Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Human Factors

Date Submitted: Apr 20, 2022
Open Peer Review Period: Apr 13, 2022 - Jun 8, 2022
Date Accepted: Aug 2, 2022
Date Submitted to PubMed: Aug 5, 2022
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

A Mobile App Leveraging Citizenship Engagement to Perform Anonymized Longitudinal Studies in the Context of COVID-19 Adverse Drug Reaction Monitoring: Development and Usability Study

Di Filippo M, Avellone A, Belingheri M, Paladino ME, Riva MA, Zambon A, Pescini D

A Mobile App Leveraging Citizenship Engagement to Perform Anonymized Longitudinal Studies in the Context of COVID-19 Adverse Drug Reaction Monitoring: Development and Usability Study

JMIR Hum Factors 2022;9(4):e38701

DOI: 10.2196/38701

PMID: 35930561

PMCID: 9640205

Mobile app to perform anonymized longitudinal studies in the context of COVID-19 adverse drug reaction monitoring, leveraging the citizenship engagement

  • Marzia Di Filippo; 
  • Alessandro Avellone; 
  • Michael Belingheri; 
  • Maria Emilia Paladino; 
  • Michele Augusto Riva; 
  • Antonella Zambon; 
  • Dario Pescini

ABSTRACT

Background:

Over the last few years, increasingly studies focused on the development of mobile apps as complementary tools to existing pharmacovigilance traditional surveillance systems for improving and facilitating adverse drug reactions reporting.

Objective:

In this study, we evaluated the potentiality of a new mobile app called vaxEffect@UniMiB in increasing the spontaneous citizenship participation to an adverse reactions drug data collection campaign. In particular, we evaluated the reporting rate of adverse reactions in a cohort of academic subjects vaccinated for COVID-19, together with its capability to enable longitudinal studies by analysing per subject time series.

Methods:

vaxEffect@UniMiB was developed for both Android and iOS devices. The mobile app asks users to send their medical history and, upon every vaccine administration, their vaccination data and the adverse symptoms that occurred within seven days after the vaccination. The app sends data over the web to an application server. The web server, along with receiving all user data, saves them in a SQL database server, and reminds patients to submit vaccine and adverse symptoms’ data by push notifications sent to the mobile app through Firebase Cloud Messaging. On initial startup of the app, a unique user identifier was generated for each respondent, so that its anonymity is completely ensured.

Results:

A total of 2733 respondents between the ages of 19 and 80 coming from the University of Milano-Bicocca and the Politecnico of Milan participated in the survey. Overall, we collected the information about vaccination and adverse reactions to the first vaccine dose for 2226 subjects (59.9%), to the second dose for 1610 subjects (43.3%), and, in a non sponsored fashion, to the third dose only for 169 individuals.

Conclusions:

vaxEffect@UniMiB revealed to be the first attempt in performing longitudinal studies to monitor the same subject over time in terms of the reported ADRs after each vaccine administration, while guaranteeing at the same time complete anonymity of the submitted data. A series of aspects contributed to a positive involvement from people in using this application to report their ADRs to vaccination: ease of use, availability from multiple platforms, anonymity of all the survey participants and protection of the submitted data.


 Citation

Please cite as:

Di Filippo M, Avellone A, Belingheri M, Paladino ME, Riva MA, Zambon A, Pescini D

A Mobile App Leveraging Citizenship Engagement to Perform Anonymized Longitudinal Studies in the Context of COVID-19 Adverse Drug Reaction Monitoring: Development and Usability Study

JMIR Hum Factors 2022;9(4):e38701

DOI: 10.2196/38701

PMID: 35930561

PMCID: 9640205

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.