Identifying distinct career indecision profiles allows for the tailoring of counseling interventions to address each client’s specific needs. While Levin, Lipshits-Braziler, and Gati (2024) established a general seven-profile typology across 16 countries, cultural and socioeconomic variations necessitate replicating this model while exploring potential context-specific profiles within a specific country. Accordingly, this study explored career indecision types among Turkish undergraduate students (N = 1,377) and examined profile differences in relation to background characteristics and career-related outcomes. Latent profile analysis replicated six profiles from the general typology with some nuances: Unrealistic–Indecisive, Generally Uninformed, Uninformed–Conflicted, Internally Conflicted, Externally Conflicted, and Unmotivated. Additionally, a context-specific seventh profile—Generally Conflicted—emerged. Results indicated that gender and socioeconomic status were significant predictors of profile membership, whereas age had a minimal impact. Furthermore, profiles differed significantly in career decidedness, self-efficacy, locus of control, and ambiguity intolerance. These findings are discussed within the Turkish socioeconomic and cultural framework, as well as the broader international literature. The findings provide a basis for implementing targeted counseling strategies and outline key directions for future research.
AsparouhovT.MuthénB. (2014). Auxiliary variables in mixture modeling: Three-step approaches using Mplus. Structural Equation Modeling: A Multidisciplinary Journal, 21(3), 329–341. https://doi.org/10.1080/10705511.2014.915181
5.
BacanliF. (2016). Career decision-making difficulties of Turkish adolescents. International Journal for Educational and Vocational Guidance, 16(2), 233–250. https://doi.org/10.1007/s10775-015-9304-8
6.
BacanlıF.ÖztemelK. (2017). Kariyer karar verme güçlükleri ölçeğinin genç yetişkin örnekleminde faktör yapısının ve güvenirliğinin incelenmesi [Investigation of factor structure and reliability of career decision-making difficulties scale in young adult sample] [Conference presentation]. 26th international conference on educational sciences, Antalya, Türkiye.
7.
BakkZ.VermuntJ. K. (2016). Robustness of stepwise latent class modeling with continuous distal outcomes. Structural Equation Modeling: A Multidisciplinary Journal, 23(1), 20–31. https://doi.org/10.1080/10705511.2014.955104
BetzN. E.KleinK. L.TaylorK. M. (1996). Evaluation of a short form of the career decision-making self-efficacy scale. Journal of Career Assessment, 4(1), 47–57. https://doi.org/10.1177/106907279600400103
BlusteinD. L.ChavesA. P.DiemerM. A.GallagherL. A.MarshallK. G.SirinS.BhatiK. S. (2002). Voices of the forgotten half: The role of social class in the school-to-work transition. Journal of Counseling Psychology, 49(3), 311–323. https://doi.org/10.1037/0022-0167.49.3.311
12.
BlusteinD. L.EllisM. V.DevenisL. E. (1989). The development and validation of a two-dimensional model of the commitment to career choices process. Journal of Vocational Behavior, 35(3), 342–378. https://doi.org/10.1016/0001-8791(89)90034-1
13.
BrownS. D.RectorC. C. (2008). Conceptualizing and diagnosing problems in career decision-making. In BrownS. D.LentR. W. (Eds.), Handbook of counseling psychology (4th ed., pp. 392–407). Wiley.
14.
Buyukgoze-KavasA. (2014). A psychometric evaluation of the career decision self-efficacy scale–short form with Turkish university students. Journal of Career Assessment, 22(2), 386–397. https://doi.org/10.1177/1069072713484561
15.
Buyukgoze-KavasA.AllanB. A.TuranM.KirazciF. (2021). Context and validation of the subjective underemployment scale among Turkish employees. Journal of Career Assessment, 29(2), 283–302. https://doi.org/10.1177/1069072720961542
CorrellS. J. (2004). Constraints into preferences: Gender, status, and emerging career aspirations. American Sociological Review, 69(1), 93–113. https://doi.org/10.1177/000312240406900106
19.
CostaP. T.Jr.McCraeR. R. (2008). The revised NEO personality inventory (NEO-PI-R). In BoyleG. J.MatthewsG.SaklofskeD. H. (Eds.), The SAGE handbook of personality theory and assessment, Vol. 2. Personality measurement and testing (pp. 179–198). Sage Publications.
20.
DawisR. V. (2005). The Minnesota theory of work adjustment. In BrownS. D.LentR. W. (Eds.), Career development and counseling: Putting theory and research to work (pp. 3–23). John Wiley & Sons.
21.
FitchG. (1970). Effects of self-esteem, perceived performance, and choice on causal attributions. Journal of Personality and Social Psychology, 16(2), 311–315. https://doi.org/10.1037/h0029847
22.
GatiI.KrauszM.OsipowS. H. (1996). A taxonomy of difficulties in career decision making. Journal of Counseling Psychology, 43(4), 510–526. https://doi.org/10.1037/0022-0167.43.4.510
GeliboluS. (2022). Yetişkinlerin kariyer uyumunu paradigma değişimi bağlamında kişisel ve kültürel değişkenlerle inceleyen bir model sınaması [A model testing examining adults’ career adaptability with personal and cultural variables in the context of paradigm shift]. Thesis No. 772408 [Doctoral dissertation, Ankara University]. Council of Higher Education Thesis Center.
25.
HigginsE. T. (1989). Self-discrepancy theory: What patterns of self-beliefs cause people to suffer?Advances in Experimental Social Psychology, 22, 93–136. https://doi.org/10.1016/S0065-2601(08)60306-8
26.
HollandJ. L. (1997). Making vocational choices: A theory of vocational personalities and work environments (3rd ed.). Psychological Assessment Resources.
27.
HooleyT.HertzbergF.Mariager-AndersonK.SaurH.SundelinÅ.VarjoJ.ValdimarsdóttirS.Author (2024). A systematic review of research into career guidance policy in the nordic countries (2008-2022). Nordic Journal of Studies in Educational Policy, 10(2), 126–139. https://doi.org/10.1080/20020317.2024.2352004
28.
HowardM. C.HoffmanM. E. (2018). Variable-centered, person-centered, and person-specific approaches: Where theory meets the method. Organizational Research Methods, 21(4), 846–876. https://doi.org/10.1177/1094428117744021
29.
KağıtçıbaşıÇ. (2017). Family, self, and human development across cultures: Theory and applications. Routledge.
30.
KellyK. R.PulverC. A. (2003). Refining measurement of career indecision types: A validity study. Journal of Counseling and Development, 81(4), 445–453. https://doi.org/10.1002/j.1556-6678.2003.tb00271.x
31.
KirazcıF.ÖztemelK. (2021). Üniversite öğrencilerinin kariyer karar verme belirsizliklerine toleranslarının çeşitli değişkenlerle ilişkilerinin incelenmesi [An examination of university students’ career decision ambiguity tolerance with several variables]. Mehmet Akif Ersoy University Journal of Education Faculty, 58, 442–477. https://izlik.org/JA66AA74FY
LeeB. H.LeeS. M.LeeJ. H. (2025). Unrealistic career optimism among Korean adolescents: A discrepancy between career aspirations and career preparation behaviors. Journal of Career Development, 52(3), 354–368. https://doi.org/10.1177/08948453251322444
34.
LentR. W.BrownS. D. (2020). Career decision making, fast and slow: Toward an integrative model of intervention for sustainable career choice. Journal of Vocational Behavior, 120, 103448. https://doi.org/10.1016/j.jvb.2020.103448
35.
LevinN.Braunstein-BercovitzH.Lipshits-BrazilerY.GatiI.RossierJ. (2020). Testing the structure of the career decision-making difficulties questionnaire across country, gender, age, and decision status. Journal of Vocational Behavior, 116, 103365. https://doi.org/10.1016/j.jvb.2019.103365
36.
LevinN.Lipshits-BrazilerY.GatiI. (2024). Patterns of career decision-making difficulties in 16 countries: A person-centered investigation. Journal of Counseling Psychology, 71(1), 34–47. https://doi.org/10.1037/cou0000704
37.
LevinN.Lipshits-BrazilerY.GatiI. (2022). The identification and validation of five types of career indecision: A latent profile analysis of career decision-making difficulties. Journal of Counseling Psychology, 69(4), 452–462. https://doi.org/10.1037/cou0000603
38.
LevinN.MasdonatiJ.CastellaP.GrassiE. (2024). Associations of career decision-making strategies with career decision-making self-efficacy and difficulties among French-speaking Swiss adolescents and young adults. Journal of Career Assessment, 32(4), 698–720. https://doi.org/10.1177/10690727241232439
39.
LevinN.UdayarS.Lipshits-BrazilerY.GatiI.RossierJ. (2023). The structure of the career decision-making difficulties questionnaire across 13 countries. Journal of Career Assessment, 31(1), 129–148. https://doi.org/10.1177/10690727221099226
MasynK. E. (2013). Latent class analysis and finite mixture modeling. In LittleT. D. (Ed.), The Oxford handbook of quantitative methods (2, pp. 551–611). Oxford University Press. Statistical analysis. https://doi.org/10.1093/oxfordhb/9780199934898.013.0025
42.
MillarR.ShevlinM. (2007). The development and factor structure of a career locus of control scale for use with school pupils. Journal of Career Development, 33(3), 224–249. https://doi.org/10.1177/0894845306296643
43.
MorinA. J. S.MeyerJ. P.CreusierJ.BiétryF. (2016). Multiple-group analysis of similarity in latent profile solutions. Organizational Research Methods, 19(2), 231–254. https://doi.org/10.1177/1094428115621148
44.
MurryR. T.PujarL. A. T. A. (2017). Influence of socioeconomic status on career decision making of undergraduate emerging adults. International Journal of Educational Research, 7, 55–62.
Nylund-GibsonK.ChoiA. Y. (2018). Ten frequently asked questions about latent class analysis. Translational Issues in Psychological Science, 4(4), 440–461. https://doi.org/10.1037/tps0000176
47.
Nylund-GibsonK. L.GrimmR.QuirkM.FurlongM. (2014). A latent transition mixture model using the three-step specification. Structural Equation Modeling: A Multidisciplinary Journal, 21(3), 439–454. https://doi.org/10.1080/10705511.2014.915375
OkorieC. O.OkolieU. C.AwotoyeY. F.MezieobiK. C. (2025). Exploring the impact of family financial support withdrawal on graduates’ school-to-work transition. Career Development International, 31(1), 54–74. https://doi.org/10.1108/CDI-12-2024-0546
50.
PattonW.McMahonM. (2014). Career development and systems theory: Connecting theory and practice (3rd ed.). Sense.
51.
R Core Team. (2025). R: A Language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org
52.
RochatS. (2022). Mapping career counseling interventions: A guide for career practitioners. Routledge.
53.
SakaN.GatiI. (2007). Emotional and personality-related aspects of persistent career decision-making difficulties. Journal of Vocational Behavior, 71(3), 340–358. https://doi.org/10.1016/j.jvb.2007.08.003
54.
SalmanN.KanA. (2021). Predicting career decision-making difficulties: The role of barriers, self-efficacy, and decision status. Turkish Psychological Counseling and Guidance Journal, 11(60), 49–66. https://izlik.org/JA55NE33CR
55.
SampsonJ. P.LenzJ. G.Bullock-YowellE.OsbornD. S.HaydenS. C. W. (Eds.). (2023). Cognitive information processing: Career theory, research, and practice. Florida state open publishing. https://doi.org/10.33009/fsop_sampson1123
56.
SavickasM. L.NotaL.RossierJ.DauwalderJ.-P.DuarteM. E.GuichardJ.SoresiS.Van EsbroeckR.van VianenA. E. M. (2009). Life designing: A paradigm for career construction in the 21st century. Journal of Vocational Behavior, 75(3), 239–250. https://doi.org/10.1016/j.jvb.2009.04.004
57.
SavickasM. L.PorfeliE. J. (2012). Career adapt-abilities scale: Construction, reliability, and measurement equivalence across 13 countries. Journal of Vocational Behavior, 80(3), 661–673. https://doi.org/10.1016/j.jvb.2012.01.011
58.
SimpsonK.JanssenI.CraigW. M.PickettW. (2005). Multilevel analysis of associations between socioeconomic status and injury among Canadian adolescents. Journal of Epidemiology & Community Health, 59(12), 1072–1077. https://doi.org/10.1136/jech.2005.036723
59.
SiyezD. M. (2015). Validity and reliability of a Turkish version of the career locus of control scale. Journal of Career Development, 42(4), 281–293. https://doi.org/10.1177/0894845314557814
SteadG. B.WatsonM. B. (1993). The career myths scale: Its validity and applicability. International Journal for the Advancement of Counselling, 16(2), 89–97. https://doi.org/10.1007/BF01418145
TaylorK. M.BetzN. E. (1983). Applications of self-efficacy theory to the understanding and treatment of career indecision. Journal of Vocational Behavior, 22(1), 63–81. https://doi.org/10.1016/0001-8791(83)90006-4
64.
VermuntJ. K.MagidsonJ. (2002). Latent class cluster analysis. In HagenaarsJ. A.McCutcheonA. L. (Eds.), Advances in latent class analysis (pp. 89–114). Cambridge University Press.
65.
WeinsteinN. D. (1980). Unrealistic optimism about future life events. Journal of Personality and Social Psychology, 39(5), 806–820. https://doi.org/10.1037/0022-3514.39.5.806
66.
WestA.LewisJ.RobertsJ.NodenP. (2017). Young adult graduates living in the parental home: Expectations, negotiations, and parental financial support. Journal of Family Issues, 38(17), 2449–2473. https://doi.org/10.1177/0192513X16643745
67.
WhistonS. C.KellerB. K. (2004). The influences of the family of origin on career development: A review and analysis. The Counseling Psychologist, 32(4), 493–568. https://doi.org/10.1177/0011000004265660
68.
XuH.TraceyT. J. (2014). The role of ambiguity tolerance in career decision making. Journal of Vocational Behavior, 85(1), 18–26. https://doi.org/10.1016/j.jvb.2014.04.001
69.
XuH.TraceyT. J. (2015a). Ambiguity tolerance with career indecision: An examination of the mediation effect of career decision-making self-efficacy. Journal of Career Assessment, 23(4), 519–532. https://doi.org/10.1177/1069072714553073
70.
XuH.TraceyT. J. (2015b). Career decision ambiguity tolerance scale: Construction and initial validations. Journal of Vocational Behavior, 88, 1–9. https://doi.org/10.1016/j.jvb.2015.01.006
71.
ZenerT. B.SchnuelleL. (1976). Effects of the self-directed search on high school students. Journal of Counseling Psychology, 23(4), 353–359. https://doi.org/10.1037/0022-0167.23.4.353
72.
ZhangC.SackettP. R. (2023). Planned missingness: An underused but practical approach to reducing survey and test length. Industrial and Organizational Psychology, 16(1), 129–142. https://doi.org/10.1017/iop.2022.113
