google scholar literature review

Literature Review: Google Scholar

• Sample Searches
• Examples of Published Literature Reviews
• Researching Your Topic
• Subject Searching
• Google Scholar
• Track Your Work
• Citation Managers This link opens in a new window
• Citation Guides This link opens in a new window
• Tips on Writing Your Literature Review This link opens in a new window
• Research Help

Google Scholar Library Links

To see links to BenU Library subscription content in your Google Scholar search results:

• Go to Google Scholar > Settings > Library Links
• Search " Benedictine "
• Check the boxes
• Click Save and you're done!
• Google Scholar Library Links Tutorial This tutorial will guide you step-by-step through the quick setup process.

Finding Academic Literature

• 8 Winning hacks to use Google Scholar for your research paper

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Google Scholar: the ultimate guide

What is Google Scholar?

Why is google scholar better than google for finding research papers, the google scholar search results page, the first two lines: core bibliographic information, quick full text-access options, "cited by" count and other useful links, tips for searching google scholar, 1. google scholar searches are not case sensitive, 2. use keywords instead of full sentences, 3. use quotes to search for an exact match, 3. add the year to the search phrase to get articles published in a particular year, 4. use the side bar controls to adjust your search result, 5. use boolean operator to better control your searches, google scholar advanced search interface, customizing search preferences and options, using the "my library" feature in google scholar, the scope and limitations of google scholar, alternatives to google scholar, country-specific google scholar sites, frequently asked questions about google scholar, related articles.

Google Scholar (GS) is a free academic search engine that can be thought of as the academic version of Google. Rather than searching all of the indexed information on the web, it searches repositories of:

• universities
• scholarly websites

This is generally a smaller subset of the pool that Google searches. It's all done automatically, but most of the search results tend to be reliable scholarly sources.

However, Google is typically less careful about what it includes in search results than more curated, subscription-based academic databases like Scopus and Web of Science . As a result, it is important to take some time to assess the credibility of the resources linked through Google Scholar.

➡️ Take a look at our guide on the best academic databases .

One advantage of using Google Scholar is that the interface is comforting and familiar to anyone who uses Google. This lowers the learning curve of finding scholarly information .

There are a number of useful differences from a regular Google search. Google Scholar allows you to:

• copy a formatted citation in different styles including MLA and APA
• export bibliographic data (BibTeX, RIS) to use with reference management software
• explore other works have cited the listed work
• easily find full text versions of the article

Although it is free to search in Google Scholar, most of the content is not freely available. Google does its best to find copies of restricted articles in public repositories. If you are at an academic or research institution, you can also set up a library connection that allows you to see items that are available through your institution.

The Google Scholar results page differs from the Google results page in a few key ways. The search result page is, however, different and it is worth being familiar with the different pieces of information that are shown. Let's have a look at the results for the search term "machine learning.”

• The first line of each result provides the title of the document (e.g. of an article, book, chapter, or report).
• The second line provides the bibliographic information about the document, in order: the author(s), the journal or book it appears in, the year of publication, and the publisher.

Clicking on the title link will bring you to the publisher’s page where you may be able to access more information about the document. This includes the abstract and options to download the PDF.

To the far right of the entry are more direct options for obtaining the full text of the document. In this example, Google has also located a publicly available PDF of the document hosted at umich.edu . Note, that it's not guaranteed that it is the version of the article that was finally published in the journal.

Below the text snippet/abstract you can find a number of useful links.

• Cited by : the cited by link will show other articles that have cited this resource. That is a super useful feature that can help you in many ways. First, it is a good way to track the more recent research that has referenced this article, and second the fact that other researches cited this document lends greater credibility to it. But be aware that there is a lag in publication type. Therefore, an article published in 2017 will not have an extensive number of cited by results. It takes a minimum of 6 months for most articles to get published, so even if an article was using the source, the more recent article has not been published yet.
• Versions : this link will display other versions of the article or other databases where the article may be found, some of which may offer free access to the article.
• Quotation mark icon : this will display a popup with commonly used citation formats such as MLA, APA, Chicago, Harvard, and Vancouver that may be copied and pasted. Note, however, that the Google Scholar citation data is sometimes incomplete and so it is often a good idea to check this data at the source. The "cite" popup also includes links for exporting the citation data as BibTeX or RIS files that any major reference manager can import.

Pro tip: Use a reference manager like Paperpile to keep track of all your sources. Paperpile integrates with Google Scholar and many popular academic research engines and databases, so you can save references and PDFs directly to your library using the Paperpile buttons and later cite them in thousands of citation styles:

Although Google Scholar limits each search to a maximum of 1,000 results , it's still too much to explore, and you need an effective way of locating the relevant articles. Here’s a list of pro tips that will help you save time and search more effectively.

You don’t need to worry about case sensitivity when you’re using Google scholar. In other words, a search for "Machine Learning" will produce the same results as a search for "machine learning.”

Let's say your research topic is about self driving cars. For a regular Google search we might enter something like " what is the current state of the technology used for self driving cars ". In Google Scholar, you will see less than ideal results for this query .

The trick is to build a list of keywords and perform searches for them like self-driving cars, autonomous vehicles, or driverless cars. Google Scholar will assist you on that: if you start typing in the search field you will see related queries suggested by Scholar!

If you put your search phrase into quotes you can search for exact matches of that phrase in the title and the body text of the document. Without quotes, Google Scholar will treat each word separately.

This means that if you search national parks , the words will not necessarily appear together. Grouped words and exact phrases should be enclosed in quotation marks.

A search using “self-driving cars 2015,” for example, will return articles or books published in 2015.

Using the options in the left hand panel you can further restrict the search results by limiting the years covered by the search, the inclusion or exclude of patents, and you can sort the results by relevance or by date.

Searches are not case sensitive, however, there are a number of Boolean operators you can use to control the search and these must be capitalized.

• AND requires both of the words or phrases on either side to be somewhere in the record.
• NOT can be placed in front of a word or phrases to exclude results which include them.
• OR will give equal weight to results which match just one of the words or phrases on either side.

➡️ Read more about how to efficiently search online databases for academic research .

In case you got overwhelmed by the above options, here’s some illustrative examples:

Tip: Use the advanced search features in Google Scholar to narrow down your search results.

You can gain even more fine-grained control over your search by using the advanced search feature. This feature is available by clicking on the hamburger menu in the upper left and selecting the "Advanced search" menu item.

Adjusting the Google Scholar settings is not necessary for getting good results, but offers some additional customization, including the ability to enable the above-mentioned library integrations.

The settings menu is found in the hamburger menu located in the top left of the Google Scholar page. The settings are divided into five sections:

• Collections to search: by default Google scholar searches articles and includes patents, but this default can be changed if you are not interested in patents or if you wish to search case law instead.
• Bibliographic manager: you can export relevant citation data via the “Bibliography manager” subsection.
• Languages: if you wish for results to return only articles written in a specific subset of languages, you can define that here.
• Library links: as noted, Google Scholar allows you to get the Full Text of articles through your institution’s subscriptions, where available. Search for, and add, your institution here to have the relevant link included in your search results.
• Button: the Scholar Button is a Chrome extension which adds a dropdown search box to your toolbar. This allows you to search Google Scholar from any website. Moreover, if you have any text selected on the page and then click the button it will display results from a search on those words when clicked.

When signed in, Google Scholar adds some simple tools for keeping track of and organizing the articles you find. These can be useful if you are not using a full academic reference manager.

All the search results include a “save” button at the end of the bottom row of links, clicking this will add it to your "My Library".

To help you provide some structure, you can create and apply labels to the items in your library. Appended labels will appear at the end of the article titles. For example, the following article has been assigned a “RNA” label:

Within your Google Scholar library, you can also edit the metadata associated with titles. This will often be necessary as Google Scholar citation data is often faulty.

There is no official statement about how big the Scholar search index is, but unofficial estimates are in the range of about 160 million , and it is supposed to continue to grow by several million each year.

Yet, Google Scholar does not return all resources that you may get in search at you local library catalog. For example, a library database could return podcasts, videos, articles, statistics, or special collections. For now, Google Scholar has only the following publication types:

• Journal articles : articles published in journals. It's a mixture of articles from peer reviewed journals, predatory journals and pre-print archives.
• Books : links to the Google limited version of the text, when possible.
• Book chapters : chapters within a book, sometimes they are also electronically available.
• Book reviews : reviews of books, but it is not always apparent that it is a review from the search result.
• Conference proceedings : papers written as part of a conference, typically used as part of presentation at the conference.
• Court opinions .
• Patents : Google Scholar only searches patents if the option is selected in the search settings described above.

The information in Google Scholar is not cataloged by professionals. The quality of the metadata will depend heavily on the source that Google Scholar is pulling the information from. This is a much different process to how information is collected and indexed in scholarly databases such as Scopus or Web of Science .

➡️ Visit our list of the best academic databases .

Google Scholar is by far the most frequently used academic search engine , but it is not the only one. Other academic search engines include:

• Science.gov
• Semantic Scholar
• scholar.google.fr : Sur les épaules d'un géant
• scholar.google.es (Google Académico): A hombros de gigantes
• scholar.google.pt (Google Académico): Sobre os ombros de gigantes
• scholar.google.de : Auf den Schultern von Riesen

➡️ Once you’ve found some research, it’s time to read it. Take a look at our guide on how to read a scientific paper .

No. Google Scholar is a bibliographic search engine rather than a bibliographic database. In order to qualify as a database Google Scholar would need to have stable identifiers for its records.

No. Google Scholar is an academic search engine, but the records found in Google Scholar are scholarly sources.

No. Google Scholar collects research papers from all over the web, including grey literature and non-peer reviewed papers and reports.

Google Scholar does not provide any full text content itself, but links to the full text article on the publisher page, which can either be open access or paywalled content. Google Scholar tries to provide links to free versions, when possible.

The easiest way to access Google scholar is by using The Google Scholar Button. This is a browser extension that allows you easily access Google Scholar from any web page. You can install it from the Chrome Webstore .

How To Write An A-Grade Literature Review

3 straightforward steps (with examples) + free template.

By: Derek Jansen (MBA) | Expert Reviewed By: Dr. Eunice Rautenbach | October 2019

Quality research is about building onto the existing work of others , “standing on the shoulders of giants”, as Newton put it. The literature review chapter of your dissertation, thesis or research project is where you synthesise this prior work and lay the theoretical foundation for your own research.

Long story short, this chapter is a pretty big deal, which is why you want to make sure you get it right . In this post, I’ll show you exactly how to write a literature review in three straightforward steps, so you can conquer this vital chapter (the smart way).

Overview: The Literature Review Process

• Understanding the “ why “
• Finding the relevant literature
• Cataloguing and synthesising the information
• Outlining & writing up your literature review
• Example of a literature review

But first, the “why”…

Before we unpack how to write the literature review chapter, we’ve got to look at the why . To put it bluntly, if you don’t understand the function and purpose of the literature review process, there’s no way you can pull it off well. So, what exactly is the purpose of the literature review?

Well, there are (at least) four core functions:

• For you to gain an understanding (and demonstrate this understanding) of where the research is at currently, what the key arguments and disagreements are.
• For you to identify the gap(s) in the literature and then use this as justification for your own research topic.
• To help you build a conceptual framework for empirical testing (if applicable to your research topic).
• To inform your methodological choices and help you source tried and tested questionnaires (for interviews ) and measurement instruments (for surveys ).

Most students understand the first point but don’t give any thought to the rest. To get the most from the literature review process, you must keep all four points front of mind as you review the literature (more on this shortly), or you’ll land up with a wonky foundation.

Okay – with the why out the way, let’s move on to the how . As mentioned above, writing your literature review is a process, which I’ll break down into three steps:

• Finding the most suitable literature
• Understanding , distilling and organising the literature
• Planning and writing up your literature review chapter

Importantly, you must complete steps one and two before you start writing up your chapter. I know it’s very tempting, but don’t try to kill two birds with one stone and write as you read. You’ll invariably end up wasting huge amounts of time re-writing and re-shaping, or you’ll just land up with a disjointed, hard-to-digest mess . Instead, you need to read first and distil the information, then plan and execute the writing.

Step 1: Find the relevant literature

Naturally, the first step in the literature review journey is to hunt down the existing research that’s relevant to your topic. While you probably already have a decent base of this from your research proposal , you need to expand on this substantially in the dissertation or thesis itself.

Essentially, you need to be looking for any existing literature that potentially helps you answer your research question (or develop it, if that’s not yet pinned down). There are numerous ways to find relevant literature, but I’ll cover my top four tactics here. I’d suggest combining all four methods to ensure that nothing slips past you:

Method 1 – Google Scholar Scrubbing

Google’s academic search engine, Google Scholar , is a great starting point as it provides a good high-level view of the relevant journal articles for whatever keyword you throw at it. Most valuably, it tells you how many times each article has been cited, which gives you an idea of how credible (or at least, popular) it is. Some articles will be free to access, while others will require an account, which brings us to the next method.

Method 2 – University Database Scrounging

Generally, universities provide students with access to an online library, which provides access to many (but not all) of the major journals.

So, if you find an article using Google Scholar that requires paid access (which is quite likely), search for that article in your university’s database – if it’s listed there, you’ll have access. Note that, generally, the search engine capabilities of these databases are poor, so make sure you search for the exact article name, or you might not find it.

Method 3 – Journal Article Snowballing

At the end of every academic journal article, you’ll find a list of references. As with any academic writing, these references are the building blocks of the article, so if the article is relevant to your topic, there’s a good chance a portion of the referenced works will be too. Do a quick scan of the titles and see what seems relevant, then search for the relevant ones in your university’s database.

Method 4 – Dissertation Scavenging

Similar to Method 3 above, you can leverage other students’ dissertations. All you have to do is skim through literature review chapters of existing dissertations related to your topic and you’ll find a gold mine of potential literature. Usually, your university will provide you with access to previous students’ dissertations, but you can also find a much larger selection in the following databases:

• Open Access Theses & Dissertations
• Stanford SearchWorks

Keep in mind that dissertations and theses are not as academically sound as published, peer-reviewed journal articles (because they’re written by students, not professionals), so be sure to check the credibility of any sources you find using this method. You can do this by assessing the citation count of any given article in Google Scholar. If you need help with assessing the credibility of any article, or with finding relevant research in general, you can chat with one of our Research Specialists .

Alright – with a good base of literature firmly under your belt, it’s time to move onto the next step.

Need a helping hand?

Step 2: Log, catalogue and synthesise

Once you’ve built a little treasure trove of articles, it’s time to get reading and start digesting the information – what does it all mean?

While I present steps one and two (hunting and digesting) as sequential, in reality, it’s more of a back-and-forth tango – you’ll read a little , then have an idea, spot a new citation, or a new potential variable, and then go back to searching for articles. This is perfectly natural – through the reading process, your thoughts will develop , new avenues might crop up, and directional adjustments might arise. This is, after all, one of the main purposes of the literature review process (i.e. to familiarise yourself with the current state of research in your field).

As you’re working through your treasure chest, it’s essential that you simultaneously start organising the information. There are three aspects to this:

• Logging reference information
• Building an organised catalogue
• Distilling and synthesising the information

I’ll discuss each of these below:

2.1 – Log the reference information

As you read each article, you should add it to your reference management software. I usually recommend Mendeley for this purpose (see the Mendeley 101 video below), but you can use whichever software you’re comfortable with. Most importantly, make sure you load EVERY article you read into your reference manager, even if it doesn’t seem very relevant at the time.

2.2 – Build an organised catalogue

In the beginning, you might feel confident that you can remember who said what, where, and what their main arguments were. Trust me, you won’t. If you do a thorough review of the relevant literature (as you must!), you’re going to read many, many articles, and it’s simply impossible to remember who said what, when, and in what context . Also, without the bird’s eye view that a catalogue provides, you’ll miss connections between various articles, and have no view of how the research developed over time. Simply put, it’s essential to build your own catalogue of the literature.

I would suggest using Excel to build your catalogue, as it allows you to run filters, colour code and sort – all very useful when your list grows large (which it will). How you lay your spreadsheet out is up to you, but I’d suggest you have the following columns (at minimum):

• Author, date, title – Start with three columns containing this core information. This will make it easy for you to search for titles with certain words, order research by date, or group by author.
• Categories or keywords – You can either create multiple columns, one for each category/theme and then tick the relevant categories, or you can have one column with keywords.
• Key arguments/points – Use this column to succinctly convey the essence of the article, the key arguments and implications thereof for your research.
• Context – Note the socioeconomic context in which the research was undertaken. For example, US-based, respondents aged 25-35, lower- income, etc. This will be useful for making an argument about gaps in the research.
• Methodology – Note which methodology was used and why. Also, note any issues you feel arise due to the methodology. Again, you can use this to make an argument about gaps in the research.
• Quotations – Note down any quoteworthy lines you feel might be useful later.
• Notes – Make notes about anything not already covered. For example, linkages to or disagreements with other theories, questions raised but unanswered, shortcomings or limitations, and so forth.

If you’d like, you can try out our free catalog template here (see screenshot below).

2.3 – Digest and synthesise

Most importantly, as you work through the literature and build your catalogue, you need to synthesise all the information in your own mind – how does it all fit together? Look for links between the various articles and try to develop a bigger picture view of the state of the research. Some important questions to ask yourself are:

• What answers does the existing research provide to my own research questions ?
• Which points do the researchers agree (and disagree) on?
• How has the research developed over time?
• Where do the gaps in the current research lie?

To help you develop a big-picture view and synthesise all the information, you might find mind mapping software such as Freemind useful. Alternatively, if you’re a fan of physical note-taking, investing in a large whiteboard might work for you.

Step 3: Outline and write it up!

Once you’re satisfied that you have digested and distilled all the relevant literature in your mind, it’s time to put pen to paper (or rather, fingers to keyboard). There are two steps here – outlining and writing:

3.1 – Draw up your outline

Having spent so much time reading, it might be tempting to just start writing up without a clear structure in mind. However, it’s critically important to decide on your structure and develop a detailed outline before you write anything. Your literature review chapter needs to present a clear, logical and an easy to follow narrative – and that requires some planning. Don’t try to wing it!

Naturally, you won’t always follow the plan to the letter, but without a detailed outline, you’re more than likely going to end up with a disjointed pile of waffle , and then you’re going to spend a far greater amount of time re-writing, hacking and patching. The adage, “measure twice, cut once” is very suitable here.

In terms of structure, the first decision you’ll have to make is whether you’ll lay out your review thematically (into themes) or chronologically (by date/period). The right choice depends on your topic, research objectives and research questions, which we discuss in this article .

Once that’s decided, you need to draw up an outline of your entire chapter in bullet point format. Try to get as detailed as possible, so that you know exactly what you’ll cover where, how each section will connect to the next, and how your entire argument will develop throughout the chapter. Also, at this stage, it’s a good idea to allocate rough word count limits for each section, so that you can identify word count problems before you’ve spent weeks or months writing!

PS – check out our free literature review chapter template…

3.2 – Get writing

With a detailed outline at your side, it’s time to start writing up (finally!). At this stage, it’s common to feel a bit of writer’s block and find yourself procrastinating under the pressure of finally having to put something on paper. To help with this, remember that the objective of the first draft is not perfection – it’s simply to get your thoughts out of your head and onto paper, after which you can refine them. The structure might change a little, the word count allocations might shift and shuffle, and you might add or remove a section – that’s all okay. Don’t worry about all this on your first draft – just get your thoughts down on paper.

Once you’ve got a full first draft (however rough it may be), step away from it for a day or two (longer if you can) and then come back at it with fresh eyes. Pay particular attention to the flow and narrative – does it fall fit together and flow from one section to another smoothly? Now’s the time to try to improve the linkage from each section to the next, tighten up the writing to be more concise, trim down word count and sand it down into a more digestible read.

Once you’ve done that, give your writing to a friend or colleague who is not a subject matter expert and ask them if they understand the overall discussion. The best way to assess this is to ask them to explain the chapter back to you. This technique will give you a strong indication of which points were clearly communicated and which weren’t. If you’re working with Grad Coach, this is a good time to have your Research Specialist review your chapter.

Finally, tighten it up and send it off to your supervisor for comment. Some might argue that you should be sending your work to your supervisor sooner than this (indeed your university might formally require this), but in my experience, supervisors are extremely short on time (and often patience), so, the more refined your chapter is, the less time they’ll waste on addressing basic issues (which you know about already) and the more time they’ll spend on valuable feedback that will increase your mark-earning potential.

Literature Review Example

In the video below, we unpack an actual literature review so that you can see how all the core components come together in reality.

Let’s Recap

In this post, we’ve covered how to research and write up a high-quality literature review chapter. Let’s do a quick recap of the key takeaways:

• It is essential to understand the WHY of the literature review before you read or write anything. Make sure you understand the 4 core functions of the process.
• The first step is to hunt down the relevant literature . You can do this using Google Scholar, your university database, the snowballing technique and by reviewing other dissertations and theses.
• Next, you need to log all the articles in your reference manager , build your own catalogue of literature and synthesise all the research.
• Following that, you need to develop a detailed outline of your entire chapter – the more detail the better. Don’t start writing without a clear outline (on paper, not in your head!)
• Write up your first draft in rough form – don’t aim for perfection. Remember, done beats perfect.
• Refine your second draft and get a layman’s perspective on it . Then tighten it up and submit it to your supervisor.

Psst… there’s more!

This post is an extract from our bestselling short course, Literature Review Bootcamp . If you want to work smart, you don't want to miss this .

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38 Comments

Thank you very much. This page is an eye opener and easy to comprehend.

This is awesome!

I wish I come across GradCoach earlier enough.

But all the same I’ll make use of this opportunity to the fullest.

Thank you for this good job.

Keep it up!

You’re welcome, Yinka. Thank you for the kind words. All the best writing your literature review.

Thank you for a very useful literature review session. Although I am doing most of the steps…it being my first masters an Mphil is a self study and one not sure you are on the right track. I have an amazing supervisor but one also knows they are super busy. So not wanting to bother on the minutae. Thank you.

You’re most welcome, Renee. Good luck with your literature review 🙂

This has been really helpful. Will make full use of it. 🙂

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Thank you the video was great – from someone that knows nothing thankyou

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It is timely

It is very good video of guidance for writing a research proposal and a dissertation. Since I have been watching and reading instructions, I have started my research proposal to write. I appreciate to Mr Jansen hugely.

I learn a lot from your videos. Very comprehensive and detailed.

Thank you for sharing your knowledge. As a research student, you learn better with your learning tips in research

I was really stuck in reading and gathering information but after watching these things are cleared thanks, it is so helpful.

Really helpful, Thank you for the effort in showing such information

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Thank you for this whole literature writing review.You have simplified the process.

I’m so glad I found GradCoach. Excellent information, Clear explanation, and Easy to follow, Many thanks Derek!

You’re welcome, Maithe. Good luck writing your literature review 🙂

Thank you Coach, you have greatly enriched and improved my knowledge

Great piece, so enriching and it is going to help me a great lot in my project and thesis, thanks so much

This is THE BEST site for ANYONE doing a masters or doctorate! Thank you for the sound advice and templates. You rock!

Thanks, Stephanie 🙂

This is mind blowing, the detailed explanation and simplicity is perfect.

I am doing two papers on my final year thesis, and I must stay I feel very confident to face both headlong after reading this article.

thank you so much.

if anyone is to get a paper done on time and in the best way possible, GRADCOACH is certainly the go to area!

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Good morning scholar. I’m delighted coming to know you even before the commencement of my dissertation which hopefully is expected in not more than six months from now. I would love to engage my study under your guidance from the beginning to the end. I love to know how to do good job

Thank you so much Derek for such useful information on writing up a good literature review. I am at a stage where I need to start writing my one. My proposal was accepted late last year but I honestly did not know where to start

Like the name of your YouTube implies you are GRAD (great,resource person, about dissertation). In short you are smart enough in coaching research work.

This is a very well thought out webpage. Very informative and a great read.

Very timely.

I appreciate.

Very comprehensive and eye opener for me as beginner in postgraduate study. Well explained and easy to understand. Appreciate and good reference in guiding me in my research journey. Thank you

Thank you. I requested to download the free literature review template, however, your website wouldn’t allow me to complete the request or complete a download. May I request that you email me the free template? Thank you.

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How To Conduct A Literature Review Using Google Scholar Step By Step Guide

A free academic search engine known as Google Scholar (GS) is sometimes referred to as the academic counterpart of Google. Instead of searching all of the online content that has been indexed, it searches publisher repositories, academic databases, or scholarly websites.

Typically, a smaller portion of the pool gets searched by Google in this manner. Even though everything is done automatically, the majority of search results come from trustworthy academic sources. In contrast to highly moderated subscription-based academic databases like Scopus and Web of Science, Google is also less selective about what it includes in search results, therefore it is important to determine the authority of the sources linked through Google Scholar on your own.

When conducting thorough searches, such as systematic reviews, Google Scholar (and Web of Science ) shouldn’t be used as a stand-alone resource for locating evidence and finding: Title searches rather than full-text searches in Google Scholar get much more results for ancient literature.

When you are going to complete a literature review , it’s essential to collect research information from many domains and eras, and google scholar is helpful in that regard.

Now, there are a few different reasons why I prefer using Google Scholar while conducting a literature review study.

The first is that Google does a reasonably good job of discovering all of the relevant work that is available online and indexing journals, conference papers, and research databases.

The second is that Google provides us with a few useful tools that we may use to browse the literature and find new information as we search.

• Tools for Automatic Referencing
• Free Online Citation Generator Tools

In order to show you how to use Google Scholar, allow me to give you an example. Consider that our literature review is looking for information on social eye observation in robotics.

Step By Step Guide of using Google Scholar for Literature search

Step 1: Type “ Google Schola r” into the search bar and click and find the google scholar dashboard

Note: The first thing to keep in mind is that you may type “google scholar” in the search field and use the same Google tactics as you would when conducting a regular Google search.

Step 2: Now you can search any topic of your interest on the search bar of google scholar For example, you can Search Fish farming by typing the word in the search bar and clicking the enter button.

Note: Add the word(s) in question to the search tab and press Enter to look for the exact phrase. And it’s clear that Google provides us with a lengthy list of results with the same outcomes. Additionally, it provides us with the paper’s title, the authors who wrote it (although it can be difficult to see on other platforms), where it was published, and the year (see above screenshot) So feel free to click on any of these sites immediately and find the articles details.

Despite these details, Google Scholar Dashboard will also indicate on the right-hand side of this page whether the article is directly available as a PDF (see above screenshot). If so, it will also let you know which website is hosting the PDF. This is due to the fact that PDFs aren’t always hosted by the journal or conference that published the work; instead, writers may upload the PDFs on their own personal pages, for instance.

If you want to find older works that may have been published a little while ago as well as more recent publications that really show the recent R&D in the field of the subject selected.

Step 3: Google scholar allows us to search for articles based on their publication date and years and if you wish to restrict our search, you can search articles starting in the year (as shown below ) 2022, we will only see paper those that have been released in the selected years and this aids in limiting the scope to the most recent work.

As shown above, we are obtaining all 2022 academic research papers (shown in the above screenshot) that have been published in that particular field, complete with source information If you wish to look for research within specific timeframes, you may also build a custom range of your search.

Now, if you read the references in a certain paper, you can locate pertinent articles that were released earlier than that paper. But google scholar offers us a convenient way to locate publications citation and cite scores (see inside the red circle in below screenshot)

Note: If you are enjoying a specific research article and also wanted to see whether there was any additional research that was interested in it and had cited the publication. To view a list of publications that have mentioned the article we are most interested in, click the “cited by” (as shown in the red circle of below screenshot) link and see results and use these papers for your literature review.

Step 4: Google Scholar also offers the ability to automatically generate references, and you can easily obtain several citation types or styles by simply checking the cite button and finding the results as displayed below screenshot.

As mentioned above, you can find references for citations in several citation formats. To use them, just copy and paste the references into your written document’s references area.

• Citation Writing Pattern
• How to Increase Your Citation

You can see that you may acquire the citations in a variety of different standardized formats by clicking the cite link that is located beneath each article as shown in the picture above.

In fact, if you read down to the bottom, you may also find the citation in BibTeX style (see in the red circle below screenshot) a text format that you can copy and paste directly into your bib file, which is particularly useful for students studying computer science field.

You can also use one more useful feature of Google Scholar is the ability to conduct a fresh Google search inside the articles that are quoting the article we’re most interested in by selecting “search within citing articles” from the drop-down menu. And by doing so, you can significantly hone in on your area of interest.

Step 5: Google scholar dashboard also provides us with the beneficial feature of occasionally being able to click on individual author names to access that author’s research profile.

As an illustration, by clicking on my name (Koshal Kumar) here, you can find a Google Scholar profile which I set up with a picture of myself and my affiliation and citation I received till date (see below red circle) and Google automatically indexes all of the articles online that are published by me.

In this way, you can find the literature you want, and google scholar is also automatically ordered by how frequently they have been cited, but you can manually sort by recency by clicking the year or by author name and titles of the paper. Additionally, it might occasionally be helpful to research recent works by a particular author while building your literature review, and finally, Google provides us with a convenient way to cite, allowing us to determine how to cite specific articles.

I do recommend checking the citation over, because oftentimes Google automatically generates it, and there may be some weirdness or errors in the way it has handled the title or the journal-title. So that was a whirlwind tour of how to use Google Scholar to do a literature review.

This is all about this article, and we sincerely hope that these steps and advice of using google scholar in the literature review will be useful to you as you are going to search for literature review online in your journey of research and you are familiar with the online literature review process. KressUp is an online learning platform that occasionally publishes new articles; stay connected to more updates

Please share and subscribe to our website so that it can help as many people as possible. You can also write to us at [email protected] for a free consultation if you’re looking for further E-content or research support.

If you find this article useful, don’t forget to share it!

Related Articles:

• What is A literature Review and Types of Literature Review
• How to write A literature Review paper II Literature Review Paper structure
• 4 Easy Steps To Writing A Literature Review Paper
• Important Purpose of Literature Review in Research

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Literature Review & Research Skills Guide: Use Google Scholar

• Introduction
• What is a Literature Review?
• Your research topic
• Topic Analysis
• Developing a Search Strategy
• Preliminary Reading
• Use Primo Search
• Use Google Scholar
• Use Journal Databases
• Sage Research Methods
• Managing your literature review
• Evaluation & Critical Appraisal
• Referencing

Using Google Scholar

Google Scholar allows you to locate resources such as articles, theses and books.

Unlike Primo Search, which is set to search the Library's holdings only, Google Scholar searches beyond Charles Sturt University Library and will include resources that are not available to you.

Set up Library Links to access the Library's online resources using these instructions .

Google Scholar

Google Scholar is a search engine for scholarly information. It makes available information records that its 'robots' find or that an author, university repository, or journal publisher have chosen to list. It is useful because it searches across many resources and returns many resource types, including journal articles and book chapters, though it is important to note that results are not always from academic-quality sources and it will return both results you do have access to via Charles Sturt Library, and those you do not.

The video to the right provides you with an overview of Google Scholar, including how to change the settings so that it shows you which search results are held in Charles Sturt Library's collection:

Citation Searching

You can see who has cited a resource from the results page in Google Scholar. Once you've located a source you like, you can view who has cited that resource by clicking on the 'Cited by x' link beneath the item record.

You will then see all of the resources that have cited the original item. Keep in mind that this does not include every resource that has ever cited the original item - it only includes those resources that are indexed in Google Scholar.

In the Google Scholar Search box at the top of the page, enter some keywords that you identified in your topic analysis

• Use the left hand menu to limit by date.
• Have you set your library links? Select the Find it at CSU links to access articles in our collection.
• You may notice that there is a mix of topics, including health, education etc. Add more keywords to your search to narrow it down.

Search Google Scholar

Using Google effectively

Citation searching

• << Previous: Use Primo Search
• Next: Use Journal Databases >>
• Last Updated: Apr 8, 2024 11:56 AM
• URL: https://libguides.csu.edu.au/education-research

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• CAREER FEATURE
• 04 December 2020
• Correction 09 December 2020

How to write a superb literature review

Andy Tay is a freelance writer based in Singapore.

You can also search for this author in PubMed   Google Scholar

Literature reviews are important resources for scientists. They provide historical context for a field while offering opinions on its future trajectory. Creating them can provide inspiration for one’s own research, as well as some practice in writing. But few scientists are trained in how to write a review — or in what constitutes an excellent one. Even picking the appropriate software to use can be an involved decision (see ‘Tools and techniques’). So Nature asked editors and working scientists with well-cited reviews for their tips.

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doi: https://doi.org/10.1038/d41586-020-03422-x

Interviews have been edited for length and clarity.

Updates & Corrections

Correction 09 December 2020 : An earlier version of the tables in this article included some incorrect details about the programs Zotero, Endnote and Manubot. These have now been corrected.

Hsing, I.-M., Xu, Y. & Zhao, W. Electroanalysis 19 , 755–768 (2007).

Article   Google Scholar  

Ledesma, H. A. et al. Nature Nanotechnol. 14 , 645–657 (2019).

Article   PubMed   Google Scholar  

Brahlek, M., Koirala, N., Bansal, N. & Oh, S. Solid State Commun. 215–216 , 54–62 (2015).

Choi, Y. & Lee, S. Y. Nature Rev. Chem . https://doi.org/10.1038/s41570-020-00221-w (2020).

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Literature Reviews and Annotated Bibliographies

Initial databases for a literature review.

What is a Literature Review?

• How to Write a Literature Review?
• Graduate Research and the Literature Review
• What is an Annotated Bibliography?
• How to Evaluate Sources?
• Citation & Avoiding Plagiarism

The databases listed here are interdisciplinary and suitable for most disciplines. For databases specific to your discipline see our Research Guides  

Academic Search Ultimate  Includes some full text

A great place to start to search for magazine and journal articles on almost all topics. Tip : Check "peer reviewed" box to limit your search to scholarly journals.

Dissertations and Theses   (1861+) Indexes dissertations accepted for doctoral degrees by accredited North American educational institutions and over 200 other institutions. Also covers masters theses since 1962. Starting in the early to mid-1900's, the full text is included for an increasingly comprehensive number of dissertations and theses. 

Google Scholar   Enables you to search specifically for scholarly literature, including peer-reviewed papers, theses, books, preprints, abstracts and technical reports from all broad areas of research. Use Google Scholar to find articles from a widevariety of academic publishers, professional societies, preprint repositories and universities, as well as scholarly articles available across the web

Humanities and Social Science Retrospective   Bibliographic database that provides citations to articles in a wide range of English language journals in the humanities and social sciences for the period 1907-1984.

  JSTOR Includes full text Includes long runs of backfiles of scholarly journals. Subjects covered include Anthropology, Asian Studies, Ecology, Economics, Education, Finance, History, Mathematics, Philosophy, Political Science, Population Studies, and Sociology.

Periodical Archives Online- (1770-1995) Includes full text; Full text archive of hundreds of periodicals in the humanities and social sciences from their first issues to 1995 Allows date-limited searching. Periodical Index Online, 1665 - 1995

"A literature review is an account of what has been published on a topic by accredited scholars and researchers. Occasionally you will be asked to write one as a separate assignment, ..., but more often it is part of the introduction to an essay, research report, or thesis. In writing the literature review, your purpose is to convey to your reader what knowledge and ideas have been established on a topic, and what their strengths and weaknesses are. As a piece of writing, the literature review must be defined by a guiding concept (e.g., your research objective, the problem or issue you are discussing, or your argumentative thesis). It is not just a descriptive list of the material available, or a set of summaries."

--Written by Dena Taylor, Health Sciences Writing Centre and available at http://www.writing.utoronto.ca/advice/specific-types-of-writing/literature-review (Accessed August 8th, 2011)

Writing the Literature Review sites :

  Literature Reviews: UNC - Chapel Hill

Write a Literature Review: UC-Santa Cruz  

Writing a Literature Review: Perdue OWL

Methods Map: Literature Review

What are the goals of creating a Literature Review?

• To develop a new theory
• To evaluate a theory or theories
• To survey what’s known about a topic
• Identify a problem in a field of research 
• Provide a historical overview of the development of a topic

Type of Literature Reviews:

• Mature and/or established topic: Topic is well-known and the purpose of this type of review is to analyze and synthesize this accumulated body of research.
• Emerging Topic: The purpose of this type of review to identify understudy or new emerging research area.
• << Previous: Home
• Next: How to Write a Literature Review? >>
• Last updated: Jan 8, 2024 2:52 PM
• URL: https://libguides.asu.edu/LiteratureReviews

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Approaching literature review for academic purposes: The Literature Review Checklist

Debora f.b. leite.

I Departamento de Ginecologia e Obstetricia, Faculdade de Ciencias Medicas, Universidade Estadual de Campinas, Campinas, SP, BR

II Universidade Federal de Pernambuco, Pernambuco, PE, BR

III Hospital das Clinicas, Universidade Federal de Pernambuco, Pernambuco, PE, BR

Maria Auxiliadora Soares Padilha

Jose g. cecatti.

A sophisticated literature review (LR) can result in a robust dissertation/thesis by scrutinizing the main problem examined by the academic study; anticipating research hypotheses, methods and results; and maintaining the interest of the audience in how the dissertation/thesis will provide solutions for the current gaps in a particular field. Unfortunately, little guidance is available on elaborating LRs, and writing an LR chapter is not a linear process. An LR translates students’ abilities in information literacy, the language domain, and critical writing. Students in postgraduate programs should be systematically trained in these skills. Therefore, this paper discusses the purposes of LRs in dissertations and theses. Second, the paper considers five steps for developing a review: defining the main topic, searching the literature, analyzing the results, writing the review and reflecting on the writing. Ultimately, this study proposes a twelve-item LR checklist. By clearly stating the desired achievements, this checklist allows Masters and Ph.D. students to continuously assess their own progress in elaborating an LR. Institutions aiming to strengthen students’ necessary skills in critical academic writing should also use this tool.

INTRODUCTION

Writing the literature review (LR) is often viewed as a difficult task that can be a point of writer’s block and procrastination ( 1 ) in postgraduate life. Disagreements on the definitions or classifications of LRs ( 2 ) may confuse students about their purpose and scope, as well as how to perform an LR. Interestingly, at many universities, the LR is still an important element in any academic work, despite the more recent trend of producing scientific articles rather than classical theses.

The LR is not an isolated section of the thesis/dissertation or a copy of the background section of a research proposal. It identifies the state-of-the-art knowledge in a particular field, clarifies information that is already known, elucidates implications of the problem being analyzed, links theory and practice ( 3 - 5 ), highlights gaps in the current literature, and places the dissertation/thesis within the research agenda of that field. Additionally, by writing the LR, postgraduate students will comprehend the structure of the subject and elaborate on their cognitive connections ( 3 ) while analyzing and synthesizing data with increasing maturity.

At the same time, the LR transforms the student and hints at the contents of other chapters for the reader. First, the LR explains the research question; second, it supports the hypothesis, objectives, and methods of the research project; and finally, it facilitates a description of the student’s interpretation of the results and his/her conclusions. For scholars, the LR is an introductory chapter ( 6 ). If it is well written, it demonstrates the student’s understanding of and maturity in a particular topic. A sound and sophisticated LR can indicate a robust dissertation/thesis.

A consensus on the best method to elaborate a dissertation/thesis has not been achieved. The LR can be a distinct chapter or included in different sections; it can be part of the introduction chapter, part of each research topic, or part of each published paper ( 7 ). However, scholars view the LR as an integral part of the main body of an academic work because it is intrinsically connected to other sections ( Figure 1 ) and is frequently present. The structure of the LR depends on the conventions of a particular discipline, the rules of the department, and the student’s and supervisor’s areas of expertise, needs and interests.

Interestingly, many postgraduate students choose to submit their LR to peer-reviewed journals. As LRs are critical evaluations of current knowledge, they are indeed publishable material, even in the form of narrative or systematic reviews. However, systematic reviews have specific patterns 1 ( 8 ) that may not entirely fit with the questions posed in the dissertation/thesis. Additionally, the scope of a systematic review may be too narrow, and the strict criteria for study inclusion may omit important information from the dissertation/thesis. Therefore, this essay discusses the definition of an LR is and methods to develop an LR in the context of an academic dissertation/thesis. Finally, we suggest a checklist to evaluate an LR.

WHAT IS A LITERATURE REVIEW IN A THESIS?

Conducting research and writing a dissertation/thesis translates rational thinking and enthusiasm ( 9 ). While a strong body of literature that instructs students on research methodology, data analysis and writing scientific papers exists, little guidance on performing LRs is available. The LR is a unique opportunity to assess and contrast various arguments and theories, not just summarize them. The research results should not be discussed within the LR, but the postgraduate student tends to write a comprehensive LR while reflecting on his or her own findings ( 10 ).

Many people believe that writing an LR is a lonely and linear process. Supervisors or the institutions assume that the Ph.D. student has mastered the relevant techniques and vocabulary associated with his/her subject and conducts a self-reflection about previously published findings. Indeed, while elaborating the LR, the student should aggregate diverse skills, which mainly rely on his/her own commitment to mastering them. Thus, less supervision should be required ( 11 ). However, the parameters described above might not currently be the case for many students ( 11 , 12 ), and the lack of formal and systematic training on writing LRs is an important concern ( 11 ).

An institutional environment devoted to active learning will provide students the opportunity to continuously reflect on LRs, which will form a dialogue between the postgraduate student and the current literature in a particular field ( 13 ). Postgraduate students will be interpreting studies by other researchers, and, according to Hart (1998) ( 3 ), the outcomes of the LR in a dissertation/thesis include the following:

• To identify what research has been performed and what topics require further investigation in a particular field of knowledge;
• To determine the context of the problem;
• To recognize the main methodologies and techniques that have been used in the past;
• To place the current research project within the historical, methodological and theoretical context of a particular field;
• To identify significant aspects of the topic;
• To elucidate the implications of the topic;
• To offer an alternative perspective;
• To discern how the studied subject is structured;
• To improve the student’s subject vocabulary in a particular field; and
• To characterize the links between theory and practice.

A sound LR translates the postgraduate student’s expertise in academic and scientific writing: it expresses his/her level of comfort with synthesizing ideas ( 11 ). The LR reveals how well the postgraduate student has proceeded in three domains: an effective literature search, the language domain, and critical writing.

Effective literature search

All students should be trained in gathering appropriate data for specific purposes, and information literacy skills are a cornerstone. These skills are defined as “an individual’s ability to know when they need information, to identify information that can help them address the issue or problem at hand, and to locate, evaluate, and use that information effectively” ( 14 ). Librarian support is of vital importance in coaching the appropriate use of Boolean logic (AND, OR, NOT) and other tools for highly efficient literature searches (e.g., quotation marks and truncation), as is the appropriate management of electronic databases.

Language domain

Academic writing must be concise and precise: unnecessary words distract the reader from the essential content ( 15 ). In this context, reading about issues distant from the research topic ( 16 ) may increase students’ general vocabulary and familiarity with grammar. Ultimately, reading diverse materials facilitates and encourages the writing process itself.

Critical writing

Critical judgment includes critical reading, thinking and writing. It supposes a student’s analytical reflection about what he/she has read. The student should delineate the basic elements of the topic, characterize the most relevant claims, identify relationships, and finally contrast those relationships ( 17 ). Each scientific document highlights the perspective of the author, and students will become more confident in judging the supporting evidence and underlying premises of a study and constructing their own counterargument as they read more articles. A paucity of integration or contradictory perspectives indicates lower levels of cognitive complexity ( 12 ).

Thus, while elaborating an LR, the postgraduate student should achieve the highest category of Bloom’s cognitive skills: evaluation ( 12 ). The writer should not only summarize data and understand each topic but also be able to make judgments based on objective criteria, compare resources and findings, identify discrepancies due to methodology, and construct his/her own argument ( 12 ). As a result, the student will be sufficiently confident to show his/her own voice .

Writing a consistent LR is an intense and complex activity that reveals the training and long-lasting academic skills of a writer. It is not a lonely or linear process. However, students are unlikely to be prepared to write an LR if they have not mastered the aforementioned domains ( 10 ). An institutional environment that supports student learning is crucial.

Different institutions employ distinct methods to promote students’ learning processes. First, many universities propose modules to develop behind the scenes activities that enhance self-reflection about general skills (e.g., the skills we have mastered and the skills we need to develop further), behaviors that should be incorporated (e.g., self-criticism about one’s own thoughts), and each student’s role in the advancement of his/her field. Lectures or workshops about LRs themselves are useful because they describe the purposes of the LR and how it fits into the whole picture of a student’s work. These activities may explain what type of discussion an LR must involve, the importance of defining the correct scope, the reasons to include a particular resource, and the main role of critical reading.

Some pedagogic services that promote a continuous improvement in study and academic skills are equally important. Examples include workshops about time management, the accomplishment of personal objectives, active learning, and foreign languages for nonnative speakers. Additionally, opportunities to converse with other students promotes an awareness of others’ experiences and difficulties. Ultimately, the supervisor’s role in providing feedback and setting deadlines is crucial in developing students’ abilities and in strengthening students’ writing quality ( 12 ).

HOW SHOULD A LITERATURE REVIEW BE DEVELOPED?

A consensus on the appropriate method for elaborating an LR is not available, but four main steps are generally accepted: defining the main topic, searching the literature, analyzing the results, and writing ( 6 ). We suggest a fifth step: reflecting on the information that has been written in previous publications ( Figure 2 ).

First step: Defining the main topic

Planning an LR is directly linked to the research main question of the thesis and occurs in parallel to students’ training in the three domains discussed above. The planning stage helps organize ideas, delimit the scope of the LR ( 11 ), and avoid the wasting of time in the process. Planning includes the following steps:

• Reflecting on the scope of the LR: postgraduate students will have assumptions about what material must be addressed and what information is not essential to an LR ( 13 , 18 ). Cooper’s Taxonomy of Literature Reviews 2 systematizes the writing process through six characteristics and nonmutually exclusive categories. The focus refers to the reviewer’s most important points of interest, while the goals concern what students want to achieve with the LR. The perspective assumes answers to the student’s own view of the LR and how he/she presents a particular issue. The coverage defines how comprehensive the student is in presenting the literature, and the organization determines the sequence of arguments. The audience is defined as the group for whom the LR is written.
• Designating sections and subsections: Headings and subheadings should be specific, explanatory and have a coherent sequence throughout the text ( 4 ). They simulate an inverted pyramid, with an increasing level of reflection and depth of argument.
• Identifying keywords: The relevant keywords for each LR section should be listed to guide the literature search. This list should mirror what Hart (1998) ( 3 ) advocates as subject vocabulary . The keywords will also be useful when the student is writing the LR since they guide the reader through the text.
• Delineating the time interval and language of documents to be retrieved in the second step. The most recently published documents should be considered, but relevant texts published before a predefined cutoff year can be included if they are classic documents in that field. Extra care should be employed when translating documents.

Second step: Searching the literature

The ability to gather adequate information from the literature must be addressed in postgraduate programs. Librarian support is important, particularly for accessing difficult texts. This step comprises the following components:

• Searching the literature itself: This process consists of defining which databases (electronic or dissertation/thesis repositories), official documents, and books will be searched and then actively conducting the search. Information literacy skills have a central role in this stage. While searching electronic databases, controlled vocabulary (e.g., Medical Subject Headings, or MeSH, for the PubMed database) or specific standardized syntax rules may need to be applied.

In addition, two other approaches are suggested. First, a review of the reference list of each document might be useful for identifying relevant publications to be included and important opinions to be assessed. This step is also relevant for referencing the original studies and leading authors in that field. Moreover, students can directly contact the experts on a particular topic to consult with them regarding their experience or use them as a source of additional unpublished documents.

Before submitting a dissertation/thesis, the electronic search strategy should be repeated. This process will ensure that the most recently published papers will be considered in the LR.

• Selecting documents for inclusion: Generally, the most recent literature will be included in the form of published peer-reviewed papers. Assess books and unpublished material, such as conference abstracts, academic texts and government reports, are also important to assess since the gray literature also offers valuable information. However, since these materials are not peer-reviewed, we recommend that they are carefully added to the LR.

This task is an important exercise in time management. First, students should read the title and abstract to understand whether that document suits their purposes, addresses the research question, and helps develop the topic of interest. Then, they should scan the full text, determine how it is structured, group it with similar documents, and verify whether other arguments might be considered ( 5 ).

Third step: Analyzing the results

Critical reading and thinking skills are important in this step. This step consists of the following components:

• Reading documents: The student may read various texts in depth according to LR sections and subsections ( defining the main topic ), which is not a passive activity ( 1 ). Some questions should be asked to practice critical analysis skills, as listed below. Is the research question evident and articulated with previous knowledge? What are the authors’ research goals and theoretical orientations, and how do they interact? Are the authors’ claims related to other scholars’ research? Do the authors consider different perspectives? Was the research project designed and conducted properly? Are the results and discussion plausible, and are they consistent with the research objectives and methodology? What are the strengths and limitations of this work? How do the authors support their findings? How does this work contribute to the current research topic? ( 1 , 19 )
• Taking notes: Students who systematically take notes on each document are more readily able to establish similarities or differences with other documents and to highlight personal observations. This approach reinforces the student’s ideas about the next step and helps develop his/her own academic voice ( 1 , 13 ). Voice recognition software ( 16 ), mind maps ( 5 ), flowcharts, tables, spreadsheets, personal comments on the referenced texts, and note-taking apps are all available tools for managing these observations, and the student him/herself should use the tool that best improves his/her learning. Additionally, when a student is considering submitting an LR to a peer-reviewed journal, notes should be taken on the activities performed in all five steps to ensure that they are able to be replicated.

Fourth step: Writing

The recognition of when a student is able and ready to write after a sufficient period of reading and thinking is likely a difficult task. Some students can produce a review in a single long work session. However, as discussed above, writing is not a linear process, and students do not need to write LRs according to a specific sequence of sections. Writing an LR is a time-consuming task, and some scholars believe that a period of at least six months is sufficient ( 6 ). An LR, and academic writing in general, expresses the writer’s proper thoughts, conclusions about others’ work ( 6 , 10 , 13 , 16 ), and decisions about methods to progress in the chosen field of knowledge. Thus, each student is expected to present a different learning and writing trajectory.

In this step, writing methods should be considered; then, editing, citing and correct referencing should complete this stage, at least temporarily. Freewriting techniques may be a good starting point for brainstorming ideas and improving the understanding of the information that has been read ( 1 ). Students should consider the following parameters when creating an agenda for writing the LR: two-hour writing blocks (at minimum), with prespecified tasks that are possible to complete in one section; short (minutes) and long breaks (days or weeks) to allow sufficient time for mental rest and reflection; and short- and long-term goals to motivate the writing itself ( 20 ). With increasing experience, this scheme can vary widely, and it is not a straightforward rule. Importantly, each discipline has a different way of writing ( 1 ), and each department has its own preferred styles for citations and references.

Fifth step: Reflecting on the writing

In this step, the postgraduate student should ask him/herself the same questions as in the analyzing the results step, which can take more time than anticipated. Ambiguities, repeated ideas, and a lack of coherence may not be noted when the student is immersed in the writing task for long periods. The whole effort will likely be a work in progress, and continuous refinements in the written material will occur once the writing process has begun.

LITERATURE REVIEW CHECKLIST

In contrast to review papers, the LR of a dissertation/thesis should not be a standalone piece or work. Instead, it should present the student as a scholar and should maintain the interest of the audience in how that dissertation/thesis will provide solutions for the current gaps in a particular field.

A checklist for evaluating an LR is convenient for students’ continuous academic development and research transparency: it clearly states the desired achievements for the LR of a dissertation/thesis. Here, we present an LR checklist developed from an LR scoring rubric ( 11 ). For a critical analysis of an LR, we maintain the five categories but offer twelve criteria that are not scaled ( Figure 3 ). The criteria all have the same importance and are not mutually exclusive.

First category: Coverage

1. justified criteria exist for the inclusion and exclusion of literature in the review.

This criterion builds on the main topic and areas covered by the LR ( 18 ). While experts may be confident in retrieving and selecting literature, postgraduate students must convince their audience about the adequacy of their search strategy and their reasons for intentionally selecting what material to cover ( 11 ). References from different fields of knowledge provide distinct perspective, but narrowing the scope of coverage may be important in areas with a large body of existing knowledge.

Second category: Synthesis

2. a critical examination of the state of the field exists.

A critical examination is an assessment of distinct aspects in the field ( 1 ) along with a constructive argument. It is not a negative critique but an expression of the student’s understanding of how other scholars have added to the topic ( 1 ), and the student should analyze and contextualize contradictory statements. A writer’s personal bias (beliefs or political involvement) have been shown to influence the structure and writing of a document; therefore, the cultural and paradigmatic background guide how the theories are revised and presented ( 13 ). However, an honest judgment is important when considering different perspectives.

3. The topic or problem is clearly placed in the context of the broader scholarly literature

The broader scholarly literature should be related to the chosen main topic for the LR ( how to develop the literature review section). The LR can cover the literature from one or more disciplines, depending on its scope, but it should always offer a new perspective. In addition, students should be careful in citing and referencing previous publications. As a rule, original studies and primary references should generally be included. Systematic and narrative reviews present summarized data, and it may be important to cite them, particularly for issues that should be understood but do not require a detailed description. Similarly, quotations highlight the exact statement from another publication. However, excessive referencing may disclose lower levels of analysis and synthesis by the student.

4. The LR is critically placed in the historical context of the field

Situating the LR in its historical context shows the level of comfort of the student in addressing a particular topic. Instead of only presenting statements and theories in a temporal approach, which occasionally follows a linear timeline, the LR should authentically characterize the student’s academic work in the state-of-art techniques in their particular field of knowledge. Thus, the LR should reinforce why the dissertation/thesis represents original work in the chosen research field.

5. Ambiguities in definitions are considered and resolved

Distinct theories on the same topic may exist in different disciplines, and one discipline may consider multiple concepts to explain one topic. These misunderstandings should be addressed and contemplated. The LR should not synthesize all theories or concepts at the same time. Although this approach might demonstrate in-depth reading on a particular topic, it can reveal a student’s inability to comprehend and synthesize his/her research problem.

6. Important variables and phenomena relevant to the topic are articulated

The LR is a unique opportunity to articulate ideas and arguments and to purpose new relationships between them ( 10 , 11 ). More importantly, a sound LR will outline to the audience how these important variables and phenomena will be addressed in the current academic work. Indeed, the LR should build a bidirectional link with the remaining sections and ground the connections between all of the sections ( Figure 1 ).

7. A synthesized new perspective on the literature has been established

The LR is a ‘creative inquiry’ ( 13 ) in which the student elaborates his/her own discourse, builds on previous knowledge in the field, and describes his/her own perspective while interpreting others’ work ( 13 , 17 ). Thus, students should articulate the current knowledge, not accept the results at face value ( 11 , 13 , 17 ), and improve their own cognitive abilities ( 12 ).

Third category: Methodology

8. the main methodologies and research techniques that have been used in the field are identified and their advantages and disadvantages are discussed.

The LR is expected to distinguish the research that has been completed from investigations that remain to be performed, address the benefits and limitations of the main methods applied to date, and consider the strategies for addressing the expected limitations described above. While placing his/her research within the methodological context of a particular topic, the LR will justify the methodology of the study and substantiate the student’s interpretations.

9. Ideas and theories in the field are related to research methodologies

The audience expects the writer to analyze and synthesize methodological approaches in the field. The findings should be explained according to the strengths and limitations of previous research methods, and students must avoid interpretations that are not supported by the analyzed literature. This criterion translates to the student’s comprehension of the applicability and types of answers provided by different research methodologies, even those using a quantitative or qualitative research approach.

Fourth category: Significance

10. the scholarly significance of the research problem is rationalized.

The LR is an introductory section of a dissertation/thesis and will present the postgraduate student as a scholar in a particular field ( 11 ). Therefore, the LR should discuss how the research problem is currently addressed in the discipline being investigated or in different disciplines, depending on the scope of the LR. The LR explains the academic paradigms in the topic of interest ( 13 ) and methods to advance the field from these starting points. However, an excess number of personal citations—whether referencing the student’s research or studies by his/her research team—may reflect a narrow literature search and a lack of comprehensive synthesis of ideas and arguments.

11. The practical significance of the research problem is rationalized

The practical significance indicates a student’s comprehensive understanding of research terminology (e.g., risk versus associated factor), methodology (e.g., efficacy versus effectiveness) and plausible interpretations in the context of the field. Notably, the academic argument about a topic may not always reflect the debate in real life terms. For example, using a quantitative approach in epidemiology, statistically significant differences between groups do not explain all of the factors involved in a particular problem ( 21 ). Therefore, excessive faith in p -values may reflect lower levels of critical evaluation of the context and implications of a research problem by the student.

Fifth category: Rhetoric

12. the lr was written with a coherent, clear structure that supported the review.

This category strictly relates to the language domain: the text should be coherent and presented in a logical sequence, regardless of which organizational ( 18 ) approach is chosen. The beginning of each section/subsection should state what themes will be addressed, paragraphs should be carefully linked to each other ( 10 ), and the first sentence of each paragraph should generally summarize the content. Additionally, the student’s statements are clear, sound, and linked to other scholars’ works, and precise and concise language that follows standardized writing conventions (e.g., in terms of active/passive voice and verb tenses) is used. Attention to grammar, such as orthography and punctuation, indicates prudence and supports a robust dissertation/thesis. Ultimately, all of these strategies provide fluency and consistency for the text.

Although the scoring rubric was initially proposed for postgraduate programs in education research, we are convinced that this checklist is a valuable tool for all academic areas. It enables the monitoring of students’ learning curves and a concentrated effort on any criteria that are not yet achieved. For institutions, the checklist is a guide to support supervisors’ feedback, improve students’ writing skills, and highlight the learning goals of each program. These criteria do not form a linear sequence, but ideally, all twelve achievements should be perceived in the LR.

CONCLUSIONS

A single correct method to classify, evaluate and guide the elaboration of an LR has not been established. In this essay, we have suggested directions for planning, structuring and critically evaluating an LR. The planning of the scope of an LR and approaches to complete it is a valuable effort, and the five steps represent a rational starting point. An institutional environment devoted to active learning will support students in continuously reflecting on LRs, which will form a dialogue between the writer and the current literature in a particular field ( 13 ).

The completion of an LR is a challenging and necessary process for understanding one’s own field of expertise. Knowledge is always transitory, but our responsibility as scholars is to provide a critical contribution to our field, allowing others to think through our work. Good researchers are grounded in sophisticated LRs, which reveal a writer’s training and long-lasting academic skills. We recommend using the LR checklist as a tool for strengthening the skills necessary for critical academic writing.

AUTHOR CONTRIBUTIONS

Leite DFB has initially conceived the idea and has written the first draft of this review. Padilha MAS and Cecatti JG have supervised data interpretation and critically reviewed the manuscript. All authors have read the draft and agreed with this submission. Authors are responsible for all aspects of this academic piece.

ACKNOWLEDGMENTS

We are grateful to all of the professors of the ‘Getting Started with Graduate Research and Generic Skills’ module at University College Cork, Cork, Ireland, for suggesting and supporting this article. Funding: DFBL has granted scholarship from Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES) to take part of her Ph.D. studies in Ireland (process number 88881.134512/2016-01). There is no participation from sponsors on authors’ decision to write or to submit this manuscript.

No potential conflict of interest was reported.

1 The questions posed in systematic reviews usually follow the ‘PICOS’ acronym: Population, Intervention, Comparison, Outcomes, Study design.

2 In 1988, Cooper proposed a taxonomy that aims to facilitate students’ and institutions’ understanding of literature reviews. Six characteristics with specific categories are briefly described: Focus: research outcomes, research methodologies, theories, or practices and applications; Goals: integration (generalization, conflict resolution, and linguistic bridge-building), criticism, or identification of central issues; Perspective: neutral representation or espousal of a position; Coverage: exhaustive, exhaustive with selective citations, representative, central or pivotal; Organization: historical, conceptual, or methodological; and Audience: specialized scholars, general scholars, practitioners or policymakers, or the general public.

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Literature reviews as independent studies: guidelines for academic practice

• Original Paper
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• Published: 14 October 2022
• Volume 16 , pages 2577–2595, ( 2022 )

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• Sascha Kraus   ORCID: orcid.org/0000-0003-4886-7482 1 , 2 ,
• Matthias Breier 3 ,
• Weng Marc Lim 4 , 8 , 22 ,
• Marina Dabić 5 , 6 ,
• Satish Kumar 7 , 8 ,
• Dominik Kanbach 9 , 10 ,
• Debmalya Mukherjee 11 ,
• Vincenzo Corvello 12 ,
• Juan Piñeiro-Chousa 13 ,
• Eric Liguori 14 ,
• Daniel Palacios-Marqués 15 ,
• Francesco Schiavone 16 , 17 ,
• Alberto Ferraris 18 , 21 ,
• Cristina Fernandes 19 , 20 &
• João J. Ferreira 19  

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Review articles or literature reviews are a critical part of scientific research. While numerous guides on literature reviews exist, these are often limited to the philosophy of review procedures, protocols, and nomenclatures, triggering non-parsimonious reporting and confusion due to overlapping similarities. To address the aforementioned limitations, we adopt a pragmatic approach to demystify and shape the academic practice of conducting literature reviews. We concentrate on the types, focuses, considerations, methods, and contributions of literature reviews as independent, standalone studies. As such, our article serves as an overview that scholars can rely upon to navigate the fundamental elements of literature reviews as standalone and independent studies, without getting entangled in the complexities of review procedures, protocols, and nomenclatures.

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1 Introduction

A literature review – or a review article – is “a study that analyzes and synthesizes an existing body of literature by identifying, challenging, and advancing the building blocks of a theory through an examination of a body (or several bodies) of prior work (Post et al. 2020 , p. 352). Literature reviews as standalone pieces of work may allow researchers to enhance their understanding of prior work in their field, enabling them to more easily identify gaps in the body of literature and potential avenues for future research. More importantly, review articles may challenge established assumptions and norms of a given field or topic, recognize critical problems and factual errors, and stimulate future scientific conversations around that topic. Literature reviews Footnote 1 come in many different formats and purposes:

Some review articles conduct a critical evaluation of the literature, whereas others elect to adopt a more exploratory and descriptive approach.

Some reviews examine data, methodologies, and findings, whereas others look at constructs, themes, and theories.

Some reviews provide summaries by holistically synthesizing the existing research on a topic, whereas others adopt an integrative approach by assessing related and interdisciplinary work.

The number of review articles published as independent or standalone studies has been increasing over time. According to Scopus (i.e., search database ), reviews (i.e., document type ) were first published in journals (i.e., source type ) as independent studies in 1945, and they subsequently appeared in three digits yearly from the late 1980s to the late 1990s, four digits yearly from the early 2000s to the late 2010s, and five digits in the year 2021 (Fig.  1 ). This increase is indicative that reviewers and editors in business and management research alike see value and purpose in review articles to such a level that they are now commonly accepted as independent, standalone studies. This development is also reflected in the fact that some academic journals exclusively publish review articles (e.g., the Academy of Management Annals , or the  International Journal of Management Reviews ), and journals publishing in various fields often have special issues dedicated to literature reviews on certain topic areas (e.g., the Journal of Management and the Journal of International Business Studies ).

Full-year publication trend of review articles on Scopus (1945–2021)

One of the most important prerequisites of a high-quality review article is that the work follows an established methodology, systematically selects and analyzes articles, and periodically covers the field to identify latest developments (Snyder 2019 ). Additionally, it needs to be reproducible, well-evidenced, and transparent, resulting in a sample inclusive of all relevant and appropriate studies (Gusenbauer and Haddaway 2020; Hansen et al. 2021 ). This observation is in line with Palmatier et al. ( 2018 ), who state that review articles provide an important synthesis of findings and perspectives in a given body of knowledge. Snyder ( 2019 ) also reaffirmed this rationale, pointing out that review articles have the power to answer research questions beyond that which can be achieved in a single study. Ultimately, readers of review articles stand to gain a one-stop, state-of-the-art synthesis (Lim et al. 2022a ; Popli et al. 2022) that encapsulates critical insights through the process of re-interpreting, re-organizing, and re-connecting a body knowledge (Fan et al. 2022 ).

There are many reasons to conduct review articles. Kraus et al. ( 2020 ) explicitly mention the benefits of conducting systematic reviews by declaring that they often represent the first step in the context of larger research projects, such as doctoral dissertations. When carrying out work of this kind, it is important that a holistic overview of the current state of literature is achieved and embedded into a proper synthesis. This allows researchers to pinpoint relevant research gaps and adequately fit future conceptual or empirical studies into the state of the academic discussion (Kraus et al., 2021 ). A review article as an independent or standalone study is a viable option for any academic – especially young scholars, such as doctoral candidates – who wishes to delve into a specific topic for which a (recent) review article is not available.

The process of conducting a review article can be challenging, especially for novice scholars (Boell and Cecez-Kecmanovic 2015 ). Therefore, it is not surprising that numerous guides have been written in an attempt to improve the quality of review studies and support emerging scholars in their endeavors to have their work published. These guides for conducting review articles span a variety of academic fields, such as engineering education (Borrego et al. 2014 ), health sciences (Cajal et al. 2020 ), psychology (Laher and Hassem 2020 ), supply chain management (Durach et al. 2017 ), or business and entrepreneurship (Kraus et al. 2020 ; Tranfield et al. 2003 ) – the latter were among the first scholars to recognize the need to educate business/management scholars on the roles of review studies in assembling, ascertaining, and assessing the intellectual territory of a specific knowledge domain. Furthermore, they shed light on the stages (i.e., planning the review, conducting the review, reporting, and dissemination) and phases (i.e., identifying the need for a review, preparation of a proposal for a review, development of a review protocol, identification of research, selection of studies, study quality assessment, data extraction and monitoring progress, data synthesis, the report and recommendations, and getting evidence into practice) of conducting a systematic review. Other scholars have either adapted and/or developed new procedures (Kraus et al. 2020 ; Snyder 2019 ) or established review protocols such as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram (Moher et al. 2015 ). The latter provides a checklist that improves transparency and reproducibility, thus reducing questionable research practices. The declarative and procedural knowledge of a checklist allows users to derive value from (and, in some cases, produce) methodological literature reviews.

Two distinct and critical gaps or issues provide impetus for our article. First, while the endeavors of the named scholars are undoubtedly valuable contributions, they often encourage other scholars to explain the methodology of their review studies in a non-parsimonious way ( 1st issue ). This can become problematic if this information distracts and deprives scholars from providing richer review findings, particularly in instances in which publication outlets impose a strict page and/or word limit. More often than not, the early parts (i.e., stages/phases, such as needs, aims, and scope) of these procedures or protocols are explained in the introduction, but they tend to be reiterated in the methodology section due to the prescription of these procedures or protocols. Other parts of these procedures or protocols could also be reported more parsimoniously, for example, by filtering out documents, given that scientific databases (such as Scopus or Web of Science ) have since been upgraded to allow scholars to select and implement filtering criteria when conducting a search (i.e., criterion-by-criterion filtering may no longer be necessary). More often than not, the procedures or protocols of review studies can be signposted (e.g., bracket labeling) and disclosed in a sharp and succinct manner while maintaining transparency and replicability.

Other guides have been written to introduce review nomenclatures (i.e., names/naming) and their equivalent philosophical underpinnings. Palmatier et al. ( 2018 ) introduced three clearly but broadly defined nomenclatures of literature reviews as independent studies: domain-based reviews, theory-based reviews, and method-based reviews. However, such review nomenclatures can be confusing due to their overlapping similarities ( 2nd issue ). For example, Lim et al. ( 2022a ) highlighted their observation that the review nomenclatures associated with domain-based reviews could also be used for theory-based and method-based reviews.

The two aforementioned issues – i.e., the lack of a parsimonious understanding and the reporting of the review methodology , and the confusion emerging from review nomenclatures – are inarguably the unintended outcomes of diving into an advanced (i.e., higher level) understanding of literature review procedures, protocols, and nomenclatures from a philosophical perspective (i.e., underpinnings) without a foundational (i.e., basic level) understanding of the fundamental (i.e., core) elements of literature reviews from a pragmatic perspective. Our article aims to shed light on these issues and hopes to provide clarity for future scholarly endeavors.

Having a foundational understanding of literature reviews as independent studies is (i) necessary when addressing the aforementioned issues; (ii) important in reconciling and scaffolding our understanding, and (iii) relevant and timely due to the proliferation of literature reviews as independent studies. To contribute a solution toward addressing this gap , we aim to demystify review articles as independent studies from a pragmatic standpoint (i.e., practicality). To do so, we deliberately (i) move away from review procedures, protocols, and nomenclatures, and (ii) invest our attention in developing a parsimonious, scaffolded understanding of the fundamental elements (i.e., types, focuses, considerations, methods, and contributions) of review articles as independent studies.

Three contributions distinguish our article. It is worth noting that pragmatic guides (i.e., foundational knowledge), such as the present one, are not at odds with extant philosophical guides (i.e., advanced knowledge), but rather they complement them. Having a foundational knowledge of the fundamental elements of literature reviews as independent studies is valuable , as it can help scholars to (i) gain a good grasp of the fundamental elements of literature reviews as independent studies ( 1st contribution ), and (ii) mindfully adopt or adapt existing review procedures, protocols, and nomenclatures to better suit the circumstances of their reviews (e.g., choosing and developing a well-defined review nomenclature, and choosing and reporting on review considerations and steps more parsimoniously) ( 2nd contribution ). Therefore, this pragmatic guide serves as (iii) a foundational article (i.e., preparatory understanding) for literature reviews as independent studies ( 3rd contribution ). Following this, extant guides using a philosophical approach (i.e., advanced understanding) could be relied upon to make informed review decisions (e.g., adoption, adaptation) in response to the conventions of extant review procedures, protocols, and nomenclatures (Fig.  2 ).

Foundational and advanced understanding of literature reviews as independent studies

2 Fundamental elements of literature reviews as independent studies

A foundational understanding of literature reviews as independent studies can be acquired through the appreciation of five fundamental elements – i.e., types, focuses, considerations, methods, and contributions – which are illustrated in Fig.  3 and summarized in the following sections.

Fundamental elements of literature reviews as independent studies

There are two types of literature reviews as independent studies: systematic literature reviews ( SLRs ) and non-systematic literature reviews ( non-SLRs ). It is important to recognize that SLRs and non-SLRs are not review nomenclatures (i.e., names/naming) but rather review types (i.e., classifications).

In particular, SLRs are reviews carried out in a systematic way using an adopted or adapted procedure or protocol to guide data curation and analysis, thus enabling transparent disclosure and replicability (Lim et al. 2022a ; Kraus et al. 2020 ). Therefore, any review nomenclature guided by a systematic methodology is essentially an SLR. The origin of this type of literature review can be traced back to the evidence-based medicine movement in the early 1990s, with the objective being to overcome the issue of inconclusive findings in studies for medical treatments (Boell and Cecez-Kecmanovic 2015 ).

In contrast, non-SLRs are reviews conducted without any systematic procedure or protocol; instead, they weave together relevant literature based on the critical evaluations and (subjective) choices of the author(s) through a process of discovery and critique (e.g., pointing out contradictions and questioning assertions or beliefs); they are shaped by the exposure, expertise, and experience (i.e., the “3Es” in judgement calls) of the author(s). Therefore, non-SLRs are essentially critical reviews of the literature (Lim and Weissmann 2021 ).

2.2 Focuses

Unlike Palmatier et al. ( 2018 ) who considered domain-based reviews, theory-based reviews, and method-based reviews as review nomenclatures, we consider domain , theory , and method as three substantive focuses that can take center stage in literature reviews as independent studies. This is in line with our attempt to move away from review nomenclatures when providing a foundational understanding of literature reviews as independent studies.

A review that is domain-focused can examine: (i) a  concept (e.g., customer engagement; Lim et al. 2022b ; digital transformation; Kraus et al. 2021 ; home sharing; Lim et al. 2021 ; sharing economy; Lim 2020 ), (ii) a context (e.g., India; Mukherjee et al. 2022a ), (iii) a discipline (e.g., entrepreneurship; Ferreira et al. 2015 ; international business; Ghauri et al. 2021 ), (iv) a field (e.g., family business; Lahiri et al. 2020 ; Rovelli et al. 2021 ; female entrepreneurship; Ojong et al. 2021 ), or (v) an outlet (e.g., Journal of Business Research ; Donthu et al. 2020 ; Management International Review ; Mukherjee et al. 2021 ; Review of Managerial Science ; Mas-Tur et al. 2020 ), which typically offer broad, overarching insights.

Domain-focused hybrids , such as the between-domain hybrid (e.g., concept-discipline hybrid, such as digital transformation in business and management; Kraus et al. 2022 ; religion in business and entrepreneurship; Kumar et al. 2022a ; personality traits in entrepreneurship; Salmony and Kanbach 2022 ; and policy implications in HR and OB research; Aguinis et al., 2022 ) and the within-domain hybrid (e.g., the concept-concept hybrid, such as customer engagement and social media; Lim and Rasul 2022 ; and global business and organizational excellence; Lim 2022 ; and the discipline-discipline hybrid, such as neuromarketing; Lim 2018 ) are also common as they can provide finer-grained insights.

A review that is theory-focused can explore a standalone theory (e.g., theory of planned behavior; Duan and Jiang 2008 ), as well as a theory in conjunction with a domain , such as the concept-theory hybrid (e.g., behavioral control and theory of planned behavior; Lim and Weissmann 2021 ) and the theory-discipline hybrid (e.g., theory of planned behavior in hospitality, leisure, and tourism; Ulker-Demirel and Ciftci 2020 ), or a theory in conjunction with a method (e.g., theory of planned behavior and structural equation modeling).

A review that is method-focused can investigate a standalone method (e.g., structural equation modeling; Deng et al. 2018 ) or a method in conjunction with a domain , such as the method-discipline hybrid (e.g., fsQCA in business and management; Kumar et al. 2022b ).

2.3 Planning the review, critical considerations, and data collection

The considerations required for literature reviews as independent studies depend on their type: SLRs or non-SLRs.

For non-SLRs, scholars often rely on the 3Es (i.e., exposure, expertise, and experience) to provide a critical review of the literature. Scholars who embark on non-SLRs should be well versed with the literature they are dealing with. They should know the state of the literature (e.g., debatable, underexplored, and well-established knowledge areas) and how it needs to be deciphered (e.g., tenets and issues) and approached (e.g., reconciliation proposals and new pathways) to advance theory and practice. In this regard, non-SLRs follow a deductive reasoning approach, whereby scholars initially develop a set of coverage areas for reviewing a domain, theory, or method and subsequently draw on relevant literature to shed light and support scholarly contentions in each area.

For SLRs, scholars often rely on a set of criteria to provide a well-scoped (i.e., breadth and depth), structured (i.e., organized aspects), integrated (i.e., synthesized evidence) and interpreted/narrated (i.e., describing what has happened, how and why) systematic review of the literature. Footnote 2 In this regard, SLRs follow an inductive reasoning approach, whereby a set of criteria is established and implemented to develop a corpus of scholarly documents that scholars can review. They can then deliver a state-of-the-art overview, as well as a future agenda for a domain, theory, or method. Such criteria are often listed in philosophical guides on SLR procedures (e.g., Kraus et al. 2020 ; Snyder 2019 ) and protocols (e.g., PRISMA), and they may be adopted/adapted with justifications Footnote 3 . Based on their commonalities they can be summarized as follows:

Search database (e.g., “Scopus” and/or “Web of Science”) can be defined based on justified evidence (e.g., by the two being the largest scientific databases of scholarly articles that can provide on-demand bibliographic data or records; Pranckutė 2021 ). To avoid biased outcomes due to the scope covered by the selected database, researchers could utilize two or more different databases (Dabić et al. 2021 ).

Search keywords may be developed by reading scholarly documents and subsequently brainstorming with experts. The expanding number of databases, journals, periodicals, automated approaches, and semi-automated procedures that use text mining and machine learning can offer researchers the ability to source new, relevant research and forecast the citations of influential studies. This enables them to determine further relevant articles.

Boolean operators (e.g., AND, OR) should be strategically used in developing the  string   of search keywords (e.g., “engagement” AND “customer” OR “consumer” OR “business”). Furthermore, the correct and precise application of quotation marks is important but is very frequently sidestepped, resulting in incorrect selection processes and differentiated results.

Search period (e.g., between a specified period [e.g., 2000 to 2020] or up to the latest full year at the time or writing [e.g., up to 2021]) can be defined based on the justified scope of study (e.g., contemporary evolution versus historical trajectory).

Search field (e.g., “article title, abstract, keywords”) can be defined based on justified assumptions (e.g., it is assumed that the focus of relevant documents will be mentioned in the article title, abstract, and/or keywords).

Subject area (e.g., “business, management, and accounting”) can be defined based on justified principles (e.g., the focus of the review is on the marketing discipline, which is located under the “business, management, and accounting” subject area in Scopus).

Publication stage (e.g., “final”) can be defined based on justified grounds (e.g., enabling greater accuracy in replication).

Document type (e.g., “article” and/or “review”), which reflects the type of scientific/practical contributions (e.g., empirical, synthesis, thought), can be defined based on justified rationales (e.g., articles selected because they are peer-reviewed; editorials not selected because they are not peer-reviewed).

Source type (e.g., “journal”) can be defined based on justified reasons (e.g., journals selected because they publish finalized work; conference proceedings not selected because they are work in progress, and in business/management, they are usually not being considered as full-fledged “publications”).

Language (e.g., “English”) can be determined based on justified limitations (e.g., nowadays, there are not many reasons to use another language besides the academic lingua franca English). Different spellings should also be considered, as the literature may contain both American and British spelling variants (e.g., organization and organisation). Truncation and wildcards in searches are recommended to capture both sets of spellings. It is important to note that each database varies in its symbology.

Quality filtering (e.g., “A*” and “A” or “4*”, “4”, and “3”) can be defined based on justified motivations (e.g., the goal is to unpack the most originally and rigorously produced knowledge, which is the hallmark of premier journals, such as those ranked “A*” and “A” by the Australian Business Deans Council [ABDC] Journal Quality List [JQL] and rated “4*”, “4”, and “3” by the Chartered Association of Business Schools [CABS] Academic Journal Guide [AJG]).

Document relevance (i.e., within the focus of the review) can be defined based on justified judgement (e.g., for a review focusing on customer engagement, articles that mention customer engagement as a passing remark without actually investigating it would be excluded).

Others: Screening process should be accomplished by beginning with the deduction of duplicate results from other databases, tracked using abstract screening to exclude unfitting studies, and ending with the full-text screening of the remaining documents.

Others: Exclusion-inclusion criteria interpretation of the abstracts/articles is obligatory when deciding whether or not the articles dealt with the matter. This step could involve removing a huge percentage of initially recognized articles.

Others: Codebook building pertains to the development of a codebook of the main descriptors within a specific field. An inductive approach can be followed and, in this case, descriptors are not established beforehand. Instead, they are established through the analysis of the articles’ content. This procedure is made up of several stages: (i) the extraction of important content from titles, abstracts, and keywords; (ii) the classification of this content to form a reduced list of the core descriptors; and (iii) revising the codebook in iterations and combining similar categories, thus developing a short list of descriptors (López-Duarte et al. 2016 , p. 512; Dabić et al. 2015 ; Vlacic et al. 2021 ).

2.4 Methods

Various methods are used to analyze the pertinent literature. Often, scholars choose a method for corpus analysis before corpus curation. Knowing the analytical technique beforehand is useful, as it allows researchers to acquire and prepare the right data in the right format. This typically occurs when scholars have decided upon and justified pursuing a specific review nomenclature upfront (e.g., bibliometric reviews) based on the problem at hand (e.g., broad domain [outlet] with a large corpus [thousands of articles], such as a premier journal that has been publishing for decades) (Donthu et al. 2021 ). However, this may not be applicable in instances where (i) scholars do not curate a corpus of articles (non-SLRs), and (ii) scholars only know the size of the corpus of articles once that corpus is curated (SLRs). Therefore, scholars may wish to decide on a method of analyzing the literature depending on (i) whether they rely on a corpus of articles (i.e., yes or no), and (ii) the size of the corpus of articles that they rely on to review the literature (i.e., n  = 0 to ∞).

When analytical techniques (e.g., bibliometric analysis, critical analysis, meta-analysis) are decoupled from review nomenclatures (e.g., bibliometric reviews, critical reviews, meta-analytical reviews), we uncover a toolbox of the following methods for use when analyzing the literature:

Bibliometric analysis measures the literature and processes data by using algorithm, arithmetic, and statistics to analyze, explore, organize, and investigate large amounts of data. This enables scholars to identify and recognize potential “hidden patterns” that could help them during the literature review process. Bibliometrics allows scholars to objectively analyze a large corpus of articles (e.g., high hundreds or more) using quantitative techniques (Donthu et al. 2021 ). There are two overarching categories for bibliometric analysis: performance analysis and science mapping. Performance analysis enables scholars to assess the productivity (publication) and impact (citation) of the literature relating to a domain, method, or theory using various quantitative metrics (e.g., average citations per publication or year, h -index, g -index, i -index). Science mapping grants scholars the ability to map the literature in that domain, method, or theory based on bibliographic data (e.g., bibliographic coupling generates thematic clusters based on similarities in shared bibliographic data [e.g., references] among citing articles; co-citation analysis generates thematic clusters based on commonly cited articles; co-occurrence analysis generates thematic clusters based on bibliographic data [e.g., keywords] that commonly appear together; PageRank analysis generates thematic clusters based on articles that are commonly cited in highly cited articles; and topic modeling generates thematic clusters based on the natural language processing of bibliographic data [e.g., article title, abstract, and keywords]). Footnote 4 Given the advancement in algorithms and technology, reviews using bibliometric analysis are considered to be smart (Kraus et al. 2021 ) and technologically-empowered (Kumar et al. 2022b ) SLRs, in which a review has harnessed the benefits of (i) the machine learning of the bibliographic data of scholarly research from technologically-empowered scientific databases, and (ii) big data analytics involving various science mapping techniques (Kumar et al. 2022c ).

Content analysis allows scholars to analyze a small to medium corpus of articles (i.e., tens to low hundreds) using quantitative and qualitative techniques. From a quantitative perspective , scholars can objectively carry out a content analysis by quantifying a specific unit of analysis . A useful method of doing so involves adopting, adapting, or developing an organizing framework . For example, Lim et al. ( 2021 ) employed an organizing (ADO-TCM) framework to quantify content in academic literature based on: (i) the categories of knowledge; (ii) the relationships between antecedents, decisions, and outcomes; and (iii) the theories, contexts, and methods used to develop the understanding for (i) and (ii). The rapid evolution of software for content analysis allows scholars to carry out complex elaborations on the corpus of analyzed articles, so much so that the most recent software enables the semi-automatic development of an organizing framework (Ammirato et al. 2022 ). From a qualitative perspective , scholars can conduct a content analysis or, more specifically, a thematic analysis , by subjectively organizing the content into themes. For example, Creevey et al. ( 2022 ) reviewed the literature on social media and luxury, providing insights on five core themes (i.e., luxury brand strategy, luxury brand social media communications, luxury consumer attitudes and perceptions, engagement, and the influence of social media on brand performance-related outcomes) generated through a content (thematic) analysis. Systematic approaches for inductive concept development through qualitative research are similarly applied in literature reviews in an attempt to reduce the subjectivity of derived themes. Following the principles of the approach by Gioia et al. ( 2012 ), Korherr and Kanbach ( 2021 ) develop a taxonomy of human-related capabilities in big data analytics. Building on a sample of 75 studies for the literature review, 33 first-order concepts are identified. These are categorized into 15 second-order themes and are finally merged into five aggregate dimensions. Using the same procedure, Leemann and Kanbach ( 2022 ) identify 240 idiosyncratic dynamic capabilities in a sample of 34 studies for their literature review. They then categorize these into 19 dynamic sub-capabilities. The advancement of technology also makes it possible to conduct content analysis using computer assisted qualitative data analysis (CAQDA) software (e.g., ATLAS.ti, Nvivo, Quirkos) (Lim et al. 2022a ).

Critical analysis allows scholars to subjectively use their 3Es (i.e., exposure, expertise, and experience) to provide a critical evaluation of academic literature. This analysis is typically used in non-SLRs, and can be deployed in tandem with other analyses, such as bibliometric analysis and content analysis in SLRs, which are used to discuss consensual, contradictory, and underexplored areas of the literature. For SLRs, scholars are encouraged to engage in critical evaluations of the literature so that they can truly contribute to advancing theory and practice (Baker et al. 2022 ; Lim et al. 2022a ; Mukherjee et al. 2022b ).

Meta-analysis allows scholars to objectively establish a quantitative estimate of commonly studied relationships in the literature (Grewal et al. 2018 ). This analysis is typically employed in SLRs intending to reconcile a myriad of relationships (Lim et al. 2022a ). The relationships established are often made up of conflicting evidence (e.g., a positive or significant effect in one study, but a negative or non-significant effect in another study). However, through meta-analysis, scholars are able to identify potential factors (e.g., contexts or sociodemographic information) that may have led to the conflict.

Others: Multiple correspondence analysis helps to map the field, assessing the associations between qualitative content within a matrix of variables and cases. Homogeneity Analysis by Means of Alternating Least Squares ( HOMALS ) is also considered useful in allowing researchers to map out the intellectual structure of a variety of research fields (Gonzalez-Loureiro et al. 2015 ; Gonzalez-Louriero 2021; Obradović et al. 2021 ). HOMALS can be performed in R or used along with a matrix through SPSS software. In summary, the overall objective of this analysis is to discover a low dimensional representation of the original high dimensional space (i.e., the matrix of descriptors and articles). To measure the goodness of fit, a loss function is used. This function is used minimally, and the HOMALS algorithm is applied to the least squares loss functions in SPSS. This analysis provides a proximity map, in which articles and descriptors are shown in low-dimensional spaces (typically on two axes). Keywords are paired and each couple that appears together in a large number of articles is shown to be closer on the map and vice-versa.

When conducting a literature review, software solutions allow researchers to cover a broad range of variables, from built-in functions of statistical software packages to software orientated towards meta-analyses, and from commercial to open-source solutions. Personal preference plays a huge role, but the decision as to which software will be the most useful is entirely dependent on how complex the methods and the dataset are. Of all the commercial software providers, we have found the built-in functions of (i) R and VOSviewer most useful in performing bibliometric analysis (Aria and Cuccurullo 2017 ; R Core Team 2021 ; Van Eck and Waltman 2014 ) and (ii) Stata most useful in performing meta-analytical tasks.

Many different analytical tools have been used. These include simple document counting, citation analysis, word frequency analysis, cluster analysis, co-word analysis, and cooperation analysis (Daim et al. 2006 ). Software has also been produced for bibliometric analysis, such as the Thomson Data Analyzer (TDA), which Thomson Reuters created, and CiteSpace developed by Chen ( 2013 ). VOSviewer helps us to construct and visualize bibliometric networks, which can include articles, journals, authors, countries, and institutions, among others (Van Eck and Waltman 2014 ). These can be organized based on citations, co-citations, bibliographic coupling, or co-authorship relations. In addition, VOSviewer provides text mining functions, which can be used to facilitate a better understanding of co-occurrence networks with regards to the key terms taken from a body of scientific literature (Donthu et al. 2021 ; Wong 2018 ). Other frequently used tools include for bibliometric analysis include Bibliometrix/Biblioshiny in R, CitNetExplorer, and Gephi, among others.

2.5 Contributions

Well-conducted literature reviews may make multiple contributions to the literature as standalone, independent studies.

Generally, there are three primary contributions of literature reviews as independent studies: (i) to provide an overview of current knowledge in the domain, method, or theory, (ii) to provide an evaluation of knowledge progression in the domain, method, or theory, including the establishment of key knowledge, conflicting or inconclusive findings, and emerging and underexplored areas, and (iii) to provide a proposal for potential pathways for advancing knowledge in the domain, method, or theory (Lim et al. 2022a , p. 487). Developing theory through literature reviews can take many forms, including organizing and categorizing the literature, problematizing the literature, identifying and exposing contradictions, developing analogies and metaphors, and setting out new narratives and conceptualizations (Breslin and Gatrell 2020 ). Taken collectively, these contributions offer crystalized, evidence-based insights that both ‘mine’ and ‘prospect’ the literature, highlighting extant gaps and how they can be resolved (e.g., flags paradoxes or theoretical tensions, explaining why something has not been done, what the challenges are, and how these challenges can be overcome). These contributions can be derived through successful bibliometric analysis, content analysis, critical analysis, and meta-analysis.

Additionally, the deployment of specific methods can bring in further added value. For example, a performance analysis in a bibliometric analysis can contribute to: (i) objectively assessing and reporting research productivity and impact ; (ii) ascertaining reach for coverage claims ; (iii) identifying social dominance and hidden biases ; (iv) detecting anomalies ; and (v) evaluating ( equitable ) relative performance ; whereas science mapping in bibliometric analysis can contribute to: (i) objectively discovering thematic clusters of knowledge ; (ii) clarifying nomological networks ; (iii) mapping social patterns ; (iv) tracking evolutionary nuances ; and (v) recognizing knowledge gaps (Mukherjee et al. 2022b , p. 105).

3 Conclusion

Independent literature reviews will continue to be written as a result of their necessity, importance, relevance, and urgency when it comes to advancing knowledge (Lim et al. 2022a ; Mukherjee et al. 2022b ), and this can be seen in the increasing number of reviews being published over the last several years. Literature reviews advance academic discussion. Journal publications on various topics and subject areas are becoming more frequent sites for publication. This trend will only heighten the need for literature reviews. This article offers directions and control points that address the needs of three different stakeholder groups: producers (i.e., potential authors), evaluators (i.e., journal editors and reviewers), and users (i.e., new researchers looking to learn more about a particular methodological issue, and those teaching the next generation of scholars). Future producers will derive value from this article’s teachings on the different fundamental elements and methodological nuances of literature reviews. Procedural knowledge (i.e., using control points to assist in decision-making during the manuscript preparation phase) will also be of use. Evaluators will be able to make use of the procedural and declarative knowledge evident in control points as well. As previously outlined, the need to cultivate novelty within research on business and management practices is vital. Scholars must also be supported to choose not only safe mining approaches; they should also be encouraged to attempt more challenging and risky ventures. It is important to note that abstracts often seem to offer a lot of potential, stating that authors intend to make large conceptual contributions, broadening the horizons of the field.

Our article offers important insights also for practitioners. Noteworthily, our framework can support corporate managers in decomposing and better understanding literature reviews as ad-hoc and independent studies about specific topics that matter for their organization. For instance, practitioners can understand more easily what are the emerging trends within their domain of interest and make corporate decisions in line with such trends.

This article arises from an intentional decoupling from philosophy, in favor of adopting a more pragmatic approach. This approach can assist us in clarifying the fundamental elements of literature reviews as independent studies. Five fundamental elements must be considered: types, focuses, considerations, methods, and contributions. These elements offer a useful frame for scholars starting to work on a literature review. Overview articles (guides) such as ours are thus invaluable, as they equip scholars with a solid foundational understanding of the integral elements of a literature review. Scholars can then put these teachings into practice, armed with a better understanding of the philosophy that underpins the procedures, protocols, and nomenclatures of literature reviews as independent studies.

Data availability

Our manuscript has no associate data.

Our focus here is on standalone literature reviews in contrast with literature reviews that form the theoretical foundation for a research article.

Scoping reviews, structured reviews, integrative reviews, and interpretive/narrative reviews are commonly found in review nomenclature. However, the philosophy of these review nomenclatures essentially reflects what constitutes a good SLR. That is to say, a good SLR should be well scoped, structured, integrated, and interpreted/narrated. This observation reaffirms our position and the value of moving away from review nomenclatures to gain a foundational understanding of literature reviews as independent studies.

Given that many of these considerations can be implemented simultaneously in contemporary versions of scientific databases, scholars may choose to consolidate them into a single (or a few) step(s), where appropriate, so that they can be reported more parsimoniously. For a parsimonious but transparent and replicable exemplar, see Lim ( 2022 ).

Where keywords are present (e.g., author keywords or keywords derived from machine learning [e.g., natural language processing]), it is assumed that each keyword represents a specific meaning (e.g., topic [concept, context], method), and that a collection of keywords grouped under the same cluster represents a specific theme.

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Kraus, S., Breier, M., Lim, W.M. et al. Literature reviews as independent studies: guidelines for academic practice. Rev Manag Sci 16 , 2577–2595 (2022). https://doi.org/10.1007/s11846-022-00588-8

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The Role of Google Scholar in Evidence Reviews and Its Applicability to Grey Literature Searching

Affiliations.

• 1 MISTRA EviEM, Royal Swedish Academy of Sciences, Stockholm, Sweden.
• 2 Centre for Environmental Policy, Imperial College, London, United Kingdom; Department for Environmental, Food and Rural Affairs, London, United Kingdom.
• 3 Department for Environmental, Food and Rural Affairs, London, United Kingdom; Department for Civil and Environmental Engineering, Imperial College, London, United Kingdom.
• 4 Department for Environmental, Food and Rural Affairs, London, United Kingdom; Environment Agency, London, United Kingdom.
• PMID: 26379270
• PMCID: PMC4574933
• DOI: 10.1371/journal.pone.0138237

Google Scholar (GS), a commonly used web-based academic search engine, catalogues between 2 and 100 million records of both academic and grey literature (articles not formally published by commercial academic publishers). Google Scholar collates results from across the internet and is free to use. As a result it has received considerable attention as a method for searching for literature, particularly in searches for grey literature, as required by systematic reviews. The reliance on GS as a standalone resource has been greatly debated, however, and its efficacy in grey literature searching has not yet been investigated. Using systematic review case studies from environmental science, we investigated the utility of GS in systematic reviews and in searches for grey literature. Our findings show that GS results contain moderate amounts of grey literature, with the majority found on average at page 80. We also found that, when searched for specifically, the majority of literature identified using Web of Science was also found using GS. However, our findings showed moderate/poor overlap in results when similar search strings were used in Web of Science and GS (10-67%), and that GS missed some important literature in five of six case studies. Furthermore, a general GS search failed to find any grey literature from a case study that involved manual searching of organisations' websites. If used in systematic reviews for grey literature, we recommend that searches of article titles focus on the first 200 to 300 results. We conclude that whilst Google Scholar can find much grey literature and specific, known studies, it should not be used alone for systematic review searches. Rather, it forms a powerful addition to other traditional search methods. In addition, we advocate the use of tools to transparently document and catalogue GS search results to maintain high levels of transparency and the ability to be updated, critical to systematic reviews.

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• Research Support, Non-U.S. Gov't
• Databases, Bibliographic*
• Databases, Factual
• Peer Review, Research
• Publications*
• Search Engine*

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• Open access
• Published: 16 April 2024

Review on epidemiology, disease burden, and treatment patterns of IgA nephropathy in select APAC countries

• Omer Zaidi 1 ,
• Zhaoli Tang 2 ,
• Sandipan Bhattacharjee 3 &
• Kristin Pareja 3  

BMC Nephrology volume  25 , Article number:  136 ( 2024 ) Cite this article

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Metrics details

Immunoglobulin type A (IgA) nephropathy is the most common primary glomerulonephritis (GN) worldwide with higher rates in East and Pacific Asia compared to North America and Europe. Despite high reported prevalence of IgAN in these countries, the overall disease prevalence across Asia is not available. Treatment patterns of IgAN patients across Asian countries have also not been summarized. The aim of this study was to review and summarize evidence on IgA nephropathy prevalence, treatment patterns, and humanistic and economic burden in mainland China, Taiwan, South Korea, Japan, and Australia.

A targeted literature review was conducted in PubMed and local databases in China (including Taiwan), South Korea, Japan, and Australia between January 2010-December 2021. Website literature searches were conducted using Google Scholar and Baidu.

Sixty-nine publications and 3 clinical guidelines were included. Incidence ranged from 0 to 10.7 per 100 000 people per year in Australia, Japan, and Taiwan, and ranged from 6.3 to 24.70% among patients who underwent renal biopsy in mainland China. Prevalence and diagnosis rates ranged from 0 to 72.1% in mainland China, South Korea, Taiwan, Japan, and Australia. Mortality rates in mainland China, South Korea, and Japan varied widely. The top 3 commonly used therapies were angiotensin-converting enzyme inhibitor/angiotensin receptor blockers (0.9-99.6%), corticosteroids (3.5-100%), and immunosuppressants (1.6-85.5%) in Japan, mainland China, and South Korea. Patient quality of life was measured by different tools, and annual hospitalization costs ranged from $1 284.73 to $2 252.12 (2015–2018) in China.

Conclusions

The prevalence of IgA nephropathy among the general population in select countries/regions is not commonly available, despite evidence from studies and clinical guidelines. In addition, it is observed across geographic regions that heterogeneity exists in prevalence rates, and large variations exist in treatment patterns. There is need to fill in these gaps to understand the contributing factors behind the differences through population-based, multi-center, and real-world studies.

Peer Review reports

Immunoglobulin type A nephropathy (IgAN), also known as Berger’s disease, is a kidney disease caused by kidney deposition of immunoglobulin type A (IgA) complexes involving galactose-deficient IgA [ 1 ] and resulting in inflammatory tissue damage [ 2 ]. IgAN affects the kidneys by attacking the glomeruli and is characterized by persistent urinary abnormalities including microscopic hematuria, gross hematuria, and/or proteinuria [ 2 , 3 ]. IgAN is the most common form of biopsy-proven primary glomerulonephritis (PGN) worldwide [ 3 ] and is one of the leading causes of chronic kidney disease (CKD) and end-stage renal disease (ESRD) [ 4 ].

Primary treatments for IgAN include angiotensin-converting enzyme inhibitor/angiotensin receptor blockers (ACEIs/ARBs), corticosteroids, and immunosuppressants [ 1 , 4 ]. These treatments aim to address symptoms and manifestations of IgAN but not the underlying cause. Nearly one-third of IgAN patients develop ESRD within 10 years [ 5 ]. On average, patients with IgAN die 6 years earlier than the general population [ 6 ]. In addition, patients’ quality of life (QoL) is greatly impacted due to pain, fatigue, and poor mental health [ 4 ], and indirect caregiver burden is high due to time spent caring for patients who progress to ESRD. Thus, caregivers’ QoL and psychological well-being can also be negatively impacted [ 7 ].

IgAN prevalence is highest in Asia, intermediate in Europe and the US, and lower in African countries [ 8 ]. The overall global incidence is approximately 2.5 per 100,000 people per year [ 2 ]. A higher prevalence of IgAN is seen in countries where routine screening is practiced [ 4 ]. While geographic variations of IgAN have been studied previously [ 3 , 9 ], few recent studies have focused on regional disease burden differences and treatment patterns in among IgAN patients across Asian countries/regions and Australia.

This review aimed to summarize the disease burden and treatment patterns of IgAN in select countries/regions in the Asia-Pacific region, specifically mainland China, Taiwan, South Korea, Japan, and Australia.

Data sources and search strategy

A targeted literature review (TLR) was conducted to identify relevant literature published from January 2010 to December 2021 for mainland China, Taiwan, South Korea, Australia, and Japan. The earliest year of publication was expanded from 2010 to 2001 to capture evidence more comprehensively on outcomes of interest. Medline and Embase were the primary databases for publications in English. For publications in local languages, WANFANG and China National Knowledge Infrastructure (CNKI) databases were searched for publications in Chinese, Korean Medical Database and Korean Information Service System (KISS) databases were searched for publications in Korean, and Scholarly and Academic Information Navigator (CiNii) was searched for publications in Japanese. Supplementary searches for clinical guidelines, conference proceedings, and websites of governmental and non-governmental organizations were conducted using Google, Baidu (for Chinese sources), and Naver (for Korean sources). Publications cited as references were also considered for screening.

Search terms included IgA nephropathy, Berger’s disease, incidence, prevalence, mortality, quality of life, cost, burden, and treatment. Observational studies, reviews, and registry studies were included in the search. Publications that reported prevalence, incidence, mortality, treatment patterns, guidelines, economic, and humanistic burden were included for data extraction. Search terms in English and local languages are listed in Supplementary Table S1 .

Study selection and data extraction

After the search was conducted and duplicates were removed, the title, abstract, and full texts of the remaining publications were screened. A second reviewer conducted the validation and finalization for publications to be included in the data extraction phase. During screening, the inclusion and exclusion criteria mainly focused on outcomes. Systematic reviews, observational studies including registry/database studies and other real-world studies, annual reports were considered for inclusion. Publications that reported evidence regarding epidemiology (incidence, prevalence, and mortality), humanistic and economic burden, and treatment patterns (treatment guidelines, duration, adherence, persistence, switching, and discontinuation) were included for data extraction. Studies that did not include outcomes of interest were excluded, as were studies with a small sample size (< 25). Strict predefined population, intervention, comparators, outcomes, and study design (PICOS) selection criteria and a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) diagram were not used in this study. Study characteristics, patient characteristics, epidemiological outcomes, disease burden, and treatment patterns were extracted.

Study quality assessment

All eligible studies went through a quality assessment (QA) using a recommended checklist, according to the Center for Reviews and Dissemination Guidance for Undertaking Reviews in Health Care recommendations [ 10 ]. Quality assessment was performed for all eligible articles by two reviewers. The checklist consisted of 9 items excluding basic information for the included studies. Because all publications included in this study were observational studies or reviews, only the non-randomized clinical trial checklist was used for observational studies.

Sixty-nine publications were included for this review, among which 38 were from mainland China (2015–2021) [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 ], 15 from Japan (2003–2021) [ 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 ], 10 from South Korea (2010–2020) [ 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 ], 3 from Taiwan (2014–2019) [ 74 , 75 , 76 ], and 3 from Australia (2001–2021) [ 77 , 78 , 79 ]; characteristics of the studies are shown in Supplementary Table S2 . Approximately 83% the publications reported a retrospective study design ( n  = 57). For publications from mainland China, sample sizes ranged from 74 [ 37 ] to 4,367,829 [ 47 ], and male percentages ranged from 37.5% [ 17 ] to 97.3% [ 32 ]. For publications from Japan, sample sizes ranged from 52 [ 53 ] to 270,902 [ 63 ]; the male percentage ranged from 37.1% [ 58 ] to 56.96% [ 52 ]. For publications from South Korea, sample sizes ranged from 25 [ 64 ] to 5,114 [ 67 ]; the male percentage ranged from 36% [ 64 ] to 66.6% [ 73 ]. For publications from Taiwan, sample sizes ranged from 91 [ 75 ] to 7,073 [ 76 ]; the male percentage ranged from 45.9% [ 76 ] to 52.7% [ 75 ]. For publications from Australia, sample sizes ranged from 1,147 [ 78 ] to 2,457 [ 79 ]; the male percentage ranged from 60% [ 77 ] to 69.7% [ 79 ]. The Kidney Disease: Improving Global Outcomes (KDIGO) Clinical Practice Guideline [ 1 ] and 2 country-specific guidelines [ 80 , 81 ] were also included for evidence on treatment patterns.

Sixty-eight journal articles were assessed for study quality (all details of the quality assessment are shown in Supplementary Table S3 ); one white paper was not included in the study quality assessment. Approximately 75% (51/68 articles) were deemed to be of good quality (i.e., without inherent flaws). Few studies reported the incidence/prevalence of IgAN directly and percentage of IgAN were extracted from included studies. The appropriateness of the statistical analysis conducted was not clear or not specified in 5 studies, as they did not define P values and the level of significance for all observations. Across studies, outcome measures were generally considered reliable. However, 33 articles stated that the results could be generalized to routine practice. In one case-control study, the similarity of both groups at the outset of the study was not clear.

Six publications provided evidence on IgAN incidence [ 30 , 61 , 63 , 74 , 77 , 78 ] in Australia ( n  = 2), Japan ( n  = 2), mainland China ( n  = 1), and Taiwan ( n  = 1). Most were cross-sectional observational studies ( n  = 4), and sample sizes ranged from 156 [ 74 ] to 270,902 [ 63 ].

In Australia, IgAN incidence was estimated to be 1.41–10.5 per 100,000 people per year [ 77 , 78 ]. According to Briganti 2001 [ 78 ], IgAN incidence in Australia was lowest (0.0 per 100,000 per year) among male children and highest (10.7 per 100,000 per year) among male adults [ 78 ]. In Japan, only 2 studies reporting incidence data among children were identified. Utsunomiya 2003 [ 63 ] reported an incidence rate of 4.5 per 100,000 per year among 270,902 junior high and elementary school students; Kajiwara 2020 [ 61 ] reported a rate of 3.3 per 100,000 per year among 60,816 junior high and elementary school students. Both publications collected urine samples through a school urinary screening system in students 6 to 15 years old. In mainland China, the incidence rate of IgAN was estimated to be 6.3% among elderly patients who underwent renal biopsy and 24.7% among non-elderly patients who underwent renal biopsy [ 30 ]. In Taiwan, IgAN incidence was estimated to be 5.5 per million per year among the general population (around 23.5 million between 2014 and 2016), based on 1,445 renal biopsy records from a registry database [ 74 ]. In general, IgAN incidence was higher in males (5.7 per 100,000 per year) compared with females (2.9 per 100,000 per year) [ 78 ]. IgAN incidence was not reported in Korean populations.

Prevalence and diagnosis rate

IgAN prevalence among the general population was not reported in the included publications. But one cross-sectional study ( n  = 3,623) reported an IgAN prevalence rate of 0.03% among the general Chinese pediatric population [ 34 ]. Thirty-five publications were identified with diagnosis rates among 2 populations: patients who received renal biopsies and PGN patients [ 13 , 14 , 17 , 18 , 19 , 21 , 22 , 24 , 30 , 31 , 33 , 34 , 35 , 36 , 39 , 40 , 43 , 44 , 45 , 46 , 47 , 48 , 52 , 59 , 67 , 68 , 69 , 70 , 71 , 72 , 74 , 75 , 76 , 79 ]. Twenty-one publications were from mainland China [ 13 , 14 , 17 , 18 , 19 , 21 , 24 , 30 , 31 , 33 , 34 , 35 , 36 , 39 , 40 , 43 , 44 , 45 , 46 , 47 , 48 ], 6 from South Korea [ 67 , 68 , 69 , 70 , 71 , 72 ], 3 from Taiwan [ 74 , 75 , 76 ], 3 from Japan [ 52 , 55 , 59 ], and 1 from Australia [ 79 ]. The majority (88%) were cohort studies ( n  = 17) [ 13 , 21 , 31 , 33 , 35 , 36 , 39 , 40 , 43 , 44 , 45 , 46 , 52 , 68 , 69 , 70 , 71 ] and cross-sectional studies ( n  = 13) [ 14 , 17 , 18 , 19 , 21 , 24 , 34 , 37 , 47 , 59 , 67 , 72 , 74 , 79 ], with the remainder being an annual report [ 76 ], a registry study [ 55 ] and a chart review [ 75 ]. Sample sizes ranged from 33 [ 70 ] to 43,67,829 [ 47 ].

In mainland China, the mean diagnosis rate of IgAN was estimated to be 24.1% among patients undergoing renal biopsies (median: 23.0%; range: 6.3-40.9%) [ 13 , 19 , 21 , 22 , 24 , 30 , 46 ] and 27.3% (median: 27.9%; range: 0-72.1%) [ 14 , 19 , 21 , 33 , 36 , 40 , 43 , 44 , 45 , 48 ] among PGN patients (Fig.  1 a); The mean IgAN diagnosis rate was estimated to be 21.7% (median: 17.5%; 17-30.4%) among children who underwent renal biopsy [ 17 , 18 , 35 ]. In Taiwan, the mean diagnosis rate of IgAN was 12.1% (median: 12.2%; range: 10.8-13.2%) among patients undergoing renal biopsies [ 74 , 75 ] and was reported similar (26%) among PGN patients [ 74 , 76 ] (Fig.  1 b). In South Korea, the mean diagnosis rate was 41% (median: 38.1%; range: 25.8-61.9%) among patients undergoing renal biopsies [ 67 , 69 , 71 , 72 ] and around 51.6% (average of 51.3% and 51.9%) among PGN patients [ 68 , 70 ] (Fig.  1 c). In Japan, Hattori 2016 reported a mean estimated IgAN diagnosis rate of 23% (median: 22.9%) among CKD patients [ 59 ]. In addition, the reported IgAN diagnosis rate among patients who underwent renal biopsy was 31%, with 6.9% in patients aged 65 to 80 years old and 10.5% in patients aged 80 years or older [ 52 , 55 ]. In Australia, Lee 2020 reported an IgAN diagnosis rate of 13% among patients undergoing renal biopsy [ 79 ].

IgAN Prevalence in Mainland China, Taiwan and South Korea (Abbreviation: ANS, acute nephritic syndrome; CNS, chronic nephrotic syndrome; NHRI, National Health Research Institute & Taiwan Society of Nephrology; NS, nephritis syndrome(e; PGN, primary glomerulonephritis; RPG, rapidly progressive glomerulonephritis)

Disease progression and mortality

Among included studies, all-cause mortality was mainly reported as deaths due to ESRD. Seven publications from mainland China [ 23 , 26 , 27 , 28 , 29 , 41 , 42 ], 7 from Korea [ 64 , 65 , 66 , 68 , 70 , 71 , 73 ], 4 from Japan [ 50 , 51 , 57 , 62 ], and 1 from Taiwan [ 75 ] reported rate of progression to ESRD in IgAN. These studies varied in the definition of endpoint, patient characteristics, and follow-up duration. In China, the median rate of progression to ESRD was 4.1% [ 28 ] over 6 months, ranged from 1.3 to 15.8% (median: 1.3%) over 40–45 months [ 29 , 41 ], ranged from 6.6 to 15% (median: 8.3%) over 4–10 years [ 23 , 27 , 42 ], and 33% over 15 years [ 42 ]. In Korea, the median rate of progression to ESRD ranged from 2.5 to 39.7% (median: 19%) from 60 to 100 months [ 64 , 65 , 66 , 68 , 70 , 71 , 73 ].

Regarding direct reports on mortality, in mainland China, 0.7% of adult IgAN patients progressed to death according to 1 study of 944 patients from 2003 to 2014 with a median follow-up of 4.2 years [ 23 ]. In South Korea, the median death rate was 5.3% (range: 4.4-5.9%) [ 65 , 66 , 68 ] for 1,364 IgAN patients with a median follow-up of 100 months. In addition, 2 publications reported a standard mortality ratio (expressed as the ratio between the observed and the expected number of deaths in the general population) of 1.43 (95% confidence interval:1.04–1.92) among 1,364 IgAN patients in relation to the general population [ 65 , 68 ]. In Japan, IgAN mortality was estimated to be 0.3 per 100 person-years among non-smokers [ 51 ], 1.3 per 100 person-years among smokers [ 51 ] and 1.2 per 100 person-years among patients who received kidney replacement therapy [ 53 ] based on 2 retrospective studies [ 51 , 53 ]. No mortality data was found among IgAN patients in Taiwan or Australia.

• Treatment patterns

Twenty publications [ 1 , 11 , 15 , 26 , 27 , 29 , 42 , 49 , 50 , 54 , 56 , 57 , 58 , 60 , 62 , 64 , 68 , 71 , 73 , 81 ] and 3 clinical guidelines reported treatment patterns. Nine from mainland China [ 11 , 15 , 26 , 27 , 28 , 29 , 32 , 41 , 42 ], 8 from Japan [ 49 , 50 , 54 , 56 , 57 , 58 , 60 , 62 ], and 4 from South Korea [ 64 , 68 , 71 , 73 ]. 80% publications were retrospective studies ( n  = 16) [ 11 , 15 , 26 , 27 , 29 , 42 , 49 , 56 , 57 , 58 , 60 , 62 , 64 , 68 , 71 , 73 ]. Sample sizes ranged from 25 [ 64 ] to 2,283 [ 50 ]. The KDIGO [ 1 ] and 2 country-specific treatment guidelines, 1 from mainland China [ 80 ] and 1 from Japan [ 81 ], were identified. No treatment guidelines were identified in Taiwan, South Korea, or Australia.

The KDIGO guidelines (2021 version) provide treatment recommendations for adults and children with IgAN [ 1 ]. The guidelines state that the management of IgAN should be multifaceted, optimized with supportive care, and include ACEIs/ARBs as tolerated or allowed, control blood pressure, minimize cardiovascular risk, and adherence to lifestyle changes including dietary counseling, smoking cessation, weight control, and exercise, as appropriate. The guidelines provide specific treatment recommendations according to the variant forms of IgAN, the level of proteinuria, and high-risk rate for progression after maximal supportive care. The main treatment regimens include ACEIs and ARBs, immunosuppressants, cyclophosphamide, tonsillectomy, and lifestyle modification [ 1 ]. Similar to the KDIGO guidelines, the primary treatment recommendations in the Chinese 2017 guidelines for children with IgAN were glucocorticoids, immunosuppressants, and ACEIs/ARBs [ 80 ]. Japanese 2020 guidelines covered children and adults, with different treatment recommendations based on symptoms and subtype of IgAN (the subgroup classification for adults was based on estimated glomerular filtration rate and proteinuria; symptoms among children were classified as mild or severe) [ 81 ].

In mainland China, 6 studies investigated adult populations [ 15 , 26 , 28 , 29 , 32 , 42 ] (Table  1 ) and 3 investigated pediatric populations [ 11 , 27 , 41 ] (Table  2 ). For drug usage among adult patients, ACEIs/ARBs had the largest median percentage at 66.7% (range: 38-90%) [ 15 , 26 , 28 , 29 , 32 , 42 ], followed by steroids, with median of 36% (corticosteroids/prednisone/intravenous methylprednisolone injection, range: 10-100%) [ 15 , 26 , 28 , 29 , 32 , 42 ] and immunosuppressants (including in combination with steroids), with median of 25.9% (cyclophosphamide, tacrolimus and tripterygium wilfordii, range: 1.6-72%) [ 15 , 26 , 28 , 29 , 32 , 42 ]. Among pediatric patients, immunosuppressants (cyclophosphamide/mycophenolate /Tripterygium wilfordii /leflunomide) were the common drugs recommended, with a median of 64% (range: 1.7–72.2%) [ 11 , 27 , 41 ], followed by ACEIs/ARBs, with a median of 49.5% (range: 2.5-70%) [ 11 , 27 , 41 ] and steroids with a median of 45% (range: 25.3-69.3% as sum of oral prednisone and intravenous methylprednisolone) [ 11 , 27 , 41 ].

In South Korea, 3 publications on adult IgAN patients [ 64 , 68 , 71 ] (Table  1 ) and 1 publication among pediatric patients [ 73 ] (Table  2 ) were identified. Among adults, ACEIs/ARBs were the most common treatments (27.7-83.4%) [ 68 , 71 , 73 ], followed by ACEIs/ARBs and corticosteroid combinations (33.9%) [ 64 ] and corticosteroids alone (12.4-28.8%) [ 68 , 71 , 73 ]. Among pediatric patients, the frequency of immunosuppressant use was 50.2% [ 73 ].

In Japan, 7 publications reported IgAN treatment patterns among adults [ 50 , 54 , 56 , 57 , 58 , 60 , 62 ] (Table  1 ) and 2 publications [ 49 , 54 ] among pediatric patients (Table  2 ). Among adults, ACEIs/ARBs were the most common treatment (25-99.6%) [ 50 , 54 , 56 , 57 , 58 , 60 , 62 ], followed by antiplatelet agents (58.1-96.8%) [ 54 ] and corticosteroid-immunosuppressant combination therapy (1.5-74%) [ 62 ]. Notably, the rate of administering steroid-immunosuppressant combination was only 1.5% in a retrospective cohort study that sampled 1,012 IgAN patients with a mean age of 32.96 ± 12 years [ 56 ]. Among pediatric patients, ACEIs/ARBs were the most frequently administered treatments (0.9-95.7%) [ 49 , 54 ], followed by antiplatelet agents (range: 1.2-82.6%) [ 49 , 54 ] and immunosuppressants (range: 4.6-68.5%) [ 49 ]. The frequency of administering treatments varied greatly across different subgroups. For example, the frequency of administering ACEIs/ARBs ranged from 0.9% for the diffuse mesangial proliferation subgroup ( n  = 108) to 50.9% for the focal mesangial proliferation subgroup ( n  = 173) in 1 retrospective study in Japanese children with IgAN from 1990 to 2004 [ 49 ]. Tonsillectomy or tonsillectomy combined with steroid was mostly reported in Japanese studies, with frequencies ranging from 1 to 66.2% across publications (Table  1 ). This is in accordance with the KDIGO 2021 guidelines’ evidence that supports the routine use of tonsillectomy in Japanese high-risk patients with IgAN [ 1 ]. No publications reporting IgAN treatment patterns were identified for Taiwan or Australia.

Humanistic burden

Four publications in China reported QoL, measured by the 36-Item Short Form Health Survey (SF-36) [ 16 , 25 ], Daily Living Ability Rating Scale (DLARS) [ 37 ], and QoL scale (QOLs) combined with Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS) [ 38 ]. SF-36 scores reflect physical and mental health based on 8 health concepts, including physical and social functioning, role limitations due to physical and emotional problems, mental health, vitality, bodily pain, and general health (GH) perception [ 82 ]. Two publications evaluated the effects of individualized nursing intervention (INI, one improved nursing intervention which costs more time than routine nursing intervention [RNI]) on the psychological mood and QoL among IgAN patients [ 16 , 25 ]. There were two subgroups, the patients in the control group received RNI and patients in the intervention group received INI [ 16 , 25 ]. The mean GH score was 32.16 [ 16 ] among total IgAN patients ( n  = 98; mean age: 32.74 years; male percentage: 50%) in 2017 and 80.15 increasing from 69.93 at baseline [ 25 ] after intervention among total IgAN patients ( n  = 84; mean age: 33.57 years; male percentage: 60.7%) in 2019. In both publications, the intervention groups had higher mean GH scores than that in the control groups (39.47 vs. 24.84 [ 16 ] and 85.73 vs. 74.56 [ 25 ], respectively). Two other prospective studies assessed the effect of INI for IgAN patients [ 37 , 38 ]. Results showed that both mean DLARS and QOLs scores were higher among the intervention group compared to the control group (88.5 vs. 75.7 and 39.5 vs. 24.8, respectively) [ 37 , 38 ]. SAS and SDS scores were also evaluated by Qi 2021 [ 38 ], the mean SAS score decreased more in the intervention group (49.2 ± 6.3 decreased from 62.1 ± 5.8) than that in the control group (57 ± 4.9 decreased from 62.4 ± 6.1) from baseline. Similarly, the mean SDS score decreased more in the intervention group (43.3 ± 5.2 decreased from 56.2 ± 6) than in the control group (52.6 ± 6.4 decreased from 57 ± 6.2) from baseline [ 38 ].

Economic burden

No publications reported indirect costs, but 3 retrospective studies reported hospitalization costs for IgAN patients in China (see Supplementary Figure S1 ) [ 12 , 20 , 47 ]. Hospitalization cost per patient per year is ¥14,900 ($2,252.12; exchange rate of Chinese Yuan [CNY] and US dollar in 2018 was 6.616 [ 83 ]) as reported by Zheng 2018 [ 20 ], and between ¥9,618 ($1,532.26; exchange rate of CNY and US dollar in 2015 is 6.227 [ 83 ]) and ¥10,019 ($1,608.96) as reported by Peng 2015 [ 12 ]. One large database study covering 54.1% of tertiary hospitals in 31 Chinese provinces from 2010 to 2015 reported a hospitalization cost of ¥8,000/$1,284.73 (¥6,000-¥12,000) [ 47 ]. Drug costs accounted for 28.39% of total hospitalization costs, followed by diagnostic testing costs [ 12 ]. Length of stay per patient per year in China ranged from 10 to 14.3 days across 3 publications [ 12 , 20 , 47 ].

To our knowledge, this is the first TLR to summarize the evidence on IgAN disease burden and treatment patterns in mainland China, Taiwan, South Korea, Japan, and Australia. The findings of this review revealed evidence gaps in IgAN epidemiology and humanistic and economic burden. No incidence data was identified in South Korea; no mortality data was identified in Taiwan and Australia; no country/region-specific treatment guidelines were found for Taiwan, South Korea, or Australia; no evidence on treatment patterns from the publications was identified for Taiwan or Australia; and no humanistic burden or economic data was identified except for mainland China.

The IgAN incidence rates among Japanese, Taiwanese, and Australian populations ranged from 0 to 10.7 per 100,000 people per year, higher than the incidence rate reported in a recent systematic literature review (SLR) by Kwon 2021 [ 84 ] (1.29 per 100,000 people per year). Kwon 2021 [ 84 ] is an SLR focusing on US epidemiology, health-related QoL, and the economic burden of IgAN (the included studies were published from January 2010 to June 2020), similar to our study’s objective. Incidence rates among children and teenagers (0-4.5 per 100,000 per year) were similar to the incidence rate in Venezuela (0.03 per 100,000 per year) [ 85 ] and in Italy (0.31 per 100,000 per year) [ 86 ]. The overall prevalence and diagnosis rates of IgAN were similar across selected countries/regions. The diagnosis rates in this review differed from those found in PGN patients and patients who received renal biopsy in Kwon 2021 [ 84 ]; diagnosis rates of IgAN from our results were higher in PGN patients compared with patients who received renal biopsies since renal biopsies were often performed on PGN patients before diagnosis. This applied to both adult and pediatric populations. Compared to the US population in Kwon 2021 [ 84 ], the diagnosis rate among PGN populations in this review was higher (26-72.1% vs. 9.4-19.7%). The diagnosis rate among populations with renal biopsies was also higher (6.3-61.9% vs. 6.3-14.3%). Notably, though not covered by this review, the pathological profile such as Oxford Classification/MEST classification could also shed light upon disease burden, which could be further explored by future studies.

IgAN treatments primarily consisted of ACEIs/ARBs, and high utilization of steroids was found despite mixed evidence on their benefits and safety. There is limited data on IgAN treatment patterns from Taiwan and Australia. Among the publications that reported treatment patterns, few specified drugs’ generic names. The primary treatment patterns reported among select countries/regions in this study are similar to those in US as reported by Kwon 2021 (frequently used therapies were immunosuppressives, corticosteroids, and ACEIs/ARBs) [ 84 ]. Immunosuppressives were used more by children than adults based on data from mainland China, South Korea, and Japan. According to the KDIGO guideline regarding glomerular diseases, the immunosuppressive therapies including azathioprine, cyclophosphamide, calcineurin inhibitors, and rituximab are not recommended for treating IgAN. Mycophenolate mofetil is recommended in Chinese patients and tonsillectomy is recommended to be used in Japanese IgAN patients [ 1 ]. Only Chinese studies reporting SF-36 scores and other metrics were identified. Therefore, more studies on QoL in IgAN patients and caregivers in other regions are warranted.

Evidence of economic burden was identified only from studies in mainland China; Li 2018 was one retrospective national inpatient database study, which included the major hospitals that covers multiple geographic locations [ 47 ], other two studies used the data from one hospital. The mean cost per patient per year reported by Li 2018 is $1,284.73, while one Canadian retrospective study for costs and healthcare resource utilization reported a mean outpatient medication cost per patient per year of Canadian dollar (CAD) $221 in 2016 [ 87 ]. To control medical costs, hospitals in China are undergoing clinical pathway optimization programs [ 12 ].

Publications reported heterogeneous sample populations where IgAN prevalence/diagnosis rates were evaluated. Among 22 publications that reported IgAN prevalence/diagnosis rates, 15 measured IgAN prevalence for patients who underwent renal biopsy and 9 measured IgAN prevalence for patients diagnosed with PGN. Heterogeneity in IgAN prevalence/diagnosis rates may be attributed to differences in study years, patient race/ethnicity, patient age, treatment method, risk factors, diagnosis, and follow-up duration. Other study design–related factors that could introduce bias include sample size and gender composition.

Finally, differences in IgAN prevalence across regions should be noted. County/region-specific healthcare infrastructure and policies influence the epidemiological evidence of IgAN. systematic urine screening programs among individuals with asymptomatic, persistent microscopic hematuria with/without mild proteinuria are commonly implemented in certain countries/regions. These programs facilitate detection of IgAN patients who would otherwise receive a delayed diagnosis or none at all. Countries/regions where screening programs are performed may therefore have higher reported IgAN prevalence. Screening programs play a crucial role in early diagnosis and early treatment [ 88 ].

To our knowledge, this is the first TLR for IgAN in mainland China, Taiwan, South Korea, Japan, and Australia. However, several limitations should be noted. Due to the targeted nature of this review, the search focused on the most relevant literature, and the publications included in this study were prioritized, which potentially have led to an incomplete picture of IgAN-related epidemiology, treatment patterns and disease burden. Across included publications, the sample sizes varied widely and were not always reported. Additionally, this TLR did not weigh the data from included publications; therefore, biases should be considered when comparing outcomes. Studies came from primarily single institutions, and national-level data was not always available for the selected countries/regions. Moreover, this review only covered select Asia-Pacific countries/regions; future reviews and studies in other countries and regions within Asia-Pacific are therefore warranted. Despite these limitations, the evidence gathered in this literature review may help provide a preliminary understanding of the disease burden of IgAN in the Asia-Pacific region.

This TLR summarized evidence on Immunoglobulin type A nephropathy (IgAN) prevalence, treatment patterns, and humanistic and economic burden. Our results suggest that despite the overall scarcity of information in general, evidence on disease burden and treatment patterns has been reported by some studies and several clinical guidelines. The prevalence of IgAN among the general population is not commonly available, while that among patients receiving renal biopsies and diagnosed with PGN is more frequently reported. Heterogeneity in prevalence rates across geographic regions might be explained by differences in initial diagnosis in some regions due to variation in local screening policy and disease management. There is a need to understand how the disease progression differs by those practices. Treatment patterns have been reported mainly in studies from some Asia areas, but geographic variations are noticeable. There is also a need to generate more evidence to shed light upon the possible explanation to the differences in the treatment patterns across geographic regions. In sum, more real-world studies at national levels across select countries/regions are warranted to fill the evidence gaps, particularly regarding incidence, humanistic burden, and economic burden.

The prevalence of IgA nephropathy among the general population in select APAC countries/regions is not commonly available, despite evidence from studies and clinical guidelines. In addition, it is observed across geographic regions that heterogeneity exists in prevalence rates, and large variations exist in treatment patterns. Future studies are needed to fill in these gaps to understand the contributing factors behind the differences through population-based, multi-center, and real-world studies.

Data availability

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

Abbreviations

Angiotensin-converting enzyme inhibitor

Acute nephritic syndrome

Asia Pacific

Angiotensin receptor blockers

Canadian dollar

Chronic kidney disease

China National Knowledge Infrastructure

Chronic nephrotic syndrome

Chinese Yuan

Cyclophosphamide

Daily Living Ability Rating Scale

Diffuse mesangial proliferation

Excerpta Medica Database

End-stage kidney failure

Focal mesangial proliferation

General health

Individualized nursing intervention

The Kidney Disease: Improving Global Outcomes

Korean Information Service System

Mycophenolate mofetil

Not reported

Nephritis syndrome

Primary glomerulonephritis

Population, intervention, comparators, outcomes, and study design

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Quality assessment

Routine nursing intervention

Rapidly progressive glomerulonephritis

Self-Rating Anxiety Scale

Standard deviation

Self-Rating Depression Scale

36-Item Short Form Health Survey

Systematic literature review

Targeted literature review

Taiwan Society of Nephrology

Working Group for National Survey on Status of Diagnosis and Treatment of Childhood Renal Diseases

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Research conception and/or design: Kristin Pareja, Sandipan Bhattacharjee, Omer Zaidi, Fen Du, and Zhaoli Tang; Literature searching strategy: Omer Zaidi, Fen Du, and Zhaoli Tang; literature screening and data extraction and analysis: Fen Du and Zhaoli Tang; All authors were involved in the drafting and /or substantial revision of manuscript; All authors accept accountability for their contributions and agree as a condition of authorship to ensure resolution of questions about the work. All authors approved the submitted version.

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Zaidi, O., Du, F., Tang, Z. et al. Review on epidemiology, disease burden, and treatment patterns of IgA nephropathy in select APAC countries. BMC Nephrol 25 , 136 (2024). https://doi.org/10.1186/s12882-024-03555-5

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Lack of curation 

The i nternet is full of ‘scholarly’ content, information, and data in various formats and of various quality. As John Naisbitt  said ,   “We are drowning in information ,  but starv ed for knowledge”  

When Google Scholar trawls the  i nternet to seek out scholarly content, it does not assess it. It does not try to make sense of it for researchers in a logical indexed structure. And, unlike many trusted curated tools 4 , Google Scholar does not have transparent indexing guideline s that  defin e  what they collect,  and  why they collect it and make it available.   

Recent research shows that Google Scholar is “unsuitable as a primary review for resources” 5 . Other research argues that Google Scholar has flaws and lacks technological features to enable systematic searching. As a result, it fails to   adhere to several FAIR principles (Findable, Accessible, Interoperable and Reusable) and cannot be classed as a professional searching tool 6 .    

Google Scholar is not a curated controlled database. Content is harvested automatically.   

Whilst there are some advantages to this, for example in the retrieval of grey literature 7 , there are also significant disadvantages.  

Search results rankings 

Research has shown that Google Scholar results can be dated. This presents an issue when most people don’t go beyond the first page of results when searching for papers.    

The citation count of an article is a major factor in the Google Scholar results ranking 8 , 9 . This benefits publications from high Impact Factor sources, which are cited or linked to extensively around the Internet.    

Unfortunately, new papers have what’s called a citation lag, and older papers are cited more often 10 . Newly published papers may be retrieved by GS, but they will be further down the results list and you may not see them.     

P aper s can also be manipulated into a higher rank than it ‘deserves’ by placing words in titles or abstracts to increase recall or manipulate citing data 3 .    

Should you need to include multi-lingual items in your search, there is a definite bias in Google Scholar towards English-language content. Documents published in languages other than English are relegated to positions that make them virtually invisible 8 .  

Replicating your search 

It is nearly impossible to replicate a search in GS, to retrieve the same references again. For this reason, it’s recommended to carefully document a search done in Google Scholar for full transparency 6 .  That can be extremely time consuming.   

References are often dropped unknowingly from GS 5 , 11 , 12   and you won’t even know the ones that might be missing 1 .   

Using your results 

In Google Scholar, once you have the results, it does not allow you to see beyond 1,000 records or to download more than 20 references to your bibliographic tool at a time. Most curated databases allow you to run your search, save it, download the results to your tool and revisit it.   

How to search more effectively 

IFIS has published a guide called  Best Practice for Literature Searching . This provides guidance on where to search; how to formulate research questions and evaluate results. Click here to access the guide

(Image Credit: Kaitlyn Baker and Solen Feyissa at Unsplash )

• Gardner T, Inger S. How readers discover content: Trends in reader behaviour from 2005 to 2021. Renew Consultants. 2021; 17. Available from: https://renewconsultants.com/wp-content/uploads/2021/07/How-Readers-Discover-Content-2021.pdf
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• Gusenbauer M, Haddaway NR. "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 2020; 11(2): 181-217. Available from: https://doi.org/10.1002/jrsm.1378  
• Boeker M, Vach W, Motschall E. Google Scholar as replacement for systematic literature searches: Good relative recall and precision are not enough. BMC Medical Research Methodology. 2013; 13(1):1-2. Available from: https://doi.org/10.1186/1471-2288-13-131  
• Haddaway NR, Collins AM, Coughlin D, Kirk S. The role of Google Scholar in evidence reviews and its applicability to grey literature searching. PloS One. 2015; 17;10(9): e0138237. Available from: https://doi.org/10.1371/journal.pone.0138237  
• Beel J, Gipp B. Google Scholar's ranking algorithm: The impact of citation counts (an empirical study). Proceedings of the 2009 3rd International Conference on Research Challenges in Information Science, RCIS 2009; 439–446. Available from: http://doi.org/10.1109/RCIS.2009.5089308  
• Rovira C, Codina L, Guerrero-Solé F, Lopezosa C. Ranking by relevance and citation counts, a comparative study: Google Scholar, Microsoft Academic, WoS and Scopus. Future Internet. 2019 Sep;11(9):202. Available from: https://doi.org/10.3390/fi11090202
• Khare R, Leaman R, Lu Z. Accessing biomedical literature in the current information landscape. Biomedical Literature Mining. 2014; 11-31. Available from: https://doi.org/10.1007/978-1-4939-0709-0_2
• Nicholas D, Boukacem‐Zeghmouri C, Rodríguez‐Bravo B, Xu J, Watkinson A, Abrizah A, Herman E, Świgoń M. Where and how early career researchers find scholarly information. Learned Publishing. 2017; 30(1): 19-29. Available from: https://doi.org/10.1002/leap.1087 .
• Jamali HR, Asadi S. Google and the scholar: The role of Google in scientists' information‐seeking behaviour. Online Information Review. 2010 Apr 20.. Available from: https://doi.org/10.1108/14684521011036990 .

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Open Access

Peer-reviewed

Research Article

The Role of Google Scholar in Evidence Reviews and Its Applicability to Grey Literature Searching

* E-mail: [email protected]

Affiliation MISTRA EviEM, Royal Swedish Academy of Sciences, Stockholm, Sweden

Affiliations Centre for Environmental Policy, Imperial College, London, United Kingdom, Department for Environmental, Food and Rural Affairs, London, United Kingdom

Affiliations Department for Environmental, Food and Rural Affairs, London, United Kingdom, Department for Civil and Environmental Engineering, Imperial College, London, United Kingdom

Affiliations Department for Environmental, Food and Rural Affairs, London, United Kingdom, Environment Agency, London, United Kingdom

• Neal Robert Haddaway, 
• Alexandra Mary Collins, 
• Deborah Coughlin, 
• Stuart Kirk

• Published: September 17, 2015
• https://doi.org/10.1371/journal.pone.0138237
• Reader Comments

Google Scholar (GS), a commonly used web-based academic search engine, catalogues between 2 and 100 million records of both academic and grey literature (articles not formally published by commercial academic publishers). Google Scholar collates results from across the internet and is free to use. As a result it has received considerable attention as a method for searching for literature, particularly in searches for grey literature, as required by systematic reviews. The reliance on GS as a standalone resource has been greatly debated, however, and its efficacy in grey literature searching has not yet been investigated. Using systematic review case studies from environmental science, we investigated the utility of GS in systematic reviews and in searches for grey literature. Our findings show that GS results contain moderate amounts of grey literature, with the majority found on average at page 80. We also found that, when searched for specifically, the majority of literature identified using Web of Science was also found using GS. However, our findings showed moderate/poor overlap in results when similar search strings were used in Web of Science and GS (10–67%), and that GS missed some important literature in five of six case studies. Furthermore, a general GS search failed to find any grey literature from a case study that involved manual searching of organisations’ websites. If used in systematic reviews for grey literature, we recommend that searches of article titles focus on the first 200 to 300 results. We conclude that whilst Google Scholar can find much grey literature and specific, known studies, it should not be used alone for systematic review searches. Rather, it forms a powerful addition to other traditional search methods. In addition, we advocate the use of tools to transparently document and catalogue GS search results to maintain high levels of transparency and the ability to be updated, critical to systematic reviews.

Citation: Haddaway NR, Collins AM, Coughlin D, Kirk S (2015) The Role of Google Scholar in Evidence Reviews and Its Applicability to Grey Literature Searching. PLoS ONE 10(9): e0138237. https://doi.org/10.1371/journal.pone.0138237

Editor: K. Brad Wray, State University of New York, Oswego, UNITED STATES

Received: June 23, 2015; Accepted: August 26, 2015; Published: September 17, 2015

Copyright: © 2015 Haddaway 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: All relevant data are within the paper and its Supporting Information files.

Funding: AMC acknowledges a Policy Placement Fellowship funded by the Natural Environment Research Council, the UK Department for Environment Food and Rural Affairs and the Environment Agency. Some ideas for this project were prompted by a forthcoming Defra research project (WT1552). NH was hosted at Bangor University ( http://www.bangor.ac.uk/ ).

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

Introduction

Searching for information is an integral part of research. Over 11,500 journals are catalogued by Journal Citation Reports ( http://thomsonreuters.com/journal-citation-reports/ ), and the volume of published scientific research is growing at an ever-increasing rate [ 1 , 2 ]. Scientists must sift through this information to find relevant research, and do so today most commonly by using online citation databases (e.g. Web of Science) and search engines (e.g. Google Scholar). Just as the number of academic articles and journals is steadily increasing, so too are the number of citation databases.

A citation database is a set of citations that can be searched using an online tool, for example Web of Science ( https://webofknowledge.com/ ). These databases typically charge subscription fees for access to the database that do not cover the cost of access to the full text of the research articles themselves. Generally these databases selectively catalogue citations according to a predefined list of journals, publishers or subject areas. Several free-to-use services have recently appeared that search for citations on the internet, most notably Google Scholar and Microsoft Academic Search. These search engines do not store citations within a specific database, instead they regularly ‘crawl’ the internet for information that appears to be a citation. Some key characteristics of databases and search engines are compared in Table 1 .

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https://doi.org/10.1371/journal.pone.0138237.t001

According to Thomson Reuters, the Web of Science Core Collections citation database contains almost 50 million research records ( http://wokinfo.com/citationconnection/realfacts/ ; February 2015), with Microsoft Academic Search reporting to catalogue in excess of 45 million records as of January 2013 ( http://academic.research.microsoft.com/About/help.htm#9 ). Google Scholar does not report the volume of citations identifiable via their search facility, although attempts have been made to estimate this that suggest between 1.8 million [ 3 ] and 100 million records [ 4 ] are identifiable.

“Grey literature” is the term given to describe documents not published by commercial publishers, and it may form a vital component of evidence reviews such as systematic reviews and systematic maps [ 5 ], rapid evidence assessments [ 6 ] and synopses [ 7 ]. Grey literature includes academic theses, organisation reports, government papers, etc. and may prove highly influential in syntheses, despite not being formally published in the same way as traditional academic literature e.g. [ 8 ]. Considerable efforts are typically required within systematic reviews to search for grey literature in an attempt to include practitioner-held data and also account for possible publication bias [ 5 , 9 ]. Publication bias is the tendency for significant, positive research to be more likely to be published than non-significant or negative research, leading to an increased likelihood of overestimating effect sizes in meta-analyses and other syntheses [ 10 ]. The inclusion of grey literature is a central tenet of systematic review methodology, which aims to include all available documented evidence and reduce susceptibility to bias.

Academic citation databases are often the first port of call for researchers looking for information. However, access to databases is often expensive; some costing c. £100,000 per annum for organisations of up to 100 employees. Increasingly, researchers are using academic citation search engines to find information (Haddaway, unpublished data). Academic citation search engines appear to represent an attractive alternative to costly citation databases, cataloguing research almost immediately and not restricting results to certain journals, publishers or subject categories. Search engines are particularly attractive to systematic reviewers, since they have the potential to be used to search for grey literature quickly and simply using one search facility rather than a plethora of individual websites [ 5 ].

There is on-going debate regarding the utility of Google Scholar as an academic resource e.g. [ 11 , 12 ], but also as a replacement for traditional academic citation databases and in searches for grey literature in systematic reviews [ 13 , 14 ]. Google Scholar represents an attractive resource for researchers, since it is free-to-use, appears to catalogue vast numbers of academic articles, allows citations to be exported individually, and also provides citation tracking (although see criticism of citation tracking by Delgado Lopez-Cozar et al. [ 15 ]). Google Scholar is also potentially useful in systematic reviews, since reliance on just one such platform for searches would: i) offer resource efficiency, ii) offer cost efficiency, iii) allow rapid linking to full texts, iv) provide access to a substantial body of grey literature as well as academic literature, and v) be compatible with new methods for downloading citations in bulk that would allow for a very transparent approach to searching [ 16 ].

Previous research has shown that articles identified within systematic reviews are identifiable using Google Scholar [ 13 ]. However, other authors have suggested that this does not make Google Scholar an appropriate replacement for academic citation databases, as, in practice, there are considerable limitations in the search facility relative to those of academic databases [ 11 ], and there is on-going debate about Google Scholar’s place in research [ 12 ]. Shultz [ 17 ] listed many limitations that have been attributed to Google Scholar, including that the service permits use of only basic Boolean operators in search strings, which are limited to 256 characters, and that users cannot sort results (although some of the other cited disadvantages have been corrected in recent updates). Two further limitations to the use of Google Scholar in academic searches are the inability to directly export results in bulk as citations (although a limited number of individual citations can be extracted within a set time period) and the display of only the first 1,000 search records with no details of the means by which they are ordered.

Web-based academic search engines, such as Google Scholar, are often used within secondary syntheses (i.e. literature reviews, meta-analyses and systematic reviews). Systematic reviews typically screen the first 50 to 100 search records within Google Scholar e.g. [ 18 , 19 , 20 ], sometimes restricting searches to title rather than full-text searches e.g. [ 21 ]. Such activities are not themselves evidence-based, however. Little is known about how these results are ordered, or what proportion of search results are traditional academic relative to grey literature. Furthermore, this small degree of screening (50 to 100 records) is a very small proportion of the volume of literature found through other sources (often 10s of thousands of records).

Google Scholar has improved greatly in recent iterations; evident from early critiques of the service relative to academic citation databases that cite problems that no longer exist e.g. [ 22 , 23 ]. Whilst the debate on the usefulness of Google Scholar in academic activities has continued in recent years, some improvements to the service offer unequivocal utility; for example, Shariff et al. [ 24 ] found that Google Scholar provided access to almost three times as many articles free of charge than PubMed (14 and 5%, respectively).

Any recommendations in systematic review guidance that are made regarding the allocation of greater resources to the use of academic search engines, such as Google Scholar, should be based on knowledge that such resources are worthwhile, and that academic search engines provide meaningful sources of evidence, and do not correspond to wasted effort.

Here, we describe a study investigating the use of Google Scholar as a source of research literature to help answer the following questions:

• What proportion of Google Scholar search results is academic literature and what proportion grey literature, and how does this vary between different topics?
• How much overlap is there between the results obtained from Google Scholar and those obtained from Web of Science?
• What proportion of Google Scholar and Web of Science search results are duplicates and what causes this duplication ?
• Are articles included in previous environmental systematic reviews identifiable by using Google Scholar alone?
• Is Google Scholar an effective means of finding grey literature relative to that identified from hand searches of organisational websites?

Seven published systematic reviews were used as case studies [ 20 , 25 , 26 , 27 , 28 , 29 , 30 ] (see Table 2 ). These reviews were chosen as they covered a diverse range of topics in environmental management and conservation, and included interdisciplinary elements relevant to public health, social sciences and molecular biology. The importance and types of grey literature vary between subjects, and a diversity of topics is necessary for any assessment of the utility of a grey literature search tool. The search strings used herein were either taken directly from the string used in Google Scholar in each systematic review’s methods or were based on the review’s academic search string where Google Scholar was not originally searched. Search results in Google Scholar were performed both at “full text” (i.e. the entire full text of each document was searched for the specified terms) and “title” (i.e. only the title of each document was searched for the specified terms) level using the advanced search facility (see https://scholar.google.se/intl/en/scholar/help.html#searching for further details). Searches included patents and citations. Since Google Scholar displays a maximum of 1,000 search results this was the maximum number of citations that could be extracted using the specially developed method described below.

Searches were performed on 06/02/15. Web of Science includes the following databases as part of the MISTRA EviEM subscription; KCI-Korean Journal Database, SciELO Citation Index and Web of Sciences Core Collection.

https://doi.org/10.1371/journal.pone.0138237.t002

1. What proportion of Google Scholar search results is grey literature?

A download manager (DownThemAll!; http://www.downthemall.net ) and web-scraping programme (Import.io; http://www.import.io ) were used to download each page of search results (to a maximum of 100 pages; 1000 results) and then extract citations as patterned data from the locally stored HTML files into a database. Two databases (one for the title only search and one for the full text search) for each of the 7 systematic reviews were created, each holding up to 1,000 Google Scholar citations (see S1 File ).

Exported citations were assessed and categorised by NRH and AMC as one of the following types of literature:

• ‘Black’–peer-reviewed articles published in academic journals
• ‘Book’–monographs or complete books produced by commercial publishers
• ‘Book chapter’–chapters within books produced by commercial publishers
• ‘Patent’–registered patents and patent applications with the United States Patent and Trademark Office (USPTO)
• ‘Thesis’–dissertations from postgraduate degrees (master’s and doctorates)
• ‘Conference’–presentations, abstracts, posters and proceedings from conferences, workshops, meetings, congresses, symposia and colloquia
• ‘Other’–all other literature that may or may not be peer-reviewed, including; reports, working papers, self-published books, etc.
• ‘Unclear’–any search record that could not be categorised according to the above classification (ambiguous citations were discussed by the reviewers and classed as ‘unclear’ if no consensus could be reached due to limited information).

Book chapters are a subcategory of books but have been separated for additional clarity. These categories have been chosen because they reflect the type of information returned by Web of Science (‘black’ literature) and Google Scholar (all literature). The categories also reflect the emergent classifications that were possible based on information in the citations and any associated descriptions.

For each search type (title or full text) the proportion of literature types across the search results was summarised per page of results to assess the relative location of the types within the results.

2. How much overlap is there between Google Scholar and Web of Science?

For each of the 7 systematic review case studies title and full text searches were performed in Google Scholar and Web of Science (25/01/2015) and citation records extracted (all records for Web of Science or the first 1,000 for Google Scholar). Full text search results were not extracted for SR4 since over 47,000 records were returned, which was deemed too expansive for this assessment. The search results were then compared using the fuzzy duplicate identification add-in for Excel described below to investigate the degree of overlap between Web of Science and the first 1,000 Google Scholar search results.

3. What proportion of Google Scholar and Web of Science search results are duplicates and what causes this duplication?

Duplicate records are multiple citations that refer to the same article. They are disadvantageous in search results since they do not represent truly unique records and require time and resources for processing. Duplicates also lead to a false estimation of the size of search results: depending on the level of duplication there may be a significant deviation from the true size of search results. The fourteen databases from the 7 case study systematic reviews described above were screened for Google Scholar duplicates using the Excel Fuzzy Duplicate Finder add-in ( https://www.ablebits.com/excel-find-similar/ ) set to find up to 10 character differences between record titles. Potential duplicates were then manually assessed and reasons for duplication (e.g. spelling mistakes or grammatical differences) were recorded.

Searches were performed using Web of Science (using Bangor University’s subscription consisting of Biological Abstracts, MEDLINE, SciELO, Web of Science Core Collections and Zoological Record) using the same 7 search strings used with the above case studies in Google Scholar for topic words. The first 1,000 search results were extracted and assessed for duplicates on title using the Fuzzy Duplicate Finder as described above. Search results were extracted for records ordered both by relevance and by publication date (newest first), with the exception of SR2, SR5 and SR7, where totals of 230, 1,058 and 1,071 records respectively (all returned) were obtained and extracted in full.

4. Are articles included in previous environmental systematic reviews identifiable using Google Scholar?

In order to examine the coverage of Google Scholar in relation to studies included in environmental management systematic reviews, the lists of included articles following full text assessment were extracted from six reviews (four SRs described in Table 2 ; SR1, SR4, SR5, SR6 and two additional reviews; [ 8 , 31 ]) and each record’s title was searched for using Google Scholar. The option in Google Scholar to include citations was selected. Where titles were not found immediately, quotation marks were used, followed by partial removal of the title where possible typographical errors or punctuation variations might cause a record not to be found. Where records were identified as citations (i.e. Google Scholar found a reference within the reference list of another article) this was also recorded. In addition, references from the final lists of included article for three systematic reviews (SR1, SR4, SR6) were searched for in Web of Science as described for Google Scholar, above.

5. Is Google Scholar an effective means of finding grey literature identified from hand searches of organisational websites?

For another systematic review search string (SR5, Table 2 ) the 84 articles that were identified during searches for grey literature in the published review [ 28 ] from 16 organisational web sites (see S1 Table ) were used to test the ability of Google Scholar to find relevant grey literature using a single search string. The 84 articles were checked against the exported search results for both title and full text searches in Google Scholar (see Methods Section 1 above). The 84 articles were then screened in Google Scholar individually to assess whether they were included in the search engine’s coverage.

1. What proportion of Google Scholar search results is grey literature

Between 8 and 39% of full text search results from Google Scholar were classed as grey literature (mean ± SD: 19% ± 11), and between 8 and 64% of title search results (40% ± 17). Fig 1 displays search results by grey literature category, showing a greater percentage of grey literature than academic literature in title search results (43.0%) than full text results (18.9%). Conference proceedings, theses and “other” grey literature (i.e. reports and white-papers) accounted for the increase in the proportion of grey literature in title searches relative to full text searches. Theses formed a particularly small proportion of the full text search results across all case studies (1.3%), but formed a larger proportion of title search results (6.4%). Similarly, conference proceedings were less common in full text search results (3.2%) than title search results (15.3%). The proportion of patents, book chapters and books was similar in full text and title searches (0.2 and 0.3; 1.7 and 2.5; 4.2 and 2.8% respectively).

https://doi.org/10.1371/journal.pone.0138237.g001

When examining the location of literature categories across search results (see S1 Fig ) several patterns emerge. “Peak” grey literature content (i.e. the point at which the volume of grey literature per page of search results was at its highest and where the bulk of grey literature is found) occurred on average at page 80 (±15 (SD)) for full text results, whilst it occurred at page 35 (± 25 (SD)) for title results. Before these points in the search results grey literature content was low in relative terms. For the majority of the case studies it was not until page 20 to 30 that grey literature formed a majority of each page of search results.

Google Scholar demonstrated modest overlap with Web of Science title searches: this overlap ranged from 10 to 67% of the total results in Web of Science ( Table 3 ). The overlap was highly variable between subjects, with reviews on marine protected area efficacy and terrestrial protected area socioeconomic impacts demonstrating the lowest overlap (17.1 and 10.3% respectively). Two case study title searches returned more than the viewable limit of 1,000 search results in Google Scholar (SR1 and SR4) and so only the first 1,000 could be extracted.

See Table 2 for case study explanations.

https://doi.org/10.1371/journal.pone.0138237.t003

Full text search results from Google Scholar demonstrated low overlap with Web of Science results ( Table 4 ), ranging from 0.2 to 19.8% of the total Web of Science results.

n/a corresponds to search results that were too voluminous to download in full. See Table 2 for case study explanations.

https://doi.org/10.1371/journal.pone.0138237.t004

3. What proportion of Google Scholar and Web of Science search results are duplicates and how do these duplicates come about?

Duplication rates (i.e. the percentage of total results that are duplicate records) for Google Scholar and Web of Science are shown in Table 5 and range from 0.00 to 2.93%. Rates of duplication are substantially higher within Google Scholar than Web of Science, and rates are far higher in title searches within Google Scholar than full text searches ( Table 6 ), although this is quite variable between the 7 case studies (1.0 to 4.8%%).

Numbers in parentheses correspond to the standard deviations of the individual case study duplication rates. Sample size refers to the number of search records in total, followed by the number of independent search strings (i.e. the number of case studies investigated).

https://doi.org/10.1371/journal.pone.0138237.t005

Duplication rates are assessed for up to 1,000 search records (or the total number where less than c. 1,300). For Web of Science the full text results were ordered by publication date (newest first) and relevance where more than 1,000 results were returned. Numbers are duplication rate (%) followed by total search records in parentheses.

https://doi.org/10.1371/journal.pone.0138237.t006

Duplicates appear to have arisen for a range of reasons. First, typographical errors introduced by manual transcription were found in both Google Scholar (15% of title records) and Web of Science. For example, the sole example of a duplicate from Web of Science is that of the two records that differ only in the spelling of the word ‘Goukamma’ (or Goukarmma) in the following title: “A change of the seaward boundary of Goukamma Marine Protected Area could increase conservation and fishery benefits”. Differences in formatting and punctuation are a subset of typographical errors and corresponded to 18% of title level duplicates. Second, capitalisation causes duplication in Google Scholar, and was responsible for 36% of title level duplicates. Third, incomplete titles (i.e. some missing words) were responsible for 15% of title level duplicates. Fourth, automated text detection (i.e. when scanning documents digitally) was responsible for 3% of title level duplicates. Fifth, Google Scholar also scans for citations within references of selected included literature, and the presence of both these citations and the original articles themselves was responsible for 13% of title level duplication.

Many of the included articles from the six published systematic review case studies were identified when searching for those articles specifically in Google Scholar ( Table 7 ). However, a significant proportion of studies in one review [ 31 ] were not found at all using Google Scholar (31.5%). Other reviews were better represented by Google Scholar coverage (94.3 to 100% of studies). Only one review had an included article list that was fully covered by Google Scholar, the review with the smallest evidence base of only 37 studies [ 31 ]. For those reviews where studies were not identified by Google Scholar, a further search was performed for these missing studies in Web of Science ( Table 7 ), which demonstrated that some of these studies (6 studies from 2 case study reviews) were catalogued by Web of Science.

Records identified as citations are found only within reference lists of other articles (their existence is not verified by the presence of a publisher version or full text article, unlike hyperlinked citations).

https://doi.org/10.1371/journal.pone.0138237.t007

Google Scholar search results that were available only as citations (i.e. obtained from the reference lists of other search results) constituted between 0 and 15.2% of identified results. Citations typically do not lead to web pages that provide additional information and cannot therefore be verified manually by users.

When searching specifically for individual articles, Google Scholar catalogued a larger proportion of articles than Web of Science (% of total in Google Scholar / % of total in Web of Science: SR1, 98.3/96.7; SR4, 94.3/83.9; SR6, 99.4/89.7).

None of the 84 grey literature articles identified by SR5 [ 28 ] were found within the exported Google Scholar search results (68 total records from title searches and 1,000 of a total 49,700 records from full text searches). However, when searched for specifically 61 of the 84 articles were identified by Google Scholar.

This paper set out to investigate the role of Google Scholar in searches for academic and grey literature in systematic and other literature reviews. There is much interest in Google Scholar due to its free-to-use interface, apparent comprehensiveness e.g. [ 11 , 12 , 13 , 14 ], and application within systematic reviews [ 16 ]. However, previous studies have disagreed on whether the service could be used as a standalone resource e.g. [ 11 , 12 ]. Our study enables recommendations to be made for the use of Google Scholar in systematic searches for academic and grey literature, particularly in systematic reviews.

Our results show that Google Scholar is indeed a useful platform for searching for environmental science grey literature that would benefit researchers such as systematic reviewers, agreeing with previous research in medicine [ 32 , 33 ]. Our investigations also demonstrate that more grey literature is returned in title searches than full text searches (43% relative to 19%, respectively), slightly more than previously found in an investigation of full text searching alone in an early version of Google Scholar (13% of total results; [ 17 ]). The grey literature returned by Google Scholar may be seen by some as disadvantageous given its perceived lack of verification (through formal academic peer-review), particularly where researchers are looking for purely traditional academic evidence. However, this may be particularly useful for those seeking evidence from across academic and grey literature domains; for example, those wishing to minimise the risk of publication bias (the over-representation of significant research in academic publications [ 34 ]).

We found that the greatest volume of grey literature in searches occurs at around page 35 for title searches. This finding indicates that researchers, including systematic reviewers, using Google Scholar as a source of grey literature should revise the current common practice of searching the first 50–100 results (5–10 pages) in favour of a more extensive search that looks further into the records returned. Conversely, those wishing to use title searching for purely academic literature should focus on the first 300 results to reduce the proportion of grey literature in their search results.

The grey literature returned in the 7 systematic review case studies examined herein mostly consisted of “other” grey literature and conference proceedings; i.e. white papers and organisational reports. Reports and white papers may prove particularly useful for secondary syntheses, since they may often represent resources that are commissioned by policy and practice decision-makers. Conference proceedings typically represent academic works that have not been formally published in commercial academic journals: such articles may also provide useful evidence for reviewers, particularly systematic reviewers. Academic theses were more common in title searches in Google Scholar, whilst books were more common in full text searches. Theses can provide a vital source of grey literature [ 35 ], research that never makes it into the public domain through academic publications. It is worth noting that whilst academic peer-review is not a guarantee of rigour, research that has not been through formal academic peer-review should be carefully appraised before being integrated into syntheses such as systematic reviews [ 5 ]. Google Scholar may thus prove to be a useful resource in addition to dedicated databases of theses (e.g. DART-Europe; http://www.dart-europe.eu/basic-search.php ) and other grey literature repositories (e.g. ProceedingsFirst; https://www.oclc.org/support/services/firstsearch/documentation/dbdetails/details/Proceeding.en.html ).

Surprisingly, we found relatively little overlap between Google Scholar and Web of Science (10–67% of WoS results were returned using searches in Google Scholar using title searches). For the largest set of results (SR4) only 17% of WoS records were returned in the viewable results in Google Scholar (restricted to the first 1,000 records). However, the actual number of returned results in Google Scholar was 4,310, with only the first 1,000 being viewable due to the limitations of Google Scholar. Assuming an even distribution of overlapping studies across these results we might expect a modest 73% coverage in total (calculated by applying a consistent rate of 17% from the first 1,000 to the full set of 4,310 search records). The limitations of viewable results in Google Scholar make an assessment of overlap impossible when the number of results is greater than 1,000. The case study SR1 only slightly exceeded the viewable limit of 1,000 studies and identified an overlap of 38%, however.

The relatively low overlap between the two services demonstrates that Google Scholar is not a suitable replacement for traditional academic searches: although its results are greater than those in Web of Science, the majority of Web of Science search results are not returned by Google Scholar. However, Google Scholar is a useful addition to traditional database searching, since a large body of search records was returned for each case study that did not overlap, potentially increasing the coverage of any multi-database search, such as those carried out in systematic reviews.

Duplicates within citation databases are disadvantageous because they represent false records. Although the individual reference may be correct, its presence in the database contributes to the number of results. Where large numbers of references must be screened manually, as in systematic reviews, duplicates may also represent a waste of resources where they are not automatically detectable. Duplication rates in Web of Science were very low (0–0.05%), but notably higher in Google Scholar (1–5%). Duplication in Google Scholar occurred as a result of differences in formatting, punctuation, capitalisation, incomplete records, and mistakes during automated scanning and population of the search records. The sensitivity of Google Scholar searches comes at a cost, since identical records are identified as unique references. This may not be a significant problem for small-scale searches, but a 5% duplication rate represents a substantial waste of resources in a systematic review where tens of thousands of titles must be screened manually.

Gehano et al. [ 13 ] found that Google Scholar was able to identify all 738 articles from across 29 systematic reviews in medicine, and concluded that it could be used as a standalone resource in systematic reviews, stating that “if the authors of the 29 systematic reviews had used only GS, no reference would have been missed”. As pointed out by other researchers e.g. [ 14 ], this conclusion is incorrect, since the ability to find specific, known references does not equate to an ability to return these references using a search strategy as might be conducted within a systematic review: most importantly, the relevant articles may be returned outside of the viewable 1,000 records. Giustini and Boulos [ 14 ] found that 5% of studies from a systematic review could not be identified using specific searches in Google Scholar, whilst Boeker et al. [ 11 ] found that up to 34% of studies from 14 systematic reviews were missed.

Google Scholar was able to find much of the existing literature included within the systematic review case studies in our investigations, and indeed found more than Web of Science in the three case studies examined. As such, Google Scholar provides a powerful tool for identifying articles that are already known to exist (for example, when looking for a citation or access to a full text document). In addition, the search engine was also able to identify large amounts of potentially relevant grey literature. However, some important evidence was not identified at all by Google Scholar (31.5% in one case study), meaning that the review may have come to a very different conclusion if it had relied solely on Google Scholar. Similarly, Web of Science alone is insufficient to identify all relevant literature. As described above, Google Scholar may provide a useful source of evidence in addition to traditional academic databases, but it should not be used as a standalone resource in evidence-gathering exercises such as systematic reviews.

Google Scholar was able to identify a large proportion of the grey literature found in one case study through hand searching of organisational websites (61 of 84 articles). However, 23 articles could not be found using the search engine. Furthermore, the 61 articles found were not returned when using a typical systematic review-style search string. Together, these factors demonstrate that Google Scholar is a useful resource in addition to hand searching of organisational websites, returning a large volume of potentially relevant information, but that it should not be used as a standalone resource for grey literature searching, since some vital information is missed. Hand searching, as recommended by the Collaboration for Environmental Evidence Guidelines in Systematic Reviews [ 5 ], is restricted only to those websites included in an a priori protocol. Google Scholar exhaustively searches the internet for studies, however, and whilst it may be more coarse than fine-level hand searching (i.e. missing studies), the addition of a Google Scholar search targeting grey literature would increase comprehensiveness without giving cause for concern with relation to any systematic bias. However, since the algorithms that order search results are not disclosed, a substantial proportion of search results should be examined.

Other Considerations

As mentioned above, only the first 1,000 search results can be viewed in Google Scholar, and the order in which results are returned is not disclosed. Furthermore, the ‘advanced’ search facility supports only very basic Boolean logic, accepting only one set of ‘OR’ or ‘AND’ arguments, not both. In addition, variations in the way that subscript and superscript text, for example with chemical symbols, are displayed and recognised mean that poor matching occurs during searches where these characters form part of article titles. Finally, Google Scholar has a low threshold for repetitive activity that triggers an automated block to a user’s IP address (in our experience the export of approximately 180 citations or 180 individual searches). Thankfully this can be readily circumvented with the use of IP-mirroring software such as Hola ( https://hola.org/ ), although care should be taken when systematically accessing Google Scholar to ensure the terms of use are not violated.

Conclusions

We have provided evidence that Google Scholar is a powerful tool for finding specific literature, but that it cannot be a replacement for traditional academic citation databases, nor can it replace hand-searching for grey literature. The limitations of the number of search results displayed, the incomplete Boolean operation of the advanced search facility, and the non-disclosure of the algorithm by which search results are ordered mean that Google Scholar is not a transparent search facility. Moreover, the high proportion of grey literature that is missed by Google Scholar mean that it is not a viable alternative to hand searching for grey literature as a stand-alone tool. Despite this, Google Scholar is able to identify a large body of additional grey literature in excess of that found by either traditional academic citation databases or grey literature identification methods. These factors make Google Scholar an attractive supplement to hand searching, further increasing comprehensiveness of searches for evidence.

We also note that the development of tools to take snapshots of search results from Google Scholar and extract these results as citations can significantly increase the efficiency and transparency of using Google Scholar (i.e. beyond the arbitrary first 50 search results currently favoured in many systematic reviews).

Several recommendations can be made based on our findings for those wishing to use Google Scholar as a resource for research evidence:

• 1. Finding : Google Scholar is capable of identifying the majority of evidence in the systematic review case studies examined when searching specifically for known articles.
• Recommendation : Google Scholar is a powerful, free-to-use tool that can be recommended if looking for specific research studies.
• 2. Finding : Google Scholar is not capable of identifying all relevant evidence identified in the systematic review case studies examined, missing some vital information (as did Web of Science).
• Recommendation : Google Scholar (and Web of Science) should not be used as standalone resources for finding evidence as part of comprehensive searching activities, such as systematic reviews.
• 3. Finding: Substantially more grey literature is found using title searches in Google Scholar than full text searches.
• Recommendation: If looking for grey literature, reviewers should consider using title searches. If looking for academic literature title searches will yield a great deal of unsuitable information.
• 4. Finding: Title level searches yield more conference proceedings, theses and ‘other’ grey literature.
• Recommendation: Title level searches may be particularly useful in identifying as yet unpublished academic research grey literature as well as organisational reports and government papers [ 9 ]
• 5. Finding: The majority of grey literature begins to appear after approximately 20 to 30 pages of results.
• Recommendation: If looking for grey literature the results should be screened well beyond the 20 th page.

In summary, we find Google Scholar to be a useful supplement in searches for evidence, particularly grey literature so long as its limitations are recognised. We recommend that the arbitrary assessment of the first 50 search results from Google Scholar, frequently undertaken in systematic reviews, should be replaced with the practice of recording snapshots of all viewable search results: i.e. the first 1,000 records. This change in practice could significantly improve both the transparency and coverage of systematic reviews, especially with respect to their grey literature components.

Supporting Information

S1 fig. google scholar search results separated by literature type..

Search results by page for 7 case studies (see Table 2 for descriptions), for a) full text and b) title searches. Results displayed are for the total number of extractable records in Google Scholar.

https://doi.org/10.1371/journal.pone.0138237.s001

S1 File. Google Scholar Search Results.

Database of Google Scholar full text and title searches for 7 case study systematic reviews.

https://doi.org/10.1371/journal.pone.0138237.s002

S1 Table. Organisational websites list for SR5.

List of organisations yielding potentially relevant evidence for a systematic review on the human wellbeing impacts of terrestrial protected areas.

https://doi.org/10.1371/journal.pone.0138237.s003

Acknowledgments

The authors wish to thank Helen Bayliss and Beth Hall for discussion of the topic. AMC acknowledges a Policy Placement Fellowship funded by the Natural Environment Research Council, the UK Department for Environment Food and Rural Affairs and the Environment Agency. Some ideas for this project were prompted by a forthcoming Defra research project (WT1552).

Author Contributions

Conceived and designed the experiments: NH. Performed the experiments: NH AC. Analyzed the data: NH. Contributed reagents/materials/analysis tools: NH. Wrote the paper: NH AC DC SK.

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