Skip to main content

Rasch Analysis of the Behavioral Assessment Screening Tool (BAST) in Chronic Traumatic Brain Injury


The Behavioral Assessment Screening Tool (BAST) measures neurobehavioral symptoms in adults with traumatic brain injury (TBI). Exploratory Factor Analyses established five subscales: Negative Affect, Fatigue, Executive Function, Impulsivity, and Substance Abuse. In the current study, we assessed all the subscales except Substance Abuse using Rasch analysis following the Rasch Reporting Guidelines in Rehabilitation Research (RULER) framework. RULER identifies unidimensionality and fit statistics, item hierarchies, targeting, and symptom severity strata as areas of interest for Rasch analysis. The BAST displayed good unidimensionality with only one item from the Impulsivity scale exhibiting potential item misfit (MnSQ 1.40). However, removing this item resulted in a lower average domain measure (1.42 to − 1.49) and higher standard error (0.34 to 0.43) so the item was retained. Items for each of the four subscales also ranged in difficulty (i.e. endorsement of symptom frequency) with more severe symptoms being endorsed in the Fatigue subscale and more mild symptoms being endorsed in the Impulsivity subscale. Though Negative Affect and Executive Function displayed appropriate targeting, the Fatigue and Impulsivity Subscales had larger average domain values (1.35 and − 1.42) meaning that more items may need to be added to these subscales to capture differences across a wider range of symptom severity. The BAST displayed excellent reliability via item and person separation indices and distinct strata for each of the four subscales. Future work should use Rasch analysis in a larger, more representative sample, include more items for the Fatigue and Impulsivity subscale, and include the Substance Abuse subscale.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Data Availability

The dataset generated for this study will not be made publicly available. The corresponding author can provide the dataset upon request and execution of the necessary data use agreements.


  1. 1.

    Alderman N, Dawson K, Rutterford NA, Reynolds PJ. A comparison of the validity of self-report measures amongst people with acquired brain injury: a preliminary study of the usefulness of EuroQol-5D. Neuropsychol Rehabil. 2001;11(5):529–37.

    Article  Google Scholar 

  2. 2.

    Applying the Rasch Model: Fundamental Measurement in the Human Sciences, Third Edition. (n.d.). CRC Press. Accessed 8 July 2020.

  3. 3.

    Bailie J, Babakhanyan I, Jolly M, Ekanayake V, Sargent P, Duckworth J, Ekanayke V, Ekanayake V. Traumatic Brain Injury-2Accuracy of self-reported questions for assessment of TBI history. Arch Clin Neuropsychol. 2017;32(6):656–66.

    Article  Google Scholar 

  4. 4.

    Briggs DC, Wilson M. An Introduction to Multidimensional Measurement using Rasch Models. 2003.

  5. 5.

    Corrigan JD, Bogner J. Initial reliability and validity of the Ohio State University TBI identification method. J Head Trauma Rehabilit. 2007;22(6):318–29.

    Article  Google Scholar 

  6. 6.

    Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.

    Article  Google Scholar 

  7. 7.

    Higashi R, Juengst SB. Patient-centered measure development and Spanish validation exemplar. Health Lit Res Pract. 2019;3(4):e243–9.

    PubMed  PubMed Central  Google Scholar 

  8. 8.

    Juengst SB, Nabasny A, Terhorst L. Neurobehavioral symptoms in community-dwelling adults with and without chronic traumatic brain injury: differences by age, gender, education, and health condition. Front Neurol. 2019.

    Article  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Juengst SB, Nabasny A, Terhorst L. Cohort differences in neurobehavioral symptoms in chronic mild to severe traumatic brain injury. Front Neurol. 2020.

    Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Juengst SB, Switzer G, Oh BM, Arenth PM, Wagner AK. Conceptual model and cluster analysis of behavioral symptoms in two cohorts of adults with traumatic brain injuries. J Clin Exp Neuropsychol. 2017;39(6):513–24.

    Article  PubMed  Google Scholar 

  11. 11.

    Juengst SB, Terhorst L, Dicianno BE, Niemeier JP, Wagner AK. Development and content validity of the behavioral assessment screening tool (BASTβ). Disabil Rehabil. 2018.

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Juengst SB, Terhorst L, Kew CL, Wagner AK. Variability in daily self-reported emotional symptoms and fatigue measured over eight weeks in community dwelling individuals with traumatic brain injury. Brain Inj. 2019.

    Article  PubMed  Google Scholar 

  13. 13.

    Juengst SB, Terhorst L, Nabasny A, Wallace T, Weaver JA, Osborne CL, Burns SP, Wright B, Wen P-S, Kew C-LN, Morris J. Use of mHealth technology for patient-reported outcomes in community-dwelling adults with acquired brain injuries: a scoping review. Int J Environ Res Public Health. 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Juengst SB, Terhorst L, Wagner AK. Factor structure of the Behavioral Assessment Screening Tool (BAST) in traumatic brain injury. Disabil Rehabil. 2018.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Juengst S, Conley M, Terhorst L. Convergent and divergent validity of the Behavioral Assessment Screening Tool (BAST) in traumatic brain injury. Arch Phys Med Rehabil. 2019;100(10):e59.

    Article  Google Scholar 

  16. 16.

    Juengst S, Terhorst L. Further psychometric development of the Behavioral Assessment Screening Tool (BAST). Arch Phys Med Rehabil. 2020;101(12):e140.

    Article  Google Scholar 

  17. 17.

    Lequerica AH, Lucca C, Chiaravalloti ND, Ward I, Corrigan JD. Feasibility and preliminary validation of an online version of the Ohio State University traumatic brain injury identification method. Arch Phys Med Rehabil. 2018;99(9):1811–7.

    Article  PubMed  Google Scholar 

  18. 18.

    Linacre JM. Investigating rating scale category utility. J Outcome Meas. 1999;3(2):103–22.

    PubMed  Google Scholar 

  19. 19.

    Linacre JM. Understanding Rasch measurement: estimation methods for Rasch measures. J Outcome Meas. 1999;3:382–405.

    PubMed  Google Scholar 

  20. 20.

    Linacre JM. Understanding Rasch measurement: optimizing rating scale category effectiveness. J Appl Meas. 2002;3(1):85–106.

    PubMed  Google Scholar 

  21. 21.

    Masters GN. A Rasch model for partial credit scoring. Psychometrika. 1982;47(2):149–74.

    Article  Google Scholar 

  22. 22.

    Menon DK, Schwab K, Wright DW, Maas AI. Position statement: definition of traumatic brain injury. Arch Phys Med Rehabilit. 2010;91(11):1637–40.

    Article  Google Scholar 

  23. 23.

    Osborne CL, Kauvar DS, Juengst SB. Linking the behavioral assessment screening tool to the international classification of functioning, disability, and health as a novel indicator of content validity. Disabil Rehabil. 2019.

    Article  PubMed  Google Scholar 

  24. 24.

    Rabinowitz AR, Chervoneva I, Hart T, O’Neil-Pirozzi TM, Bogner J, Dams-O’Connor K, Brown AW, Johnson-Greene D. Influence of prior and intercurrent brain injury on 5-year outcome trajectories after moderate to severe traumatic brain injury. J Head Trauma Rehabil. 2020;35(4):E342–51.

    Article  PubMed  Google Scholar 

  25. 25.

    Rasch Reporting Guidelines Task Force. (n.d.). ACRM. Accessed 9 Nov 2020.

  26. 26.

    Sample Size and Item Calibration or Person Measure Stability. (n.d.). Accessed 10 Jan 2021.

  27. 27.

    Silverstein B, Fisher WP, Kilgore KM, Harley JP, Harvey RF. Applying psychometric criteria to functional assessment in medical rehabilitation: II. Defining interval measures. Arch Phys Med Rehabilit. 1992;73(6):507–18.

    Article  Google Scholar 

  28. 28.

    Table 6.1 Person statistics in misfit order: Winsteps Help. (n.d.). Accessed 1 Apr 2021.

  29. 29.

    Terhorst L, Juengst SB, Beck KB, Shiffman S. People can change: measuring individual variability in rehabilitation science. Rehabilit Psychol. 2018;63(3):468–73.

    Article  Google Scholar 

  30. 30.

    Wright B, Masters G. Rating scale analysis. Measurement and Statistics. 1982.

Download references


This work was funded by the National Institutes for Health, Eunice Kennedy Shriver.

National Institute of Child Health and Human Development (NIH/NICHD). Grant No: R03HD09445 (PI: Juengst).  Funding for RedCap to support data collection came from CTSA NIH Grant UL1TR001105.

Author information



Corresponding author

Correspondence to Shannon Juengst.

Ethics declarations

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Ethical Approval

Approval was obtained from the Institutional Review Board (IRB) at UT Southwestern Medical Center and the study was performed in line with the principles of the Declaration of Helsinki.

Consent to Participate

Participants involved in this study consented to the research.

Consent for Publication

Participants involved in this study were made aware of and consented to publication.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Juengst, S., Grattan, E., Wright, B. et al. Rasch Analysis of the Behavioral Assessment Screening Tool (BAST) in Chronic Traumatic Brain Injury. J. Psychosoc. Rehabil. Ment. Health (2021).

Download citation


  • Traumatic brain injury
  • Psychometrics
  • Measurement
  • Behavior
  • Emotions