Eye tracking has become the gold standard in measuring human attention and information-processing behavior. As such, eye tracking in mixed-methods user experience (UX) research serves as an invaluable tool to learn about user needs and to create actionable insights for improving product and service design during the development cycle. Here, we discuss the iterative process that we used to improve the design of a decision aid (DA) developed to facilitate shared decision making. We explain the use of eye tracking during this process to examine how users processed the information provided by the DA. We also explain how we used eye tracking in a retrospective “think-aloud” protocol to gain insight about users’ needs. Our results show that user reactions captured by eye tracking can not only be used to optimize design decisions but also to gather user feedback about their information processing needs. 

Using Eye Tracking to Measure User Engagement with a Decision Aid

ABSTRACT Objective Evaluate the effect of risk communication tools on the understanding of statistical risk of complications occurring in patients undergoing a surgical or interventional procedure. Summary Background Data Informed consent is an essential process in clinical decision-making, through which healthcare providers educate patients about the benefits, risks and alternatives of a procedure. Numerical risk information is by nature probabilistic and difficult to communicate. Aids which support statistical risk communication and studies assessing their effectiveness are needed. Methods A systematic search was performed across Medline, Embase, PsycINFO, Scopus and Web of Science until July 2021 with a repeated search in September 2022. Studies examining risk communication tools (e.g. informative leaflets, audio-video) in adults (age&gt;16) patients undergoing a surgical or interventional procedure were included. Studies only assessing understanding of non-statistical aspects of the procedure were excluded. Both randomised control trials (RCTs) and observational studies were included. Cochrane risk-of-bias and the Newcastle-Ottawa Scale were used to assess the quality of studies. Due to heterogeneity of the studies, a narrative synthesis was performed (PROSPERO ID: CRD42022285789). Results A total of 4348 articles were identified and following abstract and full-text screening a total of 11 articles were included. 8 studies were RCTs and 3 were cross-sectional. The total number of adult patients was 1030. The most common risk communication tool used was additional written information (n=7). Of the 8 RCTs, 5 showed statistically significant improvements in the intervention group in outcomes relating to recall of statistical risk. Quality assessment of RCTs found some concerns with all studies. Conclusions Risk communication tools appear to improve recall of statistical risk. Additional prospective trials are warranted which can compare various aids and determine the most effective method of improving patient understanding. 

https://www.medrxiv.org/content/medrxiv/early/2023/01/19/2023.01.19.23284521.full.pdf

Aids to Improve Statistical Risk Communication in Patients Consenting for Surgery and Interventional Procedures: a Systematic Review

Background Few studies have examined the best way to convey the probability of serious events occurring in the future (i.e., risk of stroke or death) to persons with low numeracy or graph literacy proficiency. To address this gap, we developed and user-tested a bar graph and compared it to icon arrays to assess its impact on understanding and preference for viewing risk information. Objectives To determine the: (i) formats’ impact on participants’ understanding of risk information; (ii) formats’ impact on understanding and format preference across numeracy and graph literacy subgroups; (iii) rationale supporting participants’ preference for each graphical display format. Methods An online sample (evenly made up of participants with high and low objective numeracy and graph literacy) was randomized to view either the icon array or the bar graph. Each format conveyed the risk of major stroke and death five years after choosing surgery, a stent, or medication to treat carotid artery stenosis. Participants answered questions to assess their understanding of the risk information. Lastly, both formats were presented in parallel, and participants were asked to identify their preferred format to view risk information and explain their preference. Results Of the 407 participants, 197 were assigned the icon array and 210 the bar graph. Understanding of risk information and format preference did not differ significantly between the two trial arms, irrespective of numeracy and graph literacy proficiency. High numeracy and graph literacy proficiency was associated with high understanding (p<0.01) and a preference for the bar graph (p = 0.01). Conclusion We found no evidence to demonstrate the superiority of one format over another on understanding. The majority of participants preferred viewing the risk information using the bar graph format.

/pdf/comparing-the-impact-of-an-icon-array-versus-a-bar-graph-on-21hdzvb0nn.pdf

Comparing the impact of an icon array versus a bar graph on preference and understanding of risk information: Results from an online, randomized study.

Guillermina Noel

Papers

Comparing the impact of an icon array versus a bar graph on preference and understanding of risk information: Results from an online, randomized study.