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Direct linkOscar W. H. Wong; Sandra S. M. Chan; Steven W. H. Chau; Winnie C. W. Chu; Carol S. W. Ho; Stephy W. S. Ho; Se Fong Hung; Samara Hussain; Kelly Y. C. Lai; Angela M. W. Lam; Holly H. L. Lo; Karen K. Y. Ma; Suk Ling Ma; Flora Y. M. Mo; Pak Chung Sham; Caroline K. S. Shea; Suzanne H. W. So; Kelvin K. F. Tsoi; Patrick W. L. Leung – Autism: The International Journal of Research and Practice, 2025
Epidemiological studies on autism lack representation from Asia. We estimated the prevalence of autism among children and youths in Hong Kong using a two-stage approach. In addition, we evaluated the psychometric properties of the screening instrument and explored sex differences within an epidemiological context. A random school-based sample of…
Descriptors: Foreign Countries, Autism Spectrum Disorders, Epidemiology, Children
Ayelet Ben-Sasson; Joshua Guedalia; Keren Ilan; Meirav Shaham; Galit Shefer; Roe Cohen; Yuval Tamir; Lidia V. Gabis – Autism: The International Journal of Research and Practice, 2024
Early detection of autism spectrum condition is crucial for children to maximally benefit from early intervention. The study examined a machine learning model predicting the increased likelihood for autism from wellness records from 0 to 24 months. The study included 591,989 non-autistic and 12,846 autistic children. A gradient boosting model with…
Descriptors: Foreign Countries, Autism Spectrum Disorders, Infants, Predictor Variables
Amy S. Weitlauf; Tori Foster; James C. Slaughter; Mary Fleck; Jill Harris; Caroline Coffield; Kathleen Simcoe; Jenny Baggett; Alacia Stainbrook; Zachary E. Warren – Journal of Autism and Developmental Disorders, 2025
Tele-assessment of autism in early childhood has increased. However, it is unclear how autism screening tools (M-CHAT-R, DCI) function as part of tele-assessment and relate to a commonly used tele-assessment instrument, the TAP. 361 families from a clinically referred sample of children (mean age: 27.63 months, sd = 4.86 months) completed the…
Descriptors: Screening Tests, Clinical Diagnosis, Diagnostic Tests, Telecommunications
Emily Graybill; Scott Lewis; Ella Anghel; Sofia Awan; Brian Barger; Ashley Salmon – Psychology in the Schools, 2025
Early warning indicator and intervention systems (EWS) have been promoted to identify students at risk of school underperformance or dropout. Current EWS systems typically include administrative data on attendance, behavior incidents requiring disciplinary action, and course performance. This study tested whether specific emotional and behavioral…
Descriptors: Screening Tests, Student Behavior, Early Intervention, Middle School Students
Zanko, Amanda E. – ProQuest LLC, 2022
Although numerous studies have focused on understanding the utility of the Behavior Assessment System for Children (BASC; Reynolds & Kamphaus, 2015) across multiple populations, many of the studies that focus on the use of this measure with the college population have used the previous edition (BASC-2). Given the rising rates of anxiety and…
Descriptors: College Students, At Risk Students, Mental Health, Anxiety
James R. Izzo – ProQuest LLC, 2024
Curriculum-based measurements (CBM) are used in schools to screen students for academic difficulties. Oral reading fluency curriculum-based measures (CBM-R) are the most popular, yet several studies have identified predictive bias in CBM-Rs in relation to key variables (e.g., race, sex). Despite a massive increase in the use of these measures as…
Descriptors: Predictor Variables, Bias, Curriculum Based Assessment, Reading Tests
Judith Solheim, Oddny; Torppa, Minna; Henning Uppstad, Per; Lerkkanen, Marja-Kristiina – Scandinavian Journal of Educational Research, 2021
Early identification of children at risk of developing reading difficulties is crucial for effective interventions. While orthographies and educational contexts differ, predictors included in early at-risk screening tend to remain rather homogeneous across countries. In this study, we compared longitudinal prediction patterns of being among the 20…
Descriptors: Reading Difficulties, Reading Fluency, Grade 1, At Risk Students
Danowitz, Andrew; Beddoes, Kacey – IEEE Transactions on Education, 2022
Contribution: Screening rates for engineering students for several major and moderate mental health issues are reported, including unspecified psychological distress as captured by the Kessler 6 screening instrument; screening rates for depressive, anxiety, and eating disorders as measured by the patient health questionnaire (PHQ); and screening…
Descriptors: Engineering Education, College Students, Mental Disorders, Screening Tests
Download full textBingöl, Tugba Yilmaz – Universal Journal of Educational Research, 2018
In this study, the predictive role of self-efficacy, gender and cyber victimization on cyber bullying in adolescents was examined. Examining whether the participants' mean self-efficacy, cyberbullying and cyber victimization scores differ significantly by gender are the sub-objectives of the research. The present study which was designed with a…
Descriptors: Role, Self Efficacy, Bullying, Computer Mediated Communication
Gniewosz, Burkhard; Gniewosz, Gabriela – International Journal of Behavioral Development, 2018
The present article aims to show how to model longitudinal change in cohort sequential data applying latent true change models using Mplus' multi-group approach. The underlying modeling ideas are described and explained in this article. As an example, change in internalizing problem behaviors between the age of 8 and 13 years is modeled and…
Descriptors: Models, Data, Behavior Problems, Children
Leitch, David B. – Journal of Correctional Education, 2019
The use of mental health-related intake assessments by juvenile correctional facilities as predictive measures of confinement behavior has seen limited use in recent years. This study employs the Massachusetts Youth Screening Instrument-Version 2 (MAYSI-2) and How I Think Questionnaire (HIT) as measurement tools on the same data set to assess the…
Descriptors: Mental Health, Screening Tests, Correctional Institutions, Institutionalized Persons
Smith, Karen G. – ProQuest LLC, 2019
Many adolescents struggle with reading comprehension, despite an emphasis on reading instruction over recent decades. Evidence suggests that informational text is particularly challenging for students. To implement assessments within a multi-tiered framework, schools must have psychometrically adequate tools. Using data of 473 students in Grades 6…
Descriptors: Reading Comprehension, Middle School Students, Grade 6, Grade 7
Powell, Michael; Newgent, Rebecca A. – Measurement and Evaluation in Counseling and Development, 2016
This article describes the development and psychometrics of the Juvenile Addiction Risk Rating. The Juvenile Addiction Risk Rating is a brief screening of addiction potential based on 10 risk factors predictive of youth alcohol and drug-related problems that assists examiners in more accurate treatment planning when self-report information is…
Descriptors: Addictive Behavior, At Risk Students, Substance Abuse, Adolescents
Kloos, Heidi – Online Submission, 2019
A data set from an urban Midwestern school district was mined to explore how the technology-based reading enrichment known as Mindplay Virtual Reading Coach (MVRC) affects children's performance on the English Language Arts (ELA) Standards state-wide assessment (N = 6098 students from Grades 3 to 9). ELA data from two times points were available,…
Descriptors: Poverty, Urban Schools, Language Arts, Educational Technology
Frei, Lukas; Schuepbach, Marianne; Nieuwenboom, Wim; von Allmen, Benjamin – International Journal for Research on Extended Education, 2016
So far, empirical evidence regarding the effects of extended education on externalizing behavior is mixed. To explore possible moderators, multilevel-analyses were conducted in a longitudinal sample of 492 students from 51 all-day schools in Switzerland. No main effects of utilization intensity, interaction quality and externalizing behavior in…
Descriptors: After School Programs, Behavior Problems, School Schedules, Peer Influence
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