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

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  • Mahalingam Vasantha
  • Malaisamy Muniyandi
  • Chinnaiyan Ponnuraja
  • Ramalingam Srinivasan
  • Perumal Venkatesan

Abstract

Background: 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. Objective: To identify the factors that contribute to the HRQoL of TB patients using BSEM. Methods: 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. Results: 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

Suggested Citation

  • Mahalingam Vasantha & Malaisamy Muniyandi & Chinnaiyan Ponnuraja & Ramalingam Srinivasan & Perumal Venkatesan, 2021. "Bayesian structural equation modeling for post treatment health related quality of life among tuberculosis patients," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-10, May.
    • Handle: RePEc:plo:pone00:0252205
    DOI: 10.1371/journal.pone.0252205
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    References listed on IDEAS

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    4. Rajeswari, R. & Muniyandi, M. & Balasubramanian, R. & Narayanan, P.R., 2005. "Perceptions of tuberculosis patients about their physical, mental and social well-being: a field report from south India," Social Science & Medicine, Elsevier, vol. 60(8), pages 1845-1853, April.
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