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Literature Review Generator

Welcome to Jenni AI, the ultimate tool for researchers and students. Our AI Literature Review Generator is designed to assist you in creating comprehensive, high-quality literature reviews, enhancing your academic and research endeavors. Say goodbye to writer's block and hello to seamless, efficient literature review creation.

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Define Your Research Scope

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Frequently asked questions

What exactly does jenni ai do, is jenni ai suitable for all academic disciplines, is there a trial period or a free version available.

How does Jenni AI help with writer's block?

Can Jenni AI write my literature review for me?

How often is the literature database updated in Jenni AI?

How user-friendly is Jenni AI for those not familiar with AI tools?

Jenni AI: Standing Out From the Competition

In a sea of online proofreaders, Jenni AI stands out. Here’s how we compare to other tools on the market:

Feature Featire

COMPETITORS

Advanced AI-Powered Assistance

Uses state-of-the-art AI technology to provide relevant literature suggestions and structural guidance.

May rely on simpler algorithms, resulting in less dynamic or comprehensive support.

User-Friendly Interface

Designed for ease of use, making it accessible for users with varying levels of tech proficiency.

Interfaces can be complex or less intuitive, posing a challenge for some users.

Transparent and Flexible Pricing

Offers a free trial and clear, flexible pricing plans suitable for different needs.

Pricing structures can be opaque or inflexible, with fewer user options.

Unparalleled Customization

Offers highly personalized suggestions and adapts to your specific research needs over time.

Often provide generic suggestions that may not align closely with individual research topics.

Comprehensive Literature Access

Provides access to a vast and up-to-date range of academic literature, ensuring comprehensive research coverage.

Some may have limited access to current or diverse research materials, restricting the scope of literature reviews.

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LITERATURE REVIEW SOFTWARE FOR BETTER RESEARCH

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

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Austin Health, Australia

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

Ritwik Pandey

Doctoral Research Scholar – Sri Sathya Sai Institute of Higher Learning

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

David Fischer

Research Associate – University of Applied Sciences Kempten

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

Christoph Ludwig

Technische Universität Dresden, Germany

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

Aran Warren

Canterbury University, NZ

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

Professor at The Chinese University of Hong Kong

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

Katholieke Universiteit Leuven, Belgium

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

KU Leuven, Belgium

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

Franklin Jeffers

South Oregon University, USA

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

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

Ali Mohammed-Djafari

Director of Research at LSS-CNRS, France

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

Daniel Fuller

Clarkson University, USA

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

Baylor Fain

Postdoctoral Associate – University of Florida

Literature Review Generator by AcademicHelp

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Features of Our Literature Review Generator

Advanced power of AI

Advanced power of AI

Simplified information gathering

Simplified information gathering

Enhanced quality

Enhanced quality

Rrl generator – your friend in academic writing.

Literature reviews can be tricky. They require your full attention and dedication, leaving no place for distractions. And with so many assignments on your hands, it must be very hard to concentrate just on this one thing.

No need to worry though. With our RRL AI Generator creating any type of paper that requires scrupulous literature will be as easy as it gets.

How to Work With Literature Review Generator

We designed our platform in a way that wouldn’t require you to spend much time figuring out how to work with it. What you have to do is just specify your topic, the subject of your literature review, and any further instructions on the style, formatting, and structure. After that you enter the number of pages you need to be written and, if there’s a requirement for that, formatting style. Wait for around 2 minutes and that’s all – our AI will give you the paper crafted according to your specifications.

What Makes AI Literature Review Generator Special

You are probably wondering how our AI bot is better than basically any other AI-powered solution you can find online. Well, we won’t say that our tool is a magical service that can do everything better. To be fair, as any AI it is not yet ideal. Still, our platform is more tailored to academic writing than most of the other bots. With its help, you can not just simply produce text, but also receive a paper with sources and properly organized formatting. This makes it a perfect match for those who specifically need help with tough papers, such as literature reviews, research abstracts, and analysis essays.

Why Use the Free Online Literature Review Generator 

With our Free Online Literature Review you will be able to finish your literature review assignments in just a few minutes. This will allow you to dedicate your free time to a) proofreading, and b) finishing or starting on more important tasks and projects. This tool can also help you understand the direction of your work, its structure, and possible sources you can use. In general, it is a more efficient way of doing your homework and organizing the writing process that can help you get better grades and improve your writing skills.

Free Literature Review Generator

literature review maker

Is there a free AI tool for literature review?

Yes, of course, some tools will help you with your literature review. One of the great solutions is the AcademicHelp Literature Review Generator. It offers a quick and simple work process, where you can specify all the requirements for your paper, and then receive a fully completed task in just 2 minutes. It is a specially fitting service for those looking for a budget-friendly tool.

How to create a literature review?

Crafting a literature review calls for a systematic approach to examining existing scholarly work on a specific topic. Thus, start by defining a clear research question or thesis statement to guide your focus. Conduct a thorough search of relevant databases and academic journals to gather sources that address your topic. Read and analyze these sources, noting key themes, methodologies, and conclusions. Organize the literature by themes or methods, and synthesize the findings to provide a critical overview of the existing research. Your review should give context to the research within the field, noting areas of consensus, debate, and gaps in knowledge. Finally, write your literature review, integrating your analysis with your thesis statement, providing a clear and structured narrative that offers insights into the research topic.

Can I write a literature review in 5 days?

It is possible to write a literature review in 5 days, but you will need careful planning and dedication. Start by quickly defining your topic and research question. Dedicate a day to intensive research, finding and selecting relevant sources. Spend the next two days reading and summarizing these sources. On the fourth day, organize your notes and outline the review, focusing on arranging the main findings around key themes. Use the final day to write and revise your literature review, so that it is logically structured.

What are the 5 rules for writing a literature review?

When writing a literature review, you initially need to follow these essential rules: First, maintain a clear focus and structure. Your review should be organized around your thesis statement or key question, with each section logically leading to the next. Second, be critical and analytical rather than merely descriptive. Discuss the strengths and weaknesses of the research, the methodologies used, and the conclusions drawn. Third, include credible and versatile sources to represent a balanced view of the topic. Fourth, synthesize the information from your sources to create a narrative that adds value to your field of study. Finally, your writing should be clear, concise, and plagiarism-free, with all the sources appropriately cited.

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  • 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 Review with MAXQDA

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

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

Literature Review with MAXQDA - User interface

How to conduct a literature review with MAXQDA

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

Step one: Plan your literature review

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

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

literature review maker

Step two: Search, Select, Save your material

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

Search, select, save your literature

Step three: Import & Organize your material in MAXQDA

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

Import and organize your literature

Analyze your literature with MAXQDA

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

Use the power of AI for your analysis

AI Assist: Introducing AI to literature reviews

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

AI for Literature Review

Code & Retrieve important segments

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

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

Code name suggestions and quick resize

Paraphrase literature into your own words

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

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

Summaries & Overview tables: A look at the Bigger Picture

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

Summarize content with MAXQDA for your literature review

Visualize your qualitative data

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

QTT: Synthesize your results and write up the review

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

Collect relevant insights and develop new theories with MAXQDA

Literature about Literature Reviews and Analysis

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

Getting started with MAXQDA

Getting Started with MAXQDA

Literature Review Guide

Literature Reviews with MAXQDA

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

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

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

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

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

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

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

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

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literature review maker

7 open source tools to make literature reviews easy

Open source, library schools, libraries, and digital dissemination

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

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

1. GNU Linux

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

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

3. Unpaywall

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

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

5. LibreOffice

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

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

7. MediaWiki

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

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

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

Wrapping up

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

Joshua Pearce

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Silvi is an end-to-end screening and data extraction tool supporting Systematic Literature Review and Meta-analysis.

Silvi helps create systematic literature reviews and meta-analyses that follow Cochrane guidelines in a highly reduced time frame, giving a fast and easy overview. It supports the user through the full process, from literature search to data analyses. Silvi is directly connected with databases such as PubMed and ClinicalTrials.gov and is always updated with the latest published research. It also supports RIS files, making it possible to upload a search string from your favorite search engine (i.e., Ovid). Silvi has a tagging system that can be tailored to any project.

Silvi is transparent, meaning it documents and stores the choices (and the reasons behind them) the user makes. Whether publishing the results from the project in a journal, sending them to an authority, or collaborating on the project with several colleagues, transparency is optimal to create robust evidence.

Silvi is developed with the user experience in mind. The design is intuitive and easily available to new users. There is no need to become a super-user. However, if any questions should arise anyway, we have a series of super short, instructional videos to get back on track.

To see Silvi in use, watch our short introduction video.

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Silvi.ai was founded in 2018 by Professor in Health Economic Evidence, Tove Holm-Larsen, and expert in Machine Learning, Rasmus Hvingelby. The idea for Silvi stemmed from their own research, and the need to conduct systematic literature reviews and meta-analyses faster.

The ideas behind Silvi were originally a component of a larger project. In 2016, Tove founded the group “Evidensbaseret Medicin 2.0” in collaboration with researchers from Ghent University, Technical University of Denmark, University of Copenhagen, and other experts. EBM 2.0  wanted to optimize evidence-based medicine to its highest potential using Big Data and Artificial Intelligence, but needed a highly skilled person within AI.

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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.

Free Webinar: Literature Review 101

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.

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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).

Excel literature review template

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.

Mind mapping is a useful way to plan your literature review.

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.

start writing

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.

Literature Review Course

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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How To Find a Research Gap (Fast)

38 Comments

Phindile Mpetshwa

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

Yinka

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!

Derek Jansen

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

Renee Buerger

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 🙂

Sheemal Prasad

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

Thank you Gradcoach.

Tahir

Really agreed. Admirable effort

Faturoti Toyin

thank you for this beautiful well explained recap.

Tara

Thank you so much for your guide of video and other instructions for the dissertation writing.

It is instrumental. It encouraged me to write a dissertation now.

Lorraine Hall

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

araz agha

an amazing and very constructive way of presetting a topic, very useful, thanks for the effort,

Suilabayuh Ngah

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.

Nancy Geregl

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

Uzma

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

Xaysukith thorxaitou

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

Sheila Jerome

This is super helpful thank you very much.

Mary

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

Maithe

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 🙂

Anthony

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

Eunice

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

Stephanie Louw

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

Thanks, Stephanie 🙂

oghenekaro Silas

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!

tarandeep singh

This is very good video which is well explained with detailed explanation

uku igeny

Thank you excellent piece of work and great mentoring

Abdul Ahmad Zazay

Thanks, it was useful

Maserialong Dlamini

Thank you very much. the video and the information were very helpful.

Suleiman Abubakar

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

Mthuthuzeli Vongo

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

SEID YIMAM MOHAMMED (Technic)

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.

Richie Buffalo

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

Adekoya Opeyemi Jonathan

Very timely.

I appreciate.

Norasyidah Mohd Yusoff

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

Maryellen Elizabeth Hart

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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  • Literature review tool

The following tool will help you learn how to conduct a solid review of literature. To do so, you will have to answer the questions posed in the form you will find on the lower left side, while checking the resources provided on the right side.

Positionality is the notion that identity , paradigmatic views , and location in time and space influence how one understands the world. Consequently, it is essential to take into account positionality before engaging in research, including research synthesis. Learn more about identity, approaches or paradigmatic views such as positivism, interpretivism, constructivism, and others here

The second step in the generation of the literature review design is setting purposes and objectives that will drive the review process.  Your searching strategies, the literature analysis, and even a review structure depend on the purposes of a review, the same way as the goals and research questions in a research study shape its design. Learn more about the purposes and objectives of a traditional literature "nested" in a research study and a research synthesis.

There are key things to think about before you start searching for literature or conduct research synthesis.  You should define and narrow your topic. Since each disciplinary domain has its own thesaurus, index, and databases,  contemplate in which disciplines or areas of study your research synthesis will be conducted. Formulate the initial research question that you will develop further during the search for the literature and the design step. Learn more here.

The conceptual & theoretical framework of your study is the system of concepts, assumptions, expectations, beliefs, and theories that supports and informs your research. It is a formulation of what you think is going on with what you are studying—a tentative theory of what is happening and why. Read more about "concepts" and how to search for and clarify them, how to find a relevant theory,   here .

Secondary data analysis and review of literature involve collecting and analyzing a vast array of information and sources.  To help you stay focused, your first step should be to develop a research design or a step-by-step plan or a protocol that guides data collection and analysis. Get familiar with different types if the research designs on this page .

As with any research study, the basic purpose of data collection is to create a systematically organized set of materials that will be analyzed or interpreted. Any type of reviews, not only a systematic review,  benefit from applying relatively systematic methods of searching and collecting secondary data. In this part of the guide , I describe sampling methods, instruments (or searching techniques), and organization of sources.

The seventh step regards the selection and definition of the data analysis strategies that will be used in your study, depending on the research approach followed. You can find here resources that might be of help to better understand the way data analysis work. 

After analyzing studies or literature in a depth and the systematic way one should move to the iterative process of exploring, commonalities and contradictions across relevant studies, emergent themes in order to build a theory, frame future research, or creating a final integrated presentation of finding. Find out more here.

Ethical considerations of conducting literature reviews and the issues of quality are not widely discussed in the literature. Consult t his guide where you will find references to work on ethics of conducting systematic reviews, checklists for quality of meta-analysis and research synthesis.

literature review maker

The following AI tools can assist you in step 9 of the process of generating your design:

Google Bard can be used to identify potential ethical principles a researcher could define to ethically conduct a given study.

For instance, we could use the following prompt: What principles could a researcher define to ethically conduct a qualitative case study regarding the long-term impact of competency-based assessment on secondary education students in a secondary school in Marietta (Georgia)?

literature review maker

The following AI tools can assist you in step 8 of the process of generating your design:

Google Bard can be used to identify potential strategies we could implement as researchers to ensure the trustworthiness/validity of a given study.

For instance, we could use the following prompt: What strategies could a researcher use to ensure the trustworthiness qualitative case study regarding the long-term impact of competency-based assessment on secondary education students in a secondary school in Marietta (Georgia).

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The following AI tools can assist you in step 7 of the process of generating your design:

AI data analysis is on the rise. For instance,  the AI module of Atlas.ti can be used to analyze qualitative data.

The following AI tools can assist you in step 5 of the process of generating your design:

Consensus could be used to identify research questions that have been used in previously published studies. Consensus is an AI-powered search engine designed to take in research questions, find relevant insights within research papers, and synthesize the results using large language models. It is not a chatbot. Consensus only searches through peer-reviewed scientific research articles to find the most credible insights to your queries.

AI: Google Bard could be used to identify potential questions for a particular research tradition or design.

For instance, we could use the following prompt: Generate examples of research questions that could be used to drive a qualitative case study regarding the long-term impact of competency-based assessment on secondary education students in a secondary school in Marietta (Georgia).

The following AI tools can assist you in step 4 of the process of generating your design:

Google Bard could be used to help users of Hopscotch understand the differences between research traditions for a certain topic.

For instance, we could use the following prompt:   Generate a brief description of the key elements of a qualitative case study research design regarding the long-term impact of competency-based assessment on secondary education students in a secondary school in Marietta (Georgia). To do this, use the following nine steps proposed by the Hopscotch Model:

Step 1: Paradigmatic View of the Researcher

Step 2: Topics & Goals of the Study

Step 3: Conceptual framework of the study

Step 4: Research Design/tradition

Step 5: Research Questions

Step 6: Data Gathering Methods

Step 7: Data Analysis

Step 8: Trustworthiness/Validity

Step 9: Ethics driving the study

The following AI tools can assist you in step 3 of the process of generating your design:

AI: ResearchRabbit is a scholarly publication discovery tool supported by artificial intelligence (AI). The tool is designed to support your research without you switching between searching modes and databases, a process that is time-consuming and often escalates into further citation mining; a truly unpleasant rabbit hole (and that’s what inspired the name ResearchRabbit)

AI: 2Dsearch  is a radical alternative to conventional ‘advanced search’. Instead of entering Boolean strings into one-dimensional search boxes, queries are formulated by manipulating objects on a two-dimensional canvas. This eliminates syntax errors, makes the query semantics more transparent, and offers new ways to collaborate, share, and optimize search strategies and best practices.

Welcome to ResearchRabbit from ResearchRabbit on Vimeo .

The following AI tools can assist you in step 2 of the process of generating your design:

AI: Consensus could be used to assist users in the identification of relevant topics that have been published in peer-reviewed articles. Consensus is an AI-powered search engine designed to take in research questions, find relevant insights within research papers, and synthesize the results using large language models. It is not a chatbot. Consensus only searches through peer-reviewed scientific research articles to find the most credible insights to your queries.

AI: Carrot2 could be used to identify potential research topics. Carrot2  organizes your search results into topics. With an instant overview of what’s available, you will quickly find what you’re looking for.

The following AI tools can assist you in step 1 of the process of generating your design:

You could use Google Bard , Perplexity , or ChatGPT , to ask for the differences between the key wordlviews that a researcher can bring to a given study.

For instance, we could use the following prompt:   What are the defining characteristics of the main worldviews or paradigmatic positioning (positivistic worldviews, post-positivistic worldview; constructivistic worldview; transformative worldview, and; pragmatic worldview) a researcher can bring to a given study?

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The following AI tools can assist you in step 6 of the process of generating your design:

We could use Google Bard to develop a draft of a data collection protocol for a given study.

For instance, we could use the following prompt: Generate an interview protocol for students involved in a qualitative case study regarding the long-term impact of competency-based assessment on secondary education students in a secondary school in Marietta (Georgia).

literature review maker

You can use the following AI tools to assist you in the process of generating your design:

Step 1: Paradigmatic View of the Researcher 

AI: You could use Google Bard , Perplexity , or ChatGPT , to ask for the differences between the key wordlviews that a researcher can bring to a given study.  

Step 2: Topics & Goals of the Study

AI: Google Bard could be used to help users of Hopscotch understand the differences between research traditions for a certain topic.  

AI: Consensus could be used to identify research questions that have been used in previously published studies. Consensus is an AI-powered search engine designed to take in research questions, find relevant insights within research papers, and synthesize the results using large language models. It is not a chatbot. Consensus only searches through peer-reviewed scientific research articles to find the most credible insights to your queries.

AI: We could use Google Bard to develop a draft of a data collection protocol for a given study.

AI: We could use the AI module of Atlas.ti to analyze qualitative data

AI: Google Bard could be used to identify potential strategies we could implement as researchers to ensure the trustworthiness/validity of a given study.

AI: Google Bard   could be used to identify potential ethical principles a researcher could define to ethically conduct a given study.

Consensus uses AI to find answers in research papers. You can search for previous research in your field of study that might be helpful to better support the relevance of your research topic and the need to conduct the study that you are proposing. The best way to search is to ask a question.

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Research Sources Log

Welcome aboard, how to get started, how to use the template, starting with research sources log, it’s okay if you don’t fill out all of the fields. the more fields filled out, the more accurate the analysis., hint: to view a bigger view of the field. click on the field and click on the “ ⤢ ” icon..

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  • Open access
  • Published: 14 May 2024

Research outcomes informing the selection of public health interventions and strategies to implement them: A cross-sectional survey of Australian policy-maker and practitioner preferences

  • Luke Wolfenden 1 , 2 , 3 ,
  • Alix Hall 1 , 2 , 3 ,
  • Adrian Bauman 1 , 4 , 5 ,
  • Andrew Milat 6 , 7 ,
  • Rebecca Hodder 1 , 2 , 3 ,
  • Emily Webb 1 ,
  • Kaitlin Mooney 1 ,
  • Serene Yoong 1 , 2 , 3 , 8 , 9 ,
  • Rachel Sutherland 1 , 2 , 3 &
  • Sam McCrabb 1 , 2 , 3  

Health Research Policy and Systems volume  22 , Article number:  58 ( 2024 ) Cite this article

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A key role of public health policy-makers and practitioners is to ensure beneficial interventions are implemented effectively enough to yield improvements in public health. The use of evidence to guide public health decision-making to achieve this is recommended. However, few studies have examined the relative value, as reported by policy-makers and practitioners, of different broad research outcomes (that is, measures of cost, acceptability, and effectiveness). To guide the conduct of research and better inform public health policy and practice, this study aimed at describing the research outcomes that Australian policy-makers and practitioners consider important for their decision-making when selecting: (a) public health interventions; (b) strategies to support their implementation; and (c) to assess the differences in research outcome preferences between policy-makers and practitioners.

An online value-weighting survey was conducted with Australian public health policy-makers and practitioners working in the field of non-communicable disease prevention. Participants were presented with a list of research outcomes and were asked to select up to five they considered most critical to their decision-making. They then allocated 100 points across these – allocating more points to outcomes perceived as more important. Outcome lists were derived from a review and consolidation of evaluation and outcome frameworks in the fields of public health knowledge translation and implementation. We used descriptive statistics to report relative preferences overall and for policy-makers and practitioners separately.

Of the 186 participants; 90 primarily identified as policy-makers and 96 as public health prevention practitioners. Overall, research outcomes of effectiveness, equity, feasibility, and sustainability were identified as the four most important outcomes when considering either interventions or strategies to implement them. Scores were similar for most outcomes between policy-makers and practitioners.

For Australian policy-makers and practitioners working in the field of non-communicable disease prevention, outcomes related to effectiveness, equity, feasibility, and sustainability appear particularly important to their decisions about the interventions they select and the strategies they employ to implement them. The findings suggest researchers should seek to meet these information needs and prioritize the inclusion of such outcomes in their research and dissemination activities. The extent to which these outcomes are critical to informing the decision of policy-makers and practitioners working in other jurisdictions or contexts warrants further investigation.

Peer Review reports

Research evidence has a key role in public health policy-making [ 1 ]. Consideration of research is important to maximize the potential impact of investments in health policies and services. Public health policy-makers and practitioners frequently seek out research to inform their professional decision-making [ 2 ]. However, they report that published research is not well aligned with their evidence needs [ 3 , 4 ]. Public health decision-making is a complex and dynamic process where evidence is used in a variety of ways, and for different purposes [ 3 , 5 , 6 ]. Ensuring research meets the evidence needs of public health policy-makers and practitioners is, therefore, an important strategy to improve its use in decision-making [ 7 , 8 , 9 , 10 ].

“Research outcomes” are broad domains or constructs measured to evaluate the impacts of health policies, practices or interventions, such as their effectiveness or acceptability. They are distinct from “outcome measures”, which are the measures selected to assess an outcome. Outcome measures require detailed specification of measurement parameters, including the measurement techniques and instrument, and consideration of the suitability of its properties (for example, validity) given the research question. The inclusion of research outcomes considered most relevant to public health policy-makers and practitioners is one way in which researchers can support evidence-informed decision-making.

Policy-makers are primarily responsible for developing public health policy and selecting and resourcing health programs. Practitioners are primarily responsible for supporting their implementation. As such, public health policy-makers and practitioners require research to: (i) help identify “what works” to guide the selection of interventions that will be beneficial for their community, for example, those that are effective in improving health, and acceptable to the target population and/or (ii) to help identify “how to implement” effective intervention, for example, strategies that are capable of achieving implementation at a level sufficient to accrue benefit, are affordable and reach the targeted population [ 6 , 11 ]. Research that includes outcomes relevant to these responsibilities facilitates evidence-informed decision-making by public health policy-makers and practitioners.

Initiatives such as the World Health Organization INTEGRATe Evidence (WHO INTEGRATE) framework [ 12 ], and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision framework [ 13 ] have been designed to support the selection of public health interventions. Application of these frameworks required the collation and synthesis of a range of scientific evidence including studies employing qualitative and quantitative research designs. Collectively, the frameworks suggest public health policy-makers and practitioners should consider, alongside research outcomes reporting the effectiveness of a public health intervention, other research outcomes such as cost–effectiveness, potential harms and acceptability of an intervention to patients or community.

Several authors have also sought to guide outcomes researchers should include in implementation studies [ 11 ]. Proctor and colleagues defined a range of implementation research outcomes [distinct from service or clinical (intervention) effectiveness outcomes] – including intervention adoption, appropriateness, feasibility, fidelity, cost, penetration and sustainability [ 14 ]. This work helped standardize how the field of implementation science defined, measured and reported implementation outcomes. More recently McKay and colleagues put forward measures of implementation “determinants” and “outcomes” and proposed a “minimum set” of such outcomes to include in implementation and scale-up studies. The implementation research outcomes proposed by both Proctor and McKay and colleagues were developed primarily from the input of researchers to improving the quality and consistency of reporting in implementation science. However, the relative value of these outcomes to the decision-making of public health policy-makers, and in particular practitioners, has largely been unexplored.

While several studies have explored policy-maker and practitioner research evidence preferences, these have focused on a small number of potential outcomes [ 15 , 16 , 17 ]. An appraisal of the potential value, and importance of a comprehensive range of research outcomes to public health policy-maker and practitioner decision-making, therefore, is warranted. In this study, we sought to quantify the relative importance of research outcomes from the perspective of Australian public health policy-makers and practitioners working in the field of non-communicable disease prevention (hereafter referred to as “prevention” policy-makers or practitioners). Specifically, using a value-weighting methodology to elicit relative preferences, the study aimed to describe: (a) research the outcomes prevention policy-makers and practitioners regard as important to their decision-making when selecting a public health intervention to address an identified health issue, (b), research the outcomes prevention policy-makers and practitioners regard as important to their decision-making when selecting a strategy to support the implementation of a public health intervention in the community and (c) assess the differences between prevention policy-makers and practitioners regarding their research outcome preferences.

Design and setting

An online cross-sectional value-weighting survey was conducted with Australian public health prevention policy-makers and practitioners. This study was undertaken as one step of a broader program of work to establish a core outcome set that has been prospectively registered on the Core Outcome Measures in Effectiveness Trials (COMET database; https://www.comet-initiative.org/Studies/Details/1791 ).

Participant eligibility

To be eligible, participants had to self-identify as having worked as a public health prevention policy-maker or practitioner at a government or non-government health organization within the past 5 years. While the term “policy-maker” has been used to describe legislators in US studies, in Australian research it has broadly been used to describe employees of government departments (or non-government agencies) involved in the development of public health policy [ 18 , 19 , 20 , 21 , 22 ]. Policy-makers are not typically involved in the direct implementation of policy or the delivery of health services. We defined a “policy-maker” as a professional who makes decisions, plans and actions that are undertaken to achieve specific public health prevention goals on behalf of a government or non-government organization [ 23 ]. Practitioners are typically employed by government or non-government organizations responsible for prevention service provision, and are directly involved in the implementation or supporting the implementation of public health policies or programs. Specifically, we defined a “practitioner” as a professional engaged in the delivery of public health prevention programs, implementing services or models of care in health and community settings (definition developed by research team). Research and evaluation are a core competency of the public health prevention workforce in Australia [ 24 ], as it is in other countries [ 25 ]. As such, participants may be engaged in research and have published research studies. Researchers, such as those employed by academic institutions only and without an explicit public health policy or practice role in a policy or practice organization, were excluded.

Recruitment

Comprehensive methods were used to recruit individuals through several agencies. First, email invitations were distributed to Australian government health agencies at local (for example, New South Wales Local Health District Population Health units), state (for example, departments or ministries of health) and national levels, as well as to non-government organizations (for example, Cancer Council) and professional societies (for example, Public Health Association Australia). Registered practitioners with the International Union for Health Promotion and Education (IUHPE) from Australia were contacted by public domain emails or on LinkedIn (where identified) with the study invitation. Authors who had published articles of relevant topics from 2018 to 2021 within three Australian public health journals [ Australian and New Zealand Journal of Public Health ( ANZJPH ), Health Promotion Journal of Australia ( HPJA ) and Public Health Research and Practice ( PHRP )] were invited to participate in the study. Invitation emails included links to the information statement for participants and the online survey. The online survey was also promoted on the social media account of a partnering organization [National Centre of Implementation Science (NCOIS)] as well as on Twitter and LinkedIn. From these social media accounts individuals could self-select to participate in the online survey. Reminder emails were sent to non-responders at approximately 2 and 4 weeks following the initial email invitation.

Data collection and measures

The online survey was kept on servers at the Hunter Medical Research Institute, New South Wales, Australia, and deployed using the REDCap software [ 26 ], a secured web-based application for building and managing online surveys and databases. The length of the survey was approximately 20–30 min in duration.

Professional characteristics

Participants completed brief items assessing their professional role (that is, practitioner or policy-maker), the number of years’ experience as policy-makers or practitioners, their professional qualifications and the prevention risk factors (for example, smoking, nutrition, physical activity, injury, sexual health, etc.) for which they had expertise.

Valued intervention and implementation outcomes

We sought to identify outcomes that may be valued by public health policy-makers and practitioners when making decisions about what policies and/or programs of interventions to implement and how implementation could best occur. We separated outcomes on this basis, consistent with recommendations of the evidence policy and practice [ 27 ], the effectiveness–implementation research typology [ 28 , 29 ] and trial conduct and reporting guidelines [ 30 ]. This is illustrated in a broad study logic model (Fig.  1 ).

figure 1

Both effective interventions and effective implementation are required to improve health outcomes

The authors undertook a review of intervention- and implementation-relevant outcome frameworks to determine program and intervention outcomes that may be of interest to policy-makers and practitioners, including the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) Framework [ 31 , 32 ], the Intervention Scalability Assessment Tool (ISAT) [ 18 ] and Proctor and colleagues’ implementation outcome definitions [ 14 ] as well as a series of publications on the topic [ 31 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 ]. This was used to generate a comprehensive inventory of all possible outcomes (and outcome definitions) that may be of interest to public health policy-makers and practitioners. The outcome list was then reduced following grouping of outcomes addressing similar constructs or concepts. A panel of 16 public health policy-makers provided feedback on their perceived importance of each outcome for evidence-informed policy and practice decision-making, as well as the proposed outcome definition. This process occurred over two rounds until no further suggested improvements or clarifications were provided or requested, yielding a final list of 17 outcomes to inform the selection of public health intervention and 16 outcomes for the selection of implementation strategies (Additional file 1 : Table S1). Panel participants also pre-tested the survey instrument; however, they were not invited to participate in the value-weighting study.

Participating public health policy-makers and practitioners completed the value-weighting survey. Value-weighting surveys offer advantages over other methods to identify preferences (such as ranks or mean scores on a rating scale), as they provide an opportunity to quantify the relative preference or value of different dissemination strategies from the perspective of public health policy-makers or practitioners. Specifically, they were only presented with the list of outcomes and their definition, and were asked to select up to 5 of the 17 interventions “that they considered are critical to their decision-making when selecting a public health intervention to address an identified health issue” and 16 implementation outcomes “that they consider to be critical to their decision-making when selecting a strategy to support the implementation of a public health intervention in the community” in a decision-making context. Participants were then asked to value weight, allocating 100 points across their five (or less) intervention and implementation outcomes. A higher allocation of points represented a greater level of perceived importance. In this way, participants weight the allocation of points to outcomes based on preference. No statistical weights are applied in the analysis. Participants were asked to select up to five outcomes as this restriction forced a prioritization of the outcomes among participants. The identification of a small number of critical outcomes, rather than all relevant outcomes, is also recommended to facilitate research outcome harmonization [ 44 , 45 ].

Statistical analysis

All statistical analyses and data management were undertaken in SAS version 9.3. Descriptive statistics were used to describe the study sample. Similar to other value-weighting studies, we used descriptive analyses to identify the intervention and implementation outcomes ranked from highest to lowest importance [ 46 , 47 ]. Items not selected or allocated any points were assumed a score of 0, to reflect that they were not perceived as a high-priority outcome by the participant. Specifically, the mean points allocated to each of the individual outcomes were calculated and ranked in descending order. This was calculated overall for the entire participant sample, as well as separately by policy-makers and practitioners. As points were assigned in free-text fields, in instances where participants allocated more or less than 100 points across the individual items, the points they allocated were standardized to 100. Differences in the points allocated to each individual outcome by policy-maker/practitioner role were explored using Mann–Whitney U test. To examine any differences in the outcome preferences by participant risk factor expertise, we also examined and described outcome preferences among risk factor subgroups (with a combined sample of > 30 participants). These findings are discussed.

A total of 186 eligible participants completed the survey in part or in full.

Of the 186 participants, 90 primarily identified as policy-makers and 96 as public health prevention practitioners (Table  1 ). In all, 37% of participants (47% policy-makers, 27% practitioners) had over 15 years’ experience, and approximately one third (32% policy-makers, 36% practitioners) had a PhD. The most common areas of experience were nutrition and dietetics (38% policy-maker, 53% practitioner), physical activity or sedentary behaviour (46% policy-maker, 44% practitioner), obesity (49% policy-maker, 48% practitioner) and tobacco, alcohol or other drugs (51% policy-maker, 34% practitioner).

Valued outcomes

Intervention outcomes.

A total of 169 participants (83 policy-makers and 86 practitioners, with 7 and 10 missing, respectively) responded to the value-weighting questions for the 17 listed intervention outcomes. Table 2 (Fig.  2 ) reports the mean and standard deviation of points allocated by policy-makers and practitioners for each outcome, ranked in descending order to represent the most to least important. For policy-makers and practitioners combined, the effectiveness of an intervention, and its impact on equity, were clearly identified by participants as the leading two outcomes, with a mean allocation of 24.47 [standard deviation (SD) = 17.43] and 13.44(SD = 12.80), respectively. The mean scores for outcomes of feasibility (9.78) and sustainability (9.04) that ranked third and fourth, respectively, were similar; then scores dropped noticeably to 7.24 for acceptability and 5.81 for economic outcomes.

figure 2

Line graph representing mean points allocated for the 17 intervention outcomes overall and by role

For most outcomes, average scores were similar for policy-makers and practitioners. However, practitioner scores for the outcome of acceptability (mean = 8.95, SD = 9.11), which ranked third most important for practitioners was significantly different than for policy-makers (mean = 5.48, SD = 9.62), where it was ranked seventh ( p  = 0.005). Economics/cost outcomes were ranked fifth by policy-makers (mean = 8.28, SD = 10.63), which significantly differed from practitioners (mean = 3.43, SD = 6.56), where it was ranked ninth ( p  = 0.002). For co-benefits, ranked eighth by policy-makers (mean = 4.37, SD = 7.78), scores were significantly different than for practitioners (mean = 2.27, SD = 6.49), where it was ranked thirteenth ( p  = 0.0215). Rankings for the top five outcomes were identical for those with expertise in nutrition and dietetics, physical activity or sedentary behaviour, obesity and tobacco, alcohol or other drugs (Additional file 1 : Table S2).

Implementation outcomes

A total of 153 participants (75 policy-makers and 78 practitioners, with 15 and 18 missing, respectively) responded to the value-weighting questions for the 16 listed implementation outcomes (Table  3 , Fig.  3 ). The effectiveness of an implementation strategy was clearly identified by participants as the most important intervention outcome, with a mean allocation of 19.82 (SD = 16.85) overall. The mean scores for the next three ranked outcomes namely equity (mean = 10.42, SD = 12.7), feasibility (mean = 10.2, SD = 12.91) and sustainability (mean = 10.08, SD = 10.58) were similar, and thereafter, scores noticeably dropped for measures of adoption (mean = 8.55, SD = 10.90), the fifth-ranked outcome.

figure 3

Line graph representing mean points allocated for the 16 implementation outcomes overall and by role

For most implementation outcomes (Fig.  3 ) policy-makers and practitioners scores were similar. However, economics outcomes were ranked seventh for policy-makers with a mean = 5.58 (SD = 9.25), compared with practitioners who had a ranking of eleventh for this outcome (mean = 2.88, SD = 6.67). The difference in the points allocated were statistically significant between the two groups ( p  = 0.0439). Timeliness was ranked tenth most important for policy-makers, with a mean allocation of 4.03 (SD = 7.72), compared with practitioners who had a ranking of fourteenth for this outcome and a mean allocation of 2.05 (SD = 5.78). The difference in mean scores between policy-makers and practitioners on this outcome was not significant. Rankings and scores were similar for those with expertise in nutrition and dietetics, physical activity or sedentary behaviour, obesity and tobacco, alcohol or other drugs (Additional file 1 : Table S3).

Broadly, this study sought to better understand the information valued by public health policy-makers and practitioners to support their decisions regarding what and how interventions should be implemented in the community. The most valued research outcomes were the same regardless of whether policy-makers or practitioners were selecting interventions or implementation strategies. Namely outcomes regarding the effectiveness of interventions and implementation strategies. Following this, outcomes about equity, feasibility and sustainability also appeared to represent priorities. The study also found broad convergence among the most valued research outcomes, between policy-makers and practitioners, and across participants with expertise across different non-communicable disease (NCD) risk factors (for example, nutrition, obesity and tobacco). Such findings underscore the importance of research reporting these outcomes to support the translation of public health research into policy and practice.

For outcomes about decisions regarding intervention selection, the findings are broadly consistent with factors recommended by evidence-to-decision frameworks. For example, the top six ranked outcomes (effectiveness, equity, feasibility, sustainability, acceptability and economic), are also represented in both the WHO INTEGRATE framework [ 12 ] and the GRADE Evidence to Decision framework [ 13 ]. However, research outcomes about harms (adverse effects), which are included in both the WHO INTEGRATE and GRADE frameworks were ranked 13th by participants in this study. Such a finding was surprising given that potential benefits and harms of an intervention must be considered to appraise its net impact on patient or public health. Health professionals, however, do not have accurate expectations of the harms and benefits of therapeutic interventions. This appears particularly to be the case for public health professionals who acknowledge the potential for unintended consequences of policies [ 48 ] but consider these risks to be minimal [ 49 ]. The findings, therefore, may reflect the tendency of health professionals to overestimate the benefits of therapeutic interventions, and to a larger extent, underestimate harms [ 50 , 51 ]. In doing so, participants may have elevated their reported value of outcomes regarding the beneficial effectiveness of an intervention and discounted their value of outcomes reporting potential harms. Further research is warranted to substantiate this hypothesis, or explore whether other factors such as participant comprehension or misinterpretation of the outcome description may explain the finding. Nonetheless, the inclusion of measures of adverse effects (or harms) as trial outcomes is prudent to support evidence-informed public health decision-making, as is the use of strategies to facilitate risk communication to ensure the likelihood of such outcomes is understood by policy-makers and practitioners [ 52 , 53 , 54 ].

To our knowledge, this is the first study to examine the research evidence needs of public health policy-makers and practitioners when deciding on what strategies may be used to support policy or program implementation. Most of the eight implementation outcomes recommended by Proctor and colleagues [ 14 ] were ranked within the top eight by participants of this study. However, equity outcomes, ranked second by these participants, were not an outcome included in the list of outcomes defined by Proctor and colleagues. The findings may reflect public health values, which, as a discipline, has equity at its core [ 55 ]. It may also reflect the increasing attention to issues of health equity in implementation science [ 56 ].

Further, one of the eight Proctor outcomes, penetration – defined by Proctor and colleagues as the integration or saturation of an intervention within a service setting and its subsystems – was not ranked highly. Successful penetration implies a level of organization institutionalization of an intervention, which once achieved may continue to provide ongoing benefit to patients or populations. It may also suggest the capacity within the organization to expand implementation or adopt new interventions. Penetration outcomes, therefore, have been suggested to be particularly important to model and understand the potential impact of investment of scarce health resources in the implementation of public health policies and interventions [ 57 ].

At face value, such findings may suggest, at least from the perspective of public health policy-makers and practitioners, that penetration outcomes may not be particularly valued in terms of decision-making. However, it may also reflect a lack of familiarity with this term among public health policy-makers and practitioners, where related outcomes such as “reach” are more commonly used in the literature [ 14 , 58 ]. Alternatively it may be due to the conceptual similarity of this and other outcomes such as adoption, maintenance or sustainability. In other studies, for example, penetration has been operationalized to include the product of “reach”, “adoption” and “organizational maintenance” [ 58 ]. A lack of clear conceptual distinction may have led some participants to allocate points to related outcomes such as “adoption” rather than “penetration”.

The use of concept mapping techniques, consolidation of definitions of existing outcomes, and articulation of specific measures aligned to these outcomes may reduce some of these conceptual challenges. Indeed, best practice processes to develop core outcome sets for clinical trials suggest processes of engagement with end-users [ 45 ], stakeholders and researchers to articulate both broad outcomes and specific measures of these to support a shared understanding of important outcomes (and measures) to be included in such research. For example, there are many measures and economic methods to derive related to a broad outcome of “cost” (for example, absolute costs, cost–effectiveness, cost–benefit, cost–utility, and budget impact analysis) [ 59 ]. However, public health policy-makers’ preference or perceived value of these different measures to their decision-making will likely vary. While work in the field to map or align specific measures to broad outcomes is ongoing [ 57 , 58 , 60 ], extending this to empirically investigate end-user preferences for measures would be an important contribution to the field.

Broadly speaking, there was little variation in the outcomes valued between policy-makers and practitioners. However, economic evaluations were ranked as more important by policy-makers. The findings may reflect differences in the roles of Australian public health policy-makers and practitioners. That is, government policy-makers are often responsible for setting and financing the provision of public health programs, whereas health practitioners are responsible for directly supporting or undertaking their delivery. Economic considerations, therefore, may have greater primacy among policy-makers, who may be more likely to incur program costs [ 19 ]. Further research to explore and better understand these areas of divergence is warranted.

The study intended to provide information about outcomes that were generally of most use in public health policy and practice decision-making. However, such decisions are often highly contextual, and preferences may vary depending on the policy-maker or practitioner, the health issue to be addressed, the target population or broader decision-making circumstances [ 2 , 61 ]. As such, the extent to which the findings reported in this study generalize to other contexts, such as those working in different fields of public health, on different health issues or from countries or jurisdictions outside Australia is unknown. Future research examining the outcome preferences of public health policy-makers and practitioners in different contexts, therefore, is warranted.

The contextual nature of evidence needs of policy-makers and practitioners may explain, in part, the variability in outcome preferences. In many cases, for example, the mean of the outcome preference was less than its standard deviation. The interpretation of the study findings should consider this variability. That is, there is little distinguishing the mean preference ranks of many outcomes. However, the study findings at the extremes are unambiguous, suggesting clear preferences for the highest over the lowest ranking outcomes that did not differ markedly across policy-makers, practitioners or those with expertise in addressing different non-communicable disease risks such as nutrition, physical activity or tobacco or alcohol use.

Several study limitations are worth considering when interpreting the research findings. The initial inventory of outcomes was compiled from outcome frameworks, many of which were generic health or medical research outcomes that are uncommon in public health prevention research. There was considerable overlap in the outcomes included across frameworks, though how these were defined at times varied. Variability in outcome terminology has previously been identified as a problem for the field [ 62 ]. Despite being provided definitions for each, some participants may have responded to survey items based on their pre-existing understanding of these terms. Furthermore, following completion of the study, a programming error was identified whereby the definition of “Acceptability of the implementation strategy” was incorrectly assigned as “A measure of the uptake or reach of an implementation strategy”. The extent to which this may have influenced participant preferences is unclear, so sensitivity analysis was conducted by removing all participants who selected acceptability as a measure of interest. We conducted two analyses, one where the people who chose acceptability were removed but their other rankings remained and another where all their data were deleted. Results indicated that the top five outcomes did not differ after conducting the analysis, with only sustainability moving from fourth to second place in the second sensitivity analysis (Additional file 1 : Tables S4 and S5).

The pathway from research production to research in health policy or practice is complex. While a range of effective public health policies and interventions exist across a range of community settings [ 63 , 64 , 65 , 66 ], their implementation at a level capable of achieving population-level risk reductions remains elusive [ 67 , 68 , 69 , 70 ]. Nonetheless, undertaking research with end-use in mind, including reporting of outcomes valued by decision-makers, will likely facilitate the knowledge translation process [ 7 ]. In this study we found that outcomes related to effectiveness, equity, feasibility and sustainability appear important to decisions policy-makers and practitioners make about the interventions they select and the strategies they employ to implement public health prevention initiatives. Researchers interested in supporting evidence-informed decision-making should seek to provide for these information needs and prioritize such outcomes in dissemination activities to policy-makers and practitioners.

Contribution to the literature

It is essential to the research needs of policy-makers and practitioners to determine core outcomes to facilitate research use and knowledge translation.

Here we quantify the relative values of a variety of research outcomes commonly used in health research.

Findings suggest the primary outcomes of interest to public health prevention policy-makers and practitioners when making decisions about the selection of interventions and strategies to implement them are related to effectiveness, equity, feasibility and sustainability and that these do not differ markedly between public health prevention policy-makers and practitioners.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Australian and New Zealand Journal of Public Health

Health Promotion Journal of Australia

Intervention scalability assessment tool

Non-communicable disease

National Centre of Implementation Science

Public Health Research and Practice

World Health Organization

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Acknowledgements

Not applicable.

This study was funded in part by a National Health and Medical Research Council (NHMRC) Centre for Research Excellence – National Centre of Implementation Science (NCOIS) Grant (APP1153479) and a New South Wales (NSW) Cancer Council Program Grant (G1500708). LW is supported by an NHMRC Investigator Grant (G1901360).

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Luke Wolfenden, Alix Hall, Adrian Bauman, Rebecca Hodder, Emily Webb, Kaitlin Mooney, Serene Yoong, Rachel Sutherland & Sam McCrabb

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LW and SMc led the conception and design of the study, were closely involved in data analysis and interpretation and wrote the manuscript. AH, AB, AM and RH comprised the study advisory committee, reviewed the study’s methods and assisted with survey development. AH was responsible for data analysis. KM and EW assisted with survey development, data collection and preliminary analysis. AH, AB, AM, RH, SY and RS were involved in interpretation and revised the manuscript critically for important intellectual content. All authors read and approved the final manuscript.

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Additional file 1:.

Table S1. Mean point allocations for each of the 17 intervention outcomes overall and by area of expertise (where field of expertise n ≥ 30). Table S2. Mean point allocations for each of the 16 implementation outcomes overall and by area of expertise (where field of expertise n ≥ 30). Table S3. Mean points for implementation outcomes overall and by area of expertise (field of expertise n ≥ 30). Table S4. Sensitivity analysis, participants who selected ‘acceptability’ removed from the analysis, their other rankings remained. Table S5. Sensitivity analysis, participants who selected ‘acceptability’ whole data set removed from the analysis.

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Wolfenden, L., Hall, A., Bauman, A. et al. Research outcomes informing the selection of public health interventions and strategies to implement them: A cross-sectional survey of Australian policy-maker and practitioner preferences. Health Res Policy Sys 22 , 58 (2024). https://doi.org/10.1186/s12961-024-01144-4

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