Table 2.

Hierarchical Linear Regression Analysis Predicting eHealth Scores Among a Sample of Men (n = 865).

	Model 1 R2 = .167			Model 2 R2 = .190			Model 3 R2 = .293
Predictors	β	t	p	β	t	P	β	t	p
Education	.179	5.249	<.001	.177	5.516	<.001	.133	4.106	<.001
Age	−.177	−4.912	<.001	−.210	−5.637	<.001	−.109	−2.986	.003
Income	.255	6.987	<.001	.221	5.910	<.001	.151	4.237	<.001
Employed	−.036	−.959	.338	−.036	−.959	.338	−.039	−1.104	.270
Hispanic	−.095	−2.016	.044	−.105	−2.239	.025	−.103	−2.335	.020
Non-Hispanic Black	−.053	−1.231	.219	−.051	−1.192	.234	−.059	−1.490	.136
Non-Hispanic White	−.066	−1.260	.208	−.069	−1.317	.188	−.086	−1.757	.079
Comorbidities				.075	2.211	.027	.013	.411	.681
Current smoker				−.115	−3.510	<.001	−.094	−3.057	.002
Weekly minutes of PA				−.043	−1.362	.174	−.027	−.928	.354
Cups of fruit				−.005	−.137	.891	−.002	−.061	.952
Cups of vegetables				.051	1.411	.159	.029	.848	<.397
Tablet or smartphone health tracking							.126	3.879	<.001
Other device health tracking							.173	5.507	<.001
Digital information seeking							.227	7.439	<.001

Note. PA = physical activity.