Self-stigma profiles in patients with schizophrenia: a Latent Class Analysis approach

Caqueo-Urizar A.; Ponce-Correa F.; Urzua Á.; Fond G.; Boyer L.

Abstract

Objective: this study aimed at analyzing the internalized stigma latent profiles and the covariates that predict variations in their levels considering antecedent variables such as ethnicity, gender and some relevant clinical characteristics like premorbid adjustment, Duration of Untreated Psychosis and symptoms. Method: Latent Class Analysis (LCA) was used to devise a solution with three internalized stigma profiles in a sample comprised by 227 patients diagnosed with schizophrenia from the Public Mental Health Centers of the city of Arica, Chile. Results: the results showed that premorbid adjustment is a significant predictor of class belonging for the latent stigma profiles. When analyzing the sociodemographic characteristics and contrary to what was hypothesized, ethnicity was not a relevant predictor of internalized stigma profiles. Conclusion: the latent classification model is suitable for assessing stigma profiles in order to target future interventions in specific foci and at-risk populations. © 2025 Revista Latino-Americana de Enfermagem.

Más información

Título según WOS: Self-stigma profiles in patients with schizophrenia: a Latent Class Analysis approach
Título según SCOPUS: Self-stigma profiles in schizophrenia: a Latent Class Analysis approach; Perfis de autoestigma em pacientes com esquizofrenia: uma abordagem de Análise de Classe Latente; Perfiles de autoestigma en pacientes con esquizofrenia: enfoque basado en Análisis de Clases Latentes
Título de la Revista: Revista Latino-Americana de Enfermagem
Volumen: 33
Editorial: Escola de Enfermagem de Ribeirão Preto / Universidade de São Paulo
Fecha de publicación: 2025
Idioma: English
DOI:

10.1590/1518-8345.7504.4593

Notas: ISI, SCOPUS