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Chinese Journal of Antituberculosis ›› 2025, Vol. 47 ›› Issue (10): 1326-1332.doi: 10.19982/j.issn.1000-6621.20250193

• Original Articles • Previous Articles     Next Articles

Research on influencing factors of preventive treatment of latent tuberculosis infection based on thematic analysis:Taking Shijiazhuang City as an example

Shi Xiaojing1, Wang Xin2, Guo Jianhua3,4(), Zhao Qingran5, Wang Yuhan5   

  1. 1Department of Medical Engineering,Shijiazhuang Science and Technology Career Academy, Shijiazhuang 052165, China
    2College of Public Health,North China University of Science and Technology, Tangshan 063210,China
    3Institute of Tuberculosis Prevention,Shijiazhuang Center for Disease Control and Prevention, Shijiazhuang 050011, China
    4Hebei Key Laboratory of Intractable Pathogens,Shijiazhuang 050011, China
    5College of Public Health,Hebei Medical University, Shijiazhuang 050017,China
  • Received:2025-05-09 Online:2025-10-10 Published:2025-09-29
  • Contact: Guo Jianhua,Email:guoflowers@163.com
  • Supported by:
    Hebei Medical Applicable Technology Tracking Project(GZ2024087)

Abstract:

Objective: To analyze influencing factors of preventive treatment of latent tuberculosis infection (LTBI) based on thematic analysis, to provide reference for rapid promotion of preventive treatment. Methods: A purposive sampling method was used to select 30 managers involved in all aspects of preventive treatment work in Shijiazhuang City from 2022 to 2023 and 75 latent tuberculosis infectors who met the preventive treatment standard and lived in the city during the same period as the research objects. Semi-structured in-depth individual interview was conducted to collect their understanding and attitude towards preventive treatment policy. Thematic analysis was conducted for summarization and analysis with software MAXQDA 22.0. Through double independent open coding and axial coding, a theme framework of influencing factors of LTBI preventive treatment was constructed, reliability of coding results was evaluated with coding consistency coefficient, then difference in response frequency on the overall theme between latent tuberculosis infectors and preventive treatment managers was analyzed. Results: In-depth interview with 105 subjects formed a final thematic framework of LTBI preventive treatment influencing factors which included four general themes: cognitive factors (95 times), decision support (54 times), risk management (48 times) and policy funds (33 times), covering 8 sub-themes and 230 categories. There was a statistically significant difference in the response frequencies of latent tuberculosis infectors and preventive treatment managers in the overall theme (χ2=13.097, P=0.004). Latent tuberculosis infectors and preventive treatment managers had insufficient knowledge of LTBI and preventive treatment (46 times), latent tuberculosis infectors cannot obtain effective decision support (54 times), difficulties in treatment management (21 times), and lack of policy and financial support (33 times) directly affected the smooth conduction of preventive treatment. Conclusion: Individual cognitive level and health beliefs, timeliness and effectiveness of decision support, risk management, policy and financial support affect the promotion of preventive treatment.

Key words: Mycobacterium tuberculosis, Mycobacterium infections, Protective agents, Factor analysis, statistical

CLC Number: