Measuring Graph Literacy without a Test: A Brief Subjective Assessment

Boundary Conditions for the Positive Skew Bias

Gambles that involve a large but unlikely gain coupled with a small but likely loss-like a lottery ticket-are known as positively-skewed. There is evidence that people tend to prefer these positively skewed choices, leading to what is called a positive-skew bias. In this study, we attempt to better understand under what conditions people are more drawn toward positively skewed, relative to symmetric, gambles. Based on the animal literature, there is reason to believe that preference for skewed gambles is dependent on the strength of the skew, with a greater preference for more strongly skewed options. In two online studies (Study 1: N = 209; Study 2: N = 210), healthy participants across the lifespan (ages 22-85) made a series of choices between a positively skewed risky gamble and either a certain outcome (Study 1) or risky symmetric gamble (Study 2). Logistic regression analyses revealed that people were more likely to choose moderately- and strongly skewed gambles over certain outcomes, with the exception of when there were large potential losses (Study 1). However, a stronger skewness did not increase preference for positively skewed gambles over symmetric gambles, findings which also may depend on the valence of the expected outcome (Study 2). Taken together, these results suggest that there may be a greater preference for more strongly positively skewed gambles but it 1) is dependent on what other gamble is presented and 2) is most prevalent for positive expected values. Additionally, contrary to previous findings, we did not find strong evidence of an age-related increase in positive skew bias in either study. However, exploratory analyses revealed that decision making strategy and cognitive abilities may play a role.

Visualizing Uncertainty to Promote Clinicians' Understanding of Measurement Error

Measurement error is an inherent part of any test score. This uncertainty is generally communicated in ways that can be difficult to understand for clinical practitioners. In this empirical study, we evaluate the impact of several communication formats on the interpretation of measurement accuracy and its influence on the decision-making process in clinical practice. We provided 230 clinical practitioners with score reports in five formats: textual, error bar, violin plot, diamond plot, and quantile dot plot. We found that quantile dot plots significantly increased accuracy in the assessment of measurement uncertainty compared with other formats. However, a direct relation between visualization format and decision quality could not be found. Although traditional confidence intervals and error bars were favored by many participants due to their familiarity, responses revealed several misconceptions that make the suitability of these formats for communicating uncertainty questionable. Our results indicate that new visualization formats can successfully reduce errors in interpretation.

Patient-Reported Outcome Measurement in Orthopaedic Trauma

Patient-reported outcome (PRO) measurements are validated tools developed to quantify self-reported aspects of capability, mindset, and circumstances in a standardized fashion. While PRO measurements have primarily been used in the research realm, a growing body of work now underscores substantial opportunities in applying the data generated by these tools to advance patient-centered musculoskeletal care. Specifically, the insights into a patient's health status derived from these measures can augment the standard biomedical approach to the management of patients with orthopaedic trauma. For instance, PRO measures have demonstrated the high prevalence of psychological distress and social concerns within trauma populations and shown that mindsets and circumstances account for a substantial amount of the variation in levels of symptom intensity and capability in these patients. Such findings support the need for a more integrated, biopsychosocial, and multidisciplinary team-based approach to orthopaedic trauma care that include both technical and nontechnical skillsets. In this chapter, we explore the range of available fixed-scale and computer adaptive PRO measures that can quantify aspects of capability, mindsets, and circumstances of the patient with orthopaedic trauma during their experience of injury, recovery, and rehabilitation. Furthermore, we define human, technical, and system-level challenges within the often complex, dynamic, and clinically intense trauma setting. Finally, we highlight potential opportunities through successfully implementing PRO measurements for clinical decision support, shared decision making, predicting health outcomes, and developing advanced care pathways for patients and populations with orthopaedic trauma.

How Do People Process Different Representations of Statistical Information? Insights into Cognitive Effort, Representational Inconsistencies, and Individual Differences

BACKGROUND

Graphical representation formats (e.g., icon arrays) have been shown to lead to better understanding of the benefits and risks of treatments compared to numbers. We investigate the cognitive processes underlying the effects of format on understanding: how much cognitive effort is required to process numerical and graphical representations, how people process inconsistent representations, and how numeracy and graph literacy affect information processing.

METHODS

In a preregistered between-participants experiment, 665 participants answered questions about the relative frequencies of benefits and side effects of 6 medications. First, we manipulated whether the medical information was represented numerically, graphically (as icon arrays), or inconsistently (numerically for 3 medications and graphically for the other 3). Second, to examine cognitive effort, we manipulated whether there was time pressure or not. In an additional intervention condition, participants translated graphical information into numerical information before answering questions. We also assessed numeracy and graph literacy.

RESULTS

Processing icon arrays was more strongly affected by time pressure than processing numbers, suggesting that graphical formats required more cognitive effort. Understanding was lower when information was represented inconsistently (v. consistently) but not if there was a preceding intervention. Decisions based on inconsistent representations were biased toward graphically represented options. People with higher numeracy processed quantitative information more efficiently than people with lower numeracy did. Graph literacy was not related to processing efficiency.

LIMITATIONS

Our study was conducted with a nonpatient sample, and the medical information was hypothetical.

CONCLUSIONS

Although graphical (v. numerical) formats have previously been found to lead to better understanding, they may require more cognitive effort. Therefore, the goal of risk communication may play an important role when choosing how to communicate medical information.

HIGHLIGHTS

This article investigates the cognitive processes underlying the effects of representation format on the understanding of statistical information and individual differences therein.Processing icon arrays required more cognitive effort than processing numbers did.When information was represented inconsistently (i.e., partly numerically and partly graphically), understanding was lower than with consistent representation, and decisions were biased toward the graphically represented options.People with higher numeracy processed quantitative information more efficiently than people with lower numeracy did.

The Lure of Beauty: People Select Representations of Statistical Information Largely Based on Attractiveness, Not Comprehensibility

OBJECTIVE

People differ in whether they understand graphical or numerical representations of statistical information better. However, assessing these skills is often not feasible when deciding which representation to select or use. This study investigates whether people choose the representation they understand better, whether this choice can improve risk comprehension, and whether results are influenced by participants' skills (graph literacy and numeracy).

METHODS

In an experiment, 160 participants received information about the benefits and side effects of painkillers using either a numerical or a graphical representation. In the "no choice" condition, the representation was randomly assigned to each participant. In the "choice" condition, participants could select the representation they would like to receive. The study assessed gist and verbatim knowledge (immediate comprehension and recall), accessibility of the information, attractiveness of the representation, as well as graph literacy and numeracy.

RESULTS

In the "choice" condition, most (62.5%) chose the graphical format, yet there was no difference in graph literacy or numeracy (nor age or gender) between people who chose the graphical or the numerical format. Whereas choice slightly increased verbatim knowledge, it did not improve gist or overall knowledge compared with random assignment. However, participants who chose a representation rated the representation as more attractive, and those who chose graphs rated them as more accessible than those without a choice.

LIMITATIONS

The sample consisted of highly educated undergraduate students with higher graph literacy than the general population. The task was inconsequential for participants in terms of their health.

CONCLUSIONS

When people can choose between representations, they fail to identify what they comprehend better but largely base that choice on how attractive the representation is for them.

HIGHLIGHTS

People differ systematically in whether they understand graphical or numerical representations of statistical information better. However, assessing these underlying skills to get the right representation to the right people is not feasible in practice. A simple and efficient method to achieve this could be to let people choose among representations themselves.However, our study showed that allowing participants to choose a representation (numerical v. graphical) did not improve overall or gist knowledge compared with determining the representation randomly, even though it did slightly improve verbatim knowledge.Rather, participants largely chose the representation they found more attractive. Most preferred the graphical representation, including those with low graph literacy.It would therefore be important to develop graphical representations that are not only attractive but also comprehensible even for people with low graph literacy.

Explaining With Examples: Lessons Learned From Crowdsourced Introductory Description of Information Visualizations

Data visualizations have been increasingly used in oral presentations to communicate data patterns to the general public. Clear verbal introductions of visualizations to explain how to interpret the visually encoded information are essential to convey the takeaways and avoid misunderstandings. We contribute a series of studies to investigate how to effectively introduce visualizations to the audience with varying degrees of visualization literacy. We begin with understanding how people are introducing visualizations. We crowdsource 110 introductions of visualizations and categorize them based on their content and structures. From these crowdsourced introductions, we identify different introduction strategies and generate a set of introductions for evaluation. We conduct experiments to systematically compare the effectiveness of different introduction strategies across four visualizations with 1,080 participants. We find that introductions explaining visual encodings with concrete examples are the most effective. Our study provides both qualitative and quantitative insights into how to construct effective verbal introductions of visualizations in presentations, inspiring further research in data storytelling.

How Do Viewers Synthesize Conflicting Information from Data Visualizations?

Scientific knowledge develops through cumulative discoveries that build on, contradict, contextualize, or correct prior findings. Scientists and journalists often communicate these incremental findings to lay people through visualizations and text (e.g., the positive and negative effects of caffeine intake). Consequently, readers need to integrate diverse and contrasting evidence from multiple sources to form opinions or make decisions. However, the underlying mechanism for synthesizing information from multiple visualizations remains under-explored. To address this knowledge gap, we conducted a series of four experiments ( N=1166) in which participants synthesized empirical evidence from a pair of line charts presented sequentially. In Experiment 1, we administered a baseline condition with charts depicting no specific context where participants held no strong belief. To test for the generalizability, we introduced real-world scenarios to our visualizations in Experiment 2 and added accompanying text descriptions similar to online news articles or blog posts in Experiment 3. In all three experiments, we varied the relative direction and magnitude of line slopes within the chart pairs. We found that participants tended to weigh the positive slope more when the two charts depicted relationships in the opposite direction (e.g., one positive slope and one negative slope). Participants tended to weigh the less steep slope more when the two charts depicted relationships in the same direction (e.g., both positive). Through these experiments, we characterize participants' synthesis behaviors depending on the relationship between the information they viewed, contribute to theories describing underlying cognitive mechanisms in information synthesis, and describe design implications for data storytelling.

Striking a Balance: Reader Takeaways and Preferences when Integrating Text and Charts

While visualizations are an effective way to represent insights about information, they rarely stand alone. When designing a visualization, text is often added to provide additional context and guidance for the reader. However, there is little experimental evidence to guide designers as to what is the right amount of text to show within a chart, what its qualitative properties should be, and where it should be placed. Prior work also shows variation in personal preferences for charts versus textual representations. In this paper, we explore several research questions about the relative value of textual components of visualizations. 302 participants ranked univariate line charts containing varying amounts of text, ranging from no text (except for the axes) to a written paragraph with no visuals. Participants also described what information they could take away from line charts containing text with varying semantic content. We find that heavily annotated charts were not penalized. In fact, participants preferred the charts with the largest number of textual annotations over charts with fewer annotations or text alone. We also find effects of semantic content. For instance, the text that describes statistical or relational components of a chart leads to more takeaways referring to statistics or relational comparisons than text describing elemental or encoded components. Finally, we find different effects for the semantic levels based on the placement of the text on the chart; some kinds of information are best placed in the title, while others should be placed closer to the data. We compile these results into four chart design guidelines and discuss future implications for the combination of text and charts.

Graph schema and best graph type to compare discrete groups: Bar, line, and pie

Different graph types may differ in their suitability to support group comparisons, due to the underlying graph schemas. This study examined whether graph schemas are based on perceptual features (i.e., each graph type, e.g., bar or line graph, has its own graph schema) or common invariant structures (i.e., graph types share common schemas). Furthermore, it was of interest which graph type (bar, line, or pie) is optimal for comparing discrete groups. A switching paradigm was used in three experiments. Two graph types were examined at a time (Experiment 1: bar vs. line, Experiment 2: bar vs. pie, Experiment 3: line vs. pie). On each trial, participants received a data graph presenting the data from three groups and were to determine the numerical difference of group A and group B displayed in the graph. We scrutinized whether switching the type of graph from one trial to the next prolonged RTs. The slowing of RTs in switch trials in comparison to trials with only one graph type can indicate to what extent the graph schemas differ. As switch costs were observed in all pairings of graph types, none of the different pairs of graph types tested seems to fully share a common schema. Interestingly, there was tentative evidence for differences in switch costs among different pairings of graph types. Smaller switch costs in Experiment 1 suggested that the graph schemas of bar and line graphs overlap more strongly than those of bar graphs and pie graphs or line graphs and pie graphs. This implies that results were not in line with completely distinct schemas for different graph types either. Taken together, the pattern of results is consistent with a hierarchical view according to which a graph schema consists of parts shared for different graphs and parts that are specific for each graph type. Apart from investigating graph schemas, the study provided evidence for performance differences among graph types. We found that bar graphs yielded the fastest group comparisons compared to line graphs and pie graphs, suggesting that they are the most suitable when used to compare discrete groups.

Meta-summaries effective for improving awareness and understanding of COVID-19 vaccine safety research

Despite the efficacy, safety, and availability of COVID-19 vaccines, a lack of awareness and trust of vaccine safety research remains an important barrier to public health. The goal of this research was to design and test online meta-summaries-transparent, interactive summaries of the state of relevant studies-to improve people's awareness and opinion of vaccine safety research. We used insights from a set of co-design interviews (n = 22) to develop meta-summaries to highlight metascientific information about vaccine safety research. An experiment with 863 unvaccinated participants showed that our meta-summaries increased participants' perception of the amount, consistency, and direction of vaccine safety research relative to the U.S. Center for Disease Control (CDC) webpage, and that participants found them more trustworthy than the CDC page as well. They were also more likely to discuss it with others in the week following. We conclude that direct summaries of scientific research can be a useful communication tool for controversial scientific topics.

Best Graph Type to Compare Discrete Groups: Bar, Dot, and Tally

Different graph types might differ in group comparison due to differences in underlying graph schemas. Thus, this study examined whether graph schemas are based on perceptual features (i.e., each graph has a specific schema) or common invariant structures (i.e., graphs share several common schemas), and which graphic type (bar vs. dot vs. tally) is the best to compare discrete groups. Three experiments were conducted using the mixing-costs paradigm. Participants received graphs with quantities for three groups in randomized positions and were given the task of comparing two groups. The results suggested that graph schemas are based on a common invariant structure. Tally charts mixed either with bar graphs or with dot graphs showed mixing costs. Yet, bar and dot graphs showed no mixing costs when paired together. Tally charts were the more efficient format for group comparison compared to bar graphs. Moreover, processing time increased when the position difference of compared groups was increased.

Parental Risk Literacy is Related to Quality of Life in Spanish Families of Children with Autism Spectrum Disorder

Families of children with autism spectrum disorder (ASD) often experience much more negative perceptions of their family quality of life (FQoL). To investigate key factors that may shape these experiences, we conducted a case-control study of sixty-one Spanish families (29 with a child with ASD) using a broad psychosocial assessment (e.g., ASD severity, social support, demographics), including the first direct test of the relationship between FQoL and parental risk literacy (i.e., the ability to evaluate and understand risk, as measured by numeracy). Results revealed that numeracy was associated with differences in perceived FQoL among families of children with ASD (R² = .10), a finding that held across several models statistically controlling for the influence of other variables. Findings suggest that parental risk literacy skills may generally be associated with differences in decision making vulnerabilities (e.g., risk evaluation and interpretation) that influence family outcomes including FQoL.

Improving Debt Literacy by 2/3 Through Four Simple Infographics Requires Numeracy and Not Focusing on Negatives of Debt

Borrowing behavior may be more resistant to formal educational treatments than other financial behaviors. In order to study the process and results of infographics-based debt education, we used eye tracking technology (SMI RED 500 Hz) to monitor the oculomotor behavior of 108 participants (68 females) aged 18 to 60 who were shown 4 infographics. The study used an experimental design with repeated measures and an internal comparison group. We also used scales of debt literacy and a set of information literacy scales: numerical, graph, and linguistic. The results confirm that short-term infographics-based debt education can improve debt literacy significantly. The difference in processing the educational contents that were not known to participants before the educational session suggests that participants with better information literacy make more considerable debt literacy progress. Specifically, we found that numerical literacy is a significant mediator of debt education results, depending on the initial level of debt literacy; this relation is moderated by the focus of visual attention on negatives of debt. We found no significant relationship between debt literacy education results and those of graph and linguistic literacy.

Current Best Practice for Presenting Probabilities in Patient Decision Aids: Fundamental Principles

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.

Current Challenges When Using Numbers in Patient Decision Aids: Advanced Concepts

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.

Toward a Taxonomy for Adaptive Data Visualization in Analytics Applications

Data analytics as a field is currently at a crucial point in its development, as a commoditization takes place in the context of increasing amounts of data, more user diversity, and automated analysis solutions, the latter potentially eliminating the need for expert analysts. A central hypothesis of the present paper is that data visualizations should be adapted to both the user and the context. This idea was initially addressed in Study 1, which demonstrated substantial interindividual variability among a group of experts when freely choosing an option to visualize data sets. To lay the theoretical groundwork for a systematic, taxonomic approach, a user model combining user traits, states, strategies, and actions was proposed and further evaluated empirically in Studies 2 and 3. The results implied that for adapting to user traits, statistical expertise is a relevant dimension that should be considered. Additionally, for adapting to user states different user intentions such as monitoring and analysis should be accounted for. These results were used to develop a taxonomy which adapts visualization recommendations to these (and other) factors. A preliminary attempt to validate the taxonomy in Study 4 tested its visualization recommendations with a group of experts. While the corresponding results were somewhat ambiguous overall, some aspects nevertheless supported the claim that a user-adaptive data visualization approach based on the principles outlined in the taxonomy can indeed be useful. While the present approach to user adaptivity is still in its infancy and should be extended (e.g., by testing more participants), the general approach appears to be very promising.

Assessing Patient Interest in Individualized Preventive Care Recommendations

Background. Few Americans obtain all 41 guideline-recommended preventive services for nonpregnant adults. We assessed patient interest in prioritizing their preventive care needs. Methods. We conducted a mixed-methods study, with 4 focus groups (N = 28) at a single institution and a nationwide survey (N = 2,103). Participants were middle-aged and older adults with preventive care needs. We obtained reactions to written materials describing the magnitude of benefit from major preventive services, including both absolute and relative benefits. Recommendations were individualized for patient risk factors (“individualized preventive care recommendations”). Focus groups assessed patient interest, how patients would want to discuss individualized recommendations with their providers, and potential for individualized recommendations to influence patient decision making. Survey content was based on focus groups and analyzed with logistic regression. Results. Patients expressed strong interest in individualized recommendations. Among survey respondents, an adjusted 88.2% (95% confidence interval [CI] = 86.7% to 89.7%) found individualized recommendations very easy to understand, 77.2% (95% CI = 75.3% to 79.1%) considered them very useful, and 64.9% (95% CI = 62.8% to 67.0%) highly trustworthy (each ≥6/7 on Likert scale). Three quarters of participants wanted to receive their own individualized recommendations in upcoming primary care visits (adjusted proportion = 77.5%, 95% CI = 75.6% to 79.4%). Both focus group and survey participants supported shared decision making and reported that individualized recommendations would improve motivation to obtain preventive care. Half of survey respondents reported that they would be much more likely to visit their doctor if they knew individualized recommendations would be discussed, compared with 4.2% who would not be more likely to visit their doctor. Survey respondents already prioritized preventive services, stating they were most likely to choose quick/easy preventive services and least likely to choose expensive preventive services (adjusted proportions, 63.8% and 8.5%, respectively). Results were consistent in sensitivity analyses. Conclusions. Individualized preventive care recommendations are likely to be well received in primary care and might motivate patients to improve adherence to evidence-based care.

Using the Short Graph Literacy Scale to Predict Precursors of Health Behavior Change

BACKGROUND

Visual displays can facilitate risk communication and promote better health choices. Their effectiveness in improving risk comprehension is influenced by graph literacy. However, the construct of graph literacy is still insufficiently understood, partially because existing objective measures of graph literacy are either too difficult or too long.

OBJECTIVES

We constructed a new 4-item Short Graph Literacy (SGL) scale and examined how SGL scores relate to key cognitive, affective, and conative precursors of health behavior change described in common health behavior theories.

METHODS

We performed secondary analyses to adapt the SGL scale from an existing 13-item scale. The initial construction was based on data collected in a laboratory setting in Germany ( n = 51). The scale was then validated using data from nationally representative samples in Germany ( n = 495) and the United States ( n = 492). To examine how SGL scores relate to precursors of health behavior change, we performed secondary analyses of a third study involving a nationwide US sample with 47% participants belonging to racial/ethnic minorities and 46% with limited formal education ( n = 835).

RESULTS

Graph literacy was significantly associated with cognitive precursors in theoretically expected ways (e.g., positive associations with risk comprehension and response efficacy and a negative association with cognitive risk perception). Patterns for affective precursors generally mirrored those for cognitive precursors, although numeracy was a stronger predictor than graph literacy for some affective factors (e.g., feelings of risk). Graph literacy had predictive value for most cognitive and affective precursors beyond numeracy. In addition, graph literacy (but not numeracy) predicted key conative precursors such as defensive processing.

CONCLUSIONS

Our data suggest that the SGL scale is a fast and psychometrically valid method for measuring objective graph literacy. Our findings also highlight the theoretical and practical relevance of graph literacy.

Does Fear Increase Search Effort in More Numerate People? An Experimental Study Investigating Information Acquisition in a Decision From Experience Task

The aim of this study was to investigate the effect of numeracy and the emotion of fear on the decision-making process. While previous research demonstrated that these factors are independently related to search effort, search policy and choice in a decision from experience task, less is known about how their interaction contributes to processing information under uncertainty. We attempted to address this problem and to fill this gap. In the present study, we hypothesized that more numerate people would sample more information about a decision problem and that the effect of fear would depend on the source of this emotion: whether it is integral (i.e., relevant) or incidental (i.e., irrelevant) to a decision problem. Additionally, we tested how these factors predict choices. We addressed these hypotheses in a series of two experiments. In each experiment, we used a sampling paradigm to measure search effort, search policy and choice in nine binary problems included in a decision from experience task. In Experiment 1, before the sampling task we elicited incidental fear by asking participants to recall fearful events from their life. In Experiment 2, integral fear was elicited by asking participants to make choices concerning medical treatment. Decision problems and their payoff distributions were the same in the two experiments and across each condition. In both experiments, we assessed objective statistical numeracy and controlled for a change in the current emotional state. We found that more numerate people sampled more information about a decision problem and switched less frequently between alternatives. Incidental fear marginally predicted search effort. Integral fear led to larger sample sizes, but only among more numerate people. Neither numeracy nor fear were related to the number of choices that maximized expected values. However, across two experiments sample sizes predicted the number of choices that maximized experienced mean returns. The findings suggest that people with higher numeracy may be more sensitive to integral emotions; this may result in more effortful sampling of relevant information leading to choices maximizing experienced returns.

Patient-centered approaches to creating understandable health information

As care delivery shifts to further include patients in shared decision-making, patient-centered health information can balance the information asymmetry between patients and providers. Patient health literacy, numeracy, and graph literacy must match that of health information materials to create understandable health information that empowers patients to participate in shared decision-making. We consider an iterative approach focused on three key steps: assessment of the specific information needs of the selected patient community, assessment of that community's ability to receive and understand health information, and evaluation of the materials developed to assess effectiveness. This structured approach using validated tools maximizes the likelihood of meeting patient needs to improve health outcomes.

Designing Visual Aids That Promote Risk Literacy: A Systematic Review of Health Research and Evidence-Based Design Heuristics

Background Effective risk communication is essential for informed decision making. Unfortunately, many people struggle to understand typical risk communications because they lack essential decision-making skills. Objective The aim of this study was to review the literature on the effect of numeracy on risk literacy, decision making, and health outcomes, and to evaluate the benefits of visual aids in risk communication. Method We present a conceptual framework describing the influence of numeracy on risk literacy, decision making, and health outcomes, followed by a systematic review of the benefits of visual aids in risk communication for people with different levels of numeracy and graph literacy. The systematic review covers scientific research published between January 1995 and April 2016, drawn from the following databases: Web of Science, PubMed, PsycINFO, ERIC, Medline, and Google Scholar. Inclusion criteria were investigation of the effect of numeracy and/or graph literacy, and investigation of the effect of visual aids or comparison of their effect with that of numerical information. Thirty-six publications met the criteria, providing data on 27,885 diverse participants from 60 countries. Results Transparent visual aids robustly improved risk understanding in diverse individuals by encouraging thorough deliberation, enhancing cognitive self-assessment, and reducing conceptual biases in memory. Improvements in risk understanding consistently produced beneficial changes in attitudes, behavioral intentions, trust, and healthy behaviors. Visual aids were found to be particularly beneficial for vulnerable and less skilled individuals. Conclusion Well-designed visual aids tend to be highly effective tools for improving informed decision making among diverse decision makers. We identify five categories of practical, evidence-based guidelines for heuristic evaluation and design of effective visual aids.