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

mHealth for Data Collection and Research (955) Infectious Diseases (non-STD/STI) (1575) Influenza and Influenza-Like-Illness (ILI) Surveillance (217) Participatory Epidemiology and Surveillance (119) Surveillance Systems (462)

Published on in Vol 6, No 6 (2018): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9834, first published .
A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study

A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study

A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study

Authors of this article:

Kazutoshi Fujibayashi1 Author Orcid Image ;   Hiromizu Takahashi1 Author Orcid Image ;   Mika Tanei1 Author Orcid Image ;   Yuki Uehara1 Author Orcid Image ;   Hirohide Yokokawa1 Author Orcid Image ;   Toshio Naito1 Author Orcid Image
Article Authors Cited by (20) Tweetations (3) Metrics

Journals

  1. Inomata T, Iwagami M, Nakamura M, Shiang T, Yoshimura Y, Fujimoto K, Okumura Y, Eguchi A, Iwata N, Miura M, Hori S, Hiratsuka Y, Uchino M, Tsubota K, Dana R, Murakami A. Characteristics and Risk Factors Associated With Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application. JAMA Ophthalmology 2020;138(1):58 View
  2. Aslani N, Lazem M, Mahdavi S, Garavand A. A Review of Mobile Health Applications in Epidemic and Pandemic Outbreaks: Lessons Learned for COVID-19. Archives of Clinical Infectious Diseases 2020;15(4) View
  3. Kim M, Yune S, Chang S, Jung Y, Sa S, Han H. The Fever Coach Mobile App for Participatory Influenza Surveillance in Children: Usability Study. JMIR mHealth and uHealth 2019;7(10):e14276 View
  4. Inomata T, Sung J, Nakamura M, Fujisawa K, Muto K, Ebihara N, Iwagami M, Fujio K, Okumura Y, Okano M, Murakami A. New medical big data for P4 medicine on allergic conjunctivitis. Allergology International 2020;69(4):510 View
  5. Leal Neto O, Cruz O, Albuquerque J, Nacarato de Sousa M, Smolinski M, Pessoa Cesse E, Libel M, Vieira de Souza W. Participatory Surveillance Based on Crowdsourcing During the Rio 2016 Olympic Games Using the Guardians of Health Platform: Descriptive Study. JMIR Public Health and Surveillance 2020;6(2):e16119 View
  6. Kleber G, Alves D, Paiva J, Diógenes D, Valentim R, Medeiros A. SOS Syphilis: smartphone application for the mapping of syphilis attention networks.. Procedia Computer Science 2021;181:434 View
  7. Inomata T, Sung J, Nakamura M, Iwagami M, Okumura Y, Iwata N, Midorikawa-Inomata A, Fujimoto K, Eguchi A, Nagino K, Fujio K, Miura M, Shokirova H, Murakami A. Using Medical Big Data to Develop Personalized Medicine for Dry Eye Disease. Cornea 2020;39(1):S39 View
  8. Asadzadeh A, Kalankesh L. A scope of mobile health solutions in COVID-19 pandemics. Informatics in Medicine Unlocked 2021;23:100558 View
  9. Nishioka Y, Noda T, Okada S, Myojin T, Kubo S, Higashino T, Nakajima H, Sugiyama T, Ishii H, Imamura T. Association between influenza and the incidence rate of new‐onset type 1 diabetes in Japan. Journal of Diabetes Investigation 2021;12(10):1797 View
  10. Salehinejad S, Niakan Kalhori S, Hajesmaeel Gohari S, Bahaadinbeigy K, Fatehi F. A review and content analysis of national apps for COVID-19 management using Mobile Application Rating Scale (MARS). Informatics for Health and Social Care 2021;46(1):42 View
  11. Zhang M, Chow A, Ho R, Smith H. An Overview of Commercially Available Apps in the Initial Months of the COVID-19 Pandemic. Frontiers in Psychiatry 2021;12 View
  12. Zigman Suchsland M, Rahmatullah I, Lutz B, Lyon V, Huang S, Kline E, Graham C, Cooper S, Su P, Smedinghoff S, Chu H, Sewalk K, Brownstein J, Thompson M. Evaluating an app-guided self-test for influenza: lessons learned for improving the feasibility of study designs to evaluate self-tests for respiratory viruses. BMC Infectious Diseases 2021;21(1) View
  13. Chen Q, Tsubaki M, Minami Y, Fujibayashi K, Yumoto T, Kamei J, Yamada Y, Kominato H, Oono H, Naito T. Using Mobile Phone Data to Estimate the Relationship between Population Flow and Influenza Infection Pathways. International Journal of Environmental Research and Public Health 2021;18(14):7439 View
  14. Narayan K, Nayak M. Community Based Self-Administered Syndromic Surveillance Mobile Application – A Strategic Approach to Monitor COVID Situation at Micro Level. National Journal of Community Medicine 2022;11(10):395 View
  15. Hasan N, Bao Y, Chiong R. A multi-method analytical approach to predicting young adults’ intention to invest in mHealth during the COVID-19 pandemic. Telematics and Informatics 2022;68:101765 View
  16. Sharma S, Kumari B, Ali A, Yadav R, Sharma A, Sharma K, Hajela K, Singh G. Mobile technology. Journal of Family Medicine and Primary Care 2022;11(1):37 View
  17. Atkins N, Harikar M, Duggan K, Zawiejska A, Vardhan V, Vokey L, Dozier M, de los Godos E, Mcswiggan E, Mcquillan R, Theodoratou E, Shi T. What are the characteristics of participatory surveillance systems for influenza-like-illness?. Journal of Global Health 2023;13 View
  18. Amiri P, Nadri H, Bahaadinbeigy K. Facilitators and barriers of mHealth interventions during the Covid-19 pandemic: systematic review. BMC Health Services Research 2023;23(1) View

Books/Policy Documents

  1. Niwa M, Hara Y. Mobile Health (mHealth). View