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Latent Profile Analysis of Self-Stigma Among Individuals With Schizophrenia and Its Relationship With Illness Perception.
Article en En | MEDLINE | ID: mdl-39172889
ABSTRACT

PURPOSE:

To investigate self-stigma among individuals with schizophrenia, identify potential categories of self-stigma, and analyze the association between self-stigma categories and dimensions of disease perception.

METHOD:

Convenience sampling was used to select individuals with schizophrenia (N = 216) in psychiatric hospitals. A General Demographic Information Questionnaire, the Internalized Stigma of Mental Illness Inventory, and Brief Illness Perception Questionnaire were used for data collection. A latent profile analysis was performed on self-stigma characteristics of participants, and potential categories of influencing factors and their relationship with illness perception were examined.

RESULTS:

Participants were classified into three potential categories low self-stigma-low resistance (19.4%), medium self-stigma (55.6%), and high self-stigma-high discrimination (25%). Compared with the low self-stigma-low resistance group, those with higher illness representation and illness understanding scores were more likely to be classified as medium self-stigma, and emotional representation was the strongest predictor for high self-stigma-high discrimination.

CONCLUSION:

Self-stigma among participants was mostly medium to high. Self-stigma of individuals with schizophrenia demonstrates group heterogeneity; therefore, nurses should formulate targeted interventions based on the characteristics of each category to achieve precise interventions and reduce self-stigma. [Journal of Psychosocial Nursing and Mental Health Services, xx(xx), xx-xx.].

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Psychosoc Nurs Ment Health Serv Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Psychosoc Nurs Ment Health Serv Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos