Detailed Information on Publication Record
2024
Predictors of age at diagnosis in autism spectrum disorders : the use of multiple regression analyses and a classification tree on a clinical sample
HRDLIČKA, Michal, Tomáš URBÁNEK, Adéla ROTREKLOVÁ, Aneta KULTOVÁ, Ondřej VÁLEK et. al.Basic information
Original name
Predictors of age at diagnosis in autism spectrum disorders : the use of multiple regression analyses and a classification tree on a clinical sample
Name in Czech
Prediktory věku při stanovení diagnózy u porucha autistického spektra : užití mnohočetné regresní analýzy a klasifikačního stromu u klinického souboru
Authors
HRDLIČKA, Michal (203 Czech Republic, guarantor, belonging to the institution), Tomáš URBÁNEK (203 Czech Republic, belonging to the institution), Adéla ROTREKLOVÁ (203 Czech Republic), Aneta KULTOVÁ (203 Czech Republic), Ondřej VÁLEK (203 Czech Republic) and Iva DUDOVÁ (203 Czech Republic)
Edition
EUROPEAN CHILD & ADOLESCENT PSYCHIATRY, NEW YORK, SPRINGER, 2024, 1018-8827
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
50101 Psychology
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
Impact factor
Impact factor: 6.400 in 2022
Organization unit
Faculty of Arts
UT WoS
000953074700001
Keywords (in Czech)
Poruchy autistického spektra; věk diagnózy; společná domácnost, ADOS; věk otce; vzdělání matky
Keywords in English
Autism spectrum disorders; Age at diagnosis; Shared household; ADOS; Paternal age; Maternal education
Tags
Tags
International impact, Reviewed
Změněno: 26/6/2024 11:15, Mgr. et Mgr. Stanislav Hasil
Abstract
V originále
The increasing prevalence of autism spectrum disorders (ASD) has led to worldwide interest in factors influencing the age of ASD diagnosis. Parents or caregivers of 237 ASD children (193 boys, 44 girls) diagnosed using the Autism Diagnostic Observation Schedule (ADOS) completed a simple descriptive questionnaire. The data were analyzed using the variable-centered multiple regression analysis and the person-centered classification tree method. We believed that the concurrent use of these two methods could produce robust results. The mean age at diagnosis was 5.8 +/- 2.2 years (median 5.3 years). Younger ages for ASD diagnosis were predicted (using multiple regression analysis) by higher scores in the ADOS social domain, higher scores in ADOS restrictive and repetitive behaviors and interest domain, higher maternal education, and the shared household of parents. Using the classification tree method, the subgroup with the lowest mean age at diagnosis were children, in whom the summation of ADOS communication and social domain scores was ≥ 17, and paternal age at the delivery was ≥ 29 years. In contrast, the subgroup with the oldest mean age at diagnosis included children with summed ADOS communication and social domain scores < 17 and maternal education at the elementary school level. The severity of autism and maternal education played a significant role in both types of data analysis focused on age at diagnosis.