Metaresearch, Psychology, and Law: A Case Study on Implicit Bias

When can scientific findings from experimental psychology be confidently applied to legal issues? And when applications have clear limits, do legal commentators readily acknowledge them? To address these questions, we survey recent findings from an emerging field of research on research (i.e., metaresearch). We find that many aspects of experimental psychology’s research and reporting practices threaten the validity and generalizability of legally relevant research findings, including those relied on by courts and policy-setting bodies. As a case study, we appraise the empirical claims relied on by commentators claiming that implicit bias deeply affects legal proceedings and practices, and that training can be used to reduce that bias. We find that these claims carry many indicia of unreliability. Only limited evidence indicates that interventions designed to reduce prejudicial behavior through implicit bias training are effective, and the research area shows many signs of publication bias. To examine whether law journal articles are acknowledging these limits, we collected a sample of 100 law journal articles mentioning “implicit bias training” published from 2017-2021. Of those 100 articles, 58 recommend implicit bias training and only 8 of those 58 express any skepticism about its effectiveness. Overall, only 19 articles express skepticism about implicit bias training. We end with recommendations for law journal authors, researchers, and practitioners towards more credible application of psychology findings in law research and policy. Our focus is on how empirical research can be best used to solve our most important social issues including racism

The Transparency of Quantitative Empirical Legal Research (2018–2020)

Scientists are increasingly concerned with making their work easy to verify and build upon. Associated practices include sharing data, materials, and analytic scripts, and preregistering protocols. This has been referred to as a “credibility revolution”. The credibility of empirical legal research has been questioned in the past due to its distinctive peer review system and because the legal background of its researchers means that many often are not trained in study design or statistics. Still, there has been no systematic study of transparency and credibilityrelated characteristics of published empirical legal research. To fill this gap and provide an estimate of current practices that can be tracked as the field evolves, we assessed 300 empirical articles from highly ranked law journals including both faculty-edited journals and student-edited journals. We found high levels of article accessibility (86% could be accessed without a subscription, 95% CI = [82%, 90%]), especially among student-edited journals (100% accessibility). Few articles stated that a study’s data are available, (19%, 95% CI = [15%, 23%]), and only about half of those datasets are reportedly available without contacting the author. Preregistration (3%, 95% CI = [1%, 5%]) and availability of analytic scripts (6%, 95% = [4%, 9%]) were very uncommon. We suggest that empirical legal researchers and the journals that publish their work cultivate norms and practices to encourage research credibility

Interactive sonification exploring emergent behavior applying models for biological information and listening

Sonification is an open-ended design task to construct sound informing a listener of data. Understanding application context is critical for shaping design requirements for data translation into sound. Sonification requires methodology to maintain reproducibility when data sources exhibit non-linear properties of self-organization and emergent behavior. This research formalizes interactive sonification in an extensible model to support reproducibility when data exhibits emergent behavior. In the absence of sonification theory, extensibility demonstrates relevant methods across case studies. The interactive sonification framework foregrounds three factors: reproducible system implementation for generating sonification; interactive mechanisms enhancing a listener's multisensory observations; and reproducible data from models that characterize emergent behavior. Supramodal attention research suggests interactive exploration with auditory feedback can generate context for recognizing irregular patterns and transient dynamics. The sonification framework provides circular causality as a signal pathway for modeling a listener interacting with emergent behavior. The extensible sonification model adopts a data acquisition pathway to formalize functional symmetry across three subsystems: Experimental Data Source, Sound Generation, and Guided Exploration. To differentiate time criticality and dimensionality of emerging dynamics, are applied between subsystems to maintain scale and symmetry of concurrent processes and temporal dynamics. Tuning functions accommodate sonification design strategies that yield order parameter values to render emerging patterns discoverable as well as , to reproduce desired instances for clinical listeners. Case studies are implemented with two computational models, Chua's circuit and Swarm Chemistry social agent simulation, generating data in real-time that exhibits emergent behavior. is introduced as an informal model of a listener's clinical attention to data sonification through multisensory interaction in a context of structured inquiry. Three methods are introduced to assess the proposed sonification framework: Listening Scenario classification, data flow Attunement, and Sonification Design Patterns to classify sound control. Case study implementations are assessed against these methods comparing levels of abstraction between experimental data and sound generation. Outcomes demonstrate the framework performance as a reference model for representing experimental implementations, also for identifying common sonification structures having different experimental implementations, identifying common functions implemented in different subsystems, and comparing impact of affordances across multiple implementations of listening scenarios

The cystic fibrosis microbiome in an ecological perspective and its impact in antibiotic therapy

The recent focus on the cystic fibrosis (CF) complex microbiome has led to the recognition that the microbes can interact between them and with the host immune system, affecting the disease progression and treatment routes. Although the main focus remains on the interactions between traditional pathogens, growing evidence supports the contribution and the role of emergent species. Understanding the mechanisms and the biological effects involved in polymicrobial interactions may be the key to improve effective therapies and also to define new strategies for disease control. This review focuses on the interactions between microbe-microbe and host-microbe, from an ecological point of view, discussing their impact on CF disease progression. There are increasing indications that these interactions impact the success of antimicrobial therapy. Consequently, a new approach where therapy is personalized to patients by taking into account their individual CF microbiome is suggested.Portuguese Foundation for Science and Technology (FCT), the strategic funding of UID/BIO/04469/2013-CEB and UID/EQU/00511/2013-LEPABE units. This study was also supported by FCT and the European Community fund FEDER, through Program COMPETE, under the scope of the Projects “DNA mimics” PIC/IC/82815/2007, RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462), “BioHealth—Biotechnology and Bioengineering approaches to improve health quality”, Ref. NORTE-07-0124-FEDER-000027 and NORTE-07-0124-FEDER-000025—RL2_ Environment and Health, co-funded by the Programa Operacional Regional do Norte (ON.2 – O Novo Norte), QREN, FEDER. The authors also acknowledge the grant of Susana P. Lopes (SFRH/BPD/95616/2013) and of the COST-Action TD1004: Theragnostics for imaging and therapy

The impact of immediate breast reconstruction on the time to delivery of adjuvant therapy: the iBRA-2 study

Background: Immediate breast reconstruction (IBR) is routinely offered to improve quality-of-life for women requiring mastectomy, but there are concerns that more complex surgery may delay adjuvant oncological treatments and compromise long-term outcomes. High-quality evidence is lacking. The iBRA-2 study aimed to investigate the impact of IBR on time to adjuvant therapy. Methods: Consecutive women undergoing mastectomy ± IBR for breast cancer July–December, 2016 were included. Patient demographics, operative, oncological and complication data were collected. Time from last definitive cancer surgery to first adjuvant treatment for patients undergoing mastectomy ± IBR were compared and risk factors associated with delays explored. Results: A total of 2540 patients were recruited from 76 centres; 1008 (39.7%) underwent IBR (implant-only [n = 675, 26.6%]; pedicled flaps [n = 105,4.1%] and free-flaps [n = 228, 8.9%]). Complications requiring re-admission or re-operation were significantly more common in patients undergoing IBR than those receiving mastectomy. Adjuvant chemotherapy or radiotherapy was required by 1235 (48.6%) patients. No clinically significant differences were seen in time to adjuvant therapy between patient groups but major complications irrespective of surgery received were significantly associated with treatment delays. Conclusions: IBR does not result in clinically significant delays to adjuvant therapy, but post-operative complications are associated with treatment delays. Strategies to minimise complications, including careful patient selection, are required to improve outcomes for patients

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Metaresearch, Psychology, and Law: A Case Study on Implicit Bias

When can scientific findings from experimental psychology be confidently applied to legal issues? And when applications have clear limits, do legal commentators readily acknowledge them? To address these questions, we survey recent findings from an emerging field of research on research (i.e., metaresearch). We find that many aspects of experimental psychology’s research and reporting practices threaten the validity and generalizability of legally relevant research findings, including those relied on by courts and policy-setting bodies. As a case study, we appraise the empirical claims relied on by commentators claiming that implicit bias deeply affects legal proceedings and practices, and that training can be used to reduce that bias. We find that these claims carry many indicia of unreliability. Only limited evidence indicates that interventions designed to reduce prejudicial behavior through implicit bias training are effective, and the research area shows many signs of publication bias. To examine whether law journal articles are acknowledging these limits, we collected a sample of 100 law journal articles mentioning “implicit bias training” published from 2017-2021. Of those 100 articles, 58 recommend implicit bias training and only 8 of those 58 express any skepticism about its effectiveness. Overall, only 19 articles express skepticism about implicit bias training. We end with recommendations for law journal authors, researchers, and practitioners towards more credible application of psychology findings in law research and policy. Our focus is on how empirical research can be best used to solve our most important social issues including racism