AI analyzes texts to spot HIV risk in kenyan teens

NCT ID NCT06566417

Completed Knowledge-focused Sponsor: Massachusetts General Hospital Source: ClinicalTrials.gov ↗

First seen Jun 26, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This completed study tested whether analyzing social media messages (like WhatsApp and Instagram) from 400 young women aged 18-24 in Kisumu, Kenya could help identify those at risk for HIV. Researchers used AI to look at language patterns and compared them to standard HIV risk scores. The goal was to see if this approach could eventually be used in clinics to better target prevention tools like PrEP.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

What this could lead to: If successful, this could lead to a new way to identify young women at risk for HIV using their social media activity, helping to target prevention efforts more effectively.
What could go wrong: This was a small, completed study that only looked at associations, not a treatment. The approach may not work in real-world clinics or for other populations.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

HIV infectious disease prevention target

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

HIV PREEXPOSURE PROPHYLAXIS HIV PREVENTION

Contacts and locations

Locations

KEMRI

Kisumu, Kenya

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Other studies related to the condition(s) this trial covers.