Revisiting The Vocational Outcome Expectations Scale: A Network Psychometric Validation of The Revised Five-Point Likert Version
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https://doi.org/10.14419/nbbc9625
Received date: June 27, 2025
Accepted date: August 23, 2025
Published date: October 17, 2025
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Network Psychometrics; Social Cognitive Career Theory; Secondary School Students; Vocational Outcome Expectations; Vocational Outcome Expectations Scale. -
Abstract
The revised vocational outcome expectations scale measures the expected outcomes of an individual while pursuing a goal. The original Likert scale-based response categories of this tool are increased from four to five by including the neutral option. The tool is validated on a fresh population of high school students belonging to the North Eastern state of Tripura, India, using the Network Psychometrics approach appropriate for the ordinal data type. The purpose was to improve the quality of the responses obtained from the tool, enhance its psychometric robustness by validating it through a network approach, and increase its cross-cultural validity over a fresh population in a novel context. Data was collected through a stratified random sampling technique from schools representing all eight districts of the Tripura state. The sample size was 568 secondary school students (Boys = 286, Girls = 282). Data analysis was conducted using appropriate packages in R ver. 4.4.2. Exploratory graph analysis revealed a single cluster of the construct, consistent with previous studies, with all nodes displaying robust structural-al consistency of 0.938 within the cluster. Rationale for accepting the estimates of ordinal confirmatory factor analysis, like CFI robust, srmr_bentler, tli. robust and RMSEA. robust, as obtained in this study, is provided along with the statistical details related to the regularized network structure, centrality indices, and edge-weight accuracy. The CS-coefficient is found to be 0.362, indicating acceptable stability of the network. The revised vocational outcome expectations scale is found to be a robust instrument among the population of secondary school students.
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References
- Aunger, R., Gallyamova, A., & Grigoryev, D. (2025). Network psychometric-based identification and structural analysis of a set of evolved human motives, Personality and Individual Differences, 233, 112921, ISSN 0191-8869, https://doi.org/10.1016/j.paid.2024.112921.
- Ali, S. R., McWhirter, E. H., & Chronister, K. M. (2005). Self-efficacy and vocational outcome expectations for adolescents of lower socioeconom-ic status: A pilot study. Journal of Career Assessment, 13, 40-58. https://doi.org/10.1177/1069072704270273.
- Alwin, D. F., Baumgartner, E. M., & Beattie, B. A. (2018). “Number of Response Categories and Reliability in Attitude Measurement.” Journal of Survey Statistics and Methodology, 6(2), pp. 212-239.https://doi.org/10.1093/jssam/smx025.
- Bandura, A., & National Inst of Mental Health. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall, Inc.
- Briganti G, Scutari M, Epskamp S, Borsboom D, Hoekstra RHA, Golino HF, Christensen AP, Morvan Y, Ebrahimi OV, Costantini G, Heeren A, Ron J, Bringmann LF, Huth K, Haslbeck JMB, Isvoranu AM, Marsman M, Blanken T, Gilbert A, Henry TR, Fried EI, McNally RJ. Network anal-ysis: An overview for mental health research. Int J Methods Psychiatr Res. 2024 Dec;33(4):e2034. https://doi.org/10.1002/mpr.2034.
- Beckstead, J.W. (2014). On measurements and their quality. Paper 4: Verbal anchors and the number of response options in rating scales. Interna-tional Journal of Nursing Studies. 51, 807–814.https://doi.org/10.1016/j.ijnurstu.2013.09.004.
- Borsboom, D., Deserno, M.K., Rhemtulla, M., Epskamp, S., Fried, E.I., McNally, R.J., Robinaugh, D.J., Perugini, M., Dalege, J., Costantini, G., Isvoranu, A, Wysocki, A.C., van Borkulo, C. D., van Bork, R., & Waldrop, L.J.(2021). Network analysis of multivariate data in psychological sci-ence. Nature Reviews Methods Primers. 1, 58 (2021). https://doi.org/10.1038/s43586-021-00055-w.
- Biswal, S. & Chakraborty, R. (2025). Validation of Science Career Commitment Model for Secondary School Students: Role of Self-Efficacy, Mo-tivation, Engagement and Identity through Network Analysis, Journal of Applied Bioanalysis, 11(3), p. 34-43. https://doi.org/10.53555/jab.v11i3.218.
- Chen, C., Lee, S.Y., & Stevenson, H.W. (1995). Response style and cross-cultural comparisons of rating scales among East Asian and North Amer-ican students. Psychol. Sci., 6, 170–175.https://doi.org/10.1111/j.1467-9280.1995.tb00327.x.
- Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L. J., & Cramer, A. O. J. (2014). State of the aRt personality re-search: A tutorial on network analysis of personality data in R. Journal of Research in Personality. https://doi.org/10.1016/j.jrp.2014.07.003.
- Christensen, A. P., Golino, H., & Silvia, P. J. (2020). A Psychometric Network Perspective on the Validity and Validation of Personality Trait Questionnaires. European Journal of Personality. https://doi.org/10.1002/per.2265.
- Dalege, J., Borsboom, D., Van Harreveld, F., Van den Berg, H., Conner, M., & Van der Maas, H. L. (2016). Toward a formalized account of atti-tudes: The Causal Attitude Network (CAN) model. Psychometric Review, 123(1), 2.https://doi.org/10.1037/a0039802.
- Economic Review of Tripura Report 2023-24, Directorate of Economics and Statistics, Government of Tripura, Agartala, https://ecostat.tripura.gov.in.
- Efron, B. (1979). "Bootstrap Methods: Another Look at the Jackknife." Ann. Statist. 7 (1) 1 – 26. https://doi.org/10.1214/aos/1176344552.
- Epskamp, S., & Fried, E. I. (2018). A tutorial on regularized partial correlation networks. Psychological Methods, 23(4), 617–634. https://doi.org/10.1037/met0000167.
- Efron, B. (1979). Bootstrap methods: another look at the jackknife. The Annals of Statistics, 7(1), 1–26.https://doi.org/10.1214/aos/1176344552.
- Fouad, N. A.,& Guillen, A. (2006). Outcome expectations: Looking to the past and potential future. Journal of Career Assessment, 14, 130-142.https://doi.org/10.1177/1069072705281370.
- Finn, J. A., Ben-Porath, Y. S., &Tellegen, A. (2015). “Dichotomous Versus Polytomous Response Options in Psychopathology Assessment: Meth-od or Meaningful Variance?” Psychological Assessment, 27(1), pp. 184-193.https://doi.org/10.1037/pas0000044.
- Garretsen, H., Stoker, J. I., Soudis, D., Martin, R., &Rentfrow, J. (2019). The relevance of personality traits for urban economic growth: making space for psychological factors.Journal of Economic Geography, 19(3), 541-565. https://doi.org/10.1093/jeg/lby025.
- Golino, H.F, Epskamp, S. (2016). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PLoS ONE, 12(6): e0174035. https://doi.org/10.1371/journal.pone.0174035.
- Golino, H.F., &Demetriou, A., (2017). Estimating the dimensionality of intelligence like data using Exploratory Graph Analysis, Intelligence, https://doi.org/10.1016/j.intell.2017.02.007.
- Henry, T.R. & Ye, A. (2024). The effects of omitted variables and measurement error on cross sectional network psychometrics models, Advances in Psychology, https://doi.org/10.56296/aip00011.
- Isik, E. (2014). Psychometric Properties of Vocational Outcome Expectations Scale inTurkishUndergraduate Students. 3rd Internatonal Counseling and Education Conference, ICEC.
- Johal, S. K., &Rhemtulla, M. (2023). Comparing estimation methods for psychometric networks with ordinal data. Psychological Methods, 28(6), 1251–1272. https://doi.org/10.1037/met0000449.
- Koo M, &Yang S-W. (2025). Likert-Type Scale. Encyclopedia. 5(1):18. https://doi.org/10.3390/encyclopedia5010018.
- Kankaraš, M., Capecchi, S. (2025). Neither agree nor disagree: use and misuse of the neutral response category in Likert-type scales. Metron, 83, 111–140 (2025). https://doi.org/10.1007/s40300-024-00276-5.
- Kulas, J. T., Stachowski, A. A., & Haynes, B. A. (2008).“Middle Response Functioning in LikertResponses to Personality Items.” Journal of Busi-ness and Psychology, 22(3), pp. 251-259.https://doi.org/10.1007/s10869-008-9064-2.
- Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and perfor-mance. Journal of Vocational Behavior, 45(1), 79–122. https://doi.org/10.1006/jvbe.1994.1027.
- Lent, R. W., Brown, S. D., & Hackett, G. (2000). Contextual supports and barriers to career choice: A social cognitive analysis. Journal of Counsel-ing Psychology, 47, 36–49.https://doi.org/10.1037/0022-0167.47.1.36.
- Li, C.H.,(2016). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Be-havior Research Methods, 48, 936–949. https://doi.org/10.3758/s13428-015-0619-7.
- Lu, H., Li, X., & Li, K. (2025). Adaptation and Validation of the Scale for Chinese Preschool Teachers’ Self-Efficacy (SCPTSE): Based on Classi-cal Test Theory and Item Response Theory. Behavioral Sciences, 15(6), 741. https://doi.org/10.3390/bs15060741.
- Lee, J., &Paek, I. (2014). “In Search of the Optimal Number of Response Categories in a Rating Scale.” Journal of Psychoeducational Assessment, 32(7), pp. 663-673.https://doi.org/10.1177/0734282914522200.
- Lozano, L. M., García-Cueto, E., &Muñiz, J. (2008). “Effect of the Number of Response Categories on the Reliability and Validity of Rating Scales.” Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 4(2), pp. 73-79.https://doi.org/10.1027/1614-2241.4.2.73.
- McWhirter, E. H., Rasheed, S. & Crothers, M. (2000). The effects of high school career education on social-cognitive variables. Journal of Counsel-ing Psychology, 47, 330-341. https://doi.org/10.1037/0022-0167.47.3.330.
- Metheny, J. &McWhirter, E. H. (2013). Contributions of social status and family support to college students’ career decision self-efficacy and out-come expectations. Journal of Career Assessment, 21, 378–394. https://doi.org/10.1177/1069072712475164.
- Stella, M. (2022). Network psychometrics and cognitive network science open new ways for understanding math anxiety as a complex system, Journal of Complex Networks, 10(3), cnac012, https://doi.org/10.1093/comnet/cnac012.
- Mariano, L.T., Phillips, A., Estes, K., & Kilburn, M.R. (2024a). Should survey likert scales include neutral response categories: Evidence from a randomized school climate survey, Working Paper, RAND Corporation.
- Mariano, L.T., Phillips, A., Estes, K., & Kilburn, M.R. (2024b). Examining the inclusion of neutral response categories using an item response theo-ry approach: Analysis of a randomized survey of teachers, Working Paper, RAND Corporation.
- Negru-Subtirica, O., & Pop, E. I. (2017). Reciprocal Associations between Educational Identity and Vocational Identity in Adolescence: A Three-wave Longitudinal Investigation. Journal of Youth and Adolescence, 47(4), 703–716. https://doi.org/10.1007/s10964-017-0789-y.
- Negru-Subtirica, O., Pop, E. I., &Crocetti, E. (2017). Good omens? The intricate relations between educational and vocational identity in adoles-cence. European Journal of Developmental Psychology, 15(1), 83–98. https://doi.org/10.1080/17405629.2017.1313160.
- Niles, S. G. & Harris-Bowlsby, J. (2016). Career development interventions (5th ed.). Boston, MA: Pearson.
- Preston, C. C., & Colman, A. M. (2000). “Optimal number of response categories in rating scales: reliability, validity, discriminating power, and re-spondent preferences.” ActaPsychologica, 104(1), pp. 1-15. https://doi.org/10.1016/S0001-6918(99)00050-5.
- Qian, M., Wang, X., & Dai, S. (2025). Psychometric Network Analysis and Dimensionality Assessment: A Software Review. Education Sciences, 15(5), 555. https://doi.org/10.3390/educsci15050555.
- Rentfrow, P. J., Jokela, M., Lamb, M. E. (2015) Regional personality differences in Great Britain. PLoS One, 10: e0122245.https://doi.org/10.1371/journal.pone.0122245.
- RStudio Team (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/.
- Ramos-Vera, C., Rosa Franco, V., Vallejos Saldarriaga, J., & Serpa Barrientos, A. (2023). Psychometric Networks and Their Implications for the Treatment and Diagnosis of Psychopathologies. IntechOpen. https://doi.org/10.5772/intechopen.105404.
- Sung, C., & Connor, A. (2017). Social-cognitive predictors of vocational outcomes in transition youth with epilepsy: Application of social cognitive career theory. Rehabilitation Psychology, 62(3), 276–289. https://doi.org/10.1037/rep0000161.
- Skorikov, V. B., &Vondracek, F. W. (2011). Occupational identity. In S. J. Schwartz, K. Luyckx, & V. L. Vignoles (Eds.), Handbook of identity theory and research (pp. 693–714). New York, NY: Springer.https://doi.org/10.1007/978-1-4419-7988-9_29.
- Simms, L. J., Zelazny, K., Williams, T. F., & Bernstein, L. (2019). “Does the Number of Response Options Matter? Psychometric Perspectives Us-ing Personality Questionnaire Data.” Psychological Assessment, 31(4), 557-566.https://doi.org/10.1037/pas0000648.
- Smith, T.W. (2010). Surveying across nations and cultures. In Handbook of Survey Research, 2nd ed.; Marsden, P.V., Wright, J.D., Eds.; Emerald Group: Bingley, UK, pp. 733–763.
- Tekin, M., Toraman, C. & Kosan, A.M.A. (2024). How many grades of response categories does the commitment to the profession of medicine scale provide the most information?International Journal of Assessment Tools in Education, 11(3), 524-536.https://doi.org/10.21449/ijate.1400157.
- Terwee, C.B., Bot, S.D., de Boer, M.R., van der Windt, D.A., Knol, D.L., Dekker, J., Bouter, L.M., de Vet, H.C. (2007). Quality criteria were pro-posed for measurement properties of health status questionnaires. Journal of Clinical Epidemiology.60(1):34-42. Epub 2006 Aug 24. PMID: 17161752.https://doi.org/10.1016/j.jclinepi.2006.03.012.
- Vela, J. C., Karaman, M. A., Smith, W. D. & Hinojosa, Y. (2018). An examination of the structure of the vocational outcome expectations scale with latina/o students. UluslararasıTürkçeEdebiyatKültürEğitimDergisi, 7(4), 2733-2746.https://doi.org/10.7884/teke.4272.
- Weng, L. J. (2004). “Impact of the Number of Response Categories and Anchor Labels on Coefficient Alpha and Test-retest Reliability.” Educa-tional and Psychological Measurement, 64(6), pp. 956-972. https://doi.org/10.1177/0013164404268674.
- Xia, Y., & Yang, Y. (2018). The Influence of Number of Categories and Threshold Values on Fit Indices in Structural Equation Modeling with Ordered Categorical Data, Multivariate Behavioral Research, 53:5, 731-755, https://doi.org/10.1080/00273171.2018.1480346.
- Xia, Y., & Yang, Y. (2019). RMSEA, CFI, and TLI in structural equation modeling with ordered categorical data: The story they tell depends on the estimation methods. Behavior Research Methods, 51(1), 409–428. https://doi.org/10.3758/s13428-018-1055-2.
- Yeh, C. J. &Borrero, N. E. (2012). Evaluation of a health careers program for Asian American and Pacific Islander high school students. Journal of Multicultural Counseling and Development, 40, 227-239.https://doi.org/10.1002/j.2161-1912.2012.00020.x.
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How to Cite
Murasing, P. K., Chakraborty , D. R. ., & Raji , D. N. S. . (2025). Revisiting The Vocational Outcome Expectations Scale: A Network Psychometric Validation of The Revised Five-Point Likert Version. International Journal of Basic and Applied Sciences, 14(6), 303-312. https://doi.org/10.14419/nbbc9625
