Influencing Factors of Treatment Outcomes Among Patients with Pulmonary Tuberculosis: A Structural Equation Model Approach

Abstract

Kui Liu,1,* Mengdie Zhang,2,* Dan Luo,3 Yan Zheng,4 Zhenye Shen,4 Bin Chen,1 Jianmin Jiang1,5 1Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People’s Republic of China; 2Department of Social Medicine of School of Public Health, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, People’s Republic of China; 3Department of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang Province, People’s Republic of China; 4Department of Tuberculosis Control and Prevention, Fenghua Center for Disease Control and Prevention, Ningbo, Zhejiang Province, People’s Republic of China; 5Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bin Chen; Jianmin Jiang, Email [email protected]; [email protected]: 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.Keywords: pulmonary tuberculosis, structural equation model, treatment outcome, depression

Keywords

• pulmonary tuberculosis
• structural equation model
• treatment outcome
• depression