Development of Tuberculosis Management Model with Participation of Network Partners in Border Areas of Chiang Mai Province
Keywords:
Tuberculosis management, Participation, Network partners, Border, MulticulturalismAbstract
This action research aimed to 1) examine the situation and management of tuberculosis in the border areas of Chiang Mai Province; 2) develop a tuberculosis management model with the participation of network partners in the border areas of Chiang Mai Province; and 3) evaluate the effectiveness of the model in the same context. The sample was selected using purposive sampling. Phase 1 included 15 public health personnel and 48 network partners in the border areas. Phase 2 focused on the development of the model, involving 4 participants comprising public health personnel, network partners, tuberculosis patients, and their families, as well as an implementation group consisting of 15 tuberculosis patients and their caregivers. Phase 3 evaluated the model among public health personnel, network partners, and tuberculosis patients, their families, and at-risk groups in the border areas, totaling 82 participants. The research was carried out between October 2024 and June 2025. The study collected both quantitative and qualitative data. Quantitative data were analyzed using both descriptive and inferential statistics, specifically the paired t-test. Qualitative data were analyzed through content analysis. The results of the Phase 1 research revealed that, over the past five years (2020–2024), tuberculosis management primarily focused on screening that met the national criteria. However, the overall approach to solving tuberculosis-related problems was not systematic and lacked community participation. Phase 2 focused on the development of a tuberculosis management model with the participation of network partners in the border areas of Chiang Mai Province. The TB CD Model consists of four key components: T (Teamwork), which aims to strengthen multidisciplinary teams within the local area; B (Border Collaboration), which fosters partnerships with network stakeholders in the border regions; C (Communication), which emphasizes effective interaction in multicultural contexts; and D (Data Excellence), which involves the management of an accurate and comprehensive data system. This model was designed to address the complex challenges of tuberculosis control by leveraging collaborative efforts and robust data management. Phase 3: Evaluation of the model implementation revealed statistically significant improvements among patients in knowledge (p = 0.039), self-care (p <0.001), participation (p = 0.005), and satisfaction (p <0.001). Additionally, the rate of treatment completion increased, while medication discontinuation decreased. Therefore, effective management and resolution of tuberculosis problems in border areas require the development of strong teams, active participation of network partners, effective communication, and robust database management. These components collectively contribute to sustainable solutions for tuberculosis control.
References
Alsayed SSR, Gunosewoyo H. Tuberculosis: pathogenesis, current treatment regimens and new drug targets. Int J Mol Sci 2023; 24(6): 5202. doi: 10.3390/ijms24065202.
Nezenega ZS, Perimal-Lewis L, Maeder AJ. Factors influencing patient adherence to tuberculosis treatment in Ethiopia: a literature review. Int J Environ Res Public Health 2020 Aug 4; 17(15): 5626. doi: 10.3390/ijerph17155626.
Gebreweld FH, Kifle MM, Gebremicheal FE, Simel LL, Gezae MM, Ghebreyesus SS, et al. Factors influencing adherence to tuberculosis treatment in Asmara, Eritrea: a qualitative study. J Health Popul Nutr 2018; 37(1): 1. doi: 10.1186/s41043-017-0132-y.
กรมควบคุมโรค กระทรวงสาธารณสุข. สถานการณ์และผลการดำเนินงานควบคุมวัณโรคของประเทศไทย ปี พ.ศ. 2562–2566. นนทบุรี: กองวัณโรค กรมควบคุมโรค กระทรวงสาธารณสุข; 2567.
สำนักงานสาธารณสุขจังหวัดเชียงใหม่. รายงานวัณโรคประจำปีจังหวัดเชียงใหม่ พ.ศ. 2567. เชียงใหม่: สำนักงานสาธารณสุขจังหวัดเชียงใหม่; 2567.
Kumah A. Building community networks and engagement for effective TB case management. Front Public Health 2025; 13: 1576875. doi: 10.3389/fpubh.2025.1576875.
Baum F, MacDougall C, Smith D. Participatory action research. J Epidemiol Community Health 2006; 60(10): 854-7. doi: 10.1136/jech.2004.028662.
Kemmis S, McTaggart R. The action research planner. 3rd ed. Victoria: Deakin University; 1988.
Joshi A, Kale S, Chandel S, Pal DK. Likert scale: Explored and explained. Br J Appl Sci Technol. 2015; 7(4): 396-403. doi:10.9734/BJAST/2015/14975.
Cohen JM, Uphoff NT. Effective behavior in organizations. New York: Richard D. Irwin; 1980. p. 219-22.
Bloom BS. Handbook on formative and summative evaluation of student learning. New York: McGraw-Hill; 1971.
Best JW. Research in education. 3rd ed. Englewood Cliffs (NJ): Prentice Hall; 1977.
Rueangmankhong S, Chomjan T, Pongam S, Chatchumni M. Development of a new tuberculosis patient care system at Singburi Hospital, Thailand. Thai J Public Health 2020; 50(3): 338–47.
Ramos JP, Vieira M, Pimentel C, Argel M, Barbosa P, Duarte R. Building bridges: multidisciplinary teams in tuberculosis prevention and care. Breathe (Sheff) 2023; 19(3): 230092. doi: 10.1183/20734735.0092-2023.
Arulchelvan S, Elangovan R. Effective communication approaches in tuberculosis control: Health workers perceptions and experiences. Indian J Tuberc 2017; 64(4): 318–22. doi: 10.1016/j.ijtb.2016.11.017.
AlMossawi HJ, Longacre C, Pillay Y, Kak N. A social and behavior change communication framework for addressing delays to appropriate TB care and treatment. J Lung Health Dis 2019; 3(4): 1–7. doi: org/10.29245/2689-999X/2019/4.1156.
Limenh LW, Kasahun AE, Sendekie AK, Seid AM, Mitku ML, Fenta ET, et al. Tuberculosis treatment outcomes and associated factors among tuberculosis patients treated at healthcare facilities of Motta Town, Northwest Ethiopia: a five-year retrospective study. Sci Rep 2024 Apr 2; 14(1): 7695. doi: 10.1038/s41598-024-58080-0.
Mbuthia GW, Olungah CO, Ondicho TG. Knowledge and perceptions of tuberculosis among patients in a pastoralist community in Kenya: a qualitative study. Pan Afr Med J 2018; 30: 287. doi: 10.11604/pamj.2018.30.287.14836.
จารุวรรณ เดียวสุรินทร์. การบูรณาการปัจจัยเสี่ยงและพัฒนาคะแนนอัตราการเสียชีวิตเพื่อทำนายการพยากรณ์โดยภายหลังการวินิจฉัยวัณโรค. วารสารศูนย์การศึกษาแพทยศาสตร์คลินิก โรงพยาบาลพระปกเกล้า 2568; 42(1): 56-65.
Dara M, Sulis G, Centis R, D'Ambrosio L, de Vries G, Douglas P, et al. Cross-border collaboration for improved tuberculosis prevention and care: policies, tools and experiences. Int J Tuberc Lung Dis 2017; 21(7): 727–36. doi: 10.5588/ijtld.16.0940.
Kumar H, Teena F, Bai A, Kumar L, Gallego S. Bridging gaps in tuberculosis control: addressing cross-border challenges between India and Pakistan. J Clin Tuberc Other Mycobact Dis 2025; 39:100526. doi:10.1016/j.jctube.2025.100526.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 สำนักงานป้องกันควบคุมโรคที่7จังหวัดขอนแก่น

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
ความรับผิดชอบ
บทความที่ลงพิมพ์ในวารสารสำนักงานป้องกันควบคุมโรคที่ 7 ขอนแก่น ถือเป็นผลงานทางวิชาการหรือวิจัย และวิเคราะห์ตลอดจนเป็นความเห็นส่วนตัวของผู้เขียน ไม่ใช่ความเห็นของวารสารสำนักงาน ป้องกันควบคุมโรคที่ 7 จังหวัดขอนแก่น หรือ ของกองบรรณาธิการแต่ประการใด ผู้เขียนต้องรับผิดชอบต่อบทความของตนเอง
ลิขสิทธ์บทความ
บทความที่ได้รับการตีพิมพ์จะถือเป็นลิขสิทธิ์ของสำนักงานป้องกันตวบคุมโรคที่ 7 จังหวัดขอนแก่น
