# Evaluation of an Artificial Intelligence Conversational Chatbot to Enhance HIV Preexposure Prophylaxis Uptake: Development and Usability Internal Testing

**Authors:** Jun Tao, Ellie Pavlick, Amaris Grondin, Josue D Bustamante, Harrison Martin, Hannah Parent, Natalie Fenn, Alexi Almonte, Amanda Maguire-Wilkerson, Mofan Gu, Jack Rusley, Bryce K Perler, Tyler Wray, Amy S Nunn, Philip A Chan

PMC · DOI: 10.2196/79671 · Journal of Medical Internet Research · 2026-02-03

## TL;DR

This study developed and tested a chatbot called CHIA to help increase HIV prevention and PrEP uptake among men who have sex with men using motivational interviewing techniques in English and Spanish.

## Contribution

The paper introduces CHIA, an AI chatbot trained to deliver motivational interviewing-based counseling for PrEP in both English and Spanish.

## Key findings

- CHIA performed well in general response quality metrics like up-to-dateness and trustworthiness in both languages.
- Spanish responses scored lower on motivational interviewing-based metrics compared to English responses.
- The chatbot showed potential for promoting HIV prevention but needs improvement in Spanish language performance.

## Abstract

The HIV epidemic in the United States disproportionately impacts gay, bisexual, and other men who have sex with men (MSM). Despite the effectiveness of HIV preexposure prophylaxis (PrEP) in preventing HIV acquisition, uptake among MSM remains suboptimal. Motivational interviewing (MI) has demonstrated efficacy at increasing PrEP uptake among MSM but is resource-intensive, limiting scalability. The use of artificial intelligence, particularly large language models with conversational agents (ie, “chatbots”) such as ChatGPT, may offer a scalable approach to delivering MI-based counseling for PrEP and HIV prevention.

This internal usability testing aimed to evaluate the development of an artificial intelligence–based chatbot, including its ability to provide MI-aligned education about PrEP and HIV prevention and potential to support PrEP uptake.

The Chatbot for HIV Prevention and Action (CHIA) was built on a GPT-4o base model embedded with a validated knowledge database on HIV and PrEP in English and Spanish. The CHIA was fine-tuned through training on a large MI dataset and prompt engineering. The use of the AutoGen multiagent framework enabled the CHIA to integrate 2 agents, the PrEP Counselor Agent and the Assistant Agent, which specialized in providing MI-based counseling and handling function calls (eg, assessment of HIV risk), respectively. During internal testing from March 10-April 28, 2025, we systematically evaluated the CHIA’s performance in English and Spanish using a set of 5-point Likert scales to measure accuracy, conciseness, up-to-dateness, trustworthiness, and alignment with aspects of the MI spirit (eg, collaboration, autonomy support) and MI-consistent behaviors (eg, affirmation, open-ended questions). Descriptive statistics and mixed linear regression were used to analyze the data.

A total of 296 responses, including 145 English responses and 151 Spanish responses, were collected during the internal testing period. Overall, the CHIA demonstrated strong performance across both languages, receiving the highest combined scores in the general response quality metrics including up-to-dateness (mean 4.6, SD 0.8), trustworthiness (mean 4.5, SD 0.9), accuracy (mean 4.4, SD 0.9), and conciseness (mean 4.2, SD 1.1). The CHIA generally received higher combined scores for metrics that assessed alignment with the MI spirit (ie, empathy, evocation, autonomy support, and collaboration) and lower combined scores for MI-consistent behaviors (ie, affirmation, open-ended questions, and reflections). Spanish responses had significantly lower mean scores than English responses across nearly all MI-based metrics.

Our internal usability testing highlights the potential of the CHIA as a viable tool for delivering MI-aligned counseling in English and Spanish to promote HIV prevention and support PrEP uptake, though its Spanish language performance requires further improvement.

## Full-text entities

- **Species:** Human immunodeficiency virus 1 (no rank) [taxon 11676], Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

61 references — full list in the complete paper: https://tomesphere.com/paper/PMC12867473/full.md

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Source: https://tomesphere.com/paper/PMC12867473