Assessing User Retention of a Mobile App: Survival Analysis
| Autor: | An-Shun Tai, Si Yu Chen, Pei Hsuan Lin, Yuan Chien Pan, Chang En Hsieh, Sheng-Hsuan Lin, Yu-Hsuan Lin |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Adult
Male 020205 medical informatics Computer science Health Informatics 02 engineering and technology Information technology smartphone computer.software_genre Health development Work hours 03 medical and health sciences 0302 clinical medicine Surveys and Questionnaires 0202 electrical engineering electronic engineering information engineering Humans 030212 general & internal medicine Android (operating system) app work hours Original Paper Data collection Multimedia business.industry Mobile apps passive data user retention mobile application T58.5-58.64 Mobile Applications Survival Analysis Telemedicine Active data Active participation Global Positioning System Public aspects of medicine RA1-1270 business computer |
| Zdroj: | JMIR mHealth and uHealth, Vol 8, Iss 11, p e16309 (2020) JMIR mHealth and uHealth |
| ISSN: | 2291-5222 |
| Popis: | Background A mobile app generates passive data, such as GPS data traces, without any direct involvement from the user. These passive data have transformed the manner of traditional assessments that require active participation from the user. Passive data collection is one of the most important core techniques for mobile health development because it may promote user retention, which is a unique characteristic of a software medical device. Objective The primary aim of this study was to quantify user retention for the “Staff Hours” app using survival analysis. The secondary aim was to compare user retention between passive data and active data, as well as factors associated with the survival rates of user retention. Methods We developed an app called “Staff Hours” to automatically calculate users’ work hours through GPS data (passive data). “Staff Hours” not only continuously collects these passive data but also sends an 11-item mental health survey to users monthly (active data). We applied survival analysis to compare user retention in the collection of passive and active data among 342 office workers from the “Staff Hours” database. We also compared user retention on Android and iOS platforms and examined the moderators of user retention. Results A total of 342 volunteers (224 men; mean age 33.8 years, SD 7.0 years) were included in this study. Passive data had higher user retention than active data (P=.011). In addition, user retention for passive data collected via Android devices was higher than that for iOS devices (P=.015). Trainee physicians had higher user retention for the collection of active data than trainees from other occupations, whereas no significant differences between these two groups were observed for the collection of passive data (P=.700). Conclusions Our findings demonstrated that passive data collected via Android devices had the best user retention for this app that records GPS-based work hours. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|