Skip to main content
Log in

Gated Screening Frameworks for Academic Concerns: the Influence of Redundant Information on Diagnostic Accuracy Outcomes

  • Published:
Contemporary School Psychology Aims and scope Submit manuscript

Abstract

Recent research suggests using multiple screening measures to identify students at risk for academic difficulties may decrease the number of students incorrectly identified as such. Gated frameworks in which students that score below a cut-score on an initial measure are assessed with a follow-up measure have been recommended. Researchers have posited that gated screening practices that use measures that explain unique variance in the outcome of interest will yield optimal results. We assessed the degree to which the correlation between screening measures and an outcome, the correlation among screening measures, and cut-score thresholds influenced diagnostic accuracy outcomes. Screening measures that were highly correlated with one another were less effective at reducing false positive classifications than screeners that were less correlated. Further, using screeners that were highly correlated with one another yielded slight but statistically significant reductions in false positive rates compared to using results from a single screening measure.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  • Balu, R., Zhu, P., Doolittle, F., Schiller, E., Jenkins, J., & Gersten, R. (2015). Evaluation of response to intervention practices for elementary school reading. (NCEE 2016–4000). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education.

  • Catts, H. W., Petscher, Y., Schatschneider, C., Sittner Bridges, M., & Mednoza, K. (2009). Floor effects associated with universal screening and their impact on the early identification of reading disabilities. Journal of Learning Disabilities, 42, 163–176. https://doi.org/10.1177/0022219408326219.

    Article  PubMed  Google Scholar 

  • Center on Response to Intervention (2016). Screening tools chart. http://www.rti4success.org/sites/default/files/Screening_Tools_Chart_2014_v2.pdf

  • Clemens, N. H., Keller-Magulis, M. A., Scholten, T., & Yoon, M. (2016). Screening assessment within a multi-tiered system of support: current practices, advances, and next steps. In S. Jimerson, M. Burns, & A. VanDerHeyden (Eds.), Handbook of response to intervention (2nd ed., pp. 187–212). New York: Routledge.

    Chapter  Google Scholar 

  • Compton, D. L., Fuchs, D., Fuchs, L. S., Bouton, B., Gilbert, J. K., Barquero, L. A., Cho, E., & Crouch, R. C. (2010). Selecting at-risk first-grade readers for early intervention: eliminating false positive and exploring the promise of a two-stage gated screening process. Journal of Educational Psychology, 102, 327–340. https://doi.org/10.1037/a0018448.

    Article  PubMed  PubMed Central  Google Scholar 

  • Compton, D. L., Fuchs, D., Fuchs, L. S., & Bryant, J. D. (2006). Selecting at-risk readers in first grade for early intervention: a two year longitudinal study of decision rules and procedures. Journal of Educational Psychology, 98, 394–409. https://doi.org/10.1037/0022-0663.98.2.394.

    Article  Google Scholar 

  • Deno, S. L. (2005). Problem-solving assessment within curriculum-based measurement (cbm). In Rachel Chidsey-Brown (Ed.) Problem-solving based assessment for educational intervention. Guilford Press: New York.

  • Elliott, S. N., Huai, N., & Roach, A. T. (2007). Universal and early screening for educational difficulties: current and future approaches. Journal of School Psychology, 45, 137–161. https://doi.org/10.1016/j.jsp.2006.11.002.

    Article  Google Scholar 

  • Genz, A., Bretz, F., Miwa, T., Mi, X., Leisch, F., & Scheipl, F. (2017). mvtnorm: multivariate and t distributions. R package version 1.0–6. http://CRAN.R-project.org/package=mvtnorm.

  • Gilbert, J. K., Compton, D. L., Fuchs, D., & Fuchs, L. S. (2012). Early screening for risk of reading disabilities: recommendations for a four step system. Assessment for Effective Intervention, 38, 6–14. https://doi.org/10.1177/1534508412451491.

    Article  PubMed  PubMed Central  Google Scholar 

  • Glover, T. A., & Albers, C. A. (2007). Considerations for evaluating universal screening assessments. Journal of School Psychology, 45, 117–135. https://doi.org/10.1016/j.jsp.2006.05.005.

    Article  Google Scholar 

  • Fuchs, D., Compton, D. L., Fuchs, L. S., & Caffrey, E. (2011). The construct and predictive validity of a dynamic assessment of young children learning to read: implications for rti frameworks. Journal of Learning Disabilities, 44, 339–347. https://doi.org/10.1177/0022219411407864.

    Article  PubMed  PubMed Central  Google Scholar 

  • Fuchs, D., Fuchs, L. S., & Compton, D. L. (2012). Smart rti: a next-generation approach to multilevel prevention. Exceptional Children, 78, 263–279.

    PubMed  PubMed Central  Google Scholar 

  • Hintze, J. M., & Silberglitt, B. (2005). A longitudinal examination of the diagnostic accuracy and predictive validity of r-cbm and high stakes testing. School Psychology Review, 34, 372–386.

    Google Scholar 

  • Hughes, C. A., & Dexter, D. D. (2011). Response to intervention: a research-based summary. Theory Into Practice, 50, 4–11. https://doi.org/10.1080/00405841.2011.534909.

    Article  Google Scholar 

  • Jenkins, J. R., Hudson, R. F., & Johnson, E. S. (2007). Screening for at-risk readers in a response to intervention framework. School Psychology Review, 36, 582–600.

    Google Scholar 

  • Jenkins, J. R., Schiller, E., Blackorby, J., Thayer, S. K., & Tilly, W. D. (2013). Responsiveness to intervention in reading: architecture and practices. Learning Disability Quarterly, 36, 36–46. https://doi.org/10.1177/0731948712464963.

    Article  Google Scholar 

  • Leblanc, M., Dufore, E., & McDougal, J. (2012). Using general outcome measures to predict student performance on state-mandated assessments: an applied approach for establishing predictive cutscores. Journal of Applied School Psychology, 28, 1–13. https://doi.org/10.1080/15377903.2012.643753.

    Article  Google Scholar 

  • Mellard, D. F., McKnight, M., & Woods, K. (2009). Response to intervention screening and progress monitoring practices in 41 local schools. Learning Disabilities Research & Practice, 24, 186–195. https://doi.org/10.1111/j.1540-5826.2009.00292.x.

    Article  Google Scholar 

  • Nelson, P. M., Van Norman, E. R., & Lackner, S. K. (2016). A comparison of methods to screen students for reading and math difficulties. School Psychology Review, 45, 327–342 doi: 17105/SPR45-3.327-342.

    Article  Google Scholar 

  • R Core Team (2016). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

  • Torgesen, J. K. (2000). Individual differences in response to early intervention in reading: the lingering problem of treatment resisters. Learning Disabilities Research and Practice, 15, 55–64.

    Article  Google Scholar 

  • VanDerHeyden, A. M. (2013). Universal screening may not be for everyone: using a threshold model as a smarter way to determine risk. School Psychology Review, 42, 402–414.

    Google Scholar 

  • VanDerHeyden, A. M., Codding, R. S., & Martin, R. (2017). Relative value of common screening measures. School Psychology Review, 46, 65–87. https://doi.org/10.17105/SPR46-1.65-87.

    Article  Google Scholar 

  • Van Norman, E. R., Nelson, P. M., & Klingbeil, D. A. (2016). Single measure and gated screening approaches for identifying students at-risk for academic problems: implications for sensitivity and specificity. School Psychology Quarterly, 32, 405–413. https://doi.org/10.1037/spq0000177.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ethan R. Van Norman.

Ethics declarations

The article does not contain any studies with human participants performed by any of the authors.

Conflict of Interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Van Norman, E.R., Nelson, P.M., Klingbeil, D.A. et al. Gated Screening Frameworks for Academic Concerns: the Influence of Redundant Information on Diagnostic Accuracy Outcomes. Contemp School Psychol 23, 152–162 (2019). https://doi.org/10.1007/s40688-018-0183-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40688-018-0183-0

Keywords

Navigation