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Table 2 Standardized parameters, standard errors, 95% CI and p-values among men (n = 717) and women (n = 741)

From: Does work-personal life interference predict turnover among male and female managers, and do depressive symptoms mediate the association? A longitudinal study based on a Swedish cohort

 

Men

Women

 

B(SE)

95% CI

p

B(SE)

95% CI

p

Regression weights – WPI

 WPI t

  WPI t-1

.654 (.030)

.595; .713

.000

.644 (.025)

.594; .694

.000

  Depression t-1

.110 (.032)

.047; .173

.001

.027 (.030)

−.032; .085

.374

  Higher age

−.066 (.016)

−.119; −.012

.001

.062 (.025)

−.110; −.013

.013

  Not married

.022 (.022)

−.021; .064

.320

−.008 (.021)

−.049; .032

.687

  Children living at home

−.001 (.026)

−.053; .051

.971

−.048 (.024)

−.096; .000

.050

  Public sector

.011 (.021)

−.030; .052

.601

−.037 (.021)

−.078; .004

.077

  Higher education

−.003 (.021)

−.045; .039

.901

.064 (.021)

.023; .104

.002

WPI t-1

  WPI t-2

.638 (.031)

.577; .699

.000

.609 (.032)

.546; .671

.000

  Depression t-2

.111 (.034)

.045; .178

.001

.070 (.032)

.007; .133

.029

  Higher age

−.043 (.029)

−.100; .014

.136

.003 (.026)

−.048; .055

.902

  Not married

.006 (.024)

−.040; .053

.787

−.053 (.024)

−.099; −.006

.026

  Children living at home

−.002 (.028)

−.057; .054

.957

−.031 (.027)

−.084; .022

.254

  Public sector

.018 (.023)

−.027; .062

.431

−.020 (.024)

−.067; .026

.396

  Higher education

.049 (.023)

.004; .095

.034

.057 (.023)

.012; .103

.014

Regression weights – Depression

 Depression t

  Depression t-1

.594 (.034)

.527; .661

.000

.426 (.044)

.340; .512

.000

  WPI t-1

.089 (.033)

.024; .153

.007

.199 (.035)

.130; .268

.000

  Turnover t-1

.001 (.024)

−.045; .047

.967

.017 (.027)

−.035; .070

.514

  Higher age

−.082 (.027)

−.135; −.029

.003

−.070 (.026)

−.121; −.018

.008

  Not married

.015 (.025)

−.034; .064

.543

.027 (.023)

−.019; .073

.248

  Children living at home

−.048 (.026)

−.099; .003

.067

−.002 (.027)

−.055; .051

.937

  Public sector

.032 (.025)

−.017; .082

.201

.027 (.024)

−.020; .073

.263

  Higher education

−.053 (.023)

−.099; −.008

.021

−.058 (.024)

−.106; −.011

.017

 Depression t-1

  Depression t-2

.596 (.042)

.515; .678

.000

.506 (.041)

.425; .586

.000

  WPI t-2

.105 (.035)

.036; .173

.003

.133 (.034)

.066; .200

.000

  Turnover t-2

.004 (.031)

−.056; .064

.899

−.019 (.020)

−.057; .020

.339

  Higher age

−.070 (.027)

−.123; −.017

.009

−.051 (.024)

−.098; −.005

.031

  Not married

.013 (.027)

−.040; .065

.639

−.008 (.024)

−.056; .040

.734

  Children living at home

−.035 (.024)

−.082; .012

.142

−.022 (.026)

−.073; .030

.416

  Public sector

−.011 (.008)

−.028; .005

.182

−.005 (.009)

−.021; .012

.588

  Higher education

−.025 (.019)

−.063; .012

.182

−.009 (.017)

−.044; .025

.588

Regression weights – Turnover

 Turnover t

  Turnover t-1

.092 (.068)

−.041; .226

.175

.001 (.030)

−.059; .060

.974

  Depression t-1

−.034 (.031)

−.094; .027

.275

.065 (.038)

−.010; .141

.087

  WPI t-2

. 135 (.038)

.060; .210

.000

.060 (.028)

.004; .116

.035

  Higher age

.079 (.028)

.025; .133

.004

.097 (.029)

.040; .154

.001

  Not married

−.007 (.027)

−.060; .046

.793

.000 (.027)

−.053; .052

.986

  Children living at home

.002 (.028)

−.053; .056

.952

.041 (.029)

−.017; .098

.165

  Public sector

−.006 (.010)

−.026; .

015

.587

−.013 (.012)

−.035; .010

.271

  Higher education

−.013 (.024)

−.059; .033

.587

−.026 (.024)

−.072; .020

.271

 Turnover t-1

  Turnover t-2

.094 (.051)

−.005; .194

.063

.066 (.044)

−.020; .153

.134

  Depression t-2

.058 (.033)

−.007; .123

.080

.109 (.036)

.038; .180

.003

  Higher age

.010 (.031)

−.050; .070

.742

.051 (.024)

.005; .098

.030

  Not married

−.020 (.027)

−.073; .034

.474

.012 (.031)

−.049; .073

.693

  Children living at home

−.017 (.044)

−.103; .069

.695

.016 (.034)

−.050; .082

.632

  Public sector

−.037 (.028)

−.092; .017

.180

−.006 (.032)

−.067; .056

.861

  Higher education

.002 (.033)

−.063; .067

.947

−.010 (.032)

−.073; .053

.754

Indirect effect

.000 (.000)

.000; .000

.617

.000 (.000)

.000; .000

.612