Journal of General Internal Medicine

, Volume 19, Issue 4, pp 310–315 | Cite as

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

  • Susan L. Davids
  • Marilyn M. Schapira
  • Timothy L. McAuliffe
  • Ann B. Nattinger
Original Articles


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.

Key words

breast neoplasm risk perception pessimism numeracy 


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Copyright information

© Society of General Internal Medicine 2004

Authors and Affiliations

  • Susan L. Davids
    • 1
  • Marilyn M. Schapira
    • 1
  • Timothy L. McAuliffe
    • 2
  • Ann B. Nattinger
    • 1
  1. 1.Division of General Internal MedicineMedical College of WisconsinMilwaukee
  2. 2.the Division of BiostatisticsMedical College of WisconsinMilwaukee

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