Table 5. Logistic Regression Predicting Communication Technology Access, Use, and Preferences

Characteristics	Access		Use			Preferences for …
Characteristics	Cell phone	Computer	Internet	Email	Text	Receiving Email	Receiving Internet	Sending Email	Sending Internet
BLOCK 1
Age	0.944^*	0.960^*	0.939^*	0.943^*	0.900^*	0.956^*	0.958^*	0.949^*	0.970^{^†}
Male sex^{^‡}	—	—	—	—	—	—	—	—	—
Ethnicity (overall effect)	—	^*	^*	^*	^{^§}	^{^†}	—	^{^§}	—
Hispanic	0.401^{^§}	0.308^*	0.297^*	0.258^*	—	0.392^*	—	0.434^{^†}	—
African American	0.326^{^§}	0.464^{^§}	0.409^{^§}	0.388^{^†}	—	—	—	—	—
Asian	—	—	—	—	0.174^{^†}	—	—	—	—
Spanish language	—	—	0.300^{^†}	0.224^*	0.212^*	—	—	—	—
Insurance (overall effect)	—	^*	^*	^*	^{^†}	^*	^{^†}	^*	^*
Medicare	—	—	0.386^{^†}	—	—	0.367^{^†}	0.382^{^§}	0.304^*	0.343^{^§}
Medicaid	—	0.221^*	0.153^*	0.170^*	0.271^*	0.138^*	0.271^*	0.091^*	0.198^*
County	0.294^{^§}	0.535^{^‡}	0.370^*	0.372^*	—	0.348***	0.391^{^†}	0.361^*	0.471^{^§}
Model χ² (df = 9)	57.24	84.15	136.77	125.38	207.59	99.91	49.20	117.79	35.46
Nagelkerke R²	0.202	0.224	0.339	0.315	0.480	0.266	0.180	0.305	0.136
Hosmer-Lemeshow goodness of fit (P)	.482	.900	.835	.232	.118	.935	.440	.596	.432

Values provided as odds ratios unless otherwise indicated.
↵* P < .001.
↵† P < .01.
↵‡ Sex is not significant and therefore the characteristic male sex does not contain any data.
↵§ P < .05.