Latent variable modeling with Bayesian approach in evaluating HRQoL of Tuberculosis

What is it about?

This is a latent variable modeling with Bayesian approach in evaluating HRQoL of TB patients. The Bayesian Structural Equation Modeling was constructed using Markov Chain Monte Carlo algorithm for identifying the factors that contribute to the HRQoL of TB patients who completed treatment.

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Photo by Edge2Edge Media on Unsplash

Photo by Edge2Edge Media on Unsplash

Why is it important?

Our study is first of its kind to use BSEM models to explore HRQoL data of newly diagnosed TB patients. Measurement of the HRQoL adds a new dimension to the evaluation of psychosocial variables of TB patients. We also examined the influence of covariates such as age and occupation on HRQoL scores for four physical, mental, social and life style latent variables. Of this, the mental well-being latent variable had most significant effect on HRQoL of TB patients followed by physical and social well-being latent variables.

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