Validity of a self-reported screening test on co-occurring clinical problems in autism without intellectual disability: Evidence of factorial structure and network analysis of symptom comorbidity

Background: The high prevalence of co-occurring clinical problems in autism spectrum Conditions without Intellectual Disability (ASC-noID) highlights the need for screening tools that are both easy to administer and easy to understand. This study presents the final development and structural validit...

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Detalhes bibliográficos
Autores: Danés Henríquez, Marta, Martínez Molina, Agustín, Sotillo Méndez, María, Belinchón Carmona, Mercedes
Formato: artículo
Fecha de publicación:2026
País:España
Recursos:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:repositorio.uam.es:10486/750381
Acesso em linha:https://hdl.handle.net/10486/750381
https://dx.doi.org/10.1016/j.reia.2026.202822
Access Level:acceso abierto
Palavra-chave:Autism without intellectual disability
Clinical co-occurring problems
Self-report screening questionnaire
Psychometric properties
Structural validity
Psicología
Descrição
Resumo:Background: The high prevalence of co-occurring clinical problems in autism spectrum Conditions without Intellectual Disability (ASC-noID) highlights the need for screening tools that are both easy to administer and easy to understand. This study presents the final development and structural validity of APCA-sin DI, a Spanish self-report questionnaire designed to screen clinical problems that may require specialized attention. Method: A total of 227 young adults with ASC-noID completed an online preliminary version of APCA-sin DI consisting of: (a) 34 items covering 11 clinical categories, rated on four-point Likert scale ("Never to Always"), plus the options "I do not know" and "Prefer not to answer"; (b) three attention control items; and (c) a five-item life satisfaction scale. Descriptive statistics and factorial analysis were conducted to examine the psychometric properties of the instrument. Results: The initial factorial analysis yielded a six-factor model based on seven clinical categories (“Anxiety”; “OCD”; “Sensory disturbances”; “Agitation”; “Autolytic thoughts”; “Depression” and “Eating Disorders”). The final version of the tool (18 items, 5 factors and 5 categories) demonstrated adequate psychometric properties. Conclusions: The factors identified and the potential applications of the APCA-sin DI, for both clinical and research purposes, are discussed in relation to the existing literature