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Medical Consultation and HIV Testing After AI-Based Symptom Check: Retrospective Cohort Study
Nao Taguchi1, Kunihiro Hirahara1, Keisuke Harada1
1Gilead Sciences K.K., Chiyoda-ku, Tokyo, Japan.
Journal of Medical Internet Research
|June 18, 2026
Summary
Early HIV testing is crucial. An AI symptom checker increased HIV testing intention by 29% and identified factors influencing medical consultation for high-risk individuals.
Area of Science:
- Public Health
- Digital Health
- Infectious Disease Epidemiology
Background:
- Early HIV testing and detection are vital public health goals.
- In Japan, a significant portion of AIDS diagnoses occur late.
- Understanding barriers to HIV testing among high-risk individuals is limited.
Purpose of the Study:
- To analyze factors influencing medical consultation and HIV testing.
- To explore reasons for delayed HIV testing.
- To assess the impact of AI-driven health information on testing behavior.
Main Methods:
- Retrospective cohort study using AI symptom checker data (Ubie).
- Analysis of individuals whose symptom searches suggested HIV/AIDS/STI.
- Multivariable logistic regression to identify factors associated with consultation and testing.
Main Results:
- Older age groups showed a higher tendency for medical consultation.
- AI-provided awareness information correlated with seeking medical consultation.
- 29% of individuals initially hesitant to test expressed intent after AI interaction.
- Gynecology departments showed higher association with HIV testing than internal medicine.
Conclusions:
- AI symptom checkers can enhance awareness and consideration of medical consultation for potential HIV cases.
- Refining educational content and improving physician awareness of HIV testing are crucial for increasing testing rates.
- Targeted interventions are needed, especially within STI-related condition subgroups.
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