Single-case designs (SCDs) are used to evaluate the effects of interventions on individual participants. By repeatedly measuring participants under different conditions, SCD studies focus on individual effects rather than on group summaries. The main limitation of SCDs remains its generalisability to wider populations, reducing the relevance of their findings for practice and policy making. With this limitation in mind, methodological developments for synthesising SCD data from different studies that investigate the same research question have intensified in the past decades (e.g. multilevel modelling). However, these techniques are restricted to comparing two interventions at a time and can only incorporate evidence from studies that directly compare the two treatments of interest. These limitations could be addressed by using network meta-analysis that incorporates both direct and indirect evidence to simultaneously compare multiple interventions. Despite its potential, network meta-analytical techniques have yet to be applied to SCD data. Thus, in this paper, we argue that network meta-analysis can be a valuable tool to synthesise SCD data. We demonstrate the use of network meta-analysis in SCD data using a real dataset, and we conclude by reflecting on the challenges that SCD researchers might face when applying network meta-analysis methods to their data.

Randomized controlled trials (RCTs) are the gold standard method for evaluating whether a treatment works in health care but can be difficult to find and make use of. We describe the development and evaluation of a system to automatically find and categorize all new RCT reports.
Trialstreamer continuously monitors PubMed and the World Health Organization International Clinical Trials Registry Platform, looking for new RCTs in humans using a validated classifier. We combine machine learning and rule-based methods to extract information from the RCT abstracts, including free-text descriptions of trial PICO (populations, interventions/comparators, and outcomes) elements and map these snippets to normalized MeSH (Medical Subject Headings) vocabulary terms. We additionally identify sample sizes, predict the risk of bias, and extract text conveying key findings. We store all extracted data in a database, which we make freely available for download, and via a search portal, which allows users to enter structured clinical queries. Results are ranked automatically to prioritize larger and higher-quality studies.
As of early June 2020, we have indexed 673 191 publications of RCTs, of which 22 363 were published in the first 5 months of 2020 (142 per day). We additionally include 304 111 trial registrations from the International Clinical Trials Registry Platform. The median trial sample size was 66.
We present an automated system for finding and categorizing RCTs. This yields a novel resource: a database of structured information automatically extracted for all published RCTs in humans. We make daily updates of this database available on our website (https://trialstreamer.robotreviewer.net).

Research synthesis is an important approach to summarizing a body of literature. Usually, the goal is to determine the effectiveness of an intervention, to determine the strength of association between two factors, to determine the prevalence of a condition, or to scope the literature. Research synthesis methods can also be used to appraise the quantity and quality of research output from institutions or countries. In the latter case, standard quantitative systematic review methodologies would not apply and investigators must borrow strategies from qualitative syntheses and bibliometric analyses to develop a complete and meaningful appraisal of the literature from a given country.
In this paper, we use the example of Cameroon to highlight some of the challenges and opportunities of appraising a body of country-specific literature. A comprehensive and exhaustive search of the literature was conducted to identify health-related literature from Cameroon published from 2005 to 2014. Titles were screened in duplicate.
A total of 8624 studies were retrieved of which 721 were retained. The main challenges were making a choice of synthesis approach; selecting the right databases, data storage and management; and sustaining the team. Key opportunities include enhanced networking, a detailed appraisal of funding sources, international collaborations, language of publication, and issues with study design. The product is a comprehensive and informative body of evidence that can be used to inform policy with regards to international collaboration, location of research studies, language of publication, knowledge areas of focus, and gaps.
Knowledge synthesis approaches can be adapted for appraisal of country-specific research and offer opportunities for in-depth appraisal of research output.

Systematic reviews of qualitative evidence have been widely used to provide information on the context and implementation of interventions, and their potential barriers and facilitators. However, such reviews face a number of methodological challenges, and there are ongoing debates as to how qualitative evidence can best be used to inform our understanding of interventions. In this paper, we use a case study of two systematic reviews of qualitative evidence on the prevention of skin cancer to explore these issues. We find that qualitative evidence not directly related to interventions is likely to be of value for such reviews, that it is often not possible to construct fully comprehensive search strategies, and that there are diminishing returns to the synthesis, in terms of added value or insight, from the inclusion of large numbers of primary studies. We conclude that there are a number of ways in which systematic reviews of qualitative evidence can be utilised in conjunction with evidence on intervention effectiveness, without compromising the rigour of the review process. In particular, the use of theory to inform frameworks for synthesis is a promising way to integrate a broader range of qualitative evidence. Copyright © 2012 John Wiley & Sons, Ltd.