Accepted for/Published in: JMIR Formative Research
Date Submitted: Jan 29, 2026
Date Accepted: Jun 29, 2026
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Human-centered Design of a Multi-stakeholder Reporting Dashboard: Improving HIV Implementation Science
ABSTRACT
Background:
Information dashboards can synthesize and present implementation research data in actionable formats, but their utility depends on careful alignment with user needs and priorities, which human-centered design methods aim to address. The Ending the HIV Epidemic (EHE) initiative aims to reduce new HIV infections in the United States by 90% by 2030, yet research findings that could advance this effort are often poorly applied in practice due to limited engagement of diverse stakeholders.
Objective:
We describe the design, development, and iterative testing of the EHE Implementation Science Reporting Dashboard, a publicly accessible tool intended to collate and visualize HIV implementation science studies conducted in EHE priority jurisdictions. We aimed to document how HCD methods informed dashboard content, structure, and functionality for multiple stakeholder groups involved in the EHE initiative.
Methods:
We used an HCD approach guided by the Design Council’s Double Diamond framework (Discover, Define, Develop, Deliver) to conceptualize and operationalize the dashboard. In the Discover phase, we conducted preliminary consultations and synthesized insights into a dashboard concept, five primary user groups, and five core use cases. In the Define phase, we identified an initial set of EHE implementation science publications (n=15), developed a theory-informed and inductively refined extraction tool, and organized data into a structured online database. In the Develop phase, we created wireframes, storyboarded user journeys, and produced a low-fidelity Python prototype. In the Deliver phase, we conducted user-testing sessions (n=14) across three rounds with purposively sampled participants representing the five user groups and used structured translation tables to convert feedback into design adaptations.
Results:
The HCD process clarified that a single dashboard would need to serve distinct user priorities, leading to a data architecture organized around study design, populations, outcomes, and community engagement that could support rapid research review while supporting implementation efforts among partners. Prototyping and user testing identified several key areas for refinement, including the need for clearer explanations of the dashboard’s purpose, more intuitive navigation, and simplified terminology.
Conclusions:
Applying HCD principles throughout our dashboard development process enabled continuous alignment of the EHE Implementation Science Reporting Dashboard with stakeholder needs. Our process illustrates how HCD can both shape the interface of a digital tool and structure supra-study evidence synthesis, language, and framing in ways that make implementation science findings more accessible and actionable for diverse audiences involved in a national public health initiative. Clinical Trial: N/A
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