Objective The purpose of this study was to construct a computerized adaptive test (CAT) for measuring self-care performance (the CAT-SC) in children with developmental disabilities (DD) aged from 6 months to 12 years in a content-inclusive, precise, and efficient fashion. Methods The study was divided into 3 phases: (1) item bank development, (2) item testing, and (3) a simulation study to determine the stopping rules for the administration of the CAT-SC. A total of 215 caregivers of children with DD were interviewed with the 73-item CAT-SC item bank. An item response theory model was adopted for examining the construct validity to estimate item parameters after investigation of the unidimensionality, equality of slope parameters, item fitness, and differential item functioning (DIF). In the last phase, the reliability and concurrent validity of the CAT-SC were evaluated. Results The final CAT-SC item bank contained 56 items. The stopping rules suggested were (a) reliability coefficient greater than 0.9 or (b) 14 items administered. The results of simulation also showed that 85% of the estimated self-care performance scores would reach a reliability higher than 0.9 with a mean test length of 8.5 items, and the mean reliability for the rest was 0.86. Administering the CAT-SC could reduce the number of items administered by 75% to 84%. In addition, self-care performances estimated by the CAT-SC and the full item bank were very similar to each other (Pearson r = 0.98). Conclusion The newly developed CAT-SC can efficiently measure self-care performance in children with DD whose performances are comparable to those of TD children aged from 6 months to 12 years as precisely as the whole item bank. The item bank of the CAT-SC has good reliability and a unidimensional self-care construct, and the CAT can estimate self-care performance with less than 25% of the items in the item bank. Therefore, the CAT-SC could be useful for measuring self-care performance in children with DD in clinical and research settings.
All Science Journal Classification (ASJC) codes
- Biochemistry, Genetics and Molecular Biology(all)
- Agricultural and Biological Sciences(all)