Background Shared decision making requires evidence to be conveyed to the patient in a way they can easily understand and compare. Patient decision aids facilitate this process. This article reviews the current evidence for how to present numerical probabilities within patient decision aids. Methods Following the 2013 review method, we assembled a group of 9 international experts on risk communication across Australia, Germany, the Netherlands, the United Kingdom, and the United States. We expanded the topics covered in the first review to reflect emerging areas of research. Groups of 2 to 3 authors reviewed the relevant literature based on their expertise and wrote each section before review by the full authorship team. Results Of 10 topics identified, we present 5 fundamental issues in this article. Although some topics resulted in clear guidance (presenting the chance an event will occur, addressing numerical skills), other topics (context/evaluative labels, conveying uncertainty, risk over time) continue to have evolving knowledge bases. We recommend presenting numbers over a set time period with a clear denominator, using consistent formats between outcomes and interventions to enable unbiased comparisons, and interpreting the numbers for the reader to meet the needs of varying numeracy. Discussion Understanding how different numerical formats can bias risk perception will help decision aid developers communicate risks in a balanced, comprehensible manner and avoid accidental “nudging” toward a particular option. Decisions between probability formats need to consider the available evidence and user skills. The review may be useful for other areas of science communication in which unbiased presentation of probabilities is important.

Graph literacy is an often neglected skill that influences decision making performance. We conducted an experiment to investigate whether individual differences in graph literacy affect the extent to which people benefit from visual aids (icon arrays) designed to reduce a common judgment bias (i.e., denominator neglect—a focus on numerators in ratios while neglecting denominators). Results indicated that icon arrays more often increased risk comprehension accuracy and confidence among participants with high graph literacy as compared with those with low graph literacy. Results held regardless of how the health message was framed (chances of dying versus chances of surviving). Findings contribute to our understanding of the ways in which individual differences in cognitive abilities interact with the comprehension of different risk representation formats. Theoretical, methodological, and prescriptive implications of the results are discussed (e.g., the effective communication of quantitative medical data). Copyright © 2011 John Wiley & Sons, Ltd.

Graphs facilitate the communication of important quantitative information, often serving as effective decision support tools. Yet, graphs are not equally useful for all individuals, as people differ substantially in their graph literacythe ability to understand graphically presented information. Although some features of graphs can be interpreted using spatial-to-conceptual mappings that can be established by adults and children with no graphing experience (e.g., higher bars equal larger quantities), other features are linked to arbitrary graph conventions (e.g., axis labels and scales). In two experiments, we examined differences in the processes underlying the comprehension of graphs presenting medical information in individuals with low and high graph literacy. Participants eye movements were recorded while they interpreted graphs in which information in conventional features was incongruent with that conveyed by spatial features. Results revealed that participants with low graph literacy more often relied on misleading spatial-to-conceptual mappings and misinterpreted the data depicted. Higher graph literacy was often associated with more time spent viewing the conventional features containing essential information for accurate interpretations. This suggests that individuals with high graph literacy are better able to identify the task-relevant information in graphs, and thus attend to the relevant features to a larger extent. Theoretical, methodological, and prescriptive implications for customization of decision-support systems are discussed.Keywords: Graph comprehension, eye movements, medical decision making, individual differences, graph literacy GRAPH LITERACY AND PROCESSING OF HEALTH GRAPHS 3 How People with Low and High Graph Literacy Process Health Graphs: Evidence from Eye-TrackingGraphical displays such as line plots, bar charts, and icon arrays can serve as highly valuable tools for overcoming difficulties in the comprehension of numerical concepts, thus serving as highly effective decision support tools (Ancker, Senathirajah, Kukafka, & Starren, 2006; Garcia-Retamero & Cokely, 2011, 2013 Lipkus, 2007). Unfortunately, graphs are not equally useful for all individuals, as people in the general population differ substantially in their ability to understand graphically presented information (Galesic & Garcia-Retamero, 2011; Kutner, Greenberg, Jin, & Paulsen, 2006). These differences can affect the extent to which individuals benefit from visual displays (Gaissmaier et al., 2012; Garcia-Retamero & Cokely, 2014; Garcia-Retamero & Galesic, 2010; Okan, Garcia-Retamero, Cokely, & Maldonado, 2012). Yet the processes underlying graph comprehension in individuals with varying levels of graph literacy are not well understood. We used eye-tracking methodology to investigate this issue. Individual Differences in Graph LiteracyGraph literacy refers to ones ability to understand graphically presented information and includes general knowledge about making inferences from different graphic formats ...

Background Decision aid developers have to convey complex task-specific numeric information in a way that minimizes bias and promotes understanding of the options available within a particular decision. Whereas our companion paper summarizes fundamental issues, this article focuses on more complex, task-specific aspects of presenting numeric information in patient decision aids. Methods As part of the International Patient Decision Aids Standards third evidence update, we gathered an expert panel of 9 international experts who revised and expanded the topics covered in the 2013 review working in groups of 2 to 3 to update the evidence, based on their expertise and targeted searches of the literature. The full panel then reviewed and provided additional revisions, reaching consensus on the final version. Results Five of the 10 topics addressed more complex task-specific issues. We found strong evidence for using independent event rates and/or incremental absolute risk differences for the effect size of test and screening outcomes. Simple visual formats can help to reduce common judgment biases and enhance comprehension but can be misleading if not well designed. Graph literacy can moderate the effectiveness of visual formats and hence should be considered in tool design. There is less evidence supporting the inclusion of personalized and interactive risk estimates. Discussion More complex numeric information. such as the size of the benefits and harms for decision options, can be better understood by using incremental absolute risk differences alongside well-designed visual formats that consider the graph literacy of the intended audience. More research is needed into when and how to use personalized and/or interactive risk estimates because their complexity and accessibility may affect their feasibility in clinical practice.

Recent research has shown that patients frequently experience difficulties understanding health-relevant numerical concepts. A prominent example is denominator neglect, or the tendency to pay too much attention to numerators in ratios (e.g., number of treated patients who died) with insufficient attention to denominators (e.g., overall number of treated patients). Denominator neglect can lead to inaccurate assessments of treatment risk reduction and thus can have important consequences for decisions about health. Here, we reviewed a series of studies investigating (1) different factors that can influence patients' susceptibility to denominator neglect in medical decision making—including numerical or language-related abilities; (2) the extent to which denominator neglect can be attenuated by using visual aids; and (3) a factor that moderates the effectiveness of such aids (i.e., graph literacy). The review spans probabilistic national U.S. and German samples, as well as immigrant (i.e., Polish people living in the United Kingdom) and undergraduate samples in Spain. Theoretical and prescriptive implications are discussed.

In 2 studies, an older and a younger age group morally evaluated dilemmas contrasting a deontological judgment (do not harm others) against a utilitarian judgment (do what is best for the majority). Previous research suggests that deontological moral judgments are often underpinned by affective reactions and utilitarian moral judgments by deliberative thinking. Separately, research on the psychology of aging has shown that affect plays a more prominent role in the judgments and decision making of older (vs. younger) adults. Yet age remains a largely overlooked factor in moral judgment research. Here, we therefore investigated whether older adults would make more deontological judgments on the basis of experiencing different affective reactions to moral dilemmas as compared with younger adults. Results from 2 experiments indicated that older adults made significantly more deontological moral judgments. Mediation analyses revealed that the relationship between age and making more deontological moral judgments is partly explained by older adults exhibiting significantly more negative affective reactions and having more morally idealistic beliefs as compared with younger adults.

Explaining moral intuitions is one of the hot topics of recent cognitive sciences. In the present article we focus on a factor that attracted surprisingly little attention so far, namely the temporal order in which moral scenarios are presented. We argue that previous research points to a systematic pattern of order effects that has been overlooked until now: Only judgments of actions that are normally regarded as morally acceptable are affected by the order of presentation. Additionally, this is only the case for dilemmas immediately preceded by a scenario where the proposed action was judged as morally unacceptable. We conducted an experiment that confirmed this pattern and allowed us to analyze the individual level responses it was generated by. We argue that investigating order effects is necessary for approaching a complete descriptive moral theory.

Icon arrays have been found to improve risk understanding and reduce judgment biases across a wide range of studies. Unfortunately, individuals with low graph literacy experience only limited benefits from such displays. To enhance the efficacy and reach of these decision aids, the authors developed and tested 3 types of dynamic design features--that is, computerized display features that unfold over time. Specifically, the authors manipulated the sequential presentation of the different elements of icon arrays, the presence of explanatory labels indicating what was depicted in the different regions of the arrays, and the use of a reflective question followed by accuracy feedback. The first 2 features were designed to promote specific cognitive processes involved in graph comprehension, whereas the 3rd feature was designed to promote a more active, elaborative processing of risk information. Explanatory labels were effective in improving risk understanding among less graph-literate participants, whereas reflective questions resulted in large and robust performance benefits among participants with both low and high graph literacy. Theoretical and prescriptive implications are discussed. (PsycINFO Database Record