Conducting a Literature Review

  • Literature Review
  • Developing a Topic
  • Planning Your Literature Review
  • Developing a Search Strategy
  • Managing Citations
  • Critical Appraisal Tools
  • Writing a Literature Review

Appraise Your Research Articles

The structure of a literature review should include the following :

  • An overview of the subject, issue, or theory under consideration, along with the objectives of the literature review,
  • Division of works under review into themes or categories [e.g. works that support a particular position, those against, and those offering alternative approaches entirely],
  • An explanation of how each work is similar to and how it varies from the others,
  • Conclusions as to which pieces are best considered in their argument, are most convincing of their opinions, and make the greatest contribution to the understanding and development of their area of research.

The critical evaluation of each work should consider :

  • Provenance  -- what are the author's credentials? Are the author's arguments supported by evidence [e.g. primary historical material, case studies, narratives, statistics, recent scientific findings]?
  • Methodology  -- were the techniques used to identify, gather, and analyze the data appropriate to addressing the research problem? Was the sample size appropriate? Were the results effectively interpreted and reported?
  • Objectivity  -- is the author's perspective even-handed or prejudicial? Is contrary data considered or is certain pertinent information ignored to prove the author's point?
  • Persuasiveness  -- which of the author's theses are most convincing or least convincing?
  • Value  -- are the author's arguments and conclusions convincing? Does the work ultimately contribute in any significant way to an understanding of the subject?

Reviewing the Literature

While conducting a review of the literature, maximize the time you devote to writing this part of your paper by thinking broadly about what you should be looking for and evaluating. Review not just what the articles are saying, but how are they saying it.

Some questions to ask:

  • How are they organizing their ideas?
  • What methods have they used to study the problem?
  • What theories have been used to explain, predict, or understand their research problem?
  • What sources have they cited to support their conclusions?
  • How have they used non-textual elements [e.g., charts, graphs, figures, etc.] to illustrate key points?
  • When you begin to write your literature review section, you'll be glad you dug deeper into how the research was designed and constructed because it establishes a means for developing more substantial analysis and interpretation of the research problem.

Tools for Critical Appraisal

Now, that you have found articles based on your research question you can appraise the quality of those articles. These are resources you can use to appraise different study designs.

Centre for Evidence Based Medicine (Oxford)

University of Glasgow

"AFP uses the Strength-of-Recommendation Taxonomy (SORT), to label key recommendations in clinical review articles."

  • SORT: Rating the Strength of Evidence    American Family Physician and other family medicine journals use the Strength of Recommendation Taxonomy (SORT) system for rating bodies of evidence for key clinical recommendations.

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About Systematic Reviews

Choosing the Best Systematic Review Critical Appraisal Tool

critical appraisal tools literature reviews

Automate every stage of your literature review to produce evidence-based research faster and more accurately.

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 literature reviews

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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Systematic Reviews & Evidence Synthesis Methods

Critical appraisal.

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Some reviews require a critical appraisal for each study that makes it through the screening process. This involves a risk of bias assessment and/or a quality assessment. The goal of these reviews is not just to find all of the studies, but to determine their methodological rigor, and therefore, their credibility.

"Critical appraisal is the balanced assessment of a piece of research, looking for its strengths and weaknesses and them coming to a balanced judgement about its trustworthiness and its suitability for use in a particular context." 1

It's important to consider the impact that poorly designed studies could have on your findings and to rule out inaccurate or biased work.

Selection of a valid critical appraisal tool, testing the tool with several of the selected studies, and involving two or more reviewers in the appraisal are good practices to follow.

1. Purssell E, McCrae N. How to Perform a Systematic Literature Review: A Guide for Healthcare Researchers, Practitioners and Students. 1st ed. Springer ;  2020.

Evaluation Tools

  • The Appraisal of Guidelines for Research & Evaluation Instrument (AGREE II) The Appraisal of Guidelines for Research & Evaluation Instrument (AGREE II) was developed to address the issue of variability in the quality of practice guidelines.
  • Critical Appraisal Skills Programme (CASP) Checklists Critical Appraisal checklists for many different study types
  • Critical Review Form for Qualitative Studies Version 2, developed out of McMaster University
  • Development of a critical appraisal tool to assess the quality of cross-sectional studies (AXIS) Downes MJ, Brennan ML, Williams HC, et al. Development of a critical appraisal tool to assess the quality of cross-sectional studies (AXIS). BMJ Open 2016;6:e011458. doi:10.1136/bmjopen-2016-011458
  • Downs & Black Checklist for Assessing Studies Downs, S. H., & Black, N. (1998). The Feasibility of Creating a Checklist for the Assessment of the Methodological Quality Both of Randomised and Non-Randomised Studies of Health Care Interventions. Journal of Epidemiology and Community Health (1979-), 52(6), 377–384.
  • GRADE The Grading of Recommendations Assessment, Development and Evaluation (GRADE) working group "has developed a common, sensible and transparent approach to grading quality (or certainty) of evidence and strength of recommendations."
  • Grade Handbook Full handbook on the GRADE method for grading quality of evidence.
  • MAGIC (Making GRADE the Irresistible choice) Clear succinct guidance in how to use GRADE
  • Joanna Briggs Institute. Critical Appraisal Tools "JBI’s critical appraisal tools assist in assessing the trustworthiness, relevance and results of published papers." Includes checklists for 13 types of articles.
  • Latitudes Network This is a searchable library of validity assessment tools for use in evidence syntheses. This website also provides access to training on the process of validity assessment.
  • Mixed Methods Appraisal Tool A tool that can be used to appraise a mix of studies that are included in a systematic review - qualitative research, RCTs, non-randomized studies, quantitative studies, mixed methods studies.
  • RoB 2 Tool Higgins JPT, Sterne JAC, Savović J, Page MJ, Hróbjartsson A, Boutron I, Reeves B, Eldridge S. A revised tool for assessing risk of bias in randomized trials In: Chandler J, McKenzie J, Boutron I, Welch V (editors). Cochrane Methods. Cochrane Database of Systematic Reviews 2016, Issue 10 (Suppl 1). dx.doi.org/10.1002/14651858.CD201601.
  • ROBINS-I Risk of Bias for non-randomized (observational) studies or cohorts of interventions Sterne J A, Hernán M A, Reeves B C, Savović J, Berkman N D, Viswanathan M et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions BMJ 2016; 355 :i4919 doi:10.1136/bmj.i4919
  • Scottish Intercollegiate Guidelines Network. Critical Appraisal Notes and Checklists "Methodological assessment of studies selected as potential sources of evidence is based on a number of criteria that focus on those aspects of the study design that research has shown to have a significant effect on the risk of bias in the results reported and conclusions drawn. These criteria differ between study types, and a range of checklists is used to bring a degree of consistency to the assessment process."
  • The TREND Statement (CDC) Des Jarlais DC, Lyles C, Crepaz N, and the TREND Group. Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: The TREND statement. Am J Public Health. 2004;94:361-366.
  • Assembling the Pieces of a Systematic Reviews, Chapter 8: Evaluating: Study Selection and Critical Appraisal.
  • How to Perform a Systematic Literature Review, Chapter: Critical Appraisal: Assessing the Quality of Studies.

Other library guides

  • Duke University Medical Center Library. Systematic Reviews: Assess for Quality and Bias
  • UNC Health Sciences Library. Systematic Reviews: Assess Quality of Included Studies
  • Last Updated: Feb 27, 2024 12:53 PM
  • URL: https://guides.lib.utexas.edu/systematicreviews

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Nuffield Department of Primary Care Health Sciences, University of Oxford

Critical Appraisal tools

Critical appraisal worksheets to help you appraise the reliability, importance and applicability of clinical evidence.

Critical appraisal is the systematic evaluation of clinical research papers in order to establish:

  • Does this study address a  clearly focused question ?
  • Did the study use valid methods to address this question?
  • Are the valid results of this study important?
  • Are these valid, important results applicable to my patient or population?

If the answer to any of these questions is “no”, you can save yourself the trouble of reading the rest of it.

This section contains useful tools and downloads for the critical appraisal of different types of medical evidence. Example appraisal sheets are provided together with several helpful examples.

Critical Appraisal Worksheets

  • Systematic Reviews  Critical Appraisal Sheet
  • Diagnostics  Critical Appraisal Sheet
  • Prognosis  Critical Appraisal Sheet
  • Randomised Controlled Trials  (RCT) Critical Appraisal Sheet
  • Critical Appraisal of Qualitative Studies  Sheet
  • IPD Review  Sheet

Chinese - translated by Chung-Han Yang and Shih-Chieh Shao

  • Systematic Reviews  Critical Appraisal Sheet
  • Diagnostic Study  Critical Appraisal Sheet
  • Prognostic Critical Appraisal Sheet
  • RCT  Critical Appraisal Sheet
  • IPD reviews Critical Appraisal Sheet
  • Qualitative Studies Critical Appraisal Sheet 

German - translated by Johannes Pohl and Martin Sadilek

  • Systematic Review  Critical Appraisal Sheet
  • Diagnosis Critical Appraisal Sheet
  • Prognosis Critical Appraisal Sheet
  • Therapy / RCT Critical Appraisal Sheet

Lithuanian - translated by Tumas Beinortas

  • Systematic review appraisal Lithuanian (PDF)
  • Diagnostic accuracy appraisal Lithuanian  (PDF)
  • Prognostic study appraisal Lithuanian  (PDF)
  • RCT appraisal sheets Lithuanian  (PDF)

Portugese - translated by Enderson Miranda, Rachel Riera and Luis Eduardo Fontes

  • Portuguese – Systematic Review Study Appraisal Worksheet
  • Portuguese – Diagnostic Study Appraisal Worksheet
  • Portuguese – Prognostic Study Appraisal Worksheet
  • Portuguese – RCT Study Appraisal Worksheet
  • Portuguese – Systematic Review Evaluation of Individual Participant Data Worksheet
  • Portuguese – Qualitative Studies Evaluation Worksheet

Spanish - translated by Ana Cristina Castro

  • Systematic Review  (PDF)
  • Diagnosis  (PDF)
  • Prognosis  Spanish Translation (PDF)
  • Therapy / RCT  Spanish Translation (PDF)

Persian - translated by Ahmad Sofi Mahmudi

  • Prognosis  (PDF)
  • PICO  Critical Appraisal Sheet (PDF)
  • PICO Critical Appraisal Sheet (MS-Word)
  • Educational Prescription  Critical Appraisal Sheet (PDF)

Explanations & Examples

  • Pre-test probability
  • SpPin and SnNout
  • Likelihood Ratios

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Critical Appraisal

Use this guide to find information resources about critical appraisal including checklists, books and journal articles.

Key Resources

  • This online resource explains the sections commonly used in research articles. Understanding how research articles are organised can make reading and evaluating them easier View page
  • Critical appraisal checklists
  • Worksheets for appraising systematic reviews, diagnostics, prognostics and RCTs. View page
  • A free online resource for both healthcare staff and patients; four modules of 30–45 minutes provide an introduction to evidence based medicine, clinical trials and Cochrane Evidence. View page
  • This tool will guide you through a series of questions to help you to review and interpret a published health research paper. View page
  • The PRISMA flow diagram depicts the flow of information through the different phases of a literature review. It maps out the number of records identified, included and excluded, and the reasons for exclusions. View page
  • A useful resource for methods and evidence in applied social science. View page
  • A comprehensive database of reporting guidelines. Covers all the main study types. View page
  • A tool to assess the methodological quality of systematic reviews. View page

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  • Borrow from RCN Library services

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  • Chapter 5 covers critical appraisal of the literature. View this eBook

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  • Chapter 6 covers assessing the evidence base. Borrow from RCN Library services

Book cover

  • Section 1 covers an introduction to critical appraisal. Section 3 covers appraising difference types of papers including qualitative papers and observational studies. View this eBook

Book cover

  • Chapter 6 covers critically appraising the literature. Borrow from RCN Library services

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  • View this eBook

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  • Chapter 8 covers critical appraisal of the evidence. View this eBook

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  • Chapter 18 covers critical appraisal of nursing studies. View this eBook

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  • Borrow from RCN Library Services

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Book subject search

  • Critical appraisal

Journal articles

  • View article

Shea BJ and others (2017) AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions or both, British Medical Journal, 358.

  • An outline of AMSTAR 2 and its use for as a critical appraisal tool for systematic reviews. View article (open access)
  • View articles

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© 2024 Royal College of Nursing

  • 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.

figure 1

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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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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A systematic review of the content of critical appraisal tools

  • Persis Katrak 1 ,
  • Andrea E Bialocerkowski 2 ,
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  • VS Saravana Kumar 1 &
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Consumers of research (researchers, administrators, educators and clinicians) frequently use standard critical appraisal tools to evaluate the quality of published research reports. However, there is no consensus regarding the most appropriate critical appraisal tool for allied health research. We summarized the content, intent, construction and psychometric properties of published, currently available critical appraisal tools to identify common elements and their relevance to allied health research.

A systematic review was undertaken of 121 published critical appraisal tools sourced from 108 papers located on electronic databases and the Internet. The tools were classified according to the study design for which they were intended. Their items were then classified into one of 12 criteria based on their intent. Commonly occurring items were identified. The empirical basis for construction of the tool, the method by which overall quality of the study was established, the psychometric properties of the critical appraisal tools and whether guidelines were provided for their use were also recorded.

Eighty-seven percent of critical appraisal tools were specific to a research design, with most tools having been developed for experimental studies. There was considerable variability in items contained in the critical appraisal tools. Twelve percent of available tools were developed using specified empirical research. Forty-nine percent of the critical appraisal tools summarized the quality appraisal into a numeric summary score. Few critical appraisal tools had documented evidence of validity of their items, or reliability of use. Guidelines regarding administration of the tools were provided in 43% of cases.

Conclusions

There was considerable variability in intent, components, construction and psychometric properties of published critical appraisal tools for research reports. There is no "gold standard' critical appraisal tool for any study design, nor is there any widely accepted generic tool that can be applied equally well across study types. No tool was specific to allied health research requirements. Thus interpretation of critical appraisal of research reports currently needs to be considered in light of the properties and intent of the critical appraisal tool chosen for the task.

Peer Review reports

Consumers of research (clinicians, researchers, educators, administrators) frequently use standard critical appraisal tools to evaluate the quality and utility of published research reports [ 1 ]. Critical appraisal tools provide analytical evaluations of the quality of the study, in particular the methods applied to minimise biases in a research project [ 2 ]. As these factors potentially influence study results, and the way that the study findings are interpreted, this information is vital for consumers of research to ascertain whether the results of the study can be believed, and transferred appropriately into other environments, such as policy, further research studies, education or clinical practice. Hence, choosing an appropriate critical appraisal tool is an important component of evidence-based practice.

Although the importance of critical appraisal tools has been acknowledged [ 1 , 3 – 5 ] there appears to be no consensus regarding the 'gold standard' tool for any medical evidence. In addition, it seems that consumers of research are faced with a large number of critical appraisal tools from which to choose. This is evidenced by the recent report by the Agency for Health Research Quality in which 93 critical appraisal tools for quantitative studies were identified [ 6 ]. Such choice may pose problems for research consumers, as dissimilar findings may well be the result when different critical appraisal tools are used to evaluate the same research report [ 6 ].

Critical appraisal tools can be broadly classified into those that are research design-specific and those that are generic. Design-specific tools contain items that address methodological issues that are unique to the research design [ 5 , 7 ]. This precludes comparison however of the quality of different study designs [ 8 ]. To attempt to overcome this limitation, generic critical appraisal tools have been developed, in an attempt to enhance the ability of research consumers to synthesise evidence from a range of quantitative and or qualitative study designs (for instance [ 9 ]). There is no evidence that generic critical appraisal tools and design-specific tools provide a comparative evaluation of research designs.

Moreover, there appears to be little consensus regarding the most appropriate items that should be contained within any critical appraisal tool. This paper is concerned primarily with critical appraisal tools that address the unique properties of allied health care and research [ 10 ]. This approach was taken because of the unique nature of allied health contacts with patients, and because evidence-based practice is an emerging area in allied health [ 10 ]. The availability of so many critical appraisal tools (for instance [ 6 ]) may well prove daunting for allied health practitioners who are learning to critically appraise research in their area of interest. For the purposes of this evaluation, allied health is defined as encompassing "...all occasions of service to non admitted patients where services are provided at units/clinics providing treatment/counseling to patients. These include units primarily concerned with physiotherapy, speech therapy, family panning, dietary advice, optometry occupational therapy..." [ 11 ].

The unique nature of allied health practice needs to be considered in allied health research. Allied health research thus differs from most medical research, with respect to:

• the paradigm underpinning comprehensive and clinically-reasoned descriptions of diagnosis (including validity and reliability). An example of this is in research into low back pain, where instead of diagnosis being made on location and chronicity of pain (as is common) [ 12 ], it would be made on the spinal structure and the nature of the dysfunction underpinning the symptoms, which is arrived at by a staged and replicable clinical reasoning process [ 10 , 13 ].

• the frequent use of multiple interventions within the one contact with the patient (an occasion of service), each of which requires appropriate description in terms of relationship to the diagnosis, nature, intensity, frequency, type of instruction provided to the patient, and the order in which the interventions were applied [ 13 ]

• the timeframe and frequency of contact with the patient (as many allied health disciplines treat patients in episodes of care that contain multiple occasions of service, and which can span many weeks, or even years in the case of chronic problems [ 14 ])

• measures of outcome, including appropriate methods and timeframes of measuring change in impairment, function, disability and handicap that address the needs of different stakeholders (patients, therapists, funders etc) [ 10 , 12 , 13 ].

Search strategy

In supplementary data [see additional file 1 ].

Data organization and extraction

Two independent researchers (PK, NMW) participated in all aspects of this review, and they compared and discussed their findings with respect to inclusion of critical appraisal tools, their intent, components, data extraction and item classification, construction and psychometric properties. Disagreements were resolved by discussion with a third member of the team (KG).

Data extraction consisted of a four-staged process. First, identical replica critical appraisal tools were identified and removed prior to analysis. The remaining critical appraisal tools were then classified according to the study design for which they were intended to be used [ 1 , 2 ]. The scientific manner in which the tools had been constructed was classified as whether an empirical research approach has been used, and if so, which type of research had been undertaken. Finally, the items contained in each critical appraisal tool were extracted and classified into one of eleven groups, which were based on the criteria described by Clarke and Oxman [ 4 ] as:

• Study aims and justification

• Methodology used , which encompassed method of identification of relevant studies and adherence to study protocol;

• Sample selection , which ranged from inclusion and exclusion criteria, to homogeneity of groups;

• Method of randomization and allocation blinding;

• Attrition : response and drop out rates;

• Blinding of the clinician, assessor, patient and statistician as well as the method of blinding;

• Outcome measure characteristics;

• Intervention or exposure details;

• Method of data analyses ;

• Potential sources of bias ; and

• Issues of external validity , which ranged from application of evidence to other settings to the relationship between benefits, cost and harm.

An additional group, " miscellaneous ", was used to describe items that could not be classified into any of the groups listed above.

Data synthesis

Data was synthesized using MS Excel spread sheets as well as narrative format by describing the number of critical appraisal tools per study design and the type of items they contained. Descriptions were made of the method by which the overall quality of the study was determined, evidence regarding the psychometric properties of the tools (validity and reliability) and whether guidelines were provided for use of the critical appraisal tool.

One hundred and ninety-three research reports that potentially provided a description of a critical appraisal tool (or process) were identified from the search strategy. Fifty-six of these papers were unavailable for review due to outdated Internet links, or inability to source the relevant journal through Australian university and Government library databases. Of the 127 papers retrieved, 19 were excluded from this review, as they did not provide a description of the critical appraisal tool used, or were published in languages other than English. As a result, 108 papers were reviewed, which yielded 121 different critical appraisal tools [ 1 – 5 , 7 , 9 , 15 – 102 , 116 ].

Empirical basis for tool construction

We identified 14 instruments (12% all tools) which were reported as having been constructed using a specified empirical approach [ 20 , 29 , 30 , 32 , 35 , 40 , 49 , 51 , 70 – 72 , 79 , 103 , 116 ]. The empirical research reflected descriptive and/or qualitative approaches, these being critical review of existing tools [ 40 , 72 ], Delphi techniques to identify then refine data items [ 32 , 51 , 71 ], questionnaires and other forms of written surveys to identify and refine data items [ 70 , 79 , 103 ], facilitated structured consensus meetings [ 20 , 29 , 30 , 35 , 40 , 49 , 70 , 72 , 79 , 116 ], and pilot validation testing [ 20 , 40 , 72 , 103 , 116 ]. In all the studies which reported developing critical appraisal tools using a consensus approach, a range of stakeholder input was sought, reflecting researchers and clinicians in a range of health disciplines, students, educators and consumers. There were a further 31 papers which cited other studies as the source of the tool used in the review, but which provided no information on why individual items had been chosen, or whether (or how) they had been modified. Moreover, for 21 of these tools, the cited sources of the critical appraisal tool did not report the empirical basis on which the tool had been constructed.

Critical appraisal tools per study design

Seventy-eight percent (N = 94) of the critical appraisal tools were developed for use on primary research [ 1 – 5 , 7 , 9 , 18 , 19 , 25 – 27 , 34 , 37 – 41 ], while the remainder (N = 26) were for secondary research (systematic reviews and meta-analyses) [ 2 – 5 , 15 – 36 , 116 ]. Eighty-seven percent (N = 104) of all critical appraisal tools were design-specific [ 2 – 5 , 7 , 9 , 15 – 90 ], with over one third (N = 45) developed for experimental studies (randomized controlled trials, clinical trials) [ 2 – 4 , 25 – 27 , 34 , 37 – 73 ]. Sixteen critical appraisal tools were generic. Of these, six were developed for use on both experimental and observational studies [ 9 , 91 – 95 ], whereas 11 were purported to be useful for any qualitative and quantitative research design [ 1 , 18 , 41 , 96 – 102 , 116 ] (see Figure 1 , Table 1 ).

figure 1

Number of critical appraisal tools per study design [1,2]

Critical appraisal items

One thousand, four hundred and seventy five items were extracted from these critical appraisal tools. After grouping like items together, 173 different item types were identified, with the most frequently reported items being focused towards assessing the external validity of the study (N = 35) and method of data analyses (N = 28) (Table 2 ). The most frequently reported items across all critical appraisal tools were:

Eligibility criteria (inclusion/exclusion criteria) (N = 63)

Appropriate statistical analyses (N = 47)

Random allocation of subjects (N = 43)

Consideration of outcome measures used (N = 43)

Sample size justification/power calculations (N = 39)

Study design reported (N = 36)

Assessor blinding (N = 36)

Design-specific critical appraisal tools

Systematic reviews.

Eighty-seven different items were extracted from the 26 critical appraisal tools, which were designed to evaluate the quality of systematic reviews. These critical appraisal tools frequently contained items regarding data analyses and issues of external validity (Tables 2 and 3 ).

Items assessing data analyses were focused to the methods used to summarize the results, assessment of sensitivity of results and whether heterogeneity was considered, whereas the nature of reporting of the main results, interpretation of them and their generalizability were frequently used to assess the external validity of the study findings. Moreover, systematic review critical appraisal tools tended to contain items such as identification of relevant studies, search strategy used, number of studies included and protocol adherence, that would not be relevant for other study designs. Blinding and randomisation procedures were rarely included in these critical appraisal tools.

Experimental studies

One hundred and twenty thirteen different items were extracted from the 45 experimental critical appraisal tools. These items most frequently assessed aspects of data analyses and blinding (Tables 1 and 2 ). Data analyses items were focused on whether appropriate statistical analysis was performed, whether a sample size justification or power calculation was provided and whether side effects of the intervention were recorded and analysed. Blinding was focused on whether the participant, clinician and assessor were blinded to the intervention.

Diagnostic studies

Forty-seven different items were extracted from the seven diagnostic critical appraisal tools. These items frequently addressed issues involving data analyses, external validity of results and sample selection that were specific to diagnostic studies (whether the diagnostic criteria were defined, definition of the "gold" standard, the calculation of sensitivity and specificity) (Tables 1 and 2 ).

Observational studies

Seventy-four different items were extracted from the 19 critical appraisal tools for observational studies. These items primarily focused on aspects of data analyses (see Tables 1 and 2 , such as whether confounders were considered in the analysis, whether a sample size justification or power calculation was provided and whether appropriate statistical analyses were preformed.

Qualitative studies

Thirty-six different items were extracted from the seven qualitative study critical appraisal tools. The majority of these items assessed issues regarding external validity, methods of data analyses and the aims and justification of the study (Tables 1 and 2 ). Specifically, items were focused to whether the study question was clearly stated, whether data analyses were clearly described and appropriate, and application of the study findings to the clinical setting. Qualitative critical appraisal tools did not contain items regarding sample selection, randomization, blinding, intervention or bias, perhaps because these issues are not relevant to the qualitative paradigm.

Generic critical appraisal tools

Experimental and observational studies.

Forty-two different items were extracted from the six critical appraisal tools that could be used to evaluate experimental and observational studies. These tools most frequently contained items that addressed aspects of sample selection (such as inclusion/exclusion criteria of participants, homogeneity of participants at baseline) and data analyses (such as whether appropriate statistical analyses were performed, whether a justification of the sample size or power calculation were provided).

All study designs

Seventy-eight different items were contained in the ten critical appraisal tools that could be used for all study designs (quantitative and qualitative). The majority of these items focused on whether appropriate data analyses were undertaken (such as whether confounders were considered in the analysis, whether a sample size justification or power calculation was provided and whether appropriate statistical analyses were preformed) and external validity issues (generalization of results to the population, value of the research findings) (see Tables 1 and 2 ).

Allied health critical appraisal tools

We found no critical appraisal instrument specific to allied health research, despite finding at least seven critical appraisal instruments associated with allied health topics (mostly physiotherapy management of orthopedic conditions) [ 37 , 39 , 52 , 58 , 59 , 65 ]. One critical appraisal development group proposed two instruments [ 9 ], specific to quantitative and qualitative research respectively. The core elements of allied health research quality (specific diagnosis criteria, intervention descriptions, nature of patient contact and appropriate outcome measures) were not addressed in any one tool sourced for this evaluation. We identified 152 different ways of considering quality reporting of outcome measures in the 121 critical appraisal tools, and 81 ways of considering description of interventions. Very few tools which were not specifically targeted to diagnostic studies (less than 10% of the remaining tools) addressed diagnostic criteria. The critical appraisal instrument that seemed most related to allied health research quality [ 39 ] sought comprehensive evaluation of elements of intervention and outcome, however this instrument was relevant only to physiotherapeutic orthopedic experimental research.

Overall study quality

Forty-nine percent (N = 58) of critical appraisal tools summarised the results of the quality appraisal into a single numeric summary score [ 5 , 7 , 15 – 25 , 37 – 59 , 74 – 77 , 80 – 83 , 87 , 91 – 93 , 96 , 97 ] (Figure 2 ). This was achieved by one of two methods:

figure 2

Number of critical appraisal tools with, and without, summary quality scores

An equal weighting system, where one point was allocated to each item fulfilled; or

A weighted system, where fulfilled items were allocated various points depending on their perceived importance.

However, there was no justification provided for any of the scoring systems used. In the remaining critical appraisal tools (N = 62), a single numerical summary score was not provided [ 1 – 4 , 9 , 25 – 36 , 60 – 73 , 78 , 79 , 84 – 90 , 94 , 95 , 98 – 102 ]. This left the research consumer to summarize the results of the appraisal in a narrative manner, without the assistance of a standard approach.

Psychometric properties of critical appraisal tools

Few critical appraisal tools had documented evidence of their validity and reliability. Face validity was established in nine critical appraisal tools, seven of which were developed for use on experimental studies [ 38 , 40 , 45 , 49 , 51 , 63 , 70 ] and two for systematic reviews [ 32 , 103 ]. Intra-rater reliability was established for only one critical appraisal tool as part of its empirical development process [ 40 ], whereas inter-rater reliability was reported for two systematic review tools [ 20 , 36 ] (for one of these as part of the developmental process [ 20 ]) and seven experimental critical appraisal tools [ 38 , 40 , 45 , 51 , 55 , 56 , 63 ] (for two of these as part of the developmental process [ 40 , 51 ]).

Critical appraisal tool guidelines

Forty-three percent (N = 52) of critical appraisal tools had guidelines that informed the user of the interpretation of each item contained within them (Table 2 ). These guidelines were most frequently in the form of a handbook or published paper (N = 31) [ 2 , 4 , 9 , 15 , 20 , 25 , 28 , 29 , 31 , 36 , 37 , 41 , 50 , 64 – 67 , 69 , 80 , 84 – 87 , 89 , 90 , 95 , 100 , 116 ], whereas in 14 critical appraisal tools explanations accompanied each item [ 16 , 26 , 27 , 40 , 49 , 51 , 57 , 59 , 79 , 83 , 91 , 102 ].

Our search strategy identified a large number of published critical appraisal tools that are currently available to critically appraise research reports. There was a distinct lack of information on tool development processes in most cases. Many of the tools were reported to be modifications of other published tools, or reflected specialty concerns in specific clinical or research areas, without attempts to justify inclusion criteria. Less than 10 of these tools were relevant to evaluation of the quality of allied health research, and none of these were based on an empirical research approach. We are concerned that although our search was systematic and extensive [ 104 , 105 ], our broad key words and our lack of ready access to 29% of potentially useful papers (N = 56) potentially constrained us from identifying all published critical appraisal tools. However, consumers of research seeking critical appraisal instruments are not likely to seek instruments from outdated Internet links and unobtainable journals, thus we believe that we identified the most readily available instruments. Thus, despite the limitations on sourcing all possible tools, we believe that this paper presents a useful synthesis of the readily available critical appraisal tools.

The majority of the critical appraisal tools were developed for a specific research design (87%), with most designed for use on experimental studies (38% of all critical appraisal tools sourced). This finding is not surprising as, according to the medical model, experimental studies sit at or near the top of the hierarchy of evidence [ 2 , 8 ]. In recent years, allied health researchers have strived to apply the medical model of research to their own discipline by conducting experimental research, often by using the randomized controlled trial design [ 106 ]. This trend may be the reason for the development of experimental critical appraisal tools reported in allied health-specific research topics [ 37 , 39 , 52 , 58 , 59 , 65 ].

We also found a considerable number of critical appraisal tools for systematic reviews (N = 26), which reflects the trend to synthesize research evidence to make it relevant for clinicians [ 105 , 107 ]. Systematic review critical appraisal tools contained unique items (such as identification of relevant studies, search strategy used, number of studies included, protocol adherence) compared with tools used for primary studies, a reflection of the secondary nature of data synthesis and analysis.

In contrast, we identified very few qualitative study critical appraisal tools, despite the presence of many journal-specific guidelines that outline important methodological aspects required in a manuscript submitted for publication [ 108 – 110 ]. This finding may reflect the more traditional, quantitative focus of allied health research [ 111 ]. Alternatively, qualitative researchers may view the robustness of their research findings in different terms compared with quantitative researchers [ 112 , 113 ]. Hence the use of critical appraisal tools may be less appropriate for the qualitative paradigm. This requires further consideration.

Of the small number of generic critical appraisal tools, we found few that could be usefully applied (to any health research, and specifically to the allied health literature), because of the generalist nature of their items, variable interpretation (and applicability) of items across research designs, and/or lack of summary scores. Whilst these types of tools potentially facilitate the synthesis of evidence across allied health research designs for clinicians, their lack of specificity in asking the 'hard' questions about research quality related to research design also potentially precludes their adoption for allied health evidence-based practice. At present, the gold standard study design when synthesizing evidence is the randomized controlled trial [ 4 ], which underpins our finding that experimental critical appraisal tools predominated in the allied health literature [ 37 , 39 , 52 , 58 , 59 , 65 ]. However, as more systematic literature reviews are undertaken on allied health topics, it may become more accepted that evidence in the form of other research design types requires acknowledgement, evaluation and synthesis. This may result in the development of more appropriate and clinically useful allied health critical appraisal tools.

A major finding of our study was the volume and variation in available critical appraisal tools. We found no gold standard critical appraisal tool for any type of study design. Therefore, consumers of research are faced with frustrating decisions when attempting to select the most appropriate tool for their needs. Variable quality evaluations may be produced when different critical appraisal tools are used on the same literature [ 6 ]. Thus, interpretation of critical analysis must be carefully considered in light of the critical appraisal tool used.

The variability in the content of critical appraisal tools could be accounted for by the lack of any empirical basis of tool construction, established validity of item construction, and the lack of a gold standard against which to compare new critical tools. As such, consumers of research cannot be certain that the content of published critical appraisal tools reflect the most important aspects of the quality of studies that they assess [ 114 ]. Moreover, there was little evidence of intra- or inter-rater reliability of the critical appraisal tools. Coupled with the lack of protocols for use, this may mean that critical appraisers could interpret instrument items in different ways over repeated occasions of use. This may produce variable results [123].

Based on the findings of this evaluation, we recommend that consumers of research should carefully select critical appraisal tools for their needs. The selected tools should have published evidence of the empirical basis for their construction, validity of items and reliability of interpretation, as well as guidelines for use, so that the tools can be applied and interpreted in a standardized manner. Our findings highlight the need for consensus to be reached regarding the important and core items for critical appraisal tools that will produce a more standardized environment for critical appraisal of research evidence. As a consequence, allied health research will specifically benefit from having critical appraisal tools that reflect best practice research approaches which embed specific research requirements of allied health disciplines.

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Centre for Allied Health Evidence: A Collaborating Centre of the Joanna Briggs Institute, City East Campus, University of South Australia, North Terrace, Adelaide, 5000, Australia

Persis Katrak, Nicola Massy-Westropp, VS Saravana Kumar & Karen A Grimmer

School of Physiotherapy, The University of Melbourne, Melbourne, 3010, Australia

Andrea E Bialocerkowski

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Correspondence to Karen A Grimmer .

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PK Sourced critical appraisal tools

Categorized the content and psychometric properties of critical appraisal tools

AEB Synthesis of findings

Drafted manuscript

NMW Sourced critical appraisal tools

VSK Sourced critical appraisal tools

KAG Study conception and design

Assisted with critiquing critical appraisal tools and categorization of the content and psychometric properties of critical appraisal tools

Drafted and reviewed manuscript

Addressed reviewer's comments and re-submitted the article

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Katrak, P., Bialocerkowski, A.E., Massy-Westropp, N. et al. A systematic review of the content of critical appraisal tools. BMC Med Res Methodol 4 , 22 (2004). https://doi.org/10.1186/1471-2288-4-22

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Published : 16 September 2004

DOI : https://doi.org/10.1186/1471-2288-4-22

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Guidance to best tools and practices for systematic reviews

Kat kolaski.

1 Departments of Orthopaedic Surgery, Pediatrics, and Neurology, Wake Forest School of Medicine, Winston-Salem, NC USA

Lynne Romeiser Logan

2 Department of Physical Medicine and Rehabilitation, SUNY Upstate Medical University, Syracuse, NY USA

John P. A. Ioannidis

3 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

Associated Data

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13643-023-02255-9.

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 – 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 – 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 – 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 ​ (Table1). 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.

Guidance for development of evidence syntheses

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 – 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 – 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 – 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 – 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.

Types of traditional systematic reviews

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.

Evidence syntheses published by Cochrane and JBI

a Data from https://www.cochranelibrary.com/cdsr/reviews . Accessed 17 Sep 2022

b Data obtained via personal email communication on 18 Sep 2022 with Emilie Francis, editorial assistant, JBI Evidence Synthesis

c Includes the following categories: prevalence, scoping, mixed methods, and realist reviews

d This methodology is not supported in the current version of the JBI Manual for Evidence Synthesis

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. ​ Fig.1) 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.

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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 – 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.

Tools specifying standards for systematic reviews with and without meta-analysis

a Currently recommended

b Validated tool for systematic reviews of interventions developed for use by authors of overviews or umbrella reviews

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 ].

Comparison of AMSTAR-2 and ROBIS

a ROBIS includes an optional first phase to assess the applicability of the review to the research question of interest. The tool may be applicable to other review types in addition to the four specified, although modification of this initial phase will be needed (Personal Communication via email, Penny Whiting, 28 Jan 2022)

b AMSTAR-2 item #9 and #11 require separate responses for RCTs and NRSI

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 – 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 – 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.

PRISMA extensions

PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses

a Note the abstract reporting checklist is now incorporated into PRISMA 2020 [ 93 ]

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.

Systematic review components linked to appraisal with AMSTAR-2 and ROBIS a

CoI conflict of interest, MA meta-analysis, NA not addressed, PICO participant, intervention, comparison, outcome, PRISMA-P Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols, RoB risk of bias

a Components shown in bold are chosen for elaboration in Part 4 for one (or both) of two reasons: 1) the component has been identified as potentially problematic for systematic review authors; and/or 2) the component is evaluated by standards of an AMSTAR-2 “critical” domain

b Critical domains of AMSTAR-2 are indicated by *

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.

Research question development

a Cummings SR, Browner WS, Hulley SB. Conceiving the research question and developing the study plan. In: Hulley SB, Cummings SR, Browner WS, editors. Designing clinical research: an epidemiological approach; 4th edn. Lippincott Williams & Wilkins; 2007. p. 14–22

b Doran, GT. There’s a S.M.A.R.T. way to write management’s goals and objectives. Manage Rev. 1981;70:35-6.

c Johnson BT, Hennessy EA. Systematic reviews and meta-analyses in the health sciences: best practice methods for research syntheses. Soc Sci Med. 2019;233:237–51

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 ].

Options for protocol registration of evidence syntheses

a Authors are advised to contact their target journal regarding submission of systematic review protocols

b Registration is restricted to approved review projects

c The JBI registry lists review projects currently underway by JBI-affiliated entities. These records include a review’s title, primary author, research question, and PICO elements. JBI recommends that authors register eligible protocols with PROSPERO

d See Pieper and Rombey [ 137 ] for detailed characteristics of these five registries

e See Pieper and Rombey [ 137 ] for other systematic review data repository options

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 – 151 ]. Again, inclusiveness will allow review authors to investigate whether results differ in gray literature and trials [ 41 , 151 – 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 ].

Common methods for quantitative synthesis

CI confidence interval (or credible interval, if analysis is done in Bayesian framework)

a See text for descriptions of the types of data combined in each of these approaches

b See Additional File 4  for guidance on the structure and presentation of forest plots

c General approach is similar to aggregate data meta-analysis but there are substantial differences relating to data collection and checking and analysis [ 162 ]. This approach to syntheses is applicable to intervention, diagnostic, and prognostic systematic reviews [ 163 ]

d Examples include meta-regression, hierarchical and multivariate approaches [ 164 ]

e In-depth guidance and illustrations of these methods are provided in Chapter 12 of the Cochrane Handbook [ 160 ]

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 – 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 – 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 ).

GRADE criteria for rating certainty of evidence

a Applies to randomized studies

b Applies to non-randomized studies

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 certainty ratings and their interpretation symbols a

a From the GRADE Handbook [ 192 ]

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 ].

Criteria for using GRADE in a systematic review a

a Adapted from the GRADE working group [ 206 ]; this list does not contain the additional criteria that apply to the development of a clinical practice guideline

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.

Concise Guide to best practices for evidence syntheses, version 1.0 a

AMSTAR A MeaSurement Tool to Assess Systematic Reviews, CASP Critical Appraisal Skills Programme, CERQual Confidence in the Evidence from Reviews of Qualitative research, ConQual Establishing Confidence in the output of Qualitative research synthesis, COSMIN COnsensus-based Standards for the selection of health Measurement Instruments, DTA diagnostic test accuracy, eMERGe meta-ethnography reporting guidance, ENTREQ enhancing transparency in reporting the synthesis of qualitative research, GRADE Grading of Recommendations Assessment, Development and Evaluation, MA meta-analysis, NRSI non-randomized studies of interventions, P protocol, PRIOR Preferred Reporting Items for Overviews of Reviews, PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses, PROBAST Prediction model Risk Of Bias ASsessment Tool, QUADAS quality assessment of studies of diagnostic accuracy included in systematic reviews, QUIPS Quality In Prognosis Studies, RCT randomized controlled trial, RoB risk of bias, ROBINS-I Risk Of Bias In Non-randomised Studies of Interventions, ROBIS Risk of Bias in Systematic Reviews, ScR scoping review, SWiM systematic review without meta-analysis

a Superscript numbers represent citations provided in the main reference list. Additional File 6 lists links to available online resources for the methods and tools included in the Concise Guide

b The MECIR manual [ 30 ] provides Cochrane’s specific standards for both reporting and conduct of intervention systematic reviews and protocols

c Editorial and peer reviewers can evaluate completeness of reporting in submitted manuscripts using these tools. Authors may be required to submit a self-reported checklist for the applicable tools

d The decision flowchart described by Flemming and colleagues [ 223 ] is recommended for guidance on how to choose the best approach to reporting for qualitative reviews

e SWiM was developed for intervention studies reporting quantitative data. However, if there is not a more directly relevant reporting guideline, SWiM may prompt reviewers to consider the important details to report. (Personal Communication via email, Mhairi Campbell, 14 Dec 2022)

f JBI recommends their own tools for the critical appraisal of various quantitative primary study designs included in systematic reviews of intervention effectiveness, prevalence and incidence, and etiology and risk as well as for the critical appraisal of systematic reviews included in umbrella reviews. However, except for the JBI Checklists for studies reporting prevalence data and qualitative research, the development, validity, and reliability of these tools are not well documented

g Studies that are not RCTs or NRSI require tools developed specifically to evaluate their design features. Examples include single case experimental design [ 155 , 156 ] and case reports and series [ 82 ]

h The evaluation of methodological quality of studies included in a synthesis of qualitative research is debatable [ 224 ]. Authors may select a tool appropriate for the type of qualitative synthesis methodology employed. The CASP Qualitative Checklist [ 218 ] is an example of a published, commonly used tool that focuses on assessment of the methodological strengths and limitations of qualitative studies. The JBI Critical Appraisal Checklist for Qualitative Research [ 219 ] is recommended for reviews using a meta-aggregative approach

i Consider including risk of bias assessment of included studies if this information is relevant to the research question; however, scoping reviews do not include an assessment of the overall certainty of a body of evidence

j Guidance available from the GRADE working group [ 225 , 226 ]; also recommend consultation with the Cochrane diagnostic methods group

k Guidance available from the GRADE working group [ 227 ]; also recommend consultation with Cochrane prognostic methods group

l Used for syntheses in reviews with a meta-aggregative approach [ 224 ]

m Chapter 5 in the JBI Manual offers guidance on how to adapt GRADE to prevalence and incidence reviews [ 69 ]

n Janiaud and colleagues suggest criteria for evaluating evidence certainty for meta-analyses of non-randomized studies evaluating risk factors [ 228 ]

o The COSMIN user manual provides details on how to apply GRADE in systematic reviews of measurement properties [ 229 ]

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.

Terms relevant to the reporting of health care–related evidence syntheses a

a Reproduced from Page and colleagues [ 93 ]

Terminology suggestions for health care–related evidence syntheses

a For example, meta-aggregation, meta-ethnography, critical interpretative synthesis, realist synthesis

b This term may best apply to the synthesis in a mixed methods systematic review in which data from different types of evidence (eg, qualitative, quantitative, economic) are summarized [ 64 ]

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.

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.

Authors’ contributions

All authors participated in the development of the ideas, writing, and review of this manuscript. The author(s) read and approved the final manuscript.

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

Declarations

The authors declare no competing interests.

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 .

Publisher’ s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

  • Methodology
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SANRA—a scale for the quality assessment of narrative review articles

  • Christopher Baethge   ORCID: orcid.org/0000-0001-6246-3674 1 , 2 ,
  • Sandra Goldbeck-Wood 1 , 3 &
  • Stephan Mertens 1  

Research Integrity and Peer Review volume  4 , Article number:  5 ( 2019 ) Cite this article

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Narrative reviews are the commonest type of articles in the medical literature. However, unlike systematic reviews and randomized controlled trials (RCT) articles, for which formal instruments exist to evaluate quality, there is currently no instrument available to assess the quality of narrative reviews. In response to this gap, we developed SANRA, the Scale for the Assessment of Narrative Review Articles.

A team of three experienced journal editors modified or deleted items in an earlier SANRA version based on face validity, item-total correlations, and reliability scores from previous tests. We deleted an item which addressed a manuscript’s writing and accessibility due to poor inter-rater reliability. The six items which form the revised scale are rated from 0 (low standard) to 2 (high standard) and cover the following topics: explanation of (1) the importance and (2) the aims of the review, (3) literature search and (4) referencing and presentation of (5) evidence level and (6) relevant endpoint data. For all items, we developed anchor definitions and examples to guide users in filling out the form. The revised scale was tested by the same editors (blinded to each other’s ratings) in a group of 30 consecutive non-systematic review manuscripts submitted to a general medical journal.

Raters confirmed that completing the scale is feasible in everyday editorial work. The mean sum score across all 30 manuscripts was 6.0 out of 12 possible points (SD 2.6, range 1–12). Corrected item-total correlations ranged from 0.33 (item 3) to 0.58 (item 6), and Cronbach’s alpha was 0.68 (internal consistency). The intra-class correlation coefficient (average measure) was 0.77 [95% CI 0.57, 0.88] (inter-rater reliability). Raters often disagreed on items 1 and 4.

Conclusions

SANRA’s feasibility, inter-rater reliability, homogeneity of items, and internal consistency are sufficient for a scale of six items. Further field testing, particularly of validity, is desirable. We recommend rater training based on the “explanations and instructions” document provided with SANRA. In editorial decision-making, SANRA may complement journal-specific evaluation of manuscripts—pertaining to, e.g., audience, originality or difficulty—and may contribute to improving the standard of non-systematic reviews.

Peer Review reports

Narrative review articles are common in the medical literature. Bastian et al. found that they constitute the largest share of all text types in medicine and they concluded that they “remain the staple of medical literature” [ 1 ]. Narrative reviews also appear popular among both authors and readers, and it is plausible to assume that they exercise an enormous influence among doctors in clinical practice and research. However, because their quality varies widely, they have frequently been compared in blanket, negative terms with systematic reviews.

We use the term narrative review to refer to an attempt to summarize the literature in a way which is not explicitly systematic, where the minimum requirement for the term systematic relates to the method of the literature search, but in a wider sense includes a specific research question and a comprehensive summary of all studies [ 2 ].

While systematic reviews are not per se superior articles and while certain systematic reviews have been criticized lately [ 3 ], non-systematic reviews or narrative reviews have been widely criticized as unreliable [ 1 , 4 ]. Hence, the hierarchy of evidence-based medicine places systematic reviews much higher than non-systematic ones. However, it is likely—and even desirable—that good quality narrative reviews will continue to play an important role in medicine: while systematic reviews are superior to narrative reviews in answering specific questions (for example, whether it is advisable to switch an antidepressant among antidepressant non-responders in patients with major depressive disorder [ 5 ]), narrative reviews are better suited to addressing a topic in wider ways (for example, outlining the general principles of diagnosing and treating depression [ 6 ]).

Critical appraisal tools have been developed for systematic reviews (e.g., AMSTAR 2 [A MeaSurement Tool to Assess Systematic Reviews] [ 7 ]) and papers on RCTs (e.g., the CASP [Critical Appraisal Skills Program] checklist for randomized trials [ 8 ]) and other types of medical studies. For narrative reviews, in contrast, no critical appraisal, or quality assessment tool is available. Such a tool, however, if simple and brief enough for day-to-day use, may support editors in choosing or improving manuscripts, help reviewers and readers in assessing the quality of a paper, and aid authors in preparing narrative reviews. It may improve the general quality of narrative reviews.

As a consequence, we have developed SANRA, the Scale for the Assessment of Narrative Review Articles, a brief critical appraisal tool for the assessment of non-systematic articles. Here, we present the revised scale and the results of a field test regarding its feasibility, item-total correlation, internal consistency, reliability, and criterion validity.

SANRA was developed between 2010 and 2017 by three experienced editors (CB, SGW, and SM) working at a general medical journal, Deutsches Ärzteblatt , the journal of the German Medical Association and the National Association of Statutory Health Insurance Physicians . It is intended to be a simple and brief quality assessment instrument not only to assist editors in their decisions about manuscripts, but also to help reviewers and readers in their assessment of papers and authors in writing narrative reviews.

Two earlier, seven-item versions of SANRA have been developed and tested by the authors, the first in 10 narrative reviews from the field of neurology as retrieved through a PubMed search, the second among 12 consecutive narrative reviews submitted to Deutsches Ärzteblatt —both showing satisfactory internal consistency and inter-rater reliability [ 9 ].

The current version of SANRA [ 10 ] has been revised by the authors in 2014 in order to simplify the scale and make it more robust. We simplified the wording of the items, and we deleted an item addressing a manuscript’s writing and accessibility because ratings of that item differed considerably. The six items that form the revised scale are rated in integers from 0 (low standard) to 2 (high standard), with 1 as an intermediate score. The maximal sum score is 12.

The sum score of the scale is intended to measure the construct “quality of a narrative review article” and covers the following topics: explanation of the review’s importance (item 1) and statement of the aims (item 2) of the review, description of the literature search (item 3), referencing (item 4), scientific reasoning (item 5), and presentation of relevant and appropriate endpoint data (item 6) (Fig.  1 ). For all items, we developed anchor definitions and examples to guide users in filling out the instrument, provided in the document “explanations and instructions,” accompanying the scale. This document was also edited to improve clarity (Fig.  2 ).

figure 1

SANRA - Scale

figure 2

SANRA—explanations and instructions document

In 2015, one rater (CB) screened all submissions to Deutsches Ärzteblatt in 2015, and the first 30 consecutive review manuscripts without systematic literature searches were selected for inclusion in the present study. All three raters (CB, SGW, and SM) are editors, with, in 2015, at least 10 years of experience each. They scored the manuscripts independently and blinded to each other’s ratings.

Statistical analysis

Descriptive data are shown as means or medians, as appropriate, and as ranges, standard deviations, or confidence intervals. This study aimed at testing SANRA’s internal consistency (Cronbach’s alpha) and the item-total correlation—indicating whether the items measure the same phenomenon, here different aspects of review paper quality—as well as SANRA’s inter-rater reliability with regard to its sum score. Inter-rater reliability, as a measure of the consistency among different raters, was expressed as the average measure intra-class correlation, ICC, using a two-way random effects model (consistency definition). As an approximation of SANRA’s criterion validity (Is the score predictive of other indicators of paper quality, e.g., acceptance and rejection or citations?), we analyzed post hoc whether average sum scores of SANRA were associated with the decision to accept or reject the 30 manuscripts under study (point biserial correlation for the association between a dichotomous and a continuous variable). All calculations were carried out using SPSS. Where possible, the presentation follows the recommendations of the Guidelines for Reporting Reliability and Agreement Studies (GRRAS) [ 11 ].

All 90 ratings (3 raters × 30 manuscripts) were used for statistical analysis. The mean sum score across all 30 manuscripts ( N  = 90) was 6.0 out of 12 possible points (SD 2.6, range 1–12, median 6). Highest scores were rated for item 4 (mean 1.25; SD 0.70), item 2 (mean 1.14; SD 0.84), and item 1 (mean 1.1; SD 0.69) whereas items 6, 5, and 3 had the lowest scores (means of 0.81 (SD 0.65), 0.83 (SD 0.67), and 0.84 (SD 0.60), respectively) (all single-item medians: 1).

The scale’s internal consistency, measured as Cronbach’s alpha, was 0.68. Corrected item-total correlations ranged from 0.33 to 0.58 (Table  1 ). Tentative deletions of each item to assess the effect of these on consistency showed reduced internal consistency with every deleted item (0.58–0.67) (as shown by the alpha values in Table  1 ).

Across 180 single-item ratings (6 items × 30 manuscripts), the maximum difference among the 3 raters was 2 in 12.8% ( n  = 23; most often in items 1, 2, and 4), in 56.7% ( n  = 102), the raters differed by no more than 1 point, and in 30.6% ( n  = 55), they entirely agreed (most often in items 2 and 3). The intra-class correlation coefficient (average measure) amounted to 0.77 [95% CI 0.57, 0.88; F 4.3; df 29, 58]. Disagreements most often occurred with regard to items 1 and 4.

Average SANRA sum scores of the 30 manuscripts were modestly associated with the editorial decision of acceptance (mean score 6.6, SD 1.9; n  = 17) or rejection (mean score 5.1, SD 2.1; n  = 13): point biserial correlation of 0.37 ( t  = 2.09, df 28; two-sided p  = 0.046).

All raters confirmed that completing the scale is feasible in everyday editorial work.

This study yielded three important findings: (1) SANRA can be applied to manuscripts in everyday editorial work. (2) SANRA’s internal consistency and item-total correlation are sufficient. (3) SANRA’s inter-rater reliability is satisfactory.

Feasibility

It is our experience with the current and earlier SANRA versions that editors, once accustomed to the scale, can integrate the scale into their everyday routine. It is important, however, to learn how to fill out SANRA. To this end, together with SANRA, we provide definitions and examples in the explanations and instructions document, and we recommend that new users train filling out SANRA using this resource. Editorial teams or teams of scientists and/or clinicians may prefer to learn using SANRA in group sessions.

Consistency and homogeneity

With Cronbach’s alpha of 0.68 and corrected item-total correlations between 0.33 and 0.58, we consider the scale’s consistency and item homogeneity sufficient for widespread application. It should be noted that because coefficient alpha increases with the number of items [ 12 ], simplifying a scale by reducing the number of items—as we did—may decrease internal consistency. However, this needs to be balanced against the practical need for brevity. In fact, the earlier seven-item versions of SANRA had higher values of alpha: 0.80 and 0.84, respectively [ 9 ]. Still, the number of items is not necessarily the only explanation for differences in alpha values. For example, the manuscripts included in the two earlier studies may have been easier to rate.

Inter-rater reliability

The scale’s intra-class correlation (0.77 after 0.76 in [ 9 ]) indicates that SANRA can be used reliably by different raters—an important property of a scale that may be applied for manuscript preparation and review, in editorial decision-making, or even in research on narrative reviews. Like internal consistency, reliability increases with the number of items [ 12 ], and there is a trade-off between simplicity (e.g., a small number of items) and reliability. While the ICC suggests sufficient reliability, however, the lower confidence limit (0.57) does not preclude a level of reliability normally deemed unacceptable in most applications of critical appraisal tools. This finding underscores the importance of rater training. Raters more often disagreed on items 1 and 4. After the study, we have therefore slightly edited these items, along with items 5 and 6 which we edited for clarity. In the same vein, we revised our explanations and instructions document.

It is important to bear in mind that testing of a scale always relates only to the setting of a given study. Thus, in the strict sense, the results presented here are not a general feature of SANRA but of SANRA filled out by certain raters with regard to a particular sample of manuscripts. However, from our experience, we trust that our setting is similar to that of many journals, and our sample of manuscripts represents an average group of papers. As a consequence, we are confident SANRA can be applied by other editors, reviewers, readers, and authors.

In a post hoc analysis, we found a modest, but statistically significant correlation of SANRA sum scores with manuscript acceptance. We interpret this as a sign of criterion validity, but emphasize that this is both a post hoc result and only a weak correlation. The latter, however, points to the fact that, at the level of submitted papers, other aspects than quality alone influence editorial decision-making: for example, whether the topic has been covered in the journal recently or whether editors believe that authors or topics of manuscripts have potential, even with low initial SANRA scores. SANRA will therefore often be used as one, and not the only, decision aid. Also, the decision to accept a paper has been made after the papers had been revised.

Moreover, additional results on criterion validity are needed, as are results on SANRA’s construct validity. On the other hand, SANRA’s content validity, defined as a scale’s ability to completely cover all aspects of a construct, will be restricted because we decided to limit the scale to six items, too few to encompass all facets of review article quality—SANRA is a critical appraisal tool and not a reporting guideline. For example, we deleted an item on the accessibility of the manuscript. Other possible domains that are not part of SANRA are, for example, originality of the manuscript or quality of tables and figures. These features are important, but we believe the six items forming SANRA are a core set that sufficiently indicates the quality of a review manuscript and, at the same time, is short enough to be applied without too much time and effort. SANRA’s brevity is also in contrast to other tools to assess articles, such as AMSTAR 2, for systematic reviews, or, to a lesser extent, CASP for RCTs, with its 16 and 11 items, respectively.

Throughout this paper we have referred to the current version of SANRA as the revision of earlier forms. This is technically true. However, because it is normal that scales go through different versions before publication and because this paper is first widespread publication of SANRA, we propose to call the present version simpy SANRA.

While medicine has achieved a great deal in the formalization and improvement of the presentation of randomized trials and systematic review articles, and also a number of other text types in medicine, much less work have been done with regard to the most frequent form of medical publications, the narrative review. There are exceptions: Gasparyan et al. [ 13 ], for example, have provided guidance for writing narrative reviews, and Byrne [ 14 ] as well as Pautasso [ 15 ] has written, from different angles, thoughtful editorials on improving narrative reviews and presented lists of key features of writing a good review—lists that naturally overlap with SANRA items (e.g., on referencing). These lists, however, are not tested scales and not intended for comparing different manuscripts. SANRA can be used in comparisons of manuscripts the way we used it in our editorial office, that is, in one setting. At the present time, however, it seems unwise to compare manuscripts across different settings because, so far, there are no established cut-offs for different grades of quality (e.g., poor-fair-moderate-good-very good). Still, in our experience, a score of 4 or below indicates very poor quality.

Limitations

The main limitation of this study is its sample size. While, in our experience, a group of 30 is not unusual in testing scales, it represents a compromise between the aims of representativeness for our journal and adequate power and feasibility; it took us about 6 months to sample 30 consecutive narrative reviews. Also, in this study, the authors of the scale were also the test-raters, and it is possible that inter-rater reliability is lower in groups less familiar with the scale. As for most scales, this underscores the importance of using the instructions that belong to the scale, in the present case the explanations and instructions document. It is also advisable to train using the scale before applying SANRA for manuscript rating. In addition, by design, this is not a study of test-retest reliability, another important feature of a scale. Finally, as previously acknowledged, although we believe in the representativeness of our setting for medical journals, the present results refer to the setting of this study, and consistency and reliability measures are study-specific.

We present SANRA, a brief scale for the quality assessment of narrative review articles, the most widespread form of article in the medical literature. We suggest SANRA can be integrated into the work of editors, reviewers, and authors. We encourage readers to consider using SANRA as an aid to critically appraising articles, and authors to consider its use on preparing narrative reviews, with a view to improving the quality of submitted and published manuscripts.

SANRA and its explanations and instructions document are available (open access) at: https://www.aerzteblatt.de/down.asp?id=22862 , https://www.aerzteblatt.de/down.asp?id=22861 .

Abbreviations

A MeaSurement Tool to Assess Systematic Reviews

Critical Appraisal Skills Program

Guidelines for Reporting Reliability and Agreement Studies

Intra-class correlation

Randomized controlled trial

Scale for the Assessment of Narrative Review Articles

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Acknowledgements

This work has been presented at the Eighth International Congress on Peer Review and Scientific Publication in Chicago, Illinois, USA. (September 10-12, 2017) and at the 14th EASE Conference in Bucharest, Romania (June 8-10, 2018).

This work has not been externally funded.

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All authors (CB, SM, and SGW) made substantial contributions to the conception of the study and to the acquisition and interpretation of data. CB analyzed the data and drafted the manuscript. SM and SGW revised the draft critically for important intellectual content. All authors sufficiently participated in this work to take public responsibility for its content, all finally approved the manuscript, and all are accountable for every aspect of this project.

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Non-financial competing interest: all authors (CB, SM, and SGW) had their part in the development of the scale under study. The authors declare that they have no financial competing interests.

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Baethge, C., Goldbeck-Wood, S. & Mertens, S. SANRA—a scale for the quality assessment of narrative review articles. Res Integr Peer Rev 4 , 5 (2019). https://doi.org/10.1186/s41073-019-0064-8

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  • Intra-class correlation coefficient

Research Integrity and Peer Review

ISSN: 2058-8615

critical appraisal tools literature reviews

Critical Appraisal of a Systematic Review: A Concise Review

Affiliations.

  • 1 Division of Pulmonary and Critical Care Medicine, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI.
  • 2 Department of Anesthesiology, University Hospital RWTH Aachen University, Aachen, Germany.
  • 3 Department of Intensive Care Medicine, University Hospital RWTH Aachen University, Aachen, Germany.
  • 4 Department of Anesthesiology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia.
  • 5 Clinical Evaluation Research Unit, Department of Critical Care Medicine, Queen's University, KGH Research Institute, Kingston Health Sciences Centre, Kingston, ON, Canada.
  • 6 Department of Anesthesiology and Intensive Care Medicine, University Hospital Wuerzburg, Wuerzburg, Germany.
  • PMID: 35853198
  • DOI: 10.1097/CCM.0000000000005602

Objectives: Concise definitive review of how to read and critically appraise a systematic review.

Data sources: None.

Study selection: Current literature describing the conduct, reporting, and appraisal of systematic reviews and meta-analyses.

Data extraction: Best practices for conducting, reporting, and appraising systematic review were summarized.

Data synthesis: A systematic review is a review of a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise relevant original research, and to collect and analyze data from the studies that are included in the review. Critical appraisal methods address both the credibility (quality of conduct) and rate the confidence in the quality of summarized evidence from a systematic review. The A Measurement Tool to Assess Systematic Reviews-2 tool is a widely used practical tool to appraise the conduct of a systematic review. Confidence in estimates of effect is determined by assessing for risk of bias, inconsistency of results, imprecision, indirectness of evidence, and publication bias.

Conclusions: Systematic reviews are transparent and reproducible summaries of research and conclusions drawn from them are only as credible and reliable as their development process and the studies which form the systematic review. Applying evidence from a systematic review to patient care considers whether the results can be directly applied, whether all important outcomes have been considered, and if the benefits are worth potential harms and costs.

Copyright © 2022 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.

Publication types

  • Publications
  • Systematic Reviews as Topic*
  • PRISMA STATEMENT
  • TRANSLATIONS
  • ENDORSEMENT

IMAGES

  1. What Are The Main Types Of Literature Review

    critical appraisal tools literature reviews

  2. Critical Appraisal

    critical appraisal tools literature reviews

  3. The Differences Between a Systematic Review vs Meta Analysis

    critical appraisal tools literature reviews

  4. This set of eight critical appraisal tools are designed to be used when reading research, these

    critical appraisal tools literature reviews

  5. Overview of critical appraisal tools used for different study designs

    critical appraisal tools literature reviews

  6. What's the Difference between a Literature Review, Systematic Review, and Meta-Analysis ?

    critical appraisal tools literature reviews

VIDEO

  1. Systematic literature review

  2. What is Literature Review?

  3. SYSTEMATIC AND LITERATURE REVIEWS

  4. Critical appraisal and literature review

  5. Critical Appraisal of Research Article, and Clinical Audit

  6. Effective Review of Literature

COMMENTS

  1. Critical Appraisal Tools

    Critical Appraisal Tools ; Writing a Literature Review ; Appraise Your Research Articles. The structure of a literature review should include the following: An overview of the subject, issue, or theory under consideration, along with the objectives of the literature review,

  2. Scientific writing: Critical Appraisal Toolkit (CAT) for assessing

    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 ...

  3. Choosing the Best Systematic Review Critical Appraisal Tool

    Choosing the Best Systematic Review Critical Appraisal Tool. Automate every stage of your literature review to produce evidence-based research faster and more accurately. Critical appraisal is an important step in the systematic review methodology. It assesses the quality and validity of the studies to be considered in the research, helping ...

  4. Critical Appraisal Tools and Reporting Guidelines

    More. Critical appraisal tools and reporting guidelines are the two most important instruments available to researchers and practitioners involved in research, evidence-based practice, and policymaking. Each of these instruments has unique characteristics, and both instruments play an essential role in evidence-based practice and decision-making.

  5. Critical Appraisal

    Selection of a valid critical appraisal tool, testing the tool with several of the selected studies, and involving two or more reviewers in the appraisal are good practices to follow. 1. Purssell E, McCrae N. How to Perform a Systematic Literature Review: A Guide for Healthcare Researchers, Practitioners and Students. 1st ed. Springer; 2020.

  6. A systematic review of the content of critical appraisal tools

    A systematic review was undertaken of 121 published critical appraisal tools sourced from 108 papers located on electronic databases and the Internet. The tools were classified according to the study design for which they were intended. Their items were then classified into one of 12 criteria based on their intent.

  7. Critical Appraisal tools

    This section contains useful tools and downloads for the critical appraisal of different types of medical evidence. Example appraisal sheets are provided together with several helpful examples. Critical Appraisal Worksheets. English. Systematic Reviews Critical Appraisal Sheet; Diagnostics Critical Appraisal Sheet; Prognosis Critical Appraisal ...

  8. Full article: Critical appraisal

    Whereas critical appraisal tools help reviewers explore a study's methodological rigour, reporting guidelines allow them to examine the clarity, ... requirements typically include a literature review, a nominal group or 'consensus' process, and a mechanism for item selection (Whiting et al., Citation 2017).

  9. Critical appraisal of published literature

    Critical appraisal. ' The process of carefully and systematically examining research to judge its trustworthiness, and its value and relevance in a particular context '. -Burls A [ 1] The objective of medical literature is to provide unbiased, accurate medical information, backed by robust scientific evidence that could aid and enhance ...

  10. PDF © Joanna Briggs Institute 2017 Critical Appraisal Checklist for

    The systematic review is essentially an analysis of the available literature (that is, evidence) and a judgment of the effectiveness or otherwise of a practice, involving a series of complex ... Although designed for use in systematic reviews, JBI critical appraisal tools can also be used when creating Critically Appraised Topics (CAT), in ...

  11. Critical Appraisal

    Aveyard H (2023) Doing a literature review in health and social care: a practical guide. 5th edn. London: Open University Press. ... An outline of AMSTAR 2 and its use for as a critical appraisal tool for systematic reviews. View article (open access) Smith J and Noble H (2014) Bias in research, Evidence-Based Nursing, 17 (4), pp. 100-101. ...

  12. Guidance to best tools and practices for 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 ...

  13. JBI Critical Appraisal Tools

    JBI's critical appraisal tools assist in assessing the trustworthiness, relevance and results of published papers. These tools have been revised. Recently published articles detail the revision. "Assessing the risk of bias of quantitative analytical studies: introducing the vision for critical appraisal within JBI systematic reviews".

  14. A systematic review of the content of critical appraisal tools

    Background Consumers of research (researchers, administrators, educators and clinicians) frequently use standard critical appraisal tools to evaluate the quality of published research reports. However, there is no consensus regarding the most appropriate critical appraisal tool for allied health research. We summarized the content, intent, construction and psychometric properties of published ...

  15. Tools for critically appraising different study designs, systematic

    Key words: critical appraisal tool, systematic review, randomised controlled trial, genetically modified plant, equivalence, extensive literature search ... provided in developing the Critical Appraisal Tool on extensive literature searches. Suggested citation: European Food Safety Authority, 2015. Tools for critically appraising different

  16. Optimising the value of the critical appraisal skills programme (CASP

    It follows that quality appraisal is contingent on adequate reporting, and may only assess reporting, rather than study conduct. 17 Nevertheless, the CASP tool is the most commonly used checklist/criteria-based tool for quality appraisal in health and social care-related qualitative evidence synthesis. 16,23 Authors' reasons for using a ...

  17. A guide to critical appraisal of evidence : Nursing2020 Critical Care

    Critical appraisal is the assessment of research studies' worth to clinical practice. Critical appraisal—the heart of evidence-based practice—involves four phases: rapid critical appraisal, evaluation, synthesis, and recommendation. This article reviews each phase and provides examples, tips, and caveats to help evidence appraisers ...

  18. CASP Checklists

    Critical Appraisal Checklists. We offer a number of free downloadable checklists to help you more easily and accurately perform critical appraisal across a number of different study types. The CASP checklists are easy to understand but in case you need any further guidance on how they are structured, take a look at our guide on how to use our ...

  19. Guidance to best tools and practices for 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.

  20. A critical appraisal tool for systematic literature reviews in software

    Critical appraisal tools. AMSTAR. 1. Introduction. Inspired by medicine, evidence-based software engineering (EBSE) promotes the use of systematic literature reviews (SLRs) to systematically identify, evaluate and synthesize research on a topic of interest [1]. Since the introduction of SLRs in Software Engineering (SE), the rate of papers ...

  21. SANRA—a scale for the quality assessment of narrative review articles

    Critical appraisal tools have been developed for systematic reviews (e.g., AMSTAR 2 [A MeaSurement Tool to Assess Systematic Reviews] ) and papers on RCTs (e.g., the CASP [Critical Appraisal Skills Program] checklist for randomized trials ) and other types of medical studies. For narrative reviews, in contrast, no critical appraisal, or quality ...

  22. Critical Appraisal of a Systematic Review: A Concise Review

    Critical appraisal methods address both the credibility (quality of conduct) and rate the confidence in the quality of summarized evidence from a systematic review. The A Measurement Tool to Assess Systematic Reviews-2 tool is a widely used practical tool to appraise the conduct of a systematic review. Confidence in estimates of effect is ...

  23. PRISMA

    PRISMA is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses. PRISMA primarily focuses on the reporting of reviews evaluating the effects of interventions, but can also be used as a basis for reporting systematic reviews with objectives other than evaluating interventions (e.g. evaluating aetiology ...