Career Decision Making Profile - The Hebrew University of Jerusalem

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From Career Decision-Making Styles
to Career Decision-Making Profiles:
A Multidimensional Approach
Itamar Gati, Shiri Landman, Shlomit Davidovitch,
Lisa Asulin-Peretz, and Reuma Gadassi
The Hebrew University of Jerusalem
The four facets for assessing
career clients’ needs

Locating the focuses of the client’s career decisionmaking difficulties

Appraising the degree to which the client’s
preferences are crystallized

Assessing the client’s decision-making status

Assessing the client’s career decision-making
profile (style):
interventions aimed at facilitating career decision making
should be tailored to the client’s career decision-making profile
2
Previous approaches

Previous approaches have often focused on
classifying individuals into one of few types based
on their most dominant style (e.g., rational, intuitive,
dependent; Harren, 1979; + spontaneous and
avoidant, Scott & Bruce, 1995).

The problem:
labeling individuals by a single dominant
characteristics is an oversimplification
3
Our approach

We suggest to consider 12 dimensions
simultaneously, while referring to career decisionmaking profiles rather than career decisionmaking styles.

We use “profile” instead of “style” for two main
reasons:
 we
are dealing with a multidimensional construct
rather than with a single dominant trait;
and
 “style”
implies personality characteristics, whereas
“profile” refers to both personality and situational
influences on the decision-making behavior
4
Developing the
Multidimensional Model
Comparing the most common 16 prototypes
deduced from 40 types in previous research
From this list we derived 12 basic dimensions
Defining the high and low pole of each
dimension (e.g., for information processing:
“analytic" vs. "holistic”)
Refining the model on the basis of preliminary
empirical tests (5 samples, N=2764)
5
Assumptions underlying the multidimensional
model:




individuals differ in their approach to making
career decisions and thus in their characteristic
profile of career decision making
individuals’ career decision-making process can
be better described by a multidimensional profile
rather than by a single dominant characteristic
each dimension describes a continuum between
two extreme poles, along which the individual
can be characterized
the dimensions are not independent;
nevertheless, each has a unique contribution
6
Assumptions underlying the multidimensional
model (Cont.):

like personality-related measures (and unlike
career decision-making difficulties) the dimensions
cannot be combined to produce a single total score

depending on the dimension, some poles are more
adaptive for decision making than others

whereas some dimensions are mainly personalityrelated and more consistent across situations,
others are more situational and may depend on the
specific decision task or the stage of the decisionmaking process in which the individual is at
7
The 12 Dimensions












IG - Information gathering (much vs. little)
IP - Information processing (analytic vs. holistic)
LC- Locus of control (internal vs. external)
EI - Amount of effort invested in the process (much vs. little)
PR - Procrastination in entering the process (low vs. high)
SP - Speed of making the final decision (fast vs. slow)
CO - Consultation with others (frequent vs. rare)
DO - Dependence on others (low vs. high)
DP - Desire to please others (low vs. high)
AI - Aspiration for an "ideal occupation" (low vs. high)
WC - Willingness to compromise (high vs. low)
IN - Intuitive (much vs. little)
8
The 12 Dimensions

Information gathering (comprehensive vs. minimal) –
the degree to which individuals are meticulous and
thorough in collecting and organizing information.

Information processing (analytic vs. holistic) – the
degree to which the individual analyzes information into
its components, and processes the information
according to these components.

Locus of control (internal vs. external) – the degree to
which individuals believe they control their occupational
future and feel that their decisions affect their career
opportunities, or that these are mainly determined by
external forces such as fate or luck.

Effort invested in the process (much vs. little) – the
amount of time and mental effort individuals invests in
the decision-making process.
The 12 Dimensions

Procrastination (high vs. low) – the degree to which the
individual avoids or delays beginning or advancing
through the career decision-making process.

Speed of making the final decision (fast vs. slow) –
the length of time individuals need to make their final
decision once the information has been collected and
compiled.

Consulting with others (frequent vs. rare) – the extent
to which individuals consult with others during the
different stages of the decision process.

Dependence on others (high vs. low) – the degree to
which individuals accept full responsibility for making
their decision (even if they consult with others), as
opposed to expecting others to make the decision for
them.
The 12 Dimensions

Desire to please others (high vs. low) – the degree to
which the individual attempts to satisfy the expectations of
significant others (e.g., parents, partner, friends).

Aspiration for an ideal occupation (high vs. low) – the
extent to which individuals strive for an occupation that is
perfect for them.

Willingness to compromise – the extent to which
individuals are willing to be flexible about their preferred
alternative when they encounter difficulties in actualizing it.

Intuition –(much vs. little) - the degree to which individuals
rely on internal (gut) feelings when making a decision.
The Career-Decision-making Profile
Questionnaire (CDMP)

36 statements (3 items x 12 dimensions)

Response scale: 1- Strongly disagree to 7-Strongly agree

The CDMP is embedded in WWW.CDDQ.ORG
12
Results - CDMP

Reliabilities of the 12 Dimensions (Cronbach Alpha):



Reliabilities Test-Retest (N=212):



Test-retest (4 months) consistency: median= .70, Min .52, Max .83
Test-retest (2 weeks) reliability: median= .84, Min .75, Max .86
Among the Most Stable dimensions:



Sample 1 (N=208) – median= .79 , Min .70, Max .89
Sample 2 (N=431) – median= .81 , Min .74, Max .91
DO – Dependence on Others (r = .79)
DP – Desire to Please others (r = .78)
Least Stable dimensions:


WC - willingness to compromise (r = .52)
CO - consultation with others (r =.60)
13
Associations between CDMP and
GDMS (Scott & Bruce, 1995; N=427 )
GDMS Scales1
CDMP
CDMP
Scale2
Rational
Intuitive
Dependent
Avoidant
Spontan
IP
.62
-.05
.03
-.17
-.26
4.73
1.29
.75
IG
.40
-.12
-.08
-.32
-.47
4.73
1.41
.75
LC
.23
-.32
-.17
-.31
-.42
5.22
1.42
.77
EI
.53
-.03
.07
-.21
-.22
5.26
1.23
.81
SP
-.08
-.01
-.36
-.48
-.10
2.96
1.45
.81
PR
-.26
.06
.23
.81
.32
4.05
1.80
.88
CO
.02
-.07
.52
.05
-.20
5.47
1.33
.77
DO
-.19
.04
.48
.43
.31
2.54
1.47
.82
DP
-.18
.05
.38
.34
.29
2.90
1.42
.85
AI
.19
.10
.00
-.18
.07
5.20
1.38
.76
WC
.00
.02
.21
.23
.15
3.96
1.54
.88
IN
-.16
.70
.01
.21
.36
4.03
1.34
.83
Mean
3.83
3.17
3.73
2.99
2.28
SD
Cα
0.70
.78
0.77
.83
0.85
.82
1.09
.89
0.85
.81
Mean
SD
Cα
14
Associations between CDMP and
VDSI (Walsh,1986; N=427 )
VDSI Scales1
2
CDMP Scale
TF
IE
Mean
SD
Cα
IP
.55
.07
4.66
1.31
.78
IG
.65
.07
4.74
1.46
.81
LC
.28
.11
5.20
1.31
.74
EI
.42
-.12
5.20
1.28
.82
SP
.11
.31
3.00
1.51
.84
PR
-.45
-.14
4.04
1.73
.86
CO
.12
-.59
5.38
1.25
.74
DO
-.29
-.37
2.63
1.53
.83
DP
-.21
-.36
2.82
1.44
.85
AI
.12
.00
5.06
1.30
.70
WC
-.18
-.07
3.92
1.50
.87
IN
-.43
-.03
4.25
1.34
.82
1.17
-0.65
1.21
.83
1.19
.81
Mean
SD
Cα
15
Means of the 12 CDMP Scales by three
Levels of Decision Status (N = 427)
RCA - Decision Status
CDMP
Scale
ANOVA
Beginning
During
After
(n = 196)
(n = 199)
(n = 32)
F(2, 394)
p<
η2
IG
4.46
4.92
5.30
7.65
.05
.03
LC
5.09
5.22
5.74
3.48
.05
.02
SP
2.78
2.99
4.36
16.29
.001
.07
PR
4.48
3.89
2.28
26.50
.001
.11
DO
2.97
2.44
1.78
11.90
.001
.05
DP
2.92
2.77
2.50
1.37
ns
.01
AI
5.02
5.07
5.21
0.31
ns
.00
WC
4.16
3.82
3.11
7.76
.001
.04
IN
4.43
4.10
4.08
3.34
.05
.02
16
Incremental Validity of the
CDMP

The five GDMS styles accounts for 45.1% of the variance
in the decision-status-group membership.

The GDMS styles combined with the CDMP dimensions
accounts for 52.1% of group membership variance.

But, the CDMP dimensions alone accounts for 50.4% of
the variance.

Conclusion: The CDMP better predicts decision-statusgroup membership than the GDMS
17
Conclusions & Implications

The proposed and tested model can be used to
characterize individuals' career decision-making

There are dimensions in which one of the poles
appears more adaptive

The CDMP allows a more accurate assessment
of the counselee's career decision-making profile,
thus better “tailoring” the intervention to the
individual

The CDMP allows individuals to learn about their
career decision-making profile, and thus to
consider adopting more adaptive strategies
18
Future challenges

Further testing and validating the dimensions in
terms of which poles are the more adaptive

Expanding research related to the relations
between career decision-making profile and
other career-related factors (e.g., dysfunctional
thoughts, preference crystallization, career
decision-making difficulties)

Attempting to locate groups of individuals with
similar career decision-making profiles

Designing interventions to help clients adopt
career decision-making profiles that are more
adaptive
19
For further information:
www.cddq.org
[email protected]
20
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