Locally Adaptive Function Estimation for Binary Regression Models

In this paper we present a nonparametric Bayesian approach for fitting unsmooth or highly oscillating functions in regression models with binary responses. The approach extends previous work by Lang et al. (2002) for Gaussian responses. Nonlinear functions are modelled by first or second order random walk priors with locally varying variances or smoothing parameters. Estimation is fully Bayesian and uses latent utility representations of binary regression models for efficient block sampling from the full conditionals of nonlinear functions

Modeling Probabilities of Patent Oppositions in a Bayesian Semiparametric Regression Framework

Most econometric analyses of patent data rely on regression methods using a parametric form of the predictor for modeling the dependence of the response given certain covariates. These methods often lack the capability of identifying non-linear relationships between dependent and independent variables. We present an approach based on a generalized additive model in order to avoid these shortcomings. Our method is fully Bayesian and makes use of Markov Chain Monte Carlo (MCMC) simulation techniques for estimation purposes. Using this methodology we reanalyze the determinants of patent oppositions in Europe for biotechnology/pharmaceutical and semiconductor/computer software patents. Our results largely confirm the findings of a previous parametric analysis of the same data provided by Graham, Hall, Harhoff&Mowery (2002). However, our model specification clearly verifies considerable non-linearities in the effect of various metrical covariates on the probability of an opposition. Furthermore, our semiparametric approach shows that the categorizations of these covariates made by Graham et al. (2002) cannot capture those non--linearities and, from a statistical point of view, appear to somehow ad hoc

Creating effective quality-improvement collaboratives: a multiple case study

Objective: To explore whether differences between collaboratives with respect to type of topic, type of targets, measures (systems) are also reflected in the degree of effectiveness. Study setting: 182 teams from long-term healthcare organisation developed improvement initiatives in seven quality-improvement collaboratives (QICs) focusing on patient safety and autonomy. Study design: Multiple case before-after study. Data collection: 75 team leaders completed a written questionnaire at the end of each QIC on achievability and degree of challenge of targets and measurability of progress. Main outcome indicators were collaborative-specific measures (such as prevalence of pressure ulcers). Principal findings: The degree of effectiveness and percentage of teams realising targets varied between collaboratives. Collaboratives also varied widely in perceived measurability (F=6.798 and p=0.000) and with respect to formulating achievable targets (F=6.566 and p=0.000). The Problem Behaviour collaborative scored significantly lower than all other collaboratives on both dimensions. The collaborative on Autonomy and control scored significantly lower on measurability than the other collaboratives. Topics for which there are best practices and evidence of effective interventions do not necessarily score higher on effectiveness, measurability, achievable and challenging targets. Conclusions: The effectiveness of a QIC is associated with the efforts of programme managers to create conditions that provide insight into which changes in processes of care and in client outcomes have been made. Measurability is not an inherent property of the improvement topic. Rather, creating measurability and formulating challenging and achievable targets is one of the crucial tasks for programme managers of QICs

What happens in the Lab: Applying Midstream Modulation to Enhance Critical Reflection in the Laboratory

In response to widespread policy prescriptions for responsible innovation, social scientists and engineering ethicists, among others, have sought to engage natural scientists and engineers at the ‘midstream’: building interdisciplinary collaborations to integrate social and ethical considerations with research and development processes. Two ‘laboratory engagement studies’ have explored how applying the framework of midstream modulation could enhance the reflections of natural scientists on the socio-ethical context of their work. The results of these interdisciplinary collaborations confirm the utility of midstream modulation in encouraging both first- and second-order reflective learning. The potential for second-order reflective learning, in which underlying value systems become the object of reflection, is particularly significant with respect to addressing social responsibility in research practices. Midstream modulation served to render the socio-ethical context of research visible in the laboratory and helped enable research participants to more critically reflect on this broader context. While lab-based collaborations would benefit from being carried out in concert with activities at institutional and policy levels, midstream modulation could prove a valuable asset in the toolbox of interdisciplinary methods aimed at responsible innovation

Opening the black box of quality improvement collaboratives: an Actor-Network theory approach

<p>Abstract</p> <p>Background</p> <p>Quality improvement collaboratives are often labeled as black boxes because effect studies usually do not describe exactly how the results were obtained. In this article we propose a way of opening such a black box, by taking up a dynamic perspective based on Actor-Network Theory. We thereby analyze how the problematisation process and the measurement practices are constructed. Findings from this analysis may have consequences for future evaluation studies of collaboratives.</p> <p>Methods</p> <p>In an ethnographic design we probed two projects within a larger quality improvement collaborative on long term mental health care and care for the intellectually disabled. Ethnographic observations were made at nine national conferences. Furthermore we conducted six case studies involving participating teams. Additionally, we interviewed the two program leaders of the overall projects.</p> <p>Results</p> <p>In one project the problematisation seemed to undergo a shift of focus away from the one suggested by the project leaders. In the other we observed multiple roles of the measurement instrument used. The instrument did not only measure effects of the improvement actions but also changed these actions and affected the actors involved.</p> <p>Conclusions</p> <p>Effectiveness statistics ideally should be complemented with an analysis of the construction of the collaborative and the improvement practices. Effect studies of collaboratives could benefit from a mixed methods research design that combines quantitative and qualitative methods.</p

Evaluation of a large scale implementation of disease management programmes in various Dutch regions: a study protocol

Background. Disease management programmes (DMPs) have been developed to improve effectiveness and economic efficiency withi

ACE2-binding exposes the SARS-CoV-2 fusion peptide to broadly neutralizing coronavirus antibodies

The coronavirus spike glycoprotein attaches to host receptors and mediates viral fusion. Using a broad screening approach, we isolated seven monoclonal antibodies (mAbs) that bind to all human-infecting coronavirus spike proteins from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune donors. These mAbs recognize the fusion peptide and acquire affinity and breadth through somatic mutations. Despite targeting a conserved motif, only some mAbs show broad neutralizing activity in vitro against alpha- and betacoronaviruses, including animal coronaviruses WIV-1 and PDF-2180. Two selected mAbs also neutralize Omicron BA.1 and BA.2 authentic viruses and reduce viral burden and pathology in vivo. Structural and functional analyses showed that the fusion peptide–specific mAbs bound with different modalities to a cryptic epitope hidden in prefusion stabilized spike, which became exposed upon binding of angiotensin-converting enzyme 2 (ACE2) or ACE2-mimicking mAbs