Detailed HIV Self-Testing Patterns Derived from Paradata in the mLab App Clinical Trial

Area of Science:

• Public Health
• Digital Health
• HIV Prevention

Background:

• HIV self-testing is crucial for public health, offering accessibility and privacy.
• Digital platforms can potentially bridge the gap in linking self-testers to the HIV care continuum.
• Challenges remain in ensuring self-testing effectively connects individuals to necessary interventions.

Purpose of the Study:

• To analyze user behavior within a mobile health app (mLab App) during HIV self-test result interpretation.
• To identify friction points in the digital HIV self-testing workflow.
• To provide insights for improving digital tools supporting HIV testing and care linkage.

Main Methods:

• Collected screen-level paradata from users interacting with the mLab App during HIV self-testing.
• Focused analysis on user behavior during the test-result interpretation workflow.
• Examined the impact of discordant automated results on user engagement and future testing.

Main Results:

• 330 HIV self-tests were completed in the app; 74.2% within the scheduled window.
• Three specific screens (Preview Test, Upload Picture, Visual Result) caused 60.6% of incomplete tests.
• Discordant automated results reduced subsequent engagement but did not significantly change future testing frequency.

Conclusions:

• Specific user interface elements in digital HIV self-testing tools can create significant friction.
• Understanding these friction points is key to optimizing digital health interventions for HIV.
• Design improvements in digital platforms can enhance accurate testing and linkage to care for HIV.