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一款利用公民参与在新冠疫情药物不良反应监测背景下进行匿名纵向研究的移动应用程序:开发与可用性研究

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.

作者信息

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

机构信息

Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy.

School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.

出版信息

JMIR Hum Factors. 2022 Nov 4;9(4):e38701. doi: 10.2196/38701.

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.

摘要

背景

在过去几年中,研究越来越多地聚焦于开发移动应用程序,作为现有传统药物警戒监测系统的补充工具,以改进和促进药物不良反应(ADR)报告。

目的

在本研究中,我们评估了一款新的移动应用程序(vaxEffect@UniMiB)进行纵向研究的潜力,同时保护受访者的匿名性。我们应用该应用程序在意大利人群样本中监测新冠疫苗接种活动期间的药物不良反应。

方法

我们将vaxEffect@UniMiB应用于意大利全国疫苗接种活动期间在米兰比可卡大学中心接种新冠疫苗的学术人员便利样本。vaxEffect@UniMiB针对安卓和iOS设备开发。该移动应用程序要求用户发送其病史,并在每次接种疫苗后,发送其接种数据以及接种后7天内出现的药物不良反应,从而能够跟踪每个受访者的药物不良反应动态。该应用程序通过网络将数据发送到应用服务器。服务器在接收所有用户数据的同时,将数据保存在SQL数据库服务器中,并通过Firebase云消息传递(FCM)发送到移动应用程序的推送通知提醒患者提交疫苗和药物不良反应数据。在应用程序首次启动时,为每个受访者生成一个唯一的用户标识符(UUID),因此在确保纵向研究的同时,完全保证了其匿名性。

结果

在第一轮疫苗接种期间,共有3712人接种了疫苗。共有2733名(73.6%)年龄在19岁至80岁之间、来自米兰比可卡大学(UniMiB)和米兰理工大学(PoliMi)的受访者参与了调查。总体而言,我们收集了2226名受试者(占接种第一剂疫苗人数的60.0%)第一剂疫苗接种和药物不良反应的信息,1610名受试者(占接种第二剂疫苗人数的43.4%)第二剂疫苗接种和药物不良反应的信息,以及以非赞助方式收集了169名个体(占接种第三剂疫苗人数的4.6%)第三剂疫苗接种和药物不良反应的信息。

结论

vaxEffect@UniMiB被证明是首次尝试进行纵向研究,以监测同一受试者在每次疫苗接种后报告的药物不良反应随时间的变化,同时保证受试者的完全匿名性。一系列因素促使人们积极参与使用该应用程序报告其疫苗接种后的药物不良反应:易用性、多平台可用性、所有调查参与者的匿名性和提交数据的保护,以及医护人员的支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b25c/9640205/e391bc3b0b93/humanfactors_v9i4e38701_fig1.jpg

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