Table 4.

Associations of Exposure to Conflicting Information about Mammography with Breast Cancer Screening-Related Backlash

	Breast cancer screening recommendations should be taken with a grain of salt				Scientists really don’t know how you should avoid breast cancer
Measure	Model 1	Model 2	Model 3	Model 4	Model 1	Model 2	Model 3	Model 4
Ecological exposure	−0.001*				−0.000
	(0.0004)				(0.001)
Top-of-head thought-listing
References “old” only			−0.193				−0.194^
			(0.117)				(0.101)
References new/change			0.264*				0.077
			(0.108)				(0.100)
Self-assessed exposure to conflict in media				0.157*** (0.041)				0.123** (0.038)
Inferred exposure
Mammography conflict		0.312*				0.033
		(0.157)				(0.138)
Age-related conflict		0.003				−0.015
		(0.089)				(0.084)
Frequency-related conflict		0.226*				0.268**
		(0.109)				(0.097)
Personal conflict		0.171^				0.140
		(0.103)				(0.089)
Observations	1,060	720	773	1,059	1,058	719	771	1,057
R-squared	0.034	0.080	0.067	0.051	0.027	0.084	0.070	0.042

Note. Robust standard errors in parentheses;

^***p<0.001

^**p < 0.01

^*p < 0.05

^{^}p < 0.1. For each outcome, we generated four models, one for each of the four types of exposure measurement, to avoid multicollinearity (1=ecological, 2=inferred, 3=top-of-head, 4=self-assessed). All models control for age category, gender, educational attainment, income, race, marital status, average health news consumption, and institutional confidence.