The Severity-Calibrated Aphasia Naming Test (Walker et al., 2022)
Creators: name: Walker, Grant M.
name: Fridriksson, Julius
name: E. Hillis, Argye
name: Ouden, Dirk B. den
name: Bonilha, Leonardo
name: Hickok, Gregory
Publisher: name: ASHA journals
Year: 2022
Subjects: Speech production
Neurology and neuromuscular diseases
Speech recognition

description: <strong>Purpose:</strong> We present a 20-item naming test, the Severity-Calibrated Aphasia Naming Test (SCANT), that can serve as a proxy measure for an aphasia severity scale that is derived from a thorough test battery of connected speech production, single-word production, speech repetition, and auditory verbal comprehension. <strong>Method: </strong>We use lasso regression and cross-validation to identify an optimal subset from a set of 174 pictures to be named for prediction of aphasia severity, based on data from 200 participants with left-hemisphere stroke who were quasirandomly selected to represent the full impairment scale. Data from 20 healthy controls (i.e., participant caretakers/spouses) were also analyzed. We examine interrater reliability, test–retest reliability, sensitivity and specificity to the presence of aphasia, sensitivity to therapy gains, and external validity (i.e., correlation with aphasia severity measures) for the SCANT. <strong>Results: </strong>The SCANT has extremely high interrater reliability, and it is sensitive and specific to the presence of aphasia. We demonstrate the superiority of predictions based on the SCANT over those based on the full set of naming items. We estimate a 15% reduction in power when using the SCANT score versus the full test battery’s aphasia severity score as an outcome measure; for example, to maintain the same power to detect a significant group average change in aphasia severity, a study with 25 participants using the full test battery to measure treatment effectiveness would require 30 participants if the SCANT were to be used as the testing instrument instead. <strong>Conclusion:</strong> We provide a linear model to convert SCANT scores to aphasia severity scores, and we identify a change score cutoff of four SCANT items to obtain a high degree of confidence based on test–retest SCANT data and the modeled relation between SCANT and aphasia severity scores. <strong>Supplemental Material S1.</strong> A MATLAB matrix file (360 rows × 174 columns) containing accuracy values for each participant (row) on each item of the Philadelphia Naming Test (column). The item "Eskimo" is excluded, and the items are sorted alphabetically. <strong>Supplemental Material S2.</strong> A MATLAB matrix file (360 rows × 1 column) containing Western Aphasia Battery Aphasia Quotient values for each participant. <strong>Supplemental Material S3.</strong> A MATLAB script file containing code for nested cross-validation and item selection, as well as plotting the prediction accuracy curves as a function of naming item set size. Walker, G. M., Fridriksson, J., Hillis, A. E., den Ouden, D. B., Bonilha, L., &amp; Hickok, G. (2022). The Severity-Calibrated Aphasia Naming Test. <em>American Journal of Speech-Language Pathology</em>. Advance online publication. https://doi.org/10.1044/2022_AJSLP-22-00071