software for literature reviews

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. 

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

#3. Scite.Ai – Your personal research assistant

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

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

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.

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

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LITERATURE 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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• 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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Rayyan makes ordering articles and extracting data very easy. A great tool for undertaking literature and systematic reviews!

Excellent interface to do title and abstract screening. Also helps to keep a track on the the reasons for exclusion from the review. That too in a blinded manner.

Rayyan is a fantastic tool to save time and improve systematic reviews!!! It has changed my life as a researcher!!! thanks

Easy to use, friendly, has everything you need for cooperative work on the systematic review.

Rayyan makes life easy in every way when conducting a systematic review and it is easy to use.

Literature Review Software .

Literature review software that streamlines your systematic literature review workflow from search to reporting.

The Lindexer platform is comprehensive, user-friendly and highly customizable. Its direct search, smart screening, and efficient data extraction, with built-in analysis and reporting capabilities will make it your  go-to medical writing tool.  

Empower your literature reviews with the Lindexer literature review software platform.

No more spreadsheets .

The medical writing tools you use to manage the complexities of a systematic literature review do not have to be complex. What if you could use a single platform that supports all stages of the literature review, as easy to use as a spreadsheet?

Meet Lindexer, designed by medical writers for medical writers.

Intuitive Workflow

Optimize your workflow with a sleek, intuitive interface.

Powerful Integrations

Search directly from Lindexer or import your search results.

Smart Tools to make you faster

Accelerate your research with intelligent features.

Compliance is Key

Enhance your research with robust reporting and compliance features.

Team Collaboration

Invite your team and finish your review faster.

Make it your own

Create forms & templates, customize your screen layout.

Advantages of systematic literature review software .

• Saves time to produce MDR-compliant literature reviews efficiently without switching between applications. 
• Ensures the traceability of all inclusion and exclusion decisions.
• Includes powerful data extraction tools and the option to analyze data as they are generated.
• Makes it easy to update your review or run a living review.

Still using spreadsheets for your systematic literature review? Check out our Excel template!

European medical device regulation .

EU regulation 2017/45 (MDR) and its counterpart 2017/746 on in vitro diagnostics (IVDR) set the requirements for medical technologies to obtain CE mark and enter the European market. Compared to the replaced Directives, these regulations impose stricter processes for demonstrating device safety and performance throughout their lifecycle.

One additional requirement is a systematic literature review to establish the current state of the art, standard of care, and analyze device performance and safety compared to similar or benchmark devices.

To prevent shortages, amending regulation (EU) 2023/607 extends the certificate validity of legacy devices under MDD/AIMDD or IVDD until December 31, 2028, under certain conditions. However, the transition deadline to the new regulations remains tight.

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Systematic literature reviews are complex and time-consuming. That’s why we make it easy to turn them into a team effort. Collaborate with as many people as you need: all Lindexer pricing plans are project-based and include unlimited users.

Select the plan that fits your needs and experience the full capabilities of Lindexer Literature Review Software.

"Lindexer is easy to navigate and user friendly. The current functionality supports all steps of the systematic literature review process. Everyone involved in clinical evaluation of medical devices will benefit from this type of tool."

Get quick answers to your questions about our systematic literature review software  platform.

• Ease of use
• Fast screening with keyword highlighting, one-click screening decisions and ordering publications to screen by relevance
• Customizable forms for data collection at every step of the review. Start with ready-to-use system templates or create your own.
• Automatically generated data extraction tables, dual monitor support, traceability by allowing you to paste input data from the full text, which is automatically parsed into the correct column.
• Datasets and analysis for every step of the review, so you get exactly the data you need, without having to process a gigantic spreadsheet.
• Based on the study setup of the publication you are reviewing, and the data extraction form you set up, Lindexer automatically creates a data extraction table.
• User friendly data extraction features include dual monitor support, avoiding repetitive data entry by taking over defaults, prefilling certain data and automatically parsing text copied from the pdf.
• Lindexer provides you with customizable datasets for every step of the process so you get bite-sized exports that can be used directly. Customize standard datasets by adding computed parameters, sorting and ordering columns
• Analyze datasets directly in Lindexer by calculating summaries, minimum and maximum values using easy drag-and-drop pivot table data analysis tools. And export the result, just as you need it.
• For small projects, you can import the included publications in Lindexer and continue with a next version.
• For larger projects, you can count on our change management support.

The workload for every step of the systematic literature review process is listed directly on the workflow bar at the top of the application as a counter.

Lindexer has customization options to allow you to tailor your review to your specific needs at every step:

• Custom forms and templates for data collection at every step
• Reasons for exclusion
• Calculated parameters, unit conversions
• Custom analysis and data summaries
• Customize datasets for export

All Lindexer datasets can be exported to Excel for further analysis.

Resources .

Resources, insights and downloadable templates on systematic literature reviews for medical devices. Still using spreadsheets for your systematic literature review? Check out our Excel template as well!

Buying Guide Checklist

Download our detailed buying guide checklist to choose the ideal literature review software. Streamline your research process…

Systematic Literature Review Software Buying Guide 

Guide to describe the main benefits and of systematic literature review software and considerations for selecting them.

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• Modern design that makes you faster.
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• Data extraction tables created on the fly based on the study setup of the publication you are reading.
• Unit conversion, custom calculations, and pivot tables updated as you advance.
• (Customizable) IMDRF appraisal template available, or build your own.
• A PRISMA 2020 compliant flowchart, forest plots, and configurable data and summary tables ready to integrate directly into your report.
• Full audit trail – all activities are logged and traceable. Easily trace extracted data to source text.
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• Cloud-based SaaS solution, hosted on Google Cloud, secured by design.

Lindexer works project-based, so you can easily invite others to collaborate on your literature review without additional cost. To get started on the next stage earlier. Or have an expert opinion on whether a set of publications meet the eligibility criteria of your review. Or both.

• Use or customize predefined templates to get your MDR-compliant literature review up and running in no time. Or create your own from scratch.
• Templates are available for screening, appraisal, study summary and data extraction forms, but also for reasons for exclusion, keywords and tags. Use them as such, customize them or create your own.
• Configure your screen layout to suit your way of working.

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Advanced Literature Review Software

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

Strategic Analysis

Perform Scoping and Systematic Reviews quickly and accurately using the latest automation and information management algorithms.

Reference Management

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..

Distribution

Export capabilities for sharing the Knowledge that you have just created as either CSV files or for importing into Cite and Write managers.

Internationally Recognized

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...

How to get started

Explore the features of Synthesis to see what truly sets it apart from other approaches for managing and analyzing the academic and business literature.

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.

Find out more

I want to have Access to the latest Literature in the Fastest Possible way and Quickly Assess it. Physician

We need Systems with Automation and Artificial Intelligence that Allows Literature Reviews to be conducted quickly and efficiently. Academic Researcher

We need a Computer System for Healthcare that Puts the Information at My Finger Tips and Tells Me Everything I Need to Know. Hospital Administrator

We need Information Systems that Aren't Based in 1970s Technology Medical Student

Keep Up to Date about Synthesis

Synthesis research inc..

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.

Buyer’s Guide To Literature Review Software

About this guide.

Our team has been developing literature review software for the world’s leading research organizations for over 15 years. Though the software has evolved dramatically over that period, the questions we are asked about the features and benefits of review software haven’t changed much.

In this guide, we present a comprehensive list of things to consider when evaluating a literature review software solution.

This guide will:

• Explain what literature review software does and how it is used
• Discuss where literature review software fits within the overall review process
• Provide a checklist of features to help you with the evaluation process

Who should read this guide?

If you are doing literature reviews today, you already know that they are increasingly required for regulatory compliance and safety monitoring. You also probably know that, while reviews sound simple on the surface, they are big projects that can consume significant amounts of time and resources. Doing reviews well can be a challenge.

This guide can benefit you if:

You are struggling with the amount of time it takes to conduct a review

If you are involved in the preparation of literature reviews for Clinical Evaluation Reports (CERs), Performance Evaluation Reports (PER), or if you track literature for safety monitoring, you need to be able to enforce standardized review processes and methods across your organization. Since your work could be subject to an audit, you need to be prepared.

You need to reduce the time it takes to conduct a review

You’re concerned about manual errors compromising the quality of your review

Did I make a transcription error? Did we forget to review that paper by Nosyk? Has any of my data changed? Worries like these can keep a researcher up at night and can seriously impact the quality and integrity of your review.

You’re not sure which literature review software is the best fit for you

What does literature review software do.

Today’s literature review software automates the many manual tasks involved in conducting a review. Literature reviews are process intensive and data heavy, and not so long ago they typically involved circulating paper copies of articles and screening forms to the review team who captured their work on spreadsheets.

Most reviewers currently use some form of technology to help manage the information and data in their review projects. In fact, a recent survey showed that the vast majority of reviewers still use spreadsheets at some stage of their review process.

Of course, it is possible to produce results using spreadsheets, or even paper forms. That said, each of these methods has a number of drawbacks that can have significant impact on both the quality and the volume of research produced.

Just Say No To Spreadsheets

When using spreadsheets for review tasks such as screening, data extraction, or storing references, you may find yourself dealing with some or all of the following:

• A reviewing “bottleneck” because each stage of the review must be completed before the next one is started
• Manual data entry errors that can be difficult or even impossible to catch
• Excessive manual work in checking for disagreements and creating reports
• Questions about the validity of your results due to lost files or undocumented processes

Where does literature review software fit in the process?

Literature review software is designed to reduce the manual work involved in conducting reviews and maintain a complete record of the work that’s been done on your review projects.

But how does it do this?

Once you’ve defined your research question and completed your search of relevant databases, you can typically import your search results into your literature review software and start your screening and data extraction processes.

Similar to the paper forms used in the past, literature review software uses electronic forms to record the answers to inclusion/exclusion questions. Some forms can be configured for data extraction. One of the main advantages that electronic forms provide is that they collect all your review data in one place, eliminating the need to manually cut and paste collate individual responses for processing and analysis. 

“Why input data twice when it only needs to be done once?”

Digital forms can be reused an unlimited number of times. Depending on the form and the reviewer, they can usually be completed faster than writing or typing since they can incorporate easy-to-use answer formats like checkboxes or radio buttons. They can also validate your data and even perform calculations before you submit it, giving you cleaner results and fewer errors.

Screening and data extraction are the most common review tasks facilitated by literature review software, but there are often other valuable features such as direct connection to popular databases such as PubMed, automated report generation, and reviewer roles and permissions management.

With regulatory bodies calling for continuous monitoring and assessment of safety data, having your entire review project and all its references, full text articles and audit trail stored within your literature review software can be a huge time saver when it comes time for updates.

As literature reviews have become a fundamental component of the risk management system for many organizations, they are increasingly scrutinized for thoroughness, standardized processes, and data integrity. By maintaining complete, accurate records of every reviewer action and decision, and allowing you to establish and enforce repeatable processes, literature review software makes it easier to deliver regulatory compliant, audit-ready literature reviews on time and on budget.

Top 5 Ways Systematic Review Software Can Help You

#1 compliance.

If there’s one thing that almost every reviewer wishes for, it’s more time. In our Survey of Literature Reviews, approximately one quarter of the respondents mentioned their greatest review challenge is the time involved in completing a review – to conduct searches, remove duplicates and irrelevant articles, complete screening, extract data, and prepare reports. In a recent survey of our user community, reviewers reported that literature review software reduced the time required to produce reviews by 40%-60%.

#3 Automation

No one wants to discover a mistake in their review right before – or worse, during – an audit.

Duplicate references, transcription errors, and data entry errors can skew, or even invalidate, your results. Literature review software can provide built-in automation and validation tools that dramatically reduce the potential for errors in your reviews.

#4 Compatibility

Although literature review software can help with many tasks throughout the review lifecycle, your process likely includes other tools for searching and storing references and data. You also likely need to use the information from your completed review in reports and submissions. Your literature review software should allow you to import and export your data in all the most common file formats, such as CSV, Excel, Word, PDF, RIS, and ENLX.

#5 Collaboration

Literature review software packages today are typically cloud-based and can be used from any browser on any device. With a centralized, shared data set, your team can collaborate in real time, regardless of location.

Your Literature Review Software Checklist

Deciding to adopt literature review software is more than just a monetary investment – it’s a commitment to a new way of doing things. And just like any significant purchase, it’s always a good idea to do your research first.

Make sure you conduct a thorough assessment of each of the available options to choose the software that is the best fit for your needs. Below is a list of features that may be offered by systematic review software packages.

This requirement applies to my assessement

Automatic reference updates to prevent the review from becoming out-of-date

Compatible with standard reference file types (RIS, CSV, and ENLX)

Direct integration with reference databases

Keyword highlighting for faster screening

Full-Text Retrieval

Data extraction, project management.

Real-time updates on project progress to inform stakeholders and facilitate planning

Live customer support, professional services offerings and training

Enterprise-Grade Software (High availability and redundancy,  scalable to handle hundreds of thousands of references per project, secure and regulatory compliant )

Download this Ebook

Learn more about distillersr.

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.

MA Extraction

Qualitative

Quantitative

Search, Import, or Bibliomine.

Literature search.

Create updatable searches of PubMed, or import studies from a variety of common databases.

Add studies by mining from existing reviews, or add individual studies of interest. No matter how you get studies, we’ll set them up to be included in your living review.

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

Dive into nested knowledge:.

First review is free • No credit card required

Buying for a team? Contact Sales:

Have a question?

Send us an email and we’ll get back to you as quickly as we can!

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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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
• 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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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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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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Scholarcy is used by students around the world to read and analyse research papers in less time. Upload your articles to Scholarcy to:

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With Scholarcy Library, you can import all your papers and search results, and quickly screen them with the automatically generated ‘key takeaway’ headline.

Take the stress out of your literature review

While there are lots of tools that help you discover articles for your research, how do you analyse and synthesise the information from all of those papers?

3 easy ways to import articles

Scholarcy lets you quickly import your articles for screening and analysing.

Import papers in PDF, Word, HTML and LaTeX format

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Build your literature matrix in minutes

Our Excel export feature generates a literature synthesis matrix for you, so you can

Compare papers side by side for their study sizes, key contributions, limitations, and more.

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Integrates with your reference manager and ‘second brain’ tools such as Roam, Notion and Obsidian

Carrying out a systematic review?

Scholarcy breaks papers down into our unique summary flashcard format.

The Study subjects and analysis tab shows you study population, intervention, outcome, and statistical analyses from the paper.

And the Excel synthesis matrix generated shows the key methods and quantitative findings of each paper, side by side.

Build a knowledge graph from your papers

If you’re a fan of the latest generation of knowledge management tools such as  Roam  or  Obsidian , you’ll love our  Markdown  export.

This creates a knowledge graph of all the papers in your library by connecting them via key terms, methods, and shared citations.

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Systematic & Advanced Evidence Synthesis Reviews

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• Choosing A Review Type
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• Systematic Reviews
• Scoping & Other Types of Advanced Reviews

Online Toolkits & Workbooks

Search strategies and citation chaining, citation management, deduplication, bibliography creation, and cite-while-you-write, screening results, creating prisma compliant flow charts, data analysis & abstraction, total workflow sr products, writing a manuscript.

• Contact Your Librarian For Help

This page lists commonly used software for Systematic Review's (SRs) and other advanced evidence synthesis reviews and should not be taken as MSU Libraries endorsing one program over another. The sections of the guide list fee-based as well as free and open-source software for different aspects of the review workflow.  All-inclusive workflow products are listed in this section.

• Wanner, Amanda. 2019. Getting started with your systematic or scoping review: Workbook & Endnote Instructions. Open Science Framework. This is a librarian created workbook on OSF that includes a pretty comprehensive workbook that walks you through all the steps and stages of creating a systematic or scoping review.
• What review is right for you? This tool is designed to provide guidance and supporting material to reviewers on methods for the conduct and reporting of knowledge synthesis. As a pilot project, the current version of the tool only identifies methods for knowledge synthesis of quantitative studies. A future iteration will be developed for qualitative evidence synthesis.
• Systematic Review Toolkit The Systematic Review Toolbox is a web-based catalogue of tools that support various tasks within the systematic review and wider evidence synthesis process. The toolbox aims to help researchers and reviewers find the following: Software tools, Quality assessment / critical appraisal checklists, Reporting standards, and Guidelines.

It is highly recommended that researchers partner with the academic librarian for their specialty to create search strategies for systematic and advanced reviews. Many guidance organizations recognize the invaluable contributions of information professionals to creating search strategies - the bedrock of synthesis reviews.

• Visualising systematic review search strategies to assist information specialists
• Gusenbauer, M., & Haddaway, N. R. (2019). Which Academic Search Systems are Suitable for Systematic Reviews or Meta‐Analyses? Evaluating Retrieval Qualities of Google Scholar, PubMed and 26 other Resources. Research Synthesis Methods.
• Citation Chaser Forward citation chasing looks for all records citing one or more articles of known relevance; backward citation chasing looks for all records referenced in one or more articles. This tool automates this process by making use of the Lens.org API. An input article list can be used to return a list of all referenced records, and/or all citing records in the Lens.org database (consisting of PubMed, PubMed Central, CrossRef, Microsoft Academic Graph and CORE)

How do you track your integration and resourcing for projects that require systematic searching, like systematic or scoping reviews? What, where, and how should you be tracking? Using a tool like Air Table can help you stay organized.

• Airtable for Systematic Search Tracking Talk from Whitney Townsend at the University of Michigan - April 6, 2022

Having a software program that can store citations from databases, deduplicating your results, and automating the creation and formatting of citations and a bibliography using a cite-while-you-write plugin will save a lot of time when doing any literature review. The software listed below can do all of these functions which are not found in the fee-based total systematic review workflow products.

You could also do most of the components of an SR in these software including screening.

• Endnote Guide Endnote Online is free and has basic functionality like importing citations and cite-while-you-write for Microsoft Word. The desktop version of Endnote is a separate individual purchase and is more robust then the online version particularly for organization of citations and ease of use with large citation libraries.
• Mendeley Guide Mendeley has all the standard features of a citation manager with the addition of a social community of scholars. Mendeley can be sluggish with large file sizes of multiple thousands of citations and the free version has limited collaborative features.

Screening the titles, abstracts, and full text of your results is one of the most time consuming components of any review. There are easy-to-use free software for this process but they won't have features like automatically creating the flow charts and inter-rater reliability kappa coefficient that you need to report in your methodology section. You will have to do this by hand.

Deduplication of results before importation into one of these tools and screening should be done in a citation management program like Endnote, Mendeley, or Zotero.

• Abstrackr Created by Brown University, Abstrackr is one of the best known and easiest to use free tools for screening results.
• Colandr Colandr is an open source screening tool. Like Abstrackr, deduplication is best done in a citation manager and then results imported into Colandr. There is a learning curve to this tool but a vibrant user community does exist for troubleshooting.
• Rayyan Built by the Qatar Foundation. It is a free web-tool (Beta) designed to help researchers working on systematic reviews and other knowledge synthesis projects. It has simple interface and a mobile app for screening-on-the-go.
• PRISMA Diagram Generator Using the PRISMA Diagram Generator you can produce a diagram easily in any of 10 different formats. The official PRISMA website only has the format as a .docx or .pdf option. Using the generator the diagram is produced using the Open Source dot program (part of graphviz), and this tool provides the source for your diagram if you wish to further tweak your diagram.
• PRISMA 2020: R Package and ShinyApp This free, online tool makes use of the DiagrammeR R package to develop a customisable flow diagram that conforms to PRISMA 2020 standards. It allows the user to specify whether previous and other study arms should be included, and allows interactivity to be embedded through the use of mouseover tooltips and hyperlinks on box clicks.

Tools for data analysis can help you categorize results such as outcomes of studies and perform metanalyses. The SRDR tool may be the easiest to use and has frequent functionality updates.

• OpenMeta[Analyst] Developed by Brown University using an AHRQ grant, OpenMeta[Analyst] is a no-frills approach to data analysis.
• SRDR Developed by the AHRQ, The Systematic Review Data Repository (SRDR) is a powerful and easy-to-use tool for the extraction and management of data for systematic review or meta-analysis. It is also an open and searchable archive of systematic reviews and their data.

Data abstraction commonly refers to the extraction, synthesis, and structured visualization of evidence characteristics. Evidence tables/table shells/reading grids are the core way article extraction analyses are displayed. It lists all the included data sources and their characteristics according to your inclusion/exclusion criteria. Tools like Covidence have modules to create your own data extraction form and export a table when finished.

• OpenAcademics: Reading Grid Template
• The National Academies Press: Sample Literature Table Shells
• Campbell Collaboration: Data Extraction Tips

There are several fee-based products that are a one-stop-shop for systematic reviews. They complete all the steps from importing citations, deduplicating results, screening, bibliography management, and some even perform metanalyses. These are best used by teams that have grant or departmental funding because they can be rather expensive. 

None of these tools offers a robust bibliography creation function or cite-while-you write option. You will still need to use a separate citation manager to do these aspects of review writing. We list commonly used citation management tools on this page.

• EPPI-Reviewer 4 EPPI-Reviewer 4 is a web-based software program for managing and analysing data in literature reviews. It has been developed for all types of systematic review (meta-analysis, framework synthesis, thematic synthesis etc) but also has features that would be useful in any literature review. It manages references, stores PDF files and facilitates qualitative and quantitative analyses such as meta-analysis and thematic synthesis. It also contains some new ‘text mining’ technology which is promising to make systematic reviewing more efficient. It also supports many different analytic functions for synthesis including meta-analysis, empirical synthesis and qualitative thematic synthesis. It does not have a bibliographic manager or cite-while-you-write feature.
• JBI-SUMARI Currently, this tool can only accept Endnote XML files for citation import. So you would need to download citations to Endnote, import them into SUMARI, and when screening is complete use Endnote as your bibliographic manager for any writing. SUMARI supports 10 review types, including reviews of effectiveness, qualitative research, economic evaluations, prevalence/incidence, aetiology/risk, mixed methods, umbrella/overviews, text/opinion, diagnostic test accuracy and scoping reviews. It facilitates the entire review process, from protocol development, team management, study selection, critical appraisal, data extraction, data synthesis and writing your systematic review report.

Using Excel

Some teams may choose to use Excel for their systematic review. This is not recommended because it can be extremely time consuming and is more prone to error. However, there is a basic template for Excel-based SR's online that is good quality and walks one through the entire workflow of completing an SR (excluding bibliography creation and citation management).

• PIECES Workbook This link will open an Excel workbook designed to help conduct, document, and manage a systematic review. Made by Margaret J. Foster, MS, MPH, AHIP Systematic Reviews Coordinator Associate Professor Medical Sciences Library, Texas A&M University
• Systematic Review Accelerator: Methods Wizard An tool to help you write consistent, reproducible methods sections according to common reporting structures.
• PRISMA Extensions Each PRISMA reporting extension has a manuscript checklist that lays out exactly how to write/report your review and what information to include.
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• Next: Contact Your Librarian For Help >>
• Last Updated: May 14, 2024 2:50 PM
• URL: https://libguides.lib.msu.edu/systematic_reviews

Systematic Literature Review Tools – How To Choose One

A variety of factors (e.g., the new EU MDR & IVDR requirements, finding and retaining top talent, and tight budgets, just to name a few) have influenced Medical Device and Diagnostic manufacturers to invest in technology that streamlines and automates required compliance activities. Systematic Literature Review tools (SLR tools) can offer users many advantages over using “manual” methods such as Excel. However, with more and more SLR tools entering the market to meet the growing demand of the medical device industry, how do you know where to start?

The Celegence team is here to help. The following blog details six things to look for when choosing a systematic literature review tool to meet the MDR/IVDR requirements for your medical device or diagnostic portfolio.

#1: Ease of Use and Simple User Interface (UI)

Conducting a systematic literature review is quite time intensive. In fact, research shows that systematic literature reviews can take anywhere between 6 to 24 months to complete.[1–3] And, depending on the size of your team and product portfolio, you will likely need to execute multiple projects simultaneously. You will spend a lot of time using your chosen SLR tool or platform, so it should be easy to use and navigate. Furthermore, the composition of regulatory team members associated with any given project may change over time. Medical writers may transition, new reviewers could be assigned, and additional stakeholders from cross-functional teams might need to contribute. Given this dynamic environment, make sure that you look for a tool that is intuitive, recognizing the time commitment to implement it into your workflow. Review the provider’s training program too, ensuring ongoing support for your team well after the initial implementation.

The checklist highlights all of the documentation that you will need in place for certification of your IVD device and will serve as a guide to help you achieve ongoing compliance. In conjunction with this checklist, we are also able to provide you with bespoke strategies to bring your business up to speed. We are currently working with businesses from the United States, India, and throughout Europe to ensure that they are ready for the deadline in May of 2022.

#2: Systematic Literature Review Tools Collaboration Features

Systematic reviews are a collaborative effort. Any given systematic literature review may include multiple medical writers, inputs from medical and subject matter experts, and reviewers from regulatory, quality, and clinical departments. Your organization might even be outsourcing different regulatory functions to an external firm or consultant, so adopting an SLR tool that can accommodate internal and external users will be key. More importantly, your chosen platform should possess features that facilitate collaboration. Some key collaboration features you may want to consider include:

• Comments and Direct Messages: An avenue for threaded discussions and direct communication adds depth to collaboration.
• Full Audit Trail: Think of it as a digital breadcrumb trail – essential for traceability, discussions, and learning as projects evolve.
• Customizable Review Workflows: Flexibility to tailor workflows to your team’s unique dynamics ensures smooth progress.
• Dashboard Insights: Quick-glance dashboards brimming with project stats empower managers and executives to steer the ship confidently.

Consider all the key players involved in the post-market surveillance process for your device portfolio, document their needs, and review these needs against the feature set of the platform and the support available from the provider.

#3: Validated System

The medical device industry is highly regulated to ensure that the products that reach patients are safe and efficacious and work as intended. Once a product reaches the market, device and diagnostic manufacturers follow stringent policies and procedures to carry out the necessary post market surveillance (PMS) activities to collect, analyze, and interpret a massive amount of data about the product’s usage, performance, safety, etc.

Your chosen SLR tool will play a vital role in the ongoing lifecycle management activities of your marketed products. It will help you prove to regulators, through required PMS reports, that your device continues to be safe and efficacious. The stakes are extremely high when it comes to the data collected and reported upon within the PMS reports for any given device.

The Software as a Service (SaaS) model is becoming increasingly common within the life science industry, with several service providers available that offer platforms and tools that support the systematic literature review process. The SaaS model benefits end users by providing access to solutions that are less expensive and cheaper to maintain as the responsibility of software maintenance rests with the service provider. Nonetheless, this arrangement means that the SaaS provider retains the authority to alter and enhance elements such as the interface and functionality of the system, according to their timeline rather than yours.

As a buyer, you should seek out a validated system to ensure that the tool meets the needs of your team and works the way that it is supposed to work. Many tools that you consider will likely fall under the SaaS category. It is paramount to ascertain that the SaaS provider has a robust validation program in place that covers the process, coverage, and services that you are purchasing.

#4: Systematic Literature Review Tool Scalability

As you survey the landscape for potential SLR tools to implement, consider the current state of your team but also the future state of your organization. A cheaper “quick fix” solution may be tantalizing initially, but the solution should not only address your immediate needs, but also easily scale to support a growing product portfolio and align with your firm’s goals over the next three, five, and years beyond.

#5: SLR Tool Customer Support and Software Development

Unfortunately, no software tool is perfect, and bugs are bound to arise due to any number of conditions. It goes without saying how important PMS activities and meeting reporting deadlines for internal and external stakeholders (global Health Authorities, Notified Bodies , etc.) are for the lifecycle management of any medical product. Strong customer support will allow your team to navigate any potential hiccups that might occur with your SLR tool.

During the vetting process, ask the potential vendors about their standard response times, how often new releases or patches are issued, etc. to ensure that they are dedicated to responding to any issues that you may encounter. In addition to a strong customer support process, you should also inquire about the software vendor’s development team. You can ask questions such as: What is on the development roadmap? What features are planned to be implemented and when? How does the tool adapt to evolving regulatory requirements? How often is user feedback considered in the development cycle?

You may find that new features they’re brewing up could be a total game-changer for your team and the process that your organization follows when performing systematic literature reviews. Choosing a partner that will consider and adapt to your needs is pivotal, so don’t shy away from asking for examples or references that indicate strong customer and development support.

#6: Regulatory Expertise

A successful regulatory affairs department requires equal parts science and art; strong scientific or technical expertise is important, but so is the ability able to interpret and act upon the regulatory policy and guidance. When searching for the perfect SLR tool, you’re bound to find several tools offered by technology providers outside of the life science industry, or those that do not have regulatory experts on staff. Tread lightly.

Picture this: a vendor that employs a team of medical writers and regulatory professionals engaged in the same work that you will be doing on the platform. This will provide you with access to their goldmine of best practices and learnings from their own interactions with Notified Bodies. Furthermore, a vendor who routinely provides regulatory services to manufacturers in the life science industry will understand the challenges of your team and implement creative solutions into the tool to address these.

Researching SLR Tools

Researching and selecting the right tool for your team can be an arduous task. But fear not, these six tips will ease the burden of implementing a new SLR system for your organization. If you’ve any questions feel free to reach out to our expert team.

Meet CAPTIS  – AI Powered Systematic Literature Review Tools

Speaking of SLR software , meet CAPTIS – the end-to-end EU MDR/IVDR compliance platform developed by Celegence for the life science industry. CAPTIS was initially conceived to automate manual tasks and facilitate project collaboration for Celegence’s own medical writers, who still routinely perform systematic literature reviews and author PMS reports for medical device and diagnostic manufacturers.

Through regular monthly meetings with all CAPTIS users, Celegence actively listens to users’ needs and shares best practices for regulatory compliance using the tool. Moreover, user feedback, whether from real-world use or insights from Notified Body interactions, frequently shapes new features that benefit all customers. CAPTIS is a validated system with several automated features and an AI Assistant – CAPTIS Copilot , that helps users perform systematic reviews and create PMS report documentation in record time. To see if CAPTIS will be a good fit for your team, drop us a line today to book a demo .

Related Posts

Mastering PMCF and PMPF for Regulatory Compliance

Harmonizing ISO 14971:2019 and FDA QMSR for Medical Device Safety

Conformity Assessment Guide: EU MDR and IVDR Compliance Strategies

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Literature Reviews

• Getting Started
• Steps for Conducting a Lit Review
• Finding "The Literature"
• Organizing/Writing
• Peer Review
• Citation/Style Guides This link opens in a new window

Quick Links

What is a literature review.

A literature review is a methodical examination of the published literature on a specific topic or research question, aimed at analyzing rather than merely summarizing scholarly works relevant to your research . It includes literature that offers background on your topic and demonstrates how it aligns with your research question.

What is the Purpose of a Literature Review?

• To help define the focus of your research topic.
• To identify existing research in your area of interest, pinpoint gaps in the existing literature, and avoid duplicating previous research.
• To gain an understanding of past and current research as well as the current developments and controversies in your field of interest.
• To recognize and assess the strengths and weaknesses of works related to your area of interest.
• To evaluate the contributions of experts, theoretical approaches, methodologies, results, conclusions, and possible opportunities for future research.

A Literature Review is NOT

• An annotated bibliography or research paper
• A collection of broad, unrelated sources
• Everything that has been written on a particular topic
• Literature criticism or a book review.

Literature Review vs Annotated Bibliography

A literature review and an annotated bibliography are both tools used to assess and present scholarly research, but they serve different purposes and have distinct formats:

Where Can I Find a Lit Review?

The Literature Review portion of a scholarly article is usually close to the beginning. It often follows the introduction , or may be combined with the introduction. The writer may discuss his or her research question first, or may choose to explain it while surveying previous literature.

If you are lucky, there will be a section heading that includes " literature review ".  If not, look for the section of the article with the most citations or footnotes .

• Next: Steps for Conducting a Lit Review >>
• Last Updated: Aug 14, 2024 5:23 PM
• URL: https://westlibrary.txwes.edu/literaturereview

MAXQDA vs. ATLAS.ti | Best Qualitative Data Analysis Software

Undecided about which computer-assisted qualitative data analysis software (CAQDAS) to use for your qualitative data? Let's compare the differences between ATLAS.ti and MAXQDA so you can make an informed decision about your ideal qualitative data analysis (QDA) platform.

Choosing the right QDA platform

Qualitative researchers have a number of options to choose from when deciding what data analysis platform is best for them. Let's look at some of the important considerations that factor into the decision-making process, and why ATLAS.ti has advantages in all of these aspects.

Intuitive interface

QDA platforms should be easy to use. Qualitative research can be complicated enough in terms of theory, study design, and data collection and analysis.

A QDA program that promises complex analyses but demands a high learning curve can end up wasting more time and effort than is necessary to generate critical insights. Conversely, an intuitive platform makes data organization, coding, and visualization simple and empowers researchers to make the most of their data.

Data organization

As the needs of qualitative researchers have evolved, so have the types of data they are likely to handle. An effective QDA platform should handle not just textual data, but also multimedia, social media data, and even geographic data.

Moreover, researchers rely on a QDA platform to organize data, especially when their research collects large numbers of documents that require substantive management.

Coding capabilities

Qualitative research invariably means coding data to provide structure necessary for data analysis. Researchers need to be able to code quickly and efficiently to ensure a robust and rigorous research process.

An effective QDA program makes coding easy and organizing codes effortless. Moreover, advanced QDA platforms enable researchers to conduct manual coding and rely on artificial intelligence to assist them in coding the data.

Visualizations of data analysis

Once researchers generate key insights from their research, they need to persuade their audience through visualizations that represent their data analysis. This allows researchers to illustrate their data in ways that even an extended text description cannot.

A good QDA platform should be capable of producing persuasive visualizations aimed at delivering core insights to their research audience, while empowering researchers to quickly and easily create those visualizations.

Working with other software

Researchers tend to rely on a variety of software programs in addition to QDA software to conduct their research. From spreadsheet tools to reference manager software, there is a range of platforms that a good QDA program should work with as seamlessly as possible.

CAQDAS should be flexible and ensure the researcher remains in full control of the analysis so that the use of the software can be adapted according to the methodology guiding the research and the tools they already use in their research.

Support and guidance

A network of continuous and comprehensive support is necessary in any endeavor, but especially in qualitative research. Researchers should be able to count on the support network behind a QDA platform to provide them with the best answers for how to conduct their research.

These resources include not only technical support and guidance on program usage, but also methodological support and project optimization. A QDA platform that offers this level of support enables researchers to draw the insights they need to persuade their research audience.

MAXQDA vs. ATLAS.ti: What's the difference?

Let's look a little more deeply into the key features of both QDA platforms where ATLAS.ti has clear distinctions over MAXQDA.

Conducting Literature Reviews

• Auto-coding with Text Search

AI-powered Data Analysis

Data analysis, visualizations, research notes in memos, interface and ease-of-use, organizing data, collaboration with team members, cloud storage for project sharing, compatible data types, comprehensive support system, overall benefits.

When it comes to choosing a CAQDAS, you may be flooded with a whole host of choices for computer-based solutions to analyze qualitative data. Because qualitative data often eludes easy analysis (e.g., what are the emergent themes in this data set relevant to my research question?), you may understandably look for a CAQDAS package to help you code your data and provide a structure useful for data analysis.

To a certain extent, all major QDA platforms provide the capability to code data. Both ATLAS.ti and MAXQDA will provide you with the basic ability to code and structure your data to rigorously generate key insights.

In ATLAS.ti, manual coding is simply a matter of highlighting text and choosing from existing codes or creating new ones to apply to the data. A pop-up window that displays your code list near your text makes the coding process quick and easy. Quick Coding allows users to apply the most recently used code to any data segment with just a few clicks, while the Code In Vivo option creates codes directly from the text.

All of the major QDA platforms can read and import reference manager data from programs such as Zotero and EndNote, which is useful for moving your research library into your project so that your literature review can seamlessly inform your data analysis. However, only ATLAS.ti Web's Paper Search gives researchers the ability to directly build a useful library of journal articles and research papers in their project. With Paper Search, users can search from over 200 million articles available through Semantic Scholar and choose the papers that are most relevant to their research. Unlike with MAXQDA, users can utilize ATLAS.ti to look for the most insightful research and import it into their project to complement and jump start their literature review.

ATLAS.ti Web's Paper Search 2.0 lets users tailor their search for literature to a particular research question, get the relevant literature complete with tailored AI summaries of the most important papers in their inquiry, and integrate the results in their research projects. Paper Search provides the capability to conduct literature reviews and shape their research in ways not seen in other major QDA platforms.

Auto-coding Tools

Various features in ATLAS.ti facilitate the automation of the coding process with greater flexibility than what MAXQDA provides. The Concepts tool looks for commonly occurring phrases that a simple word cloud can't provide, while Opinion Mining conducts a sentiment analysis on those phrases, allowing researchers to separate positive and negative sentiments while coding.

Tools such as Focus Group Coding and Named Entity Recognition can help users save time by automatically adding codes to indicate who in an interview or a focus group is speaking or to identify people, places, and organizations named in the data, respectively. Using these codes in conjunction with codes from Sentiment Analysis and Opinion Mining can help generate rich insights on how the data frames the discussion of various topics of interest in a positive, negative, or neutral light.

Text Search is more powerful in ATLAS.ti, allowing for searches of synonyms and more complex queries to get the most relevant data. The flexibility of the Text Search tool allows users to construct a single search with multiple keywords to narrow the scope of the data to a specific set of text segments that can be coded, regardless of where the data is in your project.

The Word Frequencies tool has greater flexibility than MAXQDA's Word Cloud in filtering parts of speech and providing options for stop and go lists to tailor your content analysis. As a result, users have more options for developing visualizations of their qualitative data and content analysis in ATLAS.ti.

Artificial intelligence is also a major part of coding and analyzing data in ATLAS.ti and MAXQDA. MAXQDA has an AI Assist feature to summarize and explain data, but its automated coding capabilities are different from and more limited than ATLAS.ti's AI-powered tools. For example, ATLAS.ti's Conversational AI allows users to employ a chatbot that can give insights on multiple documents in one project, while MAXQDA's equivalent can only chat with one document at a time. The broader capabilities in ATLAS.ti are ideal for synthesizing information from multiple interview respondents, survey records, or other groups of text documents, allowing users to explore overarching patterns and trends in their research inquiry.

In terms of coding, ATLAS.ti gives you the flexibility to choose the extent to which AI codes your data, whether you want your entire data set coded to suit your research inquiry or you just need a little inspiration during the coding process. Users of ATLAS.ti can code a discrete data segment with AI Suggested Codes or entire documents with AI Coding or Intentional AI Coding, both of which also create a coding structure complete with category codes and sub-codes to keep your codes organized and manageable. In contrast, MAXQDA's AI capabilities can only code one segment of data at a time, rather than entire documents, and can only suggest sub-codes of already existing codes.

AI-powered tools in both platforms can code for the general meaning of your textual data, but only ATLAS.ti's Intentional AI Coding allows users to direct the AI to code data based on specific research questions. Other AI tools will simply provide answers but largely devoid of any other context to help researchers understand where the results came from; ATLAS.ti's Intentional AI Coding provides a rich coding structure that facilitates transparent analysis, and researchers can always simply double-click on any quotation to see it in its original context, allowing researchers to begin to "open the black box" of artificial intelligence and see the whole picture provided by their data.

ATLAS.ti's Intentional AI Coding creates coding structures that are tailored to your research inquiry with category codes and sub-codes that are more relevant to your data analysis. Importantly, researchers can tell the AI how it should code their data, including specifying guiding questions and relevant codes. No other CAQDAS offers researchers this level of control over how AI-driven tools should automatically code the data.

Of course, we recommend that researchers always review the results provided to them by artificial intelligence, but the time savings between manual coding and coding with AI-powered tools will undoubtedly prove consequential to the research process.

Most importantly, ATLAS.ti users have unlimited access to our AI tools, no matter the size of their dataset. MAXQDA users can use AI tools on a limited set of data per day before paying for additional usage. This can be problematic when you need to sift through large sets of data.

On the other hand, a full license to ATLAS.ti has no restrictions on the use of any AI tools, including AI Suggested Codes, AI Coding, and Intentional AI Coding. This means that, unlike with MAXQDA, projects of all sizes can take advantage of the artificial intelligence capabilities in ATLAS.ti without incurring extra costs.

The Query Tool can easily find patterns in the data, no matter in what document the insights are located. In one interface, users in ATLAS.ti can construct detailed queries of their coded data in a manner that may require the use of multiple tools in MAXQDA. Instead of conducting multiple and sequential analyses in MAXQDA's Code Explorer or Complex Coding Query, ATLAS.ti's Query Tool can accommodate multiple criteria for codes with any combination of Boolean and proximity operators that suit your research inquiry.

Analyzing data is also easy with other tools such as Code Co-Occurrence Analysis and Code-Document Analysis, creating useful visualizations of code-code and code-document relationships more quickly in ATLAS.ti than in the equivalent MAXQDA features. Both of these tools in ATLAS.ti have a simple interface that allows users to quickly create tables to analyze potential relationships between codes, and between codes and documents, respectively. While users in MAXQDA have to navigate complicated dialog boxes for the analysis tools, many key analyses in ATLAS.ti are created by simply selecting codes and/or documents to cross examine in a table. Moreover, viewing the data supporting the analysis is easier in ATLAS.ti with an elegant interface where tables, figures, and relevant quotations are shown in the same window rather than splitting each part of the analysis in separate tools with their own set-up processes and multiple windows that can clutter your screen and analysis.

Once created, tables from Code Co-Occurrence Analaysis and Code-Document Analysis can be used to provide visualizations in the form of force-directed graphs and Sankey diagrams, visualizations that are only available in ATLAS.ti.

The Network View in ATLAS.ti provides tools for researchers to create illustrative conceptual maps and in-depth visualizations of their data. Links between different codes, quotations, memos, groups, and documents can be displayed in a visualization of theory that reflects a rich qualitative analysis of the project's data. Unlike in MAXQDA where the Network View's equivalent provides only a simple set of visualization capabilities, users can define links in an ATLAS.ti network by the nature of the relationship between codes to develop their theory and propose insights.

A fully coded project in ATLAS.ti can be analyzed qualitatively, like in Networks to help visualize theories arising from your coding structure, or quantitatively, like in the Treemap view that visualizes the most frequently occurring codes and themes. The fully integrated coding system in ATLAS.ti ultimately accommodates all kinds of research paradigms in an accessible and user-friendly manner. With automatic layout options, editable links to define the relationships in your theory, and full integration with the rest of your project, you can use Networks to visualize your theory and guide further analysis.

Other visualizations such as Sankey diagrams, force-directed graphs, and Treemaps are available in ATLAS.ti to visualize your research in multiple ways. ATLAS.ti can help researchers turn their qualitative data into insightful illustrations of code distributions, themes, and much more, to persuade audiences with informative and appealing visuals.

One area where ATLAS.ti excels over MAXQDA is the tools that facilitate the development of theoretical insights. This is undoubtedly one of those tasks that a researcher can't automate or delegate to artificial intelligence, but QDA software can make this job easier and more insightful.

Memos are an often overlooked feature in qualitative research, but are integral to many rigorous studies.A space for research memos is integrated into ATLAS.ti, allowing for useful notes, reflections, and insights on potential theoretical developments that users can jot down as insights arise. ATLAS.ti memos are intuitive and can be linked to quotations, documents, codes, and groups for organized reference. Unlike in MAXQDA, quotations in ATLAS.ti can be inserted directly into memos to facilitate seamless and integrated analysis connecting key data exemplars to critical reflections.

The complexity of MAXQDA's memo system, with different types of memos, can prove limiting to researchers if their notes relate to different entities in their project. On the other hand, ATLAS.ti allows researchers to create standalone memos or link those memos to any part of their research without restrictions, offering greater flexibility in tailoring a project to any research inquiry.

ATLAS.ti is designed to ensure that the learning curve required for qualitative data analysis is as easy as possible. Organization and coding are easier in ATLAS.ti while still providing the capabilities to generate critical insights from qualitative data. This means that you can spend less time on the menial tasks of qualitative research and more time devoted to rich analysis that is accessible to you and your research audience.

ATLAS.ti has a clean interface with a clear organization of functions and capabilities. Project entities likes documents and codes are clearly delineated, while the main analysis tools are organized in one place (either in the Analysis menu in Mac or in the Analysis tab in Windows) for easy access.

Moreover, the interface allows you to organize your research in a single window and switch between multiple tabs to view your research through multiple angles. MAXQDA only has the option of undocking document windows from the main screen, a setup which can easily get cluttered without the necessary level of organization.

In-depth research projects of all sizes will undoubtedly require organization to facilitate data analysis. Even researchers with small research projects can get bogged down in the tedious tasks of categorizing documents by different data types, data collection methods, research sites, and even research participant demographics.

As cumbersome as this challenge is, organization within an entire project is necessary because the greater the level of organization the QDA platform can provide, the richer the analysis. Creswell and Poth (2018), when comparing ATLAS.ti, MAXQDA, NVivo, and HyperRESEARCH, point out ATLAS.ti's ability to quickly search and find data, which is integral to data analysis that is easy and accessible to users.

ATLAS.ti excels in data organization with an intuitive Document Manager, allowing you to sort documents by multiple categories represented by document groups. Document groups provide a level of flexibility not seen in MAXQDA, which provides a traditional file system for documents that might limit the organization of data if your documents simultaneously belong to multiple categories or analyses.

In ATLAS.ti, document groups are not mutually exclusive, meaning you can organize data by any number of analytical or organizational categories depending on your research inquiry, facilitating analysis of your data from multiple angles. This is useful when you need to, for example, sort respondent data by gender, age, ethnicity, income level, or any other category useful to your research inquiry.

Teamwork on qualitative research projects requires a QDA platform that ensures easy integration of project work. Both ATLAS.ti and MAXQDA have tools to help organize coders' efforts in a collaborative research project and calculate intercoder agreement.

However, ATLAS.ti offers various features that facilitate project sharing among team members, such as ATLAS.ti Web's real-time collaboration for team-based coding. ATLAS.ti is the only QDA software that offers full access to all platforms, including the online ATLAS.ti Web, giving researchers ultimate flexibility in deciding where and how they want to collaborate with others.

ATLAS.ti Desktop also allows for collaboration between users through asynchronous project storage. ATLAS.ti users can store their projects in our cloud storage space and share them effortlessly with other users, who can download projects onto their own devices and continue the work of coding and analysis.

Moreover, while MAXQDA limits team access to projects to up to five users, ATLAS.ti has no limits, meaning all ATLAS.ti users can join a project, regardless of what type of license each person has or where in the world they are located. This allows researchers of different institutions and countries to collaborate on the same research project without restriction.

ATLAS.ti's platform can also accommodate a greater variety of qualitative data than MAXQDA. As the needs of qualitative researchers have evolved over the years, the typical project workflow has included various forms of data, including PDF files, multimedia files for images, audio, and video, and files containing geographical data. In-depth research projects rely on various forms of data, all of which can be included in an ATLAS.ti project.

Both ATLAS.ti and MAXQDA are capable of reading commonly used file formats such as text files, GIF files, and PDF files. However, ATLAS.ti is compatible with other file types such as BMP files for images, MOBI files for eBooks, and documents handling geographic data. The wider array of file formats compatible in ATLAS.ti benefits more researchers in more research fields.

Social media research is also more flexible in ATLAS.ti. MAXQDA only allows users to import Tweets from Twitter/X, limiting researchers who want to analyze trends in social media. On the other hand, researchers can import data from any social media post, such as comments from YouTube videos, TikTok posts, Instagram posts, and more into any ATLAS.ti project.

ATLAS.ti users enjoy a greater degree of flexibility with PDF files. Comments in PDF files are preserved as quotations, which can be useful for literature reviews and smoothly transferring initial qualitative analyses from raw PDFs straight into ATLAS.ti.

The differences between ATLAS.ti and MAXQDA don't stop at the software platform. ATLAS.ti has devoted significant time and effort to building an entire ecosystem around the platform to support qualitative researchers at all stages of the research process.

License purchasing and user management are easy with ATLAS.ti. There are no hidden charges or fees for extra features; unlike in MAXQDA, a Desktop+Web license entitles users to a fully functional QDA platform in ATLAS.ti with no restrictions, no matter the size and scope of the research project. In addition, multi-user ATLAS.ti licenses can be shared with as many people as desired anywhere in the world, with no limitations on the number of software installations, devices that can use ATLAS.ti, access to Windows, Mac, or Web platforms.

In other words, an ATLAS.ti multi-user license offers ultimate flexibility, so license admins can share access with anyone else and easily manage the license users in their personal ATLAS.ti admin account. The license management system automatically frees up a seat in the license as soon as one person logs out of their session, allowing anyone else to occupy that seat when they log into ATLAS.ti Windows, Mac, or Web.

ATLAS.ti has a whole host of online trainings and written resources to guide users on qualitative research methodology and the ATLAS.ti platform. All of these resources, written by experts in ATLAS.ti, are created with the goal of instilling users with greater expertise in qualitative research.

ATLAS.ti users enjoy free perpetual access to a support team of experts who can answer technical and methodological questions, 24 hours a day, 5 days a week. Through email, telephone, and live chat, ATLAS.ti users can take advantage of a level of user support that isn't available with other QDA platforms.

While ATLAS.ti and MAXQDA serve qualitative researchers in all the core aspects of data organization and data analysis, ATLAS.ti has a number of distinct advantages that add up to overall benefits that make the research process easier and more insightful.

User-Friendly Interface

Users turn to ATLAS.ti for its intuitive and user-friendly interface. The platform is designed to make the research process as easy as possible, enabling researchers to quickly grasp its functionalities and focus more on their data analysis rather than software navigation. With a clean and organized layout, ATLAS.ti provides clear delineation of project entities such as documents, codes, and memos, making it easy to manage and analyze data efficiently.

Unlike MAXQDA's interface, which can become cluttered with undocked windows, ATLAS.ti's single-window interface with multiple tabs ensures a streamlined workflow. This ease of use allows researchers to dedicate more time to generating critical insights from their qualitative data.

Handling Qualitative Data

ATLAS.ti offers significant flexibility in data handling, accommodating a broader range of file types and data formats than MAXQDA. Whether dealing with text files, PDFs, multimedia files, or even geographical data, ATLAS.ti seamlessly integrates these diverse data sources into a cohesive project. Researchers can also import data from various social media platforms, not just limited to Twitter/X like in MAXQDA.

Additionally, ATLAS.ti’s ability to preserve PDF comments as quotations enhances the literature review process, making it easier to transfer initial qualitative analyses directly into the platform. This extensive compatibility ensures that researchers can include all relevant data in their analysis, providing a more comprehensive understanding of their research topic.

Easy and Effortless Collaboration

ATLAS.ti excels in facilitating collaboration among research team members, providing tools that enable real-time and asynchronous teamwork. With ATLAS.ti Web's real-time collaboration feature, multiple coders can work on the same project simultaneously, ensuring consistent coding and consensus among team members. In contrast, MAXQDA limits team access to projects to up to five users, which can hinder large, multi-institutional research efforts.

Furthermore, ATLAS.ti offers cloud storage for easy project sharing and collaboration without any restrictions on the number of users or licenses. This robust collaboration capability allows researchers from different locations and institutions to work together seamlessly, enhancing the overall research process and ensuring more comprehensive and rigorous data analysis.

Licensing Options

ATLAS.ti offers transparent licensing options with no hidden fees, allowing individuals and organizations to fully utilize its capabilities without unexpected financial burdens. The software is available on multiple platforms, including desktop, online, and free mobile versions. Each version of ATLAS.ti is natively designed for its specific operating system, ensuring optimal functionality and performance. Researchers can seamlessly move their projects across ATLAS.ti Desktop, Web, and Mobile, enjoying 100% compatibility between ATLAS.ti Windows and Mac. This flexibility enables researchers to work efficiently from the office, at home, or in the field, and allows teams to collaborate smoothly, even when using a mix of Windows and Mac computers. This comprehensive accessibility supports a dynamic research environment and caters to the modern researcher’s mobility needs.

More Powerful AI Tools

ATLAS.ti offers unparalleled artificial intelligence capabilities not seen in other QDA platforms, suiting researchers of all backgrounds and preferences. With the flexibility afforded by the various AI-powered tools in ATLAS.ti, users can code a little bit or a lot of their data with AI, which is made more powerful with the capability to tailor the coding process to specific research questions defined by the researcher. You can also engage in critical reflections with Conversational AI or just get to the salient points of the data with AI Summaries.

Most importantly, researchers can always easily access the exact data segments from which any AI results are generated, offering researchers greater transparency and control over how AI analyzes their data. Moreover, ATLAS.ti's AI capabilities come with a paid license, requiring none of the extra fees or restrictions found with the use of MAXQDA's AI tools. Regardless of the size of your data set, you can take full advantage of ATLAS.ti's AI-powered features and make the most of your qualitative data.

Make ATLAS.ti your qualitative data analysis solution

Take advantage of powerful analysis tools found nowhere else. Download a free trial of ATLAS.ti today.

Generative Artificial Intelligence Use in Optimising Software Engineering Process: A Systematic Literature Review

• August 2024
• Applied Computer Systems 29(1):68-77
• 29(1):68-77
• This person is not on ResearchGate, or hasn't claimed this research yet.

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Open Access

Peer-reviewed

Research Article

Impact of climate change on maternal health outcomes: An evidence gap map review

Roles Data curation, Formal analysis, Methodology, Visualization, Writing – original draft

* E-mail: [email protected]

Affiliation College of Health Sciences, Faculty of Nursing, University of Alberta, Edmonton, Canada

Roles Data curation, Formal analysis, Visualization, Writing – review & editing

Roles Data curation, Investigation, Methodology, Software

Affiliation John W. Scott Health Sciences Librarian, Walter C. Mackenzie Health Sciences Centre, University of Alberta Library, Edmonton, Canada

Roles Conceptualization, Investigation, Project administration, Writing – review & editing

Affiliation Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada

Roles Conceptualization, Investigation, Supervision, Writing – review & editing

Affiliation Department of Mental Health, School of Nursing and Midwifery, College of Health Sciences, University of Ghana, Legon, Accra, Ghana

Roles Conceptualization, Investigation, Project administration, Supervision, Writing – review & editing

Affiliation School of Allied Health Professions, Nursing and Midwifery, University of Sheffield and Doncaster and Bassetlaw Teaching Hospital Trust, Sheffield, United Kingdom

Roles Conceptualization, Methodology, Project administration, Supervision, Writing – review & editing

Affiliation Department de Enfermagem Aplicada, Escola de Enfermagem, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brasil

Roles Conceptualization, Supervision, Writing – review & editing

Affiliation College of Nursing, University of Saskatchewan, Saskatoon, Canada

Roles Conceptualization, Investigation, Methodology, Supervision, Writing – review & editing

Affiliation School of Public Health, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, Australia

• Salima Meherali, 
• Saba Nisa, 
• Yared Asmare Aynalem, 
• Megan Kennedy, 
• Bukola Salami, 
• Samuel Adjorlolo, 
• Parveen Ali, 
• Kênia Lara Silva, 
• Lydia Aziato, 

• Published: August 19, 2024
• https://doi.org/10.1371/journal.pgph.0003540
• Peer Review
• Reader Comments

Climate change poses unique challenges to maternal well-being and increases complications during pregnancy and childbirth globally. This evidence gap map (EGM) aims to identify gaps in existing knowledge and areas where further research related to climate change and its impact on maternal health is required. The following databases were searched individually from inception to present: Medline, EMBASE, and Global Health via OVID; Cumulative Index to Nursing and Allied Health Literature (CINAHL) via EBSCOhost; Scopus; and organizational websites. In this EGM, we integrated 133 studies published in English, including qualitative, quantitative, reviews and grey literature that examined the impact of climate change on maternal health (women aged 15–45). We used Covidence to screen studies and Evidence for Policy and Practice Information (Eppi reviewer)/Eppi Mapper software to generate the EGM. Data extraction and qualitative appraisal of the studies was done using critical appraisal tools. The study protocol was registered in International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) # INPLASY202370085. Out of 133 included studies, forty seven studies were of high quality, seventy nine moderate equality and seven low quality. This EGM found notable gaps in the literature regarding the distribution of research across regions. We found significant research in North America (51) and Asia (40 studies). However, Africa and the Caribbean had fewer studies, highlighting potential disparities in research attention and resources. Moreover, while the impact of extreme heat emerged as a prominent factor impacting maternal well-being, there is a need for further investigation into other climate-related factors such as drought. Additionally, while preterm stillbirth and maternal mortality have gained attention, there is an overlook of malnutrition and food insecurity indicators that require attention in future research. The EGM identifies existing research gaps in climate change and maternal health. It emphasizes the need for global collaboration and targeted interventions to address disparities and inform climate-responsive policies.

Citation: Meherali S, Nisa S, Aynalem YA, Kennedy M, Salami B, Adjorlolo S, et al. (2024) Impact of climate change on maternal health outcomes: An evidence gap map review. PLOS Glob Public Health 4(8): e0003540. https://doi.org/10.1371/journal.pgph.0003540

Editor: Rahul Goel, Indian Institute of Technology Delhi, INDIA

Received: May 17, 2024; Accepted: July 10, 2024; Published: August 19, 2024

Copyright: © 2024 Meherali et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data is freely available in the manuscript itself and uploaded supplementary files.

Funding: Author (SM) received funding from World Universities Network Research Development Funds (WUN RDF) for this project. Grant # RES0061104. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interest exist.

Introduction

The World Health Organization (WHO) refers to maternal health as women’s health during pregnancy, childbirth, and postpartum [ 1 ]. According to a report by the WHO [ 2 ], an estimated 287,000 women die due to maternal health complications each year globally, with almost 800 maternal deaths occurring daily, accounting for death every two minutes. Furthermore, regional disparities in maternal health are evident across the world. In 2020, Europe and Northern America, Eastern and South-Eastern Asia, Northern Africa, Western Asia, Latin America, and the Caribbean exhibited low maternal mortality rates below hundred. However, Sub-Saharan Africa alone contributed to about seventy percent of global maternal deaths in 2020, with Central and Southern Asia accounting for nearly seventeen percent [ 2 ]. Climate change increases the vulnerability to adverse maternal health outcomes. Mothers, especially those in resource-limited settings, face the heightened impact of climate change during the stages of pregnancy, childbirth, and the postpartum period [ 3 ]. Climate change negatively impacts maternal health during pregnancy, causing thermo-regulatory challenges due to internal heat production from fetal growth [ 4 ]. Exposure to the effects of climate change at the early stage of fetal development can cause immediate harm or damage that becomes evident later in life, resulting in lasting effects over a lifetime and even over generations [ 5 ].

Climate change affects maternal health in many ways, impacting various aspects of well-being through both direct and indirect mechanisms. Physiological risks such as extreme heat leads to dehydration by excessive sweating in pregnant women and causes the onset of early labour [ 6 ]. High temperatures can also increase the risk of preterm birth, low birth weight, abortion, and stillbirths. 3 Extreme cold and earthquake exposure in pregnancy has been associated with maternal hypertension and preeclampsia [ 7 – 9 ], and gestational diabetes [ 10 ]. Climate change indirectly affects mental health by causing anxiety and depression due to uncertainty about the environment, worries about how it will impact their children in the long term [ 11 , 12 ]. During pregnancy, the energy demand of women increases by approximately twenty percent, which also continues throughout the period of breastfeeding [ 13 ]. However, the socioeconomic challenges posed by climate change exacerbate issues related to food insecurity and limit access to antenatal and postnatal care [ 14 ]. The impact of climate change, mainly through events like drought, extends beyond food security, leading to significant consequences such as livestock deaths, crop failure, and severe malnutrition [ 13 ]. Furthermore, climate impacts the mental health of mothers and their children in their growth and development [ 5 ].

Over the past five years, the world has witnessed increased climate change events such as extreme heat, wildfires, and droughts [ 15 – 18 ]. The impacts of climate change exhibit geographical variations, affecting regions, countries, and specific locations differently. Vulnerable regions face higher risks, as research indicates that 3.6 billion people reside in areas highly susceptible to climate change [ 2 ]. The vulnerability of regions has escalated over time, with increases observed from 1990 to 2017 in the African region (28.4% to 31.3%), Southeast Asia region (28.3% to 31.3%), and the Western Pacific region (33.2% to 36.6%) (19). In 2020, 770 million people faced hunger, primarily in Africa and Asia, and vector-borne diseases posed a significant threat, causing over 700,000 annual deaths [ 2 ]. Without preventive actions, the WHO conservatively estimates an additional 295,000 yearly maternal deaths by 2030 due to climate change impacts on diseases like malaria and coastal flooding [ 2 ]. Furthermore, differentiation in geographical location, such as high temperature, increases the risk of heat shock and will be most prominent in already hot countries and for people with physically demanding labour [ 13 ].

While the effects of climate change on maternal physical health, psychological health, and food security have garnered attention in specific regions, there is a lack of understanding of how climate change affects maternal well-being in diverse geographical contexts. This review aims to bridge this gap by systematically mapping the global evidence available on the impact of climate change on maternal well-being by generating the evidence gap map (EGM).

Why it is crucial to develop an EGM

An EGM is a systematic and visual representation of the existing evidence, or lack thereof, on a specific research question or topic. EGMs help researchers, policymakers, and practitioners make informed decisions about where additional research efforts are required to address gaps in understanding or implementation [ 19 ]. EGMs typically represent and categorize studies based on specific criteria such as the number of studies, study designs, intervention/ exposure, outcomes, and quality appraisal of the included studies [ 19 ]. Additionally, the EGM aids in avoiding duplication of research efforts and resources, fostering collaboration, and maximizing the impact of interventions [ 19 ]. We conducted an EGM on climate change’s impact on maternal health following Campbell Standards ( S1 File ). Our EGM provides access to the available research evidence on the impact of climate on maternal health outcomes. Each row corresponds to different exposures or events associated with climate change, while the columns outline the outcomes related to the impact of climate change on maternal health. The segmenting section provides information on the number of included studies, the qualitative appraisal of these studies, and the study designs.

The study protocol was registered with International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) # INPLASY202370085.

Search strategy

The search strategy for this EGM is reported in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols: Extension for Scoping Reviews for Searching (PRISMA-S) extension 22 ( Fig 1 ) and followed Prisma reporting checklist ( S2 File ). The search strategy was developed by an experienced health sciences librarian at the University of Alberta (M.K.) in consultation with the research team. The following databases were searched individually from inception to (13 January 2024): Medline, EMBASE, and Global Health via OVID; Cumulative Index to Nursing and Allied Health Literature (CINAHL) via EBSCOhost; Scopus; and organizational websites. The search strategy focused on maternal health-related concepts, including maternal health, maternal mortality, and perinatal death. It also explored concepts related to maternal health services and pregnancy care. The search incorporated terms associated with pregnancy, labour, obstetrics, pregnancy outcomes, complications, and various maternal disorders. Additionally, it addressed climate change-related concepts such as the carbon cycle, global warming, droughts, floods, and extreme weather events. The strategy excluded non-human studies ( S3 File ). A total of 6895 studies were initially identified from various databases. Using Covidence software and manual review, duplicates were carefully removed. Subsequently, 300 studies underwent screening based on eligibility c criteria, with 133 studies ultimately included in this review.

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https://doi.org/10.1371/journal.pgph.0003540.g001

Selection criteria

Our selection criteria focused on primary studies (qualitative and quantitative), reviews (scoping, systematic), and grey literature that specifically examined the impact of any type of climate change on maternal health. We included studies published in English, with the target population being women aged 15–49. The review considered studies conducted globally, regardless of settings or context. Due to language limitations, only literature published in English was deemed eligible for inclusion. We excluded studies that did not focus on maternal health aged 15–49 and those published in languages other than English. Inaccessible full-text articles were also excluded after contact with the authors.

Screening and data extraction

All studies identified from the databases were imported into Covidence, an online screening software [ 20 ]. We used Covidence for title abstract screening and full-text screening. Two reviewers, SN and YA, independently completed the screening phase, with any conflicts resolved by a third reviewer, SM. Articles meeting the final inclusion criteria were exported to EndNote as RIS files [ 21 ] and then transferred to Evidence for Policy and Practice Information (EPPI) Reviewer for coding [ 19 ]. Finally, a total of 133 studies were included in our study. Data extraction was done using an EPPI reviewer software (version 6.15.0.2). Data extraction as a table was also done in Word to enhance transparency ( S4 File ). We used Eppi Reviewer software to create an EGM ( Fig 2 ). The software helped us code detailed information, including intervention outcomes and quality appraisals for all the studies. This EGM can be accessed by scanning QR code mentioned in Fig 2 and this data can be used to identify areas of available evidence related to climate change and maternal health outcomes globally.

https://doi.org/10.1371/journal.pgph.0003540.g002

Quality appraisal

Critical appraisal of all the included studies was done using specific tools: Assessment of Multiple Systematic Reviews 2 (AMSTAR) for systematic reviews (RCTs and non-RCTs), the Mixed Methods Appraisal Tool (MMAT) for primary studies (qualitative and quantitative), and a Qualitative Meta-Review Quality Assessment Tool for the qualitative synthesis. Out of the total one hundred and thirty-three studies, forty-seven were classified as high quality, indicating a robust methodology and reliability of results. Additionally, seventy-nine studies were deemed moderate quality, suggesting satisfactory methodological rigor. On the other hand, seven studies were categorized as low quality, implying potential limitations in study design or execution. This quality assessment provides a comprehensive overview of the reliability and strength of the evidence synthesized in our research.

To aid readers in understanding specialized terminology, a glossary is provided at the end of this paper, offering concise definitions of key terms for climate change events and outcomes used in our study.

The findings of this EGM highlight critical gaps in evidence. The details of the gaps are discussed below ( Fig 3 ).

https://doi.org/10.1371/journal.pgph.0003540.g003

Evidence mapping of publication trends across years

Our findings reveal a positive trend in the research landscape, demonstrating a growing focus on the impact of climate change on maternal health from 2012 to 2023. Starting with two publications in 2012, the numbers have steadily increased, reaching a peak of twenty-seven publications in 2022. The significant surge to twenty-seven publications in 2022 suggests heightened research interest and dedication to understanding the complex dynamics. While there was a slight regression in 2023 with ten publications, the overall positive trend highlights a promising trajectory in exploring climate change’s implications for maternal health ( Fig 4 ).

https://doi.org/10.1371/journal.pgph.0003540.g004

Disparities in evidence distribution across regions

We found a variation in the distribution of available evidence across regions. The EGM review revealed that Asia significantly contributes to the literature on the impact of climate change on mothers with forty studies, closely followed by North America with fifty-one. Europe adds to the discourse with nine studies, Oceania one, South America seven, the Caribbean six, and Africa with a comparatively lower count of five evidence. The observed concentration of research in North America and Asia suggests a heightened research emphasis in these regions on understanding the intricate interplay between climate change and maternal health. Conversely, Africa and the Caribbean emerge with fewer published studies, indicating a potential gap in research exploration in these areas. This geographical distribution of studies reflects the research priorities of different regions and raises important considerations regarding the global inclusivity of evidence. For a visual representation of this distribution, refer to ( Fig 5 ).

https://doi.org/10.1371/journal.pgph.0003540.g005

Findings by climate change events

This EGM ( Fig 2 ) delves deeply into the repercussions of climate change on maternal health, covering a spectrum of occurrences like extreme heat, cold, storms, floods, wildfires, earthquakes, and droughts. The comprehensive analysis reveals a significant research study conducted on extreme heat stands out with eighty-seven studies, twenty-four studies on extreme cold, earthquakes follow closely with thirty-nine studies, while storms, including hurricanes, cyclones, dust storms, and tornadoes, draw attention with thirty-two studies, providing insights into their effects on maternal health dynamics. The narrative shifts to wildfire (nineteen studies) and floods (sixteen studies), contributing to understanding water-induced impacts on maternal health. However, drought emerges as the least researched event, with only two studies dedicated to unravelling its subtle yet profound consequences on maternal health. These findings emphasize the urgency for inclusive research across all climate events, like droughts, to shape effective strategies for preserving maternal health amid a changing climate.

Findings by outcomes

Regarding maternal health-related outcomes due to climate change, the studies predominantly focus on several crucial indicators. The EGM found a concentration of studies (eight) investigating the impact of climate change on the incidence of miscarriage, shedding light on the susceptibility of pregnancies to environmental shifts. Additionally, stillbirth is extensively covered in twenty-six studies, while preterm birth is a focal point in sixty studies. Other outcomes under scrutiny include placental abruption (six studies), fetal growth restriction (eight studies), maternal mortality (three studies), malnutrition (four studies), gestational diabetes (eight studies), hypertensive disorders of pregnancy (thirteen studies), infertility (seven studies), neonatal mortality (four studies), congenital birth defects (five studies), low birth weight (thirty-two studies), peritraumatic/posttraumatic stress (six studies), depression/postpartum depression (twenty seven studies), domestic violence and rape (three studies), and reduced access to service utilization (three studies). Despite the existing evidence illuminating the impact of climate change on maternal health, there is a critical need to explore specific areas that have received insufficient attention. For instance, there is a notable dearth of research focusing on mothers with pre-existing chronic conditions. There is a notable absence of intervention studies aimed at improving the impact of climate change on maternal health. Moreover, research on climate change impact on breast feeding patterns, access to contraception and impact on social support is lacking. The lack of comprehensive research into effective interventions hampers our ability to develop strategies to enhance pregnant individuals’ well-being in the face of environmental challenges. The shortage of such intervention studies highlights a critical gap in knowledge, emphasizing the urgent need for targeted research efforts.

The findings of the EGM identify and categorize existing evidence, highlighting both areas of knowledge and research gaps. The observed upward trajectory in the number of studies examining the impact of climate change on maternal health, with a peak in 2023, as illustrated in Fig 4 , aligns with the growing global awareness of the intricate relationship between environmental shifts and maternal health [ 19 , 22 , 23 ]. This surge in research activity suggests an increasing recognition of the need to explore and comprehend the multifaceted implications of climate change on maternal health. The geographic distribution of these studies in our EGM unveils disparities across different regions ( Fig 5 ). Notably, North America and Asia emerge as focal points, boasting fifty-one and forty studies, respectively. This concentration may be attributed to these regions’ diverse climate events, population sizes, and research capacities [ 24 , 25 ] underscoring the significance of understanding region-specific nuances in the climate-maternal health discourse. Conversely, the limited representation in Africa and the Caribbean, with only five and 6 studies, respectively, draws attention to potential research gaps. The scarcity of studies in these regions may indicate challenges such as limited research infrastructure funding disparities or a potential underestimation of the impact of climate change on maternal health in these specific contexts [ 3 , 26 – 28 ]. While the increasing number of studies reflects progress, the regional disparities emphasize the imperative of a more equitable distribution of research efforts. A nuanced understanding of the impact of climate change on maternal health necessitates collaborative and region-specific investigations, ensuring that interventions and policies are effectively tailored to address the distinct challenges mothers face in different parts of the world.

The number of studies on extreme heat, earthquakes, and storms reflects a commendable effort to understand the complexities of these events and their implications on maternal health. The substantial attention given to extreme heat aligns with recognizing rising temperatures as a critical factor in climate change, with numerous studies emphasizing the adverse effects on maternal health [ 29 – 31 ]. Similarly, the focus on earthquakes and storms, including hurricanes, cyclones, dust storms, and tornadoes, acknowledges the urgency of addressing the maternal health risks associated with natural disasters. Existing literature has consistently highlighted the vulnerability of pregnant women during such events, emphasizing the need for targeted interventions and disaster preparedness strategies [ 32 – 35 ]. However, the EGM reveals a significant void in the research landscape regarding the consequences of drought on maternal health. With only two studies addressing this aspect, there is a glaring lack of understanding regarding the subtle yet profound impacts of prolonged water and food scarcity on pregnant women. This gap is concerning, given the increasing frequency and severity of drought events associated with climate change [ 36 – 38 ].

In the discourse surrounding maternal health outcomes influenced by climate change, a notable imbalance emerges in the attention afforded to specific dimensions. While mental health outcomes, stillbirth, and preterm birth have garnered significant focus, there exists a discernible lack of attention to crucial facets such as maternal mortality, malnutrition, food insecurity, and the heightened risks of domestic violence and rape. Maternal health directly influences child health. Ignoring these concerns may result in adverse effects on the well-being and development of children [ 39 ]. Malnutrition resulting from food insecurity increases the risk of complications during pregnancy, such as gestational diabetes, anemia, and low birth weight [ 40 ]. Domestic violence and sexual assault can have significant implications for reproductive health. Unplanned pregnancies, sexually transmitted infections (STIs) [ 41 ], and long-term reproductive health issues may arise, requiring appropriate medical attention. Future research should prioritize investigating the specific challenges posed by drought, exploring the intricate links between water and food scarcity, maternal well-being, and pregnancy outcomes. Moreover, the identified gaps in our study regarding certain outcomes, such as malnutrition, domestic violence, and reduced access to service utilization, underscore the need for more comprehensive investigations into these less-explored facets.

Implications

Efforts should prioritize inclusive studies, addressing vulnerabilities of marginalized populations, for a more nuanced understanding and tailored interventions in the face of climate change affecting maternal health globally. Furthermore, integrating climate change’s impact on maternal health into educational programs ensures that future healthcare professionals are well-prepared to address emerging challenges. It also supports the idea of collaboration with urban planners to design heat-resilient urban environments with consideration given to green spaces, shade provision, and climate-sensitive infrastructure to mitigate the impact of high temperatures on pregnant individuals. The intersection of climate change and maternal health demands proactive adaptation strategies, resilient healthcare systems, and global efforts to mitigate the environmental factors contributing to these adverse outcomes. Moreover, programs related to mental health of mothers and their children should be designed to meet their needs in the era of climate change.

This EGM acknowledges several limitations that merit consideration. The decision to conduct searches exclusively in English, introduces a potential language bias. The exclusion of searches in other languages may have led to the oversight of valuable evidence, potentially explaining the limited representation of studies related to the Caribbean and Central Africa. Additionally, some primary studies and systematic reviews lacked clarity regarding certain methodological aspects, hindering the confidence rating determined through the quality appraisal process. Enhanced methodological transparency in these instances could have improved the overall robustness of the EGM. These limitations underscore the importance of interpreting the EGM findings with a degree of caution and highlight areas for improvement in future research endeavours.

While existing research has effectively addressed the maternal health impacts of specific climate events, the EGM underscores the urgent need for a more balanced exploration, particularly regarding the understudied consequences of climate change events such as drought, wildfire and floods in different regions. It is a call to action for researchers, policymakers, and public health practitioners to prioritize and support studies addressing the impact of climate change on maternal health. While this EGM effectively addresses the question of ’what exists,’ there is a pressing need for additional interventional studies to delve deeper into determining the most effective strategies for enhancing maternal health in resilience to climate change. A more comprehensive examination of interventions and outcomes on a global scale is essential to identify best practices and inform robust strategies that can effectively address the intersection of maternal health in relation to climate change.

Glossary of terms

• Extreme Heat: Involves heat waves, high temperatures, and ambient temperatures.
• Extreme Cold: Encompasses occurrences such as low temperature (Cold), cold spells and ice storms.
• Storms: Includes atmospheric disturbances, including hurricanes, typhoons, cyclones, and volcanic eruptions.
• Drought: Unusually low precipitation that causes water scarcity.
• Floods: Overflow of water onto land, typically from heavy rain or melting snow.
• Wildfire Uncontrolled and rapidly spreading fire in vegetation, forests, or grasslands.
• Earthquake: A sudden and pronounced shaking of the Earth’s surface caused by the movement of tectonic plates beneath
• Maternal mortality: The death of a woman during pregnancy, childbirth, or within 42 days after delivery
• Gestational Diabetes: Diabetes that develops during pregnancy, typically in the second or third trimester, and is characterized by elevated blood sugar levels
• Hypertensive disorders of pregnancy: A group of conditions characterized by high blood pressure during pregnancy, including gestational hypertension, preeclampsia, and eclampsia, which can pose risks to both the mother and the baby.
• Infertility: Inability to carry a pregnancy
• Malnutrition : A health condition resulting from an inadequate or imbalanced intake of essential nutrients, leading to physical and developmental issues.
• Peritraumatic/Posttraumatic Stress: Emotional distress experienced during or after a traumatic event, potentially affecting mental well-being.
• Depression/Postpartum Depression: Mood disorders characterized by persistent feelings of sadness or loss of interest, occurring either during or after pregnancy.
• Domestic Violence and Rape: Physical, emotional, or sexual abuse within intimate relationships, including instances of non-consensual sexual assault.
• Reduced Access to Service Utilization: Barriers or limitations preventing individuals from accessing necessary health or support services during pregnancy and childbirth.
• Miscarriage: Unintended termination of a pregnancy before the 20th week, typically involving spontaneous expulsion of the fetus from the uterus.
• Stillbirth: A baby is born without signs of life after 20 weeks of gestation.
• Preterm Birth: The delivery of a baby before completing 37 weeks of pregnancy.
• Placental Abruption: The premature separation of the placenta from the uterus before the baby is born, which can lead to bleeding and complications for both the mother and the baby.
• Fetal growth restriction: A condition in which a fetus does not reach its expected size or fails to grow at the normal rate during pregnancy, potentially leading to health complications for the baby.
• Neonatal Mortality: The death of a newborn within the first 28 days of life.
• Congenital Birth Defects: Structural or functional abnormalities present at birth, often resulting from genetic or environmental factors affecting fetal development.
• Low Birth Weight: The condition of a newborn weighing less than 2,500 grams (5.5 pounds) at birth.

Supporting information

S1 file. campbell collaboration checklist for evidence and gap maps: reporting standards..

https://doi.org/10.1371/journal.pgph.0003540.s001

S2 File. PRISMA checklist.

https://doi.org/10.1371/journal.pgph.0003540.s002

S3 File. Search strategy: Climate change and maternal health outcomes.

https://doi.org/10.1371/journal.pgph.0003540.s003

S4 File. Data extraction for climate change and maternal health outcomes (EGM).

https://doi.org/10.1371/journal.pgph.0003540.s004

• 1. World Health Organization. (2019, September 23). Maternal health. https://www.who.int/health-topics/maternal-health#tab=tab_1 .
• 2. World Health Organization. (2023, February 22). Maternal mortality. World Health Organization (WHO). https://www.who.int/news-room/fact-sheets/detail/maternal-mortality .
• View Article
• PubMed/NCBI
• Google Scholar
• 21. Baker A. Wellness Culture: how the wellness movement has been used to empower, profit and misinform: Emerald Group Publishing Limited; 2022.

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