COMMUNITY DETECTION IN NETWORKS OF VARIABLES OF THE TRANSDIAGNOSTIC ACEDA MODEL
Name: LUCAS DOS SANTOS DO VALE
Publication date: 30/04/2025
Examining board:
Name |
Role |
|---|---|
| DANIELA LUCAS DA SILVA LEMOS | Examinador Interno |
| HENRIQUE MONTEIRO CRISTOVAO | Presidente |
Summary: In a context of increasing mental health data production, the present study investigates informational relationships among variables from the transdiagnostic ACEDA model (which integrates Affect, Cognition, Empathy, Desire, and Aggressiveness), with the aim of contributing to both the theoretical development and clinical application of this model, which is used in the identification of impulse control disorders. The relevance of this research lies in its potential to enhance the understanding of the underlying mechanisms of individual impulsivity and, consequently, to support the development of more precise diagnostic and therapeutic interventions. Using Complex Network Analysis techniques from the perspective of Information Science, the study applies methodological procedures involving the collection, cleaning, normalization, and exploratory analysis of data gathered through questionnaires administered to patients, followed by the application of data mining methods for the construction and interpretation of informational networks. The results point to the existence of significant connections among the dimensions proposed by the ACEDA model, revealing patterns and relationships that would not be evident through traditional approaches. In doing so, the study provides valuable insights into the model's internal structure and potential directions for its continuous validation, which may ultimately have a positive impact on the understanding and treatment of impulse control disorders.
