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Personality and Individual Differences 35 (2003) 537-557


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P =Standardized beta-coefficients derived from the final step, R2 =explanation rate, AR2 =change in explanation rate in each step. * P<0.05. ** P<0.01. *** P<0.001.

Table 4


Hierarchical regression analyses involving optimism in the prediction of employee well-being at Time 2

Predictors

Job satisfaction T2

Emotional exhaustion T2

Mental distress T2

Physical symptoms T2







Men b

Women b

Men b

Women b

Men b

Women b

Men b

Women b




Step 1

























1. Dependent variable at Time 1

0.65***

0.49***

0.64***

0.60***

0.33***

0.42***

0.62***

0.62***




AR2

0.41***

0.35***

0.44***

0.40***

0.28***

0.24***

0.43***

0.44***




Step 2—demographics




























2. Age

0.05

0.04

-0.07

0.11*

-0.03

0.00

0.07

-0.10




3. Education

0.01

-0.02

0.01

0.13*

0.04

0.07

-0.07

0.06




4. Leadership position

-0.11

0.00

-0.04

-0.11*

0.04

0.05

-0.07

0.03




AR2

0.01

0.00

0.01

0.03**

0.00

0.01

0.02

0.01




Step 3—work stressors at Time 1




























5. Time pressures at work

-0.01

-0.11

-0.03

0.11

0.16**

0.08

0.04

0.07




6. Lack of control

-0.01

-0.09

-0.04

0.08

0.03

-0.02

0.00

0.04




7. Job insecurity

0.02

-0.12

-0.09

0.15*

-0.02

0.16*

-0.01

-0.01

8. Poor organization climate

0.10

-0.13*

0.01

-0.03

0.03

-0.02

0.12*

0.06




DR2

0.01

0.05**

0.01

0.03*

0.02

0.02

0.01

0.01




Step 4—personality factor at Time 1




























9. Optimism

0.11

-0.04

-0.12*

0.09

-0.22**

-0.11

-0.01

-0.03




AR2

0.01

0.00

0.02*

0.01

0.04***

0.01

0.00

0.00




Step 5—two-way interactions




























10. Time pressures at workxoptimism

0.07

0.00

-0.01

0.03

-0.08

-0.14*

0.06

-0.06

11. Lack of control x optimism

0.04

-0.07

-0.04

-0.02

-0.01

0.02

0.08

0.02




12. Job insecurityx optimism

-0.04

-0.06

0.07

0.06

0.01

0.22**

0.07

0.05




13. Poor organization climatexoptimism

0.02

0.01

-0.09

0.02

-0.05

-0.15*

-0.06

-0.10




AR2

0.01

0.01

0.01

0.01

0.01

0.05**

0.02

0.01




R2

0.44***

0.41***

0.48***

0.47***

0.35***

0.33***

0.47***

0.47***




P =Standardized beta-coefficients derived from the final step, R2 =explanation rate, AR2 =change in explanation rate in each step.







* P<0.05.




























** P<0.01.




























*** P<0.001.




























548 A. Ma¨kikangas, U. Kinnunen/Personality and Individual Differences 35 (2003)537–557



Fig. 1. Significant two-way interactions in the prediction of male employees’ well-being. (a) Interaction of organiza­tional climate and self-esteem on emotional exhaustion. (b) Interaction of organizational climate and self-esteem on mental distress.

For men, only personality characteristics at Time 1 had significant main effects on emotional exhaustion and mental distress at Time 2, after controlling for the prior levels of these well-being indicators, demographics and psychosocial work stressors (see Tables 3 and 4). Among the male respondents, the higher the self-esteem and optimism at Time 1, the lower the levels of emotional exhaustion and mental distress at Time 2.

For women, as indicated in Tables 3 and 4, increased age, higher level of education and lea­dership position significantly explained emotional exhaustion. Among psychosocial work stres­sors, poor organizational climate at Time 1 exerted a negative main effect on job satisfaction at Time 2 in both regression models. Furthermore, job insecurity at Time 1 was related to women’s ratings of emotional exhaustion at Time 2 (see Table 4). Personality characteristics at Time 1 did not explain either occupational or general well-being among women employees at Time 2.



2.3. Moderator effects

Interaction terms at Step 5 (see Table 3) revealed a significant two-way interaction between self-esteem and organization climate on emotional exhaustion ((3 = —0.15, P <0.05) and mental dis­tress ((3 = —0.20, P <0.01) in the men’s sample. Graphical representations of the significant interactions that are presented in Figs. 1 and 2 were derived from simple slope analysis using the unstandardized regression coefficients (B values) of the regression lines for employees high (1 S.D. above the mean) and low (1 SD below the mean) on the moderator variable (see Aiken & West, 1991).


A. Ma¨kikangas, U. Kinnunen/Personality and Individual Differences 35 (2003)537–557 549

Fig. 2. Significant two-way interactions in the prediction of female employees’ well-being. (a) Interaction of time pressures at work and optimism on mental distress. (b) Interaction of job insecurity and optimism on mental distress. (c) Interaction of organizational climate and optimism on mental distress.

Inspection of Fig. 1(a) and (b) reveals some support for the plasticity-hypothesis among men. The regression lines indicate that as organization climate worsened, emotional exhaustion and mental distress increased for low levels of self-esteem. The relationship in levels of high self-esteem showed a reverse pattern: well-being increased as organizational climate is for a worsened. Simple slope analysis provided support for these interpretations and it revealed that the rela­tionship between organizational climate and emotional exhaustion was significant both among low self-esteem male employees [B=0.15, t (201)=1.81, P <0.05] and among high self-esteem

550 A. Ma¨kikangas, U. Kinnunen /Personality and Individual Differences 35 (2003)537–557

male employees [B= 0.16, t (201)= 2.05, P <0.05]. The relationship between organizational climate and mental distress was also significant both among low self-esteem male employees [B =0.22, t (199)=2.55, P <0.01] and among high self-esteem male employees [B= 0.17, t (199)= —1.99, P <0.05].

Fig. 2 illustrates the buffering effect of optimism. Optimism and psychosocial stressors pro­duced three significant interactions in predicting mental distress among female employees. Opti­mism buffered the effects of time pressures at work (P = —0.14, P < 0.05), job insecurity (P =0.22, P <0.01) and organization climate (P = 0.15, P <0.05) on mental distress for the women’s sample.

Fig. 2(a) indicates that when time pressures at work increased, mental distress increased among low optimism female employees. Simple slope analysis supported this trend and showed that the relationship between time pressures at work and mental distress was significant among low opti­mism female employees [B =0.22, t (197)=2.46, P < 0.01] but non-significant among high opti­mism female employees [B=— 0.07, t (197)= 0.73, NS]. The analysis indicated also that job insecurity had a positive main effect on levels of mental distress among high optimism [B=0.33, t (197)=3.08, P < 0.01] but not among low optimism females [B= —0.01, t (197)= —0.17, NS]. In addition, the relationship between organization climate and mental distress was significant among high optimists [B=— 0.16, t (197)= 1.84, P <0.05], but non-significant among low optimism female employees [B=0.12, t (197)=1.32, NS].

3. Discussion

The present study was designed to examine the roles of self-esteem and optimism on the rela­tionship between perceived psychosocial work stressors and well-being separately for men and women. Based on previous moderator studies of self-esteem (Fernandez et al., 1998; Ganster & Schaubroeck, 1991; Jex & Elacqua, 1999; Mossholder et al., 1981, 1982; Pierce et al., 1993; Wiener et al., 1992) and optimism (Fry, 1995; Lai, 1996; Sumi, 1997; Sumi et al., 1997) our hypothesis, that self-esteem and optimism would moderate the relationship between psychosocial stressors and well-being after controlling prior well-being, did receive some support.

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