Psychometric analysis of the behavioral assessment screening tool (BAST) in adults with stroke

Candice Osborne, Alex Wong, Willa Vo, Shannon Juengst

Research output: Contribution to journalArticlepeer-review


Purpose: The purpose of this study was to examine the initial psychometric properties of the Behavioral Assessment Screening Tool (BAST), a self-reported measure of neurobehavioral symptoms, in adults with stroke. Methods: We assessed subscale and item-level reliabilities of the five BAST subscales in 75 community-dwelling adults with stroke. We further assessed the known-groups validity of the BAST to differentiate individuals with and without self-reported lifetime stroke history (n = 47 with stroke and n = 1843 neurologically healthy controls). Results: Cronbach’s alpha coefficients of all subscales were >0.7, demonstrating acceptable to good internal consistency reliabilities, and corrected item-total correlations were all >.30 demonstrating good item-level reliabilities. ROC curves demonstrated strong known-groups validity of the negative affect, executive function, and fatigue subscales for classifying stroke versus healthy controls (AUC = .669-.758, p < .001). Conclusion: The BAST demonstrates good initial psychometric properties as a screening tool to identify neurobehavioral symptoms in community-dwelling adults with stroke. Future work will add stroke-specific items, further assess the validity of the BAST, and employ item response theory or Rasch analyses to identify highly discriminative items for potential smart device-based ecological momentary assessments.

Original languageEnglish
Pages (from-to)321-330
Number of pages10
JournalTopics in stroke rehabilitation
Issue number5
StatePublished - 2022


  • Stroke
  • measurement
  • neurobehavioral
  • psychometrics
  • validity


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