Literature DB >> 34936526

Identifying data elements and key features of a mobile-based self-care application for patients with COVID-19 in Iran.

Heydari Mohammad1, Monaghesh Elham2, Esmaeil Mehraeen3, Vahideh Aghamohammadi4, Seyedahmad Seyedalinaghi5, Saieed Kalantari6, Mehrabi Nahid7, Khadije Nasiri8.   

Abstract

Mobile Health applications have shown different usages in the COVID-19 pandemic, which consisted of empowering patient's awareness, promoting patient's self-care, and self-monitor behaviors. The purpose of this study is to identify key features and capabilities of a mobile-based application for self-care and self-management of people with COVID-19 disease. This study was a descriptive-analytical study that was conducted in two main phases in 2020. In the first phase, a literature review study was performed. In the second phase, using the information obtained from the review of similar articles, a questionnaire was designed to validate identified requirements. Based on the results of the first phase, 53 data elements and technical key features for mobile-based self-care application for people with COVID-19 were identified. According to the statistical population, 11 data elements for demographic requirements, 11 data elements for clinical requirements, 15 data elements for self-care specifications, and 16 features for the technical capability of this app were determined. Most of the items were selected by infectious and internal medicine specialists (94%). This study supports that the use of mobile-based applications can play an important role in the management of this disease. Software design and development could help manage and improve patients' health status.

Entities:  

Keywords:  COVID-19; Self-care; application; mobile; mobile health

Mesh:

Year:  2021        PMID: 34936526     DOI: 10.1177/14604582211065703

Source DB:  PubMed          Journal:  Health Informatics J        ISSN: 1460-4582            Impact factor:   2.681


  4 in total

1.  COVID-19: Detecting depression signals during stay-at-home period.

Authors:  Jean Marie Tshimula; Belkacem Chikhaoui; Shengrui Wang
Journal:  Health Informatics J       Date:  2022 Apr-Jun       Impact factor: 2.934

2.  Individual Factors Associated With COVID-19 Infection: A Machine Learning Study.

Authors:  Tania Ramírez-Del Real; Mireya Martínez-García; Manlio F Márquez; Laura López-Trejo; Guadalupe Gutiérrez-Esparza; Enrique Hernández-Lemus
Journal:  Front Public Health       Date:  2022-06-30

Review 3.  Internet of things in the management of chronic diseases during the COVID-19 pandemic: A systematic review.

Authors:  Ahmadreza Shamsabadi; Zahra Pashaei; Amirali Karimi; Pegah Mirzapour; Kowsar Qaderi; Mahmoud Marhamati; Alireza Barzegary; Amirata Fakhfouri; Esmaeil Mehraeen; SeyedAhmad SeyedAlinaghi; Omid Dadras
Journal:  Health Sci Rep       Date:  2022-03-14

4.  Early Warning of Infectious Diseases in Hospitals Based on Multi-Self-Regression Deep Neural Network.

Authors:  Mengying Wang; Cuixia Lee; Wei Wang; Yingyun Yang; Cheng Yang
Journal:  J Healthc Eng       Date:  2022-08-18       Impact factor: 3.822

  4 in total

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