literature review evaluation tool

10 Best Literature Review Tools for Researchers

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Boost your research game with these Best Literature Review Tools for Researchers! Uncover hidden gems, organize your findings, and ace your next research paper!

Conducting literature reviews poses challenges for researchers due to the overwhelming volume of information available and the lack of efficient methods to manage and analyze it.

Researchers struggle to identify key sources, extract relevant information, and maintain accuracy while manually conducting literature reviews. This leads to inefficiency, errors, and difficulty in identifying gaps or trends in existing literature.

Advancements in technology have resulted in a variety of literature review tools. These tools streamline the process, offering features like automated searching, filtering, citation management, and research data extraction. They save time, improve accuracy, and provide valuable insights for researchers. 

In this article, we present a curated list of the 10 best literature review tools, empowering researchers to make informed choices and revolutionize their systematic literature review process.

Table of Contents

Top 10 Literature Review Tools for Researchers: In A Nutshell (2023)

#1. semantic scholar – a free, ai-powered research tool for scientific literature.

Semantic Scholar is a cutting-edge literature review tool that researchers rely on for its comprehensive access to academic publications. With its advanced AI algorithms and extensive database, it simplifies the discovery of relevant research papers. 

By employing semantic analysis, users can explore scholarly articles based on context and meaning, making it a go-to resource for scholars across disciplines. 

Additionally, Semantic Scholar offers personalized recommendations and alerts, ensuring researchers stay updated with the latest developments. However, users should be cautious of potential limitations. 

Not all scholarly content may be indexed, and occasional false positives or inaccurate associations can occur. Furthermore, the tool primarily focuses on computer science and related fields, potentially limiting coverage in other disciplines. 

Researchers should be mindful of these considerations and supplement Semantic Scholar with other reputable resources for a comprehensive literature review. Despite these caveats, Semantic Scholar remains a valuable tool for streamlining research and staying informed.

#2. Elicit – Research assistant using language models like GPT-3

Elicit is a game-changing literature review tool that has gained popularity among researchers worldwide. With its user-friendly interface and extensive database of scholarly articles, it streamlines the research process, saving time and effort. 

The tool employs advanced algorithms to provide personalized recommendations, ensuring researchers discover the most relevant studies for their field. Elicit also promotes collaboration by enabling users to create shared folders and annotate articles.

However, users should be cautious when using Elicit. It is important to verify the credibility and accuracy of the sources found through the tool, as the database encompasses a wide range of publications. 

Additionally, occasional glitches in the search function have been reported, leading to incomplete or inaccurate results. While Elicit offers tremendous benefits, researchers should remain vigilant and cross-reference information to ensure a comprehensive literature review.

#3. Scite.Ai – Your personal research assistant

Scite.Ai is a popular literature review tool that revolutionizes the research process for scholars. With its innovative citation analysis feature, researchers can evaluate the credibility and impact of scientific articles, making informed decisions about their inclusion in their own work. 

By assessing the context in which citations are used, Scite.Ai ensures that the sources selected are reliable and of high quality, enabling researchers to establish a strong foundation for their research.

However, while Scite.Ai offers numerous advantages, there are a few aspects to be cautious about. As with any data-driven tool, occasional errors or inaccuracies may arise, necessitating researchers to cross-reference and verify results with other reputable sources. 

Moreover, Scite.Ai’s coverage may be limited in certain subject areas and languages, with a possibility of missing relevant studies, especially in niche fields or non-English publications. 

Therefore, researchers should supplement the use of Scite.Ai with additional resources to ensure comprehensive literature coverage and avoid any potential gaps in their research.

Rayyan offers the following paid plans:

• Monthly Plan: $20
• Yearly Plan: $12

#4. DistillerSR – Literature Review Software

DistillerSR is a powerful literature review tool trusted by researchers for its user-friendly interface and robust features. With its advanced search capabilities, researchers can quickly find relevant studies from multiple databases, saving time and effort. 

The tool offers comprehensive screening and data extraction functionalities, streamlining the review process and improving the reliability of findings. Real-time collaboration features also facilitate seamless teamwork among researchers.

While DistillerSR offers numerous advantages, there are a few considerations. Users should invest time in understanding the tool’s features and functionalities to maximize its potential. Additionally, the pricing structure may be a factor for individual researchers or small teams with limited budgets.

Despite occasional technical glitches reported by some users, the developers actively address these issues through updates and improvements, ensuring a better user experience. 

Overall, DistillerSR empowers researchers to navigate the vast sea of information, enhancing the quality and efficiency of literature reviews while fostering collaboration among research teams .

#5. Rayyan – AI Powered Tool for Systematic Literature Reviews

Rayyan is a powerful literature review tool that simplifies the research process for scholars and academics. With its user-friendly interface and efficient management features, Rayyan is highly regarded by researchers worldwide. 

It allows users to import and organize large volumes of scholarly articles, making it easier to identify relevant studies for their research projects. The tool also facilitates seamless collaboration among team members, enhancing productivity and streamlining the research workflow. 

However, it’s important to be aware of a few aspects. The free version of Rayyan has limitations, and upgrading to a premium subscription may be necessary for additional functionalities. 

Users should also be mindful of occasional technical glitches and compatibility issues, promptly reporting any problems. Despite these considerations, Rayyan remains a valuable asset for researchers, providing an effective solution for literature review tasks.

Rayyan offers both free and paid plans:

• Professional: $8.25/month
• Student: $4/month
• Pro Team: $8.25/month
• Team+: $24.99/month

#6. Consensus – Use AI to find you answers in scientific research

Consensus is a cutting-edge literature review tool that has become a go-to choice for researchers worldwide. Its intuitive interface and powerful capabilities make it a preferred tool for navigating and analyzing scholarly articles. 

With Consensus, researchers can save significant time by efficiently organizing and accessing relevant research material.People consider Consensus for several reasons. 

Its advanced search algorithms and filters help researchers sift through vast amounts of information, ensuring they focus on the most relevant articles. By streamlining the literature review process, Consensus allows researchers to extract valuable insights and accelerate their research progress.

However, there are a few factors to watch out for when using Consensus. As with any automated tool, researchers should exercise caution and independently verify the accuracy and relevance of the generated results. Complex or niche topics may present challenges, resulting in limited search results. Researchers should also supplement Consensus with manual searches to ensure comprehensive coverage of the literature.

Overall, Consensus is a valuable resource for researchers seeking to optimize their literature review process. By leveraging its features alongside critical thinking and manual searches, researchers can enhance the efficiency and effectiveness of their work, advancing their research endeavors to new heights.

Consensus offers both free and paid plans:

• Premium: $9.99/month
• Enterprise: Custom

#7. RAx – AI-powered reading assistant

Consensus is a revolutionary literature review tool that has transformed the research process for scholars worldwide. With its user-friendly interface and advanced features, it offers a vast database of academic publications across various disciplines, providing access to relevant and up-to-date literature. 

Using advanced algorithms and machine learning, Consensus delivers personalized recommendations, saving researchers time and effort in their literature search. 

However, researchers should be cautious of potential biases in the recommendation system and supplement their search with manual verification to ensure a comprehensive review. 

Additionally, occasional inaccuracies in metadata have been reported, making it essential for users to cross-reference information with reliable sources. Despite these considerations, Consensus remains an invaluable tool for enhancing the efficiency and quality of literature reviews.

RAx offers both free and paid plans. Currently offering 50% discounts as of July 2023:

• Premium: $6/month $3/month
• Premium with Copilot: $8/month $4/month

#8. Lateral – Advance your research with AI

“Lateral” is a revolutionary literature review tool trusted by researchers worldwide. With its user-friendly interface and powerful search capabilities, it simplifies the process of gathering and analyzing scholarly articles. 

By leveraging advanced algorithms and machine learning, Lateral saves researchers precious time by retrieving relevant articles and uncovering new connections between them, fostering interdisciplinary exploration.

While Lateral provides numerous benefits, users should exercise caution. It is advisable to cross-reference its findings with other sources to ensure a comprehensive review. 

Additionally, researchers must be mindful of potential biases introduced by the tool’s algorithms and should critically evaluate and interpret the results. 

Despite these considerations, Lateral remains an indispensable resource, empowering researchers to delve deeper into their fields of study and make valuable contributions to the academic community.

RAx offers both free and paid plans:

• Premium: $10.98
• Pro: $27.46

#9. Iris AI – Introducing the researcher workspace

Iris AI is an innovative literature review tool that has transformed the research process for academics and scholars. With its advanced artificial intelligence capabilities, Iris AI offers a seamless and efficient way to navigate through a vast array of academic papers and publications. 

Researchers are drawn to this tool because it saves valuable time by automating the tedious task of literature review and provides comprehensive coverage across multiple disciplines. 

Its intelligent recommendation system suggests related articles, enabling researchers to discover hidden connections and broaden their knowledge base. However, caution should be exercised while using Iris AI. 

While the tool excels at surfacing relevant papers, researchers should independently evaluate the quality and validity of the sources to ensure the reliability of their work. 

It’s important to note that Iris AI may occasionally miss niche or lesser-known publications, necessitating a supplementary search using traditional methods. 

Additionally, being an algorithm-based tool, there is a possibility of false positives or missed relevant articles due to the inherent limitations of automated text analysis. Nevertheless, Iris AI remains an invaluable asset for researchers, enhancing the quality and efficiency of their research endeavors.

Iris AI offers different pricing plans to cater to various user needs:

• Basic: Free
• Premium: Monthly ($82.41), Quarterly ($222.49), and Annual ($791.07)

#10. Scholarcy – Summarize your literature through AI

Scholarcy is a powerful literature review tool that helps researchers streamline their work. By employing advanced algorithms and natural language processing, it efficiently analyzes and summarizes academic papers, saving researchers valuable time. 

Scholarcy’s ability to extract key information and generate concise summaries makes it an attractive option for scholars looking to quickly grasp the main concepts and findings of multiple papers.

However, it is important to exercise caution when relying solely on Scholarcy. While it provides a useful starting point, engaging with the original research papers is crucial to ensure a comprehensive understanding. 

Scholarcy’s automated summarization may not capture the nuanced interpretations or contextual information presented in the full text. 

Researchers should also be aware that certain types of documents, particularly those with heavy mathematical or technical content, may pose challenges for the tool. 

Despite these considerations, Scholarcy remains a valuable resource for researchers seeking to enhance their literature review process and improve overall efficiency.

Scholarcy offer the following pricing plans:

• Browser Extension and Flashcards: Free 
• Personal Library: $9.99
• Academic Institution License: $8K+

Final Thoughts

In conclusion, conducting a comprehensive literature review is a crucial aspect of any research project, and the availability of reliable and efficient tools can greatly facilitate this process for researchers. This article has explored the top 10 literature review tools that have gained popularity among researchers.

Moreover, the rise of AI-powered tools like Iris.ai and Sci.ai promises to revolutionize the literature review process by automating various tasks and enhancing research efficiency. 

Ultimately, the choice of literature review tool depends on individual preferences and research needs, but the tools presented in this article serve as valuable resources to enhance the quality and productivity of research endeavors. 

Researchers are encouraged to explore and utilize these tools to stay at the forefront of knowledge in their respective fields and contribute to the advancement of science and academia.

Q1. What are literature review tools for researchers?

Literature review tools for researchers are software or online platforms designed to assist researchers in efficiently conducting literature reviews. These tools help researchers find, organize, analyze, and synthesize relevant academic papers and other sources of information.

Q2. What criteria should researchers consider when choosing literature review tools?

When choosing literature review tools, researchers should consider factors such as the tool’s search capabilities, database coverage, user interface, collaboration features, citation management, annotation and highlighting options, integration with reference management software, and data extraction capabilities. 

It’s also essential to consider the tool’s accessibility, cost, and technical support.

Q3. Are there any literature review tools specifically designed for systematic reviews or meta-analyses?

Yes, there are literature review tools that cater specifically to systematic reviews and meta-analyses, which involve a rigorous and structured approach to reviewing existing literature. These tools often provide features tailored to the specific needs of these methodologies, such as:

Screening and eligibility assessment: Systematic review tools typically offer functionalities for screening and assessing the eligibility of studies based on predefined inclusion and exclusion criteria. This streamlines the process of selecting relevant studies for analysis.

Data extraction and quality assessment: These tools often include templates and forms to facilitate data extraction from selected studies. Additionally, they may provide features for assessing the quality and risk of bias in individual studies.

Meta-analysis support: Some literature review tools include statistical analysis features that assist in conducting meta-analyses. These features can help calculate effect sizes, perform statistical tests, and generate forest plots or other visual representations of the meta-analytic results.

Reporting assistance: Many tools provide templates or frameworks for generating systematic review reports, ensuring compliance with established guidelines such as PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses).

Q4. Can literature review tools help with organizing and annotating collected references?

Yes, literature review tools often come equipped with features to help researchers organize and annotate collected references. Some common functionalities include:

Reference management: These tools enable researchers to import references from various sources, such as databases or PDF files, and store them in a central library. They typically allow you to create folders or tags to organize references based on themes or categories.

Annotation capabilities: Many tools provide options for adding annotations, comments, or tags to individual references or specific sections of research articles. This helps researchers keep track of important information, highlight key findings, or note potential connections between different sources.

Full-text search: Literature review tools often offer full-text search functionality, allowing you to search within the content of imported articles or documents. This can be particularly useful when you need to locate specific information or keywords across multiple references.

Integration with citation managers: Some literature review tools integrate with popular citation managers like Zotero, Mendeley, or EndNote, allowing seamless transfer of references and annotations between platforms.

By leveraging these features, researchers can streamline the organization and annotation of their collected references, making it easier to retrieve relevant information during the literature review process.

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Literature reviews

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When conducting your searches you may find many references that will not be suitable to use in your literature review.

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• Evaluate the quality and reliability of the references you find. Our evaluating information  page outlines what you need to consider when evaluating the books, journal articles, news and websites you find to ensure they are suitable for use in your literature review.

Critiquing the literature involves looking at the strength and weaknesses of the paper and evaluating the statements made by the author/s.

Books and resources on reading critically

• CASP Checklists Critical appraisal tools designed to be used when reading research. Includes tools for Qualitative studies, Systematic Reviews, Randomised Controlled Trials, Cohort Studies, Case Control Studies, Economic Evaluations, Diagnostic Studies and Clinical Prediction Rule.
• How to read critically - business and management From Postgraduate research in business - the aim of this chapter is to show you how to become a critical reader of typical academic literature in business and management.
• Learning to read critically in language and literacy Aims to develop skills of critical analysis and research design. It presents a series of examples of `best practice' in language and literacy education research.
• Critical appraisal in health sciences See tools for critically appraising health science research.

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Critical Appraisal Toolkit (CAT) for assessing multiple types of evidence

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Correspondence: [email protected]

Contributor: Jennifer Kruse, Public Health Agency of Canada – Conceptualization and project administration

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Collection date 2017 Sep 7.

Healthcare professionals are often expected to critically appraise research evidence in order to make recommendations for practice and policy development. Here we describe the Critical Appraisal Toolkit (CAT) currently used by the Public Health Agency of Canada. The CAT consists of: algorithms to identify the type of study design, three separate tools (for appraisal of analytic studies, descriptive studies and literature reviews), additional tools to support the appraisal process, and guidance for summarizing evidence and drawing conclusions about a body of evidence. Although the toolkit was created to assist in the development of national guidelines related to infection prevention and control, clinicians, policy makers and students can use it to guide appraisal of any health-related quantitative research. Participants in a pilot test completed a total of 101 critical appraisals and found that the CAT was user-friendly and helpful in the process of critical appraisal. Feedback from participants of the pilot test of the CAT informed further revisions prior to its release. The CAT adds to the arsenal of available tools and can be especially useful when the best available evidence comes from non-clinical trials and/or studies with weak designs, where other tools may not be easily applied.

Introduction

Healthcare professionals, researchers and policy makers are often involved in the development of public health policies or guidelines. The most valuable guidelines provide a basis for evidence-based practice with recommendations informed by current, high quality, peer-reviewed scientific evidence. To develop such guidelines, the available evidence needs to be critically appraised so that recommendations are based on the "best" evidence. The ability to critically appraise research is, therefore, an essential skill for health professionals serving on policy or guideline development working groups.

Our experience with working groups developing infection prevention and control guidelines was that the review of relevant evidence went smoothly while the critical appraisal of the evidence posed multiple challenges. Three main issues were identified. First, although working group members had strong expertise in infection prevention and control or other areas relevant to the guideline topic, they had varying levels of expertise in research methods and critical appraisal. Second, the critical appraisal tools in use at that time focused largely on analytic studies (such as clinical trials), and lacked definitions of key terms and explanations of the criteria used in the studies. As a result, the use of these tools by working group members did not result in a consistent way of appraising analytic studies nor did the tools provide a means of assessing descriptive studies and literature reviews. Third, working group members wanted guidance on how to progress from assessing individual studies to summarizing and assessing a body of evidence.

To address these issues, a review of existing critical appraisal tools was conducted. We found that the majority of existing tools were design-specific, with considerable variability in intent, criteria appraised and construction of the tools. A systematic review reported that fewer than half of existing tools had guidelines for use of the tool and interpretation of the items ( 1 ). The well-known Grading of Recommendations Assessment, Development and Evaluation (GRADE) rating-of-evidence system and the Cochrane tools for assessing risk of bias were considered for use ( 2 ), ( 3 ). At that time, the guidelines for using these tools were limited, and the tools were focused primarily on randomized controlled trials (RCTs) and non-randomized controlled trials. For feasibility and ethical reasons, clinical trials are rarely available for many common infection prevention and control issues ( 4 ), ( 5 ). For example, there are no intervention studies assessing which practice restrictions, if any, should be placed on healthcare workers who are infected with a blood-borne pathogen. Working group members were concerned that if they used GRADE, all evidence would be rated as very low or as low quality or certainty, and recommendations based on this evidence may be interpreted as unconvincing, even if they were based on the best or only available evidence.

The team decided to develop its own critical appraisal toolkit. So a small working group was convened, led by an epidemiologist with expertise in research, methodology and critical appraisal, with the goal of developing tools to critically appraise studies informing infection prevention and control recommendations. This article provides an overview of the Critical Appraisal Toolkit (CAT). The full document, entitled Infection Prevention and Control Guidelines Critical Appraisal Tool Kit is available online ( 6 ).

Following a review of existing critical appraisal tools, studies informing infection prevention and control guidelines that were in development were reviewed to identify the types of studies that would need to be appraised using the CAT. A preliminary draft of the CAT was used by various guideline development working groups and iterative revisions were made over a two year period. A pilot test of the CAT was then conducted which led to the final version ( 6 ).

The toolkit is set up to guide reviewers through three major phases in the critical appraisal of a body of evidence: appraisal of individual studies; summarizing the results of the appraisals; and appraisal of the body of evidence.

Tools for critically appraising individual studies

The first step in the critical appraisal of an individual study is to identify the study design; this can be surprisingly problematic, since many published research studies are complex. An algorithm was developed to help identify whether a study was an analytic study, a descriptive study or a literature review (see text box for definitions). It is critical to establish the design of the study first, as the criteria for assessment differs depending on the type of study.

Definitions of the types of studies that can be analyzed with the Critical Appraisal Toolkit*

Analytic study: A study designed to identify or measure effects of specific exposures, interventions or risk factors. This design employs the use of an appropriate comparison group to test epidemiologic hypotheses, thus attempting to identify associations or causal relationships.

Descriptive study: A study that describes characteristics of a condition in relation to particular factors or exposure of interest. This design often provides the first important clues about possible determinants of disease and is useful for the formulation of hypotheses that can be subsequently tested using an analytic design.

Literature review: A study that analyzes critical points of a published body of knowledge. This is done through summary, classification and comparison of prior studies. With the exception of meta-analyses, which statistically re-analyze pooled data from several studies, these studies are secondary sources and do not report any new or experimental work.

* Public Health Agency of Canada. Infection Prevention and Control Guidelines Critical Appraisal Tool Kit ( 6 )

Separate algorithms were developed for analytic studies, descriptive studies and literature reviews to help reviewers identify specific designs within those categories. The algorithm below, for example, helps reviewers determine which study design was used within the analytic study category ( Figure 1 ). It is based on key decision points such as number of groups or allocation to group. The legends for the algorithms and supportive tools such as the glossary provide additional detail to further differentiate study designs, such as whether a cohort study was retrospective or prospective.

Figure 1. Algorithm for identifying the type of analytic study.

Abbreviations: CBA, controlled before-after; ITS, interrupted time series; NRCT, non-randomized controlled trial; RCT, randomized controlled trial; UCBA, uncontrolled before-after

Separate critical appraisal tools were developed for analytic studies, for descriptive studies and for literature reviews, with relevant criteria in each tool. For example, a summary of the items covered in the analytic study critical appraisal tool is shown in Table 1 . This tool is used to appraise trials, observational studies and laboratory-based experiments. A supportive tool for assessing statistical analysis was also provided that describes common statistical tests used in epidemiologic studies.

Table 1. Aspects appraised in analytic study critical appraisal tool.

The descriptive study critical appraisal tool assesses different aspects of sampling, data collection, statistical analysis, and ethical conduct. It is used to appraise cross-sectional studies, outbreak investigations, case series and case reports.

The literature review critical appraisal tool assesses the methodology, results and applicability of narrative reviews, systematic reviews and meta-analyses.

After appraisal of individual items in each type of study, each critical appraisal tool also contains instructions for drawing a conclusion about the overall quality of the evidence from a study, based on the per-item appraisal. Quality is rated as high, medium or low. While a RCT is a strong study design and a survey is a weak design, it is possible to have a poor quality RCT or a high quality survey. As a result, the quality of evidence from a study is distinguished from the strength of a study design when assessing the quality of the overall body of evidence. A definition of some terms used to evaluate evidence in the CAT is shown in Table 2 .

Table 2. Definition of terms used to evaluate evidence.

* Considered strong design if there are at least two control groups and two intervention groups. Considered moderate design if there is only one control and one intervention group

Tools for summarizing the evidence

The second phase in the critical appraisal process involves summarizing the results of the critical appraisal of individual studies. Reviewers are instructed to complete a template evidence summary table, with key details about each study and its ratings. Studies are listed in descending order of strength in the table. The table simplifies looking across all studies that make up the body of evidence informing a recommendation and allows for easy comparison of participants, sample size, methods, interventions, magnitude and consistency of results, outcome measures and individual study quality as determined by the critical appraisal. These evidence summary tables are reviewed by the working group to determine the rating for the quality of the overall body of evidence and to facilitate development of recommendations based on evidence.

Rating the quality of the overall body of evidence

The third phase in the critical appraisal process is rating the quality of the overall body of evidence. The overall rating depends on the five items summarized in Table 2 : strength of study designs, quality of studies, number of studies, consistency of results and directness of the evidence. The various combinations of these factors lead to an overall rating of the strength of the body of evidence as strong, moderate or weak as summarized in Table 3 .

Table 3. Criteria for rating evidence on which recommendations are based.

A unique aspect of this toolkit is that recommendations are not graded but are formulated based on the graded body of evidence. Actions are either recommended or not recommended; it is the strength of the available evidence that varies, not the strength of the recommendation. The toolkit does highlight, however, the need to re-evaluate new evidence as it becomes available especially when recommendations are based on weak evidence.

Pilot test of the CAT

Of 34 individuals who indicated an interest in completing the pilot test, 17 completed it. Multiple peer-reviewed studies were selected representing analytic studies, descriptive studies and literature reviews. The same studies were assigned to participants with similar content expertise. Each participant was asked to appraise three analytic studies, two descriptive studies and one literature review, using the appropriate critical appraisal tool as identified by the participant. For each study appraised, one critical appraisal tool and the associated tool-specific feedback form were completed. Each participant also completed a single general feedback form. A total of 101 of 102 critical appraisals were conducted and returned, with 81 tool-specific feedback forms and 14 general feedback forms returned.

The majority of participants (>85%) found the flow of each tool was logical and the length acceptable but noted they still had difficulty identifying the study designs ( Table 4 ).

Table 4. Pilot test feedback on user friendliness.

* Number of tool-specific forms returned for total number of critical appraisals conducted

The vast majority of the feedback forms (86–93%) indicated that the different tools facilitated the critical appraisal process. In the assessment of consistency, however, only four of ten analytic studies appraised (40%), had complete agreement on the rating of overall study quality by participants, the other six studies had differences noted as mismatches. Four of the six studies with mismatches were observational studies. The differences were minor. None of the mismatches included a study that was rated as both high and low quality by different participants. Based on the comments provided by participants, most mismatches could likely have been resolved through discussion with peers. Mismatched ratings were not an issue for the descriptive studies and literature reviews. In summary, the pilot test provided useful feedback on different aspects of the toolkit. Revisions were made to address the issues identified from the pilot test and thus strengthen the CAT.

The Infection Prevention and Control Guidelines Critical Appraisal Tool Kit was developed in response to the needs of infection control professionals reviewing literature that generally did not include clinical trial evidence. The toolkit was designed to meet the identified needs for training in critical appraisal with extensive instructions and dictionaries, and tools applicable to all three types of studies (analytic studies, descriptive studies and literature reviews). The toolkit provided a method to progress from assessing individual studies to summarizing and assessing the strength of a body of evidence and assigning a grade. Recommendations are then developed based on the graded body of evidence. This grading system has been used by the Public Health Agency of Canada in the development of recent infection prevention and control guidelines ( 5 ), ( 7 ). The toolkit has also been used for conducting critical appraisal for other purposes, such as addressing a practice problem and serving as an educational tool ( 8 ), ( 9 ).

The CAT has a number of strengths. It is applicable to a wide variety of study designs. The criteria that are assessed allow for a comprehensive appraisal of individual studies and facilitates critical appraisal of a body of evidence. The dictionaries provide reviewers with a common language and criteria for discussion and decision making.

The CAT also has a number of limitations. The tools do not address all study designs (e.g., modelling studies) and the toolkit provides limited information on types of bias. Like the majority of critical appraisal tools ( 10 ), ( 11 ), these tools have not been tested for validity and reliability. Nonetheless, the criteria assessed are those indicated as important in textbooks and in the literature ( 12 ), ( 13 ). The grading scale used in this toolkit does not allow for comparison of evidence grading across organizations or internationally, but most reviewers do not need such comparability. It is more important that strong evidence be rated higher than weak evidence, and that reviewers provide rationales for their conclusions; the toolkit enables them to do so.

Overall, the pilot test reinforced that the CAT can help with critical appraisal training and can increase comfort levels for those with limited experience. Further evaluation of the toolkit could assess the effectiveness of revisions made and test its validity and reliability.

A frequent question regarding this toolkit is how it differs from GRADE as both distinguish stronger evidence from weaker evidence and use similar concepts and terminology. The main differences between GRADE and the CAT are presented in Table 5 . Key differences include the focus of the CAT on rating the quality of individual studies, and the detailed instructions and supporting tools that assist those with limited experience in critical appraisal. When clinical trials and well controlled intervention studies are or become available, GRADE and related tools from Cochrane would be more appropriate ( 2 ), ( 3 ). When descriptive studies are all that is available, the CAT is very useful.

Table 5. Comparison of features of the Critical Appraisal Toolkit (CAT) and GRADE.

Abbreviation: GRADE, Grading of Recommendations Assessment, Development and Evaluation

The Infection Prevention and Control Guidelines Critical Appraisal Tool Kit was developed in response to needs for training in critical appraisal, assessing evidence from a wide variety of research designs, and a method for going from assessing individual studies to characterizing the strength of a body of evidence. Clinician researchers, policy makers and students can use these tools for critical appraisal of studies whether they are trying to develop policies, find a potential solution to a practice problem or critique an article for a journal club. The toolkit adds to the arsenal of critical appraisal tools currently available and is especially useful in assessing evidence from a wide variety of research designs.

Authors’ Statement

DM – Conceptualization, methodology, investigation, data collection and curation and writing – original draft, review and editing

TO – Conceptualization, methodology, investigation, data collection and curation and writing – original draft, review and editing

KD – Conceptualization, review and editing, supervision and project administration

Acknowledgements

We thank the Infection Prevention and Control Expert Working Group of the Public Health Agency of Canada for feedback on the development of the toolkit, Lisa Marie Wasmund for data entry of the pilot test results, Katherine Defalco for review of data and cross-editing of content and technical terminology for the French version of the toolkit, Laurie O’Neil for review and feedback on early versions of the toolkit, Frédéric Bergeron for technical support with the algorithms in the toolkit and the Centre for Communicable Diseases and Infection Control of the Public Health Agency of Canada for review, feedback and ongoing use of the toolkit. We thank Dr. Patricia Huston, Canada Communicable Disease Report Editor-in-Chief, for a thorough review and constructive feedback on the draft manuscript.

Conflict of interest: None.

Funding: This work was supported by the Public Health Agency of Canada.

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• 7. Public Health Agency of Canada. Hand hygiene practices in healthcare settings. https://www.canada.ca/en/public-health/services/infectious-diseases/nosocomial-occupational-infections/hand-hygiene-practices-healthcare-settings.html [Accessed December 4, 2015].
• 8. Ha S, Paquette D, Tarasuk J, Dodds J, Gale-Rowe M, Brooks JI et al. A systematic review of HIV testing among Canadian populations. Can J Public Health 2014. Jan;105(1):e53–62. 10.17269/cjph.105.4128 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
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Choosing the Best Systematic Review Critical Appraisal Tool

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What is a critical appraisal.

Critical appraisal involves the evaluation of the quality, reliability, and relevance of studies, which is assessed based on quality measures specific to the research question, its related topics, design, methodology, data analysis, and the reporting of different types of systematic reviews .

Planning a critical appraisal starts with identifying or developing checklists. There are several critical appraisal tools that can be used to guide the process, adapting evaluation measures to be relevant to the specific research. It is important to pilot test these checklists and ensure that they are comprehensive enough to tackle all aspects of your systematic review.

What is the Purpose of a Critical Appraisal?

A critical appraisal is an integral part of a systematic review because it helps determine which studies can support the research. Here are some additional reasons why critical appraisals are important.

Assessing Quality

Critical appraisals employ measures specific to the systematic review. Through these, researchers can assess the quality of the studies—their trustworthiness, value, and reliability. This helps weed out substandard reviews, saving researchers’ time that would have been wasted reading full texts.

Determining Relevance

By appraising studies, researchers can determine whether or not they are relevant to the systematic review, such as if they’re connected to the topic or if their results support the research, etc. By doing this, the question “ Can you include a systematic review in a scoping review? ” can also be answered depending on its relevance to the study.

Identifying Flaws

Critical appraisals aim to identify methodological flaws in the literature, helping researchers and readers make informed decisions about the research evidence. They also help reduce the risk of bias when selecting studies.

What to Consider in a Critical Appraisal

Critical appraisals vary as they are specific to the topic, nature, and methodology of each systematic review. However, they generally have the same goal, trying to answer the following questions about the studies being considered:

• Is the study relevant to the research question?
• Is the study valid?
• Did the study use appropriate methods to address the research question?
• Does the study support the findings and evidence claims of the review?
• Are the valid results of the study important?
• Are the valid results of the study applicable to the research?

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Critical Appraisal Tools

There are hundreds of tools and worksheets that can serve as a guide through the critical appraisal process. Here are just some of the most common ones to consider:

• AMSTAR – to examine the effectiveness of interventions.
• CASP – to appraise randomized control trials, systematic reviews, cohort studies, case-control studies, qualitative research, economic evaluations, diagnostic tests, and clinical prediction rules.
• Cochrane Risk of Bias Tool – to assess the risk of bias of randomized control trials (RCTs).
• GRADE – to grade the quality of evidence in healthcare research and policy.
• JBI Critical Tools – to assess trustworthiness, relevance, and results of published papers.
• NOS – to assess the quality of non-randomized studies in meta-analyses.
• ROBIS – to assess the risk of bias in interventions, diagnosis, prognosis, and etiology.
• STROBE – to address cohort, case-control, and conduct cross-sectional studies.

What is the Best Critical Appraisal Tool?

There is no single best critical appraisal tool for any study design, nor is there a generic one that can be expected to consistently do well when used across different study types.

Critical appraisal tools vary considerably in intent, components, and construction, and the right one for your systematic review is the one that addresses the components that you need to tackle and ensures that your research results in comprehensive, unbiased, and valid findings.

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MAXQDA is the best choice for a comprehensive literature review. It works with a wide range of data types and offers powerful tools for literature review, such as reference management, qualitative, vocabulary, text analysis tools, and more.

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As your all-in-one literature review software, MAXQDA can be used to manage your entire research project. Easily import data from texts, interviews, focus groups, PDFs, web pages, spreadsheets, articles, e-books, and even social media data. Connect the reference management system of your choice with MAXQDA to easily import bibliographic data. Organize your data in groups, link relevant quotes to each other, keep track of your literature summaries, and share and compare work with your team members. Your project file stays flexible and you can expand and refine your category system as you go to suit your research.

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Easily import your literature review data

With a literature review software like MAXQDA, you can easily import bibliographic data from reference management programs for your literature review. MAXQDA can work with all reference management programs that can export their databases in RIS-format which is a standard format for bibliographic information. Like MAXQDA, these reference managers use project files, containing all collected bibliographic information, such as author, title, links to websites, keywords, abstracts, and other information. In addition, you can easily import the corresponding full texts. Upon import, all documents will be automatically pre-coded to facilitate your literature review at a later stage.

Capture your ideas while analyzing your literature

Great ideas will often occur to you while you’re doing your literature review. Using MAXQDA as your literature review software, you can create memos to store your ideas, such as research questions and objectives, or you can use memos for paraphrasing passages into your own words. By attaching memos like post-it notes to text passages, texts, document groups, images, audio/video clips, and of course codes, you can easily retrieve them at a later stage. Particularly useful for literature reviews are free memos written during the course of work from which passages can be copied and inserted into the final text.

Find concepts important to your generated literature review

When generating a literature review you might need to analyze a large amount of text. Luckily MAXQDA as the #1 literature review software offers Text Search tools that allow you to explore your documents without reading or coding them first. Automatically search for keywords (or dictionaries of keywords), such as important concepts for your literature review, and automatically code them with just a few clicks. Document variables that were automatically created during the import of your bibliographic information can be used for searching and retrieving certain text segments. MAXQDA’s powerful Coding Query allows you to analyze the combination of activated codes in different ways.

Aggregate your literature review

When conducting a literature review you can easily get lost. But with MAXQDA as your literature review software, you will never lose track of the bigger picture. Among other tools, MAXQDA’s overview and summary tables are especially useful for aggregating your literature review results. MAXQDA offers overview tables for almost everything, codes, memos, coded segments, links, and so on. With MAXQDA literature review tools you can create compressed summaries of sources that can be effectively compared and represented, and with just one click you can easily export your overview and summary tables and integrate them into your literature review report.

Powerful and easy-to-use literature review tools

Quantitative aspects can also be relevant when conducting a literature review analysis. Using MAXQDA as your literature review software enables you to employ a vast range of procedures for the quantitative evaluation of your material. You can sort sources according to document variables, compare amounts with frequency tables and charts, and much more. Make sure you don’t miss the word frequency tools of MAXQDA’s add-on module for quantitative content analysis. Included are tools for visual text exploration, content analysis, vocabulary analysis, dictionary-based analysis, and more that facilitate the quantitative analysis of terms and their semantic contexts.

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As an all-in-one literature review software, MAXQDA offers a variety of visual tools that are tailor-made for qualitative research and literature reviews. Create stunning visualizations to analyze your material. Of course, you can export your visualizations in various formats to enrich your literature review analysis report. Work with word clouds to explore the central themes of a text and key terms that are used, create charts to easily compare the occurrences of concepts and important keywords, or make use of the graphical representation possibilities of MAXMaps, which in particular permit the creation of concept maps. Thanks to the interactive connection between your visualizations with your MAXQDA data, you’ll never lose sight of the big picture.

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Get your maxqda license, compare the features of maxqda and maxqda analytics pro, faq: literature review software.

Literature review software is a tool designed to help researchers efficiently manage and analyze the existing body of literature relevant to their research topic. MAXQDA, a versatile qualitative data analysis tool, can be instrumental in this process.

Literature review software, like MAXQDA, typically includes features such as data import and organization, coding and categorization, advanced search capabilities, data visualization tools, and collaboration features. These features facilitate the systematic review and analysis of relevant literature.

Literature review software, including MAXQDA, can assist in qualitative data interpretation by enabling researchers to organize, code, and categorize relevant literature. This organized data can then be analyzed to identify trends, patterns, and themes, helping researchers draw meaningful insights from the literature they’ve reviewed.

Yes, literature review software like MAXQDA is suitable for researchers of all levels of experience. It offers user-friendly interfaces and extensive support resources, making it accessible to beginners while providing advanced features that cater to the needs of experienced researchers.

Getting started with literature review software, such as MAXQDA, typically involves downloading and installing the software, importing your relevant literature, and exploring the available features. Many software providers offer tutorials and documentation to help users get started quickly.

For students, MAXQDA can be an excellent literature review software choice. Its user-friendly interface, comprehensive feature set, and educational discounts make it a valuable tool for students conducting literature reviews as part of their academic research.

MAXQDA is available for both Windows and Mac users, making it a suitable choice for Mac users looking for literature review software. It offers a consistent and feature-rich experience on Mac operating systems.

When it comes to literature review software, MAXQDA is widely regarded as one of the best choices. Its robust feature set, user-friendly interface, and versatility make it a top pick for researchers conducting literature reviews.

Yes, literature reviews can be conducted without software. However, using literature review software like MAXQDA can significantly streamline and enhance the process by providing tools for efficient data management, analysis, and visualization.

• Open access
• Published: 08 June 2023

Guidance to best tools and practices for systematic reviews

• Kat Kolaski 1 ,
• Lynne Romeiser Logan 2 &
• John P. A. Ioannidis 3  

Systematic Reviews volume  12 , Article number:  96 ( 2023 ) Cite this article

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Data continue to accumulate indicating that many systematic reviews are methodologically flawed, biased, redundant, or uninformative. Some improvements have occurred in recent years based on empirical methods research and standardization of appraisal tools; however, many authors do not routinely or consistently apply these updated methods. In addition, guideline developers, peer reviewers, and journal editors often disregard current methodological standards. Although extensively acknowledged and explored in the methodological literature, most clinicians seem unaware of these issues and may automatically accept evidence syntheses (and clinical practice guidelines based on their conclusions) as trustworthy.

A plethora of methods and tools are recommended for the development and evaluation of evidence syntheses. It is important to understand what these are intended to do (and cannot do) and how they can be utilized. Our objective is to distill this sprawling information into a format that is understandable and readily accessible to authors, peer reviewers, and editors. In doing so, we aim to promote appreciation and understanding of the demanding science of evidence synthesis among stakeholders. We focus on well-documented deficiencies in key components of evidence syntheses to elucidate the rationale for current standards. The constructs underlying the tools developed to assess reporting, risk of bias, and methodological quality of evidence syntheses are distinguished from those involved in determining overall certainty of a body of evidence. Another important distinction is made between those tools used by authors to develop their syntheses as opposed to those used to ultimately judge their work.

Exemplar methods and research practices are described, complemented by novel pragmatic strategies to improve evidence syntheses. The latter include preferred terminology and a scheme to characterize types of research evidence. We organize best practice resources in a Concise Guide that can be widely adopted and adapted for routine implementation by authors and journals. Appropriate, informed use of these is encouraged, but we caution against their superficial application and emphasize their endorsement does not substitute for in-depth methodological training. By highlighting best practices with their rationale, we hope this guidance will inspire further evolution of methods and tools that can advance the field.

Part 1. The state of evidence synthesis

Evidence syntheses are commonly regarded as the foundation of evidence-based medicine (EBM). They are widely accredited for providing reliable evidence and, as such, they have significantly influenced medical research and clinical practice. Despite their uptake throughout health care and ubiquity in contemporary medical literature, some important aspects of evidence syntheses are generally overlooked or not well recognized. Evidence syntheses are mostly retrospective exercises, they often depend on weak or irreparably flawed data, and they may use tools that have acknowledged or yet unrecognized limitations. They are complicated and time-consuming undertakings prone to bias and errors. Production of a good evidence synthesis requires careful preparation and high levels of organization in order to limit potential pitfalls [ 1 ]. Many authors do not recognize the complexity of such an endeavor and the many methodological challenges they may encounter. Failure to do so is likely to result in research and resource waste.

Given their potential impact on people’s lives, it is crucial for evidence syntheses to correctly report on the current knowledge base. In order to be perceived as trustworthy, reliable demonstration of the accuracy of evidence syntheses is equally imperative [ 2 ]. Concerns about the trustworthiness of evidence syntheses are not recent developments. From the early years when EBM first began to gain traction until recent times when thousands of systematic reviews are published monthly [ 3 ] the rigor of evidence syntheses has always varied. Many systematic reviews and meta-analyses had obvious deficiencies because original methods and processes had gaps, lacked precision, and/or were not widely known. The situation has improved with empirical research concerning which methods to use and standardization of appraisal tools. However, given the geometrical increase in the number of evidence syntheses being published, a relatively larger pool of unreliable evidence syntheses is being published today.

Publication of methodological studies that critically appraise the methods used in evidence syntheses is increasing at a fast pace. This reflects the availability of tools specifically developed for this purpose [ 4 , 5 , 6 ]. Yet many clinical specialties report that alarming numbers of evidence syntheses fail on these assessments. The syntheses identified report on a broad range of common conditions including, but not limited to, cancer, [ 7 ] chronic obstructive pulmonary disease, [ 8 ] osteoporosis, [ 9 ] stroke, [ 10 ] cerebral palsy, [ 11 ] chronic low back pain, [ 12 ] refractive error, [ 13 ] major depression, [ 14 ] pain, [ 15 ] and obesity [ 16 , 17 ]. The situation is even more concerning with regard to evidence syntheses included in clinical practice guidelines (CPGs) [ 18 , 19 , 20 ]. Astonishingly, in a sample of CPGs published in 2017–18, more than half did not apply even basic systematic methods in the evidence syntheses used to inform their recommendations [ 21 ].

These reports, while not widely acknowledged, suggest there are pervasive problems not limited to evidence syntheses that evaluate specific kinds of interventions or include primary research of a particular study design (eg, randomized versus non-randomized) [ 22 ]. Similar concerns about the reliability of evidence syntheses have been expressed by proponents of EBM in highly circulated medical journals [ 23 , 24 , 25 , 26 ]. These publications have also raised awareness about redundancy, inadequate input of statistical expertise, and deficient reporting. These issues plague primary research as well; however, there is heightened concern for the impact of these deficiencies given the critical role of evidence syntheses in policy and clinical decision-making.

Methods and guidance to produce a reliable evidence synthesis

Several international consortiums of EBM experts and national health care organizations currently provide detailed guidance (Table 1 ). They draw criteria from the reporting and methodological standards of currently recommended appraisal tools, and regularly review and update their methods to reflect new information and changing needs. In addition, they endorse the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system for rating the overall quality of a body of evidence [ 27 ]. These groups typically certify or commission systematic reviews that are published in exclusive databases (eg, Cochrane, JBI) or are used to develop government or agency sponsored guidelines or health technology assessments (eg, National Institute for Health and Care Excellence [NICE], Scottish Intercollegiate Guidelines Network [SIGN], Agency for Healthcare Research and Quality [AHRQ]). They offer developers of evidence syntheses various levels of methodological advice, technical and administrative support, and editorial assistance. Use of specific protocols and checklists are required for development teams within these groups, but their online methodological resources are accessible to any potential author.

Notably, Cochrane is the largest single producer of evidence syntheses in biomedical research; however, these only account for 15% of the total [ 28 ]. The World Health Organization requires Cochrane standards be used to develop evidence syntheses that inform their CPGs [ 29 ]. Authors investigating questions of intervention effectiveness in syntheses developed for Cochrane follow the Methodological Expectations of Cochrane Intervention Reviews [ 30 ] and undergo multi-tiered peer review [ 31 , 32 ]. Several empirical evaluations have shown that Cochrane systematic reviews are of higher methodological quality compared with non-Cochrane reviews [ 4 , 7 , 9 , 11 , 14 , 32 , 33 , 34 , 35 ]. However, some of these assessments have biases: they may be conducted by Cochrane-affiliated authors, and they sometimes use scales and tools developed and used in the Cochrane environment and by its partners. In addition, evidence syntheses published in the Cochrane database are not subject to space or word restrictions, while non-Cochrane syntheses are often limited. As a result, information that may be relevant to the critical appraisal of non-Cochrane reviews is often removed or is relegated to online-only supplements that may not be readily or fully accessible [ 28 ].

Influences on the state of evidence synthesis

Many authors are familiar with the evidence syntheses produced by the leading EBM organizations but can be intimidated by the time and effort necessary to apply their standards. Instead of following their guidance, authors may employ methods that are discouraged or outdated 28]. Suboptimal methods described in in the literature may then be taken up by others. For example, the Newcastle–Ottawa Scale (NOS) is a commonly used tool for appraising non-randomized studies [ 36 ]. Many authors justify their selection of this tool with reference to a publication that describes the unreliability of the NOS and recommends against its use [ 37 ]. Obviously, the authors who cite this report for that purpose have not read it. Authors and peer reviewers have a responsibility to use reliable and accurate methods and not copycat previous citations or substandard work [ 38 , 39 ]. Similar cautions may potentially extend to automation tools. These have concentrated on evidence searching [ 40 ] and selection given how demanding it is for humans to maintain truly up-to-date evidence [ 2 , 41 ]. Cochrane has deployed machine learning to identify randomized controlled trials (RCTs) and studies related to COVID-19, [ 2 , 42 ] but such tools are not yet commonly used [ 43 ]. The routine integration of automation tools in the development of future evidence syntheses should not displace the interpretive part of the process.

Editorials about unreliable or misleading systematic reviews highlight several of the intertwining factors that may contribute to continued publication of unreliable evidence syntheses: shortcomings and inconsistencies of the peer review process, lack of endorsement of current standards on the part of journal editors, the incentive structure of academia, industry influences, publication bias, and the lure of “predatory” journals [ 44 , 45 , 46 , 47 , 48 ]. At this juncture, clarification of the extent to which each of these factors contribute remains speculative, but their impact is likely to be synergistic.

Over time, the generalized acceptance of the conclusions of systematic reviews as incontrovertible has affected trends in the dissemination and uptake of evidence. Reporting of the results of evidence syntheses and recommendations of CPGs has shifted beyond medical journals to press releases and news headlines and, more recently, to the realm of social media and influencers. The lay public and policy makers may depend on these outlets for interpreting evidence syntheses and CPGs. Unfortunately, communication to the general public often reflects intentional or non-intentional misrepresentation or “spin” of the research findings [ 49 , 50 , 51 , 52 ] News and social media outlets also tend to reduce conclusions on a body of evidence and recommendations for treatment to binary choices (eg, “do it” versus “don’t do it”) that may be assigned an actionable symbol (eg, red/green traffic lights, smiley/frowning face emoji).

Strategies for improvement

Many authors and peer reviewers are volunteer health care professionals or trainees who lack formal training in evidence synthesis [ 46 , 53 ]. Informing them about research methodology could increase the likelihood they will apply rigorous methods [ 25 , 33 , 45 ]. We tackle this challenge, from both a theoretical and a practical perspective, by offering guidance applicable to any specialty. It is based on recent methodological research that is extensively referenced to promote self-study. However, the information presented is not intended to be substitute for committed training in evidence synthesis methodology; instead, we hope to inspire our target audience to seek such training. We also hope to inform a broader audience of clinicians and guideline developers influenced by evidence syntheses. Notably, these communities often include the same members who serve in different capacities.

In the following sections, we highlight methodological concepts and practices that may be unfamiliar, problematic, confusing, or controversial. In Part 2, we consider various types of evidence syntheses and the types of research evidence summarized by them. In Part 3, we examine some widely used (and misused) tools for the critical appraisal of systematic reviews and reporting guidelines for evidence syntheses. In Part 4, we discuss how to meet methodological conduct standards applicable to key components of systematic reviews. In Part 5, we describe the merits and caveats of rating the overall certainty of a body of evidence. Finally, in Part 6, we summarize suggested terminology, methods, and tools for development and evaluation of evidence syntheses that reflect current best practices.

Part 2. Types of syntheses and research evidence

A good foundation for the development of evidence syntheses requires an appreciation of their various methodologies and the ability to correctly identify the types of research potentially available for inclusion in the synthesis.

Types of evidence syntheses

Systematic reviews have historically focused on the benefits and harms of interventions; over time, various types of systematic reviews have emerged to address the diverse information needs of clinicians, patients, and policy makers [ 54 ] Systematic reviews with traditional components have become defined by the different topics they assess (Table 2.1 ). In addition, other distinctive types of evidence syntheses have evolved, including overviews or umbrella reviews, scoping reviews, rapid reviews, and living reviews. The popularity of these has been increasing in recent years [ 55 , 56 , 57 , 58 ]. A summary of the development, methods, available guidance, and indications for these unique types of evidence syntheses is available in Additional File 2 A.

Both Cochrane [ 30 , 59 ] and JBI [ 60 ] provide methodologies for many types of evidence syntheses; they describe these with different terminology, but there is obvious overlap (Table 2.2 ). The majority of evidence syntheses published by Cochrane (96%) and JBI (62%) are categorized as intervention reviews. This reflects the earlier development and dissemination of their intervention review methodologies; these remain well-established [ 30 , 59 , 61 ] as both organizations continue to focus on topics related to treatment efficacy and harms. In contrast, intervention reviews represent only about half of the total published in the general medical literature, and several non-intervention review types contribute to a significant proportion of the other half.

Types of research evidence

There is consensus on the importance of using multiple study designs in evidence syntheses; at the same time, there is a lack of agreement on methods to identify included study designs. Authors of evidence syntheses may use various taxonomies and associated algorithms to guide selection and/or classification of study designs. These tools differentiate categories of research and apply labels to individual study designs (eg, RCT, cross-sectional). A familiar example is the Design Tree endorsed by the Centre for Evidence-Based Medicine [ 70 ]. Such tools may not be helpful to authors of evidence syntheses for multiple reasons.

Suboptimal levels of agreement and accuracy even among trained methodologists reflect challenges with the application of such tools [ 71 , 72 ]. Problematic distinctions or decision points (eg, experimental or observational, controlled or uncontrolled, prospective or retrospective) and design labels (eg, cohort, case control, uncontrolled trial) have been reported [ 71 ]. The variable application of ambiguous study design labels to non-randomized studies is common, making them especially prone to misclassification [ 73 ]. In addition, study labels do not denote the unique design features that make different types of non-randomized studies susceptible to different biases, including those related to how the data are obtained (eg, clinical trials, disease registries, wearable devices). Given this limitation, it is important to be aware that design labels preclude the accurate assignment of non-randomized studies to a “level of evidence” in traditional hierarchies [ 74 ].

These concerns suggest that available tools and nomenclature used to distinguish types of research evidence may not uniformly apply to biomedical research and non-health fields that utilize evidence syntheses (eg, education, economics) [ 75 , 76 ]. Moreover, primary research reports often do not describe study design or do so incompletely or inaccurately; thus, indexing in PubMed and other databases does not address the potential for misclassification [ 77 ]. Yet proper identification of research evidence has implications for several key components of evidence syntheses. For example, search strategies limited by index terms using design labels or study selection based on labels applied by the authors of primary studies may cause inconsistent or unjustified study inclusions and/or exclusions [ 77 ]. In addition, because risk of bias (RoB) tools consider attributes specific to certain types of studies and study design features, results of these assessments may be invalidated if an inappropriate tool is used. Appropriate classification of studies is also relevant for the selection of a suitable method of synthesis and interpretation of those results.

An alternative to these tools and nomenclature involves application of a few fundamental distinctions that encompass a wide range of research designs and contexts. While these distinctions are not novel, we integrate them into a practical scheme (see Fig. 1 ) designed to guide authors of evidence syntheses in the basic identification of research evidence. The initial distinction is between primary and secondary studies. Primary studies are then further distinguished by: 1) the type of data reported (qualitative or quantitative); and 2) two defining design features (group or single-case and randomized or non-randomized). The different types of studies and study designs represented in the scheme are described in detail in Additional File 2 B. It is important to conceptualize their methods as complementary as opposed to contrasting or hierarchical [ 78 ]; each offers advantages and disadvantages that determine their appropriateness for answering different kinds of research questions in an evidence synthesis.

Distinguishing types of research evidence

Application of these basic distinctions may avoid some of the potential difficulties associated with study design labels and taxonomies. Nevertheless, debatable methodological issues are raised when certain types of research identified in this scheme are included in an evidence synthesis. We briefly highlight those associated with inclusion of non-randomized studies, case reports and series, and a combination of primary and secondary studies.

Non-randomized studies

When investigating an intervention’s effectiveness, it is important for authors to recognize the uncertainty of observed effects reported by studies with high RoB. Results of statistical analyses that include such studies need to be interpreted with caution in order to avoid misleading conclusions [ 74 ]. Review authors may consider excluding randomized studies with high RoB from meta-analyses. Non-randomized studies of intervention (NRSI) are affected by a greater potential range of biases and thus vary more than RCTs in their ability to estimate a causal effect [ 79 ]. If data from NRSI are synthesized in meta-analyses, it is helpful to separately report their summary estimates [ 6 , 74 ].

Nonetheless, certain design features of NRSI (eg, which parts of the study were prospectively designed) may help to distinguish stronger from weaker ones. Cochrane recommends that authors of a review including NRSI focus on relevant study design features when determining eligibility criteria instead of relying on non-informative study design labels [ 79 , 80 ] This process is facilitated by a study design feature checklist; guidance on using the checklist is included with developers’ description of the tool [ 73 , 74 ]. Authors collect information about these design features during data extraction and then consider it when making final study selection decisions and when performing RoB assessments of the included NRSI.

Case reports and case series

Correctly identified case reports and case series can contribute evidence not well captured by other designs [ 81 ]; in addition, some topics may be limited to a body of evidence that consists primarily of uncontrolled clinical observations. Murad and colleagues offer a framework for how to include case reports and series in an evidence synthesis [ 82 ]. Distinguishing between cohort studies and case series in these syntheses is important, especially for those that rely on evidence from NRSI. Additional data obtained from studies misclassified as case series can potentially increase the confidence in effect estimates. Mathes and Pieper provide authors of evidence syntheses with specific guidance on distinguishing between cohort studies and case series, but emphasize the increased workload involved [ 77 ].

Primary and secondary studies

Synthesis of combined evidence from primary and secondary studies may provide a broad perspective on the entirety of available literature on a topic. This is, in fact, the recommended strategy for scoping reviews that may include a variety of sources of evidence (eg, CPGs, popular media). However, except for scoping reviews, the synthesis of data from primary and secondary studies is discouraged unless there are strong reasons to justify doing so.

Combining primary and secondary sources of evidence is challenging for authors of other types of evidence syntheses for several reasons [ 83 ]. Assessments of RoB for primary and secondary studies are derived from conceptually different tools, thus obfuscating the ability to make an overall RoB assessment of a combination of these study types. In addition, authors who include primary and secondary studies must devise non-standardized methods for synthesis. Note this contrasts with well-established methods available for updating existing evidence syntheses with additional data from new primary studies [ 84 , 85 , 86 ]. However, a new review that synthesizes data from primary and secondary studies raises questions of validity and may unintentionally support a biased conclusion because no existing methodological guidance is currently available [ 87 ].

Recommendations

We suggest that journal editors require authors to identify which type of evidence synthesis they are submitting and reference the specific methodology used for its development. This will clarify the research question and methods for peer reviewers and potentially simplify the editorial process. Editors should announce this practice and include it in the instructions to authors. To decrease bias and apply correct methods, authors must also accurately identify the types of research evidence included in their syntheses.

Part 3. Conduct and reporting

The need to develop criteria to assess the rigor of systematic reviews was recognized soon after the EBM movement began to gain international traction [ 88 , 89 ]. Systematic reviews rapidly became popular, but many were very poorly conceived, conducted, and reported. These problems remain highly prevalent [ 23 ] despite development of guidelines and tools to standardize and improve the performance and reporting of evidence syntheses [ 22 , 28 ]. Table 3.1  provides some historical perspective on the evolution of tools developed specifically for the evaluation of systematic reviews, with or without meta-analysis.

These tools are often interchangeably invoked when referring to the “quality” of an evidence synthesis. However, quality is a vague term that is frequently misused and misunderstood; more precisely, these tools specify different standards for evidence syntheses. Methodological standards address how well a systematic review was designed and performed [ 5 ]. RoB assessments refer to systematic flaws or limitations in the design, conduct, or analysis of research that distort the findings of the review [ 4 ]. Reporting standards help systematic review authors describe the methodology they used and the results of their synthesis in sufficient detail [ 92 ]. It is essential to distinguish between these evaluations: a systematic review may be biased, it may fail to report sufficient information on essential features, or it may exhibit both problems; a thoroughly reported systematic evidence synthesis review may still be biased and flawed while an otherwise unbiased one may suffer from deficient documentation.

We direct attention to the currently recommended tools listed in Table 3.1  but concentrate on AMSTAR-2 (update of AMSTAR [A Measurement Tool to Assess Systematic Reviews]) and ROBIS (Risk of Bias in Systematic Reviews), which evaluate methodological quality and RoB, respectively. For comparison and completeness, we include PRISMA 2020 (update of the 2009 Preferred Reporting Items for Systematic Reviews of Meta-Analyses statement), which offers guidance on reporting standards. The exclusive focus on these three tools is by design; it addresses concerns related to the considerable variability in tools used for the evaluation of systematic reviews [ 28 , 88 , 96 , 97 ]. We highlight the underlying constructs these tools were designed to assess, then describe their components and applications. Their known (or potential) uptake and impact and limitations are also discussed.

Evaluation of conduct

Development.

AMSTAR [ 5 ] was in use for a decade prior to the 2017 publication of AMSTAR-2; both provide a broad evaluation of methodological quality of intervention systematic reviews, including flaws arising through poor conduct of the review [ 6 ]. ROBIS, published in 2016, was developed to specifically assess RoB introduced by the conduct of the review; it is applicable to systematic reviews of interventions and several other types of reviews [ 4 ]. Both tools reflect a shift to a domain-based approach as opposed to generic quality checklists. There are a few items unique to each tool; however, similarities between items have been demonstrated [ 98 , 99 ]. AMSTAR-2 and ROBIS are recommended for use by: 1) authors of overviews or umbrella reviews and CPGs to evaluate systematic reviews considered as evidence; 2) authors of methodological research studies to appraise included systematic reviews; and 3) peer reviewers for appraisal of submitted systematic review manuscripts. For authors, these tools may function as teaching aids and inform conduct of their review during its development.

Description

Systematic reviews that include randomized and/or non-randomized studies as evidence can be appraised with AMSTAR-2 and ROBIS. Other characteristics of AMSTAR-2 and ROBIS are summarized in Table 3.2 . Both tools define categories for an overall rating; however, neither tool is intended to generate a total score by simply calculating the number of responses satisfying criteria for individual items [ 4 , 6 ]. AMSTAR-2 focuses on the rigor of a review’s methods irrespective of the specific subject matter. ROBIS places emphasis on a review’s results section— this suggests it may be optimally applied by appraisers with some knowledge of the review’s topic as they may be better equipped to determine if certain procedures (or lack thereof) would impact the validity of a review’s findings [ 98 , 100 ]. Reliability studies show AMSTAR-2 overall confidence ratings strongly correlate with the overall RoB ratings in ROBIS [ 100 , 101 ].

Interrater reliability has been shown to be acceptable for AMSTAR-2 [ 6 , 11 , 102 ] and ROBIS [ 4 , 98 , 103 ] but neither tool has been shown to be superior in this regard [ 100 , 101 , 104 , 105 ]. Overall, variability in reliability for both tools has been reported across items, between pairs of raters, and between centers [ 6 , 100 , 101 , 104 ]. The effects of appraiser experience on the results of AMSTAR-2 and ROBIS require further evaluation [ 101 , 105 ]. Updates to both tools should address items shown to be prone to individual appraisers’ subjective biases and opinions [ 11 , 100 ]; this may involve modifications of the current domains and signaling questions as well as incorporation of methods to make an appraiser’s judgments more explicit. Future revisions of these tools may also consider the addition of standards for aspects of systematic review development currently lacking (eg, rating overall certainty of evidence, [ 99 ] methods for synthesis without meta-analysis [ 105 ]) and removal of items that assess aspects of reporting that are thoroughly evaluated by PRISMA 2020.

Application

A good understanding of what is required to satisfy the standards of AMSTAR-2 and ROBIS involves study of the accompanying guidance documents written by the tools’ developers; these contain detailed descriptions of each item’s standards. In addition, accurate appraisal of a systematic review with either tool requires training. Most experts recommend independent assessment by at least two appraisers with a process for resolving discrepancies as well as procedures to establish interrater reliability, such as pilot testing, a calibration phase or exercise, and development of predefined decision rules [ 35 , 99 , 100 , 101 , 103 , 104 , 106 ]. These methods may, to some extent, address the challenges associated with the diversity in methodological training, subject matter expertise, and experience using the tools that are likely to exist among appraisers.

The standards of AMSTAR, AMSTAR-2, and ROBIS have been used in many methodological studies and epidemiological investigations. However, the increased publication of overviews or umbrella reviews and CPGs has likely been a greater influence on the widening acceptance of these tools. Critical appraisal of the secondary studies considered evidence is essential to the trustworthiness of both the recommendations of CPGs and the conclusions of overviews. Currently both Cochrane [ 55 ] and JBI [ 107 ] recommend AMSTAR-2 and ROBIS in their guidance for authors of overviews or umbrella reviews. However, ROBIS and AMSTAR-2 were released in 2016 and 2017, respectively; thus, to date, limited data have been reported about the uptake of these tools or which of the two may be preferred [ 21 , 106 ]. Currently, in relation to CPGs, AMSTAR-2 appears to be overwhelmingly popular compared to ROBIS. A Google Scholar search of this topic (search terms “AMSTAR 2 AND clinical practice guidelines,” “ROBIS AND clinical practice guidelines” 13 May 2022) found 12,700 hits for AMSTAR-2 and 1,280 for ROBIS. The apparent greater appeal of AMSTAR-2 may relate to its longer track record given the original version of the tool was in use for 10 years prior to its update in 2017.

Barriers to the uptake of AMSTAR-2 and ROBIS include the real or perceived time and resources necessary to complete the items they include and appraisers’ confidence in their own ratings [ 104 ]. Reports from comparative studies available to date indicate that appraisers find AMSTAR-2 questions, responses, and guidance to be clearer and simpler compared with ROBIS [ 11 , 101 , 104 , 105 ]. This suggests that for appraisal of intervention systematic reviews, AMSTAR-2 may be a more practical tool than ROBIS, especially for novice appraisers [ 101 , 103 , 104 , 105 ]. The unique characteristics of each tool, as well as their potential advantages and disadvantages, should be taken into consideration when deciding which tool should be used for an appraisal of a systematic review. In addition, the choice of one or the other may depend on how the results of an appraisal will be used; for example, a peer reviewer’s appraisal of a single manuscript versus an appraisal of multiple systematic reviews in an overview or umbrella review, CPG, or systematic methodological study.

Authors of overviews and CPGs report results of AMSTAR-2 and ROBIS appraisals for each of the systematic reviews they include as evidence. Ideally, an independent judgment of their appraisals can be made by the end users of overviews and CPGs; however, most stakeholders, including clinicians, are unlikely to have a sophisticated understanding of these tools. Nevertheless, they should at least be aware that AMSTAR-2 and ROBIS ratings reported in overviews and CPGs may be inaccurate because the tools are not applied as intended by their developers. This can result from inadequate training of the overview or CPG authors who perform the appraisals, or to modifications of the appraisal tools imposed by them. The potential variability in overall confidence and RoB ratings highlights why appraisers applying these tools need to support their judgments with explicit documentation; this allows readers to judge for themselves whether they agree with the criteria used by appraisers [ 4 , 108 ]. When these judgments are explicit, the underlying rationale used when applying these tools can be assessed [ 109 ].

Theoretically, we would expect an association of AMSTAR-2 with improved methodological rigor and an association of ROBIS with lower RoB in recent systematic reviews compared to those published before 2017. To our knowledge, this has not yet been demonstrated; however, like reports about the actual uptake of these tools, time will tell. Additional data on user experience is also needed to further elucidate the practical challenges and methodological nuances encountered with the application of these tools. This information could potentially inform the creation of unifying criteria to guide and standardize the appraisal of evidence syntheses [ 109 ].

Evaluation of reporting

Complete reporting is essential for users to establish the trustworthiness and applicability of a systematic review’s findings. Efforts to standardize and improve the reporting of systematic reviews resulted in the 2009 publication of the PRISMA statement [ 92 ] with its accompanying explanation and elaboration document [ 110 ]. This guideline was designed to help authors prepare a complete and transparent report of their systematic review. In addition, adherence to PRISMA is often used to evaluate the thoroughness of reporting of published systematic reviews [ 111 ]. The updated version, PRISMA 2020 [ 93 ], and its guidance document [ 112 ] were published in 2021. Items on the original and updated versions of PRISMA are organized by the six basic review components they address (title, abstract, introduction, methods, results, discussion). The PRISMA 2020 update is a considerably expanded version of the original; it includes standards and examples for the 27 original and 13 additional reporting items that capture methodological advances and may enhance the replicability of reviews [ 113 ].

The original PRISMA statement fostered the development of various PRISMA extensions (Table 3.3 ). These include reporting guidance for scoping reviews and reviews of diagnostic test accuracy and for intervention reviews that report on the following: harms outcomes, equity issues, the effects of acupuncture, the results of network meta-analyses and analyses of individual participant data. Detailed reporting guidance for specific systematic review components (abstracts, protocols, literature searches) is also available.

Uptake and impact

The 2009 PRISMA standards [ 92 ] for reporting have been widely endorsed by authors, journals, and EBM-related organizations. We anticipate the same for PRISMA 2020 [ 93 ] given its co-publication in multiple high-impact journals. However, to date, there is a lack of strong evidence for an association between improved systematic review reporting and endorsement of PRISMA 2009 standards [ 43 , 111 ]. Most journals require a PRISMA checklist accompany submissions of systematic review manuscripts. However, the accuracy of information presented on these self-reported checklists is not necessarily verified. It remains unclear which strategies (eg, authors’ self-report of checklists, peer reviewer checks) might improve adherence to the PRISMA reporting standards; in addition, the feasibility of any potentially effective strategies must be taken into consideration given the structure and limitations of current research and publication practices [ 124 ].

Pitfalls and limitations of PRISMA, AMSTAR-2, and ROBIS

Misunderstanding of the roles of these tools and their misapplication may be widespread problems. PRISMA 2020 is a reporting guideline that is most beneficial if consulted when developing a review as opposed to merely completing a checklist when submitting to a journal; at that point, the review is finished, with good or bad methodological choices. However, PRISMA checklists evaluate how completely an element of review conduct was reported, but do not evaluate the caliber of conduct or performance of a review. Thus, review authors and readers should not think that a rigorous systematic review can be produced by simply following the PRISMA 2020 guidelines. Similarly, it is important to recognize that AMSTAR-2 and ROBIS are tools to evaluate the conduct of a review but do not substitute for conceptual methodological guidance. In addition, they are not intended to be simple checklists. In fact, they have the potential for misuse or abuse if applied as such; for example, by calculating a total score to make a judgment about a review’s overall confidence or RoB. Proper selection of a response for the individual items on AMSTAR-2 and ROBIS requires training or at least reference to their accompanying guidance documents.

Not surprisingly, it has been shown that compliance with the PRISMA checklist is not necessarily associated with satisfying the standards of ROBIS [ 125 ]. AMSTAR-2 and ROBIS were not available when PRISMA 2009 was developed; however, they were considered in the development of PRISMA 2020 [ 113 ]. Therefore, future studies may show a positive relationship between fulfillment of PRISMA 2020 standards for reporting and meeting the standards of tools evaluating methodological quality and RoB.

Choice of an appropriate tool for the evaluation of a systematic review first involves identification of the underlying construct to be assessed. For systematic reviews of interventions, recommended tools include AMSTAR-2 and ROBIS for appraisal of conduct and PRISMA 2020 for completeness of reporting. All three tools were developed rigorously and provide easily accessible and detailed user guidance, which is necessary for their proper application and interpretation. When considering a manuscript for publication, training in these tools can sensitize peer reviewers and editors to major issues that may affect the review’s trustworthiness and completeness of reporting. Judgment of the overall certainty of a body of evidence and formulation of recommendations rely, in part, on AMSTAR-2 or ROBIS appraisals of systematic reviews. Therefore, training on the application of these tools is essential for authors of overviews and developers of CPGs. Peer reviewers and editors considering an overview or CPG for publication must hold their authors to a high standard of transparency regarding both the conduct and reporting of these appraisals.

Part 4. Meeting conduct standards

Many authors, peer reviewers, and editors erroneously equate fulfillment of the items on the PRISMA checklist with superior methodological rigor. For direction on methodology, we refer them to available resources that provide comprehensive conceptual guidance [ 59 , 60 ] as well as primers with basic step-by-step instructions [ 1 , 126 , 127 ]. This section is intended to complement study of such resources by facilitating use of AMSTAR-2 and ROBIS, tools specifically developed to evaluate methodological rigor of systematic reviews. These tools are widely accepted by methodologists; however, in the general medical literature, they are not uniformly selected for the critical appraisal of systematic reviews [ 88 , 96 ].

To enable their uptake, Table 4.1  links review components to the corresponding appraisal tool items. Expectations of AMSTAR-2 and ROBIS are concisely stated, and reasoning provided.

Issues involved in meeting the standards for seven review components (identified in bold in Table 4.1 ) are addressed in detail. These were chosen for elaboration for one (or both) of two reasons: 1) the component has been identified as potentially problematic for systematic review authors based on consistent reports of their frequent AMSTAR-2 or ROBIS deficiencies [ 9 , 11 , 15 , 88 , 128 , 129 ]; and/or 2) the review component is judged by standards of an AMSTAR-2 “critical” domain. These have the greatest implications for how a systematic review will be appraised: if standards for any one of these critical domains are not met, the review is rated as having “critically low confidence.”

Research question

Specific and unambiguous research questions may have more value for reviews that deal with hypothesis testing. Mnemonics for the various elements of research questions are suggested by JBI and Cochrane (Table 2.1 ). These prompt authors to consider the specialized methods involved for developing different types of systematic reviews; however, while inclusion of the suggested elements makes a review compliant with a particular review’s methods, it does not necessarily make a research question appropriate. Table 4.2  lists acronyms that may aid in developing the research question. They include overlapping concepts of importance in this time of proliferating reviews of uncertain value [ 130 ]. If these issues are not prospectively contemplated, systematic review authors may establish an overly broad scope, or develop runaway scope allowing them to stray from predefined choices relating to key comparisons and outcomes.

Once a research question is established, searching on registry sites and databases for existing systematic reviews addressing the same or a similar topic is necessary in order to avoid contributing to research waste [ 131 ]. Repeating an existing systematic review must be justified, for example, if previous reviews are out of date or methodologically flawed. A full discussion on replication of intervention systematic reviews, including a consensus checklist, can be found in the work of Tugwell and colleagues [ 84 ].

Protocol development is considered a core component of systematic reviews [ 125 , 126 , 132 ]. Review protocols may allow researchers to plan and anticipate potential issues, assess validity of methods, prevent arbitrary decision-making, and minimize bias that can be introduced by the conduct of the review. Registration of a protocol that allows public access promotes transparency of the systematic review’s methods and processes and reduces the potential for duplication [ 132 ]. Thinking early and carefully about all the steps of a systematic review is pragmatic and logical and may mitigate the influence of the authors’ prior knowledge of the evidence [ 133 ]. In addition, the protocol stage is when the scope of the review can be carefully considered by authors, reviewers, and editors; this may help to avoid production of overly ambitious reviews that include excessive numbers of comparisons and outcomes or are undisciplined in their study selection.

An association with attainment of AMSTAR standards in systematic reviews with published prospective protocols has been reported [ 134 ]. However, completeness of reporting does not seem to be different in reviews with a protocol compared to those without one [ 135 ]. PRISMA-P [ 116 ] and its accompanying elaboration and explanation document [ 136 ] can be used to guide and assess the reporting of protocols. A final version of the review should fully describe any protocol deviations. Peer reviewers may compare the submitted manuscript with any available pre-registered protocol; this is required if AMSTAR-2 or ROBIS are used for critical appraisal.

There are multiple options for the recording of protocols (Table 4.3 ). Some journals will peer review and publish protocols. In addition, many online sites offer date-stamped and publicly accessible protocol registration. Some of these are exclusively for protocols of evidence syntheses; others are less restrictive and offer researchers the capacity for data storage, sharing, and other workflow features. These sites document protocol details to varying extents and have different requirements [ 137 ]. The most popular site for systematic reviews, the International Prospective Register of Systematic Reviews (PROSPERO), for example, only registers reviews that report on an outcome with direct relevance to human health. The PROSPERO record documents protocols for all types of reviews except literature and scoping reviews. Of note, PROSPERO requires authors register their review protocols prior to any data extraction [ 133 , 138 ]. The electronic records of most of these registry sites allow authors to update their protocols and facilitate transparent tracking of protocol changes, which are not unexpected during the progress of the review [ 139 ].

Study design inclusion

For most systematic reviews, broad inclusion of study designs is recommended [ 126 ]. This may allow comparison of results between contrasting study design types [ 126 ]. Certain study designs may be considered preferable depending on the type of review and nature of the research question. However, prevailing stereotypes about what each study design does best may not be accurate. For example, in systematic reviews of interventions, randomized designs are typically thought to answer highly specific questions while non-randomized designs often are expected to reveal greater information about harms or real-word evidence [ 126 , 140 , 141 ]. This may be a false distinction; randomized trials may be pragmatic [ 142 ], they may offer important (and more unbiased) information on harms [ 143 ], and data from non-randomized trials may not necessarily be more real-world-oriented [ 144 ].

Moreover, there may not be any available evidence reported by RCTs for certain research questions; in some cases, there may not be any RCTs or NRSI. When the available evidence is limited to case reports and case series, it is not possible to test hypotheses nor provide descriptive estimates or associations; however, a systematic review of these studies can still offer important insights [ 81 , 145 ]. When authors anticipate that limited evidence of any kind may be available to inform their research questions, a scoping review can be considered. Alternatively, decisions regarding inclusion of indirect as opposed to direct evidence can be addressed during protocol development [ 146 ]. Including indirect evidence at an early stage of intervention systematic review development allows authors to decide if such studies offer any additional and/or different understanding of treatment effects for their population or comparison of interest. Issues of indirectness of included studies are accounted for later in the process, during determination of the overall certainty of evidence (see Part 5 for details).

Evidence search

Both AMSTAR-2 and ROBIS require systematic and comprehensive searches for evidence. This is essential for any systematic review. Both tools discourage search restrictions based on language and publication source. Given increasing globalism in health care, the practice of including English-only literature should be avoided [ 126 ]. There are many examples in which language bias (different results in studies published in different languages) has been documented [ 147 , 148 ]. This does not mean that all literature, in all languages, is equally trustworthy [ 148 ]; however, the only way to formally probe for the potential of such biases is to consider all languages in the initial search. The gray literature and a search of trials may also reveal important details about topics that would otherwise be missed [ 149 , 150 , 151 ]. Again, inclusiveness will allow review authors to investigate whether results differ in gray literature and trials [ 41 , 151 , 152 , 153 ].

Authors should make every attempt to complete their review within one year as that is the likely viable life of a search. (1) If that is not possible, the search should be updated close to the time of completion [ 154 ]. Different research topics may warrant less of a delay, for example, in rapidly changing fields (as in the case of the COVID-19 pandemic), even one month may radically change the available evidence.

Excluded studies

AMSTAR-2 requires authors to provide references for any studies excluded at the full text phase of study selection along with reasons for exclusion; this allows readers to feel confident that all relevant literature has been considered for inclusion and that exclusions are defensible.

Risk of bias assessment of included studies

The design of the studies included in a systematic review (eg, RCT, cohort, case series) should not be equated with appraisal of its RoB. To meet AMSTAR-2 and ROBIS standards, systematic review authors must examine RoB issues specific to the design of each primary study they include as evidence. It is unlikely that a single RoB appraisal tool will be suitable for all research designs. In addition to tools for randomized and non-randomized studies, specific tools are available for evaluation of RoB in case reports and case series [ 82 ] and single-case experimental designs [ 155 , 156 ]. Note the RoB tools selected must meet the standards of the appraisal tool used to judge the conduct of the review. For example, AMSTAR-2 identifies four sources of bias specific to RCTs and NRSI that must be addressed by the RoB tool(s) chosen by the review authors. The Cochrane RoB-2 [ 157 ] tool for RCTs and ROBINS-I [ 158 ] for NRSI for RoB assessment meet the AMSTAR-2 standards. Appraisers on the review team should not modify any RoB tool without complete transparency and acknowledgment that they have invalidated the interpretation of the tool as intended by its developers [ 159 ]. Conduct of RoB assessments is not addressed AMSTAR-2; to meet ROBIS standards, two independent reviewers should complete RoB assessments of included primary studies.

Implications of the RoB assessments must be explicitly discussed and considered in the conclusions of the review. Discussion of the overall RoB of included studies may consider the weight of the studies at high RoB, the importance of the sources of bias in the studies being summarized, and if their importance differs in relationship to the outcomes reported. If a meta-analysis is performed, serious concerns for RoB of individual studies should be accounted for in these results as well. If the results of the meta-analysis for a specific outcome change when studies at high RoB are excluded, readers will have a more accurate understanding of this body of evidence. However, while investigating the potential impact of specific biases is a useful exercise, it is important to avoid over-interpretation, especially when there are sparse data.

Synthesis methods for quantitative data

Syntheses of quantitative data reported by primary studies are broadly categorized as one of two types: meta-analysis, and synthesis without meta-analysis (Table 4.4 ). Before deciding on one of these methods, authors should seek methodological advice about whether reported data can be transformed or used in other ways to provide a consistent effect measure across studies [ 160 , 161 ].

Meta-analysis

Systematic reviews that employ meta-analysis should not be referred to simply as “meta-analyses.” The term meta-analysis strictly refers to a specific statistical technique used when study effect estimates and their variances are available, yielding a quantitative summary of results. In general, methods for meta-analysis involve use of a weighted average of effect estimates from two or more studies. If considered carefully, meta-analysis increases the precision of the estimated magnitude of effect and can offer useful insights about heterogeneity and estimates of effects. We refer to standard references for a thorough introduction and formal training [ 165 , 166 , 167 ].

There are three common approaches to meta-analysis in current health care–related systematic reviews (Table 4.4 ). Aggregate meta-analyses is the most familiar to authors of evidence syntheses and their end users. This standard meta-analysis combines data on effect estimates reported by studies that investigate similar research questions involving direct comparisons of an intervention and comparator. Results of these analyses provide a single summary intervention effect estimate. If the included studies in a systematic review measure an outcome differently, their reported results may be transformed to make them comparable [ 161 ]. Forest plots visually present essential information about the individual studies and the overall pooled analysis (see Additional File 4  for details).

Less familiar and more challenging meta-analytical approaches used in secondary research include individual participant data (IPD) and network meta-analyses (NMA); PRISMA extensions provide reporting guidelines for both [ 117 , 118 ]. In IPD, the raw data on each participant from each eligible study are re-analyzed as opposed to the study-level data analyzed in aggregate data meta-analyses [ 168 ]. This may offer advantages, including the potential for limiting concerns about bias and allowing more robust analyses [ 163 ]. As suggested by the description in Table 4.4 , NMA is a complex statistical approach. It combines aggregate data [ 169 ] or IPD [ 170 ] for effect estimates from direct and indirect comparisons reported in two or more studies of three or more interventions. This makes it a potentially powerful statistical tool; while multiple interventions are typically available to treat a condition, few have been evaluated in head-to-head trials [ 171 ]. Both IPD and NMA facilitate a broader scope, and potentially provide more reliable and/or detailed results; however, compared with standard aggregate data meta-analyses, their methods are more complicated, time-consuming, and resource-intensive, and they have their own biases, so one needs sufficient funding, technical expertise, and preparation to employ them successfully [ 41 , 172 , 173 ].

Several items in AMSTAR-2 and ROBIS address meta-analysis; thus, understanding the strengths, weaknesses, assumptions, and limitations of methods for meta-analyses is important. According to the standards of both tools, plans for a meta-analysis must be addressed in the review protocol, including reasoning, description of the type of quantitative data to be synthesized, and the methods planned for combining the data. This should not consist of stock statements describing conventional meta-analysis techniques; rather, authors are expected to anticipate issues specific to their research questions. Concern for the lack of training in meta-analysis methods among systematic review authors cannot be overstated. For those with training, the use of popular software (eg, RevMan [ 174 ], MetaXL [ 175 ], JBI SUMARI [ 176 ]) may facilitate exploration of these methods; however, such programs cannot substitute for the accurate interpretation of the results of meta-analyses, especially for more complex meta-analytical approaches.

Synthesis without meta-analysis

There are varied reasons a meta-analysis may not be appropriate or desirable [ 160 , 161 ]. Syntheses that informally use statistical methods other than meta-analysis are variably referred to as descriptive, narrative, or qualitative syntheses or summaries; these terms are also applied to syntheses that make no attempt to statistically combine data from individual studies. However, use of such imprecise terminology is discouraged; in order to fully explore the results of any type of synthesis, some narration or description is needed to supplement the data visually presented in tabular or graphic forms [ 63 , 177 ]. In addition, the term “qualitative synthesis” is easily confused with a synthesis of qualitative data in a qualitative or mixed methods review. “Synthesis without meta-analysis” is currently the preferred description of other ways to combine quantitative data from two or more studies. Use of this specific terminology when referring to these types of syntheses also implies the application of formal methods (Table 4.4 ).

Methods for syntheses without meta-analysis involve structured presentations of the data in any tables and plots. In comparison to narrative descriptions of each study, these are designed to more effectively and transparently show patterns and convey detailed information about the data; they also allow informal exploration of heterogeneity [ 178 ]. In addition, acceptable quantitative statistical methods (Table 4.4 ) are formally applied; however, it is important to recognize these methods have significant limitations for the interpretation of the effectiveness of an intervention [ 160 ]. Nevertheless, when meta-analysis is not possible, the application of these methods is less prone to bias compared with an unstructured narrative description of included studies [ 178 , 179 ].

Vote counting is commonly used in systematic reviews and involves a tally of studies reporting results that meet some threshold of importance applied by review authors. Until recently, it has not typically been identified as a method for synthesis without meta-analysis. Guidance on an acceptable vote counting method based on direction of effect is currently available [ 160 ] and should be used instead of narrative descriptions of such results (eg, “more than half the studies showed improvement”; “only a few studies reported adverse effects”; “7 out of 10 studies favored the intervention”). Unacceptable methods include vote counting by statistical significance or magnitude of effect or some subjective rule applied by the authors.

AMSTAR-2 and ROBIS standards do not explicitly address conduct of syntheses without meta-analysis, although AMSTAR-2 items 13 and 14 might be considered relevant. Guidance for the complete reporting of syntheses without meta-analysis for systematic reviews of interventions is available in the Synthesis without Meta-analysis (SWiM) guideline [ 180 ] and methodological guidance is available in the Cochrane Handbook [ 160 , 181 ].

Familiarity with AMSTAR-2 and ROBIS makes sense for authors of systematic reviews as these appraisal tools will be used to judge their work; however, training is necessary for authors to truly appreciate and apply methodological rigor. Moreover, judgment of the potential contribution of a systematic review to the current knowledge base goes beyond meeting the standards of AMSTAR-2 and ROBIS. These tools do not explicitly address some crucial concepts involved in the development of a systematic review; this further emphasizes the need for author training.

We recommend that systematic review authors incorporate specific practices or exercises when formulating a research question at the protocol stage, These should be designed to raise the review team’s awareness of how to prevent research and resource waste [ 84 , 130 ] and to stimulate careful contemplation of the scope of the review [ 30 ]. Authors’ training should also focus on justifiably choosing a formal method for the synthesis of quantitative and/or qualitative data from primary research; both types of data require specific expertise. For typical reviews that involve syntheses of quantitative data, statistical expertise is necessary, initially for decisions about appropriate methods, [ 160 , 161 ] and then to inform any meta-analyses [ 167 ] or other statistical methods applied [ 160 ].

Part 5. Rating overall certainty of evidence

Report of an overall certainty of evidence assessment in a systematic review is an important new reporting standard of the updated PRISMA 2020 guidelines [ 93 ]. Systematic review authors are well acquainted with assessing RoB in individual primary studies, but much less familiar with assessment of overall certainty across an entire body of evidence. Yet a reliable way to evaluate this broader concept is now recognized as a vital part of interpreting the evidence.

Historical systems for rating evidence are based on study design and usually involve hierarchical levels or classes of evidence that use numbers and/or letters to designate the level/class. These systems were endorsed by various EBM-related organizations. Professional societies and regulatory groups then widely adopted them, often with modifications for application to the available primary research base in specific clinical areas. In 2002, a report issued by the AHRQ identified 40 systems to rate quality of a body of evidence [ 182 ]. A critical appraisal of systems used by prominent health care organizations published in 2004 revealed limitations in sensibility, reproducibility, applicability to different questions, and usability to different end users [ 183 ]. Persistent use of hierarchical rating schemes to describe overall quality continues to complicate the interpretation of evidence. This is indicated by recent reports of poor interpretability of systematic review results by readers [ 184 , 185 , 186 ] and misleading interpretations of the evidence related to the “spin” systematic review authors may put on their conclusions [ 50 , 187 ].

Recognition of the shortcomings of hierarchical rating systems raised concerns that misleading clinical recommendations could result even if based on a rigorous systematic review. In addition, the number and variability of these systems were considered obstacles to quick and accurate interpretations of the evidence by clinicians, patients, and policymakers [ 183 ]. These issues contributed to the development of the GRADE approach. An international working group, that continues to actively evaluate and refine it, first introduced GRADE in 2004 [ 188 ]. Currently more than 110 organizations from 19 countries around the world have endorsed or are using GRADE [ 189 ].

GRADE approach to rating overall certainty

GRADE offers a consistent and sensible approach for two separate processes: rating the overall certainty of a body of evidence and the strength of recommendations. The former is the expected conclusion of a systematic review, while the latter is pertinent to the development of CPGs. As such, GRADE provides a mechanism to bridge the gap from evidence synthesis to application of the evidence for informed clinical decision-making [ 27 , 190 ]. We briefly examine the GRADE approach but only as it applies to rating overall certainty of evidence in systematic reviews.

In GRADE, use of “certainty” of a body of evidence is preferred over the term “quality.” [ 191 ] Certainty refers to the level of confidence systematic review authors have that, for each outcome, an effect estimate represents the true effect. The GRADE approach to rating confidence in estimates begins with identifying the study type (RCT or NRSI) and then systematically considers criteria to rate the certainty of evidence up or down (Table 5.1 ).

This process results in assignment of one of the four GRADE certainty ratings to each outcome; these are clearly conveyed with the use of basic interpretation symbols (Table 5.2 ) [ 192 ]. Notably, when multiple outcomes are reported in a systematic review, each outcome is assigned a unique certainty rating; thus different levels of certainty may exist in the body of evidence being examined.

GRADE’s developers acknowledge some subjectivity is involved in this process [ 193 ]. In addition, they emphasize that both the criteria for rating evidence up and down (Table 5.1 ) as well as the four overall certainty ratings (Table 5.2 ) reflect a continuum as opposed to discrete categories [ 194 ]. Consequently, deciding whether a study falls above or below the threshold for rating up or down may not be straightforward, and preliminary overall certainty ratings may be intermediate (eg, between low and moderate). Thus, the proper application of GRADE requires systematic review authors to take an overall view of the body of evidence and explicitly describe the rationale for their final ratings.

Advantages of GRADE

Outcomes important to the individuals who experience the problem of interest maintain a prominent role throughout the GRADE process [ 191 ]. These outcomes must inform the research questions (eg, PICO [population, intervention, comparator, outcome]) that are specified a priori in a systematic review protocol. Evidence for these outcomes is then investigated and each critical or important outcome is ultimately assigned a certainty of evidence as the end point of the review. Notably, limitations of the included studies have an impact at the outcome level. Ultimately, the certainty ratings for each outcome reported in a systematic review are considered by guideline panels. They use a different process to formulate recommendations that involves assessment of the evidence across outcomes [ 201 ]. It is beyond our scope to describe the GRADE process for formulating recommendations; however, it is critical to understand how these two outcome-centric concepts of certainty of evidence in the GRADE framework are related and distinguished. An in-depth illustration using examples from recently published evidence syntheses and CPGs is provided in Additional File 5 A (Table AF5A-1).

The GRADE approach is applicable irrespective of whether the certainty of the primary research evidence is high or very low; in some circumstances, indirect evidence of higher certainty may be considered if direct evidence is unavailable or of low certainty [ 27 ]. In fact, most interventions and outcomes in medicine have low or very low certainty of evidence based on GRADE and there seems to be no major improvement over time [ 202 , 203 ]. This is still a very important (even if sobering) realization for calibrating our understanding of medical evidence. A major appeal of the GRADE approach is that it offers a common framework that enables authors of evidence syntheses to make complex judgments about evidence certainty and to convey these with unambiguous terminology. This prevents some common mistakes made by review authors, including overstating results (or under-reporting harms) [ 187 ] and making recommendations for treatment. This is illustrated in Table AF5A-2 (Additional File 5 A), which compares the concluding statements made about overall certainty in a systematic review with and without application of the GRADE approach.

Theoretically, application of GRADE should improve consistency of judgments about certainty of evidence, both between authors and across systematic reviews. In one empirical evaluation conducted by the GRADE Working Group, interrater reliability of two individual raters assessing certainty of the evidence for a specific outcome increased from ~ 0.3 without using GRADE to ~ 0.7 by using GRADE [ 204 ]. However, others report variable agreement among those experienced in GRADE assessments of evidence certainty [ 190 ]. Like any other tool, GRADE requires training in order to be properly applied. The intricacies of the GRADE approach and the necessary subjectivity involved suggest that improving agreement may require strict rules for its application; alternatively, use of general guidance and consensus among review authors may result in less consistency but provide important information for the end user [ 190 ].

GRADE caveats

Simply invoking “the GRADE approach” does not automatically ensure GRADE methods were employed by authors of a systematic review (or developers of a CPG). Table 5.3 lists the criteria the GRADE working group has established for this purpose. These criteria highlight the specific terminology and methods that apply to rating the certainty of evidence for outcomes reported in a systematic review [ 191 ], which is different from rating overall certainty across outcomes considered in the formulation of recommendations [ 205 ]. Modifications of standard GRADE methods and terminology are discouraged as these may detract from GRADE’s objectives to minimize conceptual confusion and maximize clear communication [ 206 ].

Nevertheless, GRADE is prone to misapplications [ 207 , 208 ], which can distort a systematic review’s conclusions about the certainty of evidence. Systematic review authors without proper GRADE training are likely to misinterpret the terms “quality” and “grade” and to misunderstand the constructs assessed by GRADE versus other appraisal tools. For example, review authors may reference the standard GRADE certainty ratings (Table 5.2 ) to describe evidence for their outcome(s) of interest. However, these ratings are invalidated if authors omit or inadequately perform RoB evaluations of each included primary study. Such deficiencies in RoB assessments are unacceptable but not uncommon, as reported in methodological studies of systematic reviews and overviews [ 104 , 186 , 209 , 210 ]. GRADE ratings are also invalidated if review authors do not formally address and report on the other criteria (Table 5.1 ) necessary for a GRADE certainty rating.

Other caveats pertain to application of a GRADE certainty of evidence rating in various types of evidence syntheses. Current adaptations of GRADE are described in Additional File 5 B and included on Table 6.3 , which is introduced in the next section.

The expected culmination of a systematic review should be a rating of overall certainty of a body of evidence for each outcome reported. The GRADE approach is recommended for making these judgments for outcomes reported in systematic reviews of interventions and can be adapted for other types of reviews. This represents the initial step in the process of making recommendations based on evidence syntheses. Peer reviewers should ensure authors meet the minimal criteria for supporting the GRADE approach when reviewing any evidence synthesis that reports certainty ratings derived using GRADE. Authors and peer reviewers of evidence syntheses unfamiliar with GRADE are encouraged to seek formal training and take advantage of the resources available on the GRADE website [ 211 , 212 ].

Part 6. Concise Guide to best practices

Accumulating data in recent years suggest that many evidence syntheses (with or without meta-analysis) are not reliable. This relates in part to the fact that their authors, who are often clinicians, can be overwhelmed by the plethora of ways to evaluate evidence. They tend to resort to familiar but often inadequate, inappropriate, or obsolete methods and tools and, as a result, produce unreliable reviews. These manuscripts may not be recognized as such by peer reviewers and journal editors who may disregard current standards. When such a systematic review is published or included in a CPG, clinicians and stakeholders tend to believe that it is trustworthy. A vicious cycle in which inadequate methodology is rewarded and potentially misleading conclusions are accepted is thus supported. There is no quick or easy way to break this cycle; however, increasing awareness of best practices among all these stakeholder groups, who often have minimal (if any) training in methodology, may begin to mitigate it. This is the rationale for inclusion of Parts 2 through 5 in this guidance document. These sections present core concepts and important methodological developments that inform current standards and recommendations. We conclude by taking a direct and practical approach.

Inconsistent and imprecise terminology used in the context of development and evaluation of evidence syntheses is problematic for authors, peer reviewers and editors, and may lead to the application of inappropriate methods and tools. In response, we endorse use of the basic terms (Table 6.1 ) defined in the PRISMA 2020 statement [ 93 ]. In addition, we have identified several problematic expressions and nomenclature. In Table 6.2 , we compile suggestions for preferred terms less likely to be misinterpreted.

We also propose a Concise Guide (Table 6.3 ) that summarizes the methods and tools recommended for the development and evaluation of nine types of evidence syntheses. Suggestions for specific tools are based on the rigor of their development as well as the availability of detailed guidance from their developers to ensure their proper application. The formatting of the Concise Guide addresses a well-known source of confusion by clearly distinguishing the underlying methodological constructs that these tools were designed to assess. Important clarifications and explanations follow in the guide’s footnotes; associated websites, if available, are listed in Additional File 6 .

To encourage uptake of best practices, journal editors may consider adopting or adapting the Concise Guide in their instructions to authors and peer reviewers of evidence syntheses. Given the evolving nature of evidence synthesis methodology, the suggested methods and tools are likely to require regular updates. Authors of evidence syntheses should monitor the literature to ensure they are employing current methods and tools. Some types of evidence syntheses (eg, rapid, economic, methodological) are not included in the Concise Guide; for these, authors are advised to obtain recommendations for acceptable methods by consulting with their target journal.

We encourage the appropriate and informed use of the methods and tools discussed throughout this commentary and summarized in the Concise Guide (Table 6.3 ). However, we caution against their application in a perfunctory or superficial fashion. This is a common pitfall among authors of evidence syntheses, especially as the standards of such tools become associated with acceptance of a manuscript by a journal. Consequently, published evidence syntheses may show improved adherence to the requirements of these tools without necessarily making genuine improvements in their performance.

In line with our main objective, the suggested tools in the Concise Guide address the reliability of evidence syntheses; however, we recognize that the utility of systematic reviews is an equally important concern. An unbiased and thoroughly reported evidence synthesis may still not be highly informative if the evidence itself that is summarized is sparse, weak and/or biased [ 24 ]. Many intervention systematic reviews, including those developed by Cochrane [ 203 ] and those applying GRADE [ 202 ], ultimately find no evidence, or find the evidence to be inconclusive (eg, “weak,” “mixed,” or of “low certainty”). This often reflects the primary research base; however, it is important to know what is known (or not known) about a topic when considering an intervention for patients and discussing treatment options with them.

Alternatively, the frequency of “empty” and inconclusive reviews published in the medical literature may relate to limitations of conventional methods that focus on hypothesis testing; these have emphasized the importance of statistical significance in primary research and effect sizes from aggregate meta-analyses [ 183 ]. It is becoming increasingly apparent that this approach may not be appropriate for all topics [ 130 ]. Development of the GRADE approach has facilitated a better understanding of significant factors (beyond effect size) that contribute to the overall certainty of evidence. Other notable responses include the development of integrative synthesis methods for the evaluation of complex interventions [ 230 , 231 ], the incorporation of crowdsourcing and machine learning into systematic review workflows (eg the Cochrane Evidence Pipeline) [ 2 ], the shift in paradigm to living systemic review and NMA platforms [ 232 , 233 ] and the proposal of a new evidence ecosystem that fosters bidirectional collaborations and interactions among a global network of evidence synthesis stakeholders [ 234 ]. These evolutions in data sources and methods may ultimately make evidence syntheses more streamlined, less duplicative, and more importantly, they may be more useful for timely policy and clinical decision-making; however, that will only be the case if they are rigorously reported and conducted.

We look forward to others’ ideas and proposals for the advancement of methods for evidence syntheses. For now, we encourage dissemination and uptake of the currently accepted best tools and practices for their development and evaluation; at the same time, we stress that uptake of appraisal tools, checklists, and software programs cannot substitute for proper education in the methodology of evidence syntheses and meta-analysis. Authors, peer reviewers, and editors must strive to make accurate and reliable contributions to the present evidence knowledge base; online alerts, upcoming technology, and accessible education may make this more feasible than ever before. Our intention is to improve the trustworthiness of evidence syntheses across disciplines, topics, and types of evidence syntheses. All of us must continue to study, teach, and act cooperatively for that to happen.

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Acknowledgements

Michelle Oakman Hayes for her assistance with the graphics, Mike Clarke for his willingness to answer our seemingly arbitrary questions, and Bernard Dan for his encouragement of this project.

The work of John Ioannidis has been supported by an unrestricted gift from Sue and Bob O’Donnell to Stanford University.

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Kat Kolaski

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Lynne Romeiser Logan

Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, and Meta-Research Innovation Center at Stanford (METRICS), Stanford University School of Medicine, Stanford, CA, USA

John P. A. Ioannidis

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This article has been published simultaneously in BMC Systematic Reviews, Acta Anaesthesiologica Scandinavica, BMC Infectious Diseases, British Journal of Pharmacology, JBI Evidence Synthesis, the Journal of Bone and Joint Surgery Reviews , and the Journal of Pediatric Rehabilitation Medicine .

Supplementary Information

Additional file 2a..

Overviews, scoping reviews, rapid reviews and living reviews.

Additional file 2B.

Practical scheme for distinguishing types of research evidence.

Additional file 4.

Presentation of forest plots.

Additional file 5A.

Illustrations of the GRADE approach.

Additional file 5B.

 Adaptations of GRADE for evidence syntheses.

Additional file 6.

 Links to Concise Guide online resources.

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Kolaski, K., Logan, L.R. & Ioannidis, J.P.A. Guidance to best tools and practices for systematic reviews. Syst Rev 12 , 96 (2023). https://doi.org/10.1186/s13643-023-02255-9

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Writing a Literature Review

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A literature review is a document or section of a document that collects key sources on a topic and discusses those sources in conversation with each other (also called synthesis ). The lit review is an important genre in many disciplines, not just literature (i.e., the study of works of literature such as novels and plays). When we say “literature review” or refer to “the literature,” we are talking about the research ( scholarship ) in a given field. You will often see the terms “the research,” “the scholarship,” and “the literature” used mostly interchangeably.

Where, when, and why would I write a lit review?

There are a number of different situations where you might write a literature review, each with slightly different expectations; different disciplines, too, have field-specific expectations for what a literature review is and does. For instance, in the humanities, authors might include more overt argumentation and interpretation of source material in their literature reviews, whereas in the sciences, authors are more likely to report study designs and results in their literature reviews; these differences reflect these disciplines’ purposes and conventions in scholarship. You should always look at examples from your own discipline and talk to professors or mentors in your field to be sure you understand your discipline’s conventions, for literature reviews as well as for any other genre.

A literature review can be a part of a research paper or scholarly article, usually falling after the introduction and before the research methods sections. In these cases, the lit review just needs to cover scholarship that is important to the issue you are writing about; sometimes it will also cover key sources that informed your research methodology.

Lit reviews can also be standalone pieces, either as assignments in a class or as publications. In a class, a lit review may be assigned to help students familiarize themselves with a topic and with scholarship in their field, get an idea of the other researchers working on the topic they’re interested in, find gaps in existing research in order to propose new projects, and/or develop a theoretical framework and methodology for later research. As a publication, a lit review usually is meant to help make other scholars’ lives easier by collecting and summarizing, synthesizing, and analyzing existing research on a topic. This can be especially helpful for students or scholars getting into a new research area, or for directing an entire community of scholars toward questions that have not yet been answered.

What are the parts of a lit review?

Most lit reviews use a basic introduction-body-conclusion structure; if your lit review is part of a larger paper, the introduction and conclusion pieces may be just a few sentences while you focus most of your attention on the body. If your lit review is a standalone piece, the introduction and conclusion take up more space and give you a place to discuss your goals, research methods, and conclusions separately from where you discuss the literature itself.

Introduction:

• An introductory paragraph that explains what your working topic and thesis is
• A forecast of key topics or texts that will appear in the review
• Potentially, a description of how you found sources and how you analyzed them for inclusion and discussion in the review (more often found in published, standalone literature reviews than in lit review sections in an article or research paper)
• Summarize and synthesize: Give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: Don’t just paraphrase other researchers – add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically Evaluate: Mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: Use transition words and topic sentence to draw connections, comparisons, and contrasts.

Conclusion:

• Summarize the key findings you have taken from the literature and emphasize their significance
• Connect it back to your primary research question

How should I organize my lit review?

Lit reviews can take many different organizational patterns depending on what you are trying to accomplish with the review. Here are some examples:

• Chronological : The simplest approach is to trace the development of the topic over time, which helps familiarize the audience with the topic (for instance if you are introducing something that is not commonly known in your field). If you choose this strategy, be careful to avoid simply listing and summarizing sources in order. Try to analyze the patterns, turning points, and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred (as mentioned previously, this may not be appropriate in your discipline — check with a teacher or mentor if you’re unsure).
• Thematic : If you have found some recurring central themes that you will continue working with throughout your piece, you can organize your literature review into subsections that address different aspects of the topic. For example, if you are reviewing literature about women and religion, key themes can include the role of women in churches and the religious attitude towards women.
• Qualitative versus quantitative research
• Empirical versus theoretical scholarship
• Divide the research by sociological, historical, or cultural sources
• Theoretical : In many humanities articles, the literature review is the foundation for the theoretical framework. You can use it to discuss various theories, models, and definitions of key concepts. You can argue for the relevance of a specific theoretical approach or combine various theorical concepts to create a framework for your research.

What are some strategies or tips I can use while writing my lit review?

Any lit review is only as good as the research it discusses; make sure your sources are well-chosen and your research is thorough. Don’t be afraid to do more research if you discover a new thread as you’re writing. More info on the research process is available in our "Conducting Research" resources .

As you’re doing your research, create an annotated bibliography ( see our page on the this type of document ). Much of the information used in an annotated bibliography can be used also in a literature review, so you’ll be not only partially drafting your lit review as you research, but also developing your sense of the larger conversation going on among scholars, professionals, and any other stakeholders in your topic.

Usually you will need to synthesize research rather than just summarizing it. This means drawing connections between sources to create a picture of the scholarly conversation on a topic over time. Many student writers struggle to synthesize because they feel they don’t have anything to add to the scholars they are citing; here are some strategies to help you:

• It often helps to remember that the point of these kinds of syntheses is to show your readers how you understand your research, to help them read the rest of your paper.
• Writing teachers often say synthesis is like hosting a dinner party: imagine all your sources are together in a room, discussing your topic. What are they saying to each other?
• Look at the in-text citations in each paragraph. Are you citing just one source for each paragraph? This usually indicates summary only. When you have multiple sources cited in a paragraph, you are more likely to be synthesizing them (not always, but often
• Read more about synthesis here.

The most interesting literature reviews are often written as arguments (again, as mentioned at the beginning of the page, this is discipline-specific and doesn’t work for all situations). Often, the literature review is where you can establish your research as filling a particular gap or as relevant in a particular way. You have some chance to do this in your introduction in an article, but the literature review section gives a more extended opportunity to establish the conversation in the way you would like your readers to see it. You can choose the intellectual lineage you would like to be part of and whose definitions matter most to your thinking (mostly humanities-specific, but this goes for sciences as well). In addressing these points, you argue for your place in the conversation, which tends to make the lit review more compelling than a simple reporting of other sources.