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Educational strategies in the health professions to mitigate cognitive and implicit bias impact on decision making: a scoping review



Cognitive and implicit biases negatively impact clinicians’ decision-making capacity and can have devastating consequences for safe, effective, and equitable healthcare provision. Internationally, health care clinicians play a critical role in identifying and overcoming these biases. To be workforce ready, it is important that educators proactively prepare all pre-registration healthcare students for real world practice. However, it is unknown how and to what extent health professional educators incorporate bias training into curricula. To address this gap, this scoping review aims to explore what approaches to teaching cognitive and implicit bias, for entry to practice students, have been studied, and what are the evidence gaps that remain.


This scoping review was guided by the Joanna Briggs Institute (JBI) methodology. Databases were searched in May 2022 and included CINAHL, Cochrane, JBI, Medline, ERIC, Embase, and PsycINFO. The Population, Concept and Context framework was used to guide keyword and index terms used for search criteria and data extraction by two independent reviewers. Quantitative and qualitative studies published in English exploring pedagogical approaches and/or educational techniques, strategies, teaching tools to reduce the influence of bias in health clinicians' decision making were sought to be included in this review. Results are presented numerically and thematically in a table accompanied by a narrative summary.


Of the 732 articles identified, 13 met the aim of this study. Most publications originated from the United States (n=9). Educational practice in medicine accounted for most studies (n=8), followed by nursing and midwifery (n=2). A guiding philosophy or conceptual framework for content development was not indicated in most papers. Educational content was mainly provided via face-to-face (lecture/tutorial) delivery (n=10). Reflection was the most common strategy used for assessment of learning (n=6). Cognitive biases were mainly taught in a single session (n=5); implicit biases were taught via a mix of single (n=4) and multiple sessions (n=4).


A range of pedagogical strategies were employed; most commonly, these were face-to-face, class-based activities such as lectures and tutorials. Assessments of student learning were primarily based on tests and personal reflection. There was limited use of real-world settings to educate students about or build skills in biases and their mitigation. There may be a valuable opportunity in exploring approaches to building these skills in the real-world settings that will be the workplaces of our future healthcare workers.

Peer Review reports


Human judgement is inherently subjective, uncertain, and therefore, prone to bias [1]. In healthcare environments, errors in clinical reasoning can have a devastating impact on individuals and populations [2]. To mitigate risk of bias arising from cognitive and implicit influences, codes of conduct have been established to provide moral standards that guide clinical decision-making.

Egalitarian theory, a material principle of distributive justice, dictates that equitable access to health resources should be afforded to all members of the community [3]. Variations in access to healthcare based on non-clinical factors such as demographic and individual attributes continue to impact safety and quality of care in high income countries [4]. This variation can influence timely access to health resources when errors in reasoning processes missed or delayed diagnosis [5]. Diagnostic related medical errors are common and are a major contributor of patient harm [6]. In Australia, it has been estimated that 140,000 cases of diagnostic error occur annually, leading to 2,000-4,000 deaths [7].

Diagnostic and treatment errors are commonly attributed to cognitive factors [7]. Clinical decision-making, however, is an inherently social activity, and as a result, is subject to a range of situational factors. In this context, health professionals routinely reason their way through a complex array of decisions under conditions of uncertainty [2]. Cognitive and implicit bias are identified as two distinct sub-types influencing decision making in practice [8]. To date, effective strategies to systematically address diagnostic and treatment errors have mainly focussed on addressing the knowledge deficits of health professionals. This has been done with limited reference to curriculum development and pedagogical strategies to prepare the future health workforce. Education programs for new health professionals may provide an opportunity to systematically raise awareness of the role of bias in diagnostic and treatment errors and potentially mitigate the influence of bias on clinical decision making.

Cognitive bias

Tversky and Kahneman introduced the term ‘cognitive bias’ in the early 1970s to explain people’s systematic, but flawed approach to judgments and decision making [9]. Bias occurs when clinicians incorrectly interpret or apply the clinical data they have obtained [9]. It has been posited that health professionals are susceptible to cognitive biases when making clinical decisions under conditions of uncertainty [10,11,12]. To date, over 30 cognitive biases that impact medical decision making have been identified, however there may be many more in existence [13]. Common types of cognitive biases include availability, anchoring, confirmatory, and stereotyping biases [14, 15]. Importantly cognitive bias relates to how clinicians perceive and interpret both subjective and objective clinical data. Implicit bias influences how clinicians perceive and respond to others based on personal characteristics, such as sex, age, gender, weight, race, religion, socioeconomic status, and/or bodily difference [8]

Cognitive bias results from major processes that govern human cognition. Tversky and Kahneman’s [16] influential dual process model of decision making posits that humans use two systems to process information. System 1 underlies fast, automatic, intuitive decisions that make incomplete use of available information and rational processes, and instead rely on unconscious use of heuristics, or automatic thought patterns (short cuts) that reduce a complex scenario into a simpler set of parameters to facilitate efficient decision making [1, 16]. In general, System 1 thinking is often a decision making ‘default’ because it is quick, efficient, and less taxing [8]. Because of these features, it could be argued that System 1 thinking is also crucial in responding to emergency situations. While this approach usually does facilitate correct decision making, it is also open to error and therefore is an issue for clinicians and their patients [16]. In contrast, System 2 thinking is characterized by slow, effortful, deliberate decisions, associated with unfamiliar or difficult situations or judgements [16]. However, the more knowledge and experience a clinician acquires, the more mental short cuts they also possess, leading to greater adoption of Systems 1 type thinking [8]. In the healthcare setting, clinical decisions are often made under conditions of stress and/or uncertainty. Therefore, clinicians tend to, and sometimes must, adopt System 1 type thinking and employ heuristics as a cognitive resource saving strategy when making decisions. Notwithstanding this theory, commentators have called into question the view that awareness raising in and of itself reduces the impacts of cognitive bias and suggest that other contextual factors might be at play [17,18,19,20].

Implicit bias

Implicit bias involves the unconscious attitudes that precipitate unintentional discriminatory behaviour [21, 22]. Automatically classifying or grouping patients based on certain characteristics affects clinicians’ judgements relating to, and their interactions with, patients [21, 22]. Implicit bias can disadvantage those that are already vulnerable and impacts all stages of the clinician/patient relationship [23].

For over a decade, commentators have recognized an association between implicit bias and adverse events in hospitals. Instances of implicit bias in healthcare include poor pain management toward Black patients [24], suboptimal management of suicidal ideation in the elderly [25], and delayed diagnosis of chronic obstructive pulmonary disease among women compared to men despite having similar signs and symptoms [26].

How we perceive others, and the development of social or cultural biases, evolves from early childhood experiences [8]. It is thought that we develop these pathways to help provide a quick and efficient determination of groups of people [8]. This may be expressed as overt biases (i.e., explicit) such as open racism or homophobia, or more commonly as implicit bias. Studies have shown that with age, our explicit bias views reduce whereas our implicit bias views remain the same [27]. Healthcare professionals have been shown to manifest implicit biases similar to general population levels [23], which presents a concerning influence on decisions and judgements made by clinicians.

As there is potential for cognitive and implicit biases to unduly influence clinical decisions related to patient assessment (diagnostic and treatment decisions) and management (omissions), strategies to mitigate these known risks are urgently needed. Due to their unconscious nature, biases are inherently fraught and challenging to overcome [21]. Debiasing strategies in clinical medicine have been studied extensively [7, 28], and there is some evidence that targeted training can improve recognition of cognitive biases [29]. To date, little work has been undertaken to identify debiasing strategies in nursing and allied health professions [14, 30]. Yet, despite recognition of the importance of incorporating instructions about cognitive and implicit biases into tertiary level medical and health sciences curricula, the extent to which this occurs, and specific pedagogical techniques and strategies that are used, have not been systematically reported. The primary research question addressed in this review is What approaches to teaching cognitive and implicit bias, for entry to practice students, have been studied, and what are the evidence gaps that remain?

Secondary questions include:

  • What pedogeological approaches are used when teaching healthcare students about cognitive and implicit bias?

  • What educational techniques/tools/strategies are used to deliver educational interventions that attempt to mitigate cognitive and implicit biases?

  • Which specific types of cognitive and implicit biases, if any, are being addressed?

  • How do educators assess/evaluate the effectiveness of educational interventions designed to mitigate cognitive and/or implicit bias?

For this scoping review, tertiary level education refers to education that, upon successful completion, receives an award spanning the Australian Qualifications Framework (AQF) levels 5-10 [31]. These awards may include bachelor’s degrees; graduate certificates and diplomas; master’s degrees; and higher doctoral degrees [31]. Health disciplines included in this review include medicine, nursing and midwifery, allied health, and biomedicine.


This review was guided by Joanna Briggs Institute (JBI) methodology for scoping reviews [32] and registered with Open Science Framework registries ( The Population, Concept and Context (PCC) framework was used to guide the purpose of the review and construct the eligibility criteria for papers to be included (see Table 1). The population of interest was pre-registration healthcare-based students undertaking tertiary level education in any healthcare-related discipline – that is, the future workforce. As such, studies focusing health clinicians alone, were excluded as it was considered that practicing clinicians in the current workforce have greater experience in the delivery of care with structural supports in place to mitigate bias. Studies comparing both students and practicing clinicians were excluded if the results were not presented separately for each cohort. Further, studies exploring bias relating to student enrolments at universities were excluded. The concept for this review focused on- research reports exploring pedagogical approaches and/or educational techniques, strategies, and/or teaching tools to reduce the influence of bias in health clinicians' decision making. Studies exploring bias without identifying an educational strategy/approach were excluded. All types of cognitive biases (specified either broadly or specifically) or the terms cognitive bias or ‘cognitive errors’ and implicit bias were included. Papers that referred to 'decision making' or ‘clinical/diagnostic reasoning’ in general without specifically referring to cognitive/implicit biases were excluded given that many factors and processes besides cognitive/implicit bias are involved in reasoning and decision making. The context of selected studies was settings in which healthcare can be taught, such as universities, hospitals, residential facilities, and clinics. Continuing Professional Development programs, which are undertaken by practicing professionals within health organisations were excluded, given that such courses are not targeted at entry to practice students.

Table 1 Inclusion and exclusion criteria

A search strategy was developed to identify published and unpublished quantitative and qualitative studies that presented original data to support their findings. An initial limited search of MEDLINE and Cumulative Index to Nursing & Allied Health (CINAHL) was performed to identify articles on cognitive and implicit bias to identify relevant keywords and index terms to develop the full search strategy. The complete search strategy was then applied to CINAHL, Cochrane, JBI, Medline, ERIC, Embase and PsycINFO databases in May 2022 (last searched conducted 27 May 2022). Grey literature was identified by searching Open Dissertations and Google Scholar. Year limits were not placed on the search. The reference lists of systematic and scoping reviews identified at the full text screening phase were also subject to the screening process. Conference abstracts, protocols, editorials, discussion, and opinion papers were excluded as they were considered to have insufficient information, and/or have the potential to reflect individual preferences or interests. Studies were limited to those published in English and focusing on humans. An example of the search string used for Medline OVID can be found as part of supplementary material.

A data extraction tool (Table 2) was developed by the investigative team to guide data collection relating to population, concept, context, study methods and key findings relevant to this review. To assess inter-rater reliability, two members of the research team independently used the tool to extract data from 10% of the identified articles. Two rounds of testing were required to reach a threshold agreement of 95%. Two independent reviewers then completed title and abstract screening, and full text screening. Any disagreements that arose between reviewers at each stage of the selection process were resolved through discussion with a third member of the investigative team. Once data was extracted from the included articles, both reviewers then analysed each bias separately according to 1) the approach to education and 2) the approach to learning assessment employed by the study.

Table 2 Data extraction tool


The search strategy (including studies identified in other reviews) yielded 732 studies. These citations were uploaded into EndNote (Clarivate, version 9.3.3) and 155 duplicates were removed. The remaining citations were then uploaded to Covidence (version 2974 da970e19), and another 18 duplicates were removed. Two independent reviewers examined the titles and abstracts of 559 papers against the inclusion and exclusion criteria (see Table 1), and 90 papers progressed to full text review. At the full text screening phase, agreement could not be reached on two studies, so a third member of the investigative team was approached to independently review these papers for eligibility. Following the full text review, 13 articles were included in the review. Reasons for exclusion of articles at full text are reported in the Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Review (PRISMA-ScR) flow diagram [33] (Fig. 1).

Fig. 1
figure 1

PRISMA ScR flow diagram reporting the search, screening, and study selection process

Study characteristics of the 13 papers included in this review are outlined in Table 3. Publication years ranged from 1996 to 2021; the majority (n=12) were published within the past 10 years. Most publications originated from the United States (n=9), followed by Malaysia (n=2) and Canada (n=2). Educational practice in medicine accounted for a majority of studies (n=8), followed by nursing and midwifery (n=2), biomedicine (n=2), and pharmacy (n=1). Eight studies focused on implicit bias and 5 studies focused on cognitive bias. All studies were presented by a university (n=13) and most education occurred in a university setting (n=12). Study designs included qualitative studies (n=2), randomized controlled trials (n=1), mixed methods (n=2), quasi-experimental (n=4) and cross-sectional (n=4).

Table 3 Characteristics of studies

Cognitive bias and approach to education

Table 4 outlines the categories identified regarding the pedagogical approaches and teaching strategies and techniques used for teaching cognitive biases. Availability bias was the most common cognitive bias covered (n=4), followed by confirmation bias (n=3) and self-satisficing (n=3). The least common biases to be explored were the framing effect (n=1) and the representative heuristic (n=1). Most studies did not provide a guiding educational philosophy or framework (n=4). Sherbino and colleagues [18] used Croskerry’s model to guide their teaching of cognitive forcing strategies. The most common delivery mode was face-to-face teaching (n=4). The only other form of delivery of content was through simulation (n=1). All papers (n=5) focused on a single education session. Four techniques and strategies were identified to teach cognitive biases. These include case-based learning (n=2); use of mnemonics (n=2); debiasing techniques - not clearly stated (n=2); and clinical placement (n=1).

Table 4 Cognitive bias - approach to education

Approach to assessment

Table 5 outlines the key themes identified relating to assessment and evaluation of learning of cognitive biases. Three types of assessment were identified from the studies. These were reflective practice (n=1), case-based short answer quiz (n=2), and case-based multiple choice question quiz (n=2).

Table 5 Cognitive bias – approach to assessment

Implicit bias and approach to education

Table 6 summarizes the categories identified describing pedagogical approaches, teaching strategies and techniques used to address implicit biases. Racial implicit bias was the most common focus within the included studies (n=4), followed by implicit bias in general (n=3) and weight (obesity) bias (n=2). Approaches to teaching other types of implicit bias were identified in one article. The majority of studies (n=6) did not indicate a guiding philosophy or conceptual framework to educate students. Half the studies (n=4) focused on a single educational session. The most common delivery method was face-to-face (n=5), followed by flipped classroom approach (n=2), and remote online learning (n=1). A wide range of techniques were used to deliver educational content. These included group work (n=6); readings (n=5); reflection for learning (n=5); use of the Implicit Association Test (IAT) [46] (n=4); use of media (n=2); role play exercises (n=1); brainstorming exercises (n=1); community service (n=1); social identity mapping (n=1); photovoice (n=1); and the fishbowl technique (n=1).

Table 6 Implicit bias – approach to education

Approach to assessment

Table 7 provides an overview of the assessment and evaluation of learning strategies employed to address specific types of implicit biases. A wide range of assessment items were identified. The most common assessment tools were the use of a written reflective essay (n=3) and the Jefferson Scale of Empathy standardized assessment tool (n=3) [47]. Other assessment strategies included the following: a survey of the student’s perception of the course (n=2); the reflective practice questionnaire standardized tool (n=2); role play of skills assessment (n=1), portfolio of work (n=1); short answer exam (n=1); discussion threads (n=1); class participation (n=1); and the Anti-fat Attitudes Questionnaire standardized tool (n=1).

Table 7 Implicit bias – approach to assessment


In this review we sought to answer the primary question: what approaches to teaching cognitive and implicit bias, for entry to practice students, have been studied and what are the evidence gaps that remain? Our scope identified a small body of published literature describing the phenomena of cognitive and/or implicit bias and its application in curricula for courses leading to registration in the health professions. Most studies in the current review described teaching sessions delivered to medical students undertaking university-based programs in North America, where the focus was addressing implicit bias, as opposed to cognitive bias.

This review highlights a critical gap in the evidence available outlining how educators of health professionals teach cognitive and implicit bias and their impact on diagnostic and treatment-based decisions. This gap is notable for two reasons. First, it is well-recognised that bias in healthcare remains systemic and has potentially devastating impacts on safety and quality of care [48, 49]. Second, the responsibilities now incumbent on employers of health professionals in many jurisdictions to meet their obligations under anti-discrimination law mean that attention is paid to educating the workforce about implicit bias and strategies needed to address it. In this respect, tertiary education providers must work proactively to develop evidence-based approaches to learning and teaching aimed at mitigating all forms of bias that have the potential to impact the delivery of high-quality healthcare.

Cognitive bias

In addressing the potential influence of heuristic thinking on diagnostic and therapeutic decision-making, availability bias – the tendency to use information that comes to mind quickly when making judgments – was the focus of most of the strategies described [50]. This finding aligns with the view that the availability heuristic is among the most utilized by medical practitioners when making diagnostic decisions in practice [50]. A recent experimental study of medical residents’ diagnostic reasoning for cases of dengue fever by Li and colleagues [50] found that availability bias led to diagnostic error and that misdiagnosis cannot always be effectively addressed using a reflective approach. Other heuristics specifically identified in our scoping review included self-satisficing - searching through available diagnostic alternatives until an acceptable threshold is met [51] - and confirmation bias - the tendency to search for, interpret, favor, and recall information in a way that confirms or supports one's prior beliefs or values [51]. Less frequently explored were the framing effect – the same problem is presented in multiple settings, but different representations of information influence the outcome [52] —and the representative heuristic — knowledge of prior probabilities of a characteristic in a similar population incorrectly influence decision outcome [53].

In terms of theoretical orientation taken to explore cognitive bias in educational programs, most of these studies drew, to some extent, on dual systems theory [16]. Sherbino and colleagues [18] adopted Croskerry’s model to evaluate the effect of teaching of cognitive forcing strategies on diagnostic error in medical students. Croskerry’s model proposes that a prerequisite to addressing the problem of cognitive error (in emergency medicine) is to first ensure learners understand dual processing theory. While Croskerry recommended strategies to deal with different categories of error, along with an awareness of how cognitive biases can influence patient outcomes in different clinical situations as a strategy, Sherbino and colleagues [18], found this conceptual framework to be ineffective, which is a notion that has gathered support recently [17, 19, 20].

Implicit bias

In the 8 studies addressing implicit bias, race, weight (obesity), age, disability and substance use, and mental illness were the attributes addressed using a range of educational approaches. While much of the literature was published in North America, all implicit biases noted may be considered protected attributes, and as such, characteristics against which it is unlawful to discriminate [54]. Unlike the studies focused on cognitive bias, none of the studies exploring implicit bias cited specific educational theories to inform pedagogy and most utilized a single session to address the issue via face-to-face delivery. Considering both the ethical responsibilities outlined in health professionals’ codes of conduct and the legislative frameworks in place in many jurisdictions to protect citizens against discrimination, it is timely to consider how a curriculum to address implicit bias based on the different types of protected attributes might be beneficial to inform programs educating the future health workforce.

A variety of techniques were identified to engage students in and reflect on learning about implicit bias. These included working in groups, role play, fishbowl technique and brainstorming. Innovative participatory methods were also reported in a small number of studies to engage students to reflect on their own identity such as social identity mapping and the use of photovoice. Several studies reported using the Implicit Association Test (IAT) as a starting point for critical reflection, which is consistent with a review by Kruse and colleagues [55], who found that the IAT is commonly incorporated into education for healthcare students and provides a strategy to assess awareness of implicit biases. Few of the included studies employed strategies in practical or real-world environments. That is, in contrast to reviews of interventions to study or mitigate biases in healthcare professionals [56, 57], only one of the included studies in this review referred to service learning or patient/social contact as pedagogical strategies, despite evidence that such learning experiences can lead to bias mitigation by increasing compassion and reflective capacity [58].

Implicit bias by its very nature is unconscious, meaning the actions and decisions of health professionals are influenced without their awareness [59]. However, none of the included papers explored the concept of Speaking up for patient safety. Speaking up refers to health professionals expressing concerns if they observe the actions of others (e.g. mistakes, lapses, rule breaking) that can negatively impact patient safety and quality of care [60]. Barriers to staff speaking up are well known and include institutional, interpersonal, and individual factors [61]. Educating tertiary students regarding their knowledge and awareness of implicit bias should be accompanied with a framework that provides them with the tools and knowledge to speak up if they were to observe bias in action.

The findings from this review indicate that assessment of student learning about the nature and impact of implicit bias has tended to rely on traditional approaches such as tests, written reflective essays and exams. Some self-assessment tools such as the Jefferson Scale of Empathy standardized assessment and the Anti-fat Attitudes Questionnaire were employed to evaluate learning. Less commonly authentic modes of assessment such as portfolio work were utilized to assess learner knowledge.

The complex and diverse set of competencies that are required of health professionals means that no single approach to assessment is adequate [62]. In terms of Miller’s pyramid, the predominance of written, test-based assessments employed in the current review indicates that bias mitigation interventions in entry-to-practice degrees tend to evaluate student learning at the lowest levels of ‘Knows’ and/or ‘Knows How.’ Assessing the higher levels of Miller’s pyramid – particularly the ‘Does’ level – requires assessing students in real-world settings such as a clinical context [63].

The importance of multiple and varied approaches to student assessment is highlighted in Sukhera and Watling’s [64] framework for incorporating recognition of implicit bias into education for health professionals. The framework proposes that comprehensively assessing learning in this area requires several different assessment strategies targeting distinct aspects of implicit bias recognition. For example, whereas tests assess knowledge about implicit bias, reflective exercises and portfolios are more appropriate for assessing students’ development of self-awareness of their own implicit biases, while observed clinical evaluations or assessments of students during practicums or other real-world settings, are appropriate for assessing the development of conscious efforts to overcome implicit bias [64]. Considering this recommendation, it is notable that few included studies used numerous and/or diverse assessment methods. Furthermore, none of the included studies employed the observation of clinical evaluations, suggesting there is limited assessment of the extent to which students develop and maintain conscious efforts to overcome biases. This finding is surprising, given it is well recognized that clinical placements are an essential component of clinical education [65, 66].


While the search strategy included eight databases and Google, not all relevant papers may have been identified. Similarly, limiting our search strategy to English publications may have excluded relevant papers. Our population of interest was tertiary students in healthcare disciplines, and as a consequence, our exclusion of studies with mixed samples of students and healthcare professionals, and students and residents, may have potentially omitted studies that employed pedagogical and/or assessment strategies not otherwise identified here. Papers that were excluded due to incorrect population, concept or context during screening can be found as part of supplementary material. As a scoping review, our study did not include quality appraisal or grading of evidence. Nonetheless it should be noted that the high degree of variability in methods and outcomes limits more rigorous appraisal of the evidence.

Implications for teaching and learning

Antidiscrimination laws in many countries now rule it unlawful to delay or limit access to health care based on specified personal characteristics, including but not limited to age, disability, race, sex or gender identity [67, 68]. As an example, within Australia, federal laws of this type include the Age Discrimination Act 2004 [69], the Disability Discrimination Act 1992 [70], Racial Discrimination Act 1975 [71] and the Sex Discrimination Act 1984 [72]. Understanding that these laws apply to cases of explicit and overt discrimination, it is unsure if they could be enforced if implicit bias was found to be a contributing factor in a coronal inquiry into the death of an individual. Given the potential impacts of bias due to discrimination on safe, timely access to health care, it is incumbent upon tertiary education providers responsible for training our future health workforce to ensure graduates receive education of the nature and type of clinical errors or practice differences that may result from implicit bias and the strategies to mitigate these.

Training in the context of direct participation in clinical care (during a clinical placement) plays a major role in health professional education and preparedness [65, 66], therefore educators need to design learning objectives for placements that focus on translating knowledge and awareness of bias into practice and the leadership to respond when they observe the actions of others for the benefit of patient care and safety.


In this review, we sought to explore what approaches to teaching cognitive and implicit bias have been studied and what are the evidence gaps that remain for pre-registration students. A range of pedagogical strategies were employed; most commonly, these were face-to-face, class-based activities such as lectures, tutorials, and simulations, and were delivered predominantly across one as opposed to multiple sessions. Assessments of student learning were primarily based on tests and personal reflection. There was limited use of real-world settings (i.e., placements or practicums) to educate students about or build skills in biases and their mitigation, and no studies assessed students’ learning in practical settings. Further work is urgently required to develop innovative pedagogical approaches to developing the skills of future healthcare professions in recognising and mitigating the effect of different biases, and approaches to evaluate these skills comprehensively and meaningfully. There may be a valuable opportunity in exploring approaches to building these skills in the real-world settings that will be the workplaces of our future healthcare workers.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary information files.


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The investigative team were awarded a Faculty of Medicine, Dentistry and Health Science Learning and Teaching Initiative Seed Funding Grant to undertake this scoping review.

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All authors were involved in the conceptualization of the project and funding acquisition. JT, HB, SMcK, AL, SM, NH, SK and MG were responsible for project design. JT and HB reviewed papers and conducted data analysis. JT, HB and MG developed the initial manuscript draft. All authors contributed to the final review and edits of the manuscript. The author(s) read and approved the final manuscript.

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Correspondence to John Thompson.

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Thompson, J., Bujalka, H., McKeever, S. et al. Educational strategies in the health professions to mitigate cognitive and implicit bias impact on decision making: a scoping review. BMC Med Educ 23, 455 (2023).

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