Results

The basic descriptive indicators for global trait El and its four factors assessed by the TEIQue-SF questionnaire, for three main clusters and global level of

Table 9.1 Descriptive indicators of all variables in a sample of Slovak adolescents (N=313)

Min

Max

AM

SD

Skewness

Kurtosis

a

TEIQue-SF

Well-being

1.00

7.00

5.31

1.10

-.849

.388

.872

Self-control

1.33

7.00

4.40

.99

-.374

-.019

Emotionality

2.13

7.00

4.92

.95

-.275

-.429

Sociability

1.83

7.00

4.74

1.01

-.355

-.364

Global Trait El

2.47

6.63

4.83

.72

-.473

.345

EPC’D

Pessimistic views

1.50

7.33

4.89

1.01

-.253

.117

.944

Anxiety

1.19

9.00

5.32

1.87

-.338

-.673

Self-concept and Identity

1.00

7.94

4.19

1.34

.119

-.357

Global Career Difficulties

1.79

7.89

4.89

1.22

-.280

-.379

GSES

Generalized

Self-efficacy

1.50

4.00

2.95

.46

-.254

.069

.817

C’DSE

Career Decisionmaking Self-efficacy

1.84

4.88

3.47

.59

-.075

-.308

.907

Source: Authors' own compilation.

career difficulties assessed by EPCD, and the level of generalized self-efficacy by GSES and of career decision self-efficacy by CDSE of our research sample, are presented in Table 9.1.

Descriptive indicators in Table 9.1 enabled a comparison of the global trait El level in our research sample to the Slovak percentile norms for the late adolescence created by norm sample of N = 387; AMagc = 16.6; SD= 0.5 (Kaliska et ah, 2015, p. 49). It can be concluded that the global trait El level (AM=4.8) of this research sample reached the 57th percentile. We can also conclude that all of the observed inner consistencies of the instruments estimated by Cronbach’s alpha coefficients reach acceptable values.

Statistical analysis of skewness and kurtosis were in the normal distribution for the analyzed variables, therefore the relations were estimated by parametric statistical analyses. The variable relation estimate was carried out using parametric Pearson correlation analysis (r) enabling determination of the direction and strength of relations between variables (Table 9.2) followed by a three-step regression analysis in Table 9.3 where the global trait El level was entered as the last one. Table 9.4 presents the results of the three-step regression analysis where the individual factors of trait El level were entered as the last ones.

The global level of trait El and its four factors were negatively correlated to all the scales and the global level of career difficulties (supporting HI). The strongest negative and significant correlations were between the global level of career decision-making difficulties and the self-control, sociability, and well-being factor from trait El.

Table 9.2 Correlation analysis of the variables (N=313)

2

3

4

5

6

7

8

9

10

11

TElQue-SF

1 Well-being

.441

***

.326

***

.368

***

.758

***

  • -.199
  • ***
  • -.238
  • ***
  • -.488
  • ***

-.352

.504

.453

2 Self-control

1.00

.234

***

.281

***

.649

***

  • -.272
  • ***
  • -.389
  • ***
  • -.538
  • ***

-.473

.464

.396

3 Emotionality

1.00

.321

***

.689

***

  • -.185
  • **

-.056

  • -.253
  • ***
  • -.159
  • **

.163

**

.232

***

4 Sociability

1.00

.682

***

  • -.226
  • ***
  • -.308
  • ***
  • -.435
  • ***

-.380

.593

***

.434

5 Global Trait El

1.00

  • -.307
  • ***
  • -.343
  • ***

-.608

-.476

.618

.552

EPCD

6 Pessimistic views

1.00

.547

***

.472

***

.682

***

-.191 • *

  • -.343
  • ***

7 Anxiety

1.00

.683

***

.946

***

  • -.358
  • ***

-.536 ♦ **

8 Self-concept and Identity

1.00

.853'"

  • -.481
  • ***
  • -.598
  • ***

9 Global Career Difficulties

1.00

-.417

-.592

GSES

10 Generalized Self-efficacy

1.00

.592

♦ **

CDSE

11 Career Decision-making Self-efficacy

1.00

Notes: * = p < .05, ** = p < .01, *** = p < .001. Source: Authors' own compilation.

Table 9.3 Regression analysis for career difficulties by global trait El level

Career Difficulties

Step 1

F( 1,305)= 171.360"'. R2 adj. =.358

Step 2

FcKa„ge(2.304)=2.421. R2 adj. =.361, Rha„Se=0°5

Step 3

Fcha„go(3!303)= 12.564*", R2 adj. =.384. R~ change =-025

Beta

t

Partial correlations

Career Decision-making Self-efficacy (Step 1)

-.600

-13.090"*

-.600

Career Decision-making Self-efficacy

-.547

-9.648***

-.484

Generalized Self-efficacy (Step 2)

-.088

-1.556

-.089

Career Decision-making Self-efficacy

-.486

-8.322***

-.431

Generalized Self-efficacy

.005

.084

.005

Trait El (Step 3)

-.211

-3.545***

-.200

Notes: * = p < .05, ** = p < .01, *** = p < .001. Source: Authors' own compilation.

The career decision self-efficacy entered into positive significant and medium to strong correlations with trait EI and its four factors, and generalized self-efficacy. Then career decision self-efficacy and generalized self-efficacy were strongly positively related to each other (supporting H3), and both constructs were strongly negatively related to career decision-making difficulties (supporting H2).

The hierarchical three-step regression analysis was conducted to determine if the global level of the career difficulties as dependent variable could be predicted by the career decision-making self-efficacy level (Step 1), the generalized self-efficacy level (Step 2), and the global trait El level (Step 3) to support also the incremental validity of trait El. The results are presented in Table 9.3.

A three-step hierarchical regression was performed to investigate the prediction potential of the trait El of career decision-making difficulties level and at the same time to prove the incremental influence of trait El over and above the career decision self-efficacy and generalized self-efficacy. The career decision self-efficacy was entered at Step 1, then the career decision self- efficacy and generalized self-efficacy at Step 2, and at Step 3 both constructs were added followed by the global level of trait El.

In summary, two models (at Steps 1 and 3) were statistically significant. The career decision-making self-efficacy level predicted almost 36 percent of the variance in career difficulties level. Then at Step 3, trait El, was entered

192 Eva Sollarova and Lada Kaliska

Table 9.4 Regression analysis for career difficulties by significant trait El factors

Career Difficulties

Step 1 Step 2

F( 1,311)= 170.589'", R2 adj. =.352 Fchange(3,308)= 13.030***, R2 adj. =.420, F2 change —-073

Beta

t

Partial correlations

Career Decision-making Self-efficacy (Step 1)

-.595

-13.061***

-.595

Career Decision-making Self-efficacy

-.450

-8.606***

-.440

Self-control

-.264

-5.347***

-.291

Sociability

-.109

-2.214***

-.125

Well-being (Step 2)

.016

.302

.017

Notes: * = p < .05, ** = p < .01, *** = p < .001. Source: Authors’ own compilation.

on its own above the career decision self-efficacy and generalized self-efficacy. Only the model with trait El was found to be a significant negative predictor of career decision-making difficulties, over and above the career decision self- efficacy level (H4). The generalized self-efficacy lost its influence. Trait El predicted a significant almost 3 percent of unique variance in career decisionmaking difficulties after controlling for the career decision self-efficacy level supporting incremental validity of trait El with remaining partial correlation of r=-.200.

Next we explored which factors of trait El level would stay as a significant predictor of career decision-making difficulties. There was a hierarchical two-step regression analysis conducted (general self-efficacy was dropped) to determine if the global level of career difficulties as the dependent variable could be predicted by the career decision-making self-efficacy level and three factors (self-control, sociability, well-being) of the trait El. The results are presented in Table 9.4.

Only a two-step hierarchical regression was performed to investigate the prediction potential of the trait El factors of the career decision-making difficulties level over and above the career decision self-efficacy. The career decision self-efficacy entered at Step 1, and then at Step 2 were three significant factors (self-control, sociability, well-being). It can be concluded that both models stay statistically significant (p < .001).

Out of three trait El factors, only two - self-control and sociability - remained significant (RQ2) predicting significantly more than 7 percent of unique variance in career decision-making difficulties. However, only the self- control factor remains in the significant level of negative relation (r=.291) to career difficulties while controlling for other variables in the model.

 
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