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Table 2 Analysis of logistic regression models

From: A cross-sectional study on turnover intention of nurses in eastern China

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