Purpose: The aim of the present study was to compare scale and conditional reliability derived from item response theory analyses among the most commonly used, as well as several newly developed, observation, interview, and parent-report autism instruments.
Methods: When available, data sets were combined to facilitate large sample evaluation. Scale reliability (internal consistency, average corrected item-total correlations, and model reliability) and conditional reliability estimates were computed for total scores and for measure subscales.
Results: Generally good to excellent scale reliability was observed for total scores for all measures, scale reliability was weaker for RRB subscales of the ADOS and ADI-R, reflecting the relatively small number of items for these measures. For diagnostic measures, conditional reliability tended to be very good (> 0.80) in the regions of the latent trait where ASD and non-ASD developmental disability cases would be differentiated. For parent-report scales, conditional reliability of total scores tended to be excellent (> 0.90) across very wide ranges of autism symptom levels, with a few notable exceptions.
Conclusions: These findings support the use of all of the clinical observation, interview, and parent-report autism symptom measures examined, but also suggest specific limitations that warrant consideration when choosing measures for specific clinical or research applications.
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http://dx.doi.org/10.1007/s10803-023-05967-y | DOI Listing |
Med Image Anal
December 2024
University Lyon, INSA Lyon, CNRS, Inserm, CREATIS UMR5220, U1206, Lyon 69621, France.
Deep learning methods have been widely used for various glioma predictions. However, they are usually task-specific, segmentation-dependent and lack of interpretable biomarkers. How to accurately predict the glioma histological grade and molecular subtypes at the same time and provide reliable imaging biomarkers is still challenging.
View Article and Find Full Text PDFACS ES T Water
November 2024
Waterborne Disease Prevention Branch, Centers for Disease Control and Prevention, Atlanta, Georgia 30333, United States.
Irrigating fresh produce with contaminated water contributes to the burden of foodborne illness. Identifying fecal contamination of irrigation waters and characterizing fecal sources and associated environmental factors can help inform fresh produce safety and health hazard management. Using two previously collected data sets, we developed and evaluated the performance of logistic regression and conditional random forest models for predicting general and human-specific fecal contamination of ponds in southwest Georgia used for fresh produce irrigation.
View Article and Find Full Text PDFVet Sci
December 2024
Clinic of Reproductive Medicine, Department for Farm Animals, Vetsuisse Faculty, University of Zurich, Winterthurerstrasse 260, CH-8057 Zurich, Switzerland.
Sperm viability is routinely assessed for the quality control of cryopreserved bovine sperm batches but is not usually conclusive regarding their fertilizing potential. In this study, we investigated the fertility predictive value of bull sperm viability in combination with DNA integrity or the functional status of viable sperm. In addition to sperm viability, we flow cytometrically assessed the percentage of sperm with high DNA fragmentation index (%DFI) and the fraction of viable sperm with low intracellular Ca content and functional mitochondria using the Sperm Chromatin Structure Assay and a five-color staining panel in 791 and 733 cryopreserved batches with non-return rate (NRR) records after ≥100 first services, respectively.
View Article and Find Full Text PDFThe corticospinal tract (CST) facilitates skilled, precise movements, which necessitates that subcerebral projection neurons (SCPN) establish segmentally specific connectivity with brainstem and spinal circuits. Developmental molecular delineation enables prospective identification of corticospinal neurons (CSN) projecting to thoraco-lumbar spinal segments; however, it remains unclear whether other SCPN subpopulations in developing sensorimotor cortex can be prospectively identified in this manner. Such molecular tools could enable investigations of SCPN circuitry with precision and specificity.
View Article and Find Full Text PDFDev Med Child Neurol
December 2024
Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Aim: To replicate and extend previous psychometric findings for the Autism Symptom Dimensions Questionnaire (ASDQ).
Method: Using a cross-sectional design in two samples, including a total of 3366 children and adolescents (aged 2-17 years; 1399 with autism spectrum disorder) and a small case series, factor structure, measurement invariance, reliability, construct validity, screening and diagnostic efficiency, and detection of reliable change were examined for the ASDQ.
Results: Strong psychometric properties were observed, including replicable factor structure, strong measurement invariance, adequate-to-excellent scale and conditional reliability, strong convergent and discriminant validity, and good screening efficiency.
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