Advertisement

Quantitative Research Synthesis: The Use of Meta-Analysis in Career Guidance and Vocational Psychology

  • Paul A. GoreJr.
  • Takuya Minami
Chapter

Since its inception at the turn of the 20th century, vocational psychology has thrived as a result of empirical research and theoretical advances. Early studies identifying the nature of educational and career interests (Strong, 1936) and their relation to abilities (Hartman & Dashiell, 1919), and career outcomes (DiMichael, 1949) are just a few examples of how early vocational psychologists applied research methods and measurement in an effort to promote effective career decision-making. Early theories of career counselling and development often guided these research efforts and were, in turn, informed and modified by empirical findings. In the last century, our discipline has amassed a considerable volume of research. Surprisingly, however, we continue to ask similar questions with respect to the nature of educational and vocational interests (Darcy & Tracey, 2007), and their relation to abilities (Tracey & Hopkins, 2001) and important academic and career outcomes (Tracey & Robbins, 2006). One of the biggest challenges faced by scientific disciplines is that of synthesising and summarising a large number of individual studies in such a way that researchers, theoreticians, and practitioners can draw meaningful conclusions. The statistical techniques of meta-analysis permit researchers to rise to this challenge and it is this topic that will be the focus of this chapter.

The goals of this chapter are twofold. First, this chapter will provide the reader with a fundamental understanding of the family of statistical analyses collectively referred to as meta-analysis. This will include an overview of the procedure, and a brief review of the steps involved in conducting a meta-analysis. Discussion of this topic will be conceptual rather than mathematical. As such, this chapter is not a comprehensive review of current issues in meta-analyses nor will it provide sufficient procedural guidance for the reader to actually conduct an analysis. Those wishing a more comprehensive coverage of current conceptual and procedural issues should refer to Hedges and Pigott (2004), Hunter and Schmidt (1990), Kline (2004), Lipsey and Wilson (2001), and Quintana and Minami (2006).

Keywords

Effect Size Estimate Counseling Psychology Career Guidance Career Interest Critical Ingredient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Brown, S. D., Ryan Krane, N. E., Brecheisen, J., Castelino, P., Budisin, I., Miller, M., & Edens, L. (2003). Critical ingredients of career choice interventions: More analyses and new hypotheses. Journal of Vocational Behavior, 62, 411–428.CrossRefGoogle Scholar
  2. Brown, S. D., & Ryan Krane, N. E. (2000). Four (or five) sessions and a cloud of dust: Old assumptions and new observations about career counseling. In S. D. Brown & Ro. W. Lent (Eds.), Handbook of counseling psychology (3rd ed., pp. 740–766). New York: Wiley.Google Scholar
  3. Burnham, P. S. (1942). Stability of interests. School and Society, 55, 332–335.Google Scholar
  4. Carver, R. (1978). The case against statistical significance testing. Harvard Educational Review, 48, 378–399.Google Scholar
  5. Cheung, M. W. L., & Chan, W. (2005). Meta-analytic structural equation modeling: A two-stage approach. Psychological Methods, 10, 40–64.CrossRefGoogle Scholar
  6. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.Google Scholar
  7. Darcy, M. U. A., & Tracey, T. J. G. (2007). Circumplex structure of Holland’s RIASEC interests across gender and time. Journal of Counseling Psychology, 54, 17–31.CrossRefGoogle Scholar
  8. DiMichael, S. G. (1949). Work satisfaction and work efficiency of vocational counselors as related to measured interests. Journal of Applied Psychology, 33, 319–329.CrossRefGoogle Scholar
  9. Eysenck, H. J. (1952). The effects of psychotherapy: An evaluation. Journal of Consulting and Clinical Psychology, 16, 319–324.Google Scholar
  10. Friedman, H. (1968). Magnitude of experimental effect and a table for its rapid estimation. Psychological Bulletin, 70, 245–251.CrossRefGoogle Scholar
  11. Greenland, S. (1994). A critical look at some popular meta-analytic methods. American Journal of Epidemiology, 140, 290–296.Google Scholar
  12. Hartman, R., & Dashiell, J. F. (1919). An experiment to determine the relation of interest to abilities. Psychological Bulletin, 16, 259–262.CrossRefGoogle Scholar
  13. Hedges, L. V. (1994). Statistical considerations. In H. Cooper & L. V. Hedges (Eds.), The handbook of research synthesis (pp. 29–38). New York: Russell Sage Foundation.Google Scholar
  14. Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. San Diego, CA: Academic Press.Google Scholar
  15. Hedges, L. V., & Pigott, T. D. (2004). The power of statistical tests for moderators in meta. Psychological Methods, 9, 426–445.CrossRefGoogle Scholar
  16. Hunter, J. E., & Schmidt, F. L. (1990). Methods of meta-analysis: Correcting error and bias in research findings. Thousand Oaks, CA: Sage.Google Scholar
  17. Hunter, J. E., Schmidt, F. L., & Jackson, G. (1982). Meta-analysis: Cumulating research findings across studies. Beverly Hills, CA: Sage.Google Scholar
  18. Kline, R. E. (2004). Beyond significance testing: Reforming data analysis methods in behavioral research. Washington, DC: American Psychological Association.CrossRefGoogle Scholar
  19. Le, H., Casillas, A., Robbins, S. B., & Langley, R. (2004). Motivational and skills, social, and self-management predictors of college outcomes. Constructing the Student Readiness Inventory. Educational and Psychological Measurement, 65, 482–508.CrossRefGoogle Scholar
  20. Lipsey, M. W., & Wilson, D. B. (2001) Practical meta-analysis. Thousand Oaks, CA: Sage.Google Scholar
  21. Low, K. S. D., Yoon, M., Roberts, B. W., & Rounds, J. (2005). The stability of vocational interests from early adolescence to middle adulthood: A quantitative review of longitudinal studies. Psychological Bulletin, 131, 713–737.CrossRefGoogle Scholar
  22. Lubinski, D., & Dawis, R. V. (1995). Assessing individual difference in human behavior: New methods, concepts, and findings. Palo Alto, CA: Davies-Black.Google Scholar
  23. McDaniel, M. A., Whetzel, D. L., Schmidt, F. L., & Maurer, S. D. (1994). The validity of employment interviews: A comprehensive review and meta-analysis. Journal of Applied Psychology, 79, 599–616.CrossRefGoogle Scholar
  24. Oliver, L. W., & Spokane, A. R. (1988). Career intervention outcome: What contributes to client gain? Journal of Counseling Psychology, 35, 447–462.CrossRefGoogle Scholar
  25. Quintana, S. M., & Minami, T. (2006). Guidelines for meta-analysis of counseling psychology research. Counseling Psychologist, 34, 839–877.CrossRefGoogle Scholar
  26. Raudenbush, S. W. (1994). Random effects models. In H. Cooper & L. V. Hedges (Eds.), The handbook of research synthesis (pp. 301–321). New York: Russell Sage Foundation.Google Scholar
  27. Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130, 261–288.CrossRefGoogle Scholar
  28. Rosenthal, R. (1984). Meta-analytic procedures for social research. Beverly Hills, CA: Sage.Google Scholar
  29. Rottinghaus, P. J., Coon, K. L., Gaffey, A. R., & Zytowski, D. G. (2007). Thirty-year stability and predictive validity of vocational interests. Journal of Career Assessment, 15, 5–22.CrossRefGoogle Scholar
  30. Ryan, N. E. (1999). Career counseling and career choice goal attainment: A meta-analytically derived model for career counseling practice. Unpublished doctoral dissertation. Loyola University, Chicago, IL.Google Scholar
  31. Shadish, W. R., & Haddock, C. K. (1994). Combining estimates of effect size. In H. Cooper & L. V. Hedges (Eds.), The handbook of research synthesis (pp. 261–281). New York: Russell Sage Foundation.Google Scholar
  32. Sharpe, D. (1997). Of apples and oranges, file drawers and garbage: Why validity issues in meta-analysis will not go away. Clinical Psychology Review, 17, 881–901.CrossRefGoogle Scholar
  33. Smith, M. L., & Glass, G. V. (1977). Meta-analysis of psychotherapy outcome studies. American Psychologist, 32, 752–760.CrossRefGoogle Scholar
  34. Smith, M. L., Glass, G. V., & Miller, T. I. (1980). The benefits of psychotherapy. Baltimore, MD: Johns Hopkins University Press.Google Scholar
  35. Spokane, A. R., & Oliver, L. W. (1983). The outcomes of vocational interventions: In W. B. Walsh & S. H. Osipow (Eds.), Handbook of vocational psychology (pp. 99–116). Hillsdale, NJ: Erlbaum.Google Scholar
  36. Strong, E. K., Jr. (1936). Interests of men and women. Journal of Social Psychology, 29, 409–414.Google Scholar
  37. Tracey, T. J. G. (2000). Issues in the analysis and interpretation of quantitative data: Deinstitutionalization of the null hypothesis test. In S. D. Brown & R. W. Lent (Eds.), Handbook of counseling psychology (3rd ed., pp. 177–198). New York: Wiley.Google Scholar
  38. Tracey, T. J. G., & Hopkins, N. (2001). Correspondence of interests and abilities with occupational choice. Journal of Counseling Psychology, 48, 178–189.CrossRefGoogle Scholar
  39. Tracey, T. J. G., & Robbins, S. B. (2006). The interest-major congruence and college success relation: A longitudinal study. Journal of Vocational Behavior, 69, 64–89.CrossRefGoogle Scholar
  40. Ulrich, L., & Trumbo, D. (1965). The selection interview since 1949. Psychological Bulletin, 63, 100–116.CrossRefGoogle Scholar
  41. Van Dusen, A. C. (1940). Permanence of vocational interests. Journal of Educational Psychology, 6, 401–423.CrossRefGoogle Scholar
  42. Viswesvaran, C., & Ones, D. S. (1995). Theory testing: Combining psychometric meta-analysis and structural equations modeling. Personnel Psychology, 48, 865–885.CrossRefGoogle Scholar
  43. Whiston, S. C., Sexton, T. L., & Lasoff, D. L. (1998). Career-intervention outcome: A replication and extension of Oliver & Spokane (1988). Journal of Counseling Psychology, 45, 150–165.CrossRefGoogle Scholar
  44. Wilkinson, L., & Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 594–604.CrossRefGoogle Scholar
  45. Wiesner, W. H., & Cronshaw, S. F. (1988). The moderating impact of interview forma and degree of structure on the validity of the employment interview. Journal of Occupational Psychology, 61, 275–290.Google Scholar

Copyright information

© Springer Science + Business Media B.V 2008

Authors and Affiliations

  • Paul A. GoreJr.
    • 1
  • Takuya Minami
    • 1
  1. 1.University of UtahUSA

Personalised recommendations