Determinants of medication adherence among patients with tuberculosis in Ogan Komering Ulu, Indonesia: A cross-sectional study
https://doi.org/10.52235/lp.v7i1.718
Keywords:
medication adherence, patient education, social support, tuberculosisAbstract
Background: Medication adherence among tuberculosis patients is influenced by multiple behavioral, social, and healthcare-related factors. In many developing regions, challenges related to patient knowledge, family involvement, treatment perceptions, and healthcare education continue to affect the success of tuberculosis treatment programs. Understanding the determinants of medication adherence is therefore essential for improving treatment outcomes and strengthening tuberculosis control strategies at the community level.
Objective: This study aimed to identify the determinants of medication adherence among patients with tuberculosis in Ogan Komering Ulu, Indonesia.
Methods: This study employed a descriptive analytic design with a cross-sectional approach conducted at the UPTD Puskesmas Tanjung Agung, Ogan Komering Ulu Regency, South Sumatra, Indonesia. The study population consisted of all tuberculosis patients registered in the TB treatment program between January and August 2025. A total sampling technique was used, resulting in 44 respondents participating in the study. Data were collected using structured interviews with a questionnaire measuring patient knowledge, family support, perceptions of anti-tuberculosis drug side effects, quality of health education provided by healthcare workers, and medication adherence. Data analysis included univariate analysis to describe variable distributions and bivariate analysis using the Chi-square test.
Results: The results showed that 72.7% of respondents were adherent to anti-tuberculosis medication, while 27.3% were non-adherent. Bivariate analysis revealed that patient knowledge (p = 0.003), family support (p < 0.001), perception of drug side effects (p = 0.001), and quality of health education provided by healthcare workers (p < 0.001) were significantly associated with medication adherence. Patients with good knowledge, supportive family environments, positive perceptions of medication side effects, and high-quality educational support from healthcare providers demonstrated higher adherence rates during tuberculosis treatment.
Conclusion: Medication adherence among tuberculosis patients is significantly influenced by knowledge, family support, perceptions of medication side effects, and the quality of healthcare education. Strengthening patient education, promoting family involvement in treatment supervision, and improving communication between healthcare providers and patients may enhance adherence behavior and improve tuberculosis treatment outcomes.
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References
Abas, S. A., Ismail, N., Zakaria, Y., et al. (2024). Enhancing tuberculosis treatment adherence and motivation through gamified real-time mobile app utilization: A single-arm intervention study. BMC Public Health, 24, 249. https://doi.org/10.1186/s12889-023-17561-z
Al-Worafi, Y. M. (2024). Infectious disease causes and risk factors in developing countries: Adults. In Handbook of Medical and Health Sciences in Developing Countries (pp. 1–23). Springer. https://doi.org/10.1007/978-3-030-74786-2_328-1
Alee, I., Ayub, Z., & Ahmad, N. (2025). A qualitative inquiry into dietary adherence among adults with type 2 diabetes mellitus in India. Journal of Community Nursing and Primary Care, 2(1), 31-36. https://doi.org/10.63202/jcnpc.v2i1.102
Anurak, A., & Chaow, C. (2025). Association between functional status and self-care behavior among adults at high risk of stroke : A cross-sectional study. Journal of Community Nursing and Primary Care, 2(1), 17-23. https://doi.org/10.63202/jcnpc.v2i1.98
Appiah, M. A., Arthur, J. A., Gborgblorvor, D., Asampong, E., Kye-Duodu, G., Kamau, E. M., et al. (2023). Barriers to tuberculosis treatment adherence in high-burden tuberculosis settings in Ashanti Region, Ghana: A qualitative study from patient’s perspective. BMC Public Health, 23(1), 1–12. https://doi.org/10.1186/s12889-023-16259-6
Aprita, A. (2024). Correlation between family support and the level of compliance with diabetes diet control: A cross-sectional study. Journal of Community Nursing and Primary Care, 1(1), 16-22. https://doi.org/10.63202/jcnpc.v1i1.29
Atake, E. H. (2023). Health system productivity in sub-Saharan Africa: Tuberculosis control in high burden countries. Cost Effectiveness and Resource Allocation, 21(1), 1–11. https://doi.org/10.1186/s12962-023-00485-1
Bio, R. B., Akweongo, P., Koduah, A., & Adomah-Afari, A. (2024). Economic burden and coping mechanisms by tuberculosis treatment supporters: A mixed method approach from Bono Region, Ghana. BMC Health Services Research, 24(1), 148. https://doi.org/10.1186/s12913-024-10611-1
Bondarchuk, C. P., Lemon, T., Medina-Marino, A., Rousseau, E., Sindelo, S., Sibanda, N., et al. (2024). Food insecurity and unemployment as mediators of the relationship between the COVID-19 pandemic and psychological well-being in young South Africans with HIV. BMC Public Health, 24(1), 2622. https://doi.org/10.1186/s12889-024-19966-w
Burzynski, J., Mangan, J. M., Lam, C. K., Macaraig, M., Salerno, M. M., deCastro, B. R., et al. (2022). In-person vs electronic directly observed therapy for tuberculosis treatment adherence: A randomized noninferiority trial. JAMA Network Open, 5, e2144210. https://doi.org/10.1001/jamanetworkopen.2021.44210
Charalambous, S., Maraba, N., Jennings, L., Rabothata, I., Cogill, D., Mukora, R., et al. (2024). Treatment adherence and clinical outcomes amongst people with drug-susceptible tuberculosis using medication monitor and differentiated care approach compared with standard of care in South Africa: A cluster randomized trial. EClinicalMedicine, 75, 102745. https://doi.org/10.1016/j.eclinm.2024.102745
Dinas Kesehatan Kabupaten OKU. (2025). Profil Kesehatan Dinkes Tahun 2024. Baturaja.
Dinas Kesehatan Provinsi Sumatera Selatan. (2024). Profil Kesehatan Provinsi Sumatera Selatan Tahun 2024. Palembang.
Djochie, R. D. A., Anto, B. P., Opare-Addo, M. N. A., & Boakye-Yiadom, J. (2025). Factors influencing treatment success in drug-susceptible tuberculosis patients in Ghana: A prospective cohort study. PLOS Global Public Health, 5(2), e0004146. https://doi.org/10.1371/journal.pgph.0004146
Gatete, G., Njunwa, K. J., Migambi, P., Ntaganira, J., & Ndagijimana, A. (2023). Prevalence and factors associated with sputum smear non-conversion after two months of tuberculosis treatment among smear-positive pulmonary tuberculosis patients in Rwanda: A cross-sectional study. BMC Infectious Diseases, 23, 408. https://doi.org/10.1186/s12879-023-08395-6
Gedikli, C., Miraglia, M., Connolly, S., Bryan, M., & Watson, D. (2023). The relationship between unemployment and wellbeing: An updated meta-analysis of longitudinal evidence. European Journal of Work and Organizational Psychology, 32(1), 128–144. https://doi.org/10.1080/1359432X.2022.2106855
Goscé, L., Tadesse, A. W., Foster, N., van Kalmthout, K., Rest, J., Wal, J., et al. (2024). Modelling the epidemiological and economic impact of digital adherence technologies with differentiated care for tuberculosis treatment in Ethiopia. BMJ Global Health, 9, e016997. https://doi.org/10.1136/BMJGH-2024-016997
Guzman, K., Crowder, R., Leddy, A., Maraba, N., Jennings, L., Ahmed, S., et al. (2023). Acceptability and feasibility of digital adherence technologies for drug-susceptible tuberculosis treatment supervision: A meta-analysis of implementation feedback. PLOS Digital Health, 2, e0000322. https://doi.org/10.1371/journal.pdig.0000322
Jerene, D., van Kalmthout, K., Levy, J., Alacapa, J., Deyanova, N., Dube, T., et al. (2025). Effect of digital adherence technologies on treatment outcomes in people with drug-susceptible tuberculosis: Four pragmatic, cluster-randomised trials. Lancet, 405, 1155–1166. https://doi.org/10.1016/S0140-6736(24)02847-2
Kafie, C., Mohamed, M. S., Zary, M., Chilala, C. I., Bahukudumbi, S., Gore, G., et al. (2024). Cost and cost-effectiveness of digital technologies for support of tuberculosis treatment adherence: A systematic review. BMJ Global Health, 9. https://doi.org/10.1136/bmjgh-2024-015654
Kementerian Kesehatan Republik Indonesia. (2025). Buku Panduan Tenaga Medis dan Kesehatan Tuberkulosis: Langkah dalam Pencegahan, Deteksi Dini, dan Pendampingan Pasien TBC di Masyarakat. Jakarta: Kemenkes RI.
Kiwanuka, N., Kityamuwesi, A., Crowder, R., Guzman, K., Berger, C. A., Lamunu, M., et al. (2023). Implementation, feasibility, and acceptability of 99DOTS-based supervision of treatment for drug-susceptible TB in Uganda. PLOS Digital Health, 2, e0000138. https://doi.org/10.1371/journal.pdig.0000138
Li, F., Zhou, J., Ma, X., Guo, X., Zhou, J., Wang, D., et al. (2024). Analysis of treatment outcome and influencing factors among students with pulmonary tuberculosis in Guizhou Province from 2012 to 2021. Chinese Preventive Medicine, 25, 1157–1161. https://doi.org/10.16506/j.1009-6639.2024.09.013
Li, W., Wu, S., Su, M., Saad, A., Zhang, W., Fan, X., et al. (2025). Barriers and facilitators to the implementation of electronic monitors to improve adherence and health outcomes in patients with tuberculosis: A systematic review. Lancet Infectious Diseases, 25, e153–e164. https://doi.org/10.1016/S1473-3099(24)00587-5
Liu, X., Thompson, J., Dong, H., Sweeney, S., Li, X., Yuan, Y., et al. (2023). Digital adherence technologies to improve tuberculosis treatment outcomes in China: A cluster-randomised superiority trial. Lancet Global Health, 11, e693–e703. https://doi.org/10.1016/S2214-109X(23)00068-2
Manyazewal, T., Woldeamanuel, Y., Holland, D. P., Fekadu, A., & Marconi, V. C. (2022). Effectiveness of a digital medication event reminder and monitor device for patients with tuberculosis (SELFTB): A multicenter randomized controlled trial. BMC Medicine, 20, 310. https://doi.org/10.1186/s12916-022-02521-y
Nurhayati, & Febrianti. (2024). The Relationship between Knowledge Level and Smoking Habit Behavior with the Incidence of Pulmonary Tuberculosis Patients. Indonesian Journal of Health Services, 1(1), 1-6. https://doi.org/10.63202/ijhs.v1i1.4
Opito, R., Kwenya, K., Ssentongo, S. M., Kizito, M., Alwedo, S., Bakashaba, B., et al. (2024). Treatment success rate and associated factors among drug susceptible tuberculosis individuals in St. Kizito Hospital, Matany, Napak district, Karamoja region: A retrospective study. PLOS ONE, 19(5), e0300916. https://doi.org/10.1371/journal.pone.0300916
Ozaltun, S. C., & Akin, L. (2024). An evaluation of medication adherence in new tuberculosis cases in Ankara: A prospective cohort study. Healthcare, 12(23), 2353. https://doi.org/10.3390/healthcare12232353
Wei, X., Hicks, J. P., Zhang, Z., Haldane, V., Pasang, P., Li, L., et al. (2024). Effectiveness of a comprehensive package based on electronic medication monitors at improving treatment outcomes among tuberculosis patients in Tibet: A multicentre randomised controlled trial. Lancet, 403, 913–923. https://doi.org/10.1016/S0140-6736(23)02270-5
Wilkins, C. A., Hamman, H., Hamman, J. H., & Steenekamp, J. H. (2024). Fixed-dose combination formulations in solid oral drug therapy: Advantages, limitations, and design features. Pharmaceutics, 16, 178. https://doi.org/10.3390/pharmaceutics16020178
World Health Organization. (2024). Global Tuberculosis Report 2024. Geneva: WHO.
Wynn, M., Garwood-Cross, L., Vasilica, C., Griffiths, M., Heaslip, V., & Phillips, N. (2023). Digitizing nursing: A theoretical and holistic exploration to understand the adoption and use of digital technologies by nurses. Journal of Advanced Nursing, 79, 3737–3747. https://doi.org/10.1111/jan.15810
Yan, T., Ma, W., Wang, J., Li, T., Zhang, H., Zhao, Y., et al. (2025). Analysis of the factors influencing adherence and treatment outcomes among pulmonary tuberculosis patients with comorbidities in China from 2010 to 2023. Chinese Journal of Antituberculosis, 47, 1268. https://doi.org/10.19982/j.issn.1000-6621.20250237
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