Table 2.
Pre | Post | Difference (95% CI), p-value | |
---|---|---|---|
Potential Harms of Screening | |||
Who do you think is more likely to be diagnosed with lung cancer? People who are screened for lung cancer.a People who are NOT screened for lung cancer |
36% | 62% | 26% (8%, 44%), p < 0.001 |
ALL lung cancers will eventually cause illness and death if they are not found and treated. True/Falsea/Don’t Know |
6% | 54% | 48% (31%, 65%), p < 0.001 |
When screening finds lung cancer, doctors can tell whether the cancer will ever cause harm. True/Falsea/Don’t Know |
16% | 62% | 46% (62%, 30%), p < 0.001 |
Even lung cancers that may not cause any health problems are likely to be treated. Truea/False/Don’t Know |
66% | 80% | 14% (4%, 32%), p = 0.09 |
Screening tests lead some people to get cancer treatments that they do not need. Truea/False/Don’t Know |
18% | 76% | 58% (40%, 76%), p < 0.001 |
Screening tests find harmless lung cancers about as often as they prevent death from lung cancer. Truea/False/Don’t Know |
24% | 52% | 28% (9%, 47%), p < 0.001 |
Which of these 2 statements best describes over-detection from screening? Screening finds a cancer that would never have caused troublea Screening finds an abnormality but extra tests show it is not cancer |
16% | 28% | 12% (3%, 27%), p = 0.08 |
An abnormal result from lung cancer screening always means the person has lung cancer. True/Falsea/Don’t Know |
66% | 88% | 22% (5%, 39%), p < 0.001 |
Chances of Benefitting from Screening | |||
For the next question, please think about 1000 current and former smokers who are getting screened every year for lung cancer. Out of 1000 people who get a chest CT scan, about how many will have their lives prolonged? 0 1-5a 6-10a 11-30a 31–100 101–200 201–400 401–700 701–1000 Don’t Know |
18% | 48% | 30% (12%, 48%), p < 0.001 |
Average Knowledge Score (0–9 points) | 2.6 | 5.5 | 2.8 (2.1,3.6), p < 0.001 |
aCorrect response(s)