Table 4.

Hierarchical regression analyses predicting four health belief model constructs

	Perceived susceptibility			Perceived benefits			Perceived barriers			Mammogram self-efficacy
	B	SE	R 2	B	SE	R 2	B	SE	R 2	B	SE	R 2
1. Demographics			.019			.003			.020			.062**
Age	.005	.004		.002	.004		−.008	.003**		.000	.003
Race/ethnicity	.075	.055		−.058	.004		.040	.037		−.188	.042***
Education	−.056	.051		.065	.041		−.034	.034		.066	.039†
2. Visual variables			.034			.029*			.136***			.101**
V-V LP	.017	.019		−.010	.015		.001	.013		−.022	.015
VisFunction	−.008	.004†		.006	.004		−.015	.003***		.009	.003**
3. Pamphlet	.017	.016	.038	−.026	.013	.032	.009	.011	.137	−.024	.013†	.106
4. Message variables			.043			.222***			.190**			.163**
PMQ	.063	.116		.149	.093		−.099	.077		.186	.088*
PercInform	−.083	.108		.222	.086*		−.050	.071		−.031	.082
PercAttract	−.070	.067		.000	.054		.047	.044		.014	.051
5. PVI	.106	.077	.051	.168	.062**	.250**	−.146	.051**	.216**	.122	.059*	.177*
Constant	2.988	.728***		1.439	.583*		4.281	.480***		2.953	.551***
N	253	252	253	253

Note. Coefficients (B) and standard errors (SE) are for the final model in which all variables are entered. The R² column represents the amount of variance explained by all of the blocks included up to that point. Subtracting R² from the previous block will yield R² change (i.e., the amount of variance explained by that block alone). PVI = perceived visual informativeness; PMQ = perceived message quality; PercInform = perceived informativeness; PercAttrat = perceived attractiveness; V-V LP = visual/verbal learning preference (lower scores indicate verbal preference, higher scores indicate visual preference); VisFunction = visual function measured by the VF-14 (Steinberg et al., 1994), where higher scores indicate more visual ability; Pamphlet = identification of which of six pairs of images women received.

^†p < .10.

^*p < .05.

^**p < .01.

^***p < .001.