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Conversational agents (CAs) with emerging artificial intelligence present new opportunities to assist in health interventions but are difficult to evaluate, deterring their applications in the real world. We aimed to synthesize existing evidence and knowledge and outline an evaluation framework for CA interventions.

The HIV epidemic remains a significant public health issue in the United States. HIV risk prediction models could be beneficial for reducing HIV transmission by helping clinicians identify patients at high risk for infection and refer them for testing. This would facilitate initiation on treatment for those unaware of their status and pre-exposure prophylaxis for those uninfected but at high risk. Existing HIV risk prediction algorithms rely on manual construction [...]

This scoping review aims to address a gap in the literature on community engagement in developing data visualizations intended to improve population health. The review objectives are to: (1) synthesize literature on the types of community engagement activities conducted by researchers working with community partners and (2) characterize instances of "creative data literacy" within data visualizations developed in community-researcher partnerships.

We implemented a chatbot consent tool to shift the time burden from study staff in support of a national genomics research study.

Interactive data visualization can be a viable way to discover patterns in patient-generated health data and enable health behavior changes. However, very few studies have investigated the design and usability of such data visualization. The present study aimed to (1) explore user experiences with sleep data visualizations in the Fitbit app, and (2) focus on end users' perspectives to identify areas of improvement and potential solutions. The study recruited eighteen [...]

Information visualizations are increasingly being developed by informatics researchers to communicate health information to lay audiences. For high-quality results, it is advisable to collaborate with creative professionals such as graphic designers, illustrators, or user interface/user experience designers. However, such collaborations are often a novel experience for both parties, each of which may be unfamiliar with the needs and processes of the other. We have coalesced our experiences from both the [...]

Availability of easy-to-understand patient-reported outcome (PRO) trial data may help individuals make more informed healthcare decisions. Easily interpretable, patient-centric PRO data summaries and visualizations are therefore needed. This three-stage study explored graphical format preferences, understanding, and interpretability of clinical trial PRO data presented to people with prostate cancer (PC).

The increased availability of public data and accessible visualization technologies enhanced the popularity of public health data dashboards and broadened their audience from professionals to the general public. However, many dashboards have not achieved their full potential due to design complexities that are not optimized to users' needs.

Data visualization style guides are standards for formatting and designing representations of information, like charts, graphs, tables, and diagrams. To assist researchers communicate their visual content in better and more effective ways, this article accomplishes two tasks. First, we take a detailed look at a data visualization style guide and its components-what it is and what it should include. Second, we create a detailed template for the color section of [...]