Part 4 The PIC Model: Supporting Evidence

1. Part 4The PIC Model: Supporting Evidence or: Does it really work? Itamar Gati The Hebrew University of Jerusalem

2. Evaluating Prescriptive Decision Models • Descriptive models are evaluated by their empirical validity • Normative models by their theoretical adequacy • Prescriptive models are evaluated by their pragmatic value – their ability to facilitate individuals' decision-making

3. Evaluating Prescriptive Decision Models • The basic assumption: the right process increases the probability of choosing the best option • The evaluation of the model should examine: • Does the model improve individuals' decision-making processes? • Does it lead to greater occupational satisfaction in the future? • Do individuals generalize the model and apply it to future career decisions?

4. 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

5. Criteria for Testing the Benefits ofMaking 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

6. Study 1 –Gati, Kleiman, Saka, & Zakai (2003) 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 • 10% high-school students and graduates • 58% young adults (recently discharged) • 9% considering an alternative to their current major • 3% college graduates deliberating a job choice • 20% considering a career transition and other

7. Method - Instruments • "Future Directions"- Israeli website (in Hebrew) • Pre-dialogue questionnaire (prerequisite to accessing the system) • MBCD - Making Better Career Decisions (mean dialogue time = 40 minutes, SD=25) • Post-dialogue questionnaire

8. 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 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) Measure

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

10. Decidedness Before the Dialogue with MBCD Decidedness After 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 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)

11. During the Process Prior to Engaging in the Process Lack of Readiness due to Inconsistent Information due to Lack of Information about Lack of motivation Indeci-siveness Dysfunc-tionalbeliefs Cdmprocess Self Occu- pations Internal conflicts Externalconflicts Ways of obtaining info. Taxonomy of Career Decision-Making Difficulties(CDDQ; Gati, Krausz, & Osipow, 1996) Unreliable Info.

13. MBCD’s Effect (d, Cohen, 1992)on Reducing Career Decision-Making Difficulties(Gati, Saka, & Krausz, 2003)

15. Predictive Validity of MBCD(Gati, Gadassi, & Shemesh, 2006) • Design: Comparing the Occupational Choice Satisfaction (OCS) of two groups: • those whose chosen occupation was included in MBCD’s recommended list • those whose chosen occupation was not included in MBCD’s recommended list

16. 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)

17. Method • Instruments • MBCD • Questionnaire: clients were asked to report their field of studies, their satisfaction with their 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

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

19. 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

20. 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.

21. 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.

22. Conclusion • Following the recommendations of the sequential-elimination-based search of MBCD produces the best outcome

23. Gender Differences in Directly and Indirectly Elicited Career-Related Preferences (Gadassi & Gati, 2009) • Method • Participants: 226 females (74.1%) and 79 males (25.9%) who entered the Future DirectionsInternet site • Age: 17-30, mean=22.84 (median = 22, SD = 3.34) • Years of education: mean=12.67 (median 12, SD = 1.48)

24. 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 MBCDParticipants were presented with 31 aspects, and were asked to rank-order them according to importance, and to report their preferences in all 31 aspects

25. Preliminary analysis • Two lists of occupations were compared: • We used MBCD to generate the recommended list of occupations based on the individual’s preferences in the career aspects (the “elimination” list) • We compared the “elimination list” with the “explicit list” – individuals were asked to freely declare a list of occupations suited for them.

26. 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

27. Gender Differences in Directly and Indirectly Elicited Preferred Occupations(Gadassi & Gati, 2009)

28. MBCD - Summary of Major Findings • Most users reported progress in the career decision-making process • 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 the MBCD

29. MBCD - Summary of Major Findings Using MBCD contributed to a decrease in career decision-making difficulties related to a lack of information Using MBCD can contribute to decrease in the gender-bias of career choices Following the MBCD’s advice doubled the probability of high occupational choicesatisfaction 6 years later 29

30. Summary of PIC • Career counseling may be viewed as decision counseling, which aims at promoting making better career decisions • The PIC model facilitates the complex process of career choice by separating it into a sequence of well-defined tasks • MBCDis a unique combination of career information system, expert system, and a decision-support systembased on the PIC rationale

31. Summary of PIC (cont.) • The use of the PIC model and MBCD contributes to: progress in the decision process, reduction in decision-making difficulties, reduction of gender (and possibly other) stereotypes, and higher occupational satisfaction in the future • PIC and MBCD can be incorporated into career-counseling interventions

32. WWW.CDDQ.ORGitamar.gati@huji.ac.il

33. END • sofsof

34. MBCD’s Effect onReducing Career Decision-Making Difficulties (d, Cohen, 1992) 34

35. Monitoring the Dialogue Evaluating the input The 3 facets of preferences (relative importance of aspect, optimal level, willingness to compromise) Crystallization of preferences (differentiation, consistency, coherence) Evaluating the process Which options were used and in what order (almost compatible, additional search, why not? what if? Compare occupations, similar occupations) Evaluating the outcome (list of career alternatives) The number of alternatives on the list The similarity among the alternatives on the list 35