We investigated human understanding of different network visualizations in a large-scale online experiment. Three types of network visualizations were examined: node-link and two different sorting variants of matrix representations on a representative social network of either 20 or 50 nodes. Understanding of the network was quantified using task time and accuracy metrics on questions that were derived from an established task taxonomy. The sample size in our experiment was more than an order of magnitude larger (N = 600) than in previous research, leading to high statistical power and thus more precise estimation of detailed effects. Specifically, high statistical power allowed us to consider modern interaction capabilities as part of the evaluated visualizations, and to evaluate overall learning rates as well as ambient (implicit) learning. Findings indicate that participant understanding was best for the node-link visualization, with higher accuracy and faster task times than the two matrix visualizations. Analysis of participant learning indicated a large initial difference in task time between the node-link and matrix visualizations, with matrix performance steadily approaching that of the node-link visualization over the course of the experiment. This research is reproducible as the web-based module and results have been made available at: https://osf.io/qct84/.

Objectives: This study investigates the use of information graphics to display the outputs of health technology assessment (HTA) in the United Kingdom and proposes a more structured approach founded in an analysis of the decision-making requirements of the key stakeholders.

Methods: A scoping review of HTA reports was conducted to investigate current practice in the use of information graphics in HTA literature. A classification framework using dimensions of report section, graphical type, and originating research center was devised and used for a full content analysis of the graphical figures in the fifty most recent reports produced for the UK National Health Service's HTA process.

Results: Our survey shows that graphical tools are used extensively in HTA reports although less frequently than tables. Use of information graphics varies widely between different report sections and tends to follow conventional lines with little evidence of variance from established practice. The largest variance was found between the quantities of graphics used by different research centers responsible for authoring the reports.

Conclusions: HTA makes extensive use of graphics; however, there is little evidence of a systematic or standardized approach, or of much innovation. Significant potential exists to explore the application of information graphics in this field, but there are many research challenges. A contextually based, structured approach to the design of effective information graphics in HTA is proposed as a basis both to investigate the application of existing graphical tools in HTA, and to explore the considerable scope for innovation.