Purpose: Research has shown that racial minorities often have different treatment preferences than Whites.  One question is whether this is the result of knowledge deficits, differences in literacy or numeracy levels, or any of a number of factors.  In the present research, men receiving prostate cancer biopsies were given either a low or high literacy decision aid (DA), and then treatment preferences were assessed.  The purpose of the present research was to explore racial differences in treatment preferences following exposure to low versus high literacy DAs. 

Method: 1023 men from four VA hospitals were recruited at their prostate cancer biopsy appointment; 77% of the participants were White, and 23% were non-White (of which 92% were African American).  At Time 1 participants were randomly assigned to receive either a low or high literacy prostate cancer decision aid.  Literacy (using the REALM), and subjective numeracy were also assessed.   At Time 2, which occurred after participants read the DA but just prior to receiving a prostate cancer diagnosis, men were asked to report their treatment preferences by indicating whether they were considering each treatment option.  Knowledge about the treatment options was also assessed.

Result:  Across both DAs, more White men were interested in active surveillance (41%) than non-White men (23%).  However this effect was moderated by the type of DA, B=1.40, SE=.37, p=.02:  Relative to the high literacy DA, the low literacy DA increased interest in active surveillance for Whites but not non-Whites. The low literacy DA also decreased interest in external beam radiation for Whites but not non-Whites, B=-1.29, SE=.55, p=.02. These interactions were still significant when controlling for numeracy, literacy, and knowledge.  There were no effects involving race for interest in any other treatment option (i.e., surgery, brachytherapy).

Conclusion:  Results showed that White men’s preferences were influenced by the low literacy DA, but the preferences of non-White men stayed the same regardless of the DA type.  Moreover, the effect of the different DAs did not change when controlling for numeracy, literacy, or knowledge.  These results suggest that Whites may be more likely to change their treatment preferences in response to a lower-literacy DA, but the treatment preferences of racial minorities are rooted in other factors that were not identified from the current analysis. 

Purpose: Recently, expert panels have advised many Americans to reduce the frequency of screening tests for various cancers (e.g. prostate, breast).  However, these recommendations are often met with considerable resistance from the general public.  One possible way to explain this resistance is that when people feel positively toward a given behavior, they assume that the benefits of that behavior are high and the risks are low—a phenomenon known as the affect heuristic. The purpose of the present research was to determine whether the affect heuristic results in systematic biases in interpretations of screening test information. 

Method: 311 participants were recruited online and read information about the risks and benefits of a screening test (e.g. this test may detect disease before it becomes dangerous, this test may lead to unnecessary further testing and treatments that are expensive and painful).  This risk and benefit information was identical for all participants, but the screening test label was experimentally varied; participants were told that the test was for an unspecified disease, an unspecified cancer, or colon cancer.  Outcome measures included perceptions of risks and benefits of the test, and decisions to get screened or not. 

Result: Participants who believed that the test was for colon cancer were significantly more likely to decided to get the test (57%) than participants who believed the test was for an unspecified disease (38%) or unspecified cancer (41%), χ²(1)=4.67, p=.03  They also perceived the benefits as higher (M=6.38) than participants in the unspecified disease and cancer conditions (Ms=5.01 and 5.36; F(2,293)=10.39, p<.001), and the risks as lower (Ms=5.14 vs. 6.11 and 6.10; F(2,293)=6.94, p=.001). When controlling for perceptions of risks and benefits, there was no longer a relationship between test label and screening decisions (p=.61). 

Conclusion: Participants were more likely to get screened for colon cancer than an unspecified cancer or disease, even though the test information was identical for all participants.  As predicted by the affect heuristic, participants considering a colon cancer test underweighted the risks and overweighed the benefits of the test, compared to participants who judged the same information with different labels. These results demonstrate that interpretations of screening test information may be systematically biased, and can help to explain the difficulty of communicating screening test recommendations to the public.

Purpose: Guidelines recommend that decision aids provide natural frequency data regarding baseline risk, risk reduction, and chances of false positives and negatives.  Such quantitative information may confuse patients, especially those with low numeracy.  We conducted a randomized trial to compare effects of two colorectal cancer (CRC) screening decision aids – one with and one without natural frequency data. 

Method: 108 patients, aged 50-75 years, who were at average risk for CRC and due for screening were recruited from primary care clinics.  All subjects viewed a CRC screening decision aid (without numbers) and half (n=56) were randomized to view natural frequency data for two common screening tests. Participants completed questionnaires before and after viewing the decision aid that assessed subjective CRC risk, intent to be screened, and decisional conflict. At six months, screening behavior was assessed. 

Result: Members of both groups showed significant increases in subjective CRC risk, intent to be screened, intent to undergo fecal immunochemical testing (FIT), intent to undergo colonoscopy, and reduction in overall decisional conflict score (all p < 0.01). However, no significant between-group differences in change scores were observed.

Numeracy was a significant moderator. Among participants with numeracy scores above the median, those who viewed the natural frequency data had a significantly smaller increase in subjective CRC risk than those who did not view natural frequency data (-0.09 vs. 0.81, respectively, p = .009), and significantly greater intent to undergo FIT (1.00 vs. 0.1, respectively, p = .01). However, for those with numeracy scores below the median, no significant between-group differences were seen. 

At 6 months, a higher proportion of patients who viewed the natural frequency data had completed CRC screening compared to those who did not; however, this difference was not significant (39.3% vs. 26.9%, p = 0.173).  Among patients with numeracy scores above the median, a higher uptake of FIT was observed among those who viewed the natural frequency data that approached significance (12.1% vs. 0%, p = 0.148); there were no significant between-group differences for those with below median numeracy.

Conclusion: Adding natural frequency data to a decision aid had a significant effect but only for patients with higher numeracy scores. More research is needed before making recommendations to present such data to all patients.

Purpose: Although studies suggest most women have little regret with their breast cancer treatment decisions, few (or no) studies have evaluated whether decision regret changes over time, particularly as women experience disease complications or recurrence.

Method: Women diagnosed with breast cancer between August 2005 and May 2007 reported to the Detroit, Michigan or Los Angeles County SEER registry completed surveys at two time points: nine months following diagnosis (time 1) and again approximately four years later (time 2). A decision regret scale (adapted from Brehaut, 2003) consisting of 5 items was completed at both time points. Item responses were summed to create a regret score at both nine months and four years (scales of 5 to 25 points; higher values indicate higher regret). We used multivariable linear regression to examine change in regret from nine months to four years. Primary independent variables included surgery type (breast conserving surgery, unilateral mastectomy, bilateral mastectomy), invasive versus non-invasive disease, and recurrence status (yes/no) at follow-up. We included an interaction between surgery type and recurrence status at time 2. The model controlled for patient demographic and clinical factors.

Result: The analytic sample included 1,497 women who responded to both surveys. Mean decision regret at nine months was 9.5 points; mean regret at four years was 10.1 points (range 5-25) (NS). Two-thirds (64%) of respondents had breast conserving surgery, 26% had unilateral mastectomy, and 9% had bilateral mastectomy. We found no impact of surgery type on change in decision regret in the overall sample. However, among the, 86 (6%) women who experienced a recurrence, those who underwent unilateral mastectomy reported significant reduction in decision regret over time relative to recurrent women who underwent breast conserving surgery (d= -6.76, p=0.024). Average change in regret among non-recurrent women was 0.52 points and was 2.7 points for women who recurred. 

Conclusion: Decision regret in breast cancer is generally stable over time, yet changes in regret appear to be associated with disease trajectory and treatment received. Our results suggest that more extensive treatment is associated with a reduction in decision regret only when women experience a recurrence. Understanding patients’ assessment of their own decisions related to treatment may be useful for informing future decision making processes.

Purpose: Message framing can affect patient comprehension of information and treatment decisions.  We investigated the relationship between the framing of survival gains and the perceived value placed on cancer care, and examined whether the perceived value differ by prior cancer diagnosis.

Method: We conducted an internet-based, population survey of 2,050 U.S. adults (50% with cancer history).  Respondents were randomized to one of two sets of hypothetical scenarios, each of which described the survival benefit for a new treatment as either an increase in median survival time (median survival), or an increase in the probability of survival for a given length of time (landmark survival), over standard therapy.  Each respondent was presented with two randomly selected scenarios with different baseline and survival improvements, and asked about their willingness-to-pay (WTP) for the new treatments.  We used a double-bounded, dichotomous-choice bidding game to elicit WTP and performed a two-part model to examine factors influencing WTP.

Result: Predicted WTP increased with survival benefits and respondents’ income, regardless of how survival benefits were described.  Framing therapeutic benefits in terms of improvements in landmark rather than median time survival increased the proportion of the population willing to pay for that gain by 11%-35%, and the mean WTP amount by 42%-72%.  Respondents with a prior diagnosis of cancer were more likely to pay some amount for therapy that conferred survival benefit (OR=1.44, p<0.01), but their mean WTP did not differ from respondents with no history of cancer.  88% of cancer survivors stated that treatment success was a very important or important factor in deciding whether and how much to pay, compared to 84% among non-cancer respondents (p<0.01).  Approximately 80% indicated that affordability of treatment was a very important or important consideration, regardless of cancer history.

Conclusion: How survival benefits are described may influence the value people place on cancer care.  People may be willing to pay more for therapy if benefits are described as an increase in landmark survival probability than they would if the benefit is described as an increase in median survival time.  Although individuals with a prior cancer diagnosis may be more inclined to pay out-of-pocket for cancer treatment that confers additional survival advantage, the amount an individual would pay appeared to be independent of personal cancer history.

Purpose: Little is known about how young women make treatment decisions; a better understanding of these factors can potentially inform and improve the decision-making process. We sought to evaluate socio-demographic, clinical, and psychological factors in relation to surgical decisional involvement in very young women with breast cancer.

Method: As part of an ongoing multi-center cohort study enrolling women diagnosed with breast cancer at age ≤ 40, we evaluated 470 women with Stage 0-III disease. Women self-reported whether their final decision about surgical treatment was mainly their own, shared with their doctor, or mainly their doctor’s. Multinomial logistic regression models were fit to assess factors associated with: 1) patient-driven vs. shared decisions; 2) physician-driven vs. shared decisions. Independent variables with a p-value ≤ 0.15 in bi-variate analyses were included in the final multivariable model.

Result: Median age at diagnosis was 37 (range: 17-40). Most women had stage I or II disease (82%), and estrogen receptor (ER) positive tumors (70%).  42% of women reported the decision about surgery was their own, 49% reported the decision was shared, and 9% reported the decision was mainly their physician’s. Most women (452/470) were satisfied with their involvement in the decision, with only 3% indicating they would have preferred more involvement. In the multivariable analysis (Table 1), depressed women were less likely, while women who had bilateral mastectomies more likely, to report patient-driven decisions. Minority women were more likely, and women with bilateral mastectomies less likely, to report a physician-driven decision. Age at diagnosis, tumor size, nodal status, marital status, parity, radiation treatment, having a cancer-predisposing mutation, family history, and anxiety were not significantly associated with decisional involvement.

Conclusion: Our findings suggest that certain patient and clinical characteristics are associated with surgical decisional involvement in young women with breast cancer. These factors should be considered in an effort to promote quality decision-making while enhancing communication about these decisions between physicians and patients. 

Table 1. Multivariable analysis of factors associated with decisional involvement

	Patient vs. Shared	Physician vs. Shared
	OR (95% CI)	OR (95% CI)
Depression	0.40 (0.17-0.95)	2.18 (0.81-5.89)
Tumor size	1.27 (0.81-1.94)	1.49 (0.72-3.08)
Non-White non-Hispanic	1.43 (0.74-2.78)	2.73 (1.14-6.50)
Radiation	0.76 (0.46-1.25)	1.72 (0.69-4.28)
Surgery (ref=lumpectomy)
Bilateral mastectomy	2.22 (1.26-3.93)	0.23 (0.06-0.89)
Unilateral mastectomy	0.80 (0.43-1.48)	1.88 (0.80-4.38)