Evidence-Based Practice: Applying Decision-Theory to Facilitate Individual’s Career Choices

Itamar GatiThe Hebrew University Jerusalem

2

Choosing a Career as a Decision-Making 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 Soft, subjective Fuzzy Inaccurate or biased

3

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 emotional and personality-related factors necessity for compromise actual or perceived social barriers and

biases

4

0%

20%

40%

60%

yes somewhat no

CDM Difficulties of 15,000 surfers on the Future Directions website (Gati & Meyers, 2003)

Are you experiencing difficulties in making your career decision?

5

Implications and Conclusion

Many factors contribute to the complexity and difficulties involved in the career decision-making 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

6

How can Theoretical Knowledge and Empirical Methods be used for Developing Counseling Instruments?

Today’s PresentationThe 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)

7

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: 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

8

Prior to Engaging in the

Process

Lack of Readiness due

to

Lack of motivatio

n

Indeci-sivene

ss

Dysfunc-tional beliefs

During the Process

Lack of Information

about

Cdm proce

ss

Self Occu-patio

ns

Ways of obtaining info.

Inconsistent Information due

to

Unreliable Info.

Internal conflict

s

Externalconflic

ts

Figure 1: Locating Career Decision-making Difficulties based on the taxonomy of Gati, Krausz, & Osipow (1996)

9

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

10

11

Empirical Structure of the Difficulties (N= 10,000; 2004)

Lack of motivations

Indecisiveness

Dysfunctional beliefs

Lack of info about process

Lack of info about self

LoI about occupationsLoI about addition sources of help

Unreliable Information

Internal conflicts

External conflicts

12

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.

13

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 locating the individual’s salient difficulties and recommending ways to deal with them (with added reservations when needed)

14

1. Ascertaining Credibility, using validity items and the time required to fill out the questionnaire

2. Estimating Differentiation based on the standard deviation of the 10 difficulty-scale scores

3. Locating the Salient, moderate, or negligible difficulties, based on the individual's absolute and relative scale scores

4. Determining the need to add reservations to the feedback provided (based on doubtful credibility, partial differentiation, or low informativeness)

The Four Stages of Interpretation

15

The 4 Stages of Interpretation

CredibleDoubtful

HighQuestionable

Locate Salient Difficulties

Add Reservationto Feedback

Low

No Feedback

Compute Informativeness

(B /W )

Receives Feedback

B/W > 1

B/W < 1

Estimating Differentiation

EvaluatingCredibility

Not Credible

AggregateReasons to Add

Reservation (RAR)

RAR ≤ 2RAR = 3

1

2

3

4

16

The goal: empirically testing a four-stage model for interpreting the CDDQ profiles of individuals

The interpretation is based on the within-client 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

Interpreting the CDDQ results

17

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

18

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

19

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 )

Results: see Figures 3 & 4

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0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

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

p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I

1 2 3 4 5 6 7 8 9 10

salient difficulty moderate difficulty no difficulty

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)

Difficulty category

21

Figure 4: Distribution of types of feedback in the four groups

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

P & P Internet P & P Internet

feedback

add reservation

no feedback

Hebrew English

22

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

23

General Feedback on the CDDQ

24

Detailed Feedback on the CDDQ

25

26

27

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)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

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

p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I p I

1 2 3 4 5 6 7 8 9 10

salient difficulty moderate difficulty no difficulty

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The PIC model (Gati & Asher, 2001)which separates the career decision- making process into 3 distinct stages:

- Prescreening - In-depth exploration

- Choice

Guidance in the decision-making process

29

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 worth further, in-depth exploration

30

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?

This is the recommended list of occupations

worth further, in-depth exploration

yes

no

Steps in Sequential Elimination

31

A Schematic Presentation of theSequential Elimination Process (within aspects, across alternatives)

Potential Alternatives

1 2 3 4 . . . . NAspects

a (most important)

b (second in

importance)

c

.

n Promising Alternatives

32

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)

33

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

34

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

35

However,

although Internet-based, career-related self-help sites are flourishing,

these sites, as well as “stand-alone” computer-assisted career-guidance systems, vary greatly in quality.

Hence, it is very important to investigate the utility

and validity of these self-help programs.

36

Stand-Alone, Internet-Based Career-Planning Systems

Desirable Features

Possible Solutions

Assessment of needsCDDQ

Providing guidance concerning the process

Steps (PIC), factors to consider, dealing with compromises and uncertainty

Providing relevant and accurate information

potential alternatives, their characteristics, training

37

Stand-Alone Internet-Based Career-Planning Systems (continued)

Desirable Features

Possible Solutions

Monitoring the dialogueUser’s input- continuous feedback, outcome – sensitivity analysis

Guiding the user toward additional sources of information

on the Internet orelsewhere

Directing the user to face-to-face counseling when needed

informative summary of the dialogue

38

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

39

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 decision-making that can be implemented in future career decisions as well as other decisions.

MBCD – Goals

40

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

41

42

MBCD’s Key Features (cont.) 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

45

MBCD’s Key Features (cont.)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

48

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.

49

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

50

The Conjunction of the Two Lists

Users are advised to focus on the occupations that were included in the recommended list of both search models in the in-depth exploration

Sequential elimination-based list

Compensation-based list

Conjunctionlist

51

52

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”

53

54

MBCD’s Features (cont.)

Initial in-depth explorations is offered by detailed occupational descriptions

55

56

MBCD’s Features (cont.)

At the end of the dialogue 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.

57

Making Better Career Decisions

Does it really work?

58

END of PART 1

59

Making Better Career Decisions

Does it really work?

60

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

61

Examine users' perceptions of MBCD

Examine changes in user’s degree of decidedness

Examine perceived benefits

Locate factors that contribute to these variables

Criteria for Testing the Benefits of Making Better Career Decisions

62

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 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"

63

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

  Increased No change Decreased

Frequency 355 (50%)

266 (37%)

91 (13%)

MPB 3.12 2.57 2.52

WR% 93.5 74.8 72.5

Measure

Frequencies of Degree of Decidedness Before and after the Dialogue with MBCD

Decidedness After the Dialogue

Decidedness Before 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

9 20 21 41 28  

6 - sure which occupation to choose

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)

DecidednessAfter the Dialoguewith 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

100 93 82 97 100

4 - client would like to examine additional alternatives

100 92 100 82 100

5 - would like to collect information about a specific occupation

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)

Scaled

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

67

MBCD’s Effect (d, Cohen, 1992) on Reducing Career Decision-Making Difficulties

(Gati, Saka, & Krausz, 2003)

0.31

0.72

0.11

0.65

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Lack ofReadiness

Lack ofInformation

InconsistentInformation

Total CDDQ

d

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Perceived Suitability of the "Promising Alternatives" List (N=693)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

26+(n=37)

16-25(n=46)

11-15(n=40)

8-10(n=45)

7(n=236)

6(n=121)

5 (n=71)

3-4(n=74)

2 (n=23)

Number of Alternatives (n - of users)

too long

suitable

too short

69

Predictive Validity of MBCD

Design: Comparing the Occupational Choice Satisfaction (OCS) of two groups:

those whose present occupation was

included in MBCD’s recommended list those whose present occupation was not

included in MBCD’s recommended list

70

Method

Participants The original sample included 123 clients

who used MBCD in 1997, as part of their counseling at the Hadassah Career-Counseling 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)

71

Instruments MBCD 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 career-counseling center

Method

72

84%

38%

16%

44%

18%

0%10%20%30%40%50%60%70%80%90%

100%

accepted

recommendations

did not accept

recommendations

low satisfaction

medium satisfaction

high satisfaction

ResultsFrequencies of Occupational Choice Satisfaction by Acceptance and Rejection of MBCD's Recommendations, Based on Sequential Elimination

73

Frequencies of Occupational Choice Satisfaction by the Search-Model Whose Recommendations Were Accepted

3 1013 10

102

23 51

0%10%

20%30%40%

50%60%70%80%

90%100%

Elimination Conjunction Compensation None

lowsatisfaction

mediumsatisfaction

highsatisfaction

74

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 using the conjunction list over using only the sequential-elimination-search list

75

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.

76

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.

77

Gender Differences in Directly and Indirectly Elicited Career-Related PreferencesGadassi 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)

78

Instruments

Future Directions (http://www.kivunim.com)

Making Better Career Decisions (MBCD, http://mbcd.intocareers.org)

The preference questionnaire: this 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

79

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.

80

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

81

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

82

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

83

Means of the Femininity-Masculinity Ratings According to Type of List and Gender

3.18

2.96

3.13

2.71

2.42.52.62.72.82.933.13.23.3

ExplicitElimination

Men

Women

Gender Differences in Directly and Indirectly Elicited Preferred Occupations (Gadassi & Gati, 2007)

84

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)

85

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: 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

86

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 2 113

2-before in-depths exploration

11 4417 577

3- before choice 12 4529 7

93

4 – after choice 8 8550 60203

Total - over rows 34 18198 73386

(55%) 211 made progress in the process (35%) 136 stayed in the same stage (10%) 39 moved backwards

87

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 decision-making 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' career-decision making styles

88

The Ten Dimensions

1. The degree of analytic vs. holistic information-processing

2. The level of effort invested in the process 3. The degree of comprehensiveness in gathering

and integrating the information4. The degree of consultation with others5. The degree of realism (willingness to

compromise)6. Internal vs. external locus of control7. The speed of making the final decision8. The degree of procrastination9. The degree of dependence on others10. The degree of acceptance to others’ wills

89

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 career-related, self-help oriented Internet site (www.kivunim.com )

A cluster analysis supported the proposed differentiation between all ten dimensions.

90

91

92

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 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

Dimension12345

Analytic4.53.44.42.32.4

Effort4.63.94.23.32.2

Comprehens.

4.63.44.23.52.4

Consulting4.52.34.43.13.3

Realistic3.63.22.74.03.7

Locus of 2.94.14.61.92.6

Speed2.63.93.73.13.7

Procrastin3.24.13.93.42.9

Dependence

3.94.94.43.14.1

Acceptance4.14.63.62.04.2

94

General Average of the Located Groups

GroupMSd

42.910.43

53.170.50

23.820.48

13.870.36

34.030.23

95

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

96

To sum up

Career choices are decision-making processes, 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 user-friendly 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

98

END

Sofsof

99

credibledoubtful

high partial

Locate Salient Difficulty Categories

Add Reservationto Feedback

low

No Feedback

Compute Informativeness

(Bv/Wv)

Receives Feedback

B/W > 1

B/W < 1

Estimating Differentiation

AscertainingCredibility

noncredible

AggregateReasons to Add

Reservation (RAR)

RAR ≤ 2RAR = 3

Figure 2:

100

Results: Compared Means of the Femininity-Masculinity Score According to Type of List and Gender

3.182.71

3.04 3.23 3.133.22.95 2.96

11.522.533.544.55

Posit

ive

Elim

inat

ion

Compe

nsat

ion

Conj

unct

ion

fem

inin

ity-

mas

culin

ity

rati

ng

male

female

101

The Empirical Structure of the 10 Dimensions