Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Apr 1, 2020
Open Peer Review Period: Apr 1, 2020 - Apr 20, 2020
Date Accepted: Feb 3, 2021
(closed for review but you can still tweet)
A potential surveillance method in early detection of dengue fever outbreaks: Usability testing of an integrated mhealth app in the Philippines
ABSTRACT
Background:
The Philippines recently declared a national dengue fever (DF) epidemic. Yet, to our knowledge, there is no available integrated mhealth app for dengue fever that includes all the appropriate surveillance methods in early detection of disease outbreaks in the country.
Objective:
This study aimed to test and assess the Mozzify app in terms of the Mobile App Rating Scale (MARS) subscales: objective quality (engagement, functionality, aesthetics, information), app-subjective and app-specific qualities and compare the total app mean score ratings by socio-demographic profile and self and family DF history to see what factor is associated with high app mean score rating. We also conducted individual interviews and focus group discussions among the participants, and analyze their comments and suggestions to help structure further improvement and future development of the app.
Methods:
We have tested and assessed Mozzify, among health experts and members of the general public using the Mobile Application Rating Scale (MARS) professional and user versions (uMARS). We compared the total app mean score ratings by socio-demographic and DF history using mean difference analyses. Content analysis was used to analyse the topics raised in individual interviews and focus group discussions.
Results:
Mozzify obtained high acceptance rate and mean score ratings (>4 out of 5) in the MARS’ and uMARS’ app quality, subjective and specific scales among 979 participants (health experts n = 94; general public n = 885). Mean difference analyses revealed that total app mean score ratings were the same across ages and gender among health experts and general public. Similar results were found across income categories, and self and family DF history but not gender, among the general public. Content analyses of the topics discussed in the individual interviews and focus group discussions revealed eight major themes: suggestions on multi-language options and including other diseases; Android version availability; improvements on the app’s content, design and engagement; inclusion of users from low-income and rural areas; Wi-Fi connection and app size concerns; data credibility, and user security and privacy issues.
Conclusions:
This study confirms that Mozzify is a promising integrated strategic health intervention and surveillance system for reporting and mapping DF cases, increasing awareness, improving knowledge, and facilitating behavior change (practicing preventive measures against DF). It can be used by users of any age (>18 years), socioeconomic status and DF history. However, in spite of its many strengths and unique features, improvements that are tailored to the needs of the intended users should still be done without compromising their security and privacy. Mozzify could be an appropriate surveillance method in early detection of disease outbreaks in the Philippines and other countries where DF is endemic.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.