JMIR Publications

ABSTRACT

Background:

Young adults aged 18–25 in rural communities face barriers to accessing sexual and reproductive health (SRH) information, including provider shortages, clinic closures, and privacy concerns in close-knit communities. When clinical care is inaccessible, many turn to online sources of varying quality, where one analysis found that roughly 40% of birth-control video content was inaccurate or misleading. AI-enabled conversational health tools (chatbots) offer a potentially scalable, private approach to delivering SRH information; however, their implementation in rural communities may be limited by low institutional trust, privacy concerns, and the underrepresentation of rural users in AI development. SARHAchat is an AI-enabled SRH conversational health prototype developed through prior work; this protocol describes a funded study to co-design and evaluate it with rural young adults, treating trust as a design input rather than a post-deployment outcome.

Objective:

This study aims to (1) identify multilevel determinants of trust and acceptability related to AI-enabled conversational health tools among rural pregnant-capable individuals aged 18–25 in North and South Carolina; (2) co-design an enhanced SARHAchat prototype with rural stakeholders using human-centered design (HCD); and (3) evaluate the feasibility, acceptability, usability, trust, and early implementation outcomes of the enhanced prototype in a community-based pilot. The broader goal is to develop methods and provide preliminary evidence to support the responsible development and implementation of conversational AI health tools in rural and underserved communities.

Methods:

This protocol employs a 3-phase mixed-methods design, using an exploratory sequential logic to link the phases. In phase 1, we will conduct semi-structured interviews (target n=24; range 14–32 assessed for thematic saturation) with pregnant-capable individuals aged 18–25 living in HRSA-designated rural counties in NC and SC to identify determinants of trust and acceptability and develop a conceptual framework. In phase 2, we will convene 5–8 stakeholders per session across 2 iterative community feedback sessions to co-design and refine SARHAchat using HCD principles. In phase 3, we will conduct a non-randomized feasibility pilot with 75 pregnant-capable individuals aged 18–25 from HRSA-designated rural counties in NC and SC, who will be deployed on community-identified social media platforms. An explanatory sequential approach (quantitative surveys followed by qualitative interviews with a purposive subsample of 20) will assess feasibility, acceptability, usability, and implementation outcomes.

Results:

This proposal was funded in February, 2026. All three phases have been approved by the University of North Carolina at Chapel Hill Institutional Review Board 26-0669). 14 participants have been enrolled in phase 1. Phase 2 co-design activities are planned for August–October 2026, and phase 3 pilot recruitment is expected to begin in January 2027, with data collection concluding in October 2027. Findings are anticipated to be submitted for publication in spring 2028.

Conclusions:

This protocol describes a feasibility study of a community-informed AI-enabled conversational SRH tool for rural young adults. By characterizing trust-related design needs, refining a prototype through co-design, and generating preliminary feasibility, acceptability, usability, and implementation data, the study aims to establish trust-by-design methods that guide future effectiveness testing and may transfer to other sensitive health domains and underserved communities.