ArticlePsychology research and behavior management2023
Influencing Factors of Treatment Outcomes Among Patients with Pulmonary Tuberculosis: A Structural Equation Model Approach.
Article in Psychology research and behavior management, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications of causal and structural equation modeling in epidemiology: a systematic and critical review.BMC medical research methodology · 2026Pooled it
- Nomogram for Predicting Poor Prognosis of Newly Diagnosed Active Pulmonary Tuberculosis Based on PNI: Development and Internal Validation.Infection and drug resistance · 2026Article
- Effect of Drug Cost-Exemption Policy on Treatment Outcomes in Multidrug-Resistant Tuberculosis Patients in Guangxi Zhuang Autonomous Region, China: A Nested Case-Control Study.ClinicoEconomics and outcomes research : CEOR · 2026Article
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7 authors.
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Abstract
Background: Pulmonary tuberculosis (PTB) is a serious infectious disease, and the factors and pathways that influence final treatment outcomes are unclear. Here, we aimed to assess the factors that influence treatment outcomes in patients with PTB using a structural equation model. Methods: Participants completed a questionnaire covering demographics, understanding of PTB, psychological status, and history of medical treatment. Exploratory factor analysis and reliability testing were performed, and a structural equation model was constructed using the SPSS and Amos software. Results: A total of 251 participants were enrolled. Symptoms of depression were observed in 94.4% of participants, whereas 6% showed mild or greater anxiety. Through factor rotation, four common factors were extracted with a total variation of 66.15%. The structural equation model indicated that regular tuberculosis-related follow-up behaviour had a direct and positive effect on the final treatment outcome, with a path coefficient value of 0.20; the level of PTB understanding had a direct positive effect on the testing behaviour for PTB, with a path coefficient of 0.26; patients' psychological characteristics had a direct negative impact on regular testing behaviour, with a path coefficient of -0.13. The psychological characteristics and level of disease understanding of patients exerted indirect effects on the treatment outcome by affecting the way patients approached tuberculosis detection behaviour. Conclusion: Interventions aimed at improving the treatment outcomes of patients with PTB should mainly focus on financial support and improvements in psychological status in addition to a greater understanding and knowledge of PTB. Furthermore, patients should be encouraged to undergo regular PTB testing during the follow up period, as this mediates the effect of other factors on treatment outcomes and also helps in achieving favourable treatment outcomes.
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