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BACKGROUND In meta-analyses involving a few trials, appropriate measures should be employed to assess between-study heterogeneity. When the number of studies is less than five and heterogeneity is evident, the Hartung and Knapp (HK) correction should be used. The aim of this study was to compare the reported estimates of published orthodontic meta-analyses with the pooled effect size estimates and prediction intervals (PI) calculated using eight heterogeneity estimators and corrected using the HK correction. MATERIAL AND METHODS Systematic reviews (SRs) published between 2017 and 2022 in four orthodontic journals and the Cochrane Database of Systematic Reviews with a meta-analysis of at least three studies were sourced. Study characteristics were extracted at the SR and the outcome/meta-analysis levels. All selected meta-analyses were re-analysed by fitting a random-effects model using eight different heterogeneity estimators, both with and without the HK correction. For each meta-analysis, the overall estimate, along with its standard error, the P-value, and the corresponding 95% confidence interval (CI), the between-study variance (tau2), the I2 statistic, and the PI were calculated. RESULTS One-hundred-six SRs were analysed. The most prevalent type of SR was non-Cochrane (95.3%), and the most used meta-analyses synthesis model was the random effect (83.0%). The median number of primary studies was 6 (interquartile range: 5, range: 3-45). The between-study variance was reported in most of the eligible meta-analyses (91.5%), but the type of heterogeneity estimator was reported in only one of them (0.9%). In 5 of 106 meta-analyses (4.7%), the HK correction was applied to adjust the CI of the pooled estimate. The percentage of statistically significant results, which became statistically non-significant, ranged from 16.7% to 25%, depending on the heterogeneity estimator. As the number of studies in a meta-analysis increased, the difference between corrected and uncorrected CIs reduced. Based on the PIs, more than half of the meta-analyses having statistically significant results are likely to change in the future, suggesting the result of the meta-analysis is not conclusive. CONCLUSIONS The statistical significance of pooled estimates from meta-analyses with at least three studies is sensitive to the HK correction, the heterogeneity variance estimator, and PIs. Clinicians should be aware of the clinical implications of not appropriately assessing the effect of the small number of studies and the between-study heterogeneity when interpreting results from meta-analyses.

Diagnostic testing for COVID-19 is an important part of the management of the pandemic. A diagnostic testbased policy response assumes the existence of diagnostic kits on a large scale, their availability at the point of care, an efficient way to administer the tests to the economically and socially active population, and the analysis and communication of the results. Overall, information produced by a diagnostic testing strategy is a key input to individual and public health decision making. In this paper, we attempt to answer the question of where knowledge prerequisites to produce SARS-CoV-2 diagnostic tests are located in the world. We compile background knowledge on virology, particularly concerning the various options of diagnostic testing for known Coronaviruses with information retrieved from the corpus of patent documents. More specifically, we extract keywords from this field of expertise and we query these keywords in patent application filings. We construct an indicator of inventive activity in the area of Coronavirus diagnostic tests, and we decompose it across several dimensions - time, location of inventors, and thematic classifications. Our reasoning is that previous knowledge in the field might prove crucial for the development and deployment of diagnostics for SARS-CoV-2. In the current pandemic, the knowledge prerequisites for the production of diagnostic tests are pertinent to a wide range of issues. The knowledge that is encapsulated in the patenting activity, which we document, can potentially be far-reaching if it becomes widely available to the scientific and industrial actors engaged in applied biomedical research. We present, without evaluating, a number of policy options.

From their inception, digital technologies have had a huge impact on our everyday life. In both the private and the public sectors, they have contributed to, or at times driven, change in organisational structures, ways of working, and how products and services are shaped and shared. Governments and public administration units, driven by the digital evolution of information and communications technology (ICT), are evolving from traditional workflow-based public service provisions to digital equivalents (e-government), with more innovative forms of government and administration looking for the engagement of citizens and the private sector to co-create final services through user-centric approaches. Application Programming Interfaces (APIs), which are one of the most relevant ICT solutions, have contributed to this notable shift in the adoption of technology, especially when used over the web. They have affected the global economy of the private sector and are contributing to the digital transformation of governments. To explore this in more detail, the European Commission recently started the APIs4DGov study. One of the outputs of the study is an analysis of the API technological landscape, including its related standards and technical specifications for general purpose use. The goal of the analysis presented in this brief report is to support the definition of stable APIs for digital government services adopted by governments or single public administration units. Such adoption would avoid the need to develop ad hoc solutions that could have limited scalability or potential for reuse. Instead, the work suggests that we should consider a number of existing standards provided by standardisation bodies or, at least, technical specifications written by well-recognised consortia, vendors or users. The aim of this report is also to support API stakeholders in the identification and selection of such solutions. To do this, it first gives a series of definitions to help the reader understand some basic concepts, as well as related standards and technical specifications. Then, it presents the description and classification (by resource representation, security, usability, test, performance and licence) of the standards and technical specifications collected. A shortlist of these documents (based on their utilisation, maintenance and stability) is also proposed, together with a brief description of each of them. Finally, the report provides a useful glossary with definitions of the relevant terms we have collected so far within the APIs4DGov study., JRC.B.6-Digital Economy

Based on OECD evidence, equity/housing-price busts and credit crunches are followed by substantial increases in public consumption. These increases in unproductive public spending lead to increases in distortionary marginal taxes, a policy in sharp contrast with presumably optimal Keynesian fiscal stimulus after a crisis. Here we claim that this seemingly adverse policy selection is optimal under rational learning about the frequency of rare capital-value busts. Bayesian updating after a bust implies massive belief jumps toward pessimism, with investors and policymakers believing that busts will be arriving more frequently in the future. Lowering taxes would be as if trying to kick a sick horse in order to stand up and run, since pessimistic markets would be unwilling to invest enough under any temporarily generous tax regime.

We construct the first top income share series of a formerly socialist economy before, during, and after socialism in order to exploit the effect of the quasi-natural experiment of the absence of markets on incentives. We investigate top income shares dynamics and the sources of income at the upper tail of the income distribution. Within this setup, we study the effect of capital markets and liberalized wage settings on top income shares. Our estimates show that the introduction of wage-setting decentralization during socialism had a role in increasing the skill premium and income inequality in years prior the transition.