literature review best software

10 Best Literature Review Tools for Researchers

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

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

Table of Contents

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

#1. Semantic Scholar – A free, AI-powered research tool for scientific literature

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

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

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

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

#3. Scite.Ai – Your personal research assistant

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

Rayyan offers the following paid plans:

#4. DistillerSR – Literature Review Software

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

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

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

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

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

Consensus offers both free and paid plans:

#7. RAx – AI-powered reading assistant

#8. lateral – advance your research with ai.

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

#9. Iris AI – Introducing the researcher workspace

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

#10. Scholarcy – Summarize your literature through AI

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

Final Thoughts

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

Q1. What are literature review tools for researchers?

Q2. what criteria should researchers consider when choosing literature review tools.

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

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

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

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

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

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• Research Skills Blog

5 software tools to support your systematic review processes

By Dr. Mina Kalantar on 19-Jan-2021 13:01:01

Systematic reviews are a reassessment of scholarly literature to facilitate decision making. This methodical approach of re-evaluating evidence was initially applied in healthcare, to set policies, create guidelines and answer medical questions.

Systematic reviews are large, complex projects and, depending on the purpose, they can be quite expensive to conduct. A team of researchers, data analysts and experts from various fields may collaborate to review and examine incredibly large numbers of research articles for evidence synthesis. Depending on the spectrum, systematic reviews often take at least 6 months, and sometimes upwards of 18 months to complete.

The main principles of transparency and reproducibility require a pragmatic approach in the organisation of the required research activities and detailed documentation of the outcomes. As a result, many software tools have been developed to help researchers with some of the tedious tasks required as part of the systematic review process.

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The first generation of these software tools were produced to accommodate and manage collaborations, but gradually developed to help with screening literature and reporting outcomes. Some of these software packages were initially designed for medical and healthcare studies and have specific protocols and customised steps integrated for various types of systematic reviews. However, some are designed for general processing, and by extending the application of the systematic review approach to other fields, they are being increasingly adopted and used in software engineering, health-related nutrition, agriculture, environmental science, social sciences and education.

Software tools

There are various free and subscription-based tools to help with conducting a systematic review. Many of these tools are designed to assist with the key stages of the process, including title and abstract screening, data synthesis, and critical appraisal. Some are designed to facilitate the entire process of review, including protocol development, reporting of the outcomes and help with fast project completion.

As time goes on, more functions are being integrated into such software tools. Technological advancement has allowed for more sophisticated and user-friendly features, including visual graphics for pattern recognition and linking multiple concepts. The idea is to digitalise the cumbersome parts of the process to increase efficiency, thus allowing researchers to focus their time and efforts on assessing the rigorousness and robustness of the research articles.

This article introduces commonly used systematic review tools that are relevant to food research and related disciplines, which can be used in a similar context to the process in healthcare disciplines.

These reviews are based on IFIS' internal research, thus are unbiased and not affiliated with the companies.

This online platform is a core component of the Cochrane toolkit, supporting parts of the systematic review process, including title/abstract and full-text screening, documentation, and reporting.

The Covidence platform enables collaboration of the entire systematic reviews team and is suitable for researchers and students at all levels of experience.

From a user perspective, the interface is intuitive, and the citation screening is directed step-by-step through a well-defined workflow. Imports and exports are straightforward, with easy export options to Excel and CVS.

Access is free for Cochrane authors (a single reviewer), and Cochrane provides a free trial to other researchers in healthcare. Universities can also subscribe on an institutional basis.

Rayyan is a free and open access web-based platform funded by the Qatar Foundation, a non-profit organisation supporting education and community development initiative . Rayyan is used to screen and code literature through a systematic review process.

Unlike Covidence, Rayyan does not follow a standard SR workflow and simply helps with citation screening. It is accessible through a mobile application with compatibility for offline screening. The web-based platform is known for its accessible user interface, with easy and clear export options.

Function comparison of 5 software tools to support the systematic review process

EPPI-Reviewer

EPPI-Reviewer is a web-based software programme developed by the Evidence for Policy and Practice Information and Co-ordinating Centre  (EPPI) at the UCL Institute for Education, London .

It provides comprehensive functionalities for coding and screening. Users can create different levels of coding in a code set tool for clustering, screening, and administration of documents. EPPI-Reviewer allows direct search and import from PubMed. The import of search results from other databases is feasible in different formats. It stores, references, identifies and removes duplicates automatically. EPPI-Reviewer allows full-text screening, text mining, meta-analysis and the export of data into different types of reports.

There is no limit for concurrent use of the software and the number of articles being reviewed. Cochrane reviewers can access EPPI reviews using their Cochrane subscription details.

EPPI-Centre has other tools for facilitating the systematic review process, including coding guidelines and data management tools.

CADIMA is a free, online, open access review management tool, developed to facilitate research synthesis and structure documentation of the outcomes.

The Julius Institute and the Collaboration for Environmental Evidence established the software programme to support and guide users through the entire systematic review process, including protocol development, literature searching, study selection, critical appraisal, and documentation of the outcomes. The flexibility in choosing the steps also makes CADIMA suitable for conducting systematic mapping and rapid reviews.

CADIMA was initially developed for research questions in agriculture and environment but it is not limited to these, and as such, can be used for managing review processes in other disciplines. It enables users to export files and work offline.

The software allows for statistical analysis of the collated data using the R statistical software. Unlike EPPI-Reviewer, CADIMA does not have a built-in search engine to allow for searching in literature databases like PubMed.

DistillerSR

DistillerSR is an online software maintained by the Canadian company, Evidence Partners which specialises in literature review automation. DistillerSR provides a collaborative platform for every stage of literature review management. The framework is flexible and can accommodate literature reviews of different sizes. It is configurable to different data curation procedures, workflows and reporting standards. The platform integrates necessary features for screening, quality assessment, data extraction and reporting. The software uses Artificial Learning (AL)-enabled technologies in priority screening. It is to cut the screening process short by reranking the most relevant references nearer to the top. It can also use AL, as a second reviewer, in quality control checks of screened studies by human reviewers. DistillerSR is used to manage systematic reviews in various medical disciplines, surveillance, pharmacovigilance and public health reviews including food and nutrition topics. The software does not support statistical analyses. It provides configurable forms in standard formats for data extraction.

DistillerSR allows direct search and import of references from PubMed. It provides an add on feature called LitConnect which can be set to automatically import newly published references from data providers to keep reviews up to date during their progress.

The systematic review Toolbox is a web-based catalogue of various tools, including software packages which can assist with single or multiple tasks within the evidence synthesis process. Researchers can run a quick search or tailor a more sophisticated search by choosing their approach, budget, discipline, and preferred support features, to find the right tools for their research.

If you enjoyed this blog post, you may also be interested in our recently published blog post addressing the difference between a systematic review and a systematic literature review.

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LITERATURE REVIEW SOFTWARE FOR BETTER RESEARCH

“Litmaps is a game changer for finding novel literature... it has been invaluable for my productivity.... I also got my PhD student to use it and they also found it invaluable, finding several gaps they missed”

Varun Venkatesh

Austin Health, Australia

As a full-time researcher, Litmaps has become an indispensable tool in my arsenal. The Seed Maps and Discover features of Litmaps have transformed my literature review process, streamlining the identification of key citations while revealing previously overlooked relevant literature, ensuring no crucial connection goes unnoticed. A true game-changer indeed!

Ritwik Pandey

Doctoral Research Scholar – Sri Sathya Sai Institute of Higher Learning

Using Litmaps for my research papers has significantly improved my workflow. Typically, I start with a single paper related to my topic. Whenever I find an interesting work, I add it to my search. From there, I can quickly cover my entire Related Work section.

David Fischer

Research Associate – University of Applied Sciences Kempten

“It's nice to get a quick overview of related literature. Really easy to use, and it helps getting on top of the often complicated structures of referencing”

Christoph Ludwig

Technische Universität Dresden, Germany

“This has helped me so much in researching the literature. Currently, I am beginning to investigate new fields and this has helped me hugely”

Aran Warren

Canterbury University, NZ

“I can’t live without you anymore! I also recommend you to my students.”

Professor at The Chinese University of Hong Kong

“Seeing my literature list as a network enhances my thinking process!”

Katholieke Universiteit Leuven, Belgium

“Incredibly useful tool to get to know more literature, and to gain insight in existing research”

KU Leuven, Belgium

“As a student just venturing into the world of lit reviews, this is a tool that is outstanding and helping me find deeper results for my work.”

Franklin Jeffers

South Oregon University, USA

“Any researcher could use it! The paper recommendations are great for anyone and everyone”

Swansea University, Wales

“This tool really helped me to create good bibtex references for my research papers”

Ali Mohammed-Djafari

Director of Research at LSS-CNRS, France

“Litmaps is extremely helpful with my research. It helps me organize each one of my projects and see how they relate to each other, as well as to keep up to date on publications done in my field”

Daniel Fuller

Clarkson University, USA

As a person who is an early researcher and identifies as dyslexic, I can say that having research articles laid out in the date vs cite graph format is much more approachable than looking at a standard database interface. I feel that the maps Litmaps offers lower the barrier of entry for researchers by giving them the connections between articles spaced out visually. This helps me orientate where a paper is in the history of a field. Thus, new researchers can look at one of Litmap's "seed maps" and have the same information as hours of digging through a database.

Baylor Fain

Postdoctoral Associate – University of Florida

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Accelerate your research with the best systematic literature review tools

The ideal literature review tool helps you make sense of the most important insights in your research field. ATLAS.ti empowers researchers to perform powerful and collaborative analysis using the leading software for literature review.

Finalize your literature review faster with comfort

ATLAS.ti makes it easy to manage, organize, and analyze articles, PDFs, excerpts, and more for your projects. Conduct a deep systematic literature review and get the insights you need with a comprehensive toolset built specifically for your research projects.

Figure out the "why" behind your participant's motivations

Understand the behaviors and emotions that are driving your focus group participants. With ATLAS.ti, you can transform your raw data and turn it into qualitative insights you can learn from. Easily determine user intent in the same spot you're deciphering your overall focus group data.

Visualize your research findings like never before

We make it simple to present your analysis results with meaningful charts, networks, and diagrams. Instead of figuring out how to communicate the insights you just unlocked, we enable you to leverage easy-to-use visualizations that support your goals.

Paper Search – Access 200+ Million Papers with AI-Powered Insights

Unlock access to over 200 million scientific papers and streamline your research with our cutting-edge AI-powered Paper Search 2.0. Easily find, summarize, and integrate relevant papers directly into your ATLAS.ti Web workspace.

Everything you need to elevate your literature review

Import and organize literature data.

Import and analyze any type of text content – ATLAS.ti supports all standard text and transcription files such as Word and PDF.

Analyze with ease and speed

Utilize easy-to-learn workflows that save valuable time, such as auto coding, sentiment analysis, team collaboration, and more.

Leverage AI-driven tools

Make efficiency a priority and let ATLAS.ti do your work with AI-powered research tools and features for faster results.

Visualize and present findings

With just a few clicks, you can create meaningful visualizations like charts, word clouds, tables, networks, among others for your literature data.

The faster way to make sense of your literature review. Try it for free, today.

A literature review analyzes the most current research within a research area. A literature review consists of published studies from many sources:

• Peer-reviewed academic publications
• Full-length books
• University bulletins
• Conference proceedings
• Dissertations and theses

Literature reviews allow researchers to:

• Summarize the state of the research
• Identify unexplored research inquiries
• Recommend practical applications
• Critique currently published research

Literature reviews are either standalone publications or part of a paper as background for an original research project. A literature review, as a section of a more extensive research article, summarizes the current state of the research to justify the primary research described in the paper.

For example, a researcher may have reviewed the literature on a new supplement's health benefits and concluded that more research needs to be conducted on those with a particular condition. This research gap warrants a study examining how this understudied population reacted to the supplement. Researchers need to establish this research gap through a literature review to persuade journal editors and reviewers of the value of their research.

Consider a literature review as a typical research publication presenting a study, its results, and the salient points scholars can infer from the study. The only significant difference with a literature review treats existing literature as the research data to collect and analyze. From that analysis, a literature review can suggest new inquiries to pursue.

Identify a focus

Similar to a typical study, a literature review should have a research question or questions that analysis can answer. This sort of inquiry typically targets a particular phenomenon, population, or even research method to examine how different studies have looked at the same thing differently. A literature review, then, should center the literature collection around that focus.

Collect and analyze the literature

With a focus in mind, a researcher can collect studies that provide relevant information for that focus. They can then analyze the collected studies by finding and identifying patterns or themes that occur frequently. This analysis allows the researcher to point out what the field has frequently explored or, on the other hand, overlooked.

Suggest implications

The literature review allows the researcher to argue a particular point through the evidence provided by the analysis. For example, suppose the analysis makes it apparent that the published research on people's sleep patterns has not adequately explored the connection between sleep and a particular factor (e.g., television-watching habits, indoor air quality). In that case, the researcher can argue that further study can address this research gap.

External requirements aside (e.g., many academic journals have a word limit of 6,000-8,000 words), a literature review as a standalone publication is as long as necessary to allow readers to understand the current state of the field. Even if it is just a section in a larger paper, a literature review is long enough to allow the researcher to justify the study that is the paper's focus.

Note that a literature review needs only to incorporate a representative number of studies relevant to the research inquiry. For term papers in university courses, 10 to 20 references might be appropriate for demonstrating analytical skills. Published literature reviews in peer-reviewed journals might have 40 to 50 references. One of the essential goals of a literature review is to persuade readers that you have analyzed a representative segment of the research you are reviewing.

Researchers can find published research from various online sources:

• Journal websites
• Research databases
• Search engines (Google Scholar, Semantic Scholar)
• Research repositories
• Social networking sites (Academia, ResearchGate)

Many journals make articles freely available under the term "open access," meaning that there are no restrictions to viewing and downloading such articles. Otherwise, collecting research articles from restricted journals usually requires access from an institution such as a university or a library.

Evidence of a rigorous literature review is more important than the word count or the number of articles that undergo data analysis. Especially when writing for a peer-reviewed journal, it is essential to consider how to demonstrate research rigor in your literature review to persuade reviewers of its scholarly value.

Select field-specific journals

The most significant research relevant to your field focuses on a narrow set of journals similar in aims and scope. Consider who the most prominent scholars in your field are and determine which journals publish their research or have them as editors or reviewers. Journals tend to look favorably on systematic reviews that include articles they have published.

Incorporate recent research

Recently published studies have greater value in determining the gaps in the current state of research. Older research is likely to have encountered challenges and critiques that may render their findings outdated or refuted. What counts as recent differs by field; start by looking for research published within the last three years and gradually expand to older research when you need to collect more articles for your review.

Consider the quality of the research

Literature reviews are only as strong as the quality of the studies that the researcher collects. You can judge any particular study by many factors, including:

• the quality of the article's journal
• the article's research rigor
• the timeliness of the research

The critical point here is that you should consider more than just a study's findings or research outputs when including research in your literature review.

Narrow your research focus

Ideally, the articles you collect for your literature review have something in common, such as a research method or research context. For example, if you are conducting a literature review about teaching practices in high school contexts, it is best to narrow your literature search to studies focusing on high school. You should consider expanding your search to junior high school and university contexts only when there are not enough studies that match your focus.

You can create a project in ATLAS.ti for keeping track of your collected literature. ATLAS.ti allows you to view and analyze full text articles and PDF files in a single project. Within projects, you can use document groups to separate studies into different categories for easier and faster analysis.

For example, a researcher with a literature review that examines studies across different countries can create document groups labeled "United Kingdom," "Germany," and "United States," among others. A researcher can also use ATLAS.ti's global filters to narrow analysis to a particular set of studies and gain insights about a smaller set of literature.

ATLAS.ti allows you to search, code, and analyze text documents and PDF files. You can treat a set of research articles like other forms of qualitative data. The codes you apply to your literature collection allow for analysis through many powerful tools in ATLAS.ti:

• Code Co-Occurrence Explorer
• Code Co-Occurrence Table
• Code-Document Table

Other tools in ATLAS.ti employ machine learning to facilitate parts of the coding process for you. Some of our software tools that are effective for analyzing literature include:

• Named Entity Recognition
• Opinion Mining
• Sentiment Analysis

As long as your documents are text documents or text-enable PDF files, ATLAS.ti's automated tools can provide essential assistance in the data analysis process.

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5 literature review tools to ace your research (+2 bonus tools)

Table of Contents

Your literature review is the lore behind your research paper . It comes in two forms, systematic and scoping , both serving the purpose of rounding up previously published works in your research area that led you to write and finish your own.

A literature review is vital as it provides the reader with a critical overview of the existing body of knowledge, your methodology, and an opportunity for research applications.

Some steps to follow while writing your review:

• Pick an accessible topic for your paper
• Do thorough research and gather evidence surrounding your topic
• Read and take notes diligently or you can use ChatPDF tool for this
• Create a rough structure for your review
• Synthesis your notes and write the first draft
• Edit and proofread your literature review

To make your workload a little lighter, there are many literature review AI tools. These tools can help you find academic articles through AI and answer questions about a research paper.  

Best literature review tools to improve research workflow

A literature review is one of the most critical yet tedious stages in composing a research paper. Many students find it an uphill task since it requires extensive reading and careful organization .

Using some of the best literature review tools listed here, you can make your life easier by overcoming some of the existing challenges in literature reviews. From collecting and classifying to analyzing and publishing research outputs, these tools help you with your literature review and improve your productivity without additional effort or expenses.

1. SciSpace

SciSpace is an AI for academic research that will help find research papers and answer questions about a research paper. You can discover, read, and understand research papers with SciSpace making it an excellent platform for literature review. Featuring a repository with over 270 million research papers, it comes with your AI research assistant called Copilot that offers explanations, summaries , and answers as you read.

Get started now:

Find academic articles through AI

SciSpace has a dedicated literature review tool that finds scientific articles when you search for a question. Based on semantic search, it shows all the research papers relevant for your subject. You can then gather quick insights for all the papers displayed in your search results like methodology, dataset, etc., and figure out all the papers relevant for your research.

Identify relevant articles faster

Abstracts are not always enough to determine whether a paper is relevant to your research question. For starters, you can ask questions to your AI research assistant, SciSpace Copilot to explore the content and better understand the article. Additionally, use the summarize feature to quickly review the methodology and results of a paper and decide if it is worth reading in detail.

Learn in your preferred language

A big barrier non-native English speakers face while conducting a literature review is that a significant portion of scientific literature is published in English. But with SciSpace Copilot, you can review, interact, and learn from research papers in any language you prefer — presently, it supports 75+ languages. The AI will answer questions about a research paper in your mother tongue.

Integrates with Zotero

Many researchers use Zotero to create a library and manage research papers. SciSpace lets you import your scientific articles directly from Zotero into your SciSpace library and use Copilot to comprehend your research papers. You can also highlight key sections, add notes to the PDF as you read, and even turn helpful explanations and answers from Copilot into notes for future review.

Understand math and complex concepts quickly

Come across complex mathematical equations or difficult concepts? Simply highlight the text or select the formula or table, and Copilot will provide an explanation or breakdown of the same in an easy-to-understand manner. You can ask follow-up questions if you need further clarification.

Discover new papers to read without leaving

Highlight phrases or sentences in your research paper to get suggestions for related papers in the field and save time on literature reviews. You can also use the 'Trace' feature to move across and discover connected papers, authors, topics, and more.

SciSpace Copilot is now available as a Chrome extension , allowing you to access its features directly while you browse scientific literature anywhere across the web.

Get citation-backed answers

When you're conducting a literature review, you want credible information with proper references.  Copilot ensures that every piece of information provided by SciSpace Copilot is backed by a direct reference, boosting transparency, accuracy, and trustworthiness.

Ask a question related to the paper you're delving into. Every response from Copilot comes with a clickable citation. This citation leads you straight to the section of the PDF from which the answer was extracted.

By seamlessly integrating answers with citations, SciSpace Copilot assures you of the authenticity and relevance of the information you receive.

2. Mendeley

Mendeley Citation Manager is a free web and desktop application. It helps simplify your citation management workflow significantly. Here are some ways you can speed up your referencing game with Mendeley.

Generate citations and bibliographies

Easily add references from your Mendeley library to your Word document, change your citation style, and create a bibliography, all without leaving your document.

Retrieve references

It allows you to access your references quickly. Search for a term, and it will return results by referencing the year, author, or source.

Add sources to your Mendeley library by dragging PDF to Mendeley Reference Manager. Mendeley will automatically remove the PDF(s) metadata and create a library entry.‌

Read and annotate documents

It helps you highlight and comment across multiple PDFs while keep them all in one place using Mendeley Notebook . Notebook pages are not tied to a reference and let you quote from many PDFs.

A big part of many literature review workflows, Zotero is a free, open-source tool for managing citations that works as a plug-in on your browser. It helps you gather the information you need, cite your sources, lets you attach PDFs, notes, and images to your citations, and create bibliographies.

Import research articles to your database

Search for research articles on a keyword, and add relevant results to your database. Then, select the articles you are most interested in, and import them into Zotero.

Add bibliography in a variety of formats

With Zotero, you don’t have to scramble for different bibliography formats. Simply use the Zotero-Word plug-in to insert in-text citations and generate a bibliography.

Share your research

You can save a paper and sync it with an online library to easily share your research for group projects. Zotero can be used to create your database and decrease the time you spend formatting citations.

Sysrev is an AI too for article review that facilitates screening, collaboration, and data extraction from academic publications, abstracts, and PDF documents using machine learning. The platform is free and supports public and Open Access projects only.

Some of the features of Sysrev include:

Group labels

Group labels can be a powerful concept for creating database tables from documents. When exported and re-imported, each group label creates a new table. To make labels for a project, go into the manage -> labels section of the project.

Group labels enable project managers to pull table information from documents. It makes it easier to communicate review results for specific articles.

Track reviewer performance

Sysrev's label counting tool provides filtering and visualization options for keeping track of the distribution of labels throughout the project's progress. Project managers can check their projects at any point to track progress and the reviewer's performance.

Tool for concordance

The Sysrev tool for concordance allows project administrators and reviewers to perform analysis on their labels. Concordance is measured by calculating the number of times users agree on the labels they have extracted.

Colandr is a free, open-source, internet-based analysis and screening software used as an AI for academic research. It was designed to ease collaboration across various stages of the systematic review procedure. The tool can be a little complex to use. So, here are the steps involved in working with Colandr.

Create a review

The first step to using Colandr is setting up an organized review project. This is helpful to librarians who are assisting researchers with systematic reviews.

The planning stage is setting the review's objectives along with research queries. Any reviewer can review the details of the planning stage. However, they can only be modified by the author for the review.

Citation screening/import

In this phase, users can upload their results from database searches. Colandr also offers an automated deduplication system.

Full-text screening

The system in Colandr will discover the combination of terms and expressions that are most useful for the reader. If an article is selected, it will be moved to the final step.

Data extraction/export

Colandr data extraction is more efficient than the manual method. It creates the form fields for data extraction during the planning stage of the review procedure. Users can decide to revisit or modify the form for data extraction after completing the initial screening.

Bonus literature review tools

SRDR+ is a web-based tool for extracting and managing systematic review or meta-analysis data. It is open and has a searchable archive of systematic reviews and their data.

7. Plot Digitizer

Plot Digitizer is an efficient tool for extracting information from graphs and images, equipped with many features that facilitate data extraction. The program comes with a free online application, which is adequate to extract data quickly.

Final thoughts

Writing a literature review is not easy. It’s a time-consuming process, which can become tiring at times. The literature review tools mentioned in this blog do an excellent job of maximizing your efforts and helping you write literature reviews much more efficiently. With them, you can breathe a sigh of relief and give more time to your research.

As you dive into your literature review, don’t forget to use SciSpace ResearchGPT to streamline the process. It facilitates your research and helps you explore key findings, summary, and other components of the paper easily.

Frequently Asked Questions (FAQs)

1. what is rrl in research.

RRL stands for Review of Related Literature and sometimes interchanged with ‘Literature Review.’ RRL is a body of studies relevant to the topic being researched. These studies may be in the form of journal articles, books, reports, and other similar documents. Review of related literature is used to support an argument or theory being made by the researcher, as well as to provide information on how others have approached the same topic.

2. What are few softwares and tools available for literature review?

• SciSpace Discover

• Mendeley

• Zotero

• Sysrev

• Colandr

• SRDR+

3. How to generate an online literature review?

The Scispace Discover tool, which offers an excellent repository of millions of peer-reviewed articles and resources, will help you generate or create a literature review easily. You may find relevant information by utilizing the filter option, checking its credibility, tracing related topics and articles, and citing in widely accepted formats with a single click.

4. What does it mean to synthesize literature?

To synthesize literature is to take the main points and ideas from a number of sources and present them in a new way. The goal is to create a new piece of writing that pulls together the most important elements of all the sources you read. Make recommendations based on them, and connect them to the research.

5. Should we write abstract for literature review?

Abstracts, particularly for the literature review section, are not required. However, an abstract for the research paper, on the whole, is useful for summarizing the paper and letting readers know what to expect from it. It can also be used to summarize the main points of the paper so that readers have a better understanding of the paper's content before they read it.

6. How do you evaluate the quality of a literature review?

• Whether it is clear and well-written.

• Whether Information is current and up to date.

• Does it cover all of the relevant sources on the topic.

• Does it provide enough evidence to support its conclusions.

7. Is literature review mandatory?

Yes. Literature review is a mandatory part of any research project. It is a critical step in the process that allows you to establish the scope of your research and provide a background for the rest of your work.

8. What are the sources for a literature review?

• Reports

• Theses

• Conference proceedings

• Company reports

• Some government publications

• Journals

• Books

• Newspapers

• Articles by professional associations

• Indexes

• Databases

• Catalogues

• Encyclopaedias

• Dictionaries

• Bibliographies

• Citation indexes

• Statistical data from government websites

9. What is the difference between a systematic review and a literature review?

A systematic review is a form of research that uses a rigorous method to generate knowledge from both published and unpublished data. A literature review, on the other hand, is a critical summary of an area of research within the context of what has already been published.

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7 open source tools to make literature reviews easy

Opensource.com

A good literature review is critical for academic research in any field, whether it is for a research article, a critical review for coursework, or a dissertation. In a recent article, I presented detailed steps for doing  a literature review using open source software .

The following is a brief summary of seven free and open source software tools described in that article that will make your next literature review much easier.

1. GNU Linux

Most literature reviews are accomplished by graduate students working in research labs in universities. For absurd reasons, graduate students often have the worst computers on campus. They are often old, slow, and clunky Windows machines that have been discarded and recycled from the undergraduate computer labs. Installing a flavor of GNU Linux will breathe new life into these outdated PCs. There are more than 100 distributions , all of which can be downloaded and installed for free on computers. Most popular Linux distributions come with a "try-before-you-buy" feature. For example, with Ubuntu you can make a bootable USB stick that allows you to test-run the Ubuntu desktop experience without interfering in any way with your PC configuration. If you like the experience, you can use the stick to install Ubuntu on your machine permanently.

Linux distributions generally come with a free web browser, and the most popular is Firefox . Two Firefox plugins that are particularly useful for literature reviews are Unpaywall and Zotero. Keep reading to learn why.

3. Unpaywall

Often one of the hardest parts of a literature review is gaining access to the papers you want to read for your review. The unintended consequence of copyright restrictions and paywalls is it has narrowed access to the peer-reviewed literature to the point that even Harvard University is challenged to pay for it. Fortunately, there are a lot of open access articles—about a third of the literature is free (and the percentage is growing). Unpaywall is a Firefox plugin that enables researchers to click a green tab on the side of the browser and skip the paywall on millions of peer-reviewed journal articles. This makes finding accessible copies of articles much faster that searching each database individually. Unpaywall is fast, free, and legal, as it accesses many of the open access sites that I covered in my paper on using open source in lit reviews .

Formatting references is the most tedious of academic tasks. Zotero can save you from ever doing it again. It operates as an Android app, desktop program, and a Firefox plugin (which I recommend). It is a free, easy-to-use tool to help you collect, organize, cite, and share research. It replaces the functionality of proprietary packages such as RefWorks, Endnote, and Papers for zero cost. Zotero can auto-add bibliographic information directly from websites. In addition, it can scrape bibliographic data from PDF files. Notes can be easily added on each reference. Finally, and most importantly, it can import and export the bibliography databases in all publishers' various formats. With this feature, you can export bibliographic information to paste into a document editor for a paper or thesis—or even to a wiki for dynamic collaborative literature reviews (see tool #7 for more on the value of wikis in lit reviews).

5. LibreOffice

Your thesis or academic article can be written conventionally with the free office suite LibreOffice , which operates similarly to Microsoft's Office products but respects your freedom. Zotero has a word processor plugin to integrate directly with LibreOffice. LibreOffice is more than adequate for the vast majority of academic paper writing.

If LibreOffice is not enough for your layout needs, you can take your paper writing one step further with LaTeX , a high-quality typesetting system specifically designed for producing technical and scientific documentation. LaTeX is particularly useful if your writing has a lot of equations in it. Also, Zotero libraries can be directly exported to BibTeX files for use with LaTeX.

7. MediaWiki

If you want to leverage the open source way to get help with your literature review, you can facilitate a dynamic collaborative literature review . A wiki is a website that allows anyone to add, delete, or revise content directly using a web browser. MediaWiki is free software that enables you to set up your own wikis.

Researchers can (in decreasing order of complexity): 1) set up their own research group wiki with MediaWiki, 2) utilize wikis already established at their universities (e.g., Aalto University ), or 3) use wikis dedicated to areas that they research. For example, several university research groups that focus on sustainability (including mine ) use Appropedia , which is set up for collaborative solutions on sustainability, appropriate technology, poverty reduction, and permaculture.

Using a wiki makes it easy for anyone in the group to keep track of the status of and update literature reviews (both current and older or from other researchers). It also enables multiple members of the group to easily collaborate on a literature review asynchronously. Most importantly, it enables people outside the research group to help make a literature review more complete, accurate, and up-to-date.

Wrapping up

Free and open source software can cover the entire lit review toolchain, meaning there's no need for anyone to use proprietary solutions. Do you use other libre tools for making literature reviews or other academic work easier? Please let us know your favorites in the comments.

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Synthesis provides advanced literature review software with analytical and automation functionality for delivering timely evidence-based information in hours, not months, for better decisions.

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Synthesis organizes and manages all your references and PDFs. You can then quickly search the Abstract and Full-Text PDFs for keywords and phrases.

Advanced Analytics

Quickly summarize the reference by searching and tagging for keywords, preform topic clustering or word clouds on the literature, and then graph all your data.

Multiple Databases

PubMed, PubMed Central, IEEE, US Patents, Ovid (Medline, Embase, Global Health), Web of Science, Scopus, ProQuest, and many others..

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Synthesis is used in academic research universities, hospitals, government agencies, private corporations and non-governmental organziations throughout the world.

Synthesis applies the latest in automation and enhanced analytic functionality for improving the efficiency and effectiveness of conducting literature reviews...

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Synthesis provides online embedded searching on major bibliographical databases, validated automated de-duplication of references, automated importing of PDFs, methods to analyze the literature, and many more features.

Synthesis is available for Windows, Macintosh, Linux and as a Java application that can be run on any platform.

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Synthesis Research Inc is a software development company focused on improving the way that literature is managed and analyzed. This desire is based around the goal of providing the best synthesized knowledge for supporting evidence-based decision making.

Synthesis Research Inc applies the latest computer science algorithms based around automation and information retrieval and management for improving the efficiency and effectiveness of conducting literature reviews through automating manual processes and enhancing the workflow.

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Global research organizations, including 70% of the top 10 pharmaceutical and medical device companies, trust DistillerSR software to produce transparent, audit-ready, and regulatory-compliant literature reviews.

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10 Open Science Tools for Literature Review You Should Know about

Here are 10 literature search tools that will make your scientific literature search faster and more convenient. All of the presented literature review software is free and follows Open Science principles.

Traditionally, scientific literature has been tucked away behind paywalls of academic publishers. Not only is the access to papers often restricted, but subscriptions are required to use many scientific search engines. This practice discriminates against universities and institutions who cannot afford the licenses, e.g. in low-income countries. Closed publishing also makes it hard for persons not affiliated with research institutes, such as freelance journalists or the public, to learn about scientific discoveries. 

The proportion of research accessible publicly today at no cost varies between disciplines . While in the biomedical sciences and mathematics, the majority of research published between 2009 and 2015 was openly accessible, this held true only for around 15 percent of publications in chemistry. Luckily, the interest in open access publishing is steadily increasing and has gained momentum in the past decade or so.

Many governmental funding bodies around the world nowadays require science resulting from grant money they provided to be available publicly for free. The exact requirements vary and UNESCO is currently developing a framework that specifies standards for the whole area of Open Science. 

Once I started my research on the topic, I was astonished by just how many free Open Science tools for literature review already exist! Read on below for 10 literature search tools — from a search engines for research papers, over literature review software that helps you quickly find open access versions of papers, to tools that help you save the correct citation in one click.

Tools for Literature review

First, an overview of the literature search tools in this blog post:

ScienceOpen

• Citation Gecko
• Local Citation Network

ResearchRabbit

• Open Access Button
• EndNote Click

Read by QxMD

I divided the tools into four categories:

Search engines for research papers

• Literature review software based on citation networks
• Locating open access scientific papers, and
• Other tools that help in the literature review

Here, we go!

The best place to start a scientific literature search is with a search engine for research papers. Here are two you might not have heard of!

Want to perform a literature search and don’t want to pay for Web of Science or Scopus or perhaps you are tired of the limited functionality of the free Google Scholar ? ScienceOpen is many things, among others a search engine for research papers. Despite being owned by a private company, this scientific search engine is freely accessible with visually appealing and functional design. Search results are clearly labelled for type of publication, number of citations, altmetrics scores etc. and allow for filtering. You can also access citation metrics, i.e., display which publications have cited a certain paper.

Recommended by a reader of the blog (thank you!), the Lens is a search tool that doesn’t only allow you to search the scholarly literature but patents too! Millions of patents from over 95 jurisdictions can be searched. The Lens is run by the non-profit social enterprise Cambia. The search engine is free to use for the public, though charges occur for commercial use and to get additional functionality.

Literature Review software based on citation networks

The next category of tools we will be looking at are a bit more advanced than a simple search engine for research papers. These literature search tools help you discover scientific literature you may have missed by visualising citation networks.

Citation Gecko 

The literature search tool Citation Gecko is an open source web app that makes it easier to discover relevant scientific literature than your average keyword-based search engine for research papers. It works in the following way: First you upload about 5-6 “seed papers”. The program then extracts all references in and to these seed papers and creates a visual citation network. The nodes are displayed in different colours and sizes depending on whether the papers are citing a seed paper or are cited by it and how many, respectively. By combing through the citation network, you can discover new papers that may be relevant for your scientific literature search. You can also increase your citation network step by step by including more seed papers. 

This literature review tool was developed by Barney Walker , and the underlying citation data is provided by Crossref and Open Citations .

Local Citation Network 

Similar to Citation Gecko, Local Citation Network is an open source tool that works as a scientific search engine on steroids. Local Citation Network was developed by Physician Scientist Tim Wölfle. This literature review tool works best if you feed it with a larger library of seed papers than required for Citation Gecko. Therefore, Wölfle recommends using it at the end of your scientific literature search to identify papers you may have missed. 

As an alternative to the literature search tools Citation Gecko and Local Citation Network, a reader of the blog recommended ResearchRabbit . It’s free to use and looks like a versatile piece of literature review software helping you build your own citation network. ResearchRabbit lets you add labels to the entries in your citation network, download PDFs of papers and sign up for email alerts for new papers related to your research topic. Instead of a tool to use only once during your scientific literature search, ResearchRabbit seems to function more like a private scientific library storing (and connecting) all the papers in your field.

Run by (former) researchers and engineers, ResearchRabbit is partly financed through donations but their website does not state where the core funding of this literature review software originates from.

Locating open access scientific papers

You may face the problem in your scientific literature search that you don’t have access to every research paper you are interested in. I highly recommend installing at least one of the open access tools below so you can quickly locate freely accessible versions of the scientific literature if available anywhere.

Open Access Button 

Works like the scientific search engine Sci-hub but is legal: You enter the DOI, link or citation of a paper and the literature review tool Open Access Button displays it if freely accessible anywhere. To find an open access version, Open Access Button searches thousands of repositories, for example, preprint servers, authors’ personal pages, open access journals and other aggregators such as the COnnecting REpositories service based at The Open University in the UK ( CORE ), the EU-funded OpenAire infrastructure, and the US community initiative Share . 

If the article you are looking for isn’t freely available, Open Access Button asks the author to share it to a repository. You can enter your email address to be notified once it has become available. 

Open Access Button is also available as browser plugin, which means that a button appears next to an article whenever a free version is available. This search engine for research papers is funded by non-profit foundations and is open source. 

Unpaywall 

Unpaywall is a search engine for research papers similar to Open Access Button — but only available as browser plugin. If the article you are looking at is behind a paywall but freely accessible somewhere else, a green button appears on the right side of the article. I installed it recently and regret not having done it sooner, it works really smoothly! I think the plugin is a great help in your scientific literature search.

Unpaywall is run by the non-profit organisation Our Research who has created a fleet of open science tools.

EndNote Click 

Another browser extension that lets you access the scientific literature for free if available is EndNote Click (formerly Kopernio). EndNote Click claims to be faster than other search engines for research papers bypassing redirects and verification steps. I personally don’t find the Unpaywall or Open Access Button plugins inconvenient to use but I’d encourage you to try out all of these scientific search engines and see what works best for you. 

One advantage of EndNote Click that a reader of the blog told me about is the side bar that appears when opening a paper through the plugin. It lets you, for example, save citations quickly, avoiding time-consuming searches on publishers’ websites. 

As the reference manager, EndNote Click is part of the research analytics company Clarivate.  

Other tools for literature review

This last category of literature search tools features a tool that creates a personalised feed of scientific literature for you and another that makes citing the scientific literature effortless.

Available as an app or in a browser window, the literature review tool Read lets you create a personalised feed that is updated daily with new papers on research topics or from journals of your choice. If there is an openly accessible version of an article, you can read it with one click. If your institution has journal subscriptions, you can also link them to your Read profile. Read has been created by the company QxMD and is free to use. 

CiteAs 

You discovered a promising paper in your scientific literature search and want to cite it? CiteAs is a convenient literature review tool to obtain the correct citation for any publication, preprint, software or dataset in one click. Funded by the Alfred P. Sloan Foundation, CiteAs is operated partly by the non-profit Our Research . 

Beyond literature review tools

There you have it, 10 tools for literature review that are all completely free and follow Open Science principles.

Of course, finding a great literature review tool, such as a search engine for research papers or a citation tool, is only one essential part in the whole process of writing a scientific paper. If you would like to learn a complete process to write a scientific article step by step, then you’ll love our free training. Simply click on the orange button below to watch it now (or sign up to watch it later).

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Living systematic review software, optimized for clinical literature. Scroll

Autolit + synthesis:.

Nested Knowledge ® offers a comprehensive software platform for systematic literature review and meta-analysis. The software is composed of two parts which work in tandem. Search, screen, extract data, and complete critical appraisal with AutoLit ® . Visualize, analyze, publish and share insights with Synthesis.

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Search, Import, or Bibliomine.

Literature search.

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If you add studies to AutoLit, we’ll trace the path of studies from Search to Synthesis.

Use AI to find relevant concepts.

Automatic PICO highlighting, or your own keywords, directs your eye to the key phrases from any abstract.

Inclusion Prediction AI can anticipate which studies are most relevant to your research question.

Dual Screening can help you quality-control your decisions, so only the studies that actually contain data relevant to you make it through.

If you screen out irrelevant references in AutoLit, we’ll automatically generate your PRISMA diagram in Synthesis.

Connect concepts across the literature.

You understand how key concepts in your field relate to each other – but those ideas are stuck in your head unless you lay them out for your readers.

By building a tagging hierarchy, you structure your ideas. By applying those tags to the studies in your review, you capture the evidence to support each concept.

We help out by enabling you to borrow from past hierarchies, create tags ‘on the fly’ as you read studies, and by connecting your tags to the quantitative data you’ll extract.

If you build and apply your hierarchy in AutoLit, we’ll also create interactive, qualitative visuals in Synthesis.

Continuous. Dichotomous. Categorical.

Meta-analytical data extraction.

Turn your tags into data elements to connect your qualitative and quantitative concepts. 

Identify which part of your hierarchy contains your interventions of interest.

Then, you’re all set to gather continuous, dichotomous and categorical metrics across multiple arms and time points from the text and tables in your studies of interest.

If you gather data in AutoLit, we’ll summarize and analyze your quantitative findings in Synthesis.

Publish, Share, Visualize with Synthesis:

Catch a ray from the qualitative sunburst..

Qualitative Synthesis

Tagging in AutoLit continuously and automatically updates Qualitative Synthesis.

Each segment of the sunburst diagram represents a concept you tagged, and immediately directs your readers to the underlying studies.

Try it!  Select one or more of the segments in the sunburst to filter the studies from our sample review on strokes that impact the brain stem to those that report on your concept of interest. Then, select a study from the list to view the abstract and gathered data.

Was this published? Yes, as a part of our  Stanford collaboration .

What are the odds? Drill into the Data.

Quantitative synthesis.

Gathering data in AutoLit continuously and automatically updates Quantitative Synthesis.

We slice the data three ways. First, we summarize your findings at the intervention and study level in Summary. Then, we let you create scatter plots of findings in Distribution. Finally, we compute odds ratios and build forest plots in our Network Meta-Analysis.

Was this published? Yes, as a part of our  Stanford collaboration .

Excel beyond words.

Draft in Manuscript Editor, and you’ll never need to update your data manually. Whenever you add data to your review, we add it automatically to your tables!

Rich text, point-and-click citation tools, auto-updating tables, and embeddable Synthesis visuals.

Was this published? Yes, as a part of our  Stanford collaboration .

Living Systematic Reviews

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Fine-tune your literature search.

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Select phrases or specific sections and explore more research papers related to the core aspects of your selections. Pin the useful ones for future references.

Our platform brings you the latest research related to your and project work.

Speed up your literature review

Quickly generate a summary of key sections of any paper with our summarizer.

Make informed decisions about which papers are relevant, and where to invest your time in further reading.

Get key insights from the paper, quickly comprehend the paper’s unique approach, and recall the key points.

Bring order to your research projects

Organize your reading lists into different projects and maintain the context of your research.

Quickly sort items into collections and tag or filter them according to keywords and color codes.

Experience the power of sharing by finding all the shared literature at one place.

Decode papers effortlessly for faster comprehension

Highlight what is important so that you can retrieve it faster next time.

Select any text in the paper and ask Copilot to explain it to help you get a deeper understanding.

Ask questions and follow-ups from AI-powered Copilot.

Collaborate to read with your team, professors, or students

Share and discuss literature and drafts with your study group, colleagues, experts, and advisors. Recommend valuable resources and help each other for better understanding.

Work in shared projects efficiently and improve visibility within your study group or lab members.

Keep track of your team's progress by being constantly connected and engaging in active knowledge transfer by requesting full access to relevant papers and drafts.

Find papers from across the world's largest repositories

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Everything you add or create on Enago Read is private by default. It is visible if and when you share it with other users.

You can put Creative Commons license on original drafts to protect your IP. For shared files, Enago Read always maintains a copy in case of deletion by collaborators or revoked access.

We use state-of-the-art security protocols and algorithms including MD5 Encryption, SSL, and HTTPS to secure your data.

Literature Review with MAXQDA

Interview transcription examples, make the most out of your literature review.

Literature reviews are an important step in the data analysis journey of many research projects, but often it is a time-consuming and arduous affair. Whether you are reviewing literature for writing a meta-analysis or for the background section of your thesis, work with MAXQDA. Our product comes with many exciting features which make your literature review faster and easier than ever before. Whether you are a first-time researcher or an old pro, MAXQDA is your professional software solution with advanced tools for you and your team.

How to conduct a literature review with MAXQDA

Conducting a literature review with MAXQDA is easy because you can easily import bibliographic information and full texts. In addition, MAXQDA provides excellent tools to facilitate each phase of your literature review, such as notes, paraphrases, auto-coding, summaries, and tools to integrate your findings.

Step one: Plan your literature review

Similar to other research projects, one should carefully plan a literature review. Before getting started with searching and analyzing literature, carefully think about the purpose of your literature review and the questions you want to answer. This will help you to develop a search strategy which is needed to stay on top of things. A search strategy involves deciding on literature databases, search terms, and practical and methodological criteria for the selection of high-quality scientific literature.

MAXQDA supports you during this stage with memos and the newly developed Questions-Themes-Theories tool (QTT). Both are the ideal place to store your research questions and search parameters. Moreover, the Question-Themes-Theories tool is perfectly suited to support your literature review project because it provides a bridge between your MAXQDA project and your research report. It offers the perfect enviornment to bring together findings, record conclusions and develop theories.

Step two: Search, Select, Save your material

Follow your search strategy. Use the databases and search terms you have identified to find the literature you need. Then, scan the search results for relevance by reading the title, abstract, or keywords. Try to determine whether the paper falls within the narrower area of the research question and whether it fulfills the objectives of the review. In addition, check whether the search results fulfill your pre-specified eligibility criteria. As this step typically requires precise reading rather than a quick scan, you might want to perform it in MAXQDA. If the piece of literature fulfills your criteria and context, you can save the bibliographic information using a reference management system which is a common approach among researchers as these programs automatically extract a paper’s meta-data from the publishing website. You can easily import this bibliographic data into MAXQDA via a specialized import tool. MAXQDA is compatible with all reference management programs that are able to export their literature databases in RIS format which is a standard format for bibliographic information. This is the case with all mainstream literature management programs such as Citavi, DocEar, Endnote, JabRef, Mendeley, and Zotero.

Step three: Import & Organize your material in MAXQDA

Importing bibliographic data into MAXQDA is easy and works seamlessly for all reference management programs that use the standard RIS files. MAXQDA offers an import option dedicated to bibliographic data which you can find in the MAXQDA Import tab. To import the selected literature, just click on the corresponding button, select the data you want to import, and click okay. Upon import, each literature entry becomes its own text document. If full texts are imported, MAXQDA automatically connects the full text to the literature entry with an internal link. The individual information in the literature entries is automatically coded for later analysis so that, for example, all titles or abstracts can be compiled and searched. To help you keeping your literature (review) organized, MAXQDA automatically creates a document group called “References” which contains the individual literature entries. Like full texts or interview documents, the bibliographic entries can be searched, coded, linked, edited, and you can add memos for further qualitative and quantitative content analysis (Kuckartz & Rädiker, 2019). Especially, when running multiple searches using different databases or search terms, you should carefully document your approach. Besides being a great place to store the respective search parameters, memos are perfectly suited to capture your ideas while reviewing our literature and can be attached to text segments, documents, document groups, and much more.

Analyze your literature with MAXQDA

Once imported into MAXQDA, you can explore your material using a variety of tools and functions. With MAXQDA as your literature review & analysis software, you have numerous possibilities for analyzing your literature and writing your literature review – impossible to mention all. Thus, we can present only a subset of tools here. Check out our literature about performing literature reviews with MAXQDA to discover more possibilities.

AI Assist: Introducing AI to literature reviews

AI Assist – MAXQDA’s AI-based add-on module – can simplify your literature reviews in many ways. Chat with your data and ask the AI questions about your documents. Let AI Assist automatically summarize entire papers and text segments. Automatically create summaries of all coded segments of a code or generate suggestions for subcodes, and if you don’t know a word’s or concept’s meaning, use AI Assist to get a definition without leaving MAXQDA. Visit our research guide for even more ideas on how AI can support your literature review:

AI for Literature Review

Code & Retrieve important segments

Coding qualitative data lies at the heart of many qualitative data analysis approaches and can be useful for literature reviews as well. Coding refers to the process of labeling segments of your material. For example, you may want to code definitions of certain terms, pro and con arguments, how a specific method is used, and so on. In a later step, MAXQDA allows you to compile all text segments coded with one (or more) codes of interest from one or more papers, so that you can for example compare definitions across papers.

But there is more. MAXQDA offers multiple ways of coding, such as in-vivo coding, highlighters, emoticodes, Creative Coding, or the Smart Coding Tool. The compiled segments can be enriched with variables and the segment’s context accessed with just one click. MAXQDA’s Text Search & Autocode tool is especially well-suited for a literature review, as it allows one to explore large amounts of text without reading or coding them first. Automatically search for keywords (or dictionaries of keywords), such as important concepts for your literature review, and automatically code them with just a few clicks.

Paraphrase literature into your own words

Another approach is to paraphrase the existing literature. A paraphrase is a restatement of a text or passage in your own words, while retaining the meaning and the main ideas of the original. Paraphrasing can be especially helpful in the context of literature reviews, because paraphrases force you to systematically summarize the most important statements (and only the most important statements) which can help to stay on top of things.

With MAXQDA as your literature review software, you not only have a tool for paraphrasing literature but also tools to analyze the paraphrases you have written. For example, the Categorize Paraphrases tool (allows you to code your parpahrases) or the Paraphrases Matrix (allows you to compare paraphrases side-by-side between individual documents or groups of documents.)

Summaries & Overview tables: A look at the Bigger Picture

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

Visualize your qualitative data

The proverb “a picture is worth a thousand words” also applies to literature reviews. That is why MAXQDA offers a variety of Visual Tools that allow you to get a quick overview of the data, and help you to identify patterns. Of course, you can export your visualizations in various formats to enrich your final report. One particularly useful visual tool for literature reviews is the Word Cloud. It visualizes the most frequent words and allows you to explore key terms and the central themes of one or more papers. Thanks to the interactive connection between your visualizations with your MAXQDA data, you will never lose sight of the big picture. Another particularly useful tool is MAXQDA’s word/code frequency tool with which you can analyze and visualize the frequencies of words or codes in one or more documents. As with Word Clouds, nonsensical words can be added to the stop list and excluded from the analysis.

QTT: Synthesize your results and write up the review

MAXQDA has an innovative workspace to gather important visualization, notes, segments, and other analytics results. The perfect tool to organize your thoughts and data. Create a separate worksheet for your topics and research questions, fill it with associated analysis elements from MAXQDA, and add your conclusions, theories, and insights as you go. For example, you can add Word Clouds, important coded segments, and your literature summaries and write down your insights. Subsequently, you can view all analysis elements and insights to write your final conclusion. The Questions-Themes-Theories tool is perfectly suited to help you finalize your literature review reports. With just one click you can export your worksheet and use it as a starting point for your literature review report.

Literature about Literature Reviews and Analysis

We offer a variety of free learning materials to help you get started with your literature review. Check out our Getting Started Guide to get a quick overview of MAXQDA and step-by-step instructions on setting up your software and creating your first project with your brand new QDA software. In addition, the free Literature Reviews Guide explains how to conduct a literature review with MAXQDA in more detail.

Getting Started with MAXQDA

Literature Reviews with MAXQDA

A literature review is a critical analysis and summary of existing research and literature on a particular topic or research question. It involves systematically searching and evaluating a range of sources, such as books, academic journals, conference proceedings, and other published or unpublished works, to identify and analyze the relevant findings, methodologies, theories, and arguments related to the research question or topic.

A literature review’s purpose is to provide a comprehensive and critical overview of the current state of knowledge and understanding of a topic, to identify gaps and inconsistencies in existing research, and to highlight areas where further research is needed. Literature reviews are commonly used in academic research, as they provide a framework for developing new research and help to situate the research within the broader context of existing knowledge.

A literature review is a critical evaluation of existing research on a particular topic and is part of almost every research project. The literature review’s purpose is to identify gaps in current knowledge, synthesize existing research findings, and provide a foundation for further research. Over the years, numerous types of literature reviews have emerged. To empower you in coming to an informed decision, we briefly present the most common literature review methods.

• Narrative Review : A narrative review summarizes and synthesizes the existing literature on a particular topic in a narrative or story-like format. This type of review is often used to provide an overview of the current state of knowledge on a topic, for example in scientific papers or final theses.
• Systematic Review : A systematic review is a comprehensive and structured approach to reviewing the literature on a particular topic with the aim of answering a defined research question. It involves a systematic search of the literature using pre-specified eligibility criteria and a structured evaluation of the quality of the research.
• Meta-Analysis : A meta-analysis is a type of systematic review that uses statistical techniques to combine and analyze the results from multiple studies on the same topic. The goal of a meta-analysis is to provide a more robust and reliable estimate of the effect size than can be obtained from any single study.
• Scoping Review : A scoping review is a type of systematic review that aims to map the existing literature on a particular topic in order to identify the scope and nature of the research that has been done. It is often used to identify gaps in the literature and inform future research.

There is no “best” way to do a literature review, as the process can vary depending on the research question, field of study, and personal preferences. However, here are some general guidelines that can help to ensure that your literature review is comprehensive and effective:

• Carefully plan your literature review : Before you start searching and analyzing literature you should define a research question and develop a search strategy (for example identify relevant databases, and search terms). A clearly defined research question and search strategy will help you to focus your search and ensure that you are gathering relevant information. MAXQDA’s Questions-Themes-Theories tool is the perfect place to store your analysis plan.
• Evaluate your sources : Screen your search results for relevance to your research question, for example by reading abstracts. Once you have identified relevant sources, read them critically and evaluate their quality and relevance to your research question. Consider factors such as the methodology used, the reliability of the data, and the overall strength of the argument presented.
• Synthesize your findings : After evaluating your sources, synthesize your findings by identifying common themes, arguments, and gaps in the existing research. This will help you to develop a comprehensive understanding of the current state of knowledge on your topic.
• Write up your review : Finally, write up your literature review, ensuring that it is well-structured and clearly communicates your findings. Include a critical analysis of the sources you have reviewed, and use evidence from the literature to support your arguments and conclusions.

Overall, the key to a successful literature review is to be systematic, critical, and comprehensive in your search and evaluation of sources.

As in all aspects of scientific work, preparation is the key to success. Carefully think about the purpose of your literature review, the questions you want to answer, and your search strategy. The writing process itself will differ depending on the your literature review method. For example, when writing a narrative review use the identified literature to support your arguments, approach, and conclusions. By contrast, a systematic review typically contains the same parts as other scientific papers: Abstract, Introduction (purpose and scope), Methods (Search strategy, inclusion/exclusion characteristics, …), Results (identified sources, their main arguments, findings, …), Discussion (critical analysis of the sources you have reviewed), Conclusion (gaps or inconsistencies in the existing research, future research, implications, etc.).

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• Volume 28, Issue 6
• Rapid reviews methods series: Guidance on literature search
• Article Text
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• http://orcid.org/0000-0001-6644-9845 Irma Klerings 1 ,
• Shannon Robalino 2 ,
• http://orcid.org/0000-0003-4808-3880 Andrew Booth 3 ,
• http://orcid.org/0000-0002-2903-6870 Camila Micaela Escobar-Liquitay 4 ,
• Isolde Sommer 1 ,
• http://orcid.org/0000-0001-5531-3678 Gerald Gartlehner 1 , 5 ,
• Declan Devane 6 , 7 ,
• Siw Waffenschmidt 8
• On behalf of the Cochrane Rapid Reviews Methods Group
• 1 Department for Evidence-Based Medicine and Evaluation , University of Krems (Danube University Krems) , Krems , Niederösterreich , Austria
• 2 Center for Evidence-based Policy , Oregon Health & Science University , Portland , Oregon , USA
• 3 School of Health and Related Research (ScHARR) , The University of Sheffield , Sheffield , UK
• 4 Research Department, Associate Cochrane Centre , Instituto Universitario Escuela de Medicina del Hospital Italiano de Buenos Aires , Buenos Aires , Argentina
• 5 RTI-UNC Evidence-based Practice Center , RTI International , Research Triangle Park , North Carolina , USA
• 6 School of Nursing & Midwifery, HRB TMRN , National University of Ireland Galway , Galway , Ireland
• 7 Evidence Synthesis Ireland & Cochrane Ireland , University of Galway , Galway , Ireland
• 8 Information Management Department , Institute for Quality and Efficiency in Healthcare , Cologne , Germany
• Correspondence to Irma Klerings, Department for Evidence-based Medicine and Evaluation, Danube University Krems, Krems, Niederösterreich, Austria; irma.klerings{at}donau-uni.ac.at

This paper is part of a series of methodological guidance from the Cochrane Rapid Reviews Methods Group. Rapid reviews (RR) use modified systematic review methods to accelerate the review process while maintaining systematic, transparent and reproducible methods. In this paper, we address considerations for RR searches. We cover the main areas relevant to the search process: preparation and planning, information sources and search methods, search strategy development, quality assurance, reporting, and record management. Two options exist for abbreviating the search process: (1) reducing time spent on conducting searches and (2) reducing the size of the search result. Because screening search results is usually more resource-intensive than conducting the search, we suggest investing time upfront in planning and optimising the search to save time by reducing the literature screening workload. To achieve this goal, RR teams should work with an information specialist. They should select a small number of relevant information sources (eg, databases) and use search methods that are highly likely to identify relevant literature for their topic. Database search strategies should aim to optimise both precision and sensitivity, and quality assurance measures (peer review and validation of search strategies) should be applied to minimise errors.

• Evidence-Based Practice
• Systematic Reviews as Topic
• Information Science

Data availability statement

No data are available.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjebm-2022-112079

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Compared with systematic reviews, rapid reviews (RR) often abbreviate or limit the literature search in some way to accelerate review production. However, RR guidance rarely specifies how to select topic-appropriate search approaches.

WHAT THIS STUDY ADDS

This paper presents an overview of considerations and recommendations for RR searching, covering the complete search process from the planning stage to record management. We also provide extensive appendices with practical examples, useful sources and a glossary of terms.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

There is no one-size-fits-all solution for RR literature searching: review teams should consider what search approaches best fit their RR project.

Introduction

This paper is part of a series from the Cochrane Rapid Reviews Methods Group (RRMG) providing methodological guidance for rapid reviews (RRs). 1–3 While the RRMG’s guidance 4 5 on Cochrane RR production includes brief advice on literature searching, we aim to provide in-depth recommendations for the entire search process.

Literature searching is the foundation for all reviews; therefore, it is important to understand the goals of a specific RR. The scope of RRs varies considerably (from focused questions to overviews of broad topics). 6 As with conventional systematic reviews (SRs), there is not a one-size-fits-all approach for RR literature searches. We aim to support RR teams in choosing methods that best fit their project while understanding the limitations of modified search methods. Our recommendations derive from current systematic search guidance, evidence on modified search methods and practical experience conducting RRs.

This paper presents considerations and recommendations, described briefly in table 1 . The table also includes a comparison to the SR search process based on common recommendations. 7–10 We provide supplemental materials, including a list of additional resources, further details of our recommendations, practical examples, and a glossary (explaining the terms written in italics) in online supplemental appendices A–C .

Supplemental material

• View inline

Recommendations for rapid review literature searching

Preparation and planning

Given that the results of systematic literature searches underpin a review, planning the searches is integral to the overall RR preparation. The RR search process follows the same steps as an SR search; therefore, RR teams must be familiar with the general standards of systematic searching . Templates (see online supplemental appendix B ) and reporting guidance 11 for SR searches can also be adapted to structure the RR search process.

Developing a plan for the literature search forms part of protocol development and should involve an information specialist (eg, librarian). Information specialists can assist in refining the research question, selecting appropriate search methods and resources, designing and executing search strategies, and reporting the search methods. At minimum, specialist input should include assessing information sources and methods and providing feedback on the primary database search strategy.

Two options exist for abbreviating the search process: (1) reducing time spent on conducting searches (eg, using automation tools, reusing existing search strategies, omitting planning or quality assurance steps) and (2) reducing the size of the search result (eg, limiting the number of information sources, increasing the precision of search strategies, using study design filters). Study selection (ie, screening search results) is usually more resource-intensive than searching, 12 particularly for topics with complex or broad concepts or diffuse terminology; thus, the second option may be more efficient for the entire RR. Investing time upfront in optimising search sensitivity (ie, completeness) and precision (ie, positive predictive value) can save time in the long run by reducing the screening and selection workload.

Preliminary or scoping searches are critical to this process. They inform the choice of search methods and identify potentially relevant literature. Texts identified through preliminary searching serve as known relevant records that can be used throughout the search development process (see sections on database selection, development and validation of search strategies).

In addition to planning the search itself, the review team should factor in time for quality assurance steps (eg, search strategy peer review) and the management of search results (eg, deduplication, full-text retrieval).

Information sources and methods

To optimise the balance of search sensitivity and precision, RR teams should prioritise the most relevant information sources for the topic and the type of evidence required. These can include bibliographic databases (eg, MEDLINE/PubMed), grey literature sources and targeted supplementary search methods. Note that this approach differs from the Methodological Expectations of Cochrane Intervention Reviews Standards 9 where the same core set of information sources is required for every review and further supplemented by additional topic-specific and evidence-specific sources.

Choosing bibliographic databases

For many review topics, most evidence is found in peer-reviewed journal articles, making bibliographic databases the main resource of systematic searching. Limiting the number of databases searched can be a viable option in RRs, but it is important to prioritise topic-appropriate databases.

MEDLINE has been found to have high coverage for studies included in SRs 13 14 and is an appealing database choice because access is free via PubMed. However, coverage varies depending on topics and relevant study designs. 15 16 Additionally, even if all eligible studies for a topic were available in MEDLINE, search strategies will usually miss some eligible studies because search sensitivity is lower than database coverage. 13 17 This means searching MEDLINE alone is not a viable option, and additional information sources or search methods are required. Known relevant records can be used to help assess the coverage of selected databases (see also online supplemental appendix C ).

Further information sources and search techniques

Supplementary systematic search methods have three main goals, to identify (1) grey literature, (2) published literature not covered by the selected bibliographic databases and (3) database-covered literature that was not retrieved by the database searches.

When RRs search only a small number of databases, supplementary searches can be particularly important to pick up eligible studies not identified via database searching. While supplementary methods might increase the time spent on searching, they sometimes better optimise search sensitivity and precision, saving time in the long run. 18 Depending on the topic and relevant evidence, such methods can offer an alternative to adding additional specialised database searches. To decide if and what supplementary searches are helpful, it is important to evaluate what literature might be missed by the database searches and how this might affect the specific RR.

Study registries and other grey literature

Some studies indicate that the omission of grey literature searches rarely affects review conclusions. 17 19 However, the relevance of study registries and other grey literature sources is topic-dependent. 16 19–21 For example, randomised controlled trials (RCTs) on newly approved drugs are typically identified in ClinicalTrials.gov. 20 For rapidly evolving topics such as COVID-19, preprints are an important source. 21 For public health interventions, various types of grey literature may be important (eg, evaluations conducted by local public health agencies). 22

Further supplementary search methods

Other supplementary techniques (eg, checking reference lists, reviewing specific websites or electronic table of contents, contacting experts) may identify additional studies not retrieved by database searches. 23 One of the most common approaches involves checking reference lists of included studies and relevant reviews. This method may identify studies missed by limited database searches. 12 Another promising citation-based approach is using the ‘similar articles’ option in PubMed, although research has focused on updating existing SRs. 24 25

Considerations for RRs of RCTs

Databases and search methods to identify RCTs have been particularly well researched. 17 20 24 26 27 For this reason, it is possible to give more precise recommendations for RRs based on RCTs than for other types of review. Table 2 provides an overview of the most important considerations; additional information can be found in online supplemental appendix C .

Information sources for identification of randomised controlled trials (RCTs)

Search strategies

We define ‘search strategy’ as a Boolean search query in a specific database (eg, MEDLINE) using a specific interface (eg, Ovid). When several databases are searched, this query is usually developed in a primary database and interface (eg, Ovid MEDLINE) and translated to other databases.

Developing search strategies

Optimising search strategy precision while aiming for high sensitivity is critical in reducing the number of records retrieved. Preliminary searches provide crucial information to aid efficient search strategy development. Reviewing the abstracts and subject headings used in known relevant records will assist in identifying appropriate search terms. Text analysis tools can also be used to support this process, 28 29 for example, to develop ‘objectively derived’ search strategies. 30

Reusing or adapting complete search strategies (eg, from SRs identified by the preliminary searches) or selecting elements of search strategies for reuse can accelerate search strategy development. Additionally, validated search filters (eg, for study design) can be used to reduce the size of the search result without compromising the sensitivity of a search strategy. 31 However, quality assurance measures are necessary whether the search strategy is purpose-built, reused or adapted (see the ‘Quality assurance’ section.)

Database-specific and interface-specific functionalities can also be used to improve searches’ precision and reduce the search result’s size. Some options are: restricting to records where subject terms have been assigned as the major focus of an article (eg, major descriptors in MeSH), using proximity operators (ie, terms adjacent or within a set number of words), frequency operators (ie, terms have to appear a minimum number of times in an abstract) or restricting search terms to the article title. 32–34

Automated syntax translation can save time and reduce errors when translating a primary search strategy to different databases. 35 36 However, manual adjustments will usually be necessary.

The time taken to learn how to use supporting technologies (eg, text analysis, syntax translation) proficiently should not be underestimated. The time investment is most likely to pay off for frequent searchers. A later paper in this series will address supporting software for the entire review process.

Limits and restrictions

Limits and restrictions (eg, publication dates, language) are another way to reduce the number of records retrieved but should be tailored to the topic and applied with caution. For example, if most studies about an intervention were published 10 years ago, then an arbitrary cut-off of ‘the last 5 years’ will miss many relevant studies. 37 Similarly, limiting to ‘English only’ is acceptable for most cases, but early in the COVID-19 pandemic, a quarter of available research articles were written in Chinese. 38 Depending on the RR topic, certain document types (eg, conference abstracts, dissertations) might be excluded if not considered relevant to the research question.

Note also that preset limiting functions in search interfaces (eg, limit to humans) often rely on subject headings (eg, MeSH) alone. They will miss eligible studies that lack or have incomplete subject indexing. Using (validated) search filters 31 is preferable.

Updating existing reviews

One approach to RR production involves updating an existing SR. In this case, preliminary searches should be used to check if new evidence is available. If the review team decide to update the review, they should assess the original search methods and adapt these as necessary.

One option is to identify the minimum set of databases required to retrieve all the original included studies. 39 Any reused search strategies should be validated and peer-reviewed (see below) and optimised for precision and/or sensitivity.

Additionally, it is important to assess whether the topic terminology or the relevant databases have changed since the original SR search.

In some cases, designing a new search process may be more efficient than reproducing the original search.

Quality assurance and search strategy peer review

Errors in search strategies are common and can impact the sensitivity and comprehensiveness of the search result. 40 If an RR search uses a small number of information sources, such errors could affect the identification of relevant studies.

Validation of search strategies

The primary database search strategy should be validated using known relevant records (if available). This means testing if the primary search strategy retrieves eligible studies found through preliminary searching. If some known studies are not identified, the searcher assesses the reasons and decides if revisions are necessary. Even a precision-focused systematic search should identify the majority—we suggest at least 80%–90%—of known studies. This is based on benchmarks for sensitivity-precision-maximising search filters 41 and assumes that the set of known studies is representative of the whole of relevant studies.

Peer review of search strategies

Ideally, an information specialist should review the planned information sources and search methods and use the PRESS (Peer Review of Electronic Search Strategies) checklist 42 to assess the primary search strategy. Turnaround time has to be factored into the process from the outset (eg, waiting for feedback, revising the search strategy). PRESS recommends a maximum turnaround time of five working days for feedback, but in-house peer review often takes only a few hours.

If the overall RR time plan does not allow for a full peer review of the search strategy, a review team member with search experience should check the search strategy for spelling errors and correct use of Boolean operators (AND, OR, NOT) at a minimum.

Reporting and record management

Record management requirements of RRs are largely identical to SRs and have to be factored into the time plan. Teams should develop a data management plan and review the relevant reporting standards at the project’s outset. PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta-Analyses literature search extension) 11 is a reporting standard for SR searches that can be adapted for RRs.

Reference management software (eg, EndNote, 43 Zotero 44 ) should be used to track search results, including deduplication. Note that record management for database searches is less time-consuming than for many supplementary or grey literature searches, which often require manual entry into reference management software. 12

Additionally, software platforms for SR production (eg, Covidence, 45 EPPI-Reviewer, 46 Systematic Review Data Repository Plus 47 ) can provide a unified way to keep track of records throughout the whole review process, which can improve management and save time. These platforms and other dedicated tools (eg, SRA Deduplicator) 48 also offer automated deduplication. However, the time and cost investment necessary to appropriately use these tools have to be considered.

Decisions about search methods for an RR need to consider where time can be most usefully invested and processes accelerated. The literature search should be considered in the context of the entire review process, for example, protocol development and literature screening: Findings of preliminary searches often affect the development and refinement of the research question and the review’s eligibility criteria . In turn, they affect the number of records retrieved by the searches and therefore the time needed for literature selection.

For this reason, focusing only on reducing time spent on designing and conducting searches can be a false economy when seeking to speed up review production. While some approaches (eg, text analysis, automated syntax translation) may save time without negatively affecting search validity, others (eg, skipping quality assurance steps, using convenient information sources without considering their topic appropriateness) may harm the entire review. Information specialists can provide crucial aid concerning the appropriate design of search strategies, choice of methods and information sources.

For this reason, we consider that investing time at the outset of the review to carefully choose a small number of highly appropriate search methods and optimise search sensitivity and precision likely leads to better and more manageable results.

Ethics statements

Patient consent for publication.

Not applicable.

• Gartlehner G ,
• Nussbaumer-Streit B ,
• Nussbaumer Streit B ,
• Garritty C ,
• Tricco AC ,
• Nussbaumer-Streit B , et al
• Trivella M ,
• Hamel C , et al
• Hartling L ,
• Guise J-M ,
• Kato E , et al
• Lefebvre C ,
• Glanville J ,
• Briscoe S , et al
• Higgins JPT ,
• Lasserson T ,
• Chandler J , et al
• European network for Health Technology Assessment (EUnetHTA)
• Rethlefsen ML ,
• Kirtley S ,
• Waffenschmidt S , et al
• Klerings I , et al
• Bramer WM ,
• Giustini D ,
• Halladay CW ,
• Trikalinos TA ,
• Schmid IT , et al
• Frandsen TF ,
• Eriksen MB ,
• Hammer DMG , et al
• Klerings I ,
• Wagner G , et al
• Husk K , et al
• Featherstone R ,
• Nuspl M , et al
• Knelangen M ,
• Hausner E ,
• Metzendorf M-I , et al
• Gianola S ,
• Bargeri S , et al
• Hillier-Brown FC ,
• Moore HJ , et al
• Varley-Campbell J , et al
• Sampson M ,
• de Bruijn B ,
• Urquhart C , et al
• Fitzpatrick-Lewis D , et al
• Affengruber L ,
• Waffenschmidt S ,
• Kaiser T , et al
• The InterTASC Information Specialists’ Sub-Group
• Kleijnen J , et al
• Jacob C , et al
• Kaunelis D ,
• Mensinkai S , et al
• Mast F , et al
• Sanders S ,
• Carter M , et al
• Marshall IJ ,
• Marshall R ,
• Wallace BC , et al
• Fidahic M ,
• Runjic R , et al
• Hopewell S ,
• Salvador-Oliván JA ,
• Marco-Cuenca G ,
• Arquero-Avilés R
• Navarro-Ruan T ,
• Hobson N , et al
• McGowan J ,
• Salzwedel DM , et al
• Clarivate Analytics
• Corporation for Digital Scholarship
• Veritas Health Innovation Ltd
• Graziosi S ,
• Brunton J , et al
• Agency for Healthcare Research and Quality
• Institute for Evidence-Based Healthcare

Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1

Twitter @micaelaescb

Collaborators On behalf of the Cochrane Rapid Reviews Methods Group: Declan Devane, Gerald Gartlehner, Isolde Sommer.

Contributors IK, SR, AB, CME-L and SW contributed to the conceptualisation of this paper. IK, AB and CME-L wrote the first draft of the manuscript. All authors critically reviewed and revised the manuscript. IK is responsible for the overall content.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests AB is co-convenor of the Cochrane Qualitative and Implementation Methods Group. In the last 36 months, he received royalties from Systematic Approaches To a Successful Literature Review (Sage 3rd edn), payment or honoraria form the Agency for Healthcare Research and Quality, and travel support from the WHO. DD works part time for Cochrane Ireland and Evidence Synthesis Ireland, which are funded within the University of Ireland Galway (Ireland) by the Health Research Board (HRB) and the Health and Social Care, Research and Development (HSC R&D) Division of the Public Health Agency in Northern Ireland.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Linked Articles

• Research methods and reporting Rapid reviews methods series: Guidance on team considerations, study selection, data extraction and risk of bias assessment Barbara Nussbaumer-Streit Isolde Sommer Candyce Hamel Declan Devane Anna Noel-Storr Livia Puljak Marialena Trivella Gerald Gartlehner BMJ Evidence-Based Medicine 2023; 28 418-423 Published Online First: 19 Apr 2023. doi: 10.1136/bmjebm-2022-112185
• Research methods and reporting Rapid reviews methods series: Guidance on assessing the certainty of evidence Gerald Gartlehner Barbara Nussbaumer-Streit Declan Devane Leila Kahwati Meera Viswanathan Valerie J King Amir Qaseem Elie Akl Holger J Schuenemann BMJ Evidence-Based Medicine 2023; 29 50-54 Published Online First: 19 Apr 2023. doi: 10.1136/bmjebm-2022-112111
• Research methods and reporting Rapid Reviews Methods Series: Involving patient and public partners, healthcare providers and policymakers as knowledge users Chantelle Garritty Andrea C Tricco Maureen Smith Danielle Pollock Chris Kamel Valerie J King BMJ Evidence-Based Medicine 2023; 29 55-61 Published Online First: 19 Apr 2023. doi: 10.1136/bmjebm-2022-112070

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A Scoping Review in Speech Pathology and Applications to Future Health Disparity Research Questions

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Record ID: 163

Program Affiliation: Capstone

Presentation Type: Poster

Abstract: How do you know when a scoping review is a good fit for your literature review? As an undergraduate student, I participated in a project where our goal was to analyze commonly employed methodologies used to assess gender perception in speech, demographic characteristics of listeners that have been recorded, and the types of speech samples being utilized to investigate gender perception for speech pathology. However, there are many literature review styles to choose from before moving forward with a project or idea. We found that a scoping review would be the most appropriate tool to meet our goals because it highlights literature in emerging areas of science that have not been reviewed. A scoping review assesses the potential scope of research done about a certain topic in hopes of retrieving evidence on the team's research topics. To conduct our scoping review, we used the software, Covidence, which allows reviewers to complete article screening and data extraction quickly and flexibly. Articles went through multiple stages, abstract and title screening, full-text screening, and data extraction, to be filtered and eventually included in our findings. Through this experience in reviewing literature, I have gained knowledge on the benefits and disadvantages of scoping reviews, how to navigate through research article sections, and how to create a thought pattern that seeks out information for future research questions related to health disparities. 

Article Details

Lydia erwin.

Major: Speech, Language, and Hearing Services

• Introduction
• Conclusions
• Article Information

LMIC indicates low- and- middle-income country; SR, systematic review.

a This review included distinct conclusions about separate conditions and comparators, and so it appears in this map more than once.

eAppendix 1. Search Strategies

eAppendix 2. Excluded Studies

eAppendix 3. Evidence Table

eAppendix 4. Conditions in Previously Published Map in 2018 and Current Map

eReferences.

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Mak S , Allen J , Begashaw M, et al. Use of Massage Therapy for Pain, 2018-2023 : A Systematic Review . JAMA Netw Open. 2024;7(7):e2422259. doi:10.1001/jamanetworkopen.2024.22259

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Use of Massage Therapy for Pain, 2018-2023 : A Systematic Review

• 1 Veterans Health Administration, Greater Los Angeles Healthcare System, Los Angeles, California
• 2 UCLA Fielding School of Public Health, University of California, Los Angeles
• 3 RAND Corporation, Santa Monica, California

Question   What is the certainty or quality of evidence in recent systematic reviews for use of massage therapy for painful adult health conditions?

Findings   This systematic review identified 129 systematic reviews in a search of the literature published since 2018; of these, 41 assessed the certainty or quality of evidence of their conclusions. Overall, 17 systematic reviews regarding 13 health conditions were mapped, and most reviews concluded that the certainty of evidence was low or very low.

Meaning   This study found that despite massage therapy having been the subject of hundreds of randomized clinical trials and dozens of systematic reviews about adult health conditions since 2018, there were few conclusions that had greater than low certainty of evidence.

Importance   Massage therapy is a popular treatment that has been advocated for dozens of painful adult health conditions and has a large evidence base.

Objective   To map systematic reviews, conclusions, and certainty or quality of evidence for outcomes of massage therapy for painful adult health conditions.

Evidence Review   In this systematic review, a computerized search was conducted of PubMed, the Allied and Complementary Medicine Database, the Cumulated Index to Nursing and Allied Health Literature, the Cochrane Database of Systematic Reviews, and Web of Science from 2018 to 2023. Included studies were systematic reviews of massage therapy for pain in adult health conditions that formally rated the certainty, quality, or strength of evidence for conclusions. Studies of sports massage therapy, osteopathy, dry cupping or dry needling, and internal massage therapy (eg, for pelvic floor pain) were ineligible, as were self-administered massage therapy techniques, such as foam rolling. Reviews were categorized as those with at least 1 conclusion rated as high-certainty evidence, at least 1 conclusion rated as moderate-certainty evidence, and all conclusions rated as low- or very low–certainty evidence; a full list of conclusions and certainty of evidence was collected.

Findings   A total of 129 systematic reviews of massage therapy for painful adult health conditions were found; of these, 41 reviews used a formal method to rate certainty or quality of evidence of their conclusions and 17 reviews were mapped, covering 13 health conditions. Across these reviews, no conclusions were rated as high certainty of evidence. There were 7 conclusions that were rated as moderate-certainty evidence; all remaining conclusions were rated as low- or very low–certainty evidence. All conclusions rated as moderate certainty were that massage therapy had a beneficial associations with pain.

Conclusions and Relevance   This study found that despite a large number of randomized clinical trials, systematic reviews of massage therapy for painful adult health conditions rated a minority of conclusions as moderate-certainty evidence and that conclusions with moderate- or high-certainty evidence that massage therapy was superior to other active therapies were rare.

Massage therapy is a popular and widely accepted complementary and integrative health modality for individuals seeking relief from pain. 1 This therapy is the practice of manual assessment and manipulation of the superficial soft tissues of skin, muscle, tendon, ligament, and fascia and the structures that lie within the superficial tissues for therapeutic purpose. 2 Individuals may seek massage therapy to address pain where conventional treatments may not always provide complete relief or may come with potential adverse effects. Massage therapy encompasses a range of techniques, styles, and durations and is intended to be delivered by uniquely trained and credentialed therapists. 3 Original research studies have reported on massage therapy delivered by a wide variety of health care professionals, such as physical therapists, physiotherapists, and nurses. 4 , 5 Despite massage therapy’s popularity and long history in practice, evidence of beneficial outcomes associated with massage therapy remains limited.

The Department of Veterans Affairs (VA) previously produced an evidence map of massage therapy for pain, which included systematic reviews published through 2018. 6 An evidence map is a form of systemic review that assesses a broad field to identify the state of the evidence, gaps in knowledge, and future research needs and that presents results in a user-friendly format, often a visual figure or graph. 7 To categorize this evidence base for use in decision-making by policymakers and practitioners, VA policymakers requested a new evidence map of reviews published since 2018 to answer the question “What is the certainty of evidence in systematic reviews of massage therapy for pain?”

This systematic review is an extension of a study commissioned by the VA. While not a full systematic review, this study nevertheless reports methods and results using the Preferred Reporting Items for Systematic Reviews and Meta-analyses ( PRISMA ) reporting guideline where applicable and filed the a priori protocol with the VA Evidence Synthesis Program Coordinating Center. Requirements for review and informed consent were waived because the study was designated as not human participants research.

Literature searches were based on searches used for the evidence map of massage therapy completed in 2018. 8 We searched 5 databases for relevant records published from July 2018 to April 2023 using the search terms “massage,” “acupressure,” “shiatsu,” “myofascial release therapy,” “systematic*,” “metaanaly*,” and similar terms. The databases were PubMed, the Allied and Complementary Medicine Database, the Cumulated Index to Nursing and Allied Health Literature, the Cochrane Database of Systematic Reviews, and Web of Science. See eAppendix 1 in Supplement 1 for full search strategies.

Each title was screened independently by 2 authors for relevance (S.M., J.A., and P.G.S.). Abstracts were then reviewed in duplicate, with any discrepancies resolved by group discussion. To be included, abstracts or titles needed to be about efficacy or effectiveness of massage therapy for a painful adult health condition and be a systematic review with more than 1 study about massage therapy. A systematic review was defined as a review that had a documented systematic method for identifying and critically appraising evidence. In general, any therapist-delivered modality described as massage therapy by review authors was considered eligible (eg, tuina, acupressure, auricular acupressure, reflexology, and myofascial release). Sports massage therapy, osteopathy, dry cupping or dry needling, and internal massage therapy (eg, for pelvic floor pain) were ineligible, as were self-administered massage therapy techniques, like foam rolling. Reviews had to be about a painful condition for adults, and we excluded publications in low- and middle-income countries because of differences in resources for usual care or other active treatments for included conditions. Publications were required to compare massage therapy with sham or placebo massage, usual care, or other active therapies. Systematic reviews that covered other interventions were eligible if results for massage therapy were reported separately.

We next restricted eligibility to reviews that used formal methods to assess the certainty (sometimes called strength or quality) of the evidence for conclusions. In general, this meant using Grading of Recommendations, Assessment, Development, and Evaluations (GRADE). 9 However, other formal methods were also included, such as the approach used by the US Agency for Healthcare Research and Quality (AHRQ) Evidence-based Practice Center (EPC) program. To be included, a review had to state or cite the method used and report the certainty (or strength or quality) of evidence for each conclusion. After we applied this restriction, most health conditions had only 1 systematic review meeting the eligibility criteria, and we used this review for the map. Among conditions for which we identified more than 1 review meeting the eligibility criteria, we first assessed whether reviews differed in some other feature used to classify reviews on our map (eg, different comparators or type of massage therapy), which we would label with the appropriate designation (such as vs usual care or reflexology ). If there were multiple reviews about the same condition and they did not differ in some other feature, we selected the systematic review we judged as being most informative for readers. In general, this was the most recent review or the review with the greatest number of included studies.

Data on study condition, number of articles in a review, intervention characteristics, comparators, conclusions, and certainty, quality, or strength of evidence were extracted by 1 reviewer and then verified by a second reviewer (S.M., J.A., and P.G.S.). Our evidence mapping process produced a visual depiction of the evidence for massage therapy, as well as an accompanying narrative with an ancillary figure and table.

The visual depiction or evidence map uses a bubble plot format to display information on 4 dimensions: bubble size, bubble label, x-axis, and y-axis. This allowed us to provide the following types of information about each included systematic review:

Number of articles in systematic review (bubble size): The size of each bubble corresponds to the number of relevant primary research studies included in a systematic review.

Condition (bubble label): Each bubble is labeled with the condition discussed by that systematic review.

Shapes and colors: Intervention characteristics for each condition are presented in the form of colors (type of intervention) and shapes (comparators). For type of intervention, we included nonspecified massage therapy, tuina, myofascial release, reflexology, acupressure, and auricular acupressure. For comparators, we included mixed comparators with subgroups, mixed comparators with no subgroups, sham or placebo, and active therapy or usual care. A condition can appear more than once if multiple systematic reviews included different type of massage therapy or different comparators.

Strength of findings (rows): Each condition is plotted on the map based on the ratings of certainty of evidence statement as reported in the systematic reviews: high, moderate, low, or very low.

Outcome associated with massage therapy (columns): Each condition is plotted in potential benefit or no benefit as the outcome associated with massage therapy. Columns are not mutually exclusive. A review could have more than 1 conclusion, and conclusions could differ in the benefit associated with massage therapy. Both conclusions are included on the map.

Risk of bias is not part of the method of an evidence map. We assessed the quality of included reviews using criteria developed by the U S Preventive Services Task Force (USPSTF). Certainty of evidence as determined by the original authors of the systematic review was abstracted for each conclusion in each systematic review and tabulated.

The search identified 1164 potentially relevant citations. Among 129 full-text articles screened, 41 publications were retained for further review. Of these, 24 reviews were excluded from the map for the following reasons: only 1 primary study about interventions of interest (11 studies), outcomes associated with massage therapy could not be distinguished from other included interventions (5 studies), not an intervention of interest (3 studies), not a comparison of interest (2 studies), overlap with a more recent or larger review that was already included on the map (2 studies), and self-delivered therapy (1 study). We included 17 publications in this map covering 13 health conditions. 4 , 10 - 25 The literature flowchart ( Figure 1 ) summarizes results of the study selection process, and eAppendix 2 in Supplement 1 presents citations for all excluded reviews at full-text screening.

The total number of primary studies about massage therapy for pain in the included reviews ranged from 2 studies to 23 studies. There were 12 reviews that included fewer than 10 primary studies 4 , 11 - 17 , 20 - 23 and 5 reviews that included 10 to 25 studies about massage therapy for pain. 10 , 18 , 19 , 24 , 25 Of included reviews, 3 reviews were completed by the Cochrane Collaboration 4 , 19 , 23 and 2 reviews were completed by the AHRQ EPC program. 11 , 18

We categorized the included 17 reviews by health condition. These categories were cancer-related pain, 15 , 24 back pain (including chronic back pain, 25 chronic low back pain, 18 , 22 and low back pain 17 ), chronic neck pain, 18 fibromyalgia, 21 labor pain, 4 , 19 mechanical neck pain, 13 myofascial pain, 14 palliative care needs, 10 plantar fasciitis, 12 post–breast cancer surgery pain, 16 postcesarean pain, 23 postpartum pain, 20 and postoperative pain. 11

Of 17 included reviews, 3 reviews included more than 1 type of massage therapy and 14 reviews included 1 type of massage therapy. Reviews by Chou et al 11 and Smith et al 16 included acupressure and nonspecified massage therapy as interventions. The review by Candy et al 7 included reflexology and nonspecified massage therapy as interventions. Of the 14 reviews with 1 type of massage therapy, there were 5 reviews describing nonspecified massage therapy, 10 , 14 , 17 , 20 1 review about tuina, 22 5 reviews about myofascial release, 8 , 9 , 12 , 18 , 19 and 3 reviews about acupressure. 13 , 15 , 21

A variety of comparators were included in reviews. Of 9 reviews that included more than 1 comparator in analyses, 4 , 11 , 13 , 14 , 18 - 22 2 reviews did not conduct separate analyses by comparator (labeled mixed with no subgroups ) 13 , 14 and 3 reviews conducted separate analyses by comparator (labeled mixed with subgroups ). 4 , 21 , 22 The other 4 reviews included a mix of comparators with separate conclusions: sham or placebo and active therapy or usual care, 11 mixed with no subgroups and active therapy or usual care, 18 mixed with subgroups and active therapy or usual care, 20 and mixed with no subgroups, sham, and active therapy or usual care. 19 There were 8 reviews that included 1 comparator only in their analyses, 10 , 12 , 15 - 17 , 23 - 25 with 7 reviews that described interventions compared with active therapy or usual care only, 10 , 12 , 15 , 17 , 23 - 25 while 1 review limited inclusion to primary studies with a sham or placebo comparator. 16

There was substantial variation in the reporting of other details from primary studies in included reviews. Any study that did not specify the mode of delivery was included; studies that explicitly stated that massage therapy was self-delivered were excluded. Of the 17 included reviews, 5 reviews provided details of personnel who administered the therapy, including massage therapist, nurse, aromatherapist, physiotherapist, and reflexologist. 4 , 10 , 19 - 21 A total of 7 reviews presented length of sessions (eg, 5-minute or 90-minute sessions for massage therapy studies and 30-second or 5-minute sessions for acupressure studies). 10 , 16 , 18 , 20 - 23 With the exception of the review by He et al, 15 all reviews reported details about frequency, duration, or both when available. A total of 9 reviews included information about frequency of sessions (eg, 1 session or once every 3 weeks for massage therapy studies and 4 times per day or daily for acupressure studies), 10 , 12 , 16 - 18 , 20 - 23 and 9 reviews reported duration of sessions (eg, single session or 3 months). 10 - 12 , 16 - 18 , 20 , 22 , 23 There were 7 reviews that included details about follow-up (eg, 1 week or 12 months). 10 , 13 , 17 , 18 , 21 , 23 , 25

Using USPSTF criteria to rate the quality of included reviews, 10 reviews were rated good 4 , 10 , 11 , 14 - 16 , 18 , 19 , 21 , 23 and 7 reviews were rated fair. 12 , 13 , 17 , 20 , 22 , 24 , 25 See eAppendix 3 in Supplement 1 for each review’s rating.

Figure 2 is a visual depiction of the following types of information about each included systematic review: condition, types of comparison treatments (shapes), types of massage therapy (color), number of articles included for each conclusion (bubble size), outcomes associated with massage therapy for pain (columns), and certainty of evidence rating (rows). There were 6 reviews mapped more than once, reflecting primary studies describing more than 1 health condition, 18 more than 1 type of massage therapy, 10 , 20 or outcomes associated with massage therapy compared with different comparators. 11 , 17 - 19 There were 7 conditions from reviews 14 , 16 - 19 , 21 , 22 that reported 1 conclusion rated as moderate-certainty evidence, all of which concluded that massage therapy was associated with beneficial outcomes for pain ( Table 1 ). However, most other conditions had conclusions rated as low- or very low–certainty evidence (12 reviews about 10 conditions 4 , 10 - 13 , 15 , 17 - 20 , 23 - 25 ). This rating means “Our confidence in the effect estimate is limited. The true effect may be substantially different from the estimate of effect,” or “We have very little confidence in the effect estimate.” See eAppendix 3 in Supplement 1 for conclusions in all reviews. This map included 4 conditions that did not appear in the 2018 map, 12 , 16 , 20 , 23 and there were 8 conditions in the 2018 map that did not have new reviews meeting eligibility criteria (mainly a formal grading of the certainty of evidence); 7 health conditions 10 , 11 , 13 - 15 , 17 , 18 , 21 , 22 , 24 , 25 were included in the 2018 map and the new map (see details in eAppendix 4 in Supplement 1 ).

Evidence about adverse events was collected by approximately half of included reviews, and no serious adverse events were reported. While 11 of 17 reviews 10 , 11 , 13 , 15 , 17 - 19 , 22 - 25 described adverse events, 2 reviews 18 , 23 included certainty of evidence conclusions for adverse events for 3 health conditions ( Table 2 ).

There is a large literature of original randomized clinical trials and systematic reviews of randomized clinical trials of massage therapy as a treatment for pain. Our systematic review found that despite this literature, there were only a few conditions for which authors of systematic reviews concluded that there was at least moderate-certainty evidence regarding health outcomes associated with massage therapy and pain. Most reviews reported low- or very low–certainty evidence. Although adverse events associated with massage therapy for pain were rare, the evidence was limited. For reviews that had conclusions about adverse events, authors were uncertain if there was a difference between groups or did not find a difference between groups and rated the evidence low to very low certainty of evidence.

Massage therapy is a broad term that is inclusive of many styles and techniques. We applied exclusion criteria determined a priori to help identify publications for inclusion in the evidence map. Despite that procedure, there was still a lack of clarity in determining what massage therapy is. For instance, acupressure was sometimes considered acupuncture and other times considered massage therapy, depending on author definition. In this case, we reviewed and included only publications that were explicitly labeled acupressure and did not review publications about acupuncture only. This highlights a fundamental issue with examining the evidence base of massage therapy for pain when there is ambiguity in defining what is considered massage therapy.

Unlike a pharmaceutical placebo, sham massage therapy may not be truly inactive. It is conceivable that even the light touch or touch with no clear criterion 26 used in sham massage therapy may be associated with some positive outcomes, meaning that patients who receive the massage therapy intervention and those who receive a sham massage therapy could both demonstrate some degree of symptom improvement. Limitations of sham comparators raise the question of whether sham or placebo treatment is an appropriate comparison group in massage therapy trials. It may be more informative to compare massage therapy with other treatments that are accessible and whose benefits are known so that any added beneficial outcomes associated with massage therapy could be better isolated and understood.

Compared with the 2018 map, our map included 4 new conditions not on the 2018 map, while 8 conditions from the 2018 map had no new reviews meeting eligibility criteria and 7 health conditions appeared in both maps. Despite identifying new conditions and conclusions with higher certainty of evidence in several reviews in our updated search, most included reviews reported low or very low certainty of evidence, suggesting that the most critical research need is for better evidence to increase certainty of evidence for massage therapy for pain. This is a challenge given that massage, like other complementary and integrative health interventions, does not have the historical research infrastructure that most health professions have. 27 Nevertheless, it is only when systematic reviews and meta-analyses are conducted with high-quality primary studies that the association or lack of association of massage therapy with pain will reach higher certainties of evidence. Studies comparing massage therapy with placebo or sham are probably not the priority; rather, the priority should be studies comparing massage therapy with other recommended, accepted, and active therapies for pain. Studies comparing massage therapy with other recommended therapies should also have a sufficiently long follow-up to allow any nonspecific outcomes (eg, those associated with receiving some new treatment) to dissipate. For example, this period has been proposed to be at least 6 months for studies of chronic pain.

There are 2 main limitations to this systematic review’s evidence map. The first, common to all systematic reviews, is that we may not have identified all potentially eligible evidence. If a systematic review was published in a journal not indexed in any of 5 databases we searched and we did not identify it as part of our search of references of included publications, then we would have missed it. Nevertheless, our search strategy identified more than 200 publications about massage therapy for pain published since July 2018, so we did not lack potential reviews to evaluate. The second limitation of evidence maps is that we did not independently evaluate the source evidence; in other words, we took conclusions of authors of the systematic review at face value. That is the nature of an evidence map. Particular to this application of the mapping process, we mapped the review we deemed most informative for the 2 health conditions that had more than 1 eligible review (back pain and labor pain). This necessarily requires judgment, and others could disagree with that judgment. We included the citation for reviews excluded from the map for this overlap reason in supplemental material, and interested readers can review it for additional information. As in all evidence-based products and particularly in 1 such as this covering a large and complex evidence base, it is possible that there are errors of data extraction and compilation. We used dual review to minimize the chance of such errors, but if we are notified of errors, we will correct them.

Although this systematic review found that the number of conclusions about the effectiveness of massage therapy that were judged to have at least moderate certainty of evidence was greater now than in 2018, it was still small relative to the need. More high-quality randomized clinical trials are needed to provide a stronger evidence base to assess the effect of massage therapy on pain. For painful conditions that do not have at least moderate-certainty evidence supporting use of massage therapy, new studies that address limitations of existing research are needed. The field of massage therapy would be best advanced by educating the wider research community with clearer definitions of massage therapy and whether it is appropriate to include multiple modalities in the same systematic review.

Accepted for Publication: May 15, 2024.

Published: July 15, 2024. doi:10.1001/jamanetworkopen.2024.22259

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Mak S et al. JAMA Network Open .

Corresponding Author: Selene Mak, PhD, MPH, Veterans Health Administration, Greater Los Angeles Healthcare System, 11301 Wilshire Blvd, Los Angeles, CA 90073 ( [email protected] ).

Author Contributions: Drs Mak and Shekelle had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Mak, Miake-Lye, Shekelle.

Acquisition, analysis, or interpretation of data: Mak, Allen, Begashaw, Beroes-Severin, De Vries, Lawson, Shekelle.

Drafting of the manuscript: Mak, Allen, Begashaw, Beroes-Severin, De Vries, Lawson, Shekelle.

Critical review of the manuscript for important intellectual content: Mak, Miake-Lye, Shekelle.

Statistical analysis: Allen.

Obtained funding: Shekelle.

Administrative, technical, or material support: Begashaw, Miake-Lye, Beroes-Severin, De Vries, Lawson.

Supervision: Mak, Shekelle.

Conflict of Interest Disclosures: None reported.

Funding/Support: Funding was provided by the Department of Veterans Affairs Health Services Research and Development.

Role of the Funder/Sponsor: The funders had no role in the collection, management, analysis, and interpretation of the data and preparation of the manuscript. The funders participated in the design and conduct of the study, the review and approval of the manuscript, and the decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

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The Best 8 AI-Powered Tools for Literature Review

In this blog post, I will explore the benefits of using best AI-powered tools for literature review . Literature survey is a crucial step in any research work, but it can also be a daunting and time-consuming task.

You have to find, read, and evaluate hundreds or thousands of research papers, synthesize the existing knowledge, and identify the gaps and opportunities for your research.

Fortunately, there are some AI-powered apps that can help you with literature survey and make it easier and faster. In order to automate the tasks such as searching for articles, identifying relevant papers, and summarizing papers the apps use the artificial intelligence.

Besides, this saves you a significant amount of time and effort. It lets you focus on the more creative and strategic aspects of your research work.

Here are some of the best 8 AI-powered apps for literature review that you should try:

Research Rabbit

Research Rabbit is an AI-powered app that helps researchers find, organize, and analyze research papers.

It is a free tool that can be used by anyone, regardless of their research experience.

Research Rabbit uses AI to scan the web for relevant scholarly articles. In addition to that the AI-based tool allows you to save and organize articles in your own personal library.

To use Research Rabbit, you first need to create an account. Once you have created an account, you can start searching for research papers. You can search by keyword, topic, or author.

Once you have found the papers you are interested in, you can add them to your collections. Collections are a way to organize your research papers. You can create as many collections as you need.

Research Rabbit- Link

Rayyan is an AI-powered app that helps researchers conduct systematic literature review s.

A systematic literature review is a comprehensive research process that involves identifying, evaluating, and synthesizing all the available research on a particular topic.

It helps you work quickly through even your largest reviews. It lets you de-duplicate, screen, and organize references, as well as collaborate with your team and generate reports.

You can use Rayyan to import references from various sources, apply inclusion and exclusion criteria, assign labels and ratings, and export your data for further analysis.

Rayyan- Link

Scholarcy is an AI-powered app that can help you with your academic reading. It can automatically summarize articles, create flashcards, and generate bibliographies.

Scholarcy can also help you find related research and identify key information in articles.

In order to use Scholarcy, you first need to create an account. Once you have created an account, you can start adding articles to your library.

Additionally, you can add academic papers from a variety of sources like Google Scholar, PubMed, and your personal library.

Once you have added scholarly articles to your library, you can start using Scholarcy’s features. To summarize an article, simply click on the “Summarize” button.

Scholarcy will then generate a summary of the article in a few seconds.

Overall, Scholarcy is a valuable tool that can help you with your academic reading. If you are looking for a way to save time, improve your understanding, and increase your productivity, Scholarcy is a great option.

Scholarcy- Link

Lateral is an AI-powered app that can help you with your academic research. It can help you find relevant research, organize your findings, and write better papers.

Lateral uses artificial intelligence to analyze research papers and identify key concepts, relationships, and trends. This information can then be used to help you find relevant research, organize your findings, and write better papers.

It helps you organize, search, and save information from collections of articles. You can import articles from various sources, create tags and notes, and use natural language queries to find specific information in your collections.

You can use Lateral to manage your literature review workflow , keep track of your sources and citation s, and access your information anytime and anywhere.

Lateral – Link

Scite is a free, open-source AI-powered app that helps researchers better discover and understand research articles. Scite does this by providing Smart Citation s, which display the context of a citation and describe whether the article provides supporting or contrasting evidence.

To use Scite, simply go to the Scite website and sign up for an account. Once you have an account, you can start searching for research articles. Scite will display a list of articles that match your search criteria, and you can then click on an article to view its Smart Citation s.

You can use Scite to assess the quality and reliability of the literature, avoid citing unreliable sources, and find evidence for or against any hypothesis.

Scite- Link

If you are looking for a way to quickly and easily find answers from scientific research, you might want to try Consensus AI, a new search engine that uses artificial intelligence to extract and distill findings directly from peer-reviewed studies.

Consensus AI is a powerful tool that can help you find evidence-based answers from scientific research in a fast and easy way.

You can also use various features to refine your search and explore more options. Consensus AI can help you save time and effort in finding reliable information from scientific research.

Consensus- Link

Semantic Scholar

It is a free AI-powered academic search engine that helps you find relevant academic papers faster and easier than traditional methods. It uses natural language processing and machine learning to understand your research needs and provide you with smart filters, citation analysis, and key insights from papers.

You can use Semantic Scholar to discover the most influential and recent scientific literature in your field, compare different methods and results, and track the impact of your own publications.

Semantic Scholar- Link

It is an AI-powered reading assistant that helps you organize, annotate, and collaborate on your research. It helps you fine-tune your literature search, generate summaries, highlight and compare ideas, and share and discuss literature with your team.

You can use RAx to create different projects for your research topics, import articles from various sources, annotate them with notes and comments, and get personalized suggestions for further reading.

RAx Literature Review and Critical Analysis Tool-  Link

It is an AI-powered research assistant that can help you with tasks such as finding relevant articles, summarizing articles, and generating research ideas.

A comprehensive platform for all your research processing: Smart search and a wide range of smart filters, reading list analysis, auto-generated summaries, autonomous extraction and systematizing of data

Iris AI -Your Research Workspace- Link

These are some of the best 8 AI-powered apps for literature review that can help you save time and effort, improve your understanding and writing skills, and produce high-quality research. Try them out today and see how they can supercharge your literature review process.

It is important to note that AI-powered apps are not a replacement for hum an judgment. However, they can be a valuable tool for helping you to find relevant research articles, identify important concepts, and track the development of research over time.

If you are interested in trying one of these apps, I encourage you to visit their websites and sign up for a free trial. You can also read reviews from other users to get a better idea of which app is right for you.

If you want to supercharge your literature review with AI, you should try out these 8 apps today. They are easy to use, affordable, and reliable. They will transform your literature review process and help you achieve your research goals faster and easier.

Don’t wait any longer. Start using these AI-powered apps for literature review today and see the difference for yourself. You will be amazed by how much they can help you with your research.

I hope this blog post has been helpful. If you have any questions, please feel free to leave a comment below.

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Ulster University - Trial Access (29th Aug - 28th Oct 2024)

Ulster University is delighted to offer all current staff, researchers and students access to a 2-month trial institutional-wide licence to Covidence from 29th August 2024 to 28th October 2024.

Covidence is a web-based software platform that streamlines the production of systematic/ scoping/ rapid/ literature reviews. It supports reference/citation screening, full-text review, risk of bias/quality assessment, extraction of study characteristics and outcomes, and the export of data and references. The platform interface is intuitive and can save time on repetitive review tasks, enabling faster review production and more time for analysis and interpretation. 

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Reviews created using the institutional trial access account will be visible to Covidence subscription administrators. Reviews created using your personal account are only visible to you. 

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Covidence offers a range of available resources and support to help you along the way with your systematic review process - 

Try our pre-set Demo review to get familiar with how a Covidence workflow works. This will allow you to have a hands-on experience and understand the process better. You will find it at the bottom of your dashboard once you have signed in. Give it a go and feel free to explore!

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