Manal Baqer

UNSTRUCTURED Abstract Background: Generative artificial intelligence (GenAI) chatbots are increasingly being developed to deliver personalized, scalable, and interactive support for health behavior change. Although these technologies have considerable potential, there is little practical guidance for researchers and clinicians on how to design GenAI health coach chatbots that can function as health behavior change coaches. Purpose: This tutorial presents a practical framework for developing theory-driven GenAI health coach chatbots using widely available large language models (LLMs) without requiring programming expertise. Drawing on behavioral theory, ethics, digital intervention development, and recent advances in LLMs, the tutorial describes how to develop a chatbot that is grounded in behavior change theory, informed by evidence, and developed with attention to safety, privacy, and equity. The six-step framework presented here spans conceptualization, instruction writing, knowledge base curation, LLM integration, pre-release testing, and post-release monitoring. Tutorial Framework: The tutorial provides a historical overview of the development of health coach chatbots. It then conceptualizes how theory and ethics can inform chatbot development. Finally, it introduces a six-step framework for health coach chatbot development that guides developers through (1) conceptualizing the chatbot, (2) developing chatbot instructions with attention to theory, behavior change techniques, and ethical considerations, (3) identifying materials for the knowledge base, (4) integrating the instructions and knowledge base into an LLM, (5) conducting pre-release validation and safety testing, and (6) releasing the chatbot and implementing post-release monitoring and refinement. Practical recommendations are provided throughout, including approaches to prompt engineering, use of retrieval-augmented generation, theory-based personalization, red-teaming, and evaluation of chatbot fidelity and safety. Conclusions: By integrating behavioral theory and ethics with contemporary GenAI development practices, this tutorial provides researchers, clinicians, and digital health developers with a structured, replicable framework for building and evaluating GenAI health coach chatbots. As AI-assisted behavioral interventions become more widespread, theory-driven design and rigorous validation will be essential for developing chatbots that are effective, safe, equitable, and suitable for research and practice.

With a renewed focus on health equity in the United States driven by national crises and legislation to improve digital healthcare innovation, there is a need for the designers of digital health tools to take deliberate steps to design for equity in their work. A concrete toolkit of methods to design for health equity is needed to support digital health practitioners in this aim. This narrative review summarizes several health equity frameworks to help digital health practitioners conceptualize the equity dimensions of importance for their work, and then provides design approaches that accommodate an equity focus. Specifically, the Double Diamond Model, the IDEAS framework and toolkit, and community collaboration techniques such as participatory design are explored as mechanisms for practitioners to solicit input from members of underserved groups and better design digital health tools that serve their needs. Each of these design methods requires a deliberate effort by practitioners to infuse health equity into the approach. A series of case studies that use different methods to build in equity considerations are offered to provide examples of how this can be accomplished and demonstrate the range of applications available depending on resources, budget, product maturity, and other factors. We conclude with a call for shared rigor around designing digital health tools that deliver equitable outcomes for members of underserved populations.

The potential and threat of digital tools to achieve health equity has been highlighted for over a decade, but the success of achieving equitable access to health technologies remains challenging. Our paper addresses renewed concerns regarding equity in digital health access that were deepened during the COVID-19 pandemic. Our viewpoint is that (1) digital health tools have the potential to improve health equity if equitable access is achieved, and (2) improving access and equity in digital health can be strengthened by considering behavioral science–based strategies embedded in all phases of tool development. Using behavioral, equity, and access frameworks allowed for a unique and comprehensive exploration of current drivers of digital health inequities. This paper aims to present a compilation of strategies that can potentially have an actionable impact on digital health equity. Multilevel factors drive unequal access, so strategies require action from tool developers, individual delivery agents, organizations, and systems to effect change. Strategies were shaped with a behavioral medicine focus as the field has a unique role in improving digital health access; arguably, all digital tools require the user (individual, provider, and health system) to change behavior by engaging with the technology to generate impact. This paper presents a model that emphasizes using multilevel strategies across design, delivery, dissemination, and sustainment stages to advance digital health access and foster health equity.

UNSTRUCTURED The potential and threat of digital tools to achieve health equity has been highlighted for over a decade, but the success of achieving equitable access to health technologies remains challenging. Our paper addresses renewed concerns regarding equity in digital health access that were deepened during the COVID-19 pandemic. Our viewpoint is that (1) digital health tools have the potential to improve health equity if equitable access is achieved, and (2) improving access and equity in digital health can be strengthened by considering behavioral science–based strategies embedded in all phases of tool development. Using behavioral, equity, and access frameworks allowed for a unique and comprehensive exploration of current drivers of digital health inequities. This paper aims to present a compilation of strategies that can potentially have an actionable impact on digital health equity. Multilevel factors drive unequal access, so strategies require action from tool developers, individual delivery agents, organizations, and systems to effect change. Strategies were shaped with a behavioral medicine focus as the field has a unique role in improving digital health access; arguably, all digital tools require the user (individual, provider, and health system) to change behavior by engaging with the technology to generate impact. This paper presents a model that emphasizes using multilevel strategies across design, delivery, dissemination, and sustainment stages to advance digital health access and foster health equity.