluded. The findings of this study are not generalizable to the latter general medical clinic in Boston also found that group of patients, who are often treated patients’ preferences for decision making were surgically and do not require subsequent generally weak [3]. The measure of preference referral for radiotherapy or chemotherapy treatwas a 15-item Likert type scale that consisted of 6 general items and 9 items related to one of ment. The sample provided by the Winnipeg Area Study is representative of the Winnipeg three clinical vignettes that represented different population as measured in the 1986 census with levels of illness severity. Similarly, a study of 106 respect to the key variables of gender, age, rehabilitation medicine patients using a 13-item household size, household income, and neigh- rating scale of decisional preferences found bourhood. The two samples were large enough that patients preferred to delegate treatment to provide stable estimates of role preferences as decisions to physicians [16]. Any measure that they existed in 1988 to 1989. allows for more variability than a two-item The very high proportion of cancer patients indicator may find a lower preference to assume who preferred to delegate decisional responsidecisional responsibility.

Decisional Preferences

A second explanation may be that patients in our study were close to time of diagnosis. The psychological impact of cancer may have influenced most patients to prefer a passive role, at least until they had had an opportunity to learn more about their disease and its treatment. Because we were unable to test patients on initial contact with the health care system, their preferences could also have reflected a learned expectation that they should assume a passive role. Longitudinal studies that start by measuring preferences early in the illness experience are necessary to determine whether preferences change in response to the behaviors of caregivers, and whether preferences change over time and in response to significant events such as relapse. Still another explanation may be cultural differences between Canadian and American patients, and/or differences in the health care system. Using a set of five statements similar to those used in our survey, Sutherland et al. [17] studied the preferences of 52 radiotherapy patients with early stage disease receiving treatment at the Princess Margaret Hospital in Toronto. The majority (63.5%) of these patients preferred a passive role in treatment decision making; 26.9% preferred a collaborative role; and only 9.6% preferred an active role. Our findings replicate this distribution for Canadian cancer patients being treated in a tertiary referral center. The second important finding of our study was the marked differences between cancer patient and public preferences. The strong effect of the presence or absence of cancer suggested that decision making preferences might be influenced by diagnosis of a life-threatening illness. In that context, being freed of responsibility for making treatment decisions can produce an immense sense of relief, with treatment failures becoming the responsibility of the practitioner rather than the patient [18]. Although several sociodemographic variables were related to role preferences on a univariate basis, the results of statistical modelling indicated that their influence was weak and inconsistent. Our results confirm those of Ende et al. [3] who found that age had the greatest explanatory power when stepwise regression was used to predict preferences in general medical patients, but that sociodemographic variables explained only 15% of the variance in preferences. Our results indicate that previous studies where preferences were not scaled

949

have led to inappropriate conclusions about the importance of variables such as age and education because only univariate analyses could be used. The distribution of patient preferences reported here is consistent with the results of previous observational studies. In a 4-year study that involved direct observations of incidents of clinical decision making in 14 different health care settings in Manitoba, very few examples of patients playing an active role in decision making were recorded [6]. Another observational study estimated that only about 10% of patients saw themselves as having an active role in decision making [19], similar to our finding. Patients have been observed to be extremely passive in medical encounters even when they want an active role [15,20]. On average patients ask only one direct question during each consultation session with a physician [21]. Previous findings [l, 21 that patients want to play an active role in medical decision making are not consistent with the clinical reality. The findings of our study demonstrated that patients newly diagnosed with a serious illness such as cancer are unlikely to seek an active role in selecting their medical treatment. The findings also suggested that the impact of the diagnosis of cancer may influence preferences to participate. Given the small proportion of variance in preferences accounted for by sociodemographic variables, individual assessment of preferences to participate in treatment decision making remains the best clinical approach. Acknowledgement-This research was supported by a grant from the National Cancer Institute of Canada.

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Thurstone’s method of paired comparisons. Int J Epidemiol 1981; lo: 93-97. McCorkle R, Young K. Development of a sympton distress scale. Cancer Nurs 1978; 1: 373-378. McCorkle R, Benoliel JQ, Donaldson G, Georgiadou F, Moinpour C, Goode11 B. A randomized clinical trial of home nursing care for lung cancer patients. Cancer 1989; 64: 1375-1382. Moinpour CM, Feigl P, Metch B, Hayden KA, Meyskens FL, Crowley J. Quality of life end points in cancer clinical trials: Review and recommendations. J NatI Cancer Illst 1989; 81: 485-495. Currie RF. Selected findings from the 1989 Winnipeg Area Study. Research Report No. 26, Department of Sociology,. University of Manitoba, June -1989. Coombs CH. A Theorv of Data. Ann Arbor. MI: Mathesis Press; 1976. ” Aldrich JH, Nelson FD. Linear Probability, Logit, and Probit Models. Beverly Hills, CA: Sage; 1984. McCullagh P. Regression models for ordinal data. J R Stat Sot 1980; 42: 109-142.

15. Annas GJ. Breast cancer: The treatment of choice. Hastings Cent Rep 1980; IO: 27-29. 16. Beisecker AE, Bcisccker TD. Patient informationseeking behaviors when communicating with doctors. Med Care 1990; 28: 19-28. 17. Sutherland HJ, Llewellyn-Thomas HA, Lockwood GA, Trichler DL, Till JE. Cancer patients: Their desire for information and participation in treatment decisions. J R Sot Med 1989: 82: 260-263. 18. Northouse LL, Wortman CB: Models of helping and coping in cancer care. Patient Educ Counsel 1990; 15: 49-64. 19. Lidz CW, Meisel A, Osterweis M, Holden JL, Marx JH, Muneta MR. Barriers to informed consent. AM Intern Med 1983; 99: 539-543. 20. Beisccker AE. Aging and the desire for information and input in medical decisions: Patient consumerism in medical encounters. Gerontologist 1988; 28: 330-335. 21. Robinson EJ, Whitfield MJ. Improving the efficiency of patients’ comprehension monitoring. Sue Sci Med 1985; 21: 9155919.

Decision making during serious illness: what role do patients really want to play?

Two surveys were conducted to determine what roles people actually want to assume in selecting cancer treatments. 436 newly diagnosed cancer patients ...
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