Table 3. Hierarchical linear regression analysis (unstandardized regression coefficients) for variables predicting GAD-7 total sum scores.

Predictor	b	p	B	sr2	sr2	Fit	Difference
			95% CI [LL, UL]		95% CI [LL, UL]
Model 1						R2 = .039** 95% CI [.02,.07]
(Intercept)	7.41	< .001	[6.84, 7.98]
Female vs. Male	-1.80	< .001	[-2.52, -1.07]	.03	[.01, .05]
Coastal vs. Other regions	-0.87	0.017	[-1.61, -0.13]	.01	[-.00, .02]
Model 2						R2 = .118**	ΔR2 = .078**
						95% CI [.07,.16]	95% CI [.04, .11]
(Intercept)	7.60	< .001	[6.72, 8.48]
Female vs. Male	-1.29	< .001	[-2.01, -0.58]	.01	[-.00, .03]
Coastal vs. Other regions	-0.68	.054	[-1.40, 0.04]	.00	[-.00, .01]
Not regular vs. Regular schedule	-1.89	< .001	[-2.64, -1.15]	.03	[.01, .05]
Not exercising vs. exercising	-0.84	.033	[-1.59, -0.08]	.01	[-.00, .02]
One hour or less vs. More than an hour	1.75	< .001	[0.95, 2.54]	.02	[.00, .04]
One hour or less vs. Avoid the topic	1.79	< .001	[0.84, 2.74]	.02	[-.00, .03]

Note. A significant b-weight indicates the semi-partial correlation is also significant. b represents unstandardized regression weights. sr² represents the semi-partial correlation squared. LL and UL indicate the lower and upper limits of a confidence interval, respectively.

** indicates p < .01.