SciELO - Scientific Electronic Library Online

 
vol.6 número2Modelo psicológico para la investigación de los comportamientos de adhesión en personas con VIHEfectos en la ejecución durante una tarea de igualación a la muestra según el tipo y el orden de exposición a las pruebas de transferencia índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Universitas Psychologica

versão impressa ISSN 1657-9267

Resumo

A. PINEDA, David et al. Cluster taxometry of attention deficit/ hyperactivity disorder with latent class and correspondence analysis. Univ. Psychol. [online]. 2007, vol.6, n.2, pp. 409-423. ISSN 1657-9267.

Attention deficit/hyperactivity disorder (ADHD) has heterogeneous symptoms with diverse grades of severity. Latent class cluster analysis (LCCA) can be used to classify children, using direct data from any instrument that reports these symptoms, without previous gold standard diagnosis. One ADHD symptoms checklist, and one ADHD comorbidities questionnaire were used. LCCAs were developed for each instrument, which were administered to a sample of 540 children and adolescents, aged 4-17 years, from the regular school of Manizales-Colombia. A simple correspondence analysis (SCA) was done to determine the relationships between the groups classified from both LCCAs. Six clusters were obtained from ADHD checklist and five from the ADHD comorbidities questionnaire. SCA found four independent groups, derived from the concordances between the 11 clusters obtained by the LCCAs from both instruments. These findings suggest that LCCA and SCA can be use as accurate taxometric procedures to classify externalizing psychopathologies.

Palavras-chave : ADHD; inattention; hyperactivity; latent class; correspondence analysis; taxometry.

        · resumo em Espanhol     · texto em Espanhol     · Espanhol ( pdf )

 

Creative Commons License