Table 2.

Analysis of logistic regression models

Dependent variable	Independent variable	P	OR (95%CI)	P	OR (95%CI)	P	OR (95%CI)
		Model 1		Model 2		Model 3
Turnover intention	Job stress
	NJSI (1)	< 0.001	3.686(3.070 ∼ 4.425)	< 0.001	3.575(2.967 ∼ 4.307)	< 0.001	3.387(2.793 ∼ 4.108)
	Background characteristics
	Age (1)	< 0.001	2.573(1.746 ∼ 3.792)	< 0.001	2.569(1.702 ∼ 3.877)	0.002	1.981(1.298 ∼ 3.024)
	Family factors
	Children			0.042		0.023
	Children (1)			0.692	0.937(0.678 ∼ 1.294)	0.894	1.023(0.737 ∼ 1.418)
	Children (2)			0.102	1.428(0.932 ∼ 2.188)	0.030	1.617(1.048 ∼ 2.493)
	Income group			0.012		0.007
	Incomegroup (1)			0.048	1.641(1.005 ∼ 2.679)	0.047	1.657(1.006 ∼ 2.729)
	Incomegroup (2)			0.008	1.953(1.191 ∼ 3.204)	0.006	2.027(1.223 ∼ 3.359)
	Major Choice			< 0.001		< 0.001
	Major Choice (1)			0.002	1.822(1.255 ∼ 2.645)	0.001	1.947(1.338 ∼ 2.835)
	Major Choice (2)			< 0.001	1.682(1.395 ∼ 2.027)	< 0.001	1.686(1.395 ∼ 2.037)
	Job Characteristics
	ShiftStat					0.003
	ShiftStat (1)					0.046	1.319(1.005 ∼ 1.732)
	ShiftStat (2)					0.001	1.568(1.208 ∼ 2.036)
	EmployType (1)					< 0.001	1.620(1.270 ∼ 2.067)
	PartTJob (1)					0.005	2.071(1.239 ∼ 3.461)
	-2 Log likelihood	3085.112		3036.803		2996.291
	Cox & Snell R Square	0.127		0.144		0.158
	Nagelkerke R Square	0.171		0.193		0.212
	Chi-square	340.946		389.255		429.768