Reducing the Number of Test Items of the Action Research Arm Test Poststroke: A Decision Tree Analysis ✰ .

Objective: The present study aimed to create a shorter version of the Action Research Arm Test (ARAT) without compromising its measurement properties.
Design: Secondary analysis of stroke recovery cohorts that used the ARAT to measure upper limb impairment.
Setting: Rehabilitation centers.
Participants: Patients with stroke from 5 different stroke recovery cohorts (N=1425).
Interventions: Not applicable.
Main Outcome Measures: A decision tree version of the ARAT (ARAT-DT) was developed using chi-square automated interaction detection. In an independent validation subset, criterion validity, agreement of ARAT-DT with original ARAT scores and score categories, and construct validity with the Fugl-Meyer Upper Extremity Scale score were determined.
Results: In total, 3738 ARAT measurements were available involving 1425 subjects. Chi-square automated interaction detection analysis in the development subset (n=2803) revealed an optimized decision tree with a maximum of 4 consecutive items. In the validation data set (n=935), the ARAT-DT differed by a mean of 0.19 points (0.3% of the total scale) from the original ARAT scores (limits of agreement=-5.67 to 6.05). The ARAT-DT demonstrated excellent criterion validity with the original ARAT scores (intraclass correlation coefficient=0.99 and ρ=0.99) and scoring categories (κ _w =0.97). The ARAT-DT showed very good construct validity with the Fugl-Meyer Upper Extremity Scale (ρ=0.92).
Conclusion: A decision tree version of the ARAT was developed, reducing the maximum number of items necessary for ARAT administration from 19 to 4. The scores produced by the decision tree had excellent criterion validity with original ARAT scores.
Competing Interests: Declaration of Competing Interest None.
(Copyright © 2022 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.)