Cognitive biases and heuristics in medical decision making: a critical review using a systematic search strategy

A segment-based framework for explainability in animal affective computing

Recent developments in animal motion tracking and pose recognition have revolutionized the study of animal behavior. More recent efforts extend beyond tracking towards affect recognition using facial and body language analysis, with far-reaching applications in animal welfare and health. Deep learning models are the most commonly used in this context. However, their "black box" nature poses a significant challenge to explainability, which is vital for building trust and encouraging adoption among researchers. Despite its importance, the field of explainability and its quantification remains under-explored. Saliency maps are among the most widely used methods for explainability, where each pixel is assigned a significance level indicating its relevance to the neural network's decision. Although these maps are frequently used in research, they are predominantly applied qualitatively, with limited methods for quantitatively analyzing them or identifying the most suitable method for a specific task. In this paper, we propose a framework aimed at enhancing explainability in the field of animal affective computing. Assuming the availability of a classifier for a specific affective state and the ability to generate saliency maps, our approach focuses on evaluating and comparing visual explanations by emphasizing the importance of meaningful semantic parts captured as segments, which are thought to be closely linked to behavioral indicators of affective states. Furthermore, our approach introduces a quantitative scoring mechanism to assess how well the saliency maps generated by a given classifier align with predefined semantic regions. This scoring system allows for systematic, measurable comparisons of different pipelines in terms of their visual explanations within animal affective computing. Such a metric can serve as a quality indicator when developing classifiers for known biologically relevant segments or help researchers assess whether a classifier is using expected meaningful regions when exploring new potential indicators. We evaluated the framework using three datasets focused on cat and horse pain and dog emotions. Across all datasets, the generated explanations consistently revealed that the eye area is the most significant feature for the classifiers. These results highlight the potential of the explainability frameworks such as the suggested one to uncover new insights into how machines 'see' animal affective states.

Using a Bayesian network to classify time to return to sport based on football injury epidemiological data

The return-to-sport (RTS) process is multifaceted and complex, as multiple variables may interact and influence the time to RTS. These variables include intrinsic factors related the player, such as anthropometrics and playing position, or extrinsic factors, such as competitive pressure. Providing an individualised estimation of time to return to play is often challenging, and clinical decision support tools are not common in sports medicine. This study uses epidemiological data to demonstrate a Bayesian Network (BN). We applied a BN that integrated clinical, non-clinical factors, and expert knowledge to classify time day to RTS and injury severity (minimal, mild, moderate and severe) for individual players. Retrospective injury data of 3374 player seasons and 6143 time-loss injuries from seven seasons of the professional German football league (Bundesliga, 2014/2015 through 2020/2021) were collected from public databases and media resources. A total of twelve variables from three categories (player's characteristics and anthropometrics, match information and injury information) were included. The response variables were 1) days to RTS (1-3, 4-7, 8-14, 15-28, 29-60, > 60, and 2) injury severity (minimal, mild, moderate, and severe). The sensitivity of the model for days to RTS was 0.24-0.97, while for severity categories it was 0.73-1.00. The user's accuracy of the model for days to RTS was 0.52-0.83, while for severity categories, it was 0.67-1.00. The BN can help to integrate different data types to model the probability of an outcome, such as days to return to sport. In our study, the BN may support coaches and players in 1) predicting days to RTS given an injury, 2) team planning via assessment of scenarios based on players' characteristics and injury risk, and 3) understanding the relationships between injury risk factors and RTS. This study demonstrates the how a Bayesian network may aid clinical decision making for RTS.

Risks to the clinician of risk management: recalled and anticipated consequences of decision-making

Background

Despite extensive literature studying how we make decisions in the face of uncertainty, the empirical study of real-world clinical decision-making in mental health practice remains limited. Decisions in clinical settings are not just made on the basis of clinical factors. A key non-clinical influence on decision making is the clinician's concerns about the 'threat' to themselves from a future adverse incident and the subsequent retrospective scrutiny of their decision-making. A better understanding of non-clinical processes is essential to inform better ways of guiding effective decision-making. More specifically, delineating the nature of this 'threat' process will also inform approaches to patient safety.

Aims

The objective of the current study was to delineate consequences recalled and anticipated by mental health clinicians making decisions under uncertainty.

Methods

This was an analysis of data arising from six focus group discussions with professionals involved in decisions to admit patients to psychiatric hospitals (consultant psychiatrists, approved mental health practitioners, crisis resolution home treatment teams, and liaison psychiatry practitioners) in one National Health Service Trust, UK. The data were thematically analyzed to identify the nature of 'threat' processes that arise in clinical decision-making.

Results

Themes identified included (i) the location of the effect of the anticipated/recalled consequence(s), (ii) the location of the origin of the consequence, and (iii) the nature of the consequence. The recalled and anticipated consequences of decision-making were overwhelmingly, but not exclusively, negative. The consequences were largely perceived to be directed towards the self (i.e., the clinician) and were considered to originate from external scrutiny by peers, organizational leadership, and the patient safety system/processes.

Conclusions

The process of making decisions to admit patients to hospital consistently involved the decision-maker's concern with the future consequences for them, either from a prior or future adverse event. The findings of this study, alongside other evidence of the complexity of decision-making, have implications for improving and studying clinical decision-making (and, by extension, patient care and outcomes), patient safety responses, and professional well-being.

Implicit bias in referrals to relational psychological therapies: review and recommendations for mental health services

Introduction

Timely and appropriate psychological treatment is an essential element required to address the growing burden of mental health issues, which has significant implications for individuals, society, and healthcare systems. However, research indicates that implicit biases among mental health professionals may influence referral decisions, potentially leading to disparities in access to relational psychological therapies. This study investigates bias in referral practices within mental health services, identifying key themes in referral procedures and proposing recommendations to mitigate bias and promote equitable access.

Methods

A systematic review of literature published between 2002 and 2022 was conducted, focusing on biases, referral practices, and relational psychological therapies. The search strategy involved full-text screening of studies meeting inclusion criteria, specifically those examining professional and organizational implicit bias in mental health referrals. Thematic synthesis was employed to analyze and categorize bias within these domains, providing a structured framework for understanding its impact on referral decision making processes.

Results

The search yielded 2,964 relevant papers, of which 77 underwent full-text screening. Ultimately, eight studies met the inclusion criteria and were incorporated into the review. The analysis revealed that bias development mechanisms in referral decisions occurred across five key domains: resource allocation, organizational procedures, clinical roles, decision-making, and referral preferences. These domains highlight organizational and practitioner-level factors contributing to disparities in access to psychological therapies.

Discussion

Findings suggest that implicit biases within referral processes can limit equitable access to psychological therapies, particularly relational therapies that emphasize therapeutic alliance and patient-centered care. This study provides recommendations to address these biases, including standardized referral guidelines, enhanced professional training on implicit bias, and improved oversight mechanisms within mental health services.

Positive and negative framing of complication risk and long-term outcomes influences decision-making in hip and knee arthroplasty

BACKGROUND

The framing effect has been demonstrated in a variety of settings. This study aimed to determine whether framing of complication risk in total hip arthroplasty (THA) and long-term patient satisfaction rates in total knee arthroplasty (TKA) influences patient decision-making and 'worry' using hypothetical vignettes.

METHODS

Two cross-sectional survey studies were undertaken, one based on a THA vignette and one based on a TKA vignette. Participants were randomized into a positive-framing or negative-framing group and asked to read the vignette. They were then asked to indicate whether they would proceed with surgery, and to self-report their degree of 'worry' about surgery. For the THA vignette, the positive-framing group was informed '98 % of people will have no major complications' while the negative-framing group was informed that '2 % of people will have a major complication'. For the TKA vignette, the positive-framing group was informed '80/100 of people will be happy … once they have recovered' and the negative-framing group was informed '20/100 people will be unhappy … once they have recovered'. The vignettes were otherwise identical. The primary outcome was the decision to proceed with surgery. The secondary outcome was self-reported 'worry' about surgery.

RESULTS

For the THA vignette (622 individuals) 294/310 (95 %) indicated they would proceed with surgery in the positive-framing group while 275/312 (88 %) indicated they would proceed with surgery in the negative-framing group (p = 0.0037). For the TKA vignette (623 individuals), 302/311 (97.1 %) indicated they would proceed with surgery in the positive-framing group and 280/312 (89.7 %) indicated they would proceed with surgery in the negative-framing group (p = 0.0003). Self-reported 'worry' differed based on positive or negative framing in both surveys.

CONCLUSIONS

Framing of complication risk and long-term outcomes influences patient decision-making and 'worry' in a THA and TKA vignette. This has implications for shared decision-making and informed consent.

A Scoping Review of Risk Presentation in Patient Decision Aids: Communicating Risk in Imaging

PURPOSE

Best practices exist for communicating medical information to patients, but there is less emphasis on methods to communicate risks, especially in medical imaging. The authors conducted a scoping review of patient decision aids in medical imaging and characterized the presentation methods of imaging risks.

METHODS

Embase, MEDLINE, CINAHL, and PsychINFO were searched to identify studies involving patient decision aids used in diagnostic imaging that communicated the risks. Study characteristics included the number and types of risks included, as well as the presentation type and how the probability of risks were communicated.

RESULTS

The final study included 46 articles encompassing 27 distinct patient decision aids. Mammography was the most common imaging scenario (22 of 46), followed by lung cancer screening (18 of 46), traumatic brain injury (5 of 46), and urolithiasis (1 of 46). All patient decision aids included risks associated with imaging, but the number of risk types varied from two to nine (mean, 4 ± 2). Twelve risks were identified across the 27 decision aids, but no single study included all risks. Overall, most risks (65%) were communicated with text, and the presentation mode varied by type of risk. False-positive risks were most commonly communicated using a visual format, whereas radiation risk was most commonly communicated using text format.

CONCLUSIONS

There was no consistent manner of communicating risk to patients, and visual methods such as icon arrays were not consistently used. The variability of both included risks and the risk presentation modes in the patient decision aids may affect decision making, especially among patients and caregivers with lower health literacy and numeracy.

Evaluating cognitive bias in clinical ethics supports: a scoping review

BACKGROUND

A variety of cognitive biases are known to compromise ethical deliberation and decision-making processes. However, little is known about their role in clinical ethics supports (CES).

METHODS

We searched five electronic databases (Pubmed, PsychINFO, the Web of Science, CINAHL, and Medline) to identify articles describing cognitive bias in the context of committees that deliberate on ethical issues concerning patients, at all levels of care. We charted the data from the retrieved articles including the authors and year of publication, title, CES reference, the reported cognitive bias, paper type, and approach.

RESULTS

Of an initial 572 records retrieved, we screened the titles and abstracts of 128 articles, and identified 58 articles for full review. Four articles were selected for inclusion. Two are empirical investigations of bias in two CES, and two are theoretical, conceptual papers that discuss cognitive bias during CES deliberations. Our main result first shows an overview of bias related to the working human environment and to information gathering that concerns different types of CES. Second, several determinants of cognitive bias were highlighted. Especially, stressful environments could be at risk of cognitive bias, whatever the clinical dilemma.

CONCLUSIONS

Whether a need for a better taxonomy of cognitive bias in CES is highlighted, a proposal is made to focus on individual, group, institutional and professional biases that can be present during clinical ethics deliberation. However, future studies need to focus on an ecological evaluation of CES deliberations, in order to better-characterize cognitive biases and to study how they impact the quality of ethical decision-making. This information would be useful in considering countermeasures to ensure that deliberation is as unbiased as possible, and allow the most appropriate ethical decision to emerge in response to the dilemma at hand.

Expert decision-making in clinicians: An auto-analytic ethnographic study of operational decision-making in urgent care

OBJECTIVE

To conceptualise the cognitive processes of early expert decision-making in urgent care.

BACKGROUND

Expert clinicians in the UK frequently determine suitable urgent care patient pathways via telephone triage. This strategy is promoted by policymakers but how it is performed, and its effectiveness has not been evaluated. Evaluation of early senior decision-making requires knowledge of decision-processes, influences, and goals. Previous research has focused on diagnostic decision-making and rarely studied clinicians in the field.

METHOD

We triangulated analytic autoethnography of early expert decision-making with focused ethnography of experts and trainee doctors performing the task. The study took place in a medium-sized Acute Medical Unit which provided internal medical emergency care for a mixed urban and rural population in the UK. A grounded theoretical model of expert decision-making was created via Gioia Methodology. Decision types were categorised to identify differences in solutions as well as decision processes.

RESULTS

The hallmarks of intuitive decision-making were found in most expert decisions. Experts made intuitive use of pattern-matching to extract key data from large volumes of information which triggered the spontaneous manifestation of solutions. Solutions were holistic and usually solitary. Upon manifestation solutions were consciously tested for viability with emotional affect playing a key role. Expert solutions were previously applied ones but were frequently entirely novel. Novel solution generation was not a feature of trainee decisions but moments of intuition were. Expert goals varied between optimal care for individual patients, system-wide efficiency, and equity of care. The decision environment had a large influence upon experts.

CONCLUSION

Expert clinicians employ intuitive decision-making supported by rational analysis in early urgent care decision-making. Expert solutions generated in this manner are pragmatic rather than optimal, context dependent, and seek to achieve goals which vary from moment-moment. Findings are crucial to inform research evaluating the effectiveness of early expert decision-making in urgent care as it is a high cost strategy. They also have implications for methodological approaches in future studies of expert clinical decision-making, developing artificial expert systems, and clinician training.

Cognitive biases in osteopathic diagnosis: a mixed study among French osteopaths

OBJECTIVES

Although cognitive biases are one of the most frequent causes of diagnostic errors, their influence remains underestimated in allied health professions, especially in osteopathy. Yet, a part of osteopathic clinical reasoning and diagnosis rely on the practitioner's intuition and subjective haptic perceptions. The aim of this study is to highlight links between the cognitive biases perceived by the practitioner to understand cognitive patterns during osteopathic diagnosis, and to suggest debiasing strategies.

METHODS

A mixed method based on an explanatory sequential type is used. (QUAN→QUAL). A quantitative cross-sectional survey of 272 French osteopaths and three focus groups including 24 osteopaths were carried out. The quantitative analysis includes multinominal logistic regression models and multiple correspondence analysis. The qualitative analysis is based on the framework method (within thematic analysis) and followed a step-by-step guide (Gale et al.).

RESULTS

Among 19 selected biases, osteopaths feel to be affected by 9.4 ± 0.28 biases (range [1-19], median=9). Some presumed biases would be associated, and socio-demographic (gender, age) and professional (experience and types of practice) factors would modify how practitioners perceive the presence of biases. Main debiasing solutions are supervision and transcultural clinical competences.

CONCLUSIONS

Osteopaths believe their diagnosis is impaired by the presence of cognitive biases as observed in clinical reality. Some biases are shared with medical doctors, but others are more specific to osteopaths, such as confirmation bias. To reduce their effect, the practitioner needs to be aware of these cognitive patterns of clinical reasoning, understand the patient and himself better, and use objective tests.

The Evidence-Based Medicine Management of Endometriosis Should Be Updated for the Limitations of Trial Evidence, the Multivariability of Decisions, Collective Experience, Heuristics, and Bayesian Thinking

Background/Objectives: The diagnosis and treatment of endometriosis should be based on the best available evidence. Emphasising the risk of bias, the pyramid of evidence has the double-blind, randomised controlled trial and its meta-analyses on top. After the grading of all evidence by a group of experts, clinical guidelines are formulated using well-defined rules. Unfortunately, the impact of evidence-based medicine (EBM) on the management of endometriosis has been limited and, possibly, occasionally harmful. Methods: For this research, the inherent problems of diagnosis and treatment were discussed by a working group of endometriosis and EBM specialists, and the relevant literature was reviewed. Results: Most clinical decisions are multivariable, but randomized controlled trials (RCTs) cannot handle multivariability because adopting a factorial design would require prohibitively large cohorts and create randomization problems. Single-factor RCTs represent a simplification of the clinical reality. Heuristics and intuition are both important for training and decision-making in surgery; experience, Bayesian thinking, and learning from the past are seldom considered. Black swan events or severe complications and accidents are marginally discussed in EBM since trial evidence is limited for rare medical events. Conclusions: The limitations of EBM for managing endometriosis and the complementarity of multivariability, heuristics, Bayesian thinking, and experience should be recognized. Especially in surgery, the value of training and heuristics, as well as the importance of documenting the collective experience and of the prevention of complications, are fundamental. These additions to EBM and guidelines will be useful in changing the Wild West mentality of surgery resulting from the limited scope of EBM data because of the inherent multivariability, combined with the low number of similar interventions.

Experimental Study of the Promotional Implications of Proprietary Prescription Drug Names

BACKGROUND

The meaning and characteristics embedded in proprietary drug names have the potential to affect name recall, perceptions of drug benefits and risks, and attitudes toward a drug. In this study, we examined: (1) whether names that reference the drug's medical indication affect consumers' and primary care physicians' (PCPs') perceptions of the drug and (2) whether names that overstate the drug's efficacy affect consumers' and PCPs' perceptions of the drug.

METHODS

We conducted an online experiment with 455 PCPs and 450 consumers to test the effects of fictitious proprietary prescription drug names. Participants were randomized to view one neutral drug name, one name that overstated the drug's efficacy, and five names that referenced the drug's medical indication.

RESULTS

Names that referenced the drug's medical indication and names that overstated the drug's benefit both influenced perceptions of efficacy and risk compared to neutral names. For several outcomes, names evoking medical indications had similar effects to those designed to overstate the drug's efficacy. The patterns of effects were similar for PCPs and consumers.

CONCLUSION

Findings suggest drug names alone can be sufficient to produce attitudes and risk and benefit perceptions about drugs, even in the absence of any information beyond the drug's medical indication.

Prediction accuracy of discrete choice experiments in health-related research: a systematic review and meta-analysis

Background

Discrete choice experiments (DCEs) are increasingly used to inform the design of health products and services. It is essential to understand the extent to which DCEs provide reliable predictions outside of experimental settings in real-world decision-making situations. We aimed to compare the prediction accuracy of stated preferences with real-world choices, as modelled from DCE data.

Methods

We searched six databases for health-related studies that used DCE to assess external validity and reported on predicted versus real-world choices, up to July 2024. A generalised linear mixed model was used for a meta-analysis to jointly pool the sensitivity and specificity. Heterogeneity was assessed using the I 2 statistic, and sources of heterogeneity using meta-regression. This study is registered with PROSPERO (CRD42023451545).

Findings

We identified 14 relevant studies, of which 10 were included in the meta-analysis. Most studies were conducted in high-income countries (11/14, 79%) from the European region (9/14, 64%) and analysed using mixed logit models (5/14, 36%). Pooled sensitivity and specificity estimates were 89% (95% CI:77-95, I 2 = 97%) and 52% (95% CI:32-72, I 2 = 95%), respectively. The area under the SROC curve (AUC) was 0.81 (95% CI:0.77-0.84). Our meta-regression found that DCEs for prevention-related choices had higher sensitivity than treatment-related choices. DCEs conducted under clinical settings and analysed using the heteroskedastic multinomial logit model, incorporating systematic preference heterogeneity and random opt-out utility, had higher specificity than non-clinical settings and alternative models.

Interpretation

DCEs are valuable for capturing health-related preferences and possess reasonable external validity to predict health-related behaviours, particularly for opt-in choices. Contextual factors (e.g., type of intervention, study setting, analysis method) influenced the predictive accuracy.

Funding

JJO is supported by an Australian National Health and Medical Research Council Emerging Leadership Investigator Grant (GNT1193955). EBG is supported by the Dutch Research Council (NWO-Talent-Scheme-Vidi-Grant No, 09150171910002). YZ is supported by an Australian Government Research Training Program (RTP) scholarship.

Awareness of Disease Incurability Moderates the Association between Patients' Health Status and Their Treatment Preferences

BACKGROUND

With advancing illness, some patients with heart failure (HF) opt to receive life-extending treatments despite their high costs, while others choose to forgo these treatments, emphasizing cost containment. We examined the association between patients' health status and their preferences for treatment cost containment versus life extension and whether their patients' awareness of disease incurability moderated this association.

METHODS

In a prospective cohort of patients (N = 231) with advanced HF in Singapore, we assessed patients' awareness of disease incurability, health status, and treatment preferences every 4 mo for up to 4 y (up to 13 surveys). Using random effects multinomial logistic regression models, we assessed whether patients' awareness of disease incurability moderated the association between their health status and treatment preferences.

RESULTS

About half of the patients in our study lacked awareness of HF's incurability. Results from regression analyses showed that patients with better health status, as indicated by lower distress scores (odds ratio [OR] [95% confidence interval {CI}]: 0.862 [0.754, 0.985]) and greater physical well-being (1.12 [1.03, 1.21]); and who lacked awareness of their disease's incurability were more likely to prefer higher cost containment/minimal life extension treatments compared with lower cost containment/maximal life extension.

CONCLUSIONS

This study underscores the significance of patients' awareness in disease incurability in shaping the relationship between their health status and treatment preferences. Our findings emphasize the need to incorporate illness education during goals-of-care conversations with patients and the importance of revisiting these conversations frequently to accommodate changing treatment preferences.

HIGHLIGHTS

The health status of patients with advanced heart failure was associated with their treatment preferences.Patients whose health status improved and who lacked awareness of their disease's incurability were more likely to prefer higher cost containment/minimal life extension treatments.

Exposure to conflicting COVID-19 information in undergraduates: Implications for pandemic-related information-seeking and concern, attention, and cognitive workload

Objectives: To examine college students' conflicting COVID-19 information exposure, information-seeking, concern, and cognitive functioning. Participants: 179 undergraduates were recruited in March-April 2020, and 220 in September 2020 (Samples 1 and 2, respectively). Methods: Students completed the Attention Network Test, NASA Task Load Index, and COVID-related questions. Results: In Sample 1, exposure to conflicting information predicted poorer attentional performance and greater COVID-related information-seeking and concern; concern was correlated with workload. In Sample 2, conflicting information was associated with information-seeking. In Sample 1, but not Sample 2, cognitive effects of conflicting information were mediated by information-seeking and virus-related concern. Conclusions: Conflicting COVID-19 information may undermine students' cognitive functions, bearing implications for health, academic performance, and stress. Strategies for countering these effects include enhancing the clarity of institutional messaging, and tailoring course curricula and offering workshops to students, faculty, administrators, and counseling staff to augment students' capacity to comprehend and utilize COVID-related communications.

A taxonomy of the factors contributing to the overtreatment of cancer patients at the end of life. What is the problem? Why does it happen? How can it be addressed?

Many patients with cancer approaching the end of life (EOL) continue to receive treatments that are unlikely to provide meaningful clinical benefit, potentially causing more harm than good. This is called overtreatment at the EOL. Overtreatment harms patients by causing side-effects, increasing health care costs, delaying important discussions about and preparation for EOL care, and occasionally accelerating death. Overtreatment can also strain health care resources, reducing those available for palliative care services, and cause moral distress for clinicians and treatment teams. This article reviews the factors contributing to the overtreatment of patients with cancer at the EOL. It addresses the complex range of social, psychological, and cognitive factors affecting oncologists, patients, and patients' family members that contribute to this phenomenon. This intricate and complex dynamic complicates the task of reducing overtreatment. Addressing these driving factors requires a cooperative approach involving oncologists, oncology nurses, professional societies, public policy, and public education. We therefore discuss approaches and strategies to mitigate cultural and professional influences driving overtreatment, reduce the seduction of new technologies, improve clinician-patient communication regarding therapeutic options for patients approaching the EOL, and address cognitive biases that can contribute to overtreatment at the EOL.

When common cognitive biases impact debriefing conversations

Healthcare debriefing is a cognitively demanding conversation after a simulation or clinical experience that promotes reflection, underpinned by psychological safety and attention to learner needs. The process of debriefing requires mental processing that engages both "fast" or unconscious thinking and "slow" intentional thinking to be able to navigate the conversation. "Fast" thinking has the potential to surface cognitive biases that impact reflection and may negatively influence debriefer behaviors, debriefing strategies, and debriefing foundations. As a result, negative cognitive biases risk undermining learning outcomes from debriefing conversations. As the use of healthcare simulation is expanding, the need for faculty development specific to the roles bias plays is imperative. In this article, we hope to build awareness about common cognitive biases that may present in debriefing conversations so debriefers have the chance to begin the hard work of identifying and attending to their potential detrimental impacts.

COVID-19 Vaccine Effectiveness and Barriers to Vaccination: Comparing Perceptions Based on Vaccination Status

New York City (NYC) was the first epicenter of the COVID-19 pandemic in the USA. Despite the availability of COVID-19 vaccines by 2021, vaccination rates varied among racial and ethnic groups, further exacerbating COVID-19-related health disparities. This study explores the relationship between vaccination status and perspectives on COVID-19-related topics among racially and ethnically diverse NYC residents. The New York Community Engagement Alliance Against COVID-19 Disparities (NYCEAL) conducted focus groups with NYC residents to explore their perceptions about vaccine effectiveness and barriers to vaccination that may impact vaccine decision-making. We conducted seven focus groups between December 2021 and April 2022 in English and Spanish with individuals grouped based on vaccination status: (1) those vaccinated when vaccines first became available, (2) those vaccinated after mandates were announced, and (3) those who remained unvaccinated. Transcripts were initially analyzed using a priori and in vivo codes, and the team utilized framework analysis to examine similarities and differences across groups. Emerging themes centered on trust in science, perceived vaccine effectiveness, and the evolution of people's COVID-19-related perspectives, experiences, and behaviors over time. Although there were distinctions between groups on concepts like trust in science and perceived vaccine effectiveness, people's cognitive biases seemed to affect their perceptions but not necessarily their (vaccine-related) behaviors. Findings from this study may help public health professionals understand vaccine decision-making from the perspective of a diverse set of New Yorkers for use during future epidemics.

How do medical professionals make sense (or not) of AI? A social-media-based computational grounded theory study and an online survey

To investigate opinions and attitudes of medical professionals towards adopting AI-enabled healthcare technologies in their daily business, we used a mixed-methods approach. Study 1 employed a qualitative computational grounded theory approach analyzing 181 Reddit threads in the several subreddits of r/medicine. By utilizing an unsupervised machine learning clustering method, we identified three key themes: (1) consequences of AI, (2) physician-AI relationship, and (3) a proposed way forward. In particular Reddit posts related to the first two themes indicated that the medical professionals' fear of being replaced by AI and skepticism toward AI played a major role in the argumentations. Moreover, the results suggest that this fear is driven by little or moderate knowledge about AI. Posts related to the third theme focused on factual discussions about how AI and medicine have to be designed to become broadly adopted in health care. Study 2 quantitatively examined the relationship between the fear of AI, knowledge about AI, and medical professionals' intention to use AI-enabled technologies in more detail. Results based on a sample of 223 medical professionals who participated in the online survey revealed that the intention to use AI technologies increases with increasing knowledge about AI and that this effect is moderated by the fear of being replaced by AI.

Enhancing therapeutic reasoning: key insights and recommendations for education in prescribing

BACKGROUND

Despite efforts to improve undergraduate clinical pharmacology & therapeutics (CPT) education, prescribing errors are still made regularly. To improve CPT education and daily prescribing, it is crucial to understand how therapeutic reasoning works. Therefore, the aim of this study was to gain insight into the therapeutic reasoning process.

METHODS

A narrative literature review has been performed for literature on cognitive psychology and diagnostic and therapeutic reasoning.

RESULTS

Based on these insights, The European Model of Therapeutic Reasoning has been developed, building upon earlier models and insights from cognitive psychology. In this model, it can be assumed that when a diagnosis is made, a primary, automatic response as to what to prescribe arises based on pattern recognition via therapy scripts (type 1 thinking). At some point, this response may be evaluated by the reflective mind (using metacognition). If it is found to be incorrect or incomplete, an alternative response must be formulated through a slower, more analytical and deliberative process, known as type 2 thinking. Metacognition monitors the reasoning process and helps a person to form new therapy scripts after they have chosen an effective therapy. Experienced physicians have more and richer therapy scripts, mostly based on experience and enabling conditions, instead of textbook knowledge, and therefore their type 1 response is more often correct.

CONCLUSION

Because of the important role of metacognition in therapeutic reasoning, more attention should be paid to metacognition in CPT education. Both trainees and teachers should be aware of the possibility to monitor and influence these cognitive processes. Further research is required to investigate the applicability of these insights and the adaptability of educational approaches to therapeutic reasoning.

Clinicians' Use of Choice Framing in ICU Family Meetings

OBJECTIVES

To quantify the frequency and patterns of clinicians' use of choice frames when discussing preference-sensitive care with surrogate decision-makers in the ICU.

DESIGN

Secondary sequential content analysis.

SETTING

One hundred one audio-recorded and transcribed conferences between surrogates and clinicians of incapacitated, critically ill adults from a prospective, multicenter cohort study.

SUBJECTS

Surrogate decision-makers and clinicians.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Four coders identified preference-sensitive decision episodes addressed in the meetings, including topics such as mechanical ventilation, renal replacement, and overall goals of care. Prior critical care literature provided specific topics identified as preference-sensitive specific to the critical care context. Coders then examined each decision episode for the types of choice frames used by clinicians. The choice frames were selected a priori based on decision science literature. In total, there were 202 decision episodes across the 101 transcripts, with 20.3% of the decision episodes discussing mechanical ventilation, 19.3% overall goals of care, 14.4% renal replacement therapy, 14.4% post-discharge care (i.e., discharge location such as a skilled nursing facility), and the remaining 32.1% other topics. Clinicians used default framing, in which an option is presented that will be carried out if another option is not actively chosen, more frequently than any other choice frame (127 or 62.9% of decision episodes). Clinicians presented a polar interrogative, or a "yes or no question" to accept or reject a specific care choice, in 43 (21.3%) decision episodes. Clinicians more frequently presented options emphasizing both potential losses and gains rather than either in isolation.

CONCLUSIONS

Clinicians frequently use default framing and polar questions when discussing preference-sensitive choices with surrogate decision-makers, which are known to be powerful nudges. Future work should focus on designing interventions promoting the informed use of these and the other most common choice frames used by practicing clinicians.

Deep and unbiased proteomics, pathway enrichment analysis, and protein-protein interaction of biomarker signatures in migraine

Background

Currently, there are no biomarkers for migraine.

Objectives

We aimed to identify proteomic biomarker signatures for diagnosing, subclassifying, and predicting treatment response in migraine.

Design

This is a cross-sectional and longitudinal study of untargeted serum and cerebrospinal fluid (CSF) proteomics in episodic migraine (EM; n = 26), chronic migraine (CM; n = 26), and healthy controls (HC; n = 26).

Methods

We developed classification models for biomarker identification and natural clusters through unsupervised classification using agglomerative hierarchical clustering (AHC). Pathway analysis of differentially expressed proteins was performed.

Results

Of 405 CSF proteins, the top five proteins that discriminated between migraine patients and HC were angiotensinogen, cell adhesion molecule 3, immunoglobulin heavy variable (IGHV) V-III region JON, insulin-like growth factor binding protein 6 (IGFBP-6), and IGFBP-7. The top-performing classifier demonstrated 100% sensitivity and 75% specificity in differentiating the two groups. Of 229 serum proteins, the top five proteins in classifying patients with migraine were immunoglobulin heavy variable 3-74 (IGHV 3-74), proteoglycan 4, immunoglobulin kappa variable 3D-15, zinc finger protein (ZFP)-814, and mediator of RNA polymerase II transcription subunit 12. The best-performing classifier exhibited 94% sensitivity and 92% specificity. AHC separated EM, CM, and HC into distinct clusters with 90% success. Migraine patients exhibited increased ZFP-814 and calcium voltage-gated channel subunit alpha 1F (CACNA1F) levels, while IGHV 3-74 levels decreased in both cross-sectional and longitudinal serum analyses. ZFP-814 remained upregulated during the CM-to-EM reversion but was suppressed when CM persisted. CACNA1F was pronounced in CM persistence. Pathway analysis revealed immune, coagulation, glucose metabolism, erythrocyte oxygen and carbon dioxide exchange, and insulin-like growth factor regulation pathways.

Conclusion

Our data-driven study provides evidence for identifying novel proteomic biomarker signatures to diagnose, subclassify, and predict treatment responses for migraine. The dysregulated biomolecules affect multiple pathways, leading to cortical spreading depression, trigeminal nociceptor sensitization, oxidative stress, blood-brain barrier disruption, immune response, and coagulation cascades.

Trial registration

NCT03231241, ClincialTrials.gov.

Mapping cognitive biases in multidisciplinary team (MDT) decision-making for cancer care in Scotland: a cognitive ethnography study protocol

INTRODUCTION

The efficiency of multidisciplinary teams (MDTs) in cancer care hinges on facilitating clinicians' cognitive processes as they navigate complex and uncertain judgements during treatment planning. When systems and workflows are not designed to adequately support human judgement and decision-making, even experts are prone to fallible reasoning due to cognitive biases. Incomplete integration of information or biased interpretations of patient data can lead to clinical errors and delays in the implementation of treatment recommendations. Though their impact is intuitively recognised, there is currently a paucity of empirical work on cognitive biases in MDT decision-making. Our study aims to explicate the impact of such biases on treatment planning and establish a foundation for targeted investigations and interventions to mitigate their negative effects.

METHODS AND ANALYSIS

This is a qualitative, observational study. We employ cognitive ethnography, informed by the Distributed Cognition for Teamwork framework to assess and evaluate MDT decision-making processes. The study involves in-person and virtual field observations of hepatopancreaticobiliary and upper gastrointestinal MDTs and interviews with their members over several months. The data generated will be analysed in a hybrid inductive/deductive fashion to develop a comprehensive map of potential cognitive biases in MDT decision processes identifying antecedents and risk factors of suboptimal treatment planning processes. Further, we will identify components of the MDT environment that can be redesigned to support decision-making via development of an MDT workspace evaluation tool.

ETHICS AND DISSEMINATION

This project has received management and ethical approvals from NHS Lothian Research and Development (2023/0245) and the University of Edinburgh Medical School ethical review committee (23-EMREC-049). Findings will be shared with participating MDTs and disseminated via a PhD thesis, international conference presentations and relevant scientific journals.

Dual process models of clinical reasoning: The central role of knowledge in diagnostic expertise

RATIONALE

Research on diagnostic reasoning has been conducted for fifty years or more. There is growing consensus that there are two distinct processes involved in human diagnostic reasoning: System 1, a rapid retrieval of possible diagnostic hypotheses, largely automatic and based to a large part on experiential knowledge, and System 2, a slower, analytical, conscious application of formal knowledge to arrive at a diagnostic conclusion. However, within this broad framework, controversy and disagreement abound. In particular, many authors have suggested that the root cause of diagnostic errors is cognitive biases originating in System 1 and propose that educating learners about the types of cognitive biases and their impact on diagnosis would have a major influence on error reduction.

AIMS AND OBJECTIVES

In the present paper, we take issue with these claims.

METHOD

We reviewed the literature to examine the extent to which this theoretical model is supported by the evidence.

RESULTS

We show that evidence derived from fundamental research in human cognition and studies in clinical medicine challenges the basic assumptions of this theory-that errors arise in System 1 processing as a consequence of cognitive biases, and are corrected by slow, deliberative analytical processing. We claim that, to the contrary, errors derive from both System 1 and System 2 reasoning, that they arise from lack of access to the appropriate knowledge, not from errors of processing, and that the two processes are not essential to the process of diagnostic reasoning.

CONCLUSIONS

The two processing modes are better understood as a consequence of the nature of the knowledge retrieved, not as independent processes.

HIV Treatment Optimism Moderates the Relationship between Sexual Risk Behavior and HIV Risk Perception among Urban HIV-negative Gay, Bisexual, and Other Men who have Sex With Men

Using baseline data of the Engage Cohort Study, a Canadian study of sexually active gay, bisexual and other men who have sex with men (GBM), we evaluated the association between sexual behavior and risk perception among HIV-negative participants and whether HIV treatment optimism moderated this relationship. Participants were recruited by respondent-driven-sampling (RDS). We defined high-risk sexual behavior in the past six months as any condomless anal sex with a casual partner (i.e. not the participant's main partner) with either unknown HIV-status where neither used pre-exposure prophylaxis or with a partner living with HIV having detectable/unknown viral load. We assessed HIV treatment optimism-skepticism using a 12-item scale. RDS-II-weighted adjusted logistic regression models examined associations with risk perception measured by the question "How would you assess your current risk of getting HIV?" (response options were on a 6-point Likert-scale ranging from "very unlikely" to "very likely", dichotomized into "No Perceived Risk" (very unlikely/unlikely) and "Perceived Risk" (somewhat likely/likely/very likely/I think I already have HIV). Of 1961 participants, engagement in high-risk sexual behavior was reported by 155 (17.0%), 62 (12.4%), 128 (17.2%) of participants in Montréal, Toronto, and Vancouver, respectively. High-risk sexual behavior increased the odds of perceived HIV risk (pooled adjusted odds ratio = 2.9, 95%CI = 2.2-3.8). HIV treatment optimism-skepticism scores moderated the relationship: for GBM engaging in high-risk sexual behavior, higher HIV treatment optimism-skepticism scores increased perceived HIV risk. Promoting awareness around advances related to HIV prevention and treatment is important for appropriate risk assessment and for increased engagement in prevention interventions.

Leveraging emotional intelligence to foster proactive climate change adaptation: A study of engineering decision-making

The impacts of climate change and development present significant challenges and complexities that require new solutions, wise choices, and multi-disciplinary integration. In this context, emotional intelligence (EI) plays a crucial role. However, traditional engineering education and practice overlook the importance of understanding and managing emotions. This research aims to determine the impact of EI as a tool to enhance proactive decision-making and implement sustainable measures within the engineering profession.The study makes three main research contributions. First, it confirms a positive relationship between EI and proactive sustainable decision-making among engineers. This means that engineers with high EI are more likely to consider the impacts of their decisions on various stakeholders and dimensions of sustainability. Second, it suggests that EI can enhance creativity and innovative thinking in engineering, helping engineers to develop effective solutions for challenges related to climate change. Third, the study advocates for incorporating EI training and assessment into engineering curriculums to foster a sustainable and ethical engineering culture. By improving EI, engineers can enhance their interpersonal skills, self-awareness, and emotional management, which in turn can significantly improve teamwork in addressing challenges related to climate change.

Judgement and Decision Making in Clinical and Return-to-Sports Decision Making: A Narrative Review

Making return-to-sport decisions can be complex and multi-faceted, as it requires an evaluation of an individual's physical, psychological, and social well-being. Specifically, the timing of progression, regression, or return to sport can be difficult to determine due to the multitude of information that needs to be considered by clinicians. With the advent of new sports technology, the increasing volume of data poses a challenge to clinicians in effectively processing and utilising it to enhance the quality of their decisions. To gain a deeper understanding of the mechanisms underlying human decision making and associated biases, this narrative review provides a brief overview of different decision-making models that are relevant to sports rehabilitation settings. Accordingly, decisions can be made intuitively, analytically, and/or with heuristics. This narrative review demonstrates how the decision-making models can be applied in the context of return-to-sport decisions and shed light on strategies that may help clinicians improve decision quality.

Using case vignettes to study the presence of outcome, hindsight, and implicit bias in acute unplanned medical care: a cross-sectional study

BACKGROUND AND IMPORTANCE

Various biases can impact decision-making and judgment of case quality in the Emergency Department (ED). Outcome and hindsight bias can lead to wrong retrospective judgment of care quality, and implicit bias can result in unjust treatment differences in the ED based on irrelevant patient characteristics.

OBJECTIVES

First, to evaluate the extent to which knowledge of an outcome influences physicians' quality of care assessment. Secondly, to examine whether patients with functional disorders receive different treatment compared to patients with a somatic past medical history.

DESIGN

A web-based cross-sectional study in which physicians received case vignettes with a case description and care provided. Physicians were informed about vignette outcomes in a randomized way (no, good, or bad outcome). Physicians rated quality of care for four case vignettes with different outcomes. Subsequently, they received two more case vignettes. Physicians were informed about the past medical history of the patient in a randomized way (somatic or functional). Physicians made treatment and diagnostic decisions for both cases.

SETTING AND PARTICIPANTS

One hundred ninety-one Dutch emergency physicians (EPs) and general practitioners (GPs) participated.

OUTCOME MEASURES AND ANALYSIS

Quality of care was rated on a Likert scale (0-5) and dichotomized as adequate (yes/no). Physicians estimated the likelihood of patients experiencing a bad outcome for hindsight bias. For the second objective, physicians decided on prescribing analgesics and additional diagnostic tests.

MAIN RESULTS

Large differences existed in rated quality of care for three out of four vignettes based on different case outcomes. For example, physicians rated the quality of care as adequate in 44% (95% CI 33-57%) for an abdominal pain case with a bad outcome, compared to 88% (95% CI 78-94%) for a good outcome, and 84% (95% CI 73-91%) for no outcome ( P  < 0.01). The estimated likelihood of a bad outcome was higher if physicians received a vignette with a bad patient outcome. Fewer diagnostic tests were performed and fewer opioids were prescribed for patients with a functional disorder.

CONCLUSION

Outcome, hindsight, and implicit bias significantly influence decision-making and care quality assessment by Dutch EPs and GPs.

Clinical Decision Support for Surgery: A Mixed Methods Study on Design and Implementation Perspectives From Urologists

OBJECTIVE

To assess urologist attitudes toward clinical decision support (CDS) embedded into the electronic health record (EHR) and define design needs to facilitate implementation and impact. With recent advances in big data and artificial intelligence (AI), enthusiasm for personalized, data-driven tools to improve surgical decision-making has grown, but the impact of current tools remains limited.

METHODS

A sequential explanatory mixed methods study from 2019 to 2020 was performed. First, survey responses from the 2019 American Urological Association Annual Census evaluated attitudes toward an automatic CDS tool that would display risk/benefit data. This was followed by the purposeful sampling of 25 urologists and qualitative interviews assessing perspectives on CDS impact and design needs. Bivariable, multivariable, and coding-based thematic analysis were applied and integrated.

RESULTS

Among a weighted sample of 12,366 practicing urologists, the majority agreed CDS would help decision-making (70.9%, 95% CI 68.7%-73.2%), aid patient counseling (78.5%, 95% CI 76.5%-80.5%), save time (58.1%, 95% CI 55.7%-60.5%), and improve patient outcomes (42.9%, 95% CI 40.5%-45.4%). More years in practice was negatively associated with agreement (P <.001). Urologists described how CDS could bolster evidence-based care, personalized medicine, resource utilization, and patient experience. They also identified multiple implementation barriers and provided suggestions on form, functionality, and visual design to improve usefulness and ease of use.

CONCLUSION

Urologists have favorable attitudes toward the potential for clinical decision support in the EHR. Smart design will be critical to ensure effective implementation and impact.

Identifying, Understanding, and Minimizing Unconscious Cognitive Biases in Perioperative Crisis Management: A Narrative Review

Rapid clinical decision-making behavior is often based on pattern recognition and other mental shortcuts. Although such behavior is often faster than deliberative thinking, it can also lead to errors due to unconscious cognitive biases (UCBs). UCBs may contribute to inaccurate diagnoses, hamper interpersonal communication, trigger inappropriate clinical interventions, or result in management delays. The authors review the literature on UCBs and discuss their potential impact on perioperative crisis management. Using the Scale for the Assessment of Narrative Review Articles (SANRA), publications with the most relevance to UCBs in perioperative crisis management were selected for inclusion. Of the 19 UCBs that have been most investigated in the medical literature, the authors identified 9 that were judged to be clinically relevant or most frequently occurring during perioperative crisis management. Formal didactic training on concepts of deliberative thinking has had limited success in reducing the presence of UCBs during clinical decision-making. The evolution of clinical decision support tools (CDSTs) has demonstrated efficacy in improving deliberative clinical decision-making, possibly by reducing the intrusion of maladaptive UCBs and forcing reflective thinking. Anesthesiology remains a leader in perioperative crisis simulation and CDST implementation, but spearheading innovations to reduce the adverse impact of UCBs will further improve diagnostic precision and patient safety during perioperative crisis management.

Pneumonia diagnosis performance in the emergency department: a mixed-methods study about clinicians' experiences and exploration of individual differences and response to diagnostic performance feedback

OBJECTIVES

We sought to (1) characterize the process of diagnosing pneumonia in an emergency department (ED) and (2) examine clinician reactions to a clinician-facing diagnostic discordance feedback tool.

MATERIALS AND METHODS

We designed a diagnostic feedback tool, using electronic health record data from ED clinicians' patients to establish concordance or discordance between ED diagnosis, radiology reports, and hospital discharge diagnosis for pneumonia. We conducted semistructured interviews with 11 ED clinicians about pneumonia diagnosis and reactions to the feedback tool. We administered surveys measuring individual differences in mindset beliefs, comfort with feedback, and feedback tool usability. We qualitatively analyzed interview transcripts and descriptively analyzed survey data.

RESULTS

Thematic results revealed: (1) the diagnostic process for pneumonia in the ED is characterized by diagnostic uncertainty and may be secondary to goals to treat and dispose the patient; (2) clinician diagnostic self-evaluation is a fragmented, inconsistent process of case review and follow-up that a feedback tool could fill; (3) the feedback tool was described favorably, with task and normative feedback harnessing clinician values of high-quality patient care and personal excellence; and (4) strong reactions to diagnostic feedback varied from implicit trust to profound skepticism about the validity of the concordance metric. Survey results suggested a relationship between clinicians' individual differences in learning and failure beliefs, feedback experience, and usability ratings.

DISCUSSION AND CONCLUSION

Clinicians value feedback on pneumonia diagnoses. Our results highlight the importance of feedback about diagnostic performance and suggest directions for considering individual differences in feedback tool design and implementation.

Age-Based Heuristics Bias Treatment of Displaced Femoral Neck Fractures in the Elderly

Background

Surgeons performing arthroplasty for femoral neck fractures may rely on mental shortcuts (heuristics) when choosing total hip arthroplasty (THA) vs hemiarthroplasty (HA). We sought to quantify the extent to which age-based heuristics drive decision-making.

Methods

We identified all Medicare beneficiaries from 2017-2018 with femoral neck fractures who underwent THA or HA. We compared the likelihood of THA vs HA among patients admitted within 4 weeks before vs 4 weeks after their birthday for each age under the hypothesis that these cohorts would be similar except for numerical age. We controlled for race/ethnicity, sex, comorbidities, poverty status, and hospital census region in a multivariable regression that included facility-level cluster effects. We generated predicted/adjusted probabilities for THA vs HA for different age transition points.

Results

Thirteen thousand three hundred sixty-six elderly patients were included. One thousand eight hundred sixty-five (14%) received THA and 11,501 (86%) received HA. The likelihood of THA decreased from 50.3% among patients almost 67 to 8% among those ≥85 (P < .001). We found significant decreases in likelihood of THA across age transitions. The largest decrement was at age transition 69 (THA likelihood 28.7% for newly 69 vs 43.3% for almost 69, 33.7% relative change). Female gender, Black race, higher comorbidity burden, and lower socioeconomic status were also associated with a lower likelihood of THA.

Conclusions

Our data demonstrate that patient age transitions seem to influence the choice of THA vs HA. Further research is needed to develop data-driven surgical decision aids for this population.

Association of Sociodemographic Factors With Overtriage, Undertriage, and Value of Care After Major Surgery

Objective

To determine whether certain patients are vulnerable to errant triage decisions immediately after major surgery and whether there are unique sociodemographic phenotypes within overtriaged and undertriaged cohorts.

Background

In a fair system, overtriage of low-acuity patients to intensive care units (ICUs) and undertriage of high-acuity patients to general wards would affect all sociodemographic subgroups equally.

Methods

This multicenter, longitudinal cohort study of hospital admissions immediately after major surgery compared hospital mortality and value of care (risk-adjusted mortality/total costs) across 4 cohorts: overtriage (N = 660), risk-matched overtriage controls admitted to general wards (N = 3077), undertriage (N = 2335), and risk-matched undertriage controls admitted to ICUs (N = 4774). K-means clustering identified sociodemographic phenotypes within overtriage and undertriage cohorts.

Results

Compared with controls, overtriaged admissions had a predominance of male patients (56.2% vs 43.1%, P < 0.001) and commercial insurance (6.4% vs 2.5%, P < 0.001); undertriaged admissions had a predominance of Black patients (28.4% vs 24.4%, P < 0.001) and greater socioeconomic deprivation. Overtriage was associated with increased total direct costs [$16.2K ($11.4K-$23.5K) vs $14.1K ($9.1K-$20.7K), P < 0.001] and low value of care; undertriage was associated with increased hospital mortality (1.5% vs 0.7%, P = 0.002) and hospice care (2.2% vs 0.6%, P < 0.001) and low value of care. Unique sociodemographic phenotypes within both overtriage and undertriage cohorts had similar outcomes and value of care, suggesting that triage decisions, rather than patient characteristics, drive outcomes and value of care.

Conclusions

Postoperative triage decisions should ensure equality across sociodemographic groups by anchoring triage decisions to objective patient acuity assessments, circumventing cognitive shortcuts and mitigating bias.

The Schweitzer effect: The fundamental relationship between experience and medical students' opinions on professional behaviours

PURPOSE

We examined whether medical students' opinions on the acceptability of a behaviour were influenced by previously encountering a similar professionally challenging situation, assessed the magnitude of effect of 'experience' compared to other demographic factors which influence medical students' opinions, and evaluated whether opinions regarding some situations/behaviours were more susceptible to 'experience' bias?

METHODS

Confidential, on-line survey for medical students distributed to Australian and New Zealand (AUS/NZ) medical schools. Students submitted de-identified demographic information, provided opinions on the acceptability of a wide range of student behaviours in professionally challenging situations, and whether they had encountered similar situations.

RESULTS

3171 students participated from all 21 Aus/NZ medical schools (16% of registered students). Medical students reported encountering many of the professionally challenging situations, with varying opinions on what was acceptable behaviour. The most significant factor influencing acceptability towards a behaviour was whether the student reported encountering a similar situation. The professional dilemmas most significantly influenced by previous experience typically related to behaviours that students could witness in clinical environments, and often involved breaches of trust.

CONCLUSIONS

Our results demonstrate the relationship between experience and medical students' opinions on professional behaviour- the 'Schweitzer effect'. When students encounter poor examples of professional behaviour, especially concerning trust breaches, it significantly influences their perception of the behaviour. These results highlight the importance of placing students in healthcare settings with positive professional role modelling/work cultures.

Hand hygiene compliance in nursing home wards: the effect of increased accessibility of alcohol-based hand rub

BACKGROUND

Elderly nursing home residents are vulnerable to infection from micro-organisms. Hand hygiene is considered one of the most important measures to prevent transmission.

AIM

To determine the effect of increased accessibility to alcohol-based hand rub (ABHR) in nursing home wards by monitoring hand hygiene compliance (HHC) among healthcare workers (HCWs).

METHODS

An 11-month intervention study was conducted in a Danish six-ward nursing home. Data were collected using an automatic hand hygiene monitoring system (AHHMS). After a baseline period, one extra ABHR dispenser was placed in each of the 150 apartments. Baseline HHC was compared with the HHC during an immediate intervention period and a long-term intervention period.

FINDINGS

A total of 159 HCWs were included. The AHHMS registered 341,078 hand hygiene opportunities. Overall baseline HHC was 31% (95% confidence interval: 30-32). A significant +18% absolute immediate effect (first five months) (95% CI: 17-19; P < 0.0001) and +13 percentage points (95% CI: 11-14; P < 0.0001) long-term effect (another four months) were recorded. HCWs working day shifts and short-term employees had a higher baseline HHC than HCWs working evening/night shifts. However, HCWs working night shifts achieved the greatest long-term effect with a mean +27 percentage point difference (P < 0.0001).

CONCLUSION

Placing an additional ABHR dispenser strategically within staff workflow significantly increased HHC among HCWs, demonstrating a noteworthy effect. The study is the first to report the effect on nursing home dispenser accessibility as a single intervention and to show a significant unmet potential.

Racial Differences in Shared Decision-Making About Critical Illness

Importance

Shared decision-making is the preferred method for evaluating complex tradeoffs in the care of patients with critical illness. However, it remains unknown whether critical care clinicians engage diverse patients and caregivers equitably in shared decision-making.

Objective

To compare critical care clinicians' approaches to shared decision-making in recorded conversations with Black and White caregivers of patients with critical illness.

Design, Setting, and Participants

This thematic analysis consisted of unstructured clinician-caregiver meetings audio-recorded during a randomized clinical trial of a decision aid about prolonged mechanical ventilation at 13 intensive care units in the US. Participants in meetings included critical care clinicians and Black or White caregivers of patients who underwent mechanical ventilation. The codebook included components of shared decision-making and known mechanisms of racial disparities in clinical communication. Analysts were blinded to caregiver race during coding. Patterns within and across racial groups were evaluated to identify themes. Data analysis was conducted between August 2021 and April 2023.

Main Outcomes and Measures

The main outcomes were themes describing clinician behaviors varying by self-reported race of the caregivers.

Results

The overall sample comprised 20 Black and 19 White caregivers for a total of 39 audio-recorded meetings with clinicians. The duration of meetings was similar for both Black and White caregivers (mean [SD], 23.9 [13.7] minutes vs 22.1 [11.2] minutes, respectively). Both Black and White caregivers were generally middle-aged (mean [SD] age, 47.6 [9.9] years vs 51.9 [8.8] years, respectively), female (15 [75.0%] vs 14 [73.7%], respectively), and possessed a high level of self-assessed health literacy, which was scored from 3 to 15 with lower scores indicating increasing health literacy (mean [SD], 5.8 [2.3] vs 5.3 [2.0], respectively). Clinicians conducting meetings with Black and White caregivers were generally young (mean [SD] age, 38.8 [6.6] years vs 37.9 [8.2] years, respectively), male (13 [72.2%] vs 12 [70.6%], respectively), and White (14 [77.8%] vs 17 [100%], respectively). Four variations in clinicians' shared decision-making behaviors by caregiver race were identified: (1) providing limited emotional support for Black caregivers, (2) failing to acknowledge trust and gratitude expressed by Black caregivers, (3) sharing limited medical information with Black caregivers, and (4) challenging Black caregivers' preferences for restorative care. These themes encompass both relational and informational aspects of shared decision-making.

Conclusions and Relevance

The results of this thematic analysis showed that critical care clinicians missed opportunities to acknowledge emotions and value the knowledge of Black caregivers compared with White caregivers. These findings may inform future clinician-level interventions aimed at promoting equitable shared decision-making.

Behavioural 'nudging' interventions to reduce low-value care for low back pain in the emergency department (NUDG-ED): protocol for a 2×2 factorial, before-after, cluster randomised trial

INTRODUCTION

Opioids and imaging are considered low-value care for most people with low back pain. Yet around one in three people presenting to the emergency department (ED) will receive imaging, and two in three will receive an opioid. NUDG-ED aims to determine the effectiveness of two different behavioural 'nudge' interventions on low-value care for ED patients with low back pain.

METHODS AND ANALYSIS

NUDG-ED is a 2×2 factorial, open-label, before-after, cluster randomised controlled trial. The trial includes 8 ED sites in Sydney, Australia. Participants will be ED clinicians who manage back pain, and patients who are 18 years or over presenting to ED with musculoskeletal back pain. EDs will be randomly assigned to receive (i) patient nudges, (ii) clinician nudges, (iii) both interventions or (iv) no nudge control. The primary outcome will be the proportion of encounters in ED for musculoskeletal back pain where a person received a non-indicated lumbar imaging test, an opioid at discharge or both. We will require 2416 encounters over a 9-month study period (3-month before period and 6-month after period) to detect an absolute difference of 10% in use of low-value care due to either nudge, with 80% power, alpha set at 0.05 and assuming an intra-class correlation coefficient of 0.10, and an intraperiod correlation of 0.09. Patient-reported outcome measures will be collected in a subsample of patients (n≥456) 1 week after their initial ED visit. To estimate effects, we will use a multilevel regression model, with a random effect for cluster and patient, a fixed effect indicating the group assignment of each cluster and a fixed effect of time.

ETHICS AND DISSEMINATION

This study has ethical approval from Southwestern Sydney Local Health District Human Research Ethics Committee (2023/ETH00472). We will disseminate the results of this trial via media, presenting at conferences and scientific publications.

TRIAL REGISTRATION NUMBER

ACTRN12623001000695.

Consensus on relevant point-of-care ultrasound skills in General Practice: a two-round French Delphi study

CONTEXT

Point-of-Care Ultrasound (POCUS) has become an important tool in the clinical practice of many specialties, but its use and impact in General Practice in France remains to be explored.

OBJECTIVE

The objective of this study is to obtain a consensus among experienced French general practitioners on a list of relevant POCUS skills in General Practice in 4 anatomical regions.

METHOD

We used a two-round Delphi method to obtain a consensus. An initial list of skills was drawn by conducting a literature review. To rate each skill, we used a nine-point Likert scale. An interactive meeting between experts took place between Delphi rounds. POCUS experts in General Practice were defined as general practitioners with theoretical training in ultrasound who regularly perform ultrasound, who have performed ultrasound for more than five years and/or are involved in providing ultrasound training.

RESULTS

11 French general practitioners screened 83 skills in 4 anatomical regions: abdominal, urogenital, vascular, gynecology and obstetrics. An agreement was obtained for 36 POCUS skills as to their appropriateness in General Practice. There were 17 skills with a strong appropriate agreement (100% of "7-9" ratings) and 19 skills with a relative agreement (100% of "5-9" ratings).

CONCLUSION

These skills could serve as a basis for guidelines on the use and curriculum of POCUS in General Practice in France as well as in other countries with similar healthcare systems.

Deployment of a human-centred clinical decision support system for pulmonary embolism: evaluation of impact on quality of diagnostic decisions

Pulmonary embolism (PE) is a serious condition that presents a diagnostic challenge for which diagnostic errors often happen. The literature suggests that a gap remains between PE diagnostic guidelines and adherence in healthcare practice. While system-level decision support tools exist, the clinical impact of a human-centred design (HCD) approach of PE diagnostic tool design is unknown.

DESIGN

Before-after (with a preintervention period as non-concurrent control) design study.

SETTING

Inpatient units at two tertiary care hospitals.

PARTICIPANTS

General internal medicine physicians and their patients who underwent PE workups.

INTERVENTION

After a 6-month preintervention period, a clinical decision support system (CDSS) for diagnosis of PE was deployed and evaluated over 6 months. A CDSS technical testing phase separated the two time periods.

MEASUREMENTS

PE workups were identified in both the preintervention and CDSS intervention phases, and data were collected from medical charts. Physician reviewers assessed workup summaries (blinded to the study period) to determine adherence to evidence-based recommendations. Adherence to recommendations was quantified with a score ranging from 0 to 1.0 (the primary study outcome). Diagnostic tests ordered for PE workups were the secondary outcomes of interest.

RESULTS

Overall adherence to diagnostic pathways was 0.63 in the CDSS intervention phase versus 0.60 in the preintervention phase (p=0.18), with fewer workups in the CDSS intervention phase having very low adherence scores. Further, adherence was significantly higher when PE workups included the Wells prediction rule (median adherence score=0.76 vs 0.59, p=0.002). This difference was even more pronounced when the analysis was limited to the CDSS intervention phase only (median adherence score=0.80 when Wells was used vs 0.60 when Wells was not used, p=0.001). For secondary outcomes, using both the D-dimer blood test (42.9% vs 55.7%, p=0.014) and CT pulmonary angiogram imaging (61.9% vs 75.4%, p=0.005) was lower during the CDSS intervention phase.

CONCLUSION

A clinical decision support intervention with an HCD improves some aspects of the diagnostic decision, such as the selection of diagnostic tests and the use of the Wells probabilistic prediction rule for PE.

Vaccine hesitancy and equity: lessons learned from the past and how they affect the COVID-19 countermeasure in Indonesia

INTRODUCTION

Indonesia has made progress in increasing vaccine coverage, but equitable access remains challenging, especially in remote areas. Despite including vaccines in the National Immunization Program (NIP), coverage has not met WHO and UNICEF targets, with childhood immunization decreasing during the COVID-19 pandemic. COVID-19 vaccination has also experienced hesitancy, slowing efforts to end the pandemic.

SCOPE

This article addresses the issue of vaccine hesitancy and its impact on vaccination initiatives amidst the COVID-19 pandemic. This article utilizes the vaccine hesitancy framework to analyze previous outbreaks of vaccine-preventable diseases and their underlying causes, ultimately providing recommendations for addressing the current situation. The analysis considers the differences between the pre-pandemic circumstances and the present and considers the implementation of basic and advanced strategies.

KEY FINDINGS AND CONCLUSION

Vaccine hesitancy is a significant challenge in the COVID-19 pandemic, and public health campaigns and community engagement efforts are needed to promote vaccine acceptance and uptake. Efforts to address vaccine hesitancy promote trust in healthcare systems and increase the likelihood of individuals seeking preventive health services. Vaccine hesitancy requires a comprehensive, culturally sensitive approach that considers local contexts and realities. Strategies should be tailored to specific cultural and societal contexts and monitored and evaluated.

Special Considerations in Behavioral Assessments for Disorders of Consciousness

Behavioral assessment remains the cornerstone of the clinical evaluation of disorders of consciousness (DoC). Because the basic approach to these evaluations has been extensively reviewed elsewhere, this article focuses on special considerations in the behavioral assessment of patients with a DoC. All therapy disciplines (physical therapy/occupational therapy/speech language pathologist) have a significant role to play and other staff and family members should also be encouraged to share their observations. Finally, the assessment with standardized scales should be supplemented by qualitative behavioral observations as well as, when appropriate, an individualized quantitative behavioral assessment.

Shared Decision-Making in Pediatrics

This article briefly reviews a 4-step process for implementing shared decision-making (SDM) in pediatrics. The authors address difficulties with determining whether SDM should occur and comment on how the SDM process relates to, and may be conflated with, other decision-making models that leverage similar patient-centered and family-centered communication strategies.

Japanese Internists' Most Memorable Diagnostic Error Cases: A Self-reflection Survey

Objective The etiologies of diagnostic errors among internal medicine physicians are unclear. To understand the causes and characteristics of diagnostic errors through reflection by those involved in them. Methods We conducted a cross-sectional study using a web-based questionnaire in Japan in January 2019. Over a 10-day period, a total of 2,220 participants agreed to participate in the study, of whom 687 internists were included in the final analysis. Participants were asked about their most memorable diagnostic error cases, in which the time course, situational factors, and psychosocial context could be most vividly recalled and where the participant provided care. We categorized diagnostic errors and identified contributing factors (i.e., situational factors, data collection/interpretation factors, and cognitive biases). Results Two-thirds of the identified diagnostic errors occurred in the clinic or emergency department. Errors were most frequently categorized as wrong diagnoses, followed by delayed and missed diagnoses. Errors most often involved diagnoses related to malignancy, circulatory system disorders, or infectious diseases. Situational factors were the most cited error cause, followed by data collection factors and cognitive bias. Common situational factors included limited consultation during office hours and weekends and barriers that prevented consultation with a supervisor or another department. Conclusion Internists reported situational factors as a significant cause of diagnostic errors. Other factors, such as cognitive biases, were also evident, although the difference in clinical settings may have influenced the proportions of the etiologies of the errors that were observed. Furthermore, wrong, delayed, and missed diagnoses may have distinctive associated cognitive biases.

A randomized trial of mailed outreach with behavioral economic interventions to improve liver cancer surveillance

BACKGROUND

Surveillance rates for HCC remain limited in patients with cirrhosis. We evaluated whether opt-out mailed outreach increased uptake with or without a $20 unconditional incentive.

METHODS

This was a pragmatic randomized controlled trial in an urban academic health system including adult patients with cirrhosis or advanced fibrosis, at least 1 visit to a specialty practice in the past 2 years and no surveillance in the last 7 months. Patients were randomized in a 1:2:2 ratio to (1) usual care, (2) a mailed letter with a signed order for an ultrasound, or (3) a mailed letter with an order and a $20 unconditional incentive. The main outcome was the proportion with completion of ultrasound within 6 months.

RESULTS

Among the 562 patients included, the mean age was 62.1 (SD 11.1); 56.8% were male, 51.1% had Medicare, and 40.6% were Black. At 6 months, 27.6% (95% CI: 19.5-35.7) completed ultrasound in the Usual care arm, 54.5% (95% CI: 47.9-61.0) in the Letter + Order arm, and 54.1% (95% CI: 47.5-60.6) in the Letter + Order + Incentive arm. There was a significant increase in the Letter + Order arm compared to Usual care (absolute difference of 26.9%; 95% CI: 16.5-37.3; p<0.001), but no significant increase in the Letter + Order + Incentive arm compared to Letter + Order (absolute difference of -0.4; 95% CI: -9.7 to 8.8; p=0.93).

CONCLUSIONS

There was an increase in HCC surveillance from mailed outreach with opt-out framing and a signed order slip, but no increase in response to the financial incentive.

Linking cognitive and affective heuristic cues to interpersonal risk perceptions and behavior

People often use cognitive and affective heuristics when judging the likelihood of a health outcome and making health decisions. However, little research has examined how heuristics shape risk perceptions and behavior among people who make decisions on behalf of another person. We examined associations between heuristic cues and caregivers' perceptions of their child's asthma risk, the frequency of caregivers' asthma management behaviors, and child health outcomes. We used Ipsos KnowledgePanel to recruit 814 U.S. adult caregivers of children with asthma of the age <18 years. Participants completed a survey at baseline (T1) and 3 months later (T2). Caregivers who, at T1, reported greater negative affect about their child's asthma (affect heuristic cue), greater ease of imagining their child experiencing asthma symptoms (availability heuristic cue), and greater perceived similarity between their child and a child who has ever experienced asthma symptoms (representativeness heuristic cue) reported statistically significantly (p < 0.05) higher interpersonal perceived risk of their child having an exacerbation or uncontrolled asthma at T1. They also indicated at T2 that their child had poorer asthma control and more frequent exacerbations. Greater T1 negative affect was associated with more frequent T2 actions to reduce inflammation, manage triggers, and manage symptoms, and with poorer T2 child health outcomes. Heuristic cues are likely important for interpersonal-not just personal-risk perceptions. However, the interrelationship between caregivers' ratings of heuristic cues (in particular, negative affect) and risk judgments may signify a struggle with managing their child's asthma and need for extra support from health care providers or systems.

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

This paper depicts a Covid science case, that of the AstraZeneca Vaxzevria vaccine, with specific focus on what happened in Italy. Given that we believe acknowledging the role of non-evidential factors in medicine is an important insight into the recent philosophy of science, we illustrate how in the case of Vaxzevria, the interplay between facts, values (both epistemic and non-epistemic) and cognitive biases may have possibly led to different institutional decisions based on the same evidence. The structure of the paper is as follows. First, we provide a glossary of the relevant terms involved, that is to say, epistemic values, non-epistemic values and cognitive biases. Second, we sketch a timeline of Vaxzevria's approvals and suspensions by relevant institutional healthcare authorities with special focus on Italy and the Italian Medicines Agency. Then we show the interplay between the evidence base, epistemic as well as non-epistemic values and cognitive biases using a narrative review of political decisions along with newspaper and social media content pertaining to Vaxzevria. We briefly compare Italy with other European countries to show that different political decisions were made on the basis of the same evidence.

Diagnostic testing in children: A qualitative study of pediatricians' considerations

AIMS AND OBJECTIVES

Studies in adult medicine have shown that physicians base testing decisions on the patient's clinical condition but also consider other factors, including local practice or patient expectations. In pediatrics, physicians and parents jointly decide on behalf of a (young) child. This might demand more explicit and more complex deliberations, with sometimes conflicting interests. We explored pediatricians' considerations in diagnostic test ordering and the factors that influence their deliberation.

METHOD

We performed in-depth, semistructured interviews with a purposively selected heterogeneous sample of 20 Dutch pediatricians. We analyzed transcribed interviews inductively using a constant comparative approach, and clustered data across interviews to derive common themes.

RESULTS

Pediatricians perceived test-related burden in children higher compared with adults, and reported that avoiding an unjustified burden causes them to be more restrictive and deliberate in test ordering. They felt conflicted when parents desired testing or when guidelines recommended diagnostic tests pediatricians perceived as unnecessary. When parents demanded testing, they would explore parental concern, educate parents about harms and alternative explanations of symptoms, and advocate watchful waiting. Yet they reported sometimes performing tests to appease parents or to comply with guidelines, because of feared personal consequences in the case of adverse outcomes.

CONCLUSION

We obtained an overview of the considerations that are weighed in pediatric test decisions. The comparatively strong focus on prevention of harm motivates pediatricians to critically appraise the added value of testing and drivers of low-value testing. Pediatricians' relatively restrictive approach to testing could provide an example for other disciplines. Improved guidelines and physician and patient education could help to withstand the perceived pressure to test.

Perceived benefits and barriers to implementing precision preventive care: Results of a national physician survey

Polygenic risk scores (PRS) may improve risk-stratification in preventive care. Their clinical implementation will depend on primary care physicians' (PCPs) uptake. We surveyed PCPs in a national physician database about the perceived clinical utility, benefits, and barriers to the use of PRS in preventive care. Among 367 respondents (participation rate 96.3%), mean (SD) age was 54.9 (12.9) years, 137 (37.3%) were female, and mean (SD) time since medical school graduation was 27.2 (13.3) years. Respondents reported greater perceived utility for more clinical action (e.g., earlier or more intensive screening, preventive medications, or lifestyle modification) for patients with high-risk PRS than for delayed or discontinued prevention actions for low-risk patients (p < 0.001). Respondents most often chose out-of-pocket costs (48%), lack of clinical guidelines (24%), and insurance discrimination concerns (22%) as extreme barriers. Latent class analysis identified 3 subclasses of respondents. Skeptics (n = 83, 22.6%) endorsed less agreement with individual clinical utilities, saw patient anxiety and insurance discrimination as significant barriers, and agreed less often that PRS could help patients make better health decisions. Learners (n = 134, 36.5%) and enthusiasts (n = 150, 40.9%) expressed similar levels of agreement that PRS had utility for preventive actions and that PRS could be useful for patient decision-making. Compared with enthusiasts, however, learners perceived greater barriers to the clinical use of PRS. Overall results suggest that PCPs generally endorse using PRS to guide medical decision-making about preventive care, and barriers identified suggest interventions to address their needs and concerns.

Humans inherit artificial intelligence biases

Artificial intelligence recommendations are sometimes erroneous and biased. In our research, we hypothesized that people who perform a (simulated) medical diagnostic task assisted by a biased AI system will reproduce the model's bias in their own decisions, even when they move to a context without AI support. In three experiments, participants completed a medical-themed classification task with or without the help of a biased AI system. The biased recommendations by the AI influenced participants' decisions. Moreover, when those participants, assisted by the AI, moved on to perform the task without assistance, they made the same errors as the AI had made during the previous phase. Thus, participants' responses mimicked AI bias even when the AI was no longer making suggestions. These results provide evidence of human inheritance of AI bias.