BackgroundImplicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person on the basis of irrelevant characteristics such as race or gender. This review examines the evidence that healthcare professionals display implicit biases towards patients.MethodsPubMed, PsychINFO, PsychARTICLE and CINAHL were searched for peer-reviewed articles published between 1st March 2003 and 31st March 2013. Two reviewers assessed the eligibility of the identified papers based on precise content and quality criteria. The references of eligible papers were examined to identify further eligible studies.ResultsForty two articles were identified as eligible. Seventeen used an implicit measure (Implicit Association Test in fifteen and subliminal priming in two), to test the biases of healthcare professionals. Twenty five articles employed a between-subjects design, using vignettes to examine the influence of patient characteristics on healthcare professionals’ attitudes, diagnoses, and treatment decisions. The second method was included although it does not isolate implicit attitudes because it is recognised by psychologists who specialise in implicit cognition as a way of detecting the possible presence of implicit bias. Twenty seven studies examined racial/ethnic biases; ten other biases were investigated, including gender, age and weight. Thirty five articles found evidence of implicit bias in healthcare professionals; all the studies that investigated correlations found a significant positive relationship between level of implicit bias and lower quality of care.DiscussionThe evidence indicates that healthcare professionals exhibit the same levels of implicit bias as the wider population. The interactions between multiple patient characteristics and between healthcare professional and patient characteristics reveal the complexity of the phenomenon of implicit bias and its influence on clinician-patient interaction. The most convincing studies from our review are those that combine the IAT and a method measuring the quality of treatment in the actual world. Correlational evidence indicates that biases are likely to influence diagnosis and treatment decisions and levels of care in some circumstances and need to be further investigated. Our review also indicates that there may sometimes be a gap between the norm of impartiality and the extent to which it is embraced by healthcare professionals for some of the tested characteristics.ConclusionsOur findings highlight the need for the healthcare profession to address the role of implicit biases in disparities in healthcare. More research in actual care settings and a greater homogeneity in methods employed to test implicit biases in healthcare is needed.

Background Assessing the burden of COVID-19 on the basis of medically attended case numbers is suboptimal given its reliance on testing strategy, changing case definitions, and disease presentation. Population-based serosurveys measuring anti-severe acute respiratory syndrome coronavirus 2 (anti-SARS-CoV-2) antibodies provide one method for estimating infection rates and monitoring the progression of the epidemic. Here, we estimate weekly seroprevalence of anti-SARS-CoV-2 antibodies in the population of Geneva, Switzerland, during the epidemic.Methods The SEROCoV-POP study is a population-based study of former participants of the Bus Santé study and their household members. We planned a series of 12 consecutive weekly serosurveys among randomly selected participants from a previous population-representative survey, and their household members aged 5 years and older. We tested each participant for anti-SARS-CoV-2-IgG antibodies using a commercially available ELISA. We estimated seroprevalence using a Bayesian logistic regression model taking into account test performance and adjusting for the age and sex of Geneva's population. Here we present results from the first 5 weeks of the study. FindingsBetween April 6 and May 9, 2020, we enrolled 2766 participants from 1339 households, with a demographic distribution similar to that of the canton of Geneva. In the first week, we estimated a seroprevalence of 4•8% (95% CI 2•4-8•0, n=341). The estimate increased to 8•5% (5•9-11•4, n=469) in the second week, to 10•9% (7•9-14•4, n=577) in the third week, 6•6% (4•3-9•4, n=604) in the fourth week, and 10•8% (8•2-13•9, n=775) in the fifth week. Individuals aged 5-9 years (relative risk [RR] 0•32 [95% CI 0•11-0•63]) and those older than 65 years (RR 0•50 [0•28-0•78]) had a significantly lower risk of being seropositive than those aged 20-49 years. After accounting for the time to seroconversion, we estimated that for every reported confirmed case, there were 11•6 infections in the community.Interpretation These results suggest that most of the population of Geneva remained uninfected during this wave of the pandemic, despite the high prevalence of COVID-19 in the region (5000 reported clinical cases over <2•5 months in the population of half a million people). Assuming that the presence of IgG antibodies is associated with immunity, these results highlight that the epidemic is far from coming to an end by means of fewer susceptible people in the population. Further, a significantly lower seroprevalence was observed for children aged 5-9 years and adults older than 65 years, compared with those aged 10-64 years. These results will inform countries considering the easing of restrictions aimed at curbing transmission.

Biomarkers sensitive to functional impairment, neuronal loss, tau, and amyloid pathology based on MR, PET, and CSF studies are increasingly used to diagnose Alzheimer's disease (AD), but clinical validation is incomplete, hampering reimbursement by payers, widespread clinical implementation, and impacting on health care quality. An expert group convened to develop a strategic research agenda to foster the clinical validation of AD biomarkers. These demonstrated sufficient evidence of analytical validity (phase I of a structured framework adapted from oncology). Research priorities were identified based on incomplete clinical validity (phases II and III), and clinical utility (phases IV and V). Priorities included: definition of the assays; reading procedures and thresholds for normality; performance in detecting early disease; accounting for the effect of covariates; diagnostic algorithms comprising combinations of biomarkers; and developing best practice guidelines for the use of biomarkers in qualified memory clinics in the context of phase IV studies. 5 GlossaryBiomarker. An objective measure of a biological or pathogenic process with the purpose of evaluating disease risk or prognosis, guiding clinical diagnosis or monitoring therapeutic interventions. While the term originally referred to traceable substances produced by or introduced into an organism, it later evolved to any measurable parameter, including those obtained via imaging procedures.Roadmap. Objective-oriented, structured, and efficient action plan. In science and technology also called "strategic research agenda".Alzheimer's disease (AD) dementia. Traditionally and according to the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria, Alzheimer's disease was defined as a syndrome with progressive cognitive impairment severe enough to impact on daily activities. A diagnosis of Alzheimer's disease could only be made after exclusion of other possible causes. 1 Sixty-five to 80% of cases of patients fulfilling these criteria have Alzheimer's pathology (plaques and tangles), the remainder having a range of other pathologies. In order to increase diagnostic certainty, contemporary criteria for AD dementia incorporate biomarker evidence for different aspects of Alzheimer's pathology, including imaging (magnetic resonance imaging -MRI -measures of atrophy; 18 F-fluorodeoxyglucose-positron emission tomography -FDG-PET -measures of cerebral hypometabolism; amyloid PET measures of fibrillar β-amyloid -A -deposition) and cerebrospinal fluid -CSF (decreased levels of A42, increased levels of tau and phospho-tau). 2,3 Alzheimer's disease process. Recognizing that AD pathology is present many years before symptoms emerge, new criteria classify the disease process on a continuum from asymptomatic to prodromal and finally to dementia stage. 4 Individuals at the asymptomatic stage can only be identified by biomarkers of Alzheimer's pathology. None...

Despite broad agreement that the vulnerable have a claim to special protection, defining vulnerable persons or populations has proved more difficult than we would like. This is a theoretical as well as a practical problem, as it hinders both convincing justifications for this claim and the practical application of required protections. In this paper, I review consent-based, harm-based, and comprehensive definitions of vulnerability in healthcare and research with human subjects. Although current definitions are subject to critique, their underlying assumptions may be complementary. I propose that we should define vulnerability in research and healthcare as an identifiably increased likelihood of incurring additional or greater wrong. In order to identify the vulnerable, as well as the type of protection that they need, this definition requires that we start from the sorts of wrongs likely to occur and from identifiable increments in the likelihood, or to the likely degree, that these wrongs will occur. It is limited but appropriately so, as it only applies to special protection, not to any protection to which we have a valid claim. Using this definition would clarify that the normative force of claims for special protection does not rest with vulnerability itself, but with pre-existing claims when these are more likely to be denied. Such a clarification could help those who carry responsibility for the protection of vulnerable populations, such as Institutional Review Boards, to define the sort of protection required in a more targeted and effective manner.

Background Implicit biases are present in the general population and among professionals in various domains, where they can lead to discrimination. Many interventions are used to reduce implicit bias. However, uncertainties remain as to their effectiveness. Methods We conducted a systematic review by searching ERIC, PUBMED and PSYCHINFO for peer-reviewed studies conducted on adults between May 2005 and April 2015, testing interventions designed to reduce implicit bias, with results measured using the Implicit Association Test (IAT) or sufficiently similar methods. Results 30 articles were identified as eligible. Some techniques, such as engaging with others’ perspective, appear unfruitful, at least in short term implicit bias reduction, while other techniques, such as exposure to counterstereotypical exemplars, are more promising. Robust data is lacking for many of these interventions. Conclusions Caution is thus advised when it comes to programs aiming at reducing biases. This does not weaken the case for implementing widespread structural and institutional changes that are multiply justified. Electronic supplementary material The online version of this article (10.1186/s40359-019-0299-7) contains supplementary material, which is available to authorized users.