Background Since the start of the COVID-19 outbreak, a large number of COVID-19-related papers have been published. However, concerns about the risk of expedited science have been raised. We aimed at reviewing and categorizing COVID-19-related medical research and to critically appraise peer-reviewed original articles. Methods The data sources were Pubmed, Cochrane COVID-19 register study, arXiv, medRxiv and bioRxiv, from 01/11/2019 to 01/05/2020. Peer-reviewed and preprints publications related to COVID-19 were included, written in English or Chinese. No limitations were placed on study design. Reviewers screened and categorized studies according to i) publication type, ii) country of publication, and iii) topics covered. Original articles were critically appraised using validated quality assessment tools. Results Among the 11,452 publications identified, 10,516 met the inclusion criteria, among which 7468 (71.0%) were peer-reviewed articles. Among these, 4190 publications (56.1%) did not include any data or analytics (comprising expert opinion pieces). Overall, the most represented topics were infectious disease (n = 2326, 22.1%), epidemiology (n = 1802, 17.1%), and global health (n = 1602, 15.2%). The top five publishing countries were China (25.8%), United States (22.3%), United Kingdom (8.8%), Italy (8.1%) and India (3.4%). The dynamic of publication showed that the exponential growth of COVID-19 peer-reviewed articles was mainly driven by publications without original data (mean 261.5 articles ± 51.1 per week) as compared with original articles (mean of 69.3 ± 22.3 articles per week). Original articles including patient data accounted for 713 (9.5%) of peer-reviewed studies. A total of 576 original articles (80.8%) showed intermediate to high risk of bias. Last, except for simulation studies that mainly used large-scale open data, the median number of patients enrolled was of 102 (IQR = 37–337). Conclusions Since the beginning of the COVID-19 pandemic, the majority of research is composed by publications without original data. Peer-reviewed original articles with data showed a high risk of bias and included a limited number of patients. Together, these findings underscore the urgent need to strike a balance between the velocity and quality of research, and to cautiously consider medical information and clinical applicability in a pressing, pandemic context. Systematic review registration https://osf.io/5zjyx/

No abstract

Audiovisual documents provide a great primary material for analysis in multiple domains, such as sociology or interaction studies. Video annotation tools offer new ways of analysing these documents, beyond the conventional transcription. However, these tools are often dedicated to specific domains, putting constraints on the data model or interfaces that may not be convenient for alternative uses. Moreover, most tools serve as exploratory and analysis instruments only, not proposing export formats suitable for publication.We describe in this paper a usage of the Advene software, a versatile video annotation tool that can be tailored for various kinds of analyses: users can define their own analysis structure and visualizations, and share their analyses either as structured annotations with visualization templates, or published on the Web as hypervideo documents. We explain how users can customize the software through the definition of their own data structures and visualizations. We illustrate this adaptability through an actual usage for interview analysis.

Active reading of audiovisual documents is an iterative activity, dedicated to the analysis of the audiovisual source through its enrichment with structured metadata and the definition of appropriate visualisation means for this metadata, producing new multimedia objects called hypervideos. We will describe in this article the general decomposition of active reading and how it is put into practice in the Advene framework, analysing how its activities fit into the Canonical Media Processes model.