Table 4. Hierarchical linear regression analysis (unstandardized regression coefficients) for variables predicting PHQ-9 total sum scores.

Predictor	b	p	b	sr2	sr2	Fit	Difference
			95% CI		95% CI
			[LL, UL]		[LL, UL]
Model 1						R2 = .054**
						95% CI [.03,.09]
(Intercept)	7.36	< .001	[6.78, 7.95]
Female vs. Male	-1.96	< .001	[-2.70, -1.21]	.03	[.01, .06]
Coastal vs. Other regions	-1.43	< .001	[-2.19, -0.67]	.02	[-.00, .04]
Model 2						R2 = .166**	ΔR2 = .111**
						95% CI	95% CI
						[.11,.21]	[.07, .15]
(Intercept)	8.16	< .001	[7.27, 9.04]
Female vs. Male	-1.24	< .001	[-1.96, -0.52]	.01	[-.00, .03]
Coastal vs. Other regions	-1.10	< .001	[-1.82, -0.37]	.01	[-.00, .02]
Not regular vs. Regular schedule	-2.34	< .001	[-3.09, -1.59]	.04	[.02, .07]
Not exercising vs. exercising	-1.76	< .001	[-2.53, -1.00]	.02	[.00, .04]
One hour or less vs. More than an hour	1.35	< .001	[0.55, 2.15]	.01	[-.00, .03]
One hour or less vs. Avoid the topic	1.87	< .001	[0.91, 2.82]	.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.