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Direct linkZafer Ozen; Nielsen Pereira; Tugce Karatas; Hernán Castillo-Hermosilla; Yukiko Maeda – Gifted Child Quarterly, 2025
Cognitive Abilities Test (CogAT) is one of the most frequently used gifted identification tools. In this meta-analytic study, we investigated empirical evidence of the validity of CogAT, in relation to different types of instruments. After reviewing 1,480 studies, a total of 24 with 33 effect sizes were included in the meta-analysis. According to…
Descriptors: Test Validity, Cognitive Tests, Disability Identification, Scores
Peer reviewedKunyi Lan; X. X. Wang; Yan'e Lu; Anyi Zhang; Meixiang Jia; Lin Lu; Y. B. Wei; J. J. Liu – Journal of Autism and Developmental Disorders, 2025
Purpose: To make early detection of individuals with autism spectrum disorder (ASD), caregiver-report instruments remain an efficient and adaptable option for the preliminary assessment. This study aimed to compare the psychometric properties of the Clancy Autism Behavior Scale (CABS) and Autism Behavior Checklist (ABC) as screening tools for ASD…
Descriptors: Foreign Countries, Autism Spectrum Disorders, Disability Identification, Psychometrics
Ziyi Zhang; Qingyao Zhu; Tianshu Gao; Kaiyan Gan; Fei Wang; Luyang Guan; Xiaoyan Ke – Journal of Autism and Developmental Disorders, 2025
The First Year Inventory (FYI) is a parent report screening measure, aimed at identifying the risk of autism spectrum disorder (ASD) in 12-month-old infants. This study aimed to investigate the utility of FYI within the Chinese community and develop a short version, encompassing both a low-risk sample and a high-risk sample comprising infants with…
Descriptors: Foreign Countries, Screening Tests, Autism Spectrum Disorders, Infants
Norton Kitanishi; Daniela Bordini; Marcos V. V. Ribeiro; Cristiane Silvestre Paula; Helena Brentani; Joana Portelese; Pamela J. Surkan; Silvia S. Martins; Jair de Jesus Mari; Paola Matiko Martins Okuda; Sheila C. Caetano – Autism: The International Journal of Research and Practice, 2025
Early identification of autism spectrum disorder through cost-effective screening is crucial in low- and middle-income countries. The Child Behavior Checklist 1.5-5, using the Autism Spectrum Problems and Withdrawn Syndrome subscales, has potential as a level 1 autism spectrum disorder screening tool, though its construct validity in low- and…
Descriptors: Autism Spectrum Disorders, Disability Identification, Screening Tests, Test Validity
Elizabeth Choi-Tucci; John Sideris; Cristin Holland; Grace T. Baranek; Linda R. Watson – Journal of Speech, Language, and Hearing Research, 2025
Purpose: Intentional communication acts, or purposefully directed vocalizations and gestures, are particularly difficult for infants at elevated likelihood for eventual diagnosis of autism. The ability to measure and track intentional communication in infancy thus has the potential to aid early identification and intervention efforts. This study…
Descriptors: Infants, Autism Spectrum Disorders, Caregiver Child Relationship, Nonverbal Communication
Ling-Rong Xiao; Gang Zhao; Pei Zhang; Xian Tian; Xiao-Xue Wu; Jun-Ru Li; Si-Yan Liu; Hong-Mei Wu – Journal of Attention Disorders, 2025
Background: Adolescent-specific ADHD self-report screening measures can greatly increase the likelihood of correct diagnosis and timely treatment of ADHD in adolescents. This study provides preliminary evidence for evaluating the reliability and validity of the Adult ADHD Self-Report Scale-Revised (ASRS-R) in a school-based sample of Chinese…
Descriptors: Foreign Countries, Psychometrics, Attention Deficit Hyperactivity Disorder, Self Evaluation (Individuals)
Bernis Sütçübasi; Tugçe Balli; Herbert Roeyers; Jan R. Wiersema; Sami Çamkerten; Ozan Cem Öztürk; Baris Metin; Edmund Sonuga-Barke – Journal of Attention Disorders, 2025
Objective: ADHD and autism are complex and frequently co-occurring neurodevelopmental conditions with shared etiological and pathophysiological elements. In this paper, we attempt to differentiate these conditions among the young people in terms of intrinsic patterns of brain connectivity revealed during resting state using machine learning…
Descriptors: Elementary School Students, Secondary School Students, Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorders
