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Marilyn M Schapira

Publications and source records attributed to Marilyn M Schapira.

7 recordsLinked to original sources
PubMed2006

The influence of graphic format on breast cancer risk communication.

Graphic displays can enhance quantitative risk communication. However, empiric data regarding the effect of graphic format on risk perception is lacking. We evaluate the effect of graphic format elements on perceptions of risk magnitude and perceived truth of data. Preferences for format also were assessed. Participants (254 female primary care patients) viewed a series of hypothetical risk communications regarding the lifetime risk of breast cancer. Identical numeric risk information was presented using different graphic formats. Risk was perceived to be of lower magnitude when communicated with a bar graph as compared with a pictorial display (p < 0.0001), or with consecutively versus randomly highlighted symbols in a pictorial display (p = 0.0001). Data were perceived to be more true when presented with random versus consecutive highlights in a pictorial display (p < 0.01). A pictorial display was preferred to a bar graph format for the presentation of breast cancer risk estimates alone (p = 0.001). When considering breast cancer risk in comparison to heart disease, stroke, and osteoporosis, however, bar graphs were preferred pictorial displays (p < 0.001). In conclusion, elements of graphic format used to convey quantitative risk information effects key domains of risk perception. One must be cognizant of these effects when designing risk communication strategies.

Adult↗
PubMed2006

Black-white differences in risk perceptions of breast cancer survival and screening mammography benefit.

BACKGROUND: Given differences in cancer survival by race, black women may differ from white women in breast cancer risk perceptions. OBJECTIVE: To evaluate black-white differences in risk perceptions of breast cancer survival and screening mammography benefit. DESIGN: A written survey was administered to a random sample of women attending general internal medicine clinics. PARTICIPANTS: Black and white women, ages 40 to 69. MEASUREMENTS: Risk perceptions were measured regarding (1) average 5-year survival after a breast cancer diagnosis and (2) relative risk reduction of screening mammography. Women's risk perceptions were defined as being accurate, as well as more or less pessimistic. Measured patient characteristics included race, age, family history of breast cancer, income, insurance, education, and numeracy. Unadjusted Pearson chi(2) tests and adjusted multivariable regression analyses were done. RESULTS: Black women were more likely than white women to accurately perceive breast cancer survival in both unadjusted (48% vs 26%, P<.001) and adjusted analyses (adjusted odds ratio (AOR)=3.58; 95% confidence interval (CI)=1.56 to 8.21). Black women were also more likely to accurately perceive the benefit of screening mammography in unadjusted (39% vs 15%, P<.001) and adjusted analyses (AOR=2.70; 95% CI=1.09 to 6.69). Black women were more likely to have a more pessimistic perception of mammography benefit in unadjusted (47% vs 15%, P<.0001) and adjusted analyses (AOR=3.94; 95% CI=1.62 to 9.56). CONCLUSIONS: Awareness of risk perceptions can help physicians to tailor patient education. Physician acknowledgment of more accurate risk perceptions among black women may serve as a basis to improve patient-physician communication.

Adult↗
PubMed2004

Menopausal hormone therapy decisions: insights from a multi-attribute model.

A multi-attribute utility (MAU) decision model for menopausal hormone replacement therapy (HRT) was developed using structured interviews (n=40) to identify decision factors, and a telephone survey (n=97) to ascertain utility scores. Utility scores for individual factors and composite scores reflecting the HRT decision were compared according to HRT use. Composite utility scores (range of -1.0 to 1.0, with higher values supporting HRT use) were 0.55, -0.27, and -0.19 for the 48 HRT users, 23 former users, and 26 never users, respectively (P<0.0001). Among HRT current users, the main factors supporting use were concerns about heart disease, osteoporosis, and symptoms of menopause. Among former users, side effects weighed heavily against use, and among never users breast cancer concerns weighed heavily against use. Linear regression methods were used to identify the utilities most predictive of current HRT use. The decision model provided insight regarding how personal expectations and values influence HRT use.

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PubMed2004

Agreement between scales in the measurement of breast cancer risk perceptions.

The objective of this article is to compare the accuracy and numeric responses of breast cancer risk perception as measured by a frequency scale and percentage scale. A cross-sectional survey was conducted. Perceptions of five-year and lifetime breast cancer risk were measured using a frequency and a percentage scale. Estimation error was calculated as the absolute difference between actual breast cancer risk as determined by the Gail model and perceived risk. Agreement between scales was determined by calculating the mean and standard deviation of the difference between numeric responses. The study was conducted among women enrolled in two primary care clinics associated with an academic medical center. Two-hundred-fifty-four participants were recruited from one of the two participating internal medicine clinics. Inclusion criteria included female gender and age 40-84 years. Exclusion criteria included a history of breast cancer, dementia, or a life expectancy of less than two years. The frequency scale was more accurate than the percentage scale in estimating lifetime risk (p= 0.05), but less accurate in estimating five-year risk (p < 0.02). Only 79 participants (31%) were considered consistent scale users, providing identical responses when using the frequency and percentage scale for a given risk estimate. Although the mean difference (percentage-frequency scale) for estimates of breast cancer lifetime risk was only 2.4, the empirically determined 90% limits of agreement between the frequency and percentage scale for lifetime risk were wide, from -30 to 40. Higher numeracy was associated with consistent use of scales (OR 1.61, 95% CI; 1.09-2.37). We report disagreement in breast cancer risk perceptions when measured by a frequency and a percentage scale. The accuracy and direction of bias associated with each scale varies according to the time frame of risk being assessed.

Adult↗
PubMed2004

Predictors of pessimistic breast cancer risk perceptions in a primary care population.

OBJECTIVE: To identify sociodemographic characteristics, numeracy level, and breast cancer risk factors that are independently associated with the accuracy of lifetime and 5-year breast cancer risk perceptions. DESIGN: Cross-sectional survey. A probability scale was used to measure lifetime and 5-year risk perceptions. The absolute difference between perceived risk and the Gail model risk of breast cancer was calculated. Linear regression models were built to predict lifetime and 5-year breast cancer risk estimation error. SETTING: Primary care internal medicine practices (N = 2). PARTICIPANTS: Two hundred fifty-four women 40 to 85 years of age. RESULTS: The mean lifetime and 5-year calculated breast cancer risk was 8.4% (SD [standard deviation] 6.1) and 1.5% (SD 1.3), respectively. Subjects had a mean estimation error for lifetime and 5-year risk of 29.5% (SD 22.9) and 24.8% (SD 23.9), respectively. In multivariate analyses, lower numeracy scores (0.005), higher number of previous breast biopsies (0.016), and a higher number of first-degree relatives (0.054) were predictive of larger estimation error for lifetime breast cancer risk. White race (0.014), lower educational levels (0.009), higher number of previous breast biopsies (0.008), and higher number of first-degree relatives (0.014) were predictive of larger estimation error for 5-year risk. CONCLUSION: Among a primary care population, breast cancer risk factors may be more consistently associated with pessimistic perceptions of breast cancer risk than other factors studied during a lifetime and 5-year time span. Primary care physicians should consider counseling patients about individual breast cancer risk factors and risk over time.

Adult↗
PubMed2002

Methodological issues in the use of administrative claims data to study surveillance after cancer treatment.

BACKGROUND: Administrative claims databases linked to tumor registry data provide an excellent opportunity for studying the follow-up care of cancer patients. RESEARCH DESIGN: Methodological principles of study design are reviewed, using examples drawn from the recently published literature. RESULTS: Most follow-up care is outpatient-based. Therefore, in studies using Medicare claims, the patient should be eligible for Medicare Part B and should not be enrolled in a Medicare HMO. In studies of surveillance testing, it may be appropriate to exclude subjects who are near death, in a hospice, or in whom a new or recurrent cancer develops. The definition of the period for measurements of surveillance testing requires consideration, as does periodicity in patterns of testing. Several analytic methods can be employed, from proportions undergoing testing to survival analysis methods. Measurement of 'surveillance tests' among control subjects (those without cancer) may be useful for comparison with cancer patients. To date, administrative claims data have been most useful in studies investigating the quality of, and disparities in, cancer care. CONCLUSION: With appropriate attention to methodological issues, linked tumor registry and administrative databases can provide important insights into the quality of survivorship care for cancer.

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