Pictorial versus textual information and the ratio-bias effect

The unit effect from a performance management perspective

Purpose

The subjective interpretation of numerical information can induce the so-called unit effect, i.e. the scale and unit chosen to quantify such information might influence a person's judgment. Although this bias is well-known, until now, it has been difficult to obtain an overview of the respective research. There are a variety of versions of the unit effect, different terms are used for the same kind of effect and proposals for grouping such effects lack a straightforward typology.

Design/methodology/approach

A literature review is conducted using a systematic literature search design. We address the following questions: (1) What knowledge exists about the unit effect? (2) What is a suitable concept for structuring the findings? (3) What ideas can be deduced for future research focusing on performance management?

Findings

A total of 11 versions of the unit effect and 27 moderating variables are identified and grouped into four contexts in which the effects occur. Structured according to these contexts, research ideas are depicted. They include suggestions for studies adapted to the field of performance management to scrutinize the main effects and moderators addressed in the literature to date as well as to consider additional potential moderators.

Originality/value

Few publications explicitly address the unit effect from the perspective of performance management. As one of the core objectives of this business function is to enable rational decision-making based on numerical information, it can be assumed that corresponding research will be very fruitful.

Developmental frontal brain activation differences in overcoming heuristic bias

Since reasoning is often biased by intuitive heuristics, the development of sound reasoning has long been postulated to depend on successful bias monitoring and inhibition. The present fMRI study aimed to identify neural correlates of developmental changes in these processes. A group of adults and young adolescents were presented with ratio-bias problems in which an intuitively cued heuristic response could be incongruent (conflict item) or congruent (no-conflict item) with the correct response. Results showed that successfully avoiding biased responding on conflict items across both age groups was associated with increased activation in Anterior Cingulate Cortex (ACC) and the right Lateral Prefrontal Cortex (LPFC) regions of interest. Critically, the right LPFC activation decreased with age. Biased responding did not result in right LPFC or ACC modulation and failed to show any developmental activation changes. We discuss implications for ongoing debates on the nature of heuristic bias and its development.

A methodological approach to ratio bias

The ratio-bias (RB) phenomenon is considered to provide systematic evidence of irrationality. When judging the probability of a low-probability event, many people judge it as less likely when it is expressed as a ratio of small numbers (e.g., 1-in-10) than when it is expressed as a ratio of large numbers (e.g., 10-in-100). Four experiments show that the phenomenon is increased by the experimental paradigm, which misleads subjects regarding the aim of the task by inducing equal-ratio neglect. One factor is constant across the texts of the Experiment 1–3: a particular sentence that induces subjects to neglect the equal ratio and invites them to express feelings about the outcome of the target event rather than giving a rational answer. This intent is strengthened by the formulation of the question (Experiment 1), which explicitly asks the subject to express the feeling connected to the lotteries and the absence of a third option (Experiment 1, 4), the right one, which expresses the “indifference” between the two options. In Experiment 4, the task lacks only the third option, and, simply by adding the option that allows subjects to express the correct answer, the RB disappears.

Using plausible group sizes to communicate information about medical risks

OBJECTIVE

To make informed health decisions, patients must understand and recall risks, which often involve ratios with large denominators. Grasping the meaning of such numbers may be difficult, because of limited exposure to large groups of people in either our evolutionary history or daily life.

METHODS

In an experiment (n=98), we investigated whether medical risks are easier to understand and recall if their representation is based on small, evolutionarily plausible groups of people, and whether this representation especially helps patients with low numeracy.

RESULTS

Participants-especially those with low numeracy-often disregarded and incorrectly recalled denominators of ratios representing medical risks when the denominators involved were large. Risks were easier to understand and recall if their representation was based on smaller, evolutionarily plausible groups of people.

CONCLUSIONS

Our results extend previous literature on the role of numeracy in understanding health-relevant risk communications by showing the importance of using plausible group sizes to communicate these risks to people with low numeracy. Our results also support the notion that problems in risk perception occur because of inappropriate presentation formats rather than cognitive biases.

PRACTICE IMPLICATIONS

Our findings suggest suitable ways to communicate quantitative medical data-especially to people with low numeracy.

Who profits from visual aids: overcoming challenges in people's understanding of risks [corrected]

Many people have difficulties grasping numerical concepts that are prerequisites for understanding treatment risk reduction. Visual aids have been proposed as a promising method for enhancing comprehension. In a survey of probabilistic, nationally representative samples in two different countries (United States and Germany), we compared the effectiveness of adding different types of visual aids (icon arrays and bar graphs representing either affected individuals only or the entire population at risk) to the numerical information in either an absolute or a relative risk reduction format. We also analyzed whether people's numeracy and graphical literacy skills affected the efficacy of the visual aids. Our results showed large improvements in accuracy both when icon arrays and when bar graphs were added to numerical information. Highest increases were achieved when the visual aids depicted the entire population at risk. Importantly, visual aids were most useful for the participants who had low numeracy but relatively high graphical literacy skills. Building on previous research showing that problems with understanding numerical information often do not reside in people's minds, but in the representation of the problem, our results show that visual aids help to modify incorrect expectations about treatment risk reduction. Our results have important implications for medical practice.

Numeric, verbal, and visual formats of conveying health risks: suggested best practices and future recommendations

Perception of health risk can affect medical decisions and health behavior change. Yet the concept of risk is a difficult one for the public to grasp. Whether perceptions of risk affect decisions and behaviors often relies on how messages of risk magnitudes (i.e., likelihood) are conveyed. Based on expert opinion, this article offers, when possible, best practices for conveying magnitude of health risks using numeric, verbal, and visual formats. This expert opinion is based on existing empirical evidence, review of papers and books, and consultations with experts in risk communication. This article also discusses formats to use pertaining to unique risk communication challenges (e.g., conveying small-probability events, interactions). Several recommendations are suggested for enhancing precision in perception of risk by presenting risk magnitudes numerically and visually. Overall, there are little data to suggest best practices for verbal communication of risk magnitudes. Across the 3 formats, few overall recommendations could be suggested because of 1) lack of consistency in testing formats using the same outcomes in the domain of interest, 2) lack of critical tests using randomized controlled studies pitting formats against one another, and 3) lack of theoretical progress detailing and testing mechanisms why one format should be more efficacious in a specific context to affect risk magnitudes than others. Areas of future research are provided that it is hoped will help illuminate future best practices.