Table 3.

Multiple linear regression analysis predicting participants’ knowledge score.

	Model 1a			Model 2b
Variable	B	SE	ß	B	SE	ß
Demographic data
Age (years)
25–39	0.005	0.092	0.001	0.007	0.092	0.002
40–59	−0.068	0.107	−0.019	−0.056	0.108	−0.016
60 and above	−0.247	0.182	−0.024	−0.214	0.185	−0.020
Male	−0.373	0.052	−0.111***	−0.374	0.052	−0.111***
Marital status
Married	0.069	0.073	0.021	0.069	0.073	0.021
Divorced	−0.279	0.162	−0.027	−0.274	0.162	−0.026
Widowed	0.062	0.222	0.004	0.067	0.222	0.005
Education level
Under secondary level	1.092	0.533	0.142*	1.075	0.533	0.140*
Secondary/Diploma	1.074	0.524	0.293*	1.062	0.524	0.290*
Bachelor	0.993	0.524	0.283	0.979	0.524	0.279
Higher education (Master/PhD)	0.209	0.078	0.037**	0.131	0.079	0.023
Employment status
Health-related career employee	−0.109	0.133	−0.015	−0.108	0.133	−0.014
Employee	−0.134	0.100	−0.040	−0.135	0.100	−0.040
Unemployed (retired or housewife)	−0.235	0.097	−0.066*	−0.233	0.097	−0.065*
Having chronic disease history
Constant	4.838	0.525		4.855	0.526
Adjusted R2			0.012			0.012
P-value			0.000			0.000

a: includes age, gender, marital status, educational level, and employment status.

b: includes age, gender, marital status, educational level, employment status, and having chronic disease history.

B: the average change in the dependent variable associated with a 1 unit change in the independent variable, statistically controlling for the other independent variables;

SE: it is the standard deviation of its sampling distribution or an estimate of that standard deviation; ß: a statistical measure that compares the strength of the effect of each individual independent variable to the dependent variable.