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Ek-uma   Imkome

Ek-uma Imkome

Faculty of Nursing, Thammasat University

Title: A Bayesian structural equation modeling approach of the Thai Impact and Burden Care Scale (TIBCS) in caregiver of persons with schizophrenia: psychometric properties testing

Biography

Biography: Ek-uma Imkome

Abstract

Objective: The Thai Impact and Burden Care Scale (TIBCS) was developed to assess the impact on caregivers of caring for patients with schizophrenia. The objective of this study was to develop a scoring algorithm for the TIBCS, and evaluate its measurement properties.

Methods: The TIBCS was administered to 297 caregivers of persons with schizophrenia. Three a priori models, the two-factor, three factor, and bi-factor models, were examined by maximum likelihood confirmatory factor analysis (ML-CFA) and Bayesian structural equation modeling (BSEM). BSEM specified approximate zero cross-loadings and residual correlations through the use of zero-mean, small-variance informative priors. The model comparison was based on the Bayesian information criterion (BIC).

Results: The using ML-CFA, none of the three models provided an adequate fit for either sample. The BSEM two-factor model with approximate zero cross-loadings and residual correlations fitted both samples well with the lowest BIC of the three models and displayed a simple and parsimonious factor-loading pattern.

Discussion: Overall, the scale demonstrated very good measurement properties supporting its relevance to comprehensively measure the impact and burden care of caregivers of persons with schizophrenia.