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

Theme Issue: Apps for COVID-19 (#Apps4Covid) (136) JMIR Theme Issue: COVID-19 Special Issue (2452) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (573) Digital Contact Tracing, Digital Proximity Tracing, Precision Public Health (148) Infectious Diseases (non-STD/STI) (1575) Innovative Methods in Public Health and Surveillance (332) Outbreak and Pandemic Preparedness and Management (1727) Surveillance Systems (462)

Published on in Vol 8, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19902, first published .
Health Observation App for COVID-19 Symptom Tracking Integrated With Personal Health Records: Proof of Concept and Practical Use Study

Health Observation App for COVID-19 Symptom Tracking Integrated With Personal Health Records: Proof of Concept and Practical Use Study

Health Observation App for COVID-19 Symptom Tracking Integrated With Personal Health Records: Proof of Concept and Practical Use Study

Authors of this article:

Keiichi Yamamoto1 Author Orcid Image ;   Tsubasa Takahashi2 Author Orcid Image ;   Miwa Urasaki3 Author Orcid Image ;   Yoichi Nagayasu4 Author Orcid Image ;   Tomonari Shimamoto5 Author Orcid Image ;   Yukiko Tateyama5 Author Orcid Image ;   Keiichi Matsuzaki5 Author Orcid Image ;   Daisuke Kobayashi5 Author Orcid Image ;   Satoshi Kubo6 Author Orcid Image ;   Shigeyuki Mito7 Author Orcid Image ;   Tatsuya Abe4 Author Orcid Image ;   Hideo Matsuura8 Author Orcid Image ;   Taku Iwami5 Author Orcid Image
Article Authors Cited by (39) Tweetations (5) Metrics

Journals

  1. Walrave M, Waeterloos C, Ponnet K. Adoption of a Contact Tracing App for Containing COVID-19: A Health Belief Model Approach. JMIR Public Health and Surveillance 2020;6(3):e20572 View
  2. Kondylakis H, Katehakis D, Kouroubali A, Logothetidis F, Triantafyllidis A, Kalamaras I, Votis K, Tzovaras D. COVID-19 Mobile Apps: A Systematic Review of the Literature. Journal of Medical Internet Research 2020;22(12):e23170 View
  3. Watanabe O, Narita N, Katsuki M, Ishida N, Cai S, Otomo H, Yokota K. Prediction Model of Deep Learning for Ambulance Transports in Kesennuma City by Meteorological Data. Open Access Emergency Medicine 2021;Volume 13:23 View
  4. Katsuki M, Narita N, Ishida N, Watanabe O, Cai S, Ozaki D, Sato Y, Kato Y, Jia W, Nishizawa T, Kochi R, Sato K, Tominaga T. Preliminary development of a prediction model for daily stroke occurrences based on meteorological and calendar information using deep learning framework (Prediction One; Sony Network Communications Inc., Japan). Surgical Neurology International 2021;12:31 View
  5. Camacho-Rivera M, Islam J, Rivera A, Vidot D. Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey. JMIR mHealth and uHealth 2020;8(12):e24693 View
  6. Runkle J, Sugg M, Graham G, Hodge B, March T, Mullendore J, Tove F, Salyers M, Valeika S, Vaughan E. Participatory COVID-19 Surveillance Tool in Rural Appalachia. Public Health Reports® 2021;136(3):327 View
  7. Dixon B, Wools-Kaloustian K, Fadel W, Duszynski T, Yiannoutsos C, Halverson P, Menachemi N, Zaller N. Symptoms and symptom clusters associated with SARS-CoV-2 infection in community-based populations: Results from a statewide epidemiological study. PLOS ONE 2021;16(3):e0241875 View
  8. Dixon B, Mukherjee S, Wiensch A, Gray M, Ferres J, Grannis S. Capturing COVID-19–Like Symptoms at Scale Using Banner Ads on an Online News Platform: Pilot Survey Study. Journal of Medical Internet Research 2021;23(5):e24742 View
  9. Raposo A, Marques L, Correia R, Melo F, Valente J, Pereira T, Rosário L, Froes F, Sanches J, Silva H. e-CoVig: A Novel mHealth System for Remote Monitoring of Symptoms in COVID-19. Sensors 2021;21(10):3397 View
  10. Xiao D, Song C, Nakamura N, Nakayama M. Development of an application concerning fast healthcare interoperability resources based on standardized structured medical information exchange version 2 data. Computer Methods and Programs in Biomedicine 2021;208:106232 View
  11. Abd-Alrazaq A, Hassan A, Abuelezz I, Ahmed A, Alzubaidi M, Shah U, Alhuwail D, Giannicchi A, Househ M. Overview of Technologies Implemented During the First Wave of the COVID-19 Pandemic: Scoping Review. Journal of Medical Internet Research 2021;23(9):e29136 View
  12. Febriansyah M, Raiz M, Zulfikar R, Agustia R. An Android-based COVID Case Monitoring Application Using a Geographic Information System to Educate the Public to be More Aware of COVID-19 Spreads. IOP Conference Series: Materials Science and Engineering 2021;1158(1):012009 View
  13. Hogan K, Macedo B, Macha V, Barman A, Jiang X. Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation. JMIR Medical Informatics 2021;9(7):e27449 View
  14. Harahap N, Handayani P, Hidayanto A. Functionalities and Issues in the Implementation of Personal Health Records: Systematic Review. Journal of Medical Internet Research 2021;23(7):e26236 View
  15. Khoshrounejad F, Hamednia M, Mehrjerd A, Pichaghsaz S, Jamalirad H, Sargolzaei M, Hoseini B, Aalaei S. Telehealth-Based Services During the COVID-19 Pandemic: A Systematic Review of Features and Challenges. Frontiers in Public Health 2021;9 View
  16. Park J, Han J, Kim Y, Rho M. Development, Acceptance, and Concerns Surrounding App-Based Services to Overcome the COVID-19 Outbreak in South Korea: Web-Based Survey Study. JMIR Medical Informatics 2021;9(7):e29315 View
  17. Cao J, Zhang G, Liu D. The Impact of Using mHealth Apps on Improving Public Health Satisfaction during the COVID-19 Pandemic: A Digital Content Value Chain Perspective. Healthcare 2022;10(3):479 View
  18. Karthan M, Martin R, Holl F, Swoboda W, Kestler H, Pryss R, Schobel J. Enhancing mHealth data collection applications with sensing capabilities. Frontiers in Public Health 2022;10 View
  19. YEKE S, SELÇUK A. COVID-19 SÜRECİNDE MOBİL SAĞLIK UYGULAMALARI: HES UYGULAMASINA YÖNELİK KRİTİK BAŞARI FAKTÖRLERİ ANALİZİ. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi 2022;12(4):1887 View
  20. Wang Z, Xiong H, Tang M, Boukhechba M, Flickinger T, Barnes L. Mobile Sensing in the COVID-19 Era: A Review. Health Data Science 2022;2022 View
  21. Thomas Craig K, Rizvi R, Willis V, Kassler W, Jackson G. Effectiveness of Contact Tracing for Viral Disease Mitigation and Suppression: Evidence-Based Review. JMIR Public Health and Surveillance 2021;7(10):e32468 View
  22. Asadi F, Rahimi F, Ghaderkhany S, Almasi S. Self‐care for coronavirus disease through electronic health technologies: A scoping review. Health Science Reports 2023;6(2) View
  23. Sayed A, Allam A, Alruwaili A, Alraey M, Elsayed E, Aloraini G. The Use of COVID-19 Surveillance Measures in Detecting Cases of Tuberculosis (TB). Hygiene 2023;3(1):1 View
  24. Harahap N, Handayani P, Hidayanto A. Barriers and facilitators of personal health record adoption in Indonesia: Health facilities’ perspectives. International Journal of Medical Informatics 2022;162:104750 View
  25. Shanbehzadeh M, Kazemi-Arpanahi H. Developing a Minimum Dataset for a Mobile-based Contact Tracing System for the COVID-19 Pandemic. Shiraz E-Medical Journal 2021;23(3) View
  26. Shimizu N, Kotani K. Health information exchange in relation to point-of-care testing in home care: Issues in Japan. Clinica Chimica Acta 2022;532:10 View
  27. Mohammad H, Elham M, Mehraeen E, Aghamohammadi V, Seyedalinaghi S, Kalantari S, Nahid M, Nasiri K. Identifying data elements and key features of a mobile-based self-care application for patients with COVID-19 in Iran. Health Informatics Journal 2021;27(4) View
  28. Quiroz-Juárez M, Torres-Gómez A, Hoyo-Ulloa I, León-Montiel R, U’Ren A, Orzechowski P. Identification of high-risk COVID-19 patients using machine learning. PLOS ONE 2021;16(9):e0257234 View
  29. Ruiz-Aquino M, Gerson Carlos Trinidad V, Alvarez-Risco A, A. Y狁ez J. Properties of a Scale of Self-Care Behaviors Facing COVID-19: An Exploratory Analysis in a Sample of University Students in Huanuco, Peru. International Journal of Mental Health Promotion 2022;24(6):959 View
  30. Alsahli S, Hor S, Lam M. Factors Influencing the Acceptance and Adoption of Mobile Health Apps by Physicians During the COVID-19 Pandemic: Systematic Review. JMIR mHealth and uHealth 2023;11:e50419 View
  31. Garavand A, Ameri F, Salehi F, Talebi A, Karbasi Z, Sabahi A, Ortega A. A Systematic Review of Health Management Mobile Applications in COVID-19 Pandemic: Features, Advantages, and Disadvantages. BioMed Research International 2024;2024:1 View
  32. Helms Y, Stein M, Hamdiui N, van der Meer A, Ferreira J, Crutzen R, Timen A, Kretzschmar M, Ayatollahi H. Determinants of Dutch public health professionals’ intention to use digital contact tracing support tools: A cross-sectional online questionnaire study. PLOS Digital Health 2024;3(2):e0000425 View
  33. Song S, Park J, Rho M. Effectiveness and intention to use a COVID-19 self-management app for epidemiological investigation: a web-based survey study. Frontiers in Public Health 2024;12 View
  34. Yamamoto K, Sakaguchi M, Onishi A, Yokoyama S, Matsui Y, Yamamoto W, Onizawa H, Fujii T, Murata K, Tanaka M, Hashimoto M, Matsuda S, Morinobu A, Kuwana M. Energy landscape analysis and time-series clustering analysis of patient state multistability related to rheumatoid arthritis drug treatment: The KURAMA cohort study. PLOS ONE 2024;19(5):e0302308 View
  35. Unim B, Zile-Velika I, Pavlovska Z, Lapao L, Peyroteo M, Misins J, Forjaz M, Nogueira P, Grisetti T, Palmieri L. The role of digital tools and emerging devices in COVID-19 contact tracing during the first 18 months of the pandemic: a systematic review. European Journal of Public Health 2024;34(Supplement_1):i11 View

Books/Policy Documents

  1. Niwa M, Hara Y. Mobile Health (mHealth). View
  2. Niwa M. Mobile Health (mHealth). View
  3. Nawaz Chohan M, Nawaz Chohan S. Machine Intelligence for Internet of Medical Things: Applications and Future Trends. View