Communicating Conditional Probabilities in Medical Practice

Böcherer-Linder, Katharina; Binder, Karin; Büchter, Theresa; Eichler, A.; Krauß, Stefan; Steib, Nicole; Vogel, Markus

doi:10.52041/iase.icots11.t7d1

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…Since Bayesian situations often occur in medical contexts in which a physician is supposed to advise patients, the way of (verbally) communicating the meaning of a positive test result is very important ( Gigerenzer et al, 1998 ; Brose et al, 2023 ). Unfortunately, counselors are not always communicating the results in a correct and comprehensible way ( Gigerenzer et al, 1998 ; Ellis and Brase, 2015 ; Prinz et al, 2015 ) and medical students cannot even identify a high-quality communication with the correct value when it is presented as one out of several short video clips ( Böcherer-Linder et al, 2022 ). To improve (pictorial) communication, the Harding Center for Risk Literacy developed fact boxes and icon boxes ( Schwartz et al, 2007 ; McDowell et al, 2019 ), which are also based on the concept of natural frequencies.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

How general is the natural frequency effect? The case of joint probabilities

Stegmüller,

Binder,

Krauss

2024

Front. Psychol.

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Natural frequencies are known to improve performance in Bayesian reasoning. However, their impact in situations with two binary events has not yet been completely examined, as most researchers in the last 30 years focused only on conditional probabilities. Nevertheless, situations with two binary events consist of 16 elementary probabilities and so we widen the scope and focus on joint probabilities. In this article, we theoretically elaborate on the importance of joint probabilities, for example, in situations like the Linda problem. Furthermore, we implemented a study in a 2×5×2 design with the factors information format (probabilities vs. natural frequencies), visualization type (“Bayesian text” vs. tree diagram vs. double tree diagram vs. net diagram vs. 2×2 table), and context (mammography vs. economics problem). Additionally, all four “joint questions” (i.e., P(A∩B),P(A¯∩B),P(A¯∩B¯),P(A∩B¯)) were asked for. The main factor of interest was whether there is a format effect in the five visualization types named above. Surprisingly, the advantage of natural frequencies was not found for joint probabilities and, most strikingly, the format interacted with the visualization type. Specifically, while people’s understanding of joint probabilities in a double tree seems to be worse than the understanding of the corresponding natural frequencies (and, thus, the frequency effect holds true), the opposite seems to be true in the 2 × 2 table. Hence, the advantage of natural frequencies compared to probabilities in typical Bayesian tasks cannot be found in the same way when joint probability or frequency tasks are asked.

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Section: Theoretical Frameworkmentioning

confidence: 99%

How general is the natural frequency effect? The case of joint probabilities

Stegmüller,

Binder,

Krauss

2024

Front. Psychol.

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“…Furthermore, one prior study demonstrated that medical students can better distinguish between adequate and inadequate communication after having had Bayesian reasoning training (without directly being trained in communication skills; [21,22]). In the present study, though we also focus on Bayesian reasoning problems, we specifically look at the influence of different ways of communicating statistical information on the ability of patients to deduce the positive predictive value.…”

Section: Physician-patient Communicationmentioning

confidence: 99%

Bayesian versus diagnostic information in physician-patient communication: Effects of direction of statistical information and presentation of visualization

Brose,

Binder,

Fischer

et al. 2023

PLoS ONE

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Background Communicating well with patients is a competence central to everyday clinical practice, and communicating statistical information, especially in Bayesian reasoning tasks, can be challenging. In Bayesian reasoning tasks, information can be communicated in two different ways (which we call directions of information): The direction of Bayesian information (e.g., proportion of people tested positive among those with the disease) and the direction of diagnostic information (e.g., the proportion of people having the disease among those tested positive). The purpose of this study was to analyze the impact of both the direction of the information presented and whether a visualization (frequency net) is presented with it on patient’s ability to quantify a positive predictive value. Material and methods 109 participants completed four different medical cases (2⨯2⨯4 design) that were presented in a video; a physician communicated frequencies using different directions of information (Bayesian information vs. diagnostic information). In half of the cases for each direction, participants were given a frequency net. After watching the video, participants stated a positive predictive value. Accuracy and speed of response were analyzed. Results Communicating with Bayesian information led to participant performance of only 10% (without frequency net) and 37% (with frequency net) accuracy. The tasks communicated with diagnostic information but without a frequency net were correctly solved by 72% of participants, but accuracy rate decreased to 61% when participants were given a frequency net. Participants with correct responses in the Bayesian information version without visualization took longest to complete the tasks (median of 106 seconds; median of 13.5, 14.0, and 14.5 seconds in other versions). Discussion Communicating with diagnostic information rather than Bayesian information helps patients to understand specific information better and more quickly. Patients’ understanding of the relevance of test results is strongly dependent on the way the information is presented.

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Teaching and learning of probability

Batanero

Álvarez-Arroyo

2023

ZDM Mathematics Education

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In this paper, we develop a personal synthesis of the most outstanding research on the teaching and learning of probability in the past years. We conducted a systematic search to examine publications on this topic in mathematics education, statistics education, education, and psychology journals. This exploration was complemented by additional studies published in conference proceedings or books. We classified these papers to highlight the main recent research tendencies in the field, according to the theme studied and considering the research objectives. Epistemological analyses suggest that informal inference based on simulation diminishes the topic abstraction but reduces probability to its frequentist view. Topics receiving particular attention include children’s probabilistic knowledge, the effect of visualizations on solving conditional probability problems, teachers’ education and probability modelling. In the final section, we recommend relevant points in which more investigation is needed to complete our knowledge about teaching and learning. In particular, we miss research on teachers’ mathematical knowledge of many probability concepts and on their didactic knowledge.

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Communicating Conditional Probabilities in Medical Practice

Cited by 3 publications

References 17 publications

How general is the natural frequency effect? The case of joint probabilities

How general is the natural frequency effect? The case of joint probabilities

Bayesian versus diagnostic information in physician-patient communication: Effects of direction of statistical information and presentation of visualization

Teaching and learning of probability

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