Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients.

<h4>Background</h4>The use of Bayesian Structural Equation Model (BSEM) to evaluate the impact of TB on self-reported health related quality of life (HRQoL) of TB patients has been not studied.<h4>Objective</h4>To identify the factors that contribute to the HRQoL of TB patien...

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Autores principales:	Mahalingam Vasantha, Malaisamy Muniyandi, Chinnaiyan Ponnuraja, Ramalingam Srinivasan, Perumal Venkatesan
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/61e1e2d7e63e46bc9a0f37aa54d519c6
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spelling	oai:doaj.org-article:61e1e2d7e63e46bc9a0f37aa54d519c62021-12-02T20:05:27ZBayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients.1932-620310.1371/journal.pone.0252205https://doaj.org/article/61e1e2d7e63e46bc9a0f37aa54d519c62021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0252205https://doaj.org/toc/1932-6203<h4>Background</h4>The use of Bayesian Structural Equation Model (BSEM) to evaluate the impact of TB on self-reported health related quality of life (HRQoL) of TB patients has been not studied.<h4>Objective</h4>To identify the factors that contribute to the HRQoL of TB patients using BSEM.<h4>Methods</h4>This is a latent variable modeling with Bayesian approach using secondary data. HRQoL data collected after one year from newly diagnosed 436 TB patients who were registered and successfully completed treatment at Government health facilities in Tiruvallur district, south India under the National TB Elimination Programme (NTEP) were used for this analysis. In this study, the four independent latent variables such as physical well-being (PW = PW1-7), mental well-being (MW = MW1-7), social well-being (SW = SW1-4) and habits were considered. The BSEM was constructed using Markov Chain Monte Carlo algorithm for identifying the factors that contribute to the HRQoL of TB patients who completed treatment.<h4>Results</h4>Bayesian estimates were obtained using 46,300 observations after convergence and the standardized structural regression estimate of PW, MW, SW on HRQoL were 0.377 (p<0.001), 0.543 (p<0.001) and 0.208 (p<0.001) respectively. The latent variables PW, MW and SW were significantly associated with HRQoL of TB patients. The age was found to be significantly negatively associated with HRQoL of TB patients.<h4>Conclusions</h4>The current study demonstrated the application of BSEM in evaluating HRQoL. This methodology may be used to study precise estimates of HRQoL of TB patients in different time points.Mahalingam VasanthaMalaisamy MuniyandiChinnaiyan PonnurajaRamalingam SrinivasanPerumal VenkatesanPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 5, p e0252205 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Mahalingam Vasantha Malaisamy Muniyandi Chinnaiyan Ponnuraja Ramalingam Srinivasan Perumal Venkatesan Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients.
description	<h4>Background</h4>The use of Bayesian Structural Equation Model (BSEM) to evaluate the impact of TB on self-reported health related quality of life (HRQoL) of TB patients has been not studied.<h4>Objective</h4>To identify the factors that contribute to the HRQoL of TB patients using BSEM.<h4>Methods</h4>This is a latent variable modeling with Bayesian approach using secondary data. HRQoL data collected after one year from newly diagnosed 436 TB patients who were registered and successfully completed treatment at Government health facilities in Tiruvallur district, south India under the National TB Elimination Programme (NTEP) were used for this analysis. In this study, the four independent latent variables such as physical well-being (PW = PW1-7), mental well-being (MW = MW1-7), social well-being (SW = SW1-4) and habits were considered. The BSEM was constructed using Markov Chain Monte Carlo algorithm for identifying the factors that contribute to the HRQoL of TB patients who completed treatment.<h4>Results</h4>Bayesian estimates were obtained using 46,300 observations after convergence and the standardized structural regression estimate of PW, MW, SW on HRQoL were 0.377 (p<0.001), 0.543 (p<0.001) and 0.208 (p<0.001) respectively. The latent variables PW, MW and SW were significantly associated with HRQoL of TB patients. The age was found to be significantly negatively associated with HRQoL of TB patients.<h4>Conclusions</h4>The current study demonstrated the application of BSEM in evaluating HRQoL. This methodology may be used to study precise estimates of HRQoL of TB patients in different time points.
format	article
author	Mahalingam Vasantha Malaisamy Muniyandi Chinnaiyan Ponnuraja Ramalingam Srinivasan Perumal Venkatesan
author_facet	Mahalingam Vasantha Malaisamy Muniyandi Chinnaiyan Ponnuraja Ramalingam Srinivasan Perumal Venkatesan
author_sort	Mahalingam Vasantha
title	Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients.
title_short	Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients.
title_full	Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients.
title_fullStr	Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients.
title_full_unstemmed	Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients.
title_sort	bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/61e1e2d7e63e46bc9a0f37aa54d519c6
work_keys_str_mv	AT mahalingamvasantha bayesianstructuralequationmodelingforposttreatmenthealthrelatedqualityoflifeamongtuberculosispatients AT malaisamymuniyandi bayesianstructuralequationmodelingforposttreatmenthealthrelatedqualityoflifeamongtuberculosispatients AT chinnaiyanponnuraja bayesianstructuralequationmodelingforposttreatmenthealthrelatedqualityoflifeamongtuberculosispatients AT ramalingamsrinivasan bayesianstructuralequationmodelingforposttreatmenthealthrelatedqualityoflifeamongtuberculosispatients AT perumalvenkatesan bayesianstructuralequationmodelingforposttreatmenthealthrelatedqualityoflifeamongtuberculosispatients
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Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients.

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