Android-Based Prototype for Early Tuberculosis Detection via Clinical Symptoms

  • Liena Sofiana Public Health Departement, Faculty of Public Health, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
  • Suci Musvita Ayu Public Health Departement, Faculty of Public Health, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
  • Jefree Fahana Informatics Departement, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
  • Moh. Irma Sukarelawan Department of Physics Education, Faculty of Teacher Training and Education, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
DOI: https://doi.org/10.56338/mppki.v8i2.6577
Keywords: Mobile Application, Quality of Life, Recovery, Tuberculosis

Abstract

Background: Health technology has enormous potential for preventing and curing TB. As a result, this research aims to create a prototype of an early detection tool for clinical symptoms based on Android.

Methods: The Cure-TB application prototype is being developed through Research and Development, type 4D (Define, Design, Develop, and Disseminate). A total of 45 potential users evaluated the Cure-TB prototype utilizing 10 System Usability Scale (SUS) criteria. The SUS scale employs a five-point scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The SUS scale's item dependability is 0.91, and its Cronbach's alpha coefficient is 0.68. Prospective users' test results were examined using Rasch modelling approaches such as Logit Value of Person (LVP), Logit Value of Item (LVI), and Wright map.

Results: Cure-TB contains seven main elements that help in the treatment of tuberculosis. The seven elements provided support the role of each user, which includes patients, health staff, and the general public. The SUS test findings showed a score of 75, meaning that the Cure-TB application received good feedback from most prospective users. Feedback from users that it takes time to get used to the various features provided.

Conclusion: The Android-based Cure-TB application provides a unique option for early tuberculosis identification, enhancing patient treatment compliance and monitoring patients' side effects and nutritional condition.

References

Abas SA, Ismail N, Zakaria Y, Yasin SM, Ibrahim K, Ismail I, et al. Enhancing tuberculosis treatment adherence and motivation through gamified real-time mobile app utilization: a single-arm intervention study. BMC Public Health. 2024;24(1):1–10.

World Health Organization. Global Tuberculosis Report. Geneva; 2023. 1–57 p.

Islam F, Ahmad H, Nurbaya, Ahmad M, Ansar, Ramadhan K, et al. Factors Affecting Treatment Adherence Among Patients with Tuberculosis in Indonesia: Literature Review. J Public Heal Pharm. 2024;4(1):28–37.

Lutfiyah Ulfa S, Mardiana. Implementasi Penemuan Kasus TB Paru dalam Penanggulangan Tuberkulosis di Puskesmas Karangmalang Kota Semarang. Indones J Public Heal Nutr. 2021;1(1):31–41.

Madona A, Pratiwi EC, Adi MAB, Nugraha RP, Qinaya ZP, Arifah I, et al. Skrining Penyakit Menular Tuberculosis Pada Masyarakat di Kecamatan Kartasura Kabupaten Sukoharjo. Pros Semin Kesehat Masy. 2023;1(Oktober):191–200.

Putri FA, Suryawati C, Kusumastuti W. Evaluasi Pelaksanaan Program Penanggulangan Tuberkulosis Paru ( P2TB) Di Puskesmas Bandarharjo Kota Semarang. J Kesehat Masy. 2020;8(3):311–22.

Okunade KS, Adejimi AA, Adekanye T V., Allsop MJ, Adelabu H, Thomas-Ogodo O, et al. Impact of mobile health technologies on human papillomavirus vaccination uptake among mothers of unvaccinated girls aged 9–14 years in Lagos, Nigeria (mHealth-HPVac): study protocol of a randomised controlled trial. BMC Cancer. 2024 Jun;24(1):751.

Kang K, Park J. Dual verifications in mHealth apps: Supporting self-regulation or increasing friction? Electron Mark. 2024 Dec;34(1):36.

Kabir ZN, Tyrrell M, Konradsen H, Craftman Å, Joshi N, Gupta MK, et al. mHealth based intervention by social care professionals to support family caregivers to persons with dementia living at home in Sweden (Caregiver Connect): a randomized controlled trial. BMC Geriatr. 2024 Jun;24(1):519.

Plant A, Sparks P, Creech DN, Morgan T, Klausner JD, Rietmeijer C, et al. Developing an mHealth program to improve HIV care continuum outcomes among young Black gay and bisexual men. BMC Public Health. 2024 May;24(1):1247.

Salarvand S, Farzanpour F, Gharaei HA. The effect of personalized mobile health (mHealth) in cardiac rehabilitation for discharged elderly patients after acute myocardial infarction on their inner strength and resilience. BMC Cardiovasc Disord. 2024 Feb;24(1):116.

Sodhi R, Vatsyayan V, Panibatla V, Sayyad K, Williams J, Pattery T, et al. Impact of a pilot mHealth intervention on treatment outcomes of TB patients seeking care in the private sector using Propensity Scores Matching—Evidence collated from New Delhi, India. PLOS Digit Heal. 2024 Sep;3(9):e0000421.

Erni YR, Tombeg Z, Hadi AJ. Predisposisi Tuberkulosis Paru: A Cross Sectional Study. J Public Heal Pharm. 2021;1(1):9–13.

Tanjung SA, Wildani AA. Mobile Health Upaya Peningkatan Kepatuhan Pengobatan Pasien Anak dengan Tuberkulosis : Tinjauan Literatur. REAL Nurs J. 2021;4(3):185–96.

Abas SA, Ismail N, Zakaria Y, Ismail I, Zain NHM, Yasin SM, et al. A Gamified Real-time Video Observed Therapies (GRVOTS) Mobile App via the Modified Nominal Group Technique: Development and Validation Study. JMIR Serious Games. 2023;11.

Szkwarko D, Amisi JA, Peterson D, Burudi S, Angala P, Carter EJ. Using a mobile application to improve pediatric presumptive TB identification in western Kenya. Int J Tuberc Lung Dis. 2021;25(6):468–74.

Velen K, Nguyen TA, Pham CD, Le HT, Nguyen HB, Dao BT, et al. The effect of medication event reminder monitoring on treatment adherence of TB patients. Int J Tuberc Lung Dis. 2023 Apr;27(4):322–8.

Ngwatu BK, Nsengiyumva NP, Oxlade O, Mappin-Kasirer B, Nguyen NL, Jaramillo E, et al. The impact of digital health technologies on tuberculosis treatment: a systematic review. Eur Respir J. 2018;51(1).

Keutzer L, Wicha SG, Simonsson USH. Mobile Health Apps for Improvement of Tuberculosis Treatment: Descriptive Review. JMIR Mhealth Uhealth. 2020;8(4):1–9.

Htet KKK, Phyu AN, Thwin T, Chongsuvivatwong V. Mobile Health App for Tuberculosis Screening and Compliance to Undergo Chest X-ray Examination Among Presumptive Cases Detected by the App in Myanmar: Usability Study. JMIR Form Res. 2022;6(6):1–14.

Samiaji M, Masruroh SU, Khairani D, Nanang H, Rosyadi T, Shofi IM. Mobile Health Application Design: A User-Centered Approach for Pulmonary Tuberculosis Screening. In: 2023 11th International Conference on Cyber and IT Service Management (CITSM). IEEE; 2023. p. 1–7.

Ko Htet KK, Phyu AN, Zayar NN, Chongsuvivatwong V. Active Tuberculosis Screening via a Mobile Health App in Myanmar: Incremental Cost-Effectiveness Evaluation. JMIR Form Res. 2023;7(1):1–10.

Stadelman-Behar AM, Tiffin N, Ellis J, Creswell F V., Ssebambulidde K, Nuwagira E, et al. Diagnostic Prediction Model for Tuberculous Meningitis: An Individual Participant Data Meta-Analysis. Am J Trop Med Hyg. 2024 Sep;111(3):546–53.

Tu Phan LM, Tufa LT, Kim HJ, Lee J, Park TJ. Trends in Diagnosis for Active Tuberculosis Using Nanomaterials. Curr Med Chem. 2019 Jun;26(11):1946–59.

Rahayu SR, Zainafree I, Merzistya ANA, Cahyati WH, Farida E, Wandastuti AD, et al. Development of the SIKRIBO Mobile Health Application for Active Tuberculosis Case Detection in Semarang, Indonesia. Healthc Inform Res. 2022;28(4):297–306.

Lewis JR. The System Usability Scale: Past, Present, and Future. Int J Hum Comput Interact. 2018;34(7):577–90.

Sukarelawan MI, Jumadi J, Kuswanto H, Nurjannah T, Hikmah FN, Ramadhan MF. Implementation of Rasch Model for Mapping Students’ Metacognitive Awareness. J Pendidik Fis Indones. 2021 Nov;17(2):86–93.

Walthouwer MJL, Oenema A, Lechner L, de Vries H. Comparing a Video and Text Version of a Web-Based Computer-Tailored Intervention for Obesity Prevention: A Randomized Controlled Trial. J Med Internet Res. 2015 Oct;17(10):e236.

Yadav A, Phillips MM, Lundeberg MA, Koehler MJ, Hilden K, Dirkin KH. If a picture is worth a thousand words is video worth a million? Differences in affective and cognitive processing of video and text cases. J Comput High Educ. 2011 Apr;23(1):15–37.

Jefford M, Moore R. Improvement of informed consent and the quality of consent documents. Lancet Oncol. 2008 May;9(5):485–93.

Reži? S, Koš?evi? M. Patient informed consent – safety for the patient or the physician. Sestrin Glas. 2023 Dec;28(3):187–94.

Cocanour CS. Informed consent—It’s more than a signature on a piece of paper. Am J Surg. 2017 Dec;214(6):993–7.

Triyono EA, Mahanani M, Anggraini SD, Maulana H, Pratiwi WD, Yochanan C, et al. Early Detection of Tuberculosis Application (E-Tibi): a New Paradigm To Detect New Case of Tuberculosis. J Berk Epidemiol. 2023;11(3):267–76.

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. Metcalfe JZ, editor. PLOS Med. 2015 Sep;12(9):e1001876.

Ridho A, Alfian SD, van Boven JFM, Levita J, Yalcin EA, Le L, et al. Digital Health Technologies to Improve Medication Adherence and Treatment Outcomes in Patients With Tuberculosis: Systematic Review of Randomized Controlled Trials. J Med Internet Res. 2022 Feb;24(2):e33062.

Boone WJ, Staver JR, Yale MS. Wright Maps: First Steps. In: Rasch Analysis in the Human Sciences. Dordrecht: Springer Netherlands; 2014. p. 111–36.

Bond TG, Fox CM. Applying the Rasch Model: Fundamental Measurement in the Human Sciences. Routledge; 2015.

Afriansyah R, Lanaya D, Sari L, Azrul M, Riyadi M. Perancangan Aplikasi Re-Tuberis (Remember Tuberculosis) Dalam Pelayanan Informasi Dan Kepatuhan Penggunaan Obat. J Manaj Inf Kesehat Indones. 2023;11(2):157–64.

Althubaiti A. Information bias in health research: Definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016;9:211–7.

Biau DJ, Kernéis S, Porcher R. Statistics in brief: The importance of sample size in the planning and interpretation of medical research. Clin Orthop Relat Res. 2008;466(9):2282–8.

Published
2025-02-04
How to Cite
Sofiana, L., Suci Musvita Ayu, Jefree Fahana, & Moh. Irma Sukarelawan. (2025). Android-Based Prototype for Early Tuberculosis Detection via Clinical Symptoms. Media Publikasi Promosi Kesehatan Indonesia, 8(2), 87-97. https://doi.org/10.56338/mppki.v8i2.6577
Issue
Vol. 8 No. 2: FEBRUARY 2025 - Media Publikasi Promosi Kesehatan Indonesia
Section
Article

Copyright (c) 2025 Media Publikasi Promosi Kesehatan Indonesia (MPPKI)

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors who publish with Media Publikasi Promosi Kesehatan Indonesia retain the copyright of their work. The journal applies a Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0), which grants the following rights:

  1. Copyright Retention: Authors retain the copyright of their work, maintaining full control over their intellectual property without restrictions.

  2. Right of First Publication: Authors grant the journal the right of first publication of their work. This ensures that the work is initially published and credited in Media Publikasi Promosi Kesehatan Indonesia.

  3. License to Share and Reuse: The work is licensed under CC BY-SA 4.0, allowing others to copy, distribute, remix, and build upon the work for any purpose, even commercially, as long as proper credit is given to the authors, and any new creations are licensed under the same terms.