The information architecture of PDAs-its impact on user comprehension and risk perception

Abstract

Communication technology has been widely used in healthcare. There is a trend for one of the decision-making aids in innovative healthcare to become interactive web pages and applications. However, users often do not understand professional medical information and health values, especially those with poor numeracy skills. Therefore, more research is needed on translating complex medical information into simple guidelines that users can effectively understand and operate.Aims: This study aims to understand the impact of author-driven and reader-driven information architectures on users of patient decision aids.Methods: Author-driven and reader-driven framework models were developed for the same topic of patient decision aids. Users of different numerical abilities were evaluated on their comprehension, risk perception, usability, and task load. A total of 38 participants were assessed, of which 17 were reader-driven models, and 21 were author-driven models.Results: The results showed that reader-driven model participants were significantly better at comprehension than the author-driven model(p=0.025), but there was no significant difference in risk perception. Author-driven model usability was higher, but overall usability was lower. In the task load section, participants demanded more mental, physical, time pressure, effort, and stress feelings in the reader-driven model, especially in the time pressure section (p=0.011). In contrast, participants were more satisfied with their self-operational performance in the author-driven model. There was no significant difference between the two models regarding comprehension and risk perception between participants with excellent and lousy numeracy skills. However, among those with good numeracy skills, reader-driven model comprehension performance was significantly better than the author-driven model (p=0.018), and there was no significant difference in risk perception.Discussion: We found that the information architecture in patient decision aids impacts the user's comprehension. In the future, the information navigation framework of patient decision aids should consider the numerical ability of the user when developing them.