Your browser doesn't support javascript.
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, Marzia; Avellone, Alessandro; Belingheri, Michael; Paladino, Maria Emilia; Riva, Michele Augusto; Zambon, Antonella; Pescini, Dario.
  • Di Filippo M; Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.
  • Avellone A; Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.
  • Belingheri M; School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
  • Paladino ME; School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
  • Riva MA; School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
  • Zambon A; Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.
  • Pescini D; Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.
JMIR Hum Factors ; 9(4): e38701, 2022 Nov 04.
Article in English | MEDLINE | ID: covidwho-2109558
ABSTRACT

BACKGROUND:

Over the past few years, studies have increasingly focused on the development of mobile apps as complementary tools to existing traditional pharmacovigilance surveillance systems for improving and facilitating adverse drug reaction (ADR) reporting.

OBJECTIVE:

In this research, we evaluated the potentiality of a new mobile app (vaxEffect@UniMiB) to perform longitudinal studies, while preserving the anonymity of the respondents. We applied the app to monitor the ADRs during the COVID-19 vaccination campaign in a sample of the Italian population.

METHODS:

We administered vaxEffect@UniMiB to a convenience sample of academic subjects vaccinated at the Milano-Bicocca University hub for COVID-19 during the Italian national vaccination campaign. 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 ADRs that occurred within 7 days postvaccination, making it possible to follow the ADR dynamics for each respondent. The app sends data over the web to an application server. The server, along with receiving all user data, saves the data in a SQL database server and reminds patients to submit vaccine and ADR data by push notifications sent to the mobile app through Firebase Cloud Messaging (FCM). On initial startup of the app, a unique user identifier (UUID) was generated for each respondent, so its anonymity was completely ensured, while enabling longitudinal studies.

RESULTS:

A total of 3712 people were vaccinated during the first vaccination wave. A total of 2733 (73.6%) respondents between the ages of 19 and 80 years, coming from the University of Milano-Bicocca (UniMiB) and the Politecnico of Milan (PoliMi), participated in the survey. Overall, we collected information about vaccination and ADRs to the first vaccine dose for 2226 subjects (60.0% of the first dose vaccinated), to the second dose for 1610 subjects (43.4% of the second dose vaccinated), and, in a nonsponsored fashion, to the third dose for 169 individuals (4.6%).

CONCLUSIONS:

vaxEffect@UniMiB was 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 complete anonymity of the subject. A series of aspects contributed to the positive involvement from people in using this app to report their ADRs to vaccination ease of use, availability from multiple platforms, anonymity of all survey participants and protection of the submitted data, and the health care workers' support.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Topics: Vaccines Language: English Journal: JMIR Hum Factors Year: 2022 Document Type: Article Affiliation country: 38701

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Topics: Vaccines Language: English Journal: JMIR Hum Factors Year: 2022 Document Type: Article Affiliation country: 38701