Published on in Vol 24, No 2 (2022): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33062, first published .
Digital Health Technologies to Improve Medication Adherence and Treatment Outcomes in Patients With Tuberculosis: Systematic Review of Randomized Controlled Trials

Digital Health Technologies to Improve Medication Adherence and Treatment Outcomes in Patients With Tuberculosis: Systematic Review of Randomized Controlled Trials

Digital Health Technologies to Improve Medication Adherence and Treatment Outcomes in Patients With Tuberculosis: Systematic Review of Randomized Controlled Trials

Journals

  1. Pradipta I, Khairunnisa K, Bahar M, Kausar M, Fitriana E, Ruslami R, Aarnoutse R, Abdulah R. Knowledge, attitude and practice of community pharmacy personnel in tuberculosis patient detection: a multicentre cross-sectional study in a high-burden tuberculosis setting. BMJ Open 2022;12(7):e060078 View
  2. Shoaib M, Kainat S, Raja M, Nisar K. Design of artificial neural networks optimized through genetic algorithms and sequential quadratic programming for tuberculosis model. Waves in Random and Complex Media 2022:1 View
  3. Iskandar D, Suwantika A, Pradipta I, Postma M, van Boven J. Clinical and economic burden of drug-susceptible tuberculosis in Indonesia: national trends 2017–19. The Lancet Global Health 2023;11(1):e117 View
  4. Pradipta I, Idrus L, Probandari A, Puspitasari I, Santoso P, Alffenaar J, Hak E. Barriers to Optimal Tuberculosis Treatment Services at Community Health Centers: A Qualitative Study From a High Prevalent Tuberculosis Country. Frontiers in Pharmacology 2022;13 View
  5. Bundogji N, Toma G, Khan A. Identification of preferred reminder systems and patient factors to promote adherence in the management of urinary incontinence. PEC Innovation 2022;1:100067 View
  6. Musiimenta A, Tumuhimbise W, Atukunda E, Mugaba A, Linnemayr S, Haberer J. Digital Adherence Technologies and Mobile Money Incentives for Management of Tuberculosis Medication Among People Living With Tuberculosis: Mixed Methods Formative Study. JMIR Formative Research 2023;7:e45301 View
  7. Kardas P, Ágh T, Dima A, Goetzinger C, Potočnjak I, Wettermark B, van Boven J. Half a Century of Fragmented Research on Deviations from Advised Therapies: Is This a Good Time to Call for Multidisciplinary Medication Adherence Research Centres of Excellence?. Pharmaceutics 2023;15(3):933 View
  8. Mangan J, Woodruff R, Winston C, Nabity S, Haddad M, Dixon M, Parvez F, Sera-Josef C, Salmon-Trejo L, Lam C. Recommendations for Use of Video Directly Observed Therapy During Tuberculosis Treatment — United States, 2023. MMWR. Morbidity and Mortality Weekly Report 2023;72(12):313 View
  9. Liu X, Thompson J, Dong H, Sweeney S, Li X, Yuan Y, Wang X, He W, Thomas B, Xu C, Hu D, Vassall A, Huan S, Zhang H, Jiang S, Fielding K, Zhao Y. Digital adherence technologies to improve tuberculosis treatment outcomes in China: a cluster-randomised superiority trial. The Lancet Global Health 2023;11(5):e693 View
  10. Pradipta I, Yanuar E, Nurhijriah C, Maharani N, Subra L, Destiani D, Diantini A. Practical Models of Pharmaceutical Care for Improving Tuberculosis Patient Detection and Treatment Outcomes: A Systematic Scoping Review. Tropical Medicine and Infectious Disease 2023;8(5):287 View
  11. Alfian S, Khoiry Q, Andhika A. Pratama M, Pradipta I, Kristina S, Zairina E, Hak E, Abdulah R. Knowledge, perception, and willingness to provide telepharmacy services among pharmacy students: a multicenter cross-sectional study in Indonesia. BMC Medical Education 2023;23(1) View
  12. Iskandar D, Pradipta I, Anggriani A, Postma M, van Boven J. Multidisciplinary tuberculosis care: leveraging the role of hospital pharmacists. BMJ Open Respiratory Research 2023;10(1):e001887 View
  13. Wu Z, Lu L, Li Y, Chen J, Zhang Z, Ning C, Yuan Z, Pan Q, Shen X, Zhang W. Effect of mobile health reminders on tuberculosis treatment outcomes in Shanghai, China: A prospective cohort study. Frontiers in Public Health 2023;11 View
  14. Ramos J, Vieira M, Pimentel C, Argel M, Barbosa P, Duarte R. Building bridges: multidisciplinary teams in tuberculosis prevention and care. Breathe 2023;19(3):230092 View
  15. Jerene D, Levy J, van Kalmthout K, Rest J, McQuaid C, Quaife M, Charalambous S, Gamazina K, Garfin A, Mleoh L, Terleieva Y, Bogdanov A, Maraba N, Fielding K. 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 View
  16. Janssen S, Upton C, De Jager V, Faraj A, Pahar M, Miranda I, Diacon A, Simonsson U, Niesler T. Cough as Noninvasive Biomarker for Monitoring Tuberculosis Treatment: A Proof-of-Concept Study. Annals of the American Thoracic Society 2023;20(12):1822 View
  17. Lee S, Rajaguru V, Baek J, Shin J, Park Y. Digital Health Interventions to Enhance Tuberculosis Treatment Adherence: Scoping Review. JMIR mHealth and uHealth 2023;11:e49741 View
  18. Musiimenta A, Tumuhimbise W, Atukunda E, Mugaba A, Musinguzi N, Muzoora C, Bangsberg D, Davis J, Haberer J, Coffee M. The feasibility, acceptability, and preliminary impact of real-time monitors and SMS on tuberculosis medication adherence in southwestern Uganda: Findings from a mixed methods pilot randomized controlled trial. PLOS Global Public Health 2023;3(12):e0001813 View
  19. Maingi S, O’Malley E. Impact of text reminders on pneumatic compression device (PCD) compliance in patients with breast cancer-related lymphedema. Supportive Care in Cancer 2024;32(1) View
  20. Syarifah S, Santi D. The trial of sending short message service multidrug-resistant tuberculosis patients in Indonesia. Journal of Public Health in Africa 2023 View
  21. Cao W, Wang J, Wang Y, Hassan I, Kadir A. mHealth App to improve medication adherence among older adult stroke survivors: Development and usability study. DIGITAL HEALTH 2024;10 View
  22. Killian J, Jain M, Jia Y, Amar J, Huang E, Tambe M. New Approach to Equitable Intervention Planning to Improve Engagement and Outcomes in a Digital Health Program: Simulation Study. JMIR Diabetes 2024;9:e52688 View
  23. Haldane V, Zhang Z, Yin T, Zhang B, Li Y, Pan Q, Dainty K, Rea E, Pasang P, Hu J, Wei X. Exploring opportunities to strengthen rural tuberculosis health service delivery: a qualitative study with health workers in Tibet autonomous region, China. BMJ Open 2024;14(5):e079062 View
  24. Alfian S, Sania J, Aini D, Khoiry Q, Griselda M, Ausi Y, Zakiyah N, Puspitasari I, Suwantika A, Mahfud M, Aji S, Abdulah R, Kassianos A. Evaluation of usability and user feedback to guide telepharmacy application development in Indonesia: a mixed-methods study. BMC Medical Informatics and Decision Making 2024;24(1) View
  25. Xianyu F, Huang Y, Guo S, Chongsuvivatwong V. Evaluating Treatment Outcomes and Tuberculosis Infection Risks: A Comparative Study of Centralized Hospitalization vs. Home-Based Treatment. Tropical Medicine and Infectious Disease 2024;9(5):119 View
  26. Zary M, Mohamed M, Kafie C, Chilala C, Bahukudumbi S, Foster N, Gore G, Fielding K, Subbaraman R, Schwartzman K. The performance of digital technologies for measuring tuberculosis medication adherence: a systematic review. BMJ Global Health 2024;9(7):e015633 View
  27. Kamusheva M, Aarnio E, Qvarnström M, Hafez G, Mucherino S, Potočnjak I, Trečiokiene I, Mihajlović J, Ekenberg M, van Boven J, Leiva‐Fernandez F. Pan‐European survey on medication adherence management by healthcare professionals. British Journal of Clinical Pharmacology 2024;90(12):3135 View
  28. Sodhi R, Vatsyayan V, Panibatla V, Sayyad K, Williams J, Pattery T, Pal A, Ayatollahi H. 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 Digital Health 2024;3(9):e0000421 View
  29. Liquori G, Panattoni N, De Leo A, Dionisi S, Giannetta N, Gasperi B, Orsi G, Di Muzio F, Di Muzio M, Di Simone E. A Phenomenological Approach to Medication Adherence in Elderly Patients: A Qualitative Study. Healthcare 2024;12(19):1925 View
  30. Areas Lisboa Netto T, Diniz B, Odutola P, Dantas C, de Freitas M, Hefford P, Bes T, Pappas G. Video-observed therapy (VOT) vs directly observed therapy (DOT) for tuberculosis treatment: A systematic review on adherence, cost of treatment observation, time spent observing treatment and patient satisfaction. PLOS Neglected Tropical Diseases 2024;18(10):e0012565 View
  31. Goscé L, Tadesse A, Foster N, van Kalmthout K, Rest J, van der Wal J, Harker M, Madden N, Abdurhman T, Gadissa D, Bedru A, Dube T, Alacapa J, Mganga A, Deyanova N, Charalambous S, Letta T, Jerene D, White R, Fielding K, Houben R, McQuaid C. Modelling the epidemiological and economic impact of digital adherence technologies with differentiated care for tuberculosis treatment in Ethiopia. BMJ Global Health 2024;9(12):e016997 View

Books/Policy Documents

  1. Fielding K, Subbaraman R, Khan A, Celan C, Charalambous S, Franke M, Huddart S, Katamba A, Law S, Stagg H. Digital Respiratory Healthcare. View
  2. Dima A, Nabergoj‐Makovec U, van Boven J. Drug Utilization Research. View