Datamama, bringing pregnancy research into the future: design, development, and evaluation of a citizen science pregnancy mobile application

Abstract

Background: Pregnancy mobile applications (apps) have grown in popularity over the past decade, with some being used to promote study recruitment or health behaviors. However, no app serves as an all-in-one solution for collecting general data for research purposes and providing women with useful and desirable features. Aim: To create and develop a Swiss pregnancy mobile app as an innovative means to collect research data and provide users with reliable information. Methods: Determining the key features of the app involved a review of the literature and assessment of popular apps in the Swiss AppStore. A team of engineers developed the app, which includes a pregnancy timeline, questionnaires for data collection, medical and psychological articles and a checklist with appointment reminders. The content was written and reviewed by healthcare providers considered experts in the topics adressed. The questionnaires are distributed based on the user's gestational age, by a chatbot. The project was authorized by the ethics commission in the canton of Vaud. An online survey of ten questions, advertised on Datamama's home screen, was conducted to assess the users' use of the app (27.11- 19.12.2022). Results: A review of 84 articles and 25 popular apps showed the need for a comprehensive pregnancy app. The development of Datamama took 2 years and included the creation of 70 medical and psychological articles and 29 questionnaires covering 300 unique variables. Six months after the launch, there were 800 users with a 73% average participation rate in the questionnaires. Sixty-five women completed the survey, with 70.8% using the app once to multiple times per week. The primary reason for using the app was to help research by answering the questionnaires, followed by access to reliable medical information. The reason most frequently ranked first for using the app was to help research by answering the questionnaires (42/65, 67% of women rated it first), followed by access to reliable medical information (34/65, 54% women rated it second). Women rated the information as clear, understandable, and interesting with a trust rating in data handling at 98.5%. The average grade for recommending the app was 8/10, with suggestions for increasing the amount of medical content and tailoring it based on gestational age. Conclusion: Datamama is the first pregnancy app to address the needs of both patients and researchers. Initial feedback from users was positive, highlighting future challenges for success. Future work will consist in improving the app, validating the data and use it to answer specific pregnancy-related research questions.

Keywords: digital health (eHealth); electronic databases; mobile application; pharmacoepidemiology; pregnancy.

FIGURE 1

Wireframes of Datamama minimal viable product.

FIGURE 2

Screenshots of the information page and medical articles on Datamama. Left page is the information page, common to all users, divided in three main parts: at the top, a monthly blog; in the middle, “Ma grossesse” (“My pregnancy”) divided into two pages of medical articles: i.e., “Symptômes & Maladies” (“Symptoms and diseases”) and “Accouchement & postpartum” (“Delivery and Post-Partum”); and at the bottom, “Mon bien-être” (“My wellbeing”) divided into two pages of medical articles “Activité & Alimentation” (“Activity and nutrition”) and “Médicaments & Substances” (“Medication and substances”). The middle page consists of the “Symptoms and diseases”. Medical articles related to this category are sorted by alphabetical order. A search engine allows users to search by keywords. On the right page, an example of a specific article on the topic of folic acid is shown.

FIGURE 3

Screenshots of the survey tool on Datamama. The left page illustrates a question sent by the chatbot; the right page illustrates answers provided by the user. The different colours help distinguish between answers and questions, similarly to common messaging services.

FIGURE 4

Screenshots of the gamification strategy and leaderboard. The left page illustrates the visualization of the user’s own data (i.e., research status, time since first collection, participation rate) and the community’s data (i.e., cumulated data collection time, participation rate). The right page illustrates an example of a monthly contest with the type of reward offered and overview of the users with the highest ranking. Users may choose to participate to the contest and to visualize this data or not.

FIGURE 5

Screenshots of the identity and general design of datamama. The left page shows the loading page; the three next pages are explanations of the app’s purposes before subscription.