Volume 13, Issue 1 (2025)                   Health Educ Health Promot 2025, 13(1): 1-6 | Back to browse issues page


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Mashudi M, Masyitah D, Fahmi I, Dahrizal D, Idramsyah I. Impact of the TB SEHAT Application on Medication Adherence in Pulmonary Tuberculosis Patients at Putri Ayu Health Center, Jambi City. Health Educ Health Promot 2025; 13 (1) :1-6
URL: http://hehp.modares.ac.ir/article-5-77780-en.html
1- Department of Nursing, Health Polytechnic of Jambi, Jambi, Indonesia
2- Department of Nursing, Health Polytechnic of Bengkulu, Bengkulu, Indonesia
Abstract:   (772 Views)
Aims: Tuberculosis is still a significant global health challenge, particularly in developing countries. This study aimed to evaluate the impact of the TB SEHAT application on medication adherence among pulmonary tuberculosis patients in Jambi City.
Materials & Methods: This quasi-experimental study employed a one-group pre-test-post-test design with a control group, comprising two groups; an intervention group that received TB SEHAT app-based education and a medication reminder program, and a control group that received standard care from medication supervisors. Each group included 37 participants, selected through simple random sampling. Data collection was done from May 13 to August 30, 2024, within the service area of the Putri Ayu Health Center. Data analysis was performed by SPSS 23.
Findings: Following the use of the TB SEHAT application, the mean adherence to anti-tuberculosis drugs was 127.30±5.22 on the TB Medication Adherence Scale. In contrast, the mean adherence in the group receiving standard treatment supervision was 121.41±6.43. An analysis of covariance indicated a significant difference in adherence between the TB SEHAT application and standard treatment groups (p=0.001).
Conclusion: The TB SEHAT application effectively improves adherence to anti-tuberculosis drugs in patients with pulmonary tuberculosis.
Full-Text [PDF 575 kb]   (1062 Downloads) |   |   Full-Text (HTML)  (29 Views)  
Article Type: Original Research | Subject: Technology of Health Education
Received: 2024/11/1 | Accepted: 2024/12/16 | Published: 2025/01/21
* Corresponding Author Address: Department of Nursing, Health Polytechnic of Jambi, Dr. Tazar, Buluran Kenali, Kec. Telanaipura, Kota Jambi, Jambi. Postal Code: 36361 (mashudi.poltekkesjambi@gmail.com)

References
1. Keutzer L, Wicha SG, Simonsson USH. Mobile health apps for improvement of tuberculosis treatment: Descriptive review. JMIR mHealth uHealth. 2020;8(4):e17246. [] [DOI:10.2196/17246]
2. Cohen A, Mathiasen VD, Schön T, Wejse C. The global prevalence of latent tuberculosis: A systematic review and meta-analysis. Eur Respir J. 2019;54(3):1900655. [Link] [DOI:10.1183/13993003.00655-2019]
3. Novaes MT, Do Prado TN, Delcarro JCS, Rissino SDD, Crepaldi NY, Sanches TLM, et al. Development and content validation of a mobile application for monitoring latent tuberculosis treatment. Rev Soc Bras Med Trop. 2022;55:e0465-2021. [Link] [DOI:10.1590/0037-8682-0465-2021]
4. Soedarsono S, Mertaniasih NM, Kusmiati T, Permatasari A, Juliasih NN, Hadi C, et al. Determinant factors for loss to follow-up in drug-resistant tuberculosis patients: The importance of psycho-social and economic aspects. BMC Pulm Med. 2021;21(1):360. [Link] [DOI:10.1186/s12890-021-01735-9]
5. Ubajaka CF, Azuike EC, Ugoji JO, Nwibo OE, Ejiofor OC, Modebe IA, et al. Adherence to drug medications amongst tuberculosis patients in a tertiary health institution in South East Nigeria. Int J Clin Med. 2015;6(6):399-406. [Link] [DOI:10.4236/ijcm.2015.66052]
6. Mustopa R, Damris D, Syamsurizal S, Emawati MDW. Evaluation of m-health on medication adherence in tuberculosis patients: A systematic review. NSC Nurs. 2023;3(1):1-29. [Link] [DOI:10.32549/OPI-NSC-91]
7. Sehat M, Razzaghi R, Ghamsary M, Ganji MF, Sehat M. Changes in the rate of bacillus tuberculosis infection in health workers in the first year of the COVID-19 epidemic in Kashan-Iran. Heliyon. 2023;9(10):e20560. [Link] [DOI:10.1016/j.heliyon.2023.e20560]
8. Putri SE, Rekawati E, Wati DNK. Effectiveness of self-management on adherence to self-care and on health status among elderly people with hypertension. J Public Health Res. 2021;10(s1):jphr.2021.2406. [Link] [DOI:10.4081/jphr.2021.2406]
9. Supriano A, Katmini K. Analysis of factors affecting druging compliance in lung tuberculosis patients: Theory of health belief model (HBM) in the working area of the health center, Dompu City. J Qual Public Health. 2021;5(1):1-6. [Link] [DOI:10.30994/jqph.v5i1.241]
10. Boonnuddar N, Wuttidittachotti P. Mobile application: Patients' adherence to medicine in-take schedules. Proceedings of the International Conference on Big Data and Internet of Thing. New York: Association for Computing Machinery; 2017. p. 237-41. [Link] [DOI:10.1145/3175684.3175714]
11. Fuad A, Herwanto GB, Pertiwi AAP, Wahyuningtias SD, Harsini H, Maula AW, et al. Design and prototype of TOMO: An app for improving drug resistant TB treatment adherence [version 1; Peer review: 1 approved, 2 approved with reservations]. F1000Research. 2021;10:983. [Link] [DOI:10.12688/f1000research.67212.1]
12. Liu X, Lewis JJ, Zhang H, Lu W, Zhang S, Zheng G, et al. Effectiveness of electronic reminders to improve medication adherence in tuberculosis patients: A cluster-randomised trial. PLoS Med. 2015;12(9):e1001876. [Link] [DOI:10.1371/journal.pmed.1001876]
13. Haase J, Farris KB, Dorsch MP. Mobile applications to improve medication adherence. Telemed J E Health. 2017;23(2):75-9. [Link] [DOI:10.1089/tmj.2015.0227]
14. Haji HA, Rivett U, Suleman H. Improving compliance to tuberculosis treatment: Supporting patients through mobile graphic-based reminders. J Public Health Dev Ctries. 2016;2(3). [Link]
15. Yunita F, Veronica RI, Ratnasari L, Suhendra A, Basuki H. Design a TB treatment compliance application. INFORMATIKA KEDOKTERAN: JURNAL ILMIAH. 2019;2(1):54-69. [Indonesian] [Link]
16. Iribarren SJ, Milligan H, Chirico C, Goodwin K, Schnall R, Telles H, et al. Patient-centered mobile tuberculosis treatment support tools (TB-TSTs) to improve treatment adherence: A pilot randomized controlled trial exploring feasibility, acceptability and refinement needs. Lancet Reg Health Am. 2022;13:100291. [Link] [DOI:10.1016/j.lana.2022.100291]
17. Cohen J. Statistical power analysis for the behavioral sciences. UK: Routledge; 2013. [Link] [DOI:10.4324/9780203771587]
18. Hoffman G, Zhao X. A primer for conducting experiments in human-robot interaction. ACM Transactions on Human-Robot Interaction. 2020;10(1):1-31. [Link] [DOI:10.1145/3412374]
19. Jerene D, Levy J, Van Kalmthout K, Van Rest J, McQuaid CF, Quaife M, et al. Effectiveness of digital adherence technologies in improving tuberculosis treatment outcomes in four countries: A pragmatic cluster randomised trial protocol. BMJ Open. 2023;13(3):e068685. [Link] [DOI:10.1136/bmjopen-2022-068685]
20. Duko B, Bedaso A, Ayano G. The prevalence of depression among patients with tuberculosis: A systematic review and meta-analysis. Ann Gen Psychiatry. 2020;19:30. [Link] [DOI:10.1186/s12991-020-00281-8]
21. Kulchavenya E, Khomyakov V. Male genital tuberculosis in Siberians. World J Urol. 2006;24(1):74-8. [Link] [DOI:10.1007/s00345-005-0048-9]
22. Kaona FAD, Tuba M, Siziya S, Sikaona L. An assessment of factors contributing to treatment adherence and knowledge of TB transmission among patients on TB treatment. BMC Public Health. 2004;4:68. [Link] [DOI:10.1186/1471-2458-4-68]
23. Tesfahuneygn G, Medhin G, Legesse M. Adherence to anti-tuberculosis treatment and treatment outcomes among tuberculosis patients in Alamata District, northeast Ethiopia. BMC Res Notes. 2015;8:503. [Link] [DOI:10.1186/s13104-015-1452-x]
24. Fuadiati LL, Sukartini T, Makhfudli M. The effectiveness of mobile health on medication adherence in tuberculosis patients. J Telenurs. 2023;5(2):1604-13. [Indonesian] [Link] [DOI:10.31539/joting.v5i2.4234]
25. Cinderatama TA, Dianta AF, Efendi FS, Eliyen K. Web and Android-based application for monitoring tuberculosis (TB) patients in Kediri City. Matrix J Technol Inform Manag. 2021;11(1):11-25. [Link] [DOI:10.31940/matrix.v11i1.2331]
26. Arnizant TFS, Bernardi FA, Sanchez TLM, Crepaldi NY, Do Prado TN, Novaes MT, et al. My latent tuberculosis treatment-mobile application to assist in adherence to latent tuberculosis treatment. Procedia Comput Sci. 2022;196:640-6. [Link] [DOI:10.1016/j.procs.2021.12.059]
27. Wijayanti E, Bachtiar A, Achadi A, Rachmawati UA, Sjaaf AC, Eryando T, et al. Mobile application development for improving medication safety in tuberculosis patients: A quasi-experimental study protocol. PLoS One. 2022;17(9):e0272616. [Link] [DOI:10.1371/journal.pone.0272616]

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