Online tools supporting the conduct and reporting of systematic reviews and systematic maps: a case study on CADIMA and review of existing tools

Kohl, Christian; McIntosh, Emma; Unger, Stefan; Haddaway, Neal R.; Kecke, Steffen; Schiemann, Joachim; Wilhelm, Ralf

doi:10.1186/s13750-018-0115-5

Cited by 211 publications

(182 citation statements)

References 30 publications

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“…With one exception, all suggested tools were analyzed: CADIMA (Kohl et al, 2018), Covidence 6 (Veritas Health Innovation), DistillerSR 7 (Evidence Partners), Endnote 8 (Clarivate tice guidelines in medicine. The Cochrane 3 organization facilitates and ensures high quality SRs in clinical research and public health, which are achieving high societal impacts.…”

Section: Sr Tools Analyzedmentioning

confidence: 99%

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Software tools for literature screening in systematic reviews in biomedical research

Mierden¹

2019

ALTEX

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3Rs. One such approach is the systematic review (SR), which is the focus of this paper.An SR is a protocol-driven literature review that addresses a specific research question by collecting all relevant papers on the topic and extracting and analyzing their data in a transparent and objective manner. The SR results in a qualitative data analysis and may result in a quantitative meta-analysis (de Vries et al., 2014). SRs are already standard practice in clinical sciences. They are considered to provide the highest level of evidence (Hooijmans et al., 2010) and serve as a foundation of evidence-based prac-Abstract Systematic reviews (SRs) hold promise for implementing the 3Rs in animal sciences: they can retrieve available alternative models, help refine experiments, and identify insufficiencies in, or an excess of, scientific knowledge on a particular topic. Unfortunately, SRs can be labor-and time-intensive, especially the reference screening and data extraction phases. Fortunately, several software tools are available that make screening faster and easier. However, it is not always clear which features each tool offers. Therefore, a feature analysis was performed to compare different reference screening tools as objectively as possible. This analysis enables researchers to select the tool that is most appropriate for their needs. Sixteen different tools were compared: CADIMA, Covidence, DistillerSR, Endnote, Endnote using Bramer's method, EPPI-Reviewer, EROS, HAWC, Microsoft Excel, Excel using VonVille's method, Microsoft Word, Rayyan, RevMan, SyRF, SysRev.com, and SWIFT Active Screener. Their support of 21 features categorized as mandatory, desirable, and optional was tested. DistillerSR, EPPI-Reviewer, Covidence, and SWIFT Active Screener support all mandatory features. These tools are preferred for screening references, but none of them are free. The best scoring free tool is Rayyan, which lacks one mandatory function: distinct title/abstract and full-text phases. The lowest scoring tools were those not specifically designed for SRs, like Microsoft Word and Endnote. Their use can only be advised for small and simple SRs. A well-informed selection of SR screening tools will benefit review quality and speed, which can contribute to the advancement of the 3Rs in animal studies. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is appropriately cited.

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Section: Sr Tools Analyzedmentioning

confidence: 99%

“…Several articles have compared different SR tools before (e.g., Kohl et al, 2018;Marshall et al, 2014). However, these focus on the complete SR and provide little detail on the screening phase.…”

Section: Introductionmentioning

confidence: 99%

Software tools for literature screening in systematic reviews in biomedical research

Mierden¹

2019

ALTEX

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“…To formulate our search and screening protocols, we follow the guidelines of the Collaboration for Environmental Evidence (2018), and use the free online platform CADIMA to perform the screening phase (Kohl et al 2018).…”

Section: Systematic Literature Review Approachmentioning

confidence: 99%

Digitalisation of goods: a systematic review of the determinants and magnitude of the impacts on energy consumption

Court

Sorrell

2020

Environ. Res. Lett.

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Background. The contribution of information and communication technologies (ICTs) to a low carbon economy is unclear. Previous reviews emphasise the need to assess the specific factors that determine the environmental impacts of ICTs, but none of them link those factors to the magnitude of the impacts on energy consumption and carbon emissions. Our study aims to fill this evidence gap. Methods/Design. We restrict our analysis to a single application domain, namely e-materialisation, defined as the partial or complete substitution of material products with electronic equivalents. We conduct the first systematic literature review of the direct and higher order impacts of the digitalisation of goods on energy consumption. Results/Synthesis. We identify 31 relevant studies that we sort into five categories, namely: 'epublications' (e-books, e-magazines and e-journals); 'e-news'; 'e-business'; 'e-music'; and 'e-videos and games'. All but one of the 31 studies use life-cycle analysis and employ a range of product-system configurations, functional units, system boundaries and allocation rules. Confining attention to direct and substitution effects, the studies suggest potential energy savings from e-publications, e-news and e-music, and less potential from e-business and e-videos/games. However, different assumptions for key variables (such as the lifetime and energy efficiency of user devices, the extent to which personal transport is displaced and the number of users of material and digital products) lead to very different estimates-including many where lifecycle energy consumption increases. Most of the studies assume that digital goods substitute for material goods and all of them neglect rebound effects-which suggests that they overestimate energy savings. Discussion. Given the diversity and context-specificity of the available evidence, the optimistic assumptions that are frequently used (e.g. perfect substitution) and the neglect of rebound effects, we cannot conclude that e-materialisation has delivered significant energy savings to date or is likely to do so in the future.

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“…Training a machine‐learning algorithm with a subset of include/exclude decisions allows the algorithm to prioritize relevant papers and estimate when all relevant studies have been found. Automated data extraction is currently less developed as an off‐the‐shelf functionality, but is currently implemented in a few software packages (e.g., colandr; see also Kohl et al ; Westgate et al ).…”

Section: Challenges and Opportunities For Greater Use Of Srs And Evidmentioning

confidence: 99%

Using Systematic Review and Evidence Banking to Increase Uptake and Use of Aquatic Science in Decision‐Making

Bennett

Lee

Schofield

et al. 2018

Limnology & Oceanogr Bull

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To support sound decision‐making in environmental management, we need rigorous, defensible, and transparent synthesis of scientific evidence. The Association for the Sciences of Limnology and Oceanography and associated aquatic science societies are leaders in applying science to decision‐making, and yet many environmental decisions are still at risk of having to be made without a comprehensive, well‐synthesized evidence base to support them. In this article, we discuss two synergistic approaches that can help science inform decision‐making: systematic review and evidence banking. Our aim is to promote the use of these approaches, and to enlist support and action from you, the aquatic science community. We propose that you can improve the use and uptake of science in decision‐making by making your research more compatible with synthesis efforts by: considering risk of bias when designing your study and reporting results; reporting all relevant contextual information; analyzing your data using standard effect size approaches; and publishing your raw data. Awareness of how primary research feeds into informing policies can help you broaden the impact of your research, making it more directly relevant to decision‐making and more likely to contribute to the protection of aquatic ecosystems.

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Online tools supporting the conduct and reporting of systematic reviews and systematic maps: a case study on CADIMA and review of existing tools

Cited by 211 publications

References 30 publications

Software tools for literature screening in systematic reviews in biomedical research

Software tools for literature screening in systematic reviews in biomedical research

Digitalisation of goods: a systematic review of the determinants and magnitude of the impacts on energy consumption

Using Systematic Review and Evidence Banking to Increase Uptake and Use of Aquatic Science in Decision‐Making

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