Evidence-Based Practice:
Applying Decision-Theory to
Facilitate Individual’s
Career Choices
Itamar Gati
The Hebrew University Jerusalem
Choosing a Career as a DecisionMaking Process: Unique Features
 Amount of Information:




Often large N of alternatives
Large N of considerations and factors
Within-occupation variance
Practically unlimited
 Quality of Information



2
Soft, subjective
Fuzzy
Inaccurate or biased
Unique Features of Career
Decisions (continued)
 Uncertainty




about the individual’s future preferences
about future career options
unpredictable changes and opportunities
the implementation of the choice
 Non-cognitive Factors



3
emotional and personality-related factors
necessity for compromise
actual or perceived social barriers and biases
CDM Difficulties of 15,000 surfers
on the Future Directions website
(Gati & Meyers, 2003)
 Are you experiencing difficulties in making
your career decision?
60%
40%
20%
0%
yes
4
somewhat
no
Implications and Conclusion
 Many factors contribute to the complexity and
difficulties involved in the career decisionmaking process
 Career counseling may be viewed as decision
counseling, which aims at facilitating the
clients' decision-making process, and promoting
better career decisions
 By adopting decision theory and adapting it to
the unique features of career decisions,
theoretical knowledge can be translated into
practical interventions to facilitate individuals’
career choices
5
How can Theoretical Knowledge and
Empirical Methods be used for
Developing Counseling Instruments?
6
Today’s Presentation
The three bases of career counseling:
 Locating the focuses of the client’s
decision-making difficulties (CDDQ)
 Guidance in the decision-making process
 The three-stage model (PIC)
 Identifying the client’s stage in the
process
 Characterizing the client’s decision-making
style (DS)
Career Decision-Making
Difficulties
 The first step in helping individuals is to locate
the focuses of the difficulties they face in
making career decisions
 Gati, Krausz, and Osipow (1996) proposed a
taxonomy for describing the difficulties (see
Figure 1), based on:



7
the stage in the decision-making process during
which the difficulties typically arise
the similarity between the sources of the
difficulties
the effects that the difficulties may have on
the process and the relevant type of
intervention
Figure 1: Locating Career Decision-making
Difficulties based on the taxonomy of Gati, Krausz,
& Osipow (1996)
During the Process
Prior to Engaging
in the Process
Lack of Readiness
due to
Lack of
Indecimotivation siveness
8
Lack of Information
about
Dysfunc- Cdm Self Occupations
tional process
beliefs
Ways of
obtaining
info.
Inconsistent
Information due to
Unreliable Internal
Info.
conflicts
External
conflicts
The Career Decision-making
Difficulties Questionnaire (CDDQ)
 The Career Decision-making Difficulties
Questionnaire (CDDQ) was developed to test
this taxonomy and serve as a means for
assessing individuals’ career decision-making
difficulties
 Cronbach Alpha internal consistency
estimates: .70-.90 for the 3 major categories,
.95 for the total CDDQ score
9
10
Empirical Structure of the
Difficulties (N= 10,000; 2004)
Lack of motivations
Indecisiveness
Dysfunctional beliefs
Lack of info about self
Lack of info about process
LoI about occupations
LoI about addition sources of
help
Unreliable Information
Internal conflicts
External conflicts
11
Computerized Assessment of
Career Decision-Making Difficulties
 The CDDQ was incorporated into a career-
related self-help-oriented free of charge
Internet site (www.cddq.org).
 Research has shown that the Internet and the
paper-and-pencil versions of the CDDQ are
equivalent (Gati & Saka, 2001; Kleiman & Gati,
2004).
 The CDDQ was found suitable for different
countries and cultures and has been translated
into 18 languages.
12
Interpreting the CDDQ results
 Measuring career decision-making difficulties is
not enough – interpretation is very important
 Interpretation is part of face-to-face counseling
and is crucial for Internet-based assessment of
career decision-making difficulties, where no
expert counselor is available
 The proposed interpretation procedure is aimed at
13
locating the individual’s salient difficulties and
recommending ways to deal with them (with added
reservations when needed)
The Four Stages of Interpretation
1.
Ascertaining Credibility, using validity items and the
2.
Estimating Differentiation
3.
Locating the Salient, moderate, or negligible
difficulties, based on the individual's absolute and relative
time required to fill out the questionnaire
based on the standard
deviation of the 10 difficulty-scale scores
scale scores
4.
14
Determining the need to add reservations to
the feedback provided (based on doubtful credibility, partial
differentiation, or low informativeness)
The 4 Stages of Interpretation
1
Doubtful
2
Credible
Estimating
Differentiation
Questionable
3
Aggregate
Reasons to Add
Reservation (RAR)
B/W < 1
RAR = 3
RAR ≤ 2
4
15
Add Reservation
to Feedback
Not Credible
Evaluating
Credibility
Low
High
Locate Salient
Difficulties
Compute
Informativeness
(B /W )
B/W > 1
Receives
Feedback
No
Feedback
Interpreting the CDDQ results
 The goal: empirically testing a four-stage
model for interpreting the CDDQ profiles of
individuals
 The interpretation is based on the withinclient relative salience of the difficulties as
well as their absolute salience, augmented by
quality-assurance measures
 Career counselors' expert judgments were
used to validate the proposed procedures of
analyses
16
5 Studies
 Study 1: Ascertaining the Credibility of
Responses to the CDDQ, based on validity
items
 Study 2: Estimating the Differentiation of
Responses, based on the SDs of the 10 scale
scores
 Study 3: Determining the Relative Salience of
Difficulties (salient, moderate, negligible)
 Study 4: Determining the Need to Add
Reservations to the Feedback
17
Studies 1-4
 Career counselors' expert judgments were used in
the four studies for validating the proposed
procedures
 Method
 Participants: career counselors and graduate
counseling students
 Questionnaires: in studies 1,4 - all possible cases;
 in studies 2,3 - responses of 16 actual clients
 Results:
 High similarity between experts’ and students’
judgments, as well as within-groups judgments
 High similarity between the experts’ judgments
and the proposed algorithm at each stage
18
Study 5 – Testing the Applicability of
the Proposed Model
Method: Analyzing the CDDQ data of four groups (N =
6,192)
 Hebrew paper-and-pencil version – 965 university
students
 Hebrew Internet version - 4030 individuals surfing
the Future Directions Internet site (www.kivunim.com)
 English paper-and-pencil version - 452 US College
students
 English Internet version - 745 individuals who filled
out the CDDQ on the Internet ( www.cddq.org )
19
Results: see Figures 3 & 4
Figure 3: The Distribution of the Three Levels of
Difficulties (negligible, moderate, salient difficulty)
in the Ten Difficulty Categories and in Four Groups
(N = 6192; H-Hebrew, E-English, p-paper and pencil, I-Internet)
salient difficulty
moderate difficulty
no difficulty
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
0%
p I p I p Ip I p I p I p Ip I p I p I p I p I p Ip I p I p I p Ip I p I p I
1
20
2
3
4
5
6
Difficulty category
7
8
9
10
Figure 4: Distribution of types of
feedback in the four groups
100%
90%
80%
feedback
add reservation
70%
60%
50%
no feedback
40%
30%
20%
10%
0%
P&P
21
Internet
Hebrew
P&P
Internet
English
Conclusions
 The incorporation of a middle level of
discrimination increases the usefulness of the
feedback and decreases the chances and
implications of potential errors
 Adding reservations when appropriate is
essential for providing meaningful feedback
and decreasing the chances of misleading
conclusions
22
General Feedback on the CDDQ
23
Detailed Feedback on the CDDQ
24
25
26
Among the salient difficulties is
“lack of information about
the career decision-making process” (4)
The Distribution of the Three Levels of Difficulties (negligible, moderate,
salient difficulty) in the Ten Difficulty Categories and the Four Groups
(N = 6192; H-Hebrew, E-English, p-paper and pencil, I-Internet)
salient difficulty
moderate difficulty
no difficulty
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
H
H
E
E
0%
p I p I p Ip I p I p I p Ip I p I p I p I p I p Ip I p I p I p Ip I p I p I
27
1
2
3
4
5
6
7
8
9
10
Guidance in the decision-making
process
The PIC model (Gati & Asher, 2001)
which separates the career decisionmaking process into 3 distinct stages:
- Prescreening
- In-depth exploration
28
- Choice
Prescreening
 Goal: Locating a small set (about 7) of promising
alternatives that deserve further, in-depth
exploration
 Method: Sequential Elimination




Locate and prioritize aspects or factors
Explicate within-aspect preferences
Eliminate incompatible alternatives
Check list of promising alternatives
 Outcome: A list of verified promising alternatives
29
worth further, in-depth exploration
Steps in Sequential Elimination
Locating and prioritizing aspects or factors
Explicate within-factor preferences in the most
important factor not yet considered
Eliminate incompatible alternatives
Too many promising alternatives?
no
This is the recommended list of occupations
worth further, in-depth exploration
30
yes
A Schematic Presentation of the
Sequential Elimination Process
(within aspects, across alternatives)
Potential Alternatives
Aspects
a
b
1
2
3
4
(most
important)
(second in
importance)
c
.
n
31
Promising
Alternatives
.
.
.
.
N
In-depth exploration
 Goal: Locating alternatives that are not only promising
but indeed suitable for the individual.
 Method: collecting additional information, focusing on
one promising occupation at a time:


Is the occupation INDEED suitable for me?
 verifying compatibility with one’s preferences in the
most important aspects
 considering compatibility within the less important
aspects
Am I suitable for the occupation?
 probability of actualization: previous studies, grades,
achievements
 fit with the core aspects of the occupation
 Outcome: A few most suitable alternatives (about 3-4)
32
Choice
 Goal: Choosing the most suitable alternative, and rank-
ordering additional, second-best alternatives
 Method:


comparing and evaluating the suitable alternatives
pinpointing the most suitable one
 Am I likely to activate it?
 if not - selecting second-best alternative(s)
 if yes - Am I confident in my choice?
 if not: Return to In-depth exploration stage
 if yes: Done!
 Outcome: The best alternative or a rank-order of the
best alternatives
33
Still…
 Career decision-making requires collecting a vast
amount of information
 Complex information-processing is needed
But luckily,
information and communication
technologies are available
 The use of a computer-assisted career guidance
system based on a theoretical model can help
overcome human cognitive limitations
 There are several computer-assisted career guidance
systems available, most of them on the Internet
34
However,
although Internet-based, career-related selfhelp sites are flourishing,
these sites, as well as “stand-alone” computerassisted career-guidance systems, vary greatly
in quality.
Hence,
it is very important to investigate the utility
and validity of these self-help programs.
35
Stand-Alone, Internet-Based
Career-Planning Systems
Desirable Features
Possible Solutions
Assessment of needs
CDDQ
Providing guidance
concerning the process
Steps (PIC), factors to
consider, dealing with
compromises and
uncertainty
potential alternatives,
their characteristics,
training
Providing relevant and
accurate information
36
Stand-Alone Internet-Based
Career-Planning Systems (continued)
Desirable Features
Possible Solutions
Monitoring the dialogue
User’s inputcontinuous feedback,
outcome – sensitivity
analysis
on the Internet or
elsewhere
Guiding the user toward
additional sources of
information
37
Directing the user to
face-to-face counseling
when needed
informative summary
of the dialogue
MBCD
Making Better Career Decisions
MBCD is an Internet-based career planning
system that is a unique combination of
 a career-information system
 a decision-making support system
 an expert system
Based on the rationale of the PIC model,
MBCD is designed to help deliberating
individuals make better career decisions
38
MBCD – Goals
 Advancing the user’s career decision-making
by locating a small set of promising
occupational alternatives on which s/he may
focus and collect more detailed information.
 Increasing the user’s readiness and motivation
to make a career decision.
 Presenting a practical model of career
39
decision-making that can be implemented in
future career decisions as well as other
decisions.
MBCD –
System’s Features
 Prescreening
Promising alternatives are located using the
Sequential-Elimination model (Gati, 1986),
which takes into consideration those career
aspects that are most important to the
counselee.
 MBCD includes 28 career factors
40
41
MBCD’s Key Features (cont.)

42
Eliciting both facets of the individual’s
preferences:
(a) the optimal level
(b) additional levels that the user regards as
acceptable (reflecting the user’s willingness
to compromise)
43
44
MBCD’s Key Features (cont.)
45

Each occupation is characterized by a range of
levels within each aspect, reflecting the
within-occupation variance.

The system provides detailed feedback and
recommendations according to the user’s input
and its effect on the search results.

The dialogue is flexible and the users can
change their responses at any point.
46
47
MBCD’s Key Features (cont.)
 Promising alternatives are located by the
Sequential-Elimination search
model (Gati, 1986).
 But the user can also use a compensatory-
model-based search.
48
Compensatory model-based search

Goal – locating the most compatible occupations

Rationale - advantages of occupations may
compensate for their disadvantages

Steps of the compensatory search
Locate gaps between preferences and the
characteristics of the occupation for each factor
Sum the gaps, weighted by importance of factors
Locate occupations with minimal sum of gaps
49
The Conjunction of the Two Lists
Sequential
elimination-based
list
Conjunction
list
Compensationbased list
Users are advised to focus on the occupations that were included
in the recommended list of both search models in the in-depth
exploration
50
51
MBCD’s Key Features (cont.)
Options to check the quality of the list of
“promising occupations”, including:
 “Almost compatible occupations”
(i.e., sensitivity analysis)
 “Why not”
 “What if”
 “Similar occupations”
 “Compare Occupations”
52
53
MBCD’s Features (cont.)
Initial in-depth explorations is offered
by detailed occupational descriptions
54
55
MBCD’s Features (cont.)
At the end of the dialogue


56
the user receives a printed summary to take
along for further processing of the
information. The printout also provides
information for the counselor.
The user’s preferences are saved under a
personalized code for future interactions.
Making
Better
Career
Decisions
Does it really work?
57
END of PART 1
58
Making
Better
Career
Decisions
Does it really work?
59
Prescreening Based on Elimination:
Descriptive Validity (Gati &
Tikotzki,1989)
 The monitored dialogues of 384 career
counselees with a computer-assisted career
information system were analyzed.
 Results: most users (96%) employed a non-
compensatory strategy during all or at least a
part of the dialogue: many options considered at
a previous stage of the dialogue were not
considered at the following stage, showing that
individuals tend to use a prescreening strategy
based on eliminating alternatives
60
Criteria for Testing the Benefits of
Making Better Career Decisions
 Examine users' perceptions of MBCD
 Examine changes in user’s degree of
decidedness
 Examine perceived benefits
 Locate factors that contribute to these
variables
61
METHOD
Participants
 247 males and 465 females who filled out
both a pre-dialogue and a post-dialogue
questionnaire
 Mean age 22.8; mean years of education 12.6







62
4% high-school students
6% recent graduates from high school
58% recently completed their military service
9% considering an alternative to their current major
3% college graduates deliberating a job choice
8% considering a career transition
12% "other"
Mean Perceived Benefit (MPB) and Willingness to Recommend
(WR) the Use of MBCD to a Friend (%) as a Function of the
Difference in Decidedness after the Dialogue of MBCD
(N=712)
Decidedness
No change
Decreased
355
(50%)
266
(37%)
91
(13%)
MPB
3.12
2.57
2.52
WR%
93.5
74.8
72.5
Measure
Frequency
63
Increased
Frequencies of Degree of Decidedness
Before and after the Dialogue with MBCD
Decidedness Before the Dialogue
Decidedness
After the Dialogue
1
2
3
4
5
1- no direction
34
7
6
7
0
2 - only a general
direction
41
66
15
9
5
3 - Client is considering a
few specific alternatives
27
58
84
30
6
4 - would like to examine
additional alternatives
23
51
35
54
6
5 - would like to collect
information about a
specific occupation
6 - sure which
occupation to choose
9
20
21
41
28
3
0
1
9
16
Willingness to Recommend (WR) the Use of MBCD to a friend as a
Function of the Degree of Decidedness Before and After the Dialogue with
MBCD (N=712)
Decidedness
After the Dialogue
with MBCD
Decidedness Before the
Dialogue with MBCD
1
2
3
4
5
1- no direction
38
14
17
29
--
2 - only a general direction
85
73
67
67
100
3 - considering a few
specific alternatives
4 - client would like to examine
additional alternatives
5 - would like to collect information
about a specific occupation
100
93
82
97
100
100
92
100
82
100
100
85
90
98
89
6 - Client is sure which
occupation to choose
100
--
100
100
81
MBCD’s Effect on Reducing
Career Decision-Making Difficulties (d, Cohen, 1992)
Scale
d
Lack of Readiness
Motivation
General indecisiveness
Dysfunctional Beliefs
.31
.13
.29
.16
Lack of Information About
The Process
The Self
Occupational Alternatives
Additional Sources
.72
.48
.45
.78
.20
Inconsistent Information
Unreliable Information
Internal Conflicts
External Conflicts
.11
.18
.01
-.13
Total CDDQ
.65
MBCD’s Effect (d, Cohen, 1992) on Reducing
Career Decision-Making Difficulties
(Gati, Saka, & Krausz, 2003)
0.8
0.72
0.65
d
0.7
0.6
0.5
0.4
0.31
0.3
0.2
0.11
0.1
0
Lack of
Readiness
67
Lack of
Information
Inconsistent
Information
Total CDDQ
Perceived Suitability of the "Promising Alternatives" List
(N=
)
%
%
too long
%
%
%
suitable
%
%
%
too short
%
%
%
(n=
)
(n= )
(n=
) (n=
) (n=
)
(n=
)
(n= )
Number of Alternatives (n - of users)
68
(n= )
+
(n=
)
Predictive Validity of MBCD
 Design: Comparing the Occupational Choice
Satisfaction (OCS) of two groups:


69
those whose present occupation was
included in MBCD’s recommended list
those whose present occupation was not
included in MBCD’s recommended list
Method
 Participants


70
The original sample included 123 clients who
used MBCD in 1997, as part of their
counseling at the Hadassah CareerCounseling Institute
Out of the 73 that were located after six+
years, 70 agreed to participate in the
follow-up:
44 women (64%) and 26 men (36%),
aged 23 to 51 (mean = 28.4, SD = 5.03)
Method
 Instruments

Questionnaire: clients were asked to report
their field of studies, their satisfaction
with their present occupational choice (scale
of 1 – 9): “low” (1-4), “moderate” (5-7),
“high” (8-9)
 Procedure
 the located clients were interviewed by
phone, six+ years after visiting the careercounseling center

71
MBCD
Results
Frequencies of Occupational Choice Satisfaction
by Acceptance and Rejection of MBCD's Recommendations,
Based on Sequential Elimination
100%
16%
18%
90%
80%
low satisfaction
70%
medium satisfaction
60%
44%
50%
high satisfaction
84%
40%
30%
20%
38%
10%
0%
72
accepted
did not accept
recommendations
recommendations
Frequencies of Occupational Choice
Satisfaction by the Search-Model Whose
Recommendations Were Accepted
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
73
3
2
1
2
5
10
low
satisfaction
medium
satisfaction
high
satisfaction
13
10
3
10
Elimination
Conjunction
Compensation
None
Conclusions
 Accepting the recommendations of the
sequential-elimination-based search of MBCD
produces the best outcomes (i.e., highest
levels of satisfactions with the occupation)
 The data does not support the effectiveness
of the compensatory-based search
 The data does not support any advantage of
74
using the conjunction list over using only the
sequential-elimination-search list
Alternative Explanations
Differences in the lengths of the lists
 No difference was found in the OCS between clients
whose list included 15 or fewer occupations and clients
whose list included more than 15 occupations.
 Therefore, this explanation can be ruled out.
75
Alternative Explanations
(cont.)
Clients who accepted MBCD’s
recommendations are more compliant, and
therefore more inclined to report a high
level of satisfaction.
 However, following the compensatory-model-based
recommendations did not contribute to the OCS.
 Therefore, this explanation can be ruled out too.
76
Gender Differences in Directly and Indirectly
Elicited Career-Related Preferences
Gadassi and Gati 2006
Method
 Participants. 226 females (74.1%) and 79
males (25.9%) who entered the Future
Directions Internet site
 Age: 17-30, mean=22.84 (median = 22, SD =
3.34)
 Years of education: mean=12.67 (median 12,
SD = 1.48)
77
Instruments
78

Future Directions

Making Better Career Decisions (MBCD,

The preference questionnaire: this
(http://www.kivunim.com)
http://mbcd.intocareers.org)
questionnaire imitated the preference
elicitation in MBCD. Participants were
presented with 31 aspects, and were asked to
rank-order them according to importance, and
to report their preferences in all 31 aspects
Preliminary analysis
 Lists of occupations. We used MBCD to generate
three lists of occupations according to:
(1) sequential-elimination
(2) compensation, and, for 235 participants,
(3) the list based on the conjunction between the
sequential elimination and the compensatory search
lists.
79
Preliminary analysis

Lists of occupations. We used MBCD to
generate three lists of occupations according
to:
1.
2.
3.
80
sequential-elimination
compensation
and, for 235 participants,
the list based on the conjunction
between the sequential elimination and the
compensatory search lists
Preliminary analysis
 Determining the degree of gender-ratings of
occupations was based on the judgments of 10
undergraduate students.
 1 – “most (that is, over 80%) of the individuals who
work in this occupation are women”
 5 – “most (that is, over 80%) of the individuals
who work in this occupation are men – over 80%"
The inter-judge reliability was .96,
 We computed the mean gender-ratings of the lists
of occupations for each participants
81
Preliminary analysis

Lists of occupations. We used MBCD to
generate three lists of occupations according
to:
1.
2.
3.
82
sequential-elimination
compensation
and, for 235 participants,
the list based on the conjunction
between the sequential elimination and the
compensatory search lists
Gender Differences in Directly and Indirectly Elicited
Preferred Occupations (Gadassi & Gati, 2007)
Means of the Femininity-Masculinity Ratings According to
Type of List and Gender
3.18
3.13
2.96
Men
Women
2.71
Elimination
83
Explicit
3.3
3.2
3.1
3
2.9
2.8
2.7
2.6
2.5
2.4
Summary of Major Findings
 PIC is compatible with people’s intuitive ways of
making decisions (Gati & Tikotzki, 1989)
 Most users reported progress in the career
decision-making process (Gati, Kleiman, Saka, & Zakai,
2003)


Satisfaction was also reported among those who did
not progress in the process
Users are “goal-directed” – the closer they are to
making a decision, the more satisfied they are with
MBCD
 The list of Recommended Occupations are not sex-
type biased (Gadassi & Gati, 2006)
84
Identifying the Client’s Stage
in the Process
 It is possible to start the PIC process from
“the middle” – according to the client’s needs
 However, it is recommended to start the
process from the beginning, in order to:




85
Strengthen confidence in the occupational
alternatives considered by the client
Eliminate inadequate alternatives considered by
the client
Offer additional alternatives that were not
considered by the client so far
Teach decisions skills: aspect-based instead of
occupation-based approach
The stage in the PIC model decision-process
of pre-academic programs students, at the
beginning and end of the program (N=386)
The stage in the decision-making process – beginning of programs
The stage in the dcm process – end
of programs
1
2
3
4
total
1-before pre-screening
3
7
2
1
13
2-before in-depths exploration
11
44
17
5
77
3- before choice
12
45
29
7
93
4 – after choice
8
85
50
60
203
34
181
98
73
386
Total - over rows
86
211 )55%( made progress in the process
136 )35%( stayed in the same stage
39 )10%( moved backwards
Tailoring the Intervention to the
Client’s Decision-Making Style
 There is an advantage in tailoring the counseling
intervention to the client’s decision-making style
 Previous research typically characterized individuals
by the most dominant characteristic of their decisionmaking style (e.g., intuitive, dependent).
 we suggest that a multidimensional analysis should be
used to uncover a comprehensive decision-making
style-profile of clients.
 A theoretical framework based on ten dimensions
related to the career decision-making process was
developed for characterizing individuals' careerdecision making styles
87
The Ten Dimensions
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
88
The degree of analytic vs. holistic informationprocessing
The level of effort invested in the process
The degree of comprehensiveness in gathering and
integrating the information
The degree of consultation with others
The degree of realism (willingness to compromise)
Internal vs. external locus of control
The speed of making the final decision
The degree of procrastination
The degree of dependence on others
The degree of acceptance to others’ wills
Testing the Proposed Model
 To empirically test the proposed taxonomy we
developed the career Decision-making Style
Questionnaire (DSQ), in which each of the
proposed dimensions was represented by a few
statements.
 The questionnaire was uploaded to a careerrelated, self-help oriented Internet site
(www.kivunim.com )
 A cluster analysis supported the proposed
differentiation between all ten dimensions.
89
90
91
Locating Repeated Profiles of
Decision-Making Styles
 Based on a cluster analysis of the participants,
we located homogeneous groups of participants
with similar career decision-making style
profiles
 We found five groups of participants with
similar decision-making styles
 These results were discussed in terms of the
92
hypothesized ten dimensions and the
previously identified career decision-making
styles
The Means of the Located Groups in Terms of the 10
Dimensions Red = Low; Green = High
Group
3
4.4
4
2.3
5
2.4
4.2
4.2
4.4
2.7
3.3
3.5
3.1
4.0
2.2
2.4
3.3
3.7
Dimension
Analytic
1
2
4.5
Effort
Comprehens.
Consulting
Realistic
4.6
4.6
4.5
3.6
3.4
3.9
3.4
2.3
3.2
Locus of
Speed
Procrastin
2.9
2.6
3.2
4.1
3.9
4.1
4.6
3.7
3.9
1.9
3.1
3.4
2.6
3.7
2.9
Dependence
Acceptance
3.9
4.1
4.9
4.6
4.4
3.6
3.1
2.0
4.1
4.2
General Average of the Located Groups
94
Group
M
Sd
4
2.91
0.43
5
3.17
0.50
2
3.82
0.48
1
3.87
0.36
3
4.03
0.23
To sum up, I presented and
discussed:
 The CDDQ for locating the focuses of the
individual’s decision-making difficulties, and the
design and testing of a systematic procedure for
interpreting its results
 A general framework for cdm – the PIC model
 MBCD – a unique combination of career
information, expert, and a decision-support system
 DSQ – A taxonomy and a questionnaire for a
multidimensional analysis of client’s decision-making
styles
95
To sum up
 Career choices are decision-making processes,
96
therefore career counseling is also decision
counseling
 Decision theory can be translated into
practical interventions aimed at facilitating
individuals’ career decision-making
 Many tools were transformed into userfriendly Internet-based systems, which can be
incorporated into counseling interventions
 The theory-based interventions can and should
be empirically tested for theoretical validity
as well as practical effectiveness
97
END
 Sofsof
98
Figure 2:
non
credible
Ascertaining
Credibility
doubtful
credible
Estimating
Differentiation
partial
low
high
Locate Salient
Difficulty Categories
Aggregate
Reasons to Add
Reservation (RAR)
RAR = 3
B/W < 1
Compute
Informativeness
(Bv/Wv)
RAR ≤ 2
Add Reservation
to Feedback
99
B/W > 1
Receives
Feedback
No Feedback
Results:
male
2.953.04
3.23.23
3.18
2.71
3.13
2.96
El
ve
it
i
Po
s
im
in
at
io
n
on
pe
ns
at
i
Co
m
10
0
Co
nj
un
ct
io
n
female
5
4.5
4
3.5
3
2.5
2
1.5
1
femininity-masculinity rating
Compared Means of the Femininity-Masculinity Score
According to Type of List and Gender
The Empirical Structure of the
10 Dimensions
10
1
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Facilitating Career Decision-Making