User Engagement Metrics and Patterns in Phendo, an Endometriosis Research Mobile App

User Engagement Metrics and Patterns in Phendo, an Endometriosis Research Mobile App | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article User Engagement Metrics and Patterns in Phendo, an Endometriosis Research Mobile App Noemie Elhadad, Iñigo Urteaga, Sharon Lipsky-Gorman, Mollie McKillop This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1862924/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract We characterize short-term and long-term user engagement patterns in a self-tracking, mobile health app. We introduce and define engagement metrics to capture the quantity, duration, and density of participant engagement according to different domains of self-tracking. We focus our study on Phendo, a research app designed for participants to self-track their experiences of endometriosis ---a chronic disease in women of reproductive age. Given a cohort of Phendo participants with at least one initial week of use, we analyze their engagement patterns based on amount and timing of daily app usage and stratify them according to their short-term engagement patterns, i.e., within their first 12 weeks of app-use. Given the overall cohort and its stratified short-term participant engagement groups, we then assess overall longitudinal engagement patterns with the app beyond the first 12 weeks, as well as with disease-specific self-tracking domain types. We identify four groups of participants in the Phendo cohort (n=4,993) according to their short-term engagement: Regulars, Usuals, Occasionals, and Seldoms. Participants across the groups do not differ in disease status or demographics, except for age and education. We find that, while the stratification is based on a short-term period, the groups continue to exhibit distinct longitudinal engagement patterns in the long-term (up to 4 years). We also find that Regulars are more likely to engage with self-tracking related to disease self-management than the other groups. These findings have implications for the design of research mobile apps, as certain functionalities like tracking of self-management, might yield longer and richer engagement with certain types of participants, even if self-management is not part of the original intent of the research app. More broadly, our proposed engagement metrics and analyses provide a roadmap for exploring participant engagement patterns in mobile research apps. Full Text Additional Declarations (Not answered) Supplementary Files supplementaryinformation.pdf Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: revise 26 Aug, 2022 Review # 3 received at journal 24 Aug, 2022 Review # 1 received at journal 10 Aug, 2022 Review # 2 received at journal 10 Aug, 2022 Reviewer # 3 agreed at journal 08 Aug, 2022 Reviewer # 2 agreed at journal 20 Jul, 2022 Reviewer # 1 agreed at journal 19 Jul, 2022 Reviewers invited by journal 19 Jul, 2022 Editor assigned by journal 18 Jul, 2022 Submission checks completed at journal 18 Jul, 2022 First submitted to journal 15 Jul, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1862924","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":122396135,"identity":"db91e961-40a4-4be4-800d-d705a8535075","order_by":0,"name":"Noemie 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