Biases in bioethics: a narrative review

Abstract

Given that biases can distort bioethics work, it has received surprisingly little and fragmented attention compared to in other fields of research. This article provides an overview of potentially relevant biases in bioethics, such as cognitive biases, affective biases, imperatives, and moral biases. Special attention is given to moral biases, which are discussed in terms of (1) Framings, (2) Moral theory bias, (3) Analysis bias, (4) Argumentation bias, and (5) Decision bias. While the overview is not exhaustive and the taxonomy by no means is absolute, it provides initial guidance with respect to assessing the relevance of various biases for specific kinds of bioethics work. One reason why we should identify and address biases in bioethics is that it can help us assess and improve the quality of bioethics work.

Cognitive biases and moral characteristics of healthcare workers and their treatment approach for persons with advanced dementia in acute care settings

“…Most attention on cognitive biases relating to medical issues was given to their potential influence on diagnostic errors, with limited research on how they might shape treatment approaches and diminish appropriate ethical reasoning capacity ( 24 ). The risk of bias influence and moral reasoning when making decisions for clinically complex ethical situations, such as those involving the course for or against life-sustaining treatment, has been given less attention in research ( 36 , 37 ). Two reviews on cognitive biases in the context of medical decisions reported that one- to two-thirds of the studies found that risk intolerance or overconfidence resulted in availability, representativeness, and anchoring biases, which may affect the decision process ( 24 , 28 ).…”

Standard of practice in pharmacy informatics

“…• Cognitive biasesthese arise from the brain's attempt to simplify processing information and are unconscious errors in thinking that affect judgements and decisions; more than 180 human biases have been defined and classified by psychologists [19][20][21] • Lack of complete dataincomplete data are not truly representative and are therefore inherently biased • Logical fallaciesthese stem from the use of invalid or faulty reasoning in the construction of an argument which may appear to be well reasoned if not otherwise noticed. 22 To prevent bias from entering health information system models, pharmacy informaticians should ensure effective and considered consultation with relevant stakeholders and make reasonable attempts to continuously adapt information models as more information is learnt.…”

“…Challenges in the design and use of data (Figure 1) that can lead to inequality and discrimination, especially for culturally and linguistically diverse groups (e.g. Aboriginal and Torres Strait Islander Peoples) include: Cognitive biases — these arise from the brain’s attempt to simplify processing information and are unconscious errors in thinking that affect judgements and decisions; more than 180 human biases have been defined and classified by psychologists 19–21 Lack of complete data — incomplete data are not truly representative and are therefore inherently biased Logical fallacies — these stem from the use of invalid or faulty reasoning in the construction of an argument which may appear to be well reasoned if not otherwise noticed 22 …”

Unveiling the interplay between evidence, values and cognitive biases. The case of the failure of the AstraZeneca COVID‐19 vaccine

“…Typically, cognitive biases are described as predictable (they can be expected to appear under certain circumstances), universal (they affect all human beings), tenacious (they tend to affect even those who know them) and unconscious (they are cognitive processes of which the subject is unaware). In the medical field, more than a hundred cognitive biases have been detected, both in research and in the clinic 9–11 . Some examples are the availability bias, that is, the tendency to judge things as being more likely, or frequently occurring, if they readily come to mind; the confirmation bias, that is, the tendency to look for confirming evidence to support a hypothesis rather than look for disconfirming evidence to refute it; the expectation bias, that is, the tendency to provide outcomes in accordance with what is expected and the ascertainment bias which occurs when prior expectations (e.g., stereotyping and gender bias) affect our judgement.…”

“…In the medical field, more than a hundred cognitive biases have been detected, both in research and in the clinic. [9][10][11] Some examples are the availability bias, that is, the tendency to judge things as being more likely, or frequently occurring, if they readily come to mind; the confirmation bias, that is, the tendency to look for confirming evidence to support a hypothesis rather than look for disconfirming evidence to refute it; the expectation bias, that is, the tendency to provide outcomes in accordance with what is expected and the ascertainment bias which occurs when prior expectations (e.g., stereotyping and gender bias) affect our judgement. Given that they are rooted in unconscious thought processing, cognitive biases cannot be regarded as reasons, either good or bad, 12 but it remains an open question whether or not they may have some epistemic benefits in specific circumstances, for example, when they work as heuristics.…”