Abstract
BackgroundMany mobile health (mHealth) interventions have the potential to generate and store vast amounts of system-generated participant interaction data that could provide insight into user engagement, programmatic strengths, and areas that need improvement to maximize efficacy. However, despite the popularity of mHealth interventions, there is little documentation on how to use these data to monitor and improve programming or to evaluate impact.ObjectiveThis study aimed to better understand how users of the Mobile for Reproductive Health (m4RH) mHealth intervention engaged with the program in Tanzania from September 2013 to August 2016.MethodsWe conducted secondary data analysis of longitudinal data captured by system logs of participant interactions with the m4RH program from 127 districts in Tanzania from September 2013 to August 2016. Data cleaning and analysis was conducted using Stata 13. The data were examined for completeness and “correctness.” No missing data was imputed; respondents with missing or incorrect values were dropped from the analyses.ResultsThe total population for analysis included 3,673,702 queries among 409,768 unique visitors. New users represented roughly 11.15% (409,768/3,673,702) of all queries. Among all system queries for new users, 46.10% (188,904/409,768) users accessed the m4RH main menu. Among these users, 89.58% (169,218/188,904) accessed specific m4RH content on family planning, contraceptive methods, adolescent-specific and youth-specific information, and clinic locations after first accessing the m4RH main menu. The majority of these users (216,422/409,768, 52.82%) requested information on contraceptive methods; fewer users (23,236/409,768, 5.67%) requested information on clinic location. The conversion rate was highest during the first and second years of the program when nearly all users (11,246/11,470, 98.05%, and 33,551/34,830, 96.33%, respectively) who accessed m4RH continued on to query more specific content from the system. The rate of users that accessed m4RH and became active users declined slightly from 98.05% (11,246/11,470) in 2013 to 87.54% (56,696/64,765) in 2016. Overall, slightly more than one-third of all new users accessing m4RH sent queries at least once per month for 2 or more months, and 67.86% (278,088/409,768) of new and returning users requested information multiple times per month. Promotional periods were present for 15 of 36 months during the study period.ConclusionsThe analysis of the rich data captured provides a useful framework with which to measure the degree and nature of user engagement utilizing routine system-generated data. It also contributes to knowledge of how users engage with text messaging (short message service)-based health promotion interventions and demonstrates how data generated on user interactions could inform improvements to the design and delivery of a service, thereby enhancing its effectiveness.
Highlights
Mobile phones are a well-established platform for health education and behavior change, and as global levels of phone and internet access continue to rise, so does the application of mobile health approaches across multiple public health sectors [1-3]
The analysis of the rich data captured provides a useful framework with which to measure the degree and nature of user engagement utilizing routine system-generated data. It contributes to knowledge of how users engage with text messaging-based health promotion interventions and demonstrates how data generated on user interactions could inform improvements to the design and delivery of a service, thereby enhancing its effectiveness. (JMIR Mhealth Uhealth 2018;6(11):e10190) doi:10.2196/10190
Participant interactions were extracted from system logs that captured each query to the Mobile for Reproductive Health mobile health (mHealth) (m4RH) system, including respondent mobile phone number, information requested, and date and time of the query
Summary
Mobile phones are a well-established platform for health education and behavior change, and as global levels of phone and internet access continue to rise, so does the application of mobile health (mHealth) approaches across multiple public health sectors [1-3]. The analysis of mobile phone program use data allows researchers to examine information from all participants compared with traditional process evaluation approaches (such as in-depth interviews or focus group discussions and questionnaires) that collect information from a subset of program participants. It is more cost effective than other methods, and because analytics are collected in real-time, the approach improves efficiency and eliminates the potential for recall or interview bias [4,5]. Many mobile health (mHealth) interventions have the potential to generate and store vast amounts of system-generated participant interaction data that could provide insight into user engagement, programmatic strengths, and areas that need improvement to maximize efficacy. Despite the popularity of mHealth interventions, there is little documentation on how to use these data to monitor and improve programming or to evaluate impact
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
