User Engagement in Mobile Health Applications
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Abstract (arXiv)
Mobile health apps are revolutionizing the healthcare ecosystem by improving communication, efficiency, and quality of service. In low- and middle-income countries, they also play a unique role as a source of information about health outcomes and behaviors of patients and healthcare workers, while providing a suitable channel to deliver both personalized and collective policy interventions. We propose a framework to study user engagement with mobile health, focusing on healthcare workers and digital health apps designed to support them in resource-poor settings. The behavioral logs produced by these apps can be transformed into daily time series characterizing each user's activity. We use probabilistic and survival analysis to build multiple personalized measures of meaningful engagement, which could serve to tailor content and digital interventions suiting each health worker's specific needs. Special attention is given to the problem of detecting churn, understood as a marker of complete disengagement. We discuss the application of our methods to the Indian and Ethiopian users of the Safe Delivery App, a capacity-building tool for skilled birth attendants. This work represents an important step towards a full characterization of user engagement in mobile health applications, which can significantly enhance the abilities of health workers and, ultimately, save lives.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 9 of its 30 references that are in the map. First posted on arXiv 16 Jun 2022.
Builds on
9 of 30 references.
References · 9
- 2017Churn Prediction in Mobile Social Games: Towards a Complete Assessment Using Survival Ensemblescited by 11
- 2021Midwifery Learning and Forecasting: Predicting Content Demand with User-Generated Logscited by 6
- 2016Survival trees for left-truncated and right-censored data, with application to time-varying covariate datacited by 5
- 2021A Recommendation System to Enhance Midwives' Capacities in Low-Income Countriescited by 5
- 2020A Time Series Approach To Player Churn and Conversion in Videogamescited by 2
- 2022Churn prediction in online gamblingcited by 2
- 2019Understanding Player Engagement and In-Game Purchasing Behavior with Ensemble Learningcited by 1
- 2021Unpacking Adherence and Engagement in Pervasive Health Gamescited by 1
- 2021Investigating behavior change indicators and cognitive measures in persuasive health gamescited by 1
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1.
2 papers.