How to accurately assess e-health user data within the cancer setting: Assessment of Data Usage of Cancer e-Interventions (ADUCI) Framework
ABSTRACT
Background:
Multimedia interventions provide a cost-effective solution to public health needs however user engagement is low. Within specific populations such as those affected by cancer, multimedia use differs from the general population. Currently there are no frameworks on how to accurately assess usage within this population group to ensure interventions are appropriate for users. A framework was developed to improve the accuracy of determining data usage. Formative work included creating data usage framework during target audience testings in the smartphone application development and analysis in a pilot study.
Objective:
The purpose of this study was to develop a framework when assessing smartphone application usage.
Methods:
The frequency, and duration, of use were compared between manual data extraction from two previous studies and the Assessment of Data Usage of Cancer e-Interventions (ADUCI) framework were applied.
Results:
Manual extraction highlighted 279 logins occurred compared to 241 when the ADUCI framework was applied. The frequency of use in each section of the app also decreased when the framework was used. The total duration of use was 91,256 seconds (25.3 hours) compared to 53,074 seconds (14.7 hours) when using the ADUCI framework. The framework identified 38 logins with no navigation, and 15 discrepancies in the data where time on specific page of the app exceed login time. Practice recommendations to improve user engagement and capturing usage data include tracking data use in external websites, having a login function on apps, creating five-star page rating functionality, using the ADUCI framework to thoroughly clean usage data and validating the framework between expected and observed use.
Conclusions:
Applying the ADUCI framework can eliminate errors and allows for an accurate analysis of usage data in eResearch projects. The framework can also improve the process of capturing accurate usage data. It provides a solid framework for usage data analysis to facilitate fact-based assessment of user engagement with apps.
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