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Article

From Symptom Tracking to Contact Tracing: A Framework to Explore and Assess COVID-19 Apps

1
Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
2
Medical Center, Vanderbilt University, Nashville, TN 37232, USA
*
Author to whom correspondence should be addressed.
Future Internet 2020, 12(9), 153; https://doi.org/10.3390/fi12090153
Received: 6 August 2020 / Revised: 2 September 2020 / Accepted: 3 September 2020 / Published: 8 September 2020
(This article belongs to the Special Issue Recent Advances of Machine Learning Techniques on Smartphones)
Smartphone applications related to coronavirus disease 2019 (COVID-19) continue to emerge and evolve, but despite a wide variety of different app functions, there has yet to be a comprehensive study of what the most prevalent publicly available apps provide, and there exists no standardized evaluation system for end users to determine the safety and efficacy of an app before they download it. Furthermore, limited oversight means that the rapidly growing space creates challenges for end users trying to find a relevant app. We adapted the M-Health Index and Navigation Database (MIND) from apps.digitalpsych.org that previously has been used to evaluate mental health applications to guide the assessment of COVID apps. Using this framework, we conducted a thorough analysis of the top-100 returned coronavirus apps on two separate dates a month apart to understand the clinical utility and features of COVID-19 apps and how these change in a short period of time. We ultimately identified a significant turnover rate, as well as privacy concerns around lack of privacy policies and disclosure of personal information. Our research offers insight into the current status of COVID-19 apps and provides a comprehensive and adaptable framework to help individuals assess the growing number of such digital tools in the wake of the pandemic. View Full-Text
Keywords: COVID-19; smartphone; health apps COVID-19; smartphone; health apps
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MDPI and ACS Style

Ramakrishnan, A.M.; Ramakrishnan, A.N.; Lagan, S.; Torous, J. From Symptom Tracking to Contact Tracing: A Framework to Explore and Assess COVID-19 Apps. Future Internet 2020, 12, 153. https://doi.org/10.3390/fi12090153

AMA Style

Ramakrishnan AM, Ramakrishnan AN, Lagan S, Torous J. From Symptom Tracking to Contact Tracing: A Framework to Explore and Assess COVID-19 Apps. Future Internet. 2020; 12(9):153. https://doi.org/10.3390/fi12090153

Chicago/Turabian Style

Ramakrishnan, Abinaya M., Aparna N. Ramakrishnan, Sarah Lagan, and John Torous. 2020. "From Symptom Tracking to Contact Tracing: A Framework to Explore and Assess COVID-19 Apps" Future Internet 12, no. 9: 153. https://doi.org/10.3390/fi12090153

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