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Due to heterogeneity and limited medical data in primary healthcare services (PHS), assessing the psychological risk of type 2 diabetes mellitus (T2DM) patients in PHS is difficult. Using unsupervised contrastive pre-training, we proposed a deep learning framework named depression and anxiety prediction (DAP) to predict depression and anxiety in T2DM patients.

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.

Reflex testing protocols allow clinical laboratories to perform second line diagnostic tests on existing specimens based on the results of initially ordered tests. Reflex testing can support optimal clinical laboratory test ordering and diagnosis. In current clinical practice, reflex testing typically relies on simple "if-then" rules; however, this limits the opportunities for reflex testing since most test ordering decisions involve more complexity than traditional rule-based approaches would allow. Here, using [...]

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

To pilot test an infographic-based health communication intervention that our team rigorously designed and explore whether its implementation leads to better health outcomes among Latino persons with HIV (PWH).

Data visualizations can be effective and inclusive means for helping people understand health-related data. Yet numerous high-quality studies comparing data visualizations have yielded relatively little practical design guidance because of a lack of clarity about what communicators want their audience to accomplish. When conducting rigorous evaluations of communication (eg, applying the ISO 9186 method), describing the process simply as evaluating "comprehension" or "interpretation" of visualizations fails to do justice to [...]

The Advanced Visualization Branch of the National Institute of Nursing Research uses computer technologies to study information visualization in support of self-care management. Advanced technologies, such as immersive virtual reality (IVR), afford researchers the opportunity to study health information visualization where user-initiated information search in visually dense settings precedes acquisition, interpretation, and use. While IVR has broad applicability in healthcare, we chose to target lay people managing chronic disease because [...]

Although interactive data visualizations are increasingly popular for health communication, it remains to be seen what design features improve psychological and behavioral targets. This study experimentally tested how interactivity and descriptive titles may influence perceived susceptibility to the flu, intention to vaccinate, and information recall, particularly among older adults.

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 [...]