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

Thomas F Scherr1, Austin Hardcastle2, Carson P Moore2

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Summary

Digital tools can improve HIV self-testing by addressing user friction points during result interpretation. Enhancing these platforms can better link individuals to care and interventions.

Keywords:
HIV self-testingMobile healthParadata

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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.