By combining the impact of all these elements – decision contexts and ecosystem levels – we can identify how they shape the demand for HIV prevention. This means that as well as supporting program monitoring, the framework allows programmers and funders to better understand prevention decisions and identify gaps to inform future planning. AI can open the dialogue It will be interesting to see how HIV prevention organizations apply this framework – or parts of it – to reach more vulnerable people in the coming years. Technology isn’t an essential part of those efforts, but we do see potential for AI to support them. Something as simple as a discussion with an AI chatbot, for instance, could make HIV prevention more accessible and personalized. Initially, users could take this route to find out whether certain behaviors or situations put them at risk and understand their options for prevention. Enabled by behavioral models, the chatbot could provide a more personalized approach by understanding which prevention products the user might choose, suggesting the most appropriate options and predicting why, and under which conditions, those options might change. Self-testing is another emerging area where AI could help to alleviate concerns about the stigma of visiting a clinic. In this context, a chatbot or app could provide a channel for users to find out whether they should get tested and to order that test for delivery to their home. Users might feel more comfortable discussing their test results and options with a chatbot, rather than in a clinician’s office. Then they could decide on their next steps, such as ordering prevention products for delivery or booking an appointment at a suitable clinic. Of course, it will take time for user-centered approaches like these to filter into HIV prevention programs. But our framework provides a tool to help organizations think about ways to apply this concept, and technology exists to support a multitude of approaches. With these tools, we hope that service providers will find effective ways to put control into users’ hands – and enable a more productive dialog on HIV prevention with the people who need it most.
FRACTAL’S FRAMEWORK It begins with three user contexts:
RISK ASSESSMENT Accurately identifying risks and the need to mitigate them. OPPORTUNITY EVALUATION Selecting suitable methods to address the risk that has been identified. EFFECTIVE USE Building on the first two contexts to develop effective responses to those risks, vulnerabilities and prevention opportunities. In each decision context, the framework translates overall objectives into individual goals for both service users and providers. To enable a more nuanced understanding of HIV prevention behaviors, the framework also factors in three ecosystem levels: INDIVIDUAL BEHAVIORS Such as ability to cope with stigma, or perceptions of a prevention method’s effectiveness. INTERACTIONS The factors that impact the way users engage with their ecosystem while accessing HIV prevention services. SYSTEMIC INFLUENCES The policies, system design and cultures that significantly influence ecosystem dynamics.
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Volume 10 ai:sight by Fractal
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