Decisional conflict in economically disadvantaged men with newly diagnosed prostate cancer: Results from a shared decision-making trial

Abstract

BACKGROUND

Decisional conflict is a source of anxiety and stress for men diagnosed with prostate cancer given uncertainty surrounding myriad treatment options. Few data exist to help clinicians identify which patients are at risk for decisional conflict. The purpose of this study was to examine factors associated with decisional conflict in economically disadvantaged men diagnosed with prostate cancer before any treatment choices were made.

METHODS

A total of 70 men were surveyed at a Veterans Administration clinic with newly diagnosed localized prostate cancer enrolled in a randomized trial testing a novel shared decision-making tool. Baseline demographic, clinical, and functional data were collected. Independent variables included age, race, education, comorbidity, relationship status, urinary/sexual dysfunction, and prostate cancer knowledge. Tested outcomes were Decisional Conflict Scale, Uncertainty Subscale, and Perceived Effectiveness Subscale. Multiple linear regression modeling was used to identify factors associated with decisional conflict.

RESULTS

Mean age was 63 years, 49% were African American, and 70% reported an income less than $30,000. Poor prostate cancer knowledge was associated with increased decisional conflict and higher uncertainty (P < .001 and P = 0.001, respectively). Poor knowledge was also associated with lower perceived effectiveness (P = 0.003) whereas being in a relationship was associated with higher decisional conflict (P = 0.03).

CONCLUSIONS

Decreased patient knowledge about prostate cancer is associated with increased decisional conflict and lower perceived effective decision-making. Interventions to increase comprehension of prostate cancer and its treatments may reduce decisional conflict. Further work is needed to better characterize this relationship and identify effective targeted interventions.

INTRODUCTION

Men diagnosed with localized prostate cancer face myriad choices in the decision-making process. Management options include active treatment – i.e. surgery and radiation therapy – or active surveillance. While quality of life detriment has traditionally been ascribed to prostate cancer treatment¹, recent studies illustrate the health related quality of life (HRQOL) impact in men undergoing active surveillance as well^2,3. To that end, the decision-making process for men with localized prostate cancer is a challenging task for even the most well informed patients.

Shared decision making (SDM) is a process by which physicians share relevant risk and benefit information of all treatment options and patients share relevant personal information with the clinician⁴. Thereby, a truly patient-centered decision is reached. Decisional conflict is a central focus of the interactions that are a part of SDM. It is a measure of the uncertainty surrounding a treatment choice and patient confidence in making that decision⁵. Decisional conflict is especially important for choices complicated by competing risks and outcome uncertainty⁶ and may be a useful tool for measuring decision quality⁷. Decisional conflict is associated with decisional regret⁸ and a higher likelihood of blaming physicians for adverse effects⁹. Medical decision-making experts advocate for the use of decisional conflict assessment in the clinical setting to ensure provision of adequate patient support¹⁰.

The anxiety inherent in the prostate cancer decision-making process stems from the complexity surrounding treatment options and a lack of consensus on ideal management¹¹. In men with prostate cancer participating in a SDM process, reduction in decisional conflict may be a good indicator of better decision quality⁷. Identifying men who have higher pre-treatment decisional conflict may allow for targeted SDM interventions. However, few data exist to guide physicians in determining which patients are at risk for decisional conflict, particularly in economically disadvantaged populations. To identify factors associated with decisional conflict, we conducted a cross-sectional study of economically disadvantaged men with newly diagnosed localized prostate cancer before any treatment choices were made. We hypothesized that men with lower knowledge about prostate cancer and lower educational achievement in general would have higher decisional conflict scores.

METHODS

Study Design

The institutional review board at the University of California, Los Angeles, and the Greater Los Angeles Veterans Health Administration approved this study, and informed consent was obtained from all subjects. Subjects with no prior history of prostate cancer undergoing biopsy were recruited into a multiarm randomized SDM trial. The trial sought to evaluate and improve parameters of SDM through application of a novel tool employing patient preference assessment. All subjects in the study completed baseline demographic questionnaires and survey instruments, which were used in this cross-sectional analysis of baseline data. Men were included in this analysis if they had a biopsy demonstrating prostate cancer and could be enrolled before their cancer consultation. Baseline demographic, clinical, and functional data were obtained as well as prostate cancer knowledge assessment and scores from the Decisional Conflict Scale (DCS).

Instruments and Psychometric Properties

We used the Decisional Conflict Scale (Appendix 1) and its subscales, Uncertainty and Perceived Efficacy, to determine decisional conflict ⁶. The DCS is well validated and has been used in a variety of populations, including men facing decisions about treatment for benign prostatic hypertrophy¹². The Perceived Efficacy subscale measures the extent to which decisions would be informed, consistent with personal values, and would be implemented⁶. Measured variables included age, race, relationship status, education, Charlson Comorbidity Index¹³, prostate cancer knowledge score¹⁴, and EPIC urinary incontinence and sexual functioning scores¹⁵.

Statistical Analysis

We used multiple linear regression modeling to identify factors associated with decisional conflict. Demographic, medical, and baseline functional variables were selected a priori. Adjusted means were calculated as predicted means from the estimated linear regression equation with all other covariates set to their mean values. Statistical significance was defined a priori as 0.05. P-values >0.1 are omitted from the tables for clarity.

Conceptual Framework

This study was guided by a broad conceptual framework (Figure 1) – adapted from Fishbein’s Integrative Model of behavior^16,17 – that captures the working elements of the prostate cancer decision-making process. The context into which a man enters the process is framed by his demographic, medical and psychosocial backgrounds. His unique set of health beliefs direct the behavioral intention, which in turn frames the decision-making process with the physician. This study explores the unique role decisional conflict plays toward the end of the decision-making process.

Figure 1.

Conceptual framework of decision-making process in localized prostate cancer.

RESULTS

Data from all men with newly diagnosed localized prostate cancer (n=70) enrolled in the SDM trial trial between January 2011 and October 2013were for used for this analysis. Cohort characteristics are shown in Table 1. Mean age was 63 years and nearly half of the cohort was African-American. Seventy percent reported an annual income less than $30,000 and 68% were either retired or unemployed.

Table 1.

Cohort characteristics.

Characteristic	Mean ± SD, Range or n (%)
Age	63 ± 6, range 45 to 78
Race/ethnicity
White (non-Hispanic)	24 (34%)
Black/African American	34 (49%)
Hispanic/Latino	8 (11%)
Other or mixed race/ethnicity	4 (6%)
Partnership status
In significant relationship	41 (59%)
Not in a significant relationship	29 (41%)
Employment status
Employed	22 (31%)
Unemployed	12 (17%)
Retired	36 (51%)
Educational attainment
High school graduate or less	21 (30%)
Some college	29 (42%)
College graduate	19 (28%)
Household income
Less than $10,000	13 (19%)
$10,000 to $30,000	35 (51%)
More than $30,000	20 (29%)
Current smoker	19 (27%)
Medical conditions (ever had)
Diabetes	11 (16%)
Heart attack	9 (13%)
Stroke	7 (10%)
Amputation	2 (3%)
Circulation problems	12 (17%)
Asthma, emphysema or breathing problems	12 (17%)
Stomach ulcer or irritable bowel	11 (16%)
Kidney disease	3 (4%)
Major depression	18 (26%)
Seizures	4 (6%)
Alcoholism or alcohol problems	17 (24%)
Drug problems	12 (17%)
Problems in last 4 weeks
Urinary function	17 (24%)
Sexual function	31 (44%)
Bowel habits	7 (10%)
Hot flashes	1 (1%)
Breast tenderness/enlargement	0 (0%)
Depressed	10 (14%)
Lack of energy	9 (13%)
Change in body weight	6 (9%)

The linear regression analysis is presented in Table 2. Older age was associated with lower perceived efficacy in decision-making (p=0.005). Poor prostate cancer knowledge was associated with increased overall decisional conflict and more uncertainty (p<0.001 and p=0.001, respectively). Poor knowledge was also associated with lower perceived efficacy (p=0.003). Being in a relationship was associated with more decisional conflict (p=0.03). Adjusted R² values ranged from 0.13 to 0.19. Adjusted means, calculated from the regression model, are provided in Table 3. Figure 2 also displays the adjusted means from total DCS score graphically. Unadjusted means were omitted, as the results were largely similar. Higher prostate cancer knowledge scores were associated with lower decisional conflict across all domains.

Table 2.

Linear regression models.

	DCS total score		DCS Uncertainty subscale		DCS Perceived Efficacy subscale
	Adjusted R2: 0.18		Adjusted R2: 0.13		Adjusted R2: 0.19
	Coef (SE)	p	Coef (SE)	p	Coef (SE)	p
Age (10-year increase)	−.28 (.21)		.05 (.29)		−.59 (.20)	.005
Black (ref: White)	.25 (.26)		.56 (.36)		−.07 (.26)
Hispanic (ref: White)	−.14 (.39)		.30 (.55)		−.59 (.39)
Other race (ref: White)	−.11 (.49)		−.06 (.70)		−.69 (.49)
In significant relationship (ref: not)	.54 (.24)	.03	.67 (.34)	.05	.44 (.24)	.08
Some college (ref: high school or less)	.09 (.30)		−.05 (.42)		.18 (.30)
College (ref: high school or less	.04 (.32)		−.06 (.44)		.16 (.31)
Charlson Comorbidity Index (1-pt increase)	−.02 (.10)		.05 (.14)		−.02 (.10)
Urinary functioning problem	−.01 (.28)		−.01 (.40)		−.10 (.28)
Sexual functioning problem	.20 (.24)		.25 (.34)		.26 (.24)
Prostate cancer knowledge score	−1.9 (0.5)	<.001	−2.4 (0.7)	.001	−1.5 (0.5)	.003

P-values >0.1 not provided.

DCS – Decisional Conflict Scale

Table 3.

Adjusted means as derived from the regression model.

	DCS total score		DCS Uncertainty subscale		DCS Perceived Efficacy subscale
	Adjusted mean (SE)	p	Adjusted mean (SE)	p	Adjusted mean (SE)	p
Age
<65 years	2.4 (0.2)		2.4 (0.2)		2.4 (0.2)
≥65 years	2.2 (0.2)		2.4 (0.2)		2.0 (0.2)
Race/ethnicity
White	2.2 (0.2)		2.2 (0.3)		2.3 (0.2)
Black	2.5 (0.2)		2.7 (0.2)		2.3 (0.2)
Hispanic	2.0 (0.3)		2.3 (0.5)		1.8 (0.3)
Other	2.2 (0.5)		2.2 (0.6)		1.8 (0.5)
In significant relationship		.02		.04		.06
Yes	2.6 (0.2)		2.7 (0.2)		2.4 (0.2)
No	2.0 (0.2)		2.0 (0.2)		1.9 (0.2)
Education
HS or less	2.4 (0.2)		2.7 (0.3)		2.2 (0.2)
Some college	2.3 (0.2)		2.3 (0.2)		2.3 (0.2)
College graduate	2.2 (0.2)		2.3 (0.3)		2.2 (0.2)
Comorbidity Score
High	2.3 (0.1)		2.4 (0.3)		2.2 (0.2)
Low	2.3 (0.2)		2.4 (0.2)		2.2 (0.1)
Urinary functioning problem
Yes	2.4 (0.2)		2.5 (0.3)		2.2 (0.2)
No	2.3 (0.1)		2.4 (0.2)		2.2 (0.1)
Sexual functioning problem
Yes	2.5 (0.2)		2.7 (0.2)		2.4 (0.2)
No	2.2 (0.2)		2.2 (0.2)		2.1 (0.2)
Prostate cancer knowledge score		<.001		.001		.003
Above average	2.0 (0.1)		2.0 (0.2)		1.9 (0.1)
Below average	2.9 (0.2)		3.1 (0.3)		2.7 (0.2)

P-values >0.1 not provided.

DCS – Decisional Conflict Scale

Figure 2.

a. Adjusted means of total DCS score for age, race/ethnicity, relationship status, and education.

b. Adjusted means of total DCS score for comorbidity, urinary and sexual dysfunction, and prostate cancer knowledge score.

DISCUSSION

In the prostate cancer decision-making process, men must weigh the risks and benefits of complex treatment modalities in the face of outcome uncertainty and lack of consensus among physicians regarding the best decision. Men with pre-treatment decisional conflict are important targets for SDM interventions. Few data exist however to guide clinicians in identifying these patients early in the decision-making process. Our cross-sectional study, identifying factors associated with decisional conflict in economically disadvantaged men, has several important findings.

First, poor prostate cancer knowledge was associated with increased overall decisional conflict and more uncertainty. In a separate prostate cancer SDM trial, Kim et al found that poor prostate cancer knowledge corresponded to lower literacy in men of low socioeconomic status (SES)¹⁸. An estimated 36% of adults in the United States have “basic” or “below basic” health literacy¹⁹. Men from economically disadvantaged backgrounds have alarmingly low prostate health literacy^19,20, making them susceptible to poor prostate cancer knowledge and decisional conflict. This literacy-knowledge deficit is an ideal target for educational intervention to improve decision-making in economically disadvantaged men with prostate cancer.

Although the literature examining decisional conflict is relatively immature, previous authors identified other mediators of decisional conflict in prostate cancer patients. Berry et al showed that men with localized prostate cancer that exhibited less uncertainty were more satisfied with their decision²¹. This cohort comprised predominantly white men from non-disadvantaged backgrounds. The effect of poor knowledge and uncertainty is likely more pronounced in the currently described cohort. In our analysis, we used a 14-item prostate cancer knowledge questionnaire¹⁴, which may represent a practical and effective means of screening for pre-treatment decisional conflict.

Second, poor prostate cancer knowledge and older age was associated with lower perceived efficacy in the decision-making process. Perceived efficacy is the belief in one’s own ability to complete tasks. In prostate cancer decision-making, perceived efficacy represents a man’s belief in his ability to make a good decision regarding the course of management. We found that men with poor prostate cancer knowledge, as well as older men, had lower perceived efficacy.

In a cross-sectional study of men on active surveillance for localized prostate cancer, Goh et al found that men with higher self-efficacy experienced less decisional conflict ²². Heckman et al showed that among disadvantaged men with localized prostate cancer those with low self-efficacy suffered worse quality of life across all domains²³. Likewise, perceived- or self-efficacy may also be important for preparedness in decision-making. In a study evaluating cancer patients’ preparedness for clinical trials, Manne et al determined that assessing self-efficacy might be as important as examining knowledge or attitudinal beliefs²⁴.

Finally, being in a relationship predicted more decisional conflict. In a study of low-income, uninsured men with prostate cancer, Gore et al identified an association between partnership status and improved quality of life²⁵. Conversely, Bergman et al demonstrated comparable physical and mental health scores between partnered and unpartnered men with prostate cancer, although this cohort was comprised of men with a homogeneously high SES²⁶. Prostate cancer is often referred to as a “couple’s disease” because the impact of treatment on the patient can decrease his ability to be a part of an ongoing sexual relationship with his partner²⁷. Discordant preferences between patient and partner might increase decisional conflict since the partner’s views are especially salient in the face of a potential decrease in their own sexual QOL. Further work into the impact of discordant preferences between patient and partner in this setting is indicated.

For men with newly diagnosed prostate cancer, their clinical consultation is the point of interaction with the health care system²⁸ but the impact of their diagnosis will extend further than the physician’s office. Our study identifies factors that may be used to distinguish which men are at high-risk for decisional conflict. These data are also hypothesis generating in that certain factors – i.e. prostate cancer knowledge – may represent a modifiable target to reduce decisional conflict. Widespread implementation of decision support interventions in clinical practice has been slow owing to lack of physician time and resources as well as information systems that are incapable of tracking patients through the SDM process^29,30. However, individual reports indicate that systematic approaches to reducing decisional conflict are feasible and effective. In a cohort of primary care patients, Ferron Parayre et al validated a four-item checklist (SURE) to detect decisional conflict ³¹; although this has not been studied in men with prostate cancer. A Scottish randomized controlled trial using a “decision navigation” intervention in men with newly diagnosed prostate cancer found less decisional conflict and lower decisional regret³². Likewise, interventions using health coaches in low-income patients in California has shown promise³³. Through early identification of men at high-risk for decisional conflict, clinicians may be able to guide the patients most in-need toward effective decision support interventions.

The potential for shared decision-making interventions to reduce decisional conflict via potential targets identified here may have benefits beyond those experienced by the patient. Reductions in decisional conflict are associated with decreases in patient delay in making a choice as well as measures of ‘fretting’ and ‘nervousness’³⁴. Improvements in decisional conflict may result in more confidence in patients’ overall decision-making ability. Such confident patients have been termed ‘activated’. Patient activation, as measured by an individual’s knowledge, skill and confidence in managing their own healthcare, correlates with improved health economic outcomes^35,36. Patient activation is also associated with higher compliance, an important consideration for men considering active surveillance³⁶.

The results of this study must be interpreted in the context of its limitations. First, the size of the cohort is relatively small. Internal review data show dropping referral rates to our clinic for abnormal PSA – likely reflecting new VA health system screening practice guidelines – which has resulted in fewer de novo cancer diagnoses. Nonetheless, we were able to detect significant differences and the factors associated with pre-treatment decisional conflict were similar when studied at interim analysis. Second, decisional conflict measured after the prostate cancer decision has been made is not available in this analysis. We felt that identifying clinical factors associated with pre-treatment decisional conflict was important to gain an understanding of the decision-making process in economically disadvantaged men with newly diagnosed disease.

CONCLUSIONS

In this cross-sectional study of men with newly diagnosed localized prostate cancer, we found that poor prostate cancer knowledge is associated with increased decisional conflict and lower perceived efficacy in decision-making. Through early identification of men at high-risk for decisional conflict, targeted interventions aimed at increasing comprehension of prostate cancer and its treatments may reduce decisional conflict. Further work is needed to better characterize this relationship and identify strategies to improve the decision-making process in economically disadvantaged men with this disease.

Appendix 1. Decisional Conflict Scale

	Strongly Agree [0]	Agree [1]	Neither Agree Nor Disagree [2]	Disagree [3]	Strongly Disagree [4]
1. I know which options are available to me.	□	□	□	□	□
2. I know the benefits of each option.	□	□	□	□	□
3. I know the risks and side effects of each option.	□	□	□	□	□
4. I am clear about which benefits matter most to me.	□	□	□	□	□
5. I am clear about which risks and side effects matter most to me.	□	□	□	□	□
6. I am clear about which is more important to me (the benefits or the risks and side effects).	□	□	□	□	□
7. I have enough support from others to make a choice.	□	□	□	□	□
8. I am choosing without pressure from others.	□	□	□	□	□
9. I have enough advice to make a choice.	□	□	□	□	□
10.I am clear about the best choice for me,	□	□	□	□	□
11. I feel sure about what to choose.	□	□	□	□	□
12. This decision is easy for me to make.	□	□	□	□	□
13. I feel I have made an informed choice.	□	□	□	□	□
14. My decision shows what is important to me.	□	□	□	□	□
15. I expect to stick with my decision.	□	□	□	□	□
16. I am satisfied with my decision.	□	□	□	□	□