Candidate for the Lee B. Lusted Student Prize Competition
Purpose:
To evaluate the ability of a 6-item measure of physician numeracy (the ability to use numbers and numeric concepts in the context of taking care of patients) to predict enthusiasm for cancer screening.Methods: We developed the content and design of the questionnaire through an iterative 8 month process supporting content validity. Our final measure consisted of 6 items which appeared to best predict accurate perceptions of the benefit of screening mammography on pilot testing: 2 items from the Medical Data Interpretation Test (MDIT) and 4 new items. To measure enthusiasm for cancer screening we modified items from a previous survey “Enthusiasm for Cancer Screening in the United States," (JAMA 2004). We distributed a paper survey to 139 internists and medicine sub-specialists attending an annual meeting. Numeracy scores were created on a scale from 0-6 based on the number of questions correct. Answers to the enthusiasm for cancer screening items were aggregated, higher scores indicating more enthusiasm for cancer screening. We calculated the Pearson correlation coefficient between the physician numeracy score and scores on the enthusiasm for screening scale. We used multiple regression to adjust for demographics.
Results: 88 participants returned completed surveys representing a 63% response rate. No question had more than one non-response. Numeracy scores ranged from 2-6 and with 63% scoring 6 out of 6 correct. Numeracy scores had a significant negative correlation with enthusiasm for cancer screening scores (r=0.26, p=0.01). This relationship remained significant after correcting for gender and year graduated from medical school.
Conclusions: We found that physician numeracy affects attitudes toward cancer screening. Different attitudes toward cancer screening could result in different styles of risk communication and medical decision-making.
Question | Answered Correctly |
| Calculate 2 absolute risk reductions from relative risk reductions and baseline risks and select the larger. (MDIT) | 92% |
| Calculate absolute risk reduction from 2 absolute risks. (MDIT) | 91% |
| Know that survival rates are a biased estimate of the benefits of cancer screening tests. | 68% |
| Know that all-cause mortality benefits of treating a single disease will decrease with age. | 90% |
| Know that a statement about relative risk reduction is not equivalent to a statement of absolute risk reduction. | 68% |
| Know that pre-test probability affects the positive predictive value of a test. | 67% |