Background: The Token Test for Children (2nd edition) (TTFC) is a measure for assessing receptive language. In this study we describe the translation process, validity and reliability of the Arabic Token Test for Children (A-TTFC).
Aims: The aim of this study is to translate, validate and establish the reliability of the Arabic Token Test for Children (A-TTFC) for the purpose of assessing Arabic-speaking children with receptive language problems.
Methods & Procedures: The translation of the A-TTFC complied with the international translation procedures guidelines. After a multiple step translation process the A-TTFC was pilot tested and amended for any noted problems. The final version of the A-TTFC was administered to 397 typically developing Jordanian children, age range 3;0-12;11 (years; months). Children were purposefully sampled from randomly selected schools in Amman, Jordan. Another 35 bilingual children, age range 6;0-12;11, participated in the bilingual validation of the A-TTFC.
Results: Construct validity of the A-TTFC was tested using factor analysis. Factor analysis results indicated that loadings of the items on the A-TTFC were similar to the English version item loadings. Alpha-coefficients for each test section varied from 0.78 to 0.94. Intraclass correlation coefficient (ICC) scores from bilingual children supported bilingual validity of the test > 0.80. ICC between scores for repeated assessments varied from 0.76 to 0.90 supporting test-retest reliability.
Conclusions & Implications: The results support the appropriateness of using A-TTFC in assessing Arabic-speaking children with receptive language problems.
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http://dx.doi.org/10.1111/1460-6984.12198 | DOI Listing |
J Speech Lang Hear Res
January 2025
Department of Communication Science and Disorders, University of Pittsburgh, PA.
Purpose: The present study assessed the test-retest reliability of the American Sign Language (ASL) version of the Computerized Revised Token Test (CRTT-ASL) and compared the differences and similarities between ASL and English reading by Deaf and hearing users of ASL.
Method: Creation of the CRTT-ASL involved filming, editing, and validating CRTT instructions, sentence commands, and scoring. Deaf proficient (DP), hearing nonproficient (HNP), and hearing proficient sign language users completed the CRTT-ASL and the English self-paced, word-by-word reading CRTT (CRTT-Reading-Word Fade [CRTT-R-wf]).
Hear Res
January 2025
Institute of Sound and Vibration Research, University of Southampton, Southampton, United Kingdom.
The cortical tracking of the acoustic envelope is a phenomenon where the brain's electrical activity, as recorded by electroencephalography (EEG) signals, fluctuates in accordance with changes in stimulus intensity (the acoustic envelope of the stimulus). Understanding speech in a noisy background is a key challenge for people with hearing impairments. Speech stimuli are therefore more ecologically valid than clicks, tone pips, or speech tokens (e.
View Article and Find Full Text PDFPrehosp Emerg Care
January 2025
Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado.
Objectives: Abusive head trauma (AHT) is a leading cause of death in young children. Analyses of patient characteristics presenting to Emergency Medical Services (EMS) are often limited to structured data fields. Artificial Intelligence (AI) and Large Language Models (LLM) may identify rare presentations like AHT through factors not found in structured data.
View Article and Find Full Text PDFJAMIA Open
February 2025
Department of Medicine, University of Wisconsin-Madison, Madison, WI 53792, United States.
Objective: To evaluate large language models (LLMs) for pre-test diagnostic probability estimation and compare their uncertainty estimation performance with a traditional machine learning classifier.
Materials And Methods: We assessed 2 instruction-tuned LLMs, Mistral-7B-Instruct and Llama3-70B-chat-hf, on predicting binary outcomes for Sepsis, Arrhythmia, and Congestive Heart Failure (CHF) using electronic health record (EHR) data from 660 patients. Three uncertainty estimation methods-Verbalized Confidence, Token Logits, and LLM Embedding+XGB-were compared against an eXtreme Gradient Boosting (XGB) classifier trained on raw EHR data.
Curr Oncol
December 2024
Neurosurgery Unit, Head-Neck and NeuroSciences Department University Hospital of Udine, 33100 Udine, Italy.
Background: Tractography allows the in vivo study of subcortical white matter, and it is a potential tool for providing predictive indices on post-operative outcomes. We aim at establishing whether there is a relation between cognitive outcome and the status of the inferior fronto-occipital fasciculus's (IFOF's) microstructure.
Methods: The longitudinal neuropsychological data of thirty young (median age: 35 years) patients operated on for DLGG in the left temporo-insular cortex along with pre-surgery tractography data were processed.
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