This paper is in the following e-collection/theme issue:

Quality Evaluation and Descriptive Analysis/Reviews of Multiple Existing Mobile Apps (377) Mobile Health (mhealth) (2982)

Published on in Vol 4, No 2 (2016): Apr-Jun

Smartphone Applications to Support Tuberculosis Prevention and Treatment: Review and Evaluation

Smartphone Applications to Support Tuberculosis Prevention and Treatment: Review and Evaluation

Smartphone Applications to Support Tuberculosis Prevention and Treatment: Review and Evaluation

Authors of this article:

Sarah J Iribarren1 Author Orcid Image ;   Rebecca Schnall1 Author Orcid Image ;   Patricia W Stone1 Author Orcid Image ;   Alex Carballo-Diéguez2 Author Orcid Image
Article Authors Cited by (46) Tweetations (25) Metrics

Journals

  1. Gashu K, Gelaye K, Mekonnen Z, Lester R, Tilahun B. Does phone messaging improves tuberculosis treatment success? A systematic review and meta-analysis. BMC Infectious Diseases 2020;20(1) View
  2. Keutzer L, Wicha S, Simonsson U. Mobile Health Apps for Improvement of Tuberculosis Treatment: Descriptive Review. JMIR mHealth and uHealth 2020;8(4):e17246 View
  3. Karagöz R, Aslan F, Altındiş S, İnci M, Hatipoğlu H, Altındiş M. BİRİNCİ BASAMAKTA ÇALIŞAN HEKİMLERİN TÜBERKÜLOZ (TB) TANI VE TEDAVİSİNDE YAKLAŞIMLARININ VE BİLGİ DÜZEYİNİN DEĞERLENDİRİLMESİ. Online Türk Sağlık Bilimleri Dergisi 2017 View
  4. Shivalli S, Hondappagol A, Akshaya K, Nirgude A, Varun N, Reddy R, Sharath B. Does mobile phone instructional video demonstrating sputum expectoration improve the sputum sample quality and quantity in presumptive pulmonary TB cases? Protocol for a prospective pragmatic non-randomised controlled trial in Karnataka state, India. BMJ Open 2020;10(3):e032991 View
  5. Nouri R, R Niakan Kalhori S, Ghazisaeedi M, Marchand G, Yasini M. Criteria for assessing the quality of mHealth apps: a systematic review. Journal of the American Medical Informatics Association 2018;25(8):1089 View
  6. Chopra K, Arora V. TB care in Private Sector: Much more needed. Indian Journal of Tuberculosis 2016;63(4):217 View
  7. Nguyen L, Tran B, Rocha L, Nguyen H, Yang C, Latkin C, Thorson A, Strömdahl S. A Systematic Review of eHealth Interventions Addressing HIV/STI Prevention Among Men Who Have Sex With Men. AIDS and Behavior 2019;23(9):2253 View
  8. dos Santos L, Anselmo L, Oliveira L, Merli F, Silva C, Prado G, Crepaldi N, Bernardi F, Marçal M, R-Netto A, Rijo R, Bollela V, Alves D. TBM-App: a clinical decision support system for tuberculous meningitis. Procedia Computer Science 2019;164:565 View
  9. Park H, Lee S. International Nursing: Use of a Commercially Available Smartphone Application to Solve Information Needs of Orthopedic Scrub Nurses. Nursing Administration Quarterly 2019;43(4):337 View
  10. Iribarren S, Rodriguez Y, Lin L, Chirico C, Discacciati V, Schnall R, Demiris G. Converting and expanding a mobile support intervention: Focus group and field-testing findings from individuals in active tuberculosis treatment. International Journal of Medical Informatics 2020;136:104057 View
  11. Iribarren S, Wallingford J, Schnall R, Demiris G. Converting and expanding mobile support tools for tuberculosis treatment support: Design recommendations from domain and design experts. Journal of Biomedical Informatics 2020;112:100066 View
  12. Kumar A, De Costa A, Das A, Srinivasa G, D'Souza G, Rodrigues R. Mobile Health for Tuberculosis Management in South India: Is Video-Based Directly Observed Treatment an Acceptable Alternative?. JMIR mHealth and uHealth 2019;7(4):e11687 View
  13. Lee Y, Raviglione M, Flahault A. Use of Digital Technology to Enhance Tuberculosis Control: Scoping Review. Journal of Medical Internet Research 2020;22(2):e15727 View
  14. Udugama B, Kadhiresan P, Kozlowski H, Malekjahani A, Osborne M, Li V, Chen H, Mubareka S, Gubbay J, Chan W. Diagnosing COVID-19: The Disease and Tools for Detection. ACS Nano 2020;14(4):3822 View
  15. Laskar P, Yallapu M, Chauhan S. “Tomorrow Never Dies”: Recent Advances in Diagnosis, Treatment, and Prevention Modalities against Coronavirus (COVID-19) amid Controversies. Diseases 2020;8(3):30 View
  16. Heynsbergh N, O S, Livingston P. Assessment of Data Usage of Cancer e-Interventions (ADUCI) Framework for Health App Use of Cancer Patients and Their Caregivers: Framework Development Study. JMIR Cancer 2020;6(2):e18230 View
  17. Moulahoum H, Ghorbanizamani F, Zihnioglu F, Turhan K, Timur S. How should diagnostic kits development adapt quickly in COVID 19-like pandemic models? Pros and cons of sensory platforms used in COVID-19 sensing. Talanta 2021;222:121534 View
  18. Margineanu I, Louka C, Vincenti-Gonzalez M, Saktiawati A, Schierle J, Abass K, Akkerman O, Alffenaar J, Ranchor A, Stienstra Y. Patients and Medical Staff Attitudes Toward the Future Inclusion of eHealth in Tuberculosis Management: Perspectives From Six Countries Evaluated using a Qualitative Framework. JMIR mHealth and uHealth 2020;8(11):e18156 View
  19. Ghodake G, Shinde S, Kadam A, Saratale R, Saratale G, Syed A, Elgorban A, Marraiki N, Kim D. Biological characteristics and biomarkers of novel SARS-CoV-2 facilitated rapid development and implementation of diagnostic tools and surveillance measures. Biosensors and Bioelectronics 2021;177:112969 View
  20. Eftekhari A, Alipour M, Chodari L, Maleki Dizaj S, Ardalan M, Samiei M, Sharifi S, Zununi Vahed S, Huseynova I, Khalilov R, Ahmadian E, Cucchiarini M. A Comprehensive Review of Detection Methods for SARS-CoV-2. Microorganisms 2021;9(2):232 View
  21. Ahn E, Liu N, Parekh T, Patel R, Baldacchino T, Mullavey T, Robinson A, Kim J. A Mobile App and Dashboard for Early Detection of Infectious Disease Outbreaks: Development Study. JMIR Public Health and Surveillance 2021;7(3):e14837 View
  22. Milligan H, Iribarren S, Chirico C, Telles H, Schnall R. Insights from participant engagement with the tuberculosis treatment support tools intervention: Thematic analysis of interactive messages to guide refinement to better meet end user needs. International Journal of Medical Informatics 2021;149:104421 View
  23. KILIÇ E, AKOVA İ, HASDEMİR Ö. Birinci Basamak Sağlık Çalışanlarının Tüberküloz Bilgi Düzeylerinin Değerlendirilmesi (Sivas). STED / Sürekli Tıp Eğitimi Dergisi 2021 View
  24. Hensher M, Cooper P, Dona S, Angeles M, Nguyen D, Heynsbergh N, Chatterton M, Peeters A. Scoping review: Development and assessment of evaluation frameworks of mobile health apps for recommendations to consumers. Journal of the American Medical Informatics Association 2021;28(6):1318 View
  25. Iribarren S, Milligan H, Goodwin K, Aguilar Vidrio O, Chirico C, Telles H, Morelli D, Lutz B, Sprecher J, Rubinstein F. Mobile Tuberculosis Treatment Support Tools to Increase Treatment Success in Patients with Tuberculosis in Argentina: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2021;10(6):e28094 View
  26. Asif M, Xu Y, Xiao F, Sun Y. Diagnosis of COVID-19, vitality of emerging technologies and preventive measures. Chemical Engineering Journal 2021;423:130189 View
  27. Kowatsch T, Otto L, Harperink S, Cotti A, Schlieter H. A design and evaluation framework for digital health interventions. it - Information Technology 2019;61(5-6):253 View
  28. Duarte J, de Carvalho H, Campelo V, Feitosa L, Moura L, Hartz Z, Ribeiro I. Investigation of Contacts for Latent Mycobacterium Tuberculosis Infection: Application Software Development. The Open Nursing Journal 2021;15(1):380 View
  29. Fuad A, Herwanto G, Pertiwi A, Wahyuningtias S, Harsini H, Maula A, Putri D, Probandari A, Ahmad R. Design and prototype of TOMO: an app for improving drug resistant TB treatment adherence. F1000Research 2021;10:983 View
  30. Scrivano N, Gulino R, Giansanti D. Digital Contact Tracing and COVID-19: Design, Deployment, and Current Use in Italy. Healthcare 2021;10(1):67 View
  31. Tirdad R, Nami P, Samieyan S, Rahim F. Intelligent Alarm System-Based Devices Designed for People with Disabilities, Caused by Various Chronic Diseases. Jundishapur Journal of Chronic Disease Care 2021;10(4) View
  32. Khan J, Khan J, Ali F, Ullah F, Bacha J, Lee S. Artificial Intelligence and Internet of Things (AI-IoT) Technologies in Response to COVID-19 Pandemic: A Systematic Review. IEEE Access 2022;10:62613 View
  33. Rahayu S, Zainafree I, Merzistya A, Cahyati W, Farida E, Wandastuti A, Isbandi , Wahidah N, Saefurrohim M, Islam M, Fajri A, Subagja M. Development of the SIKRIBO Mobile Health Application for Active Tuberculosis Case Detection in Semarang, Indonesia. Healthcare Informatics Research 2022;28(4):297 View
  34. Shirmohammadi M, Razeghi S, Shamshiri A, Mohebbi S. Impact of smartphone application usage by mothers in improving oral health and its determinants in early childhood: a randomised controlled trial in a paediatric dental setting. European Archives of Paediatric Dentistry 2022;23(4):629 View
  35. Iribarren S, Milligan H, Chirico C, Goodwin K, Schnall R, Telles H, Iannizzotto A, Sanjurjo M, Lutz B, Pike K, Rubinstein F, Rhodehamel M, Leon D, Keyes J, Demiris G. Patient-centered mobile tuberculosis treatment support tools (TB-TSTs) to improve treatment adherence: A pilot randomized controlled trial exploring feasibility, acceptability and refinement needs. The Lancet Regional Health - Americas 2022;13:100291 View
  36. 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
  37. Heydari M, Mehraeen E, Javaherikiyan E, Mehrabi N, Langarizadeh M, Aghamohammadi V, Moghaddam H, Nasiri K. Design, development and evaluation of a mobile-based self-care application for patients with COVID-19 not requiring hospitalization; a study of Northwest of Iran. BMC Medical Informatics and Decision Making 2023;23(1) View
  38. Stabile A, Iribarren S, Sonney J, Demiris G, Schnall R. Usability testing of a mobile health application to support individuals with active tuberculosis: a mixed methods study. Informatics for Health and Social Care 2024;49(2):136 View
  39. Olawade D, Eberhardt J, David-Olawade A, Balogun M, Bolarinwa O, Esan D. Transforming multidrug-resistant tuberculosis care: The potentials of telemedicine in resource-limited settings. Health Sciences Review 2024;12:100185 View
  40. Mozini M, Rothschild R, Mioto A, Bernardi F, Lima V, Soares G, Segamarchi R, Alves D. OUTB: application for decision-support in the outcomes of Tuberculosis. Procedia Computer Science 2024;239:832 View
  41. 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

Books/Policy Documents

  1. Monteiro A, Millão L, de Castro Í, Cazella S, Caregnato R, Viegas K. Ambient Intelligence – Software and Applications –, 9th International Symposium on Ambient Intelligence. View
  2. Seneviratne M, Peiris D. Revolutionizing Tropical Medicine. View