what is a search strategy for literature review

• Study and research support
• Literature searching

Literature searching explained

Develop a search strategy.

A search strategy is an organised structure of key terms used to search a database. The search strategy combines the key concepts of your search question in order to retrieve accurate results.

Your search strategy will account for all:

• possible search terms
• keywords and phrases
• truncated and wildcard variations of search terms
• subject headings (where applicable)

Each database works differently so you need to adapt your search strategy for each database. You may wish to develop a number of separate search strategies if your research covers several different areas.

It is a good idea to test your strategies and refine them after you have reviewed the search results.

How a search strategy looks in practice

Take a look at this example literature search in PsycINFO (PDF) about self-esteem.

The example shows the subject heading and keyword searches that have been carried out for each concept within our research question and how they have been combined using Boolean operators. It also shows where keyword techniques like truncation, wildcards and adjacency searching have been used.

Search strategy techniques

The next sections show some techniques you can use to develop your search strategy.

Skip straight to:

• Choosing search terms
• Searching with keywords
• Searching for exact phrases
• Using truncated and wildcard searches

Searching with subject headings

• Using Boolean logic

Citation searching

Choose search terms.

Concepts can be expressed in different ways eg “self-esteem” might be referred to as “self-worth”. Your aim is to consider each of your concepts and come up with a list of the different ways they could be expressed.

To find alternative keywords or phrases for your concepts try the following:

• Use a thesaurus to identify synonyms.
• Search for your concepts on a search engine like Google Scholar, scanning the results for alternative words and phrases.
• Examine relevant abstracts or articles for alternative words, phrases and subject headings (if the database uses subject headings).

When you've done this, you should have lists of words and phrases for each concept as in this completed PICO model (PDF) or this example concept map (PDF).

As you search and scan articles and abstracts, you may discover different key terms to enhance your search strategy.

Using truncation and wildcards can save you time and effort by finding alternative keywords.

Search with keywords

Keywords are free text words and phrases. Database search strategies use a combination of free text and subject headings (where applicable).

A keyword search usually looks for your search terms in the title and abstract of a reference. You may wish to search in title fields only if you want a small number of specific results.

Some databases will find the exact word or phrase, so make sure your spelling is accurate or you will miss references.

Search for the exact phrase

If you want words to appear next to each other in an exact phrase, use quotation marks, eg “self-esteem”.

Phrase searching decreases the number of results you get and makes your results more relevant. Most databases allow you to search for phrases, but check the database guide if you are unsure.

Truncation and wildcard searches

You can use truncated and wildcard searches to find variations of your search term. Truncation is useful for finding singular and plural forms of words and variant endings.

Many databases use an asterisk (*) as their truncation symbol. Check the database help section if you are not sure which symbol to use. For example, “therap*” will find therapy, therapies, therapist or therapists. A wildcard finds variant spellings of words. Use it to search for a single character, or no character.

Check the database help section to see which symbol to use as a wildcard.

Wildcards are useful for finding British and American spellings, for example: “behavio?r” in Medline will find both behaviour and behavior.

There are sometimes different symbols to find a variable single character. For example, in the Medline database, “wom#n” will find woman and also women.

Use adjacency searching for more accurate results

You can specify how close two words appear together in your search strategy. This can make your results more relevant; generally the closer two words appear to each other, the closer the relationship is between them.

Commands for adjacency searching differ among databases, so make sure you consult database guides.

In OvidSP databases (like Medline), searching for “physician ADJ3 relationship” will find both physician and relationship within two major words of each other, in any order. This finds more papers than "physician relationship".

Using this adjacency retrieves papers with phrases like "physician patient relationship", "patient physician relationship", "relationship of the physician to the patient" and so on.

Database subject headings are controlled vocabulary terms that a database uses to describe what an article is about.

Watch our 3-minute introduction to subject headings video . You can also  View the video using Microsoft Stream (link opens in a new window, available for University members only).

Using appropriate subject headings enhances your search and will help you to find more results on your topic. This is because subject headings find articles according to their subject, even if the article does not use your chosen key words.

You should combine both subject headings and keywords in your search strategy for each of the concepts you identify. This is particularly important if you are undertaking a systematic review or an in-depth piece of work

Subject headings may vary between databases, so you need to investigate each database separately to find the subject headings they use. For example, for Medline you can use MeSH (Medical Subject Headings) and for Embase you can use the EMTREE thesaurus.

SEARCH TIP: In Ovid databases, search for a known key paper by title, select the "complete reference" button to see which subject headings the database indexers have given that article, and consider adding relevant ones to your own search strategy.

Use Boolean logic to combine search terms

Boolean operators (AND, OR and NOT) allow you to try different combinations of search terms or subject headings.

Databases often show Boolean operators as buttons or drop-down menus that you can click to combine your search terms or results.

The main Boolean operators are:

OR is used to find articles that mention either of the topics you search for.

AND is used to find articles that mention both of the searched topics.

NOT excludes a search term or concept. It should be used with caution as you may inadvertently exclude relevant references.

For example, searching for “self-esteem NOT eating disorders” finds articles that mention self-esteem but removes any articles that mention eating disorders.

Citation searching is a method to find articles that have been cited by other publications.

Use citation searching (or cited reference searching) to:

• find out whether articles have been cited by other authors
• find more recent papers on the same or similar subject
• discover how a known idea or innovation has been confirmed, applied, improved, extended, or corrected
• help make your literature review more comprehensive.

You can use cited reference searching in:

• OvidSP databases
• Google Scholar
• Web of Science

Cited reference searching can complement your literature search. However be careful not to just look at papers that have been cited in isolation. A robust literature search is also needed to limit publication bias.

Literature Review: Developing a search strategy

• Traditional or narrative literature reviews
• Scoping Reviews
• Systematic literature reviews
• Annotated bibliography
• Keeping up to date with literature
• Finding a thesis
• Evaluating sources and critical appraisal of literature
• Managing and analysing your literature
• Further reading and resources

From research question to search strategy

Keeping a record of your search activity

Good search practice could involve keeping a search diary or document detailing your search activities (Phelps et. al. 2007, pp. 128-149), so that you can keep track of effective search terms, or to help others to reproduce your steps and get the same results. 

This record could be a document, table or spreadsheet with:

• The names of the sources you search and which provider you accessed them through - eg Medline (Ovid), Web of Science (Thomson Reuters). You should also include any other literature sources you used.
• how you searched (keyword and/or subject headings)
• which search terms you used (which words and phrases)
• any search techniques you employed (truncation, adjacency, etc)
• how you combined your search terms (AND/OR). Check out the Database Help guide for more tips on Boolean Searching.
• The number of search results from each source and each strategy used. This can be the evidence you need to prove a gap in the literature, and confirms the importance of your research question.

A search planner may help you to organise you thoughts prior to conducting your search. If you have any problems with organising your thoughts prior, during and after searching please contact your Library  Faculty Team   for individual help.

• Literature search - a librarian's handout to introduce tools, terms and techniques Created by Elsevier librarian, Katy Kavanagh Web, this document outlines tools, terms and techniques to think about when conducting a literature search.
• Search planner

Literature search cycle

Diagram text description

This diagram illustrates the literature search cycle. It shows a circle in quarters. Top left quarter is identify main concepts with rectangle describing how to do this by identifying:controlled vocabulary terms, synonyms, keywords and spelling. Top right quarter select library resources to search and rectangle describing resources to search library catalogue relevant journal articles and other resource. Bottom right corner of circle search resources and in rectangle consider using boolean searchingproximity searching and truncated searching techniques. Bottom left quarter of circle review and refine results. In rectangle evaluate results, rethink keywords and create alerts.

Have a search framework

Search frameworks are mnemonics which can help you focus your research question. They are also useful in helping you to identify the concepts and terms you will use in your literature search.

PICO is a search framework commonly used in the health sciences to focus clinical questions.  As an example, you work in an aged care facility and are interested in whether cranberry juice might help reduce the common occurrence of urinary tract infections.  The PICO framework would look like this:

Now that the issue has been broken up to its elements, it is easier to turn it into an answerable research question: “Does cranberry juice help reduce urinary tract infections in people living in aged care facilities?”

Other frameworks may be helpful, depending on your question and your field of interest. PICO can be adapted to PICOT (which adds T ime) or PICOS (which adds S tudy design), or PICOC (adding C ontext).

For qualitative questions you could use

• SPIDER : S ample,  P henomenon of  I nterest,  D esign,  E valuation,  R esearch type  

For questions about causes or risk,

• PEO : P opulation,  E xposure,  O utcomes

For evaluations of interventions or policies, 

• SPICE: S etting,  P opulation or  P erspective,  I ntervention,  C omparison,  E valuation or
• ECLIPSE: E xpectation,  C lient group,  L ocation,  I mpact,  P rofessionals,  SE rvice 

See the University of Notre Dame Australia’s examples of some of these frameworks. 

You can also try some PICO examples in the National Library of Medicine's PubMed training site: Using PICO to frame clinical questions.

Contact Your Faculty Team Librarian

Faculty librarians are here to provide assistance to students, researchers and academic staff by providing expert searching advice, research and curriculum support.

• Faculty of Arts & Education team
• Faculty of Business, Justice & Behavioural Science team
• Faculty of Science team

Further reading

• << Previous: Annotated bibliography
• Next: Keeping up to date with literature >>
• Last Updated: Jan 16, 2024 1:39 PM
• URL: https://libguides.csu.edu.au/review

Charles Sturt University is an Australian University, TEQSA Provider Identification: PRV12018. CRICOS Provider: 00005F.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

Instantly correct all language mistakes in your text

Upload your document to correct all your mistakes in minutes

Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

The only proofreading tool specialized in correcting academic writing - try for free!

The academic proofreading tool has been trained on 1000s of academic texts and by native English editors. Making it the most accurate and reliable proofreading tool for students.

Try for free

To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

Open Google Slides Download PowerPoint

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. (2023, September 11). How to Write a Literature Review | Guide, Examples, & Templates. Scribbr. Retrieved March 25, 2024, from https://www.scribbr.com/dissertation/literature-review/

Is this article helpful?

Shona McCombes

Other students also liked, what is a theoretical framework | guide to organizing, what is a research methodology | steps & tips, how to write a research proposal | examples & templates, "i thought ai proofreading was useless but..".

I've been using Scribbr for years now and I know it's a service that won't disappoint. It does a good job spotting mistakes”

• Open access
• Published: 14 August 2018

Defining the process to literature searching in systematic reviews: a literature review of guidance and supporting studies

• Chris Cooper   ORCID: orcid.org/0000-0003-0864-5607 1 ,
• Andrew Booth 2 ,
• Jo Varley-Campbell 1 ,
• Nicky Britten 3 &
• Ruth Garside 4  

BMC Medical Research Methodology volume  18 , Article number:  85 ( 2018 ) Cite this article

198k Accesses

200 Citations

118 Altmetric

Metrics details

Systematic literature searching is recognised as a critical component of the systematic review process. It involves a systematic search for studies and aims for a transparent report of study identification, leaving readers clear about what was done to identify studies, and how the findings of the review are situated in the relevant evidence.

Information specialists and review teams appear to work from a shared and tacit model of the literature search process. How this tacit model has developed and evolved is unclear, and it has not been explicitly examined before.

The purpose of this review is to determine if a shared model of the literature searching process can be detected across systematic review guidance documents and, if so, how this process is reported in the guidance and supported by published studies.

A literature review.

Two types of literature were reviewed: guidance and published studies. Nine guidance documents were identified, including: The Cochrane and Campbell Handbooks. Published studies were identified through ‘pearl growing’, citation chasing, a search of PubMed using the systematic review methods filter, and the authors’ topic knowledge.

The relevant sections within each guidance document were then read and re-read, with the aim of determining key methodological stages. Methodological stages were identified and defined. This data was reviewed to identify agreements and areas of unique guidance between guidance documents. Consensus across multiple guidance documents was used to inform selection of ‘key stages’ in the process of literature searching.

Eight key stages were determined relating specifically to literature searching in systematic reviews. They were: who should literature search, aims and purpose of literature searching, preparation, the search strategy, searching databases, supplementary searching, managing references and reporting the search process.

Conclusions

Eight key stages to the process of literature searching in systematic reviews were identified. These key stages are consistently reported in the nine guidance documents, suggesting consensus on the key stages of literature searching, and therefore the process of literature searching as a whole, in systematic reviews. Further research to determine the suitability of using the same process of literature searching for all types of systematic review is indicated.

Peer Review reports

Systematic literature searching is recognised as a critical component of the systematic review process. It involves a systematic search for studies and aims for a transparent report of study identification, leaving review stakeholders clear about what was done to identify studies, and how the findings of the review are situated in the relevant evidence.

Information specialists and review teams appear to work from a shared and tacit model of the literature search process. How this tacit model has developed and evolved is unclear, and it has not been explicitly examined before. This is in contrast to the information science literature, which has developed information processing models as an explicit basis for dialogue and empirical testing. Without an explicit model, research in the process of systematic literature searching will remain immature and potentially uneven, and the development of shared information models will be assumed but never articulated.

One way of developing such a conceptual model is by formally examining the implicit “programme theory” as embodied in key methodological texts. The aim of this review is therefore to determine if a shared model of the literature searching process in systematic reviews can be detected across guidance documents and, if so, how this process is reported and supported.

Identifying guidance

Key texts (henceforth referred to as “guidance”) were identified based upon their accessibility to, and prominence within, United Kingdom systematic reviewing practice. The United Kingdom occupies a prominent position in the science of health information retrieval, as quantified by such objective measures as the authorship of papers, the number of Cochrane groups based in the UK, membership and leadership of groups such as the Cochrane Information Retrieval Methods Group, the HTA-I Information Specialists’ Group and historic association with such centres as the UK Cochrane Centre, the NHS Centre for Reviews and Dissemination, the Centre for Evidence Based Medicine and the National Institute for Clinical Excellence (NICE). Coupled with the linguistic dominance of English within medical and health science and the science of systematic reviews more generally, this offers a justification for a purposive sample that favours UK, European and Australian guidance documents.

Nine guidance documents were identified. These documents provide guidance for different types of reviews, namely: reviews of interventions, reviews of health technologies, reviews of qualitative research studies, reviews of social science topics, and reviews to inform guidance.

Whilst these guidance documents occasionally offer additional guidance on other types of systematic reviews, we have focused on the core and stated aims of these documents as they relate to literature searching. Table  1 sets out: the guidance document, the version audited, their core stated focus, and a bibliographical pointer to the main guidance relating to literature searching.

Once a list of key guidance documents was determined, it was checked by six senior information professionals based in the UK for relevance to current literature searching in systematic reviews.

Identifying supporting studies

In addition to identifying guidance, the authors sought to populate an evidence base of supporting studies (henceforth referred to as “studies”) that contribute to existing search practice. Studies were first identified by the authors from their knowledge on this topic area and, subsequently, through systematic citation chasing key studies (‘pearls’ [ 1 ]) located within each key stage of the search process. These studies are identified in Additional file  1 : Appendix Table 1. Citation chasing was conducted by analysing the bibliography of references for each study (backwards citation chasing) and through Google Scholar (forward citation chasing). A search of PubMed using the systematic review methods filter was undertaken in August 2017 (see Additional file 1 ). The search terms used were: (literature search*[Title/Abstract]) AND sysrev_methods[sb] and 586 results were returned. These results were sifted for relevance to the key stages in Fig.  1 by CC.

The key stages of literature search guidance as identified from nine key texts

Extracting the data

To reveal the implicit process of literature searching within each guidance document, the relevant sections (chapters) on literature searching were read and re-read, with the aim of determining key methodological stages. We defined a key methodological stage as a distinct step in the overall process for which specific guidance is reported, and action is taken, that collectively would result in a completed literature search.

The chapter or section sub-heading for each methodological stage was extracted into a table using the exact language as reported in each guidance document. The lead author (CC) then read and re-read these data, and the paragraphs of the document to which the headings referred, summarising section details. This table was then reviewed, using comparison and contrast to identify agreements and areas of unique guidance. Consensus across multiple guidelines was used to inform selection of ‘key stages’ in the process of literature searching.

Having determined the key stages to literature searching, we then read and re-read the sections relating to literature searching again, extracting specific detail relating to the methodological process of literature searching within each key stage. Again, the guidance was then read and re-read, first on a document-by-document-basis and, secondly, across all the documents above, to identify both commonalities and areas of unique guidance.

Results and discussion

Our findings.

We were able to identify consensus across the guidance on literature searching for systematic reviews suggesting a shared implicit model within the information retrieval community. Whilst the structure of the guidance varies between documents, the same key stages are reported, even where the core focus of each document is different. We were able to identify specific areas of unique guidance, where a document reported guidance not summarised in other documents, together with areas of consensus across guidance.

Unique guidance

Only one document provided guidance on the topic of when to stop searching [ 2 ]. This guidance from 2005 anticipates a topic of increasing importance with the current interest in time-limited (i.e. “rapid”) reviews. Quality assurance (or peer review) of literature searches was only covered in two guidance documents [ 3 , 4 ]. This topic has emerged as increasingly important as indicated by the development of the PRESS instrument [ 5 ]. Text mining was discussed in four guidance documents [ 4 , 6 , 7 , 8 ] where the automation of some manual review work may offer efficiencies in literature searching [ 8 ].

Agreement between guidance: Defining the key stages of literature searching

Where there was agreement on the process, we determined that this constituted a key stage in the process of literature searching to inform systematic reviews.

From the guidance, we determined eight key stages that relate specifically to literature searching in systematic reviews. These are summarised at Fig. 1 . The data extraction table to inform Fig. 1 is reported in Table  2 . Table 2 reports the areas of common agreement and it demonstrates that the language used to describe key stages and processes varies significantly between guidance documents.

For each key stage, we set out the specific guidance, followed by discussion on how this guidance is situated within the wider literature.

Key stage one: Deciding who should undertake the literature search

The guidance.

Eight documents provided guidance on who should undertake literature searching in systematic reviews [ 2 , 4 , 6 , 7 , 8 , 9 , 10 , 11 ]. The guidance affirms that people with relevant expertise of literature searching should ‘ideally’ be included within the review team [ 6 ]. Information specialists (or information scientists), librarians or trial search co-ordinators (TSCs) are indicated as appropriate researchers in six guidance documents [ 2 , 7 , 8 , 9 , 10 , 11 ].

How the guidance corresponds to the published studies

The guidance is consistent with studies that call for the involvement of information specialists and librarians in systematic reviews [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ] and which demonstrate how their training as ‘expert searchers’ and ‘analysers and organisers of data’ can be put to good use [ 13 ] in a variety of roles [ 12 , 16 , 20 , 21 , 24 , 25 , 26 ]. These arguments make sense in the context of the aims and purposes of literature searching in systematic reviews, explored below. The need for ‘thorough’ and ‘replicable’ literature searches was fundamental to the guidance and recurs in key stage two. Studies have found poor reporting, and a lack of replicable literature searches, to be a weakness in systematic reviews [ 17 , 18 , 27 , 28 ] and they argue that involvement of information specialists/ librarians would be associated with better reporting and better quality literature searching. Indeed, Meert et al. [ 29 ] demonstrated that involving a librarian as a co-author to a systematic review correlated with a higher score in the literature searching component of a systematic review [ 29 ]. As ‘new styles’ of rapid and scoping reviews emerge, where decisions on how to search are more iterative and creative, a clear role is made here too [ 30 ].

Knowing where to search for studies was noted as important in the guidance, with no agreement as to the appropriate number of databases to be searched [ 2 , 6 ]. Database (and resource selection more broadly) is acknowledged as a relevant key skill of information specialists and librarians [ 12 , 15 , 16 , 31 ].

Whilst arguments for including information specialists and librarians in the process of systematic review might be considered self-evident, Koffel and Rethlefsen [ 31 ] have questioned if the necessary involvement is actually happening [ 31 ].

Key stage two: Determining the aim and purpose of a literature search

The aim: Five of the nine guidance documents use adjectives such as ‘thorough’, ‘comprehensive’, ‘transparent’ and ‘reproducible’ to define the aim of literature searching [ 6 , 7 , 8 , 9 , 10 ]. Analogous phrases were present in a further three guidance documents, namely: ‘to identify the best available evidence’ [ 4 ] or ‘the aim of the literature search is not to retrieve everything. It is to retrieve everything of relevance’ [ 2 ] or ‘A systematic literature search aims to identify all publications relevant to the particular research question’ [ 3 ]. The Joanna Briggs Institute reviewers’ manual was the only guidance document where a clear statement on the aim of literature searching could not be identified. The purpose of literature searching was defined in three guidance documents, namely to minimise bias in the resultant review [ 6 , 8 , 10 ]. Accordingly, eight of nine documents clearly asserted that thorough and comprehensive literature searches are required as a potential mechanism for minimising bias.

The need for thorough and comprehensive literature searches appears as uniform within the eight guidance documents that describe approaches to literature searching in systematic reviews of effectiveness. Reviews of effectiveness (of intervention or cost), accuracy and prognosis, require thorough and comprehensive literature searches to transparently produce a reliable estimate of intervention effect. The belief that all relevant studies have been ‘comprehensively’ identified, and that this process has been ‘transparently’ reported, increases confidence in the estimate of effect and the conclusions that can be drawn [ 32 ]. The supporting literature exploring the need for comprehensive literature searches focuses almost exclusively on reviews of intervention effectiveness and meta-analysis. Different ‘styles’ of review may have different standards however; the alternative, offered by purposive sampling, has been suggested in the specific context of qualitative evidence syntheses [ 33 ].

What is a comprehensive literature search?

Whilst the guidance calls for thorough and comprehensive literature searches, it lacks clarity on what constitutes a thorough and comprehensive literature search, beyond the implication that all of the literature search methods in Table 2 should be used to identify studies. Egger et al. [ 34 ], in an empirical study evaluating the importance of comprehensive literature searches for trials in systematic reviews, defined a comprehensive search for trials as:

a search not restricted to English language;

where Cochrane CENTRAL or at least two other electronic databases had been searched (such as MEDLINE or EMBASE); and

at least one of the following search methods has been used to identify unpublished trials: searches for (I) conference abstracts, (ii) theses, (iii) trials registers; and (iv) contacts with experts in the field [ 34 ].

Tricco et al. (2008) used a similar threshold of bibliographic database searching AND a supplementary search method in a review when examining the risk of bias in systematic reviews. Their criteria were: one database (limited using the Cochrane Highly Sensitive Search Strategy (HSSS)) and handsearching [ 35 ].

Together with the guidance, this would suggest that comprehensive literature searching requires the use of BOTH bibliographic database searching AND supplementary search methods.

Comprehensiveness in literature searching, in the sense of how much searching should be undertaken, remains unclear. Egger et al. recommend that ‘investigators should consider the type of literature search and degree of comprehension that is appropriate for the review in question, taking into account budget and time constraints’ [ 34 ]. This view tallies with the Cochrane Handbook, which stipulates clearly, that study identification should be undertaken ‘within resource limits’ [ 9 ]. This would suggest that the limitations to comprehension are recognised but it raises questions on how this is decided and reported [ 36 ].

What is the point of comprehensive literature searching?

The purpose of thorough and comprehensive literature searches is to avoid missing key studies and to minimize bias [ 6 , 8 , 10 , 34 , 37 , 38 , 39 ] since a systematic review based only on published (or easily accessible) studies may have an exaggerated effect size [ 35 ]. Felson (1992) sets out potential biases that could affect the estimate of effect in a meta-analysis [ 40 ] and Tricco et al. summarize the evidence concerning bias and confounding in systematic reviews [ 35 ]. Egger et al. point to non-publication of studies, publication bias, language bias and MEDLINE bias, as key biases [ 34 , 35 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]. Comprehensive searches are not the sole factor to mitigate these biases but their contribution is thought to be significant [ 2 , 32 , 34 ]. Fehrmann (2011) suggests that ‘the search process being described in detail’ and that, where standard comprehensive search techniques have been applied, increases confidence in the search results [ 32 ].

Does comprehensive literature searching work?

Egger et al., and other study authors, have demonstrated a change in the estimate of intervention effectiveness where relevant studies were excluded from meta-analysis [ 34 , 47 ]. This would suggest that missing studies in literature searching alters the reliability of effectiveness estimates. This is an argument for comprehensive literature searching. Conversely, Egger et al. found that ‘comprehensive’ searches still missed studies and that comprehensive searches could, in fact, introduce bias into a review rather than preventing it, through the identification of low quality studies then being included in the meta-analysis [ 34 ]. Studies query if identifying and including low quality or grey literature studies changes the estimate of effect [ 43 , 48 ] and question if time is better invested updating systematic reviews rather than searching for unpublished studies [ 49 ], or mapping studies for review as opposed to aiming for high sensitivity in literature searching [ 50 ].

Aim and purpose beyond reviews of effectiveness

The need for comprehensive literature searches is less certain in reviews of qualitative studies, and for reviews where a comprehensive identification of studies is difficult to achieve (for example, in Public health) [ 33 , 51 , 52 , 53 , 54 , 55 ]. Literature searching for qualitative studies, and in public health topics, typically generates a greater number of studies to sift than in reviews of effectiveness [ 39 ] and demonstrating the ‘value’ of studies identified or missed is harder [ 56 ], since the study data do not typically support meta-analysis. Nussbaumer-Streit et al. (2016) have registered a review protocol to assess whether abbreviated literature searches (as opposed to comprehensive literature searches) has an impact on conclusions across multiple bodies of evidence, not only on effect estimates [ 57 ] which may develop this understanding. It may be that decision makers and users of systematic reviews are willing to trade the certainty from a comprehensive literature search and systematic review in exchange for different approaches to evidence synthesis [ 58 ], and that comprehensive literature searches are not necessarily a marker of literature search quality, as previously thought [ 36 ]. Different approaches to literature searching [ 37 , 38 , 59 , 60 , 61 , 62 ] and developing the concept of when to stop searching are important areas for further study [ 36 , 59 ].

The study by Nussbaumer-Streit et al. has been published since the submission of this literature review [ 63 ]. Nussbaumer-Streit et al. (2018) conclude that abbreviated literature searches are viable options for rapid evidence syntheses, if decision-makers are willing to trade the certainty from a comprehensive literature search and systematic review, but that decision-making which demands detailed scrutiny should still be based on comprehensive literature searches [ 63 ].

Key stage three: Preparing for the literature search

Six documents provided guidance on preparing for a literature search [ 2 , 3 , 6 , 7 , 9 , 10 ]. The Cochrane Handbook clearly stated that Cochrane authors (i.e. researchers) should seek advice from a trial search co-ordinator (i.e. a person with specific skills in literature searching) ‘before’ starting a literature search [ 9 ].

Two key tasks were perceptible in preparing for a literature searching [ 2 , 6 , 7 , 10 , 11 ]. First, to determine if there are any existing or on-going reviews, or if a new review is justified [ 6 , 11 ]; and, secondly, to develop an initial literature search strategy to estimate the volume of relevant literature (and quality of a small sample of relevant studies [ 10 ]) and indicate the resources required for literature searching and the review of the studies that follows [ 7 , 10 ].

Three documents summarised guidance on where to search to determine if a new review was justified [ 2 , 6 , 11 ]. These focused on searching databases of systematic reviews (The Cochrane Database of Systematic Reviews (CDSR) and the Database of Abstracts of Reviews of Effects (DARE)), institutional registries (including PROSPERO), and MEDLINE [ 6 , 11 ]. It is worth noting, however, that as of 2015, DARE (and NHS EEDs) are no longer being updated and so the relevance of this (these) resource(s) will diminish over-time [ 64 ]. One guidance document, ‘Systematic reviews in the Social Sciences’, noted, however, that databases are not the only source of information and unpublished reports, conference proceeding and grey literature may also be required, depending on the nature of the review question [ 2 ].

Two documents reported clearly that this preparation (or ‘scoping’) exercise should be undertaken before the actual search strategy is developed [ 7 , 10 ]).

The guidance offers the best available source on preparing the literature search with the published studies not typically reporting how their scoping informed the development of their search strategies nor how their search approaches were developed. Text mining has been proposed as a technique to develop search strategies in the scoping stages of a review although this work is still exploratory [ 65 ]. ‘Clustering documents’ and word frequency analysis have also been tested to identify search terms and studies for review [ 66 , 67 ]. Preparing for literature searches and scoping constitutes an area for future research.

Key stage four: Designing the search strategy

The Population, Intervention, Comparator, Outcome (PICO) structure was the commonly reported structure promoted to design a literature search strategy. Five documents suggested that the eligibility criteria or review question will determine which concepts of PICO will be populated to develop the search strategy [ 1 , 4 , 7 , 8 , 9 ]. The NICE handbook promoted multiple structures, namely PICO, SPICE (Setting, Perspective, Intervention, Comparison, Evaluation) and multi-stranded approaches [ 4 ].

With the exclusion of The Joanna Briggs Institute reviewers’ manual, the guidance offered detail on selecting key search terms, synonyms, Boolean language, selecting database indexing terms and combining search terms. The CEE handbook suggested that ‘search terms may be compiled with the help of the commissioning organisation and stakeholders’ [ 10 ].

The use of limits, such as language or date limits, were discussed in all documents [ 2 , 3 , 4 , 6 , 7 , 8 , 9 , 10 , 11 ].

Search strategy structure

The guidance typically relates to reviews of intervention effectiveness so PICO – with its focus on intervention and comparator - is the dominant model used to structure literature search strategies [ 68 ]. PICOs – where the S denotes study design - is also commonly used in effectiveness reviews [ 6 , 68 ]. As the NICE handbook notes, alternative models to structure literature search strategies have been developed and tested. Booth provides an overview on formulating questions for evidence based practice [ 69 ] and has developed a number of alternatives to the PICO structure, namely: BeHEMoTh (Behaviour of interest; Health context; Exclusions; Models or Theories) for use when systematically identifying theory [ 55 ]; SPICE (Setting, Perspective, Intervention, Comparison, Evaluation) for identification of social science and evaluation studies [ 69 ] and, working with Cooke and colleagues, SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, Research type) [ 70 ]. SPIDER has been compared to PICO and PICOs in a study by Methley et al. [ 68 ].

The NICE handbook also suggests the use of multi-stranded approaches to developing literature search strategies [ 4 ]. Glanville developed this idea in a study by Whitting et al. [ 71 ] and a worked example of this approach is included in the development of a search filter by Cooper et al. [ 72 ].

Writing search strategies: Conceptual and objective approaches

Hausner et al. [ 73 ] provide guidance on writing literature search strategies, delineating between conceptually and objectively derived approaches. The conceptual approach, advocated by and explained in the guidance documents, relies on the expertise of the literature searcher to identify key search terms and then develop key terms to include synonyms and controlled syntax. Hausner and colleagues set out the objective approach [ 73 ] and describe what may be done to validate it [ 74 ].

The use of limits

The guidance documents offer direction on the use of limits within a literature search. Limits can be used to focus literature searching to specific study designs or by other markers (such as by date) which limits the number of studies returned by a literature search. The use of limits should be described and the implications explored [ 34 ] since limiting literature searching can introduce bias (explored above). Craven et al. have suggested the use of a supporting narrative to explain decisions made in the process of developing literature searches and this advice would usefully capture decisions on the use of search limits [ 75 ].

Key stage five: Determining the process of literature searching and deciding where to search (bibliographic database searching)

Table 2 summarises the process of literature searching as reported in each guidance document. Searching bibliographic databases was consistently reported as the ‘first step’ to literature searching in all nine guidance documents.

Three documents reported specific guidance on where to search, in each case specific to the type of review their guidance informed, and as a minimum requirement [ 4 , 9 , 11 ]. Seven of the key guidance documents suggest that the selection of bibliographic databases depends on the topic of review [ 2 , 3 , 4 , 6 , 7 , 8 , 10 ], with two documents noting the absence of an agreed standard on what constitutes an acceptable number of databases searched [ 2 , 6 ].

The guidance documents summarise ‘how to’ search bibliographic databases in detail and this guidance is further contextualised above in terms of developing the search strategy. The documents provide guidance of selecting bibliographic databases, in some cases stating acceptable minima (i.e. The Cochrane Handbook states Cochrane CENTRAL, MEDLINE and EMBASE), and in other cases simply listing bibliographic database available to search. Studies have explored the value in searching specific bibliographic databases, with Wright et al. (2015) noting the contribution of CINAHL in identifying qualitative studies [ 76 ], Beckles et al. (2013) questioning the contribution of CINAHL to identifying clinical studies for guideline development [ 77 ], and Cooper et al. (2015) exploring the role of UK-focused bibliographic databases to identify UK-relevant studies [ 78 ]. The host of the database (e.g. OVID or ProQuest) has been shown to alter the search returns offered. Younger and Boddy [ 79 ] report differing search returns from the same database (AMED) but where the ‘host’ was different [ 79 ].

The average number of bibliographic database searched in systematic reviews has risen in the period 1994–2014 (from 1 to 4) [ 80 ] but there remains (as attested to by the guidance) no consensus on what constitutes an acceptable number of databases searched [ 48 ]. This is perhaps because thinking about the number of databases searched is the wrong question, researchers should be focused on which databases were searched and why, and which databases were not searched and why. The discussion should re-orientate to the differential value of sources but researchers need to think about how to report this in studies to allow findings to be generalised. Bethel (2017) has proposed ‘search summaries’, completed by the literature searcher, to record where included studies were identified, whether from database (and which databases specifically) or supplementary search methods [ 81 ]. Search summaries document both yield and accuracy of searches, which could prospectively inform resource use and decisions to search or not to search specific databases in topic areas. The prospective use of such data presupposes, however, that past searches are a potential predictor of future search performance (i.e. that each topic is to be considered representative and not unique). In offering a body of practice, this data would be of greater practicable use than current studies which are considered as little more than individual case studies [ 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 ].

When to database search is another question posed in the literature. Beyer et al. [ 91 ] report that databases can be prioritised for literature searching which, whilst not addressing the question of which databases to search, may at least bring clarity as to which databases to search first [ 91 ]. Paradoxically, this links to studies that suggest PubMed should be searched in addition to MEDLINE (OVID interface) since this improves the currency of systematic reviews [ 92 , 93 ]. Cooper et al. (2017) have tested the idea of database searching not as a primary search method (as suggested in the guidance) but as a supplementary search method in order to manage the volume of studies identified for an environmental effectiveness systematic review. Their case study compared the effectiveness of database searching versus a protocol using supplementary search methods and found that the latter identified more relevant studies for review than searching bibliographic databases [ 94 ].

Key stage six: Determining the process of literature searching and deciding where to search (supplementary search methods)

Table 2 also summaries the process of literature searching which follows bibliographic database searching. As Table 2 sets out, guidance that supplementary literature search methods should be used in systematic reviews recurs across documents, but the order in which these methods are used, and the extent to which they are used, varies. We noted inconsistency in the labelling of supplementary search methods between guidance documents.

Rather than focus on the guidance on how to use the methods (which has been summarised in a recent review [ 95 ]), we focus on the aim or purpose of supplementary search methods.

The Cochrane Handbook reported that ‘efforts’ to identify unpublished studies should be made [ 9 ]. Four guidance documents [ 2 , 3 , 6 , 9 ] acknowledged that searching beyond bibliographic databases was necessary since ‘databases are not the only source of literature’ [ 2 ]. Only one document reported any guidance on determining when to use supplementary methods. The IQWiG handbook reported that the use of handsearching (in their example) could be determined on a ‘case-by-case basis’ which implies that the use of these methods is optional rather than mandatory. This is in contrast to the guidance (above) on bibliographic database searching.

The issue for supplementary search methods is similar in many ways to the issue of searching bibliographic databases: demonstrating value. The purpose and contribution of supplementary search methods in systematic reviews is increasingly acknowledged [ 37 , 61 , 62 , 96 , 97 , 98 , 99 , 100 , 101 ] but understanding the value of the search methods to identify studies and data is unclear. In a recently published review, Cooper et al. (2017) reviewed the literature on supplementary search methods looking to determine the advantages, disadvantages and resource implications of using supplementary search methods [ 95 ]. This review also summarises the key guidance and empirical studies and seeks to address the question on when to use these search methods and when not to [ 95 ]. The guidance is limited in this regard and, as Table 2 demonstrates, offers conflicting advice on the order of searching, and the extent to which these search methods should be used in systematic reviews.

Key stage seven: Managing the references

Five of the documents provided guidance on managing references, for example downloading, de-duplicating and managing the output of literature searches [ 2 , 4 , 6 , 8 , 10 ]. This guidance typically itemised available bibliographic management tools rather than offering guidance on how to use them specifically [ 2 , 4 , 6 , 8 ]. The CEE handbook provided guidance on importing data where no direct export option is available (e.g. web-searching) [ 10 ].

The literature on using bibliographic management tools is not large relative to the number of ‘how to’ videos on platforms such as YouTube (see for example [ 102 ]). These YouTube videos confirm the overall lack of ‘how to’ guidance identified in this study and offer useful instruction on managing references. Bramer et al. set out methods for de-duplicating data and reviewing references in Endnote [ 103 , 104 ] and Gall tests the direct search function within Endnote to access databases such as PubMed, finding a number of limitations [ 105 ]. Coar et al. and Ahmed et al. consider the role of the free-source tool, Zotero [ 106 , 107 ]. Managing references is a key administrative function in the process of review particularly for documenting searches in PRISMA guidance.

Key stage eight: Documenting the search

The Cochrane Handbook was the only guidance document to recommend a specific reporting guideline: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 9 ]. Six documents provided guidance on reporting the process of literature searching with specific criteria to report [ 3 , 4 , 6 , 8 , 9 , 10 ]. There was consensus on reporting: the databases searched (and the host searched by), the search strategies used, and any use of limits (e.g. date, language, search filters (The CRD handbook called for these limits to be justified [ 6 ])). Three guidance documents reported that the number of studies identified should be recorded [ 3 , 6 , 10 ]. The number of duplicates identified [ 10 ], the screening decisions [ 3 ], a comprehensive list of grey literature sources searched (and full detail for other supplementary search methods) [ 8 ], and an annotation of search terms tested but not used [ 4 ] were identified as unique items in four documents.

The Cochrane Handbook was the only guidance document to note that the full search strategies for each database should be included in the Additional file 1 of the review [ 9 ].

All guidance documents should ultimately deliver completed systematic reviews that fulfil the requirements of the PRISMA reporting guidelines [ 108 ]. The guidance broadly requires the reporting of data that corresponds with the requirements of the PRISMA statement although documents typically ask for diverse and additional items [ 108 ]. In 2008, Sampson et al. observed a lack of consensus on reporting search methods in systematic reviews [ 109 ] and this remains the case as of 2017, as evidenced in the guidance documents, and in spite of the publication of the PRISMA guidelines in 2009 [ 110 ]. It is unclear why the collective guidance does not more explicitly endorse adherence to the PRISMA guidance.

Reporting of literature searching is a key area in systematic reviews since it sets out clearly what was done and how the conclusions of the review can be believed [ 52 , 109 ]. Despite strong endorsement in the guidance documents, specifically supported in PRISMA guidance, and other related reporting standards too (such as ENTREQ for qualitative evidence synthesis, STROBE for reviews of observational studies), authors still highlight the prevalence of poor standards of literature search reporting [ 31 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 ]. To explore issues experienced by authors in reporting literature searches, and look at uptake of PRISMA, Radar et al. [ 120 ] surveyed over 260 review authors to determine common problems and their work summaries the practical aspects of reporting literature searching [ 120 ]. Atkinson et al. [ 121 ] have also analysed reporting standards for literature searching, summarising recommendations and gaps for reporting search strategies [ 121 ].

One area that is less well covered by the guidance, but nevertheless appears in this literature, is the quality appraisal or peer review of literature search strategies. The PRESS checklist is the most prominent and it aims to develop evidence-based guidelines to peer review of electronic search strategies [ 5 , 122 , 123 ]. A corresponding guideline for documentation of supplementary search methods does not yet exist although this idea is currently being explored.

How the reporting of the literature searching process corresponds to critical appraisal tools is an area for further research. In the survey undertaken by Radar et al. (2014), 86% of survey respondents (153/178) identified a need for further guidance on what aspects of the literature search process to report [ 120 ]. The PRISMA statement offers a brief summary of what to report but little practical guidance on how to report it [ 108 ]. Critical appraisal tools for systematic reviews, such as AMSTAR 2 (Shea et al. [ 124 ]) and ROBIS (Whiting et al. [ 125 ]), can usefully be read alongside PRISMA guidance, since they offer greater detail on how the reporting of the literature search will be appraised and, therefore, they offer a proxy on what to report [ 124 , 125 ]. Further research in the form of a study which undertakes a comparison between PRISMA and quality appraisal checklists for systematic reviews would seem to begin addressing the call, identified by Radar et al., for further guidance on what to report [ 120 ].

Limitations

Other handbooks exist.

A potential limitation of this literature review is the focus on guidance produced in Europe (the UK specifically) and Australia. We justify the decision for our selection of the nine guidance documents reviewed in this literature review in section “ Identifying guidance ”. In brief, these nine guidance documents were selected as the most relevant health care guidance that inform UK systematic reviewing practice, given that the UK occupies a prominent position in the science of health information retrieval. We acknowledge the existence of other guidance documents, such as those from North America (e.g. the Agency for Healthcare Research and Quality (AHRQ) [ 126 ], The Institute of Medicine [ 127 ] and the guidance and resources produced by the Canadian Agency for Drugs and Technologies in Health (CADTH) [ 128 ]). We comment further on this directly below.

The handbooks are potentially linked to one another

What is not clear is the extent to which the guidance documents inter-relate or provide guidance uniquely. The Cochrane Handbook, first published in 1994, is notably a key source of reference in guidance and systematic reviews beyond Cochrane reviews. It is not clear to what extent broadening the sample of guidance handbooks to include North American handbooks, and guidance handbooks from other relevant countries too, would alter the findings of this literature review or develop further support for the process model. Since we cannot be clear, we raise this as a potential limitation of this literature review. On our initial review of a sample of North American, and other, guidance documents (before selecting the guidance documents considered in this review), however, we do not consider that the inclusion of these further handbooks would alter significantly the findings of this literature review.

This is a literature review

A further limitation of this review was that the review of published studies is not a systematic review of the evidence for each key stage. It is possible that other relevant studies could help contribute to the exploration and development of the key stages identified in this review.

This literature review would appear to demonstrate the existence of a shared model of the literature searching process in systematic reviews. We call this model ‘the conventional approach’, since it appears to be common convention in nine different guidance documents.

The findings reported above reveal eight key stages in the process of literature searching for systematic reviews. These key stages are consistently reported in the nine guidance documents which suggests consensus on the key stages of literature searching, and therefore the process of literature searching as a whole, in systematic reviews.

In Table 2 , we demonstrate consensus regarding the application of literature search methods. All guidance documents distinguish between primary and supplementary search methods. Bibliographic database searching is consistently the first method of literature searching referenced in each guidance document. Whilst the guidance uniformly supports the use of supplementary search methods, there is little evidence for a consistent process with diverse guidance across documents. This may reflect differences in the core focus across each document, linked to differences in identifying effectiveness studies or qualitative studies, for instance.

Eight of the nine guidance documents reported on the aims of literature searching. The shared understanding was that literature searching should be thorough and comprehensive in its aim and that this process should be reported transparently so that that it could be reproduced. Whilst only three documents explicitly link this understanding to minimising bias, it is clear that comprehensive literature searching is implicitly linked to ‘not missing relevant studies’ which is approximately the same point.

Defining the key stages in this review helps categorise the scholarship available, and it prioritises areas for development or further study. The supporting studies on preparing for literature searching (key stage three, ‘preparation’) were, for example, comparatively few, and yet this key stage represents a decisive moment in literature searching for systematic reviews. It is where search strategy structure is determined, search terms are chosen or discarded, and the resources to be searched are selected. Information specialists, librarians and researchers, are well placed to develop these and other areas within the key stages we identify.

This review calls for further research to determine the suitability of using the conventional approach. The publication dates of the guidance documents which underpin the conventional approach may raise questions as to whether the process which they each report remains valid for current systematic literature searching. In addition, it may be useful to test whether it is desirable to use the same process model of literature searching for qualitative evidence synthesis as that for reviews of intervention effectiveness, which this literature review demonstrates is presently recommended best practice.

Abbreviations

Behaviour of interest; Health context; Exclusions; Models or Theories

Cochrane Database of Systematic Reviews

The Cochrane Central Register of Controlled Trials

Database of Abstracts of Reviews of Effects

Enhancing transparency in reporting the synthesis of qualitative research

Institute for Quality and Efficiency in Healthcare

National Institute for Clinical Excellence

Population, Intervention, Comparator, Outcome

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Setting, Perspective, Intervention, Comparison, Evaluation

Sample, Phenomenon of Interest, Design, Evaluation, Research type

STrengthening the Reporting of OBservational studies in Epidemiology

Trial Search Co-ordinators

Booth A. Unpacking your literature search toolbox: on search styles and tactics. Health Information & Libraries Journal. 2008;25(4):313–7.

Article   Google Scholar  

Petticrew M, Roberts H. Systematic reviews in the social sciences: a practical guide. Oxford: Blackwell Publishing Ltd; 2006.

Book   Google Scholar  

Institute for Quality and Efficiency in Health Care (IQWiG). IQWiG Methods Resources. 7 Information retrieval 2014 [Available from: https://www.ncbi.nlm.nih.gov/books/NBK385787/ .

NICE: National Institute for Health and Care Excellence. Developing NICE guidelines: the manual 2014. Available from: https://www.nice.org.uk/media/default/about/what-we-do/our-programmes/developing-nice-guidelines-the-manual.pdf .

Sampson M. MJ, Lefebvre C, Moher D, Grimshaw J. Peer Review of Electronic Search Strategies: PRESS; 2008.

Google Scholar  

Centre for Reviews & Dissemination. Systematic reviews – CRD’s guidance for undertaking reviews in healthcare. York: Centre for Reviews and Dissemination, University of York; 2009.

eunetha: European Network for Health Technology Assesment Process of information retrieval for systematic reviews and health technology assessments on clinical effectiveness 2016. Available from: http://www.eunethta.eu/sites/default/files/Guideline_Information_Retrieval_V1-1.pdf .

Kugley SWA, Thomas J, Mahood Q, Jørgensen AMK, Hammerstrøm K, Sathe N. Searching for studies: a guide to information retrieval for Campbell systematic reviews. Oslo: Campbell Collaboration. 2017; Available from: https://www.campbellcollaboration.org/library/searching-for-studies-information-retrieval-guide-campbell-reviews.html

Lefebvre C, Manheimer E, Glanville J. Chapter 6: searching for studies. In: JPT H, Green S, editors. Cochrane Handbook for Systematic Reviews of Interventions; 2011.

Collaboration for Environmental Evidence. Guidelines for Systematic Review and Evidence Synthesis in Environmental Management.: Environmental Evidence:; 2013. Available from: http://www.environmentalevidence.org/wp-content/uploads/2017/01/Review-guidelines-version-4.2-final-update.pdf .

The Joanna Briggs Institute. Joanna Briggs institute reviewers’ manual. 2014th ed: the Joanna Briggs institute; 2014. Available from: https://joannabriggs.org/assets/docs/sumari/ReviewersManual-2014.pdf

Beverley CA, Booth A, Bath PA. The role of the information specialist in the systematic review process: a health information case study. Health Inf Libr J. 2003;20(2):65–74.

Article   CAS   Google Scholar  

Harris MR. The librarian's roles in the systematic review process: a case study. Journal of the Medical Library Association. 2005;93(1):81–7.

PubMed   PubMed Central   Google Scholar  

Egger JB. Use of recommended search strategies in systematic reviews and the impact of librarian involvement: a cross-sectional survey of recent authors. PLoS One. 2015;10(5):e0125931.

Li L, Tian J, Tian H, Moher D, Liang F, Jiang T, et al. Network meta-analyses could be improved by searching more sources and by involving a librarian. J Clin Epidemiol. 2014;67(9):1001–7.

Article   PubMed   Google Scholar  

McGowan J, Sampson M. Systematic reviews need systematic searchers. J Med Libr Assoc. 2005;93(1):74–80.

Rethlefsen ML, Farrell AM, Osterhaus Trzasko LC, Brigham TJ. Librarian co-authors correlated with higher quality reported search strategies in general internal medicine systematic reviews. J Clin Epidemiol. 2015;68(6):617–26.

Weller AC. Mounting evidence that librarians are essential for comprehensive literature searches for meta-analyses and Cochrane reports. J Med Libr Assoc. 2004;92(2):163–4.

Swinkels A, Briddon J, Hall J. Two physiotherapists, one librarian and a systematic literature review: collaboration in action. Health Info Libr J. 2006;23(4):248–56.

Foster M. An overview of the role of librarians in systematic reviews: from expert search to project manager. EAHIL. 2015;11(3):3–7.

Lawson L. OPERATING OUTSIDE LIBRARY WALLS 2004.

Vassar M, Yerokhin V, Sinnett PM, Weiher M, Muckelrath H, Carr B, et al. Database selection in systematic reviews: an insight through clinical neurology. Health Inf Libr J. 2017;34(2):156–64.

Townsend WA, Anderson PF, Ginier EC, MacEachern MP, Saylor KM, Shipman BL, et al. A competency framework for librarians involved in systematic reviews. Journal of the Medical Library Association : JMLA. 2017;105(3):268–75.

Cooper ID, Crum JA. New activities and changing roles of health sciences librarians: a systematic review, 1990-2012. Journal of the Medical Library Association : JMLA. 2013;101(4):268–77.

Crum JA, Cooper ID. Emerging roles for biomedical librarians: a survey of current practice, challenges, and changes. Journal of the Medical Library Association : JMLA. 2013;101(4):278–86.

Dudden RF, Protzko SL. The systematic review team: contributions of the health sciences librarian. Med Ref Serv Q. 2011;30(3):301–15.

Golder S, Loke Y, McIntosh HM. Poor reporting and inadequate searches were apparent in systematic reviews of adverse effects. J Clin Epidemiol. 2008;61(5):440–8.

Maggio LA, Tannery NH, Kanter SL. Reproducibility of literature search reporting in medical education reviews. Academic medicine : journal of the Association of American Medical Colleges. 2011;86(8):1049–54.

Meert D, Torabi N, Costella J. Impact of librarians on reporting of the literature searching component of pediatric systematic reviews. Journal of the Medical Library Association : JMLA. 2016;104(4):267–77.

Morris M, Boruff JT, Gore GC. Scoping reviews: establishing the role of the librarian. Journal of the Medical Library Association : JMLA. 2016;104(4):346–54.

Koffel JB, Rethlefsen ML. Reproducibility of search strategies is poor in systematic reviews published in high-impact pediatrics, cardiology and surgery journals: a cross-sectional study. PLoS One. 2016;11(9):e0163309.

Article   PubMed   PubMed Central   CAS   Google Scholar  

Fehrmann P, Thomas J. Comprehensive computer searches and reporting in systematic reviews. Research Synthesis Methods. 2011;2(1):15–32.

Booth A. Searching for qualitative research for inclusion in systematic reviews: a structured methodological review. Systematic Reviews. 2016;5(1):74.

Article   PubMed   PubMed Central   Google Scholar  

Egger M, Juni P, Bartlett C, Holenstein F, Sterne J. How important are comprehensive literature searches and the assessment of trial quality in systematic reviews? Empirical study. Health technology assessment (Winchester, England). 2003;7(1):1–76.

Tricco AC, Tetzlaff J, Sampson M, Fergusson D, Cogo E, Horsley T, et al. Few systematic reviews exist documenting the extent of bias: a systematic review. J Clin Epidemiol. 2008;61(5):422–34.

Booth A. How much searching is enough? Comprehensive versus optimal retrieval for technology assessments. Int J Technol Assess Health Care. 2010;26(4):431–5.

Papaioannou D, Sutton A, Carroll C, Booth A, Wong R. Literature searching for social science systematic reviews: consideration of a range of search techniques. Health Inf Libr J. 2010;27(2):114–22.

Petticrew M. Time to rethink the systematic review catechism? Moving from ‘what works’ to ‘what happens’. Systematic Reviews. 2015;4(1):36.

Betrán AP, Say L, Gülmezoglu AM, Allen T, Hampson L. Effectiveness of different databases in identifying studies for systematic reviews: experience from the WHO systematic review of maternal morbidity and mortality. BMC Med Res Methodol. 2005;5

Felson DT. Bias in meta-analytic research. J Clin Epidemiol. 1992;45(8):885–92.

Article   PubMed   CAS   Google Scholar  

Franco A, Malhotra N, Simonovits G. Publication bias in the social sciences: unlocking the file drawer. Science. 2014;345(6203):1502–5.

Hartling L, Featherstone R, Nuspl M, Shave K, Dryden DM, Vandermeer B. Grey literature in systematic reviews: a cross-sectional study of the contribution of non-English reports, unpublished studies and dissertations to the results of meta-analyses in child-relevant reviews. BMC Med Res Methodol. 2017;17(1):64.

Schmucker CM, Blümle A, Schell LK, Schwarzer G, Oeller P, Cabrera L, et al. Systematic review finds that study data not published in full text articles have unclear impact on meta-analyses results in medical research. PLoS One. 2017;12(4):e0176210.

Egger M, Zellweger-Zahner T, Schneider M, Junker C, Lengeler C, Antes G. Language bias in randomised controlled trials published in English and German. Lancet (London, England). 1997;350(9074):326–9.

Moher D, Pham B, Lawson ML, Klassen TP. The inclusion of reports of randomised trials published in languages other than English in systematic reviews. Health technology assessment (Winchester, England). 2003;7(41):1–90.

Pham B, Klassen TP, Lawson ML, Moher D. Language of publication restrictions in systematic reviews gave different results depending on whether the intervention was conventional or complementary. J Clin Epidemiol. 2005;58(8):769–76.

Mills EJ, Kanters S, Thorlund K, Chaimani A, Veroniki A-A, Ioannidis JPA. The effects of excluding treatments from network meta-analyses: survey. BMJ : British Medical Journal. 2013;347

Hartling L, Featherstone R, Nuspl M, Shave K, Dryden DM, Vandermeer B. The contribution of databases to the results of systematic reviews: a cross-sectional study. BMC Med Res Methodol. 2016;16(1):127.

van Driel ML, De Sutter A, De Maeseneer J, Christiaens T. Searching for unpublished trials in Cochrane reviews may not be worth the effort. J Clin Epidemiol. 2009;62(8):838–44.e3.

Buchberger B, Krabbe L, Lux B, Mattivi JT. Evidence mapping for decision making: feasibility versus accuracy - when to abandon high sensitivity in electronic searches. German medical science : GMS e-journal. 2016;14:Doc09.

Lorenc T, Pearson M, Jamal F, Cooper C, Garside R. The role of systematic reviews of qualitative evidence in evaluating interventions: a case study. Research Synthesis Methods. 2012;3(1):1–10.

Gough D. Weight of evidence: a framework for the appraisal of the quality and relevance of evidence. Res Pap Educ. 2007;22(2):213–28.

Barroso J, Gollop CJ, Sandelowski M, Meynell J, Pearce PF, Collins LJ. The challenges of searching for and retrieving qualitative studies. West J Nurs Res. 2003;25(2):153–78.

Britten N, Garside R, Pope C, Frost J, Cooper C. Asking more of qualitative synthesis: a response to Sally Thorne. Qual Health Res. 2017;27(9):1370–6.

Booth A, Carroll C. Systematic searching for theory to inform systematic reviews: is it feasible? Is it desirable? Health Info Libr J. 2015;32(3):220–35.

Kwon Y, Powelson SE, Wong H, Ghali WA, Conly JM. An assessment of the efficacy of searching in biomedical databases beyond MEDLINE in identifying studies for a systematic review on ward closures as an infection control intervention to control outbreaks. Syst Rev. 2014;3:135.

Nussbaumer-Streit B, Klerings I, Wagner G, Titscher V, Gartlehner G. Assessing the validity of abbreviated literature searches for rapid reviews: protocol of a non-inferiority and meta-epidemiologic study. Systematic Reviews. 2016;5:197.

Wagner G, Nussbaumer-Streit B, Greimel J, Ciapponi A, Gartlehner G. Trading certainty for speed - how much uncertainty are decisionmakers and guideline developers willing to accept when using rapid reviews: an international survey. BMC Med Res Methodol. 2017;17(1):121.

Ogilvie D, Hamilton V, Egan M, Petticrew M. Systematic reviews of health effects of social interventions: 1. Finding the evidence: how far should you go? J Epidemiol Community Health. 2005;59(9):804–8.

Royle P, Milne R. Literature searching for randomized controlled trials used in Cochrane reviews: rapid versus exhaustive searches. Int J Technol Assess Health Care. 2003;19(4):591–603.

Pearson M, Moxham T, Ashton K. Effectiveness of search strategies for qualitative research about barriers and facilitators of program delivery. Eval Health Prof. 2011;34(3):297–308.

Levay P, Raynor M, Tuvey D. The Contributions of MEDLINE, Other Bibliographic Databases and Various Search Techniques to NICE Public Health Guidance. 2015. 2015;10(1):19.

Nussbaumer-Streit B, Klerings I, Wagner G, Heise TL, Dobrescu AI, Armijo-Olivo S, et al. Abbreviated literature searches were viable alternatives to comprehensive searches: a meta-epidemiological study. J Clin Epidemiol. 2018;102:1–11.

Briscoe S, Cooper C, Glanville J, Lefebvre C. The loss of the NHS EED and DARE databases and the effect on evidence synthesis and evaluation. Res Synth Methods. 2017;8(3):256–7.

Stansfield C, O'Mara-Eves A, Thomas J. Text mining for search term development in systematic reviewing: A discussion of some methods and challenges. Research Synthesis Methods.n/a-n/a.

Petrova M, Sutcliffe P, Fulford KW, Dale J. Search terms and a validated brief search filter to retrieve publications on health-related values in Medline: a word frequency analysis study. Journal of the American Medical Informatics Association : JAMIA. 2012;19(3):479–88.

Stansfield C, Thomas J, Kavanagh J. 'Clustering' documents automatically to support scoping reviews of research: a case study. Res Synth Methods. 2013;4(3):230–41.

PubMed   Google Scholar  

Methley AM, Campbell S, Chew-Graham C, McNally R, Cheraghi-Sohi S. PICO, PICOS and SPIDER: a comparison study of specificity and sensitivity in three search tools for qualitative systematic reviews. BMC Health Serv Res. 2014;14:579.

Andrew B. Clear and present questions: formulating questions for evidence based practice. Library Hi Tech. 2006;24(3):355–68.

Cooke A, Smith D, Booth A. Beyond PICO: the SPIDER tool for qualitative evidence synthesis. Qual Health Res. 2012;22(10):1435–43.

Whiting P, Westwood M, Bojke L, Palmer S, Richardson G, Cooper J, et al. Clinical effectiveness and cost-effectiveness of tests for the diagnosis and investigation of urinary tract infection in children: a systematic review and economic model. Health technology assessment (Winchester, England). 2006;10(36):iii-iv, xi-xiii, 1–154.

Cooper C, Levay P, Lorenc T, Craig GM. A population search filter for hard-to-reach populations increased search efficiency for a systematic review. J Clin Epidemiol. 2014;67(5):554–9.

Hausner E, Waffenschmidt S, Kaiser T, Simon M. Routine development of objectively derived search strategies. Systematic Reviews. 2012;1(1):19.

Hausner E, Guddat C, Hermanns T, Lampert U, Waffenschmidt S. Prospective comparison of search strategies for systematic reviews: an objective approach yielded higher sensitivity than a conceptual one. J Clin Epidemiol. 2016;77:118–24.

Craven J, Levay P. Recording database searches for systematic reviews - what is the value of adding a narrative to peer-review checklists? A case study of nice interventional procedures guidance. Evid Based Libr Inf Pract. 2011;6(4):72–87.

Wright K, Golder S, Lewis-Light K. What value is the CINAHL database when searching for systematic reviews of qualitative studies? Syst Rev. 2015;4:104.

Beckles Z, Glover S, Ashe J, Stockton S, Boynton J, Lai R, et al. Searching CINAHL did not add value to clinical questions posed in NICE guidelines. J Clin Epidemiol. 2013;66(9):1051–7.

Cooper C, Rogers M, Bethel A, Briscoe S, Lowe J. A mapping review of the literature on UK-focused health and social care databases. Health Inf Libr J. 2015;32(1):5–22.

Younger P, Boddy K. When is a search not a search? A comparison of searching the AMED complementary health database via EBSCOhost, OVID and DIALOG. Health Inf Libr J. 2009;26(2):126–35.

Lam MT, McDiarmid M. Increasing number of databases searched in systematic reviews and meta-analyses between 1994 and 2014. Journal of the Medical Library Association : JMLA. 2016;104(4):284–9.

Bethel A, editor Search summary tables for systematic reviews: results and findings. HLC Conference 2017a.

Aagaard T, Lund H, Juhl C. Optimizing literature search in systematic reviews - are MEDLINE, EMBASE and CENTRAL enough for identifying effect studies within the area of musculoskeletal disorders? BMC Med Res Methodol. 2016;16(1):161.

Adams CE, Frederick K. An investigation of the adequacy of MEDLINE searches for randomized controlled trials (RCTs) of the effects of mental health care. Psychol Med. 1994;24(3):741–8.

Kelly L, St Pierre-Hansen N. So many databases, such little clarity: searching the literature for the topic aboriginal. Canadian family physician Medecin de famille canadien. 2008;54(11):1572–3.

Lawrence DW. What is lost when searching only one literature database for articles relevant to injury prevention and safety promotion? Injury Prevention. 2008;14(6):401–4.

Lemeshow AR, Blum RE, Berlin JA, Stoto MA, Colditz GA. Searching one or two databases was insufficient for meta-analysis of observational studies. J Clin Epidemiol. 2005;58(9):867–73.

Sampson M, Barrowman NJ, Moher D, Klassen TP, Pham B, Platt R, et al. Should meta-analysts search Embase in addition to Medline? J Clin Epidemiol. 2003;56(10):943–55.

Stevinson C, Lawlor DA. Searching multiple databases for systematic reviews: added value or diminishing returns? Complementary Therapies in Medicine. 2004;12(4):228–32.

Suarez-Almazor ME, Belseck E, Homik J, Dorgan M, Ramos-Remus C. Identifying clinical trials in the medical literature with electronic databases: MEDLINE alone is not enough. Control Clin Trials. 2000;21(5):476–87.

Taylor B, Wylie E, Dempster M, Donnelly M. Systematically retrieving research: a case study evaluating seven databases. Res Soc Work Pract. 2007;17(6):697–706.

Beyer FR, Wright K. Can we prioritise which databases to search? A case study using a systematic review of frozen shoulder management. Health Info Libr J. 2013;30(1):49–58.

Duffy S, de Kock S, Misso K, Noake C, Ross J, Stirk L. Supplementary searches of PubMed to improve currency of MEDLINE and MEDLINE in-process searches via Ovid. Journal of the Medical Library Association : JMLA. 2016;104(4):309–12.

Katchamart W, Faulkner A, Feldman B, Tomlinson G, Bombardier C. PubMed had a higher sensitivity than Ovid-MEDLINE in the search for systematic reviews. J Clin Epidemiol. 2011;64(7):805–7.

Cooper C, Lovell R, Husk K, Booth A, Garside R. Supplementary search methods were more effective and offered better value than bibliographic database searching: a case study from public health and environmental enhancement (in Press). Research Synthesis Methods. 2017;

Cooper C, Booth, A., Britten, N., Garside, R. A comparison of results of empirical studies of supplementary search techniques and recommendations in review methodology handbooks: A methodological review. (In Press). BMC Systematic Reviews. 2017.

Greenhalgh T, Peacock R. Effectiveness and efficiency of search methods in systematic reviews of complex evidence: audit of primary sources. BMJ (Clinical research ed). 2005;331(7524):1064–5.

Article   PubMed Central   Google Scholar  

Hinde S, Spackman E. Bidirectional citation searching to completion: an exploration of literature searching methods. PharmacoEconomics. 2015;33(1):5–11.

Levay P, Ainsworth N, Kettle R, Morgan A. Identifying evidence for public health guidance: a comparison of citation searching with web of science and Google scholar. Res Synth Methods. 2016;7(1):34–45.

McManus RJ, Wilson S, Delaney BC, Fitzmaurice DA, Hyde CJ, Tobias RS, et al. Review of the usefulness of contacting other experts when conducting a literature search for systematic reviews. BMJ (Clinical research ed). 1998;317(7172):1562–3.

Westphal A, Kriston L, Holzel LP, Harter M, von Wolff A. Efficiency and contribution of strategies for finding randomized controlled trials: a case study from a systematic review on therapeutic interventions of chronic depression. Journal of public health research. 2014;3(2):177.

Matthews EJ, Edwards AG, Barker J, Bloor M, Covey J, Hood K, et al. Efficient literature searching in diffuse topics: lessons from a systematic review of research on communicating risk to patients in primary care. Health Libr Rev. 1999;16(2):112–20.

Bethel A. Endnote Training (YouTube Videos) 2017b [Available from: http://medicine.exeter.ac.uk/esmi/workstreams/informationscience/is_resources,_guidance_&_advice/ .

Bramer WM, Giustini D, de Jonge GB, Holland L, Bekhuis T. De-duplication of database search results for systematic reviews in EndNote. Journal of the Medical Library Association : JMLA. 2016;104(3):240–3.

Bramer WM, Milic J, Mast F. Reviewing retrieved references for inclusion in systematic reviews using EndNote. Journal of the Medical Library Association : JMLA. 2017;105(1):84–7.

Gall C, Brahmi FA. Retrieval comparison of EndNote to search MEDLINE (Ovid and PubMed) versus searching them directly. Medical reference services quarterly. 2004;23(3):25–32.

Ahmed KK, Al Dhubaib BE. Zotero: a bibliographic assistant to researcher. J Pharmacol Pharmacother. 2011;2(4):303–5.

Coar JT, Sewell JP. Zotero: harnessing the power of a personal bibliographic manager. Nurse Educ. 2010;35(5):205–7.

Moher D, Liberati A, Tetzlaff J, Altman DG, The PG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.

Sampson M, McGowan J, Tetzlaff J, Cogo E, Moher D. No consensus exists on search reporting methods for systematic reviews. J Clin Epidemiol. 2008;61(8):748–54.

Toews LC. Compliance of systematic reviews in veterinary journals with preferred reporting items for systematic reviews and meta-analysis (PRISMA) literature search reporting guidelines. Journal of the Medical Library Association : JMLA. 2017;105(3):233–9.

Booth A. "brimful of STARLITE": toward standards for reporting literature searches. Journal of the Medical Library Association : JMLA. 2006;94(4):421–9. e205

Faggion CM Jr, Wu YC, Tu YK, Wasiak J. Quality of search strategies reported in systematic reviews published in stereotactic radiosurgery. Br J Radiol. 2016;89(1062):20150878.

Mullins MM, DeLuca JB, Crepaz N, Lyles CM. Reporting quality of search methods in systematic reviews of HIV behavioral interventions (2000–2010): are the searches clearly explained, systematic and reproducible? Research Synthesis Methods. 2014;5(2):116–30.

Yoshii A, Plaut DA, McGraw KA, Anderson MJ, Wellik KE. Analysis of the reporting of search strategies in Cochrane systematic reviews. Journal of the Medical Library Association : JMLA. 2009;97(1):21–9.

Bigna JJ, Um LN, Nansseu JR. A comparison of quality of abstracts of systematic reviews including meta-analysis of randomized controlled trials in high-impact general medicine journals before and after the publication of PRISMA extension for abstracts: a systematic review and meta-analysis. Syst Rev. 2016;5(1):174.

Akhigbe T, Zolnourian A, Bulters D. Compliance of systematic reviews articles in brain arteriovenous malformation with PRISMA statement guidelines: review of literature. Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia. 2017;39:45–8.

Tao KM, Li XQ, Zhou QH, Moher D, Ling CQ, Yu WF. From QUOROM to PRISMA: a survey of high-impact medical journals' instructions to authors and a review of systematic reviews in anesthesia literature. PLoS One. 2011;6(11):e27611.

Wasiak J, Tyack Z, Ware R. Goodwin N. Jr. Poor methodological quality and reporting standards of systematic reviews in burn care management. International wound journal: Faggion CM; 2016.

Tam WW, Lo KK, Khalechelvam P. Endorsement of PRISMA statement and quality of systematic reviews and meta-analyses published in nursing journals: a cross-sectional study. BMJ Open. 2017;7(2):e013905.

Rader T, Mann M, Stansfield C, Cooper C, Sampson M. Methods for documenting systematic review searches: a discussion of common issues. Res Synth Methods. 2014;5(2):98–115.

Atkinson KM, Koenka AC, Sanchez CE, Moshontz H, Cooper H. Reporting standards for literature searches and report inclusion criteria: making research syntheses more transparent and easy to replicate. Res Synth Methods. 2015;6(1):87–95.

McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS peer review of electronic search strategies: 2015 guideline statement. J Clin Epidemiol. 2016;75:40–6.

Sampson M, McGowan J, Cogo E, Grimshaw J, Moher D, Lefebvre C. An evidence-based practice guideline for the peer review of electronic search strategies. J Clin Epidemiol. 2009;62(9):944–52.

Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ (Clinical research ed). 2017;358.

Whiting P, Savović J, Higgins JPT, Caldwell DM, Reeves BC, Shea B, et al. ROBIS: a new tool to assess risk of bias in systematic reviews was developed. J Clin Epidemiol. 2016;69:225–34.

Relevo R, Balshem H. Finding evidence for comparing medical interventions: AHRQ and the effective health care program. J Clin Epidemiol. 2011;64(11):1168–77.

Medicine Io. Standards for Systematic Reviews 2011 [Available from: http://www.nationalacademies.org/hmd/Reports/2011/Finding-What-Works-in-Health-Care-Standards-for-Systematic-Reviews/Standards.aspx .

CADTH: Resources 2018.

Download references

Acknowledgements

CC acknowledges the supervision offered by Professor Chris Hyde.

This publication forms a part of CC’s PhD. CC’s PhD was funded through the National Institute for Health Research (NIHR) Health Technology Assessment (HTA) Programme (Project Number 16/54/11). The open access fee for this publication was paid for by Exeter Medical School.

RG and NB were partially supported by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South West Peninsula.

The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.

Author information

Authors and affiliations.

Institute of Health Research, University of Exeter Medical School, Exeter, UK

Chris Cooper & Jo Varley-Campbell

HEDS, School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK

Andrew Booth

Nicky Britten

European Centre for Environment and Human Health, University of Exeter Medical School, Truro, UK

Ruth Garside

You can also search for this author in PubMed   Google Scholar

Contributions

CC conceived the idea for this study and wrote the first draft of the manuscript. CC discussed this publication in PhD supervision with AB and separately with JVC. CC revised the publication with input and comments from AB, JVC, RG and NB. All authors revised the manuscript prior to submission. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Chris Cooper .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare that they have no competing interests.

Publisher’s Note

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

Additional file

Additional file 1:.

Appendix tables and PubMed search strategy. Key studies used for pearl growing per key stage, working data extraction tables and the PubMed search strategy. (DOCX 30 kb)

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Cite this article.

Cooper, C., Booth, A., Varley-Campbell, J. et al. Defining the process to literature searching in systematic reviews: a literature review of guidance and supporting studies. BMC Med Res Methodol 18 , 85 (2018). https://doi.org/10.1186/s12874-018-0545-3

Download citation

Received : 20 September 2017

Accepted : 06 August 2018

Published : 14 August 2018

DOI : https://doi.org/10.1186/s12874-018-0545-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Literature Search Process
• Citation Chasing
• Tacit Models
• Unique Guidance
• Information Specialists

BMC Medical Research Methodology

ISSN: 1471-2288

• General enquiries: [email protected]

How to undertake a literature search: a step-by-step guide

Affiliation.

• 1 Literature Search Specialist, Library and Archive Service, Royal College of Nursing, London.
• PMID: 32279549
• DOI: 10.12968/bjon.2020.29.7.431

Undertaking a literature search can be a daunting prospect. Breaking the exercise down into smaller steps will make the process more manageable. This article suggests 10 steps that will help readers complete this task, from identifying key concepts to choosing databases for the search and saving the results and search strategy. It discusses each of the steps in a little more detail, with examples and suggestions on where to get help. This structured approach will help readers obtain a more focused set of results and, ultimately, save time and effort.

Keywords: Databases; Literature review; Literature search; Reference management software; Research questions; Search strategy.

• Databases, Bibliographic*
• Information Storage and Retrieval / methods*
• Nursing Research
• Review Literature as Topic*

• Interlibrary Loan

Ask an Expert

Ask an expert about access to resources, publishing, grants, and more.

MD Anderson faculty and staff can also request a one-on-one consultation with a librarian or scientific editor.

• Library Calendar

Log in to the Library's remote access system using your MyID account.

• Library Home
• Research Guides

Literature Search Basics

Develop a search strategy.

• Define your search
• Decide where to search

What is a search strategy

Advanced search tips.

• Track and save your search
• Class Recording: Writing an Effective Narrative Review
• A search strategy includes  a combination of keywords, subject headings, and limiters (language, date, publication type, etc.)
• A search strategy should be planned out and practiced before executing the final search in a database.
• A search strategy and search results should be documented throughout the searching process.

What is a search strategy?

A search strategy is an organized combination of keywords, phrases, subject headings, and limiters used to search a database.

Your search strategy will include:

• keywords 
• boolean operators
• variations of search terms (synonyms, suffixes)
• subject headings 

Your search strategy  may  include:

• truncation (where applicable)
• phrases (where applicable)
• limiters (date, language, age, publication type, etc.)

A search strategy usually requires several iterations. You will need to test the strategy along the way to ensure that you are finding relevant articles. It's also a good idea to review your search strategy with your co-authors. They may have ideas about terms or concepts you may have missed.

Additionally, each database you search is developed differently. You will need to adjust your strategy for each database your search.  For instance, Embase is a European database, many of the medical terms are slightly different than those used in MEDLINE and PubMed.

Choose search terms

Start by writing down as many terms as you can think of that relate to your question. You might try  cited reference searching  to find a few good articles that you can review for relevant terms.

Remember than most terms or  concepts can be expressed in different ways.  A few things to consider:

• synonyms: "cancer" may be referred to as "neoplasms", "tumors", or "malignancy"
• abbreviations: spell out the word instead of abbreviating
• generic vs. trade names of drugs

Search for the exact phrase

If you want words to appear next to each other in an exact phrase, use quotation marks, eg “self-esteem”.

Phrase searching decreases the number of results you get. Most databases allow you to search for phrases, but check the database guide if you are unsure.

Truncation and wildcards

Many databases use an asterisk (*) as their truncation symbol  to find various word endings like singulars and plurals.  Check the database help section if you are not sure which symbol to use. 

"Therap*"

retrieves: therapy, therapies, therapist or therapists.

Use a wildcard (?) to find different spellings like British and American spellings.

"Behavio?r" retrieves behaviour and behavior.

Searching with subject headings

Database subject headings are controlled vocabulary terms that a database uses to describe what an article is about.

Using appropriate subject headings enhances your search and will help you to find more results on your topic. This is because subject headings find articles according to their subject, even if the article does not use your chosen key words.

You should combine both subject headings and keywords in your search strategy for each of the concepts you identify. This is particularly important if you are undertaking a systematic review or an in-depth piece of work

Subject headings may vary between databases, so you need to investigate each database separately to find the subject headings they use. For example, for MEDLINE you can use MeSH (Medical Subject Headings) and for Embase you can use the EMTREE thesaurus.

SEARCH TIP:  In Ovid databases, search for a known key paper by title, select the "complete reference" button to see which subject headings the database indexers have given that article, and consider adding relevant ones to your own search strategy.

Use Boolean logic to combine search terms

Boolean operators (AND, OR and NOT) allow you to try different combinations of search terms or subject headings.

Databases often show Boolean operators as buttons or drop-down menus that you can click to combine your search terms or results.

The main Boolean operators are:

OR is used to find articles that mention  either  of the topics you search for.

AND is used to find articles that mention  both  of the searched topics.

NOT excludes a search term or concept. It should be used with caution as you may inadvertently exclude relevant references.

For example, searching for “self-esteem NOT eating disorders” finds articles that mention self-esteem but removes any articles that mention eating disorders.

Adjacency searching 

Use adjacency operators to search by phrase or with two or more words in relation to one another. A djacency searching commands differ among databases. Check the database help section if you are not sure which searching commands to use. 

In Ovid Medline

"breast ADJ3 cancer" finds the word breast within three words of cancer, in any order.

This includes breast cancer or cancer of the breast.

Cited Reference Searching

Cited reference searching is a method to find articles that have been cited by other publications. 

Use cited reference searching to:

• find keywords or terms you may need to include in your search strategy
• find pivotal papers the same or similar subject area
• find pivotal authors in the same or similar subject area
• track how a topic has developed over time

Cited reference searching is available through these tools:

• Web of Science
• GoogleScholar
• << Previous: Decide where to search
• Next: Track and save your search >>
• Last Updated: Nov 29, 2022 3:34 PM
• URL: https://mdanderson.libguides.com/literaturesearchbasics

Covidence website will be inaccessible as we upgrading our platform on Monday 23rd August at 10am AEST, / 2am CEST/1am BST (Sunday, 15th August 8pm EDT/5pm PDT) 

How to write a search strategy for your systematic review

Home | Blog | How To | How to write a search strategy for your systematic review

Practical tips to write a search strategy for your systematic review

With a great review question and a clear set of eligibility criteria already mapped out, it’s now time to plan the search strategy. The medical literature is vast. Your team plans a thorough and methodical search, but you also know that resources and interest in the project are finite. At this stage it might feel like you have a mountain to climb.

The bottom line? You will have to sift through some irrelevant search results to find the studies that you need for your review. Capturing a proportion of irrelevant records in your search is necessary to ensure that it identifies as many relevant records as possible. This is the trade-off of precision versus sensitivity and, because systematic reviews aim to be as comprehensive as possible, it is best to favour sensitivity – more is more.

By now, the size of this task might be sounding alarm bells. The good news is that a range of techniques and web-based tools can help to make searching more efficient and save you time. We’ll look at some of them as we walk through the four main steps of searching for studies:

• Decide where to search
• Write and refine the search
• Run and record the search
• Manage the search results

Searching is a specialist discipline and the information given here is not intended to replace the advice of a skilled professional. Before we look at each of the steps in turn, the most important systematic reviewer pro-tip for searching is:

 Pro Tip – Talk to your librarian and do it early!

1. decide where to search .

It’s important to come up with a comprehensive list of sources to search so that you don’t miss anything potentially relevant. In clinical medicine, your first stop will likely be the databases MEDLINE , Embase , and CENTRAL . Depending on the subject of the review, it might also be appropriate to run the search in databases that cover specific geographical regions or specialist areas, such as traditional Chinese medicine.

In addition to these databases, you’ll also search for grey literature (essentially, research that was not published in journals). That’s because your search of bibliographic databases will not find relevant information if it is part of, for example:

• a trials register
• a study that is ongoing
• a thesis or dissertation
• a conference abstract.

Over-reliance on published data introduces bias in favour of positive results. Studies with positive results are more likely to be submitted to journals, published in journals, and therefore indexed in databases. This is publication bias and systematic reviews seek to minimise its effects by searching for grey literature.

2. Write and refine the search 

Search terms are derived from key concepts in the review question and from the inclusion and exclusion criteria that are specified in the protocol or research plan.

Keywords will be searched for in the title or abstract of the records in the database. They are often truncated (for example, a search for therap* to find therapy, therapies, therapist). They might also use wildcards to allow for spelling variants and plurals (for example, wom#n to find woman and women). The symbols used to perform truncation and wildcard searches vary by database.

Index terms  

Using index terms such as MeSH and Emtree in a search can improve its performance. Indexers with subject area expertise work through databases and tag each record with subject terms from a prespecified controlled vocabulary.

This indexing can save review teams a lot of time that would otherwise be spent sifting through irrelevant records. Using index terms in your search, for example, can help you find the records that are actually about the topic of interest (tagged with the index term) but ignore those that contain only a brief mention of it (not tagged with the index term).

Indexers assign terms based on a careful read of each study, rather than whether or not the study contains certain words. So the index terms enable the retrieval of relevant records that cannot be captured by a simple search for the keyword or phrase.

Use a combination

Relying solely on index terms is not advisable. Doing so could miss a relevant record that for some reason (indexer’s judgment, time lag between a record being listed in a database and being indexed) has not been tagged with an index term that would enable you to retrieve it. Good search strategies include both index terms and keywords.

Let’s see how this works in a real review! Figure 2 shows the search strategy for the review ‘Wheat flour fortification with iron and other micronutrients for reducing anaemia and improving iron status in populations’. This strategy combines index terms and keywords using the Boolean operators AND, OR, and NOT. OR is used first to reach as many records as possible before AND and NOT are used to narrow them down.

• Lines 1 and 2: contain MeSH terms (denoted by the initial capitals and the slash at the end).
• Line 3: contains truncated keywords (‘tw’ in this context is an instruction to search the title and abstract fields of the record).
• Line 4: combines the three previous lines using Boolean OR to broaden the search.
• Line 11: combines previous lines using Boolean AND to narrow the search.
• Lines 12 and 13: further narrow the search using Boolean NOT to exclude records of studies with no human subjects.

Writing a search strategy is an iterative process. A good plan is  to try out a new strategy and check that it has picked up the key studies that you would expect it to find based on your existing knowledge of the topic area. If it hasn’t, you can explore the reasons for this, revise the strategy, check it for errors, and try it again!

3. Run and record the search

Because of the different ways that individual databases are structured and indexed, a separate search strategy is needed for each database. This adds complexity to the search process, and it is important to keep a careful record of each search strategy as you run it. Search strategies can often be saved in the databases themselves, but it is a good idea to keep an offline copy as a back-up; Covidence allows you to store your search strategies online in your review settings.

The reporting of the search will be included in the methods section of your review and should follow the PRISMA guidelines. You can download a flow diagram from PRISMA’s website to help you log the number of records retrieved from the search and the subsequent decisions about the inclusion or exclusion of studies. The PRISMA-S extension provides guidance on reporting literature searches.

It is very important that search strategies are reproduced in their entirety (preferably using copy and paste to avoid typos) as part of the published review so that they can be studied and replicated by other researchers. Search strategies are often made available as an appendix because they are long and might otherwise interrupt the flow of the text in the methods section.

4. Manage the search results 

Once the search is done and you have recorded the process in enough detail to write up a thorough description in the methods section, you will move on to screening the results. This is an exciting stage in any review because it’s the first glimpse of what the search strategies have found. A large volume of results may be daunting but your search is very likely to have captured some irrelevant studies because of its high sensitivity, as we have already seen. Fortunately, it will be possible to exclude many of these irrelevant studies at the screening stage on the basis of the title and abstract alone 😅.

Search results from multiple databases can be collated in a single spreadsheet for screening. To benefit from process efficiencies, time-saving and easy collaboration with your team, you can import search results into a specialist tool such as Covidence. A key benefit of Covidence is that you can track decisions made about the inclusion or exclusion of studies in a simple workflow and resolve conflicting decisions quickly and transparently. Covidence currently supports three formats for file imports of search results:

• EndNote XML
• PubMed text format
• RIS text format

If you’d like to try this feature of Covidence but don’t have any data yet, you can download some ready-made sample data .

And you’re done!

There is a lot to think about when planning a search strategy. With practice, expert help, and the right tools your team can complete the search process with confidence.

This blog post is part of the Covidence series on how to write a systematic review.

Sign up for a free trial of Covidence today!

[1] Witt  KG, Hetrick  SE, Rajaram  G, Hazell  P, Taylor Salisbury  TL, Townsend  E, Hawton  K. Pharmacological interventions for self‐harm in adults . Cochrane Database of Systematic Reviews 2020, Issue 12. Art. No.: CD013669. DOI: 10.1002/14651858.CD013669.pub2. Accessed 02 February 2021

Laura Mellor. Portsmouth, UK

Perhaps you'd also like....

Top 5 Tips for High-Quality Systematic Review Data Extraction

Data extraction can be a complex step in the systematic review process. Here are 5 top tips from our experts to help prepare and achieve high quality data extraction.

How to get through study quality assessment Systematic Review

Find out 5 tops tips to conducting quality assessment and why it’s an important step in the systematic review process.

How to extract study data for your systematic review

Learn the basic process and some tips to build data extraction forms for your systematic review with Covidence.

Better systematic review management

Head office, working for an institution or organisation.

Find out why over 350 of the world’s leading institutions are seeing a surge in publications since using Covidence!

Request a consultation with one of our team members and start empowering your researchers:

By using our site you consent to our use of cookies to measure and improve our site’s performance. Please see our Privacy Policy for more information. 

Developing NICE guidelines: the manual

NICE process and methods [PMG20] Published: 31 October 2014 Last updated: 17 January 2024

• Tools and resources
• 1 Introduction
• 2 The scope
• 3 Decision-making committees
• 4 Developing review questions and planning the evidence review

5 Identifying the evidence: literature searching and evidence submission

• 6 Reviewing evidence
• 7 Incorporating economic evaluation
• 8 Linking to other guidance
• 9 Interpreting the evidence and writing the guideline
• 10 The validation process for draft guidelines, and dealing with stakeholder comments
• 11 Finalising and publishing the guideline recommendations
• 12 Support for putting the guideline recommendations into practice
• 13 Ensuring that published guidelines are current and accurate
• 14 Updating guideline recommendations
• 15 Appendices
• Update information

NICE process and methods

5.1 introduction, 5.2 searches during guideline recommendation scoping and surveillance, 5.3 searches during guideline recommendation development, 5.4 health inequalities and equality and diversity, 5.5 quality assurance, 5.6 documenting the search, 5.7 re-running searches, 5.8 calls for evidence from stakeholders, 5.9 references and further reading.

The systematic identification of evidence is an essential step in developing NICE guideline recommendations.

This chapter sets out how evidence is identified at each stage of the guideline development cycle. It provides details of the systematic literature searching methods used to identify the best available evidence for NICE guidelines. It also provides details of associated information management processes including quality assurance (peer review), re‑running searches, and documenting the search process.

Our searching methods are informed by the chapter on searching & selecting studies in the Cochrane Handbook for Systematic Reviews of Interventions and the Campbell Collaboration's searching for studies guide . The Summarized Research in Information Retrieval for HTA (SuRe Info) resource also provides research-based advice on information retrieval for systematic reviews.

Our literature searches are designed to be systematic, transparent, and reproducible, and minimise dissemination bias. Dissemination bias may affect the results of reviews and includes publication bias and database bias.

We use search methods that balance recall and precision. When the need to reduce the number of studies requires pragmatic search approaches that may increase the risk of missing relevant studies, the context and trade-offs are discussed and agreed within the development team and made explicit in the reported search methods.

A flexible approach to identifying evidence is adopted, guided by the subject of the review question (see the chapter on developing review questions and planning the evidence review ), type of evidence sought, and the resource constraints of the evidence review. Often an evidence review will be an update of our earlier work, therefore the approach can be informed by previous searches and surveillance reviews (see the chapter on ensuring that published guidelines are current and accurate ).

Scoping searches

Scoping searches are top-level searches to support scope development. The purpose of the searches is to investigate the current evidence around the topic, and to identify any areas where an evidence review may be beneficial and any research gaps. The results of the searches are used to draft the scope of the upcoming guideline or update and to inform the discussions at scoping workshops (if held). Scoping searches do not aim to be exhaustive.

In some cases, scoping searches are not required when it is more efficient to use the surveillance review (see the chapter on the scope ).

The sources searched at scoping stage will vary according to the topic, type of review questions the guideline or update will seek to address, and type of evidence sought. Each scoping search is tailored using combinations of the following types of information:

NICE guidance and guidance from other organisations

policy and legislation guides

key systematic reviews and epidemiological reviews

economic evaluations

current practice data, including costs and resource use and any safety concerns

views and experiences of people using services, their family members or carers, or the public

other real-world health and social care data (for example audits, surveys, registries, electronic health records, patient-generated health data), if appropriate

summaries of interventions that may be appropriate, including any national safety advice

statistics (for example on epidemiology, natural history of the condition, service configuration or national prevalence data).

All scoping searches are fully documented and if new issues are identified at a scoping workshop, the search is updated. A range of possible sources considered for scoping searches is provided in the appendix on suggested sources for scoping .

Health inequalities searches

The purpose of these searches is to identify evidence to help inform the scope, health inequalities briefing, or the equality and health inequalities assessment (EHIA). They help identify key issues relevant to health inequalities on the topic, for example covering protected characteristics, groups experiencing or at risk of inequalities, or wider determinants of health.

The searches involve finding key data sources, such as routinely available national databases, audits or published reports by charities, non-governmental bodies, or government organisations.

Surveillance searches

Surveillance determines whether published recommendations remain current. The searches are tailored to the evidence required. This may include searches for new or updated policies, legislation, guidance from other organisations, or ongoing studies in the area covered by the evidence review.

If required, published evidence is identified by searching a range of bibliographic databases relevant to the topic. Surveillance searches generally use the same core set of databases used during the development of the original evidence review. A list of sources is given in the appendix on sources for evidence reviews .

The search approach and sources will vary between topics and may include:

population and intervention searches

focused searches for specific question areas

forward and backward citation searching.

Searches usually focus on randomised controlled trials and systematic reviews, although other study types will be considered where appropriate, for example for diagnostic questions.

The search period starts at either the end of the search for the last update of a guideline evidence review, or at the last search date for any previous surveillance check. Where appropriate, living evidence surveillance could be set up to continuously monitor the publication of new evidence over a period of time until impact reaches the threshold for actions. For more information on NICE guideline recommendation surveillance, see the chapter on ensuring that guideline recommendations are current and accurate and appendix on surveillance - interim principles for monitoring approaches of guideline recommendations .

Search protocols

Search protocols form part of the wider guideline review protocol (see the appendix on the review protocol template ). They pre‑define how the evidence is identified and provide a basis for developing the search strategies.

Once the final scope is agreed, the information specialist develops the search protocols and agrees them with the development team before the evidence search begins.

A search protocol includes the following elements:

approach to the search strategy, tailored to the review question and eligibility criteria

sources to be searched

plans to use any additional or alternative search techniques , when known at the protocol development stage, and the reasons for their use

details of any limits to be applied to the search

references to any key papers used to inform the search approach.

Searches are done on a mix of bibliographic databases, websites and other sources, depending on the subject of the review question and the type of evidence sought.

For most searches there are key sources that are prioritised, and other potentially relevant sources that can be considered. It is important to ensure adequate coverage of the relevant literature and to search a range of sources. However, there are practical limits to the number of sources that can be searched in the standard time available for an evidence review.

The selection of sources varies according to the requirements of the review question.

Clinical intervention sources

For reviews of the effectiveness of clinical interventions the following sources are prioritised for searching:

the Cochrane Central Register of Controlled Trials (CENTRAL)

the Cochrane Database of Systematic Reviews (CDSR)

Clinical safety sources

In addition to the sources searched for clinical interventions, the following should be prioritised for clinical safety review questions:

MHRA drug safety updates

National patient safety alerts .

Antimicrobial resistance sources

For reviews of antimicrobial resistance, the following sources should be prioritised:

UK Health Security Agency's English surveillance programme for antimicrobial utilisation and resistance (ESPAUR) report

UK Health Security Agency's antimicrobial resistance local indicators .

Cost-effectiveness sources

For reviews of cost effectiveness, economic databases are used in combination with general bibliographic databases, such as MEDLINE and Embase (see appendix G on sources for economic reviews ).

Economic evaluations of social care interventions may be published in journals that are not identified through standard searches. Targeted searches based on references of key articles and contacting authors can be considered to identify relevant papers.

Topic-specific sources

Some topics we cover may require the use of topic-specific sources. Examples include:

PsycINFO (psychology and psychiatry)

CINAHL (nursing and allied health professions)

ASSIA (Applied Social Sciences Index and Abstracts)

HealthTalk , and other sources to identify the views and experiences of people using services, carers and the public

social policy and practice

social care online

sociological abstracts

transport database

Greenfile (environmental literature)

HMIC (Health Management Information Consortium).

Searching for model inputs

Evidence searches may be needed to inform design-oriented conceptual models. Examples include precise searches to find representative NHS costs for an intervention or finding out the proportion of people offered an intervention who take up the offer.

Some model inputs, such as costs, use national sources such as national list prices or national audit data. In some cases, it may be more appropriate to identify costs from the academic literature. Further advice on methods to identify model inputs are also informed by Paisley (2016) and Kaltenhaler et al. (2011). See also the chapter on incorporating economic evaluation .

Real-world data

Information specialists can identify sources of real-world data (such as electronic health records, registries, and audits) for data analysts to explore further. The Health Data Research Innovation Gateway can be used to identify datasets. The NICE real-world evidence framework (2022) has additional guidance on searching for and selecting real-world data sources.

Grey literature

For some review questions, for example, where significant evidence is likely to be published in non-journal sources and there is a paucity of evidence in published journal sources, it may be appropriate to search for grey literature . Useful sources of grey literature include:

HMIC (Health Management Information Consortium)

TRIP database

Canadian Agency for Drugs and Technology in Health (CADTH) Grey Matters resource .

Committee members may also be able to suggest additional appropriate sources for grey literature.

A list containing potential relevant sources is provided in the appendix on sources for evidence reviews .

Developing search strategies

The approach to devising and structuring search strategies is informed by the review protocol. The PICO (population, intervention, comparator and outcome) or SPICE (setting, perspective, intervention, comparison, evaluation) frameworks may be used to structure a search strategy for intervention review questions. For other types of review questions, alternative frameworks may be more suitable.

It is sometimes more efficient to conduct a single search for multiple review questions, rather than conducting a separate search for each question.

Some topics may not easily lend themselves to PICO- or SPICE-type frameworks. In these cases, it may be better to combine multiple, shorter searches rather than attempting to capture the entire topic using a single search. This is often referred to as multi-stranded searching.

In some instances, for example where the terminology around a topic is diffuse or ill defined, it may be difficult to specify the most appropriate search terms in advance. In these cases, an iterative approach to searching can be used.

In an iterative approach, searching is done in several stages, with each search considering the evidence that has already been retrieved (for example, see Booth et al. 2020 ). Searching in stages allows the reviewers to review the most relevant, high-quality information first and then make decisions for identifying additional evidence if needed.

Decisions to use iterative approaches are agreed by the development team and staff with responsibility for quality assurance because it can affect timelines.

Updating previous work

Where high-quality review-level evidence is available on a topic, the review team may choose to update or expand this previous work rather than duplicating the existing findings. In these cases, the original review searches are re-run and expanded to account for any differences in scope and inclusion criteria between the original review and the update.

Cost-effectiveness searches

There are several methods that can be used to identify economic evaluations:

All relevant review questions can be covered by a single search using the population search terms, combined with a search filter, to identify economic evidence.

The search strategies for individual review questions can be combined with search filters to identify economic evidence. If using this approach, it may be necessary to adapt strategies for some databases to ensure adequate sensitivity.

Economic evidence can be manually sifted while screening evidence from a general literature search (so no separate searches are required).

The rationale for the selected approach is recorded in the search protocol.

Where searches are needed to populate an economic model, these are usually done separately.

Identifying search terms

Search terms usually consist of a combination of subject headings and free‑text terms from the titles and abstracts of relevant references.

When identifying subject headings, variations in thesaurus and indexing terms for each database should be considered, for example MeSH (Medical Subject Headings) in MEDLINE and Emtree in Embase. Not all databases have indexing terms and some contain records that have not yet been indexed.

Free‑text terms may include synonyms, acronyms and abbreviations, spelling variants, old and new terminology, brand and generic medicine names, and lay and medical terminology.

For updates, previous search terms, including those from surveillance searches, are reviewed and used to inform new search terms. New or changed terms are identified, as well as any changes to indexing terms. This also applies when an existing review, for example a Cochrane review, is being updated to answer a review question.

Key studies can be a useful source of search terms, as can reports, guidelines, topic-specific websites, committee members and topic experts.

Some websites and databases have limited search functionality. It may be necessary to use fewer search terms or do multiple searches of the same resource with different search term combinations.

It may be helpful to use frequency analysis or text mining to develop the search-term strategy. Tools such as PubReMiner and Medline Ranker can help, either by highlighting search terms that might not otherwise be apparent, or by flagging terms of high value when exhaustive synonym searching is unfeasible or inadvisable.

Search limits

The application of limits to search strategies will reflect the eligibility criteria in the review protocol. Typically, English language limits, date limits, and the exclusion of conference abstracts and animal studies are usually done as a matter of routine.

Search filters

A search filter is a string of search terms with known (validated) performance. When a particular study design is required for a review question, relevant search filters are usually applied to literature search strategies.

Other search filters relating to age, setting, geography, and health inequalities are also applied as relevant. The most comprehensive list of available search filters is the search filter resource of the InterTASC Information Specialists' SubGroup . This resource also includes critical appraisal tools, which are used for filter selection.

Economics-related filters

A variety of search filters of relevance to cost effectiveness are available. These include filters for economic evaluations, quality of life data, and cost-utilities data. It may be necessary to use more than 1 filter to identify relevant data. In addition, it may be appropriate to add geographic search filters, such as those for the UK or Organisation for Economic Co-operation and Development (OECD) countries, to retrieve economic studies relevant to the UK or OECD (Ayiku et al. 2017, 2019, 2021).

Use of machine learning-based classifiers

Machine learning-based classification software has been developed for some study types (for example the Cochrane RCT classifier, Thomas et al. 2020 ). These classifiers apply a probability weighting to each bibliographical reference within a set of search results. The weighting relates to the reference's likelihood to be a particular study type, based on a model created from analysis of known, relevant papers. The weightings can then be used to either order references for screening or be used with a fixed cut-off value to divide a list of references into those more likely to be included, and those that can be excluded without manual screening.

We support the use of machine classifiers if their performance characteristics are known, and if they improve efficiency in the search and screening process. However, caution is needed when using classifiers, because they may not be as effective if used on data that is different to the type of data for which they were originally developed. For example, the Cochrane RCT classifier is reported to have over 99% recall for health studies but showed "unacceptably low" recall for educational research ( Stansfield et al. 2022 ).

Priority screening, a type of machine classifier that orders references for manual sifting based on previous sifting decisions, is considered in the chapter on reviewing evidence .

Additional search techniques

Additional search techniques are used alongside database searching when it is known, or reasonably likely, that relevant evidence is not indexed in bibliographic databases, or when it will be difficult to retrieve relevant evidence from databases in a way that adequately balances recall and precision. Additional search techniques include forward and backward citation searching, journal hand-searches and contacting experts and stakeholders.

Existing reviews may provide an additional source of primary studies, with reference lists being used as an indirect method of identifying primary research.

Various tools, including Citationchaser and Web of Science, are available to speed up the process of citation searching. These may not be as comprehensive as manual reference list checking (due to limitations of the underlying data sources), but the trade-off in terms of speed is generally acceptable.

All search techniques should follow the same principles of transparency, rigour and reproducibility as other search methods.

If possible, additional search techniques should be considered at the outset and documented in the search protocol. They should also be documented in the supporting appendices for the final evidence review.

All searches aim to be inclusive. This may mean not specifying any population groups.

Searches should avoid inadvertently excluding relevant groups. For example, if the population group is older people, a search for older people should pick up subpopulations such as disabled older people.

Additional search strategies may be needed to target evidence about people with protected characteristics or people experiencing or at risk from other inequalities.

Searches may need to be developed iteratively to ensure coverage of the health inequalities issues or evidence on the impacts of an intervention on equality.

Appropriate terminology for the search should be used, considering how language has evolved.

Quality assuring the literature search is an important step in developing guideline recommendations. Studies have shown that errors do occur.

For each search (including economic searches), the initial MEDLINE search strategy is quality assured by a second information specialist. A standardised checklist, based on the PRESS peer review of electronic search strategies: 2015 guideline statement , is used to ensure clarity and consistency when quality assuring search strategies.

The information specialist carrying out the quality assurance process also considers how appropriate the overall search approach is to the parameters of the evidence review (for example, the time available to carry out the review). The quality assurance comments are recorded and the information specialist who conducted the search should respond to the comments and revise the search strategy as needed.

Search strategy translations across the remaining databases are also checked by a second information specialist to ensure that the strategies have been adapted appropriately, in accordance with the interfaces and search functionality of the sources used.

Details of the evidence search are included as appendices to the individual evidence reviews. They are published for consultation alongside the draft evidence review and included in the final version.

Records are kept of the searches undertaken during guideline recommendation development for all review questions to ensure that the process for identifying the evidence is transparent and reproducible.

We use the PRISMA-S: an extension to the PRISMA statement for reporting literature searches in systematic reviews to inform search reporting. The search documentation is an audit trail that allows the reader to understand both the technical aspect of what was done (such as which sources were searched; what platform was used and on what date; any deviations from the original search protocol) and the underlying rationale for the search approach where this may not be immediately apparent.

Documenting the search begins with creating the search protocol (see the section on search protocols ). If using an iterative or emergent stepped approach, initial search strategies, key decision points and the reasons for subsequent search steps are clearly documented in the search protocol and final evidence review. When using a proprietary search engine such as Google, whose underlying algorithm adapts to different users, the search is reported in a way that should allow the reader to understand what was done.

Searches undertaken to identify evidence for each review question (including economics searches) may be re-run before consultation or before publication. For example, searches are re‑run if the evidence changes quickly, there is reason to believe that substantial new evidence exists, or the development time is longer than usual.

A decision to re‑run searches is taken by the development team and staff with responsibility for quality assurance.

If undertaken, searches are re‑run at least 6 to 8 weeks before the final committee meeting before consultation.

If evidence is identified after the last cut‑off date for searching but before publication, a judgement on its impact is made by the development team and staff with responsibility for quality assurance. In exceptional circumstances, this evidence can be considered if its impact is judged as potentially substantial.

In some topic areas or for some review questions, staff with responsibility for quality assurance, the development team or the committee may believe that there is relevant evidence in addition to that identified by the searches. In these situations, the development team may invite stakeholders, and possibly also other relevant organisations or individuals with a significant role or interest (see expert witnesses in the section on other attendees at committee meetings in the chapter on decision-making committees ), to submit evidence. A call for evidence is issued directly to registered stakeholders on the NICE website. Examples and details of process are included in the appendix on call for evidence and expert witnesses . Confidential information should be kept to an absolute minimum.

Ayiku L, Levay P, Hudson T et al. (2017) The medline UK filter: development and validation of a geographic search filter to retrieve research about the UK from OVID medline. Health Information and Libraries Journal 34(3): 200–216

Ayiku L, Levay P, Hudson T et al. (2019) The Embase UK filter: validation of a geographic search filter to retrieve research about the UK from OVID Embase. Health Information and Libraries Journal 36(2): 121–133

Ayiku L, Hudson T, Williams C et al. (2021) The NICE OECD countries' geographic search filters: Part 2-validation of the MEDLINE and Embase (Ovid) filters . Journal of the Medical Library Association 109(4): 583–9

Booth A, Briscoe S, Wright JM (2020) The "realist search": a systematic review of current practice and reporting . Research Synthesis Methods 11: 14–35

Canadian Agency for Drugs and Technologies in Health (2019) Grey Matters: a practical tool for searching health-related grey literature [online; accessed 24 July 2023]

Glanville J, Lefebvre C, Wright K (editors) (2008, updated 2017) The InterTASC Information Specialists' Subgroup Search Filters Resource [online; accessed 24 July 2023]

Kaltenthaler E, Tappenden P, Paisley S (2011) NICE DSU Technical support document 13: identifying and reviewing evidence to inform the conceptualisation and population of cost-effectiveness models [online; accessed 24 July 2023]

Kugley S, Wade A, Thomas J et al. (2017) Searching for studies: a guide to information retrieval for Campbell systematic reviews . Oslo: The Campbell Collaboration

Lefebvre C, Glanville J, Briscoe S et al. Chapter 4: Searching for and selecting studies . In: Higgins JPT, Thomas J, Cumpston M et al. (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.2 (updated February 2021). Cochrane, 2021

McGowan J, Sampson M, Salzwedel DM et al. (2016) PRESS Peer Review of Electronic Search Strategies: 2015 guideline statement . Journal of Clinical Epidemiology 75: 40–6

National Institute for Health and Care Excellence (2022) NICE real-world evidence framework [online; accessed 24 July 2023]

Paisley S (2016) Identification of key parameters in decision-analytic models of cost-effectiveness: a description of sources and a recommended minimum search requirement. Pharmacoeconomics 34: 597–8

Rethlefsen M, Kirtley S, Waffenschmidt S et al. (2021) PRISMA-S: an extension to the PRISMA statement for reporting literature searches in systematic reviews . Systematic Reviews 10: 39

Stansfield C, Stokes G, Thoman J (2022) Applying machine classifiers to update searches: analysis from two case studies . Research Synthesis Methods 13: 121–33

Summarized research for Information Retrieval in HTA (SuRe Info) [online; accessed 24 July 2023]

Literature Reviews & Search Strategies

• Defining the Literature Review
• Types of Literature Reviews
• Choosing Databases

Overview of Search Strategies

Search strategies, subject searching, example: iteratively developing + using keywords, demonstration: developing keywords from a question, demonstration: an advanced search.

• Organizing Your Literature
• Books: Research Design & Scholarly Writing
• Recommended Tutorials

There are many ways to find literature for your review, and we recommend that you use a combination of strategies - keeping in mind that you're going to be searching multiple times in a variety of ways, using different databases and resources. Searching the literature is not a straightforward, linear process - it's iterative (translation: you'll search multiple times, modifying your strategies as you go, and sometimes it'll be frustrating). 

• Known Item Searching
• Citation Jumping

Some form of a keyword search is the way most of us get at scholarly articles in database - it's a great approach! Make sure you're familiar with these librarian strategies to get the most out of your searches.

Figuring out the best keywords for your research topic/question is a process - you'll start with one or a few words and then shift, adapt, and expand them as you start finding source that describe the topic using other words. Your search terms are the bridge between known topics and the unknowns of your research question - so sometimes one specific word will be enough, sometimes you'll need several different words to describe a concept AND you'll need to connect that concept to a second (and/or third) concept.

The number and specificity of your search terms depend on your topic and the scope of your literature review.

Connect Keywords Using Boolean

Make the database work more.

...uses the asterisk (*) to end a word at its core, allowing you to retrieve many more documents containing variations of the search term.  Example: educat* will find educate, educates, education, educators, educating and more.

Phrase Searching

...is when you put quotations marks around two or more words, so that the database looks for those words in that exact order. Examples: "higher education," "public health" and "pharmaceutical industry."

Controlled Vocabulary

... is when you use the terms the database uses to describe what each article is about as search terms. Searching using controlled vocabularies is a great way to get at everything on a topic in a database.  

Databases and search engines are probably going to bring back a lot of results - more than a human can realistically go through. Instead of trying to manually read and sort them all, use the filters in each database to remove the stuff you wouldn't use anyway (ie it's outside the scope of your project).

To make sure you're consistent between searches and databases, write down the filters you're using.

A Few Filters to Try

Once you know you have a good article , there are a lot of useful parts to it - far beyond the content.

Not sure where to start? Try course readings and other required materials.

Useful Parts of a Good Article

Ways to use citations.

• Interactive Tutorial: Searching Cited and Citing Practice starting your search at an article and using the references to gather additional sources.

Your search results don't have to be frozen in the moment you search! There are a few things you can set up to keep your search going automatically.

Searching using subject headings is a comprehensive search strategy that requires some planning and topic knowledge. Work through this PubMed tutorial for an introduction to this important approach to searching.

Through these videos and the accompanying PDF, you'll see an example of starting with a potential research question and developing search terms through brainstorming and keyword searching.

• Slidedeck: Keywords and Advanced Search PowerPoint slides to accompany the two demonstration videos on developing keywords from a question, and doing an advanced search.
• << Previous: Choosing Databases
• Next: Organizing Your Literature >>
• Last Updated: Jun 14, 2023 11:18 AM
• URL: https://mcphs.libguides.com/litreviews

• University of Michigan Library
• Research Guides

Systematic Reviews

• Search Strategy
• Work with a Search Expert
• Covidence Review Software
• Types of Reviews
• Evidence in a Systematic Review
• Information Sources

Developing an Answerable Question

Creating a search strategy, identifying synonyms & related terms, keywords vs. index terms, combining search terms using boolean operators, a sr search strategy, search limits.

• Managing Records
• Selection Process
• Data Collection Process
• Study Risk of Bias Assessment
• Reporting Results
• For Search Professionals

Validated Search Filters

Depending on your topic, you may be able to save time in constructing your search by using specific search filters (also called "hedges") developed & validated by researchers in the Health Information Research Unit (HiRU) of McMaster University, under contract from the National Library of Medicine.  These filters can be found on

• PubMed’s Clinical Queries &  Health Services Research Queries pages
• Ovid Medline’s Clinical Queries  filters or here
• Embase  & PsycINFO
• EBSCOhost’s main search page for CINAHL (Clinical Queries category)
• HiRU’s Nephrology Filters page
• American U of Beirut, esp. for " humans" filters .
• Countway Library of Medicine methodology filters
• InterTASC Information Specialists' Sub-Group Search Filter Resource
• SIGN (Scottish Intercollegiate Guidelines Network) filters page

Why Create a Sensitive Search?

In many literature reviews, you try to balance the sensitivity of the search (how many potentially relevant articles you find) &  specificit y (how many definitely relevant articles  you find ), realizing that you will miss some.  In a systematic review, you want a very sensitive search:  you are trying to find any potentially relevant article.  A systematic review search will:

• contain many synonyms & variants of search terms
• use care in adding search filters
• search multiple resources, databases & grey literature, such as reports & clinical trials

PICO is a good framework to help clarify your systematic review question.

P -   Patient, Population or Problem: What are the important characteristics of the patients &/or problem?

I -  Intervention:  What you plan to do for the patient or problem?

C -  Comparison: What, if anything, is the alternative to the intervention?

O -  Outcome:  What is the outcome that you would like to measure?

Beyond PICO: the SPIDER tool for qualitative evidence synthesis.

5-SPICE: the application of an original framework for community health worker program design, quality improvement and research agenda setting.

A well constructed search strategy is the core of your systematic review and will be reported on in the methods section of your paper. The search strategy retrieves the majority of the studies you will assess for eligibility & inclusion. The quality of the search strategy also affects what items may have been missed.  Informationists can be partners in this process.

For a systematic review, it is important to broaden your search to maximize the retrieval of relevant results.

Use keywords:  How other people might describe a topic?

Identify the appropriate index terms (subject headings) for your topic.

• Index terms differ by database (MeSH, or  Medical Subject Headings ,   Emtree terms , Subject headings) are assigned by experts based on the article's content.
• Check the indexing of sentinel articles (3-6 articles that are fundamental to your topic).  Sentinel articles can also be used to  test your search results.

Include spelling variations (e.g., behavior, behaviour ).  

Both types of  search terms are useful & both should be used in your search.

Keywords help to broaden your results.  They will be searched for at least in journal titles, author names, article titles, & article abstracts.  They can also be tagged to search all text.

Index/subject terms  help to focus your search appropriately, looking for items that have had a specific term applied by an indexer.

Boolean operators let you combine search terms in specific ways to broaden or narrow your results.

An example of a search string for one concept in a systematic review.

In this example from a PubMed search, [mh] = MeSH &  [tiab] = Title/Abstract, a more focused version of a keyword search.

A typical database search limit allows you to narrow results so that you retrieve articles that are most relevant to your research question. Limit types vary by database & include:

• Article/publication type
• Publication dates

In a systematic review search, you should use care when applying limits, as you may lose articles inadvertently.  For more information, see, particularly regarding language & format limits.     Cochrane 2008 6.4.9

• Subject guides
• Researching for your literature review
• Develop a search strategy

Researching for your literature review: Develop a search strategy

• Literature reviews
• Literature sources
• Before you start
• Keyword search activity
• Subject search activity
• Combined keyword and subject searching
• Online tutorials
• Apply search limits
• Run a search in different databases
• Supplementary searching
• Save your searches
• Manage results

Identify key terms and concepts

Start developing a search strategy by identifying the key words and concepts within your research question. The aim is to identify the words likely to have been used in the published literature on this topic.

For example: What are the key infection control strategies for preventing the transmission of Meticillin-resistant Staphylococcus aureus (MRSA) in aged care homes .

Treat each component as a separate concept so that your topic is organised into separate blocks (concepts).

For each concept block, list the key words derived from your research question, as well as any other relevant terms or synonyms that you have found in your preliminary searches. Also consider singular and plural forms of words, variant spellings, acronyms and relevant index terms (subject headings).  

As part of the process of developing a search strategy, it is recommended that you keep a master list of search terms for each key concept. This will make it easier when it comes to translating your search strategy across multiple database platforms. 

Concept map template for documenting search terms

Combine search terms and concepts

Boolean operators are used to combine the different concepts in your topic to form a search strategy. The main operators used to connect your terms are AND and OR . See an explanation below:

• Link keywords related to a single concept with OR
• Linking with OR broadens a search (increases the number of results) by searching for any of the alternative keywords

Example: nursing home OR aged care home

• Link different concepts with AND
• Linking with AND narrows a search (reduces the number of results) by retrieving only those records that include all of your specified keywords

Example: nursing home AND infection control

• using NOT narrows a search by excluding results that contain certain search terms
• Most searches do not require the use of the NOT operator

Example: aged care homes NOT residential homes will retrieve all the results that include the words aged care homes but don't include the words residential homes . So if an article discussed both concepts this article would not be retrieved as it would be excluded on the basis of the words residential homes .

See the website for venn diagrams demonstrating the function of AND/OR/NOT:

Combine the search terms using Boolean

Advanced search operators - truncation and wildcards

By using a truncation symbol you can capture all of the various endings possible for a particular word. This may increase the number of results and reduce the likelihood of missing something relevant. Some tips about truncation:

• The truncation symbol is generally an asterisk symbol * and is added at the end of a word.
• It may be added to the root of a word that is a word in itself. Example: prevent * will retrieve prevent, prevent ing , prevent ion prevent ative etc. It may also be added to the root of a word that is not a word in itself. Example: strateg * will retrieve strateg y , strateg ies , strateg ic , strateg ize etc.
• If you don't want to retrieve all possible variations, an easy alternative is to utilise the OR operator instead e.g. strategy OR strategies. Always use OR instead of truncation where the root word is too small e.g. ill OR illness instead of ill*

There are also wildcard symbols that function like truncation but are often used in the middle of a word to replace zero, one or more characters.

• Unlike the truncator which is usually an asterisk, wildcards vary across database platforms
• Common wildcards symbols are the question mark ? and hash #.
• Example:  wom # n finds woman or women, p ? ediatric finds pediatric or paediatric.  

See the Database search tips for details of these operators, or check the Help link in any database.

Phrase searching

For words that you want to keep as a phrase, place two or more words in "inverted commas" or "quote marks". This will ensure word order is maintained and that you only retrieve results that have those words appearing together.

Example: “nursing homes”

There are a few databases that don't require the use of quote marks such as Ovid Medline and other databases in the Ovid suite. The Database search tips provides details on phrase searching in key databases, or you can check the Help link in any database.

Subject headings (index terms)

Identify appropriate subject headings (index terms).

Many databases use subject headings to index content. These are selected from a controlled list and describe what the article is about. 

A comprehensive search strategy is often best achieved by using a combination of keywords and subject headings where possible.

In-depth knowledge of subject headings is not required for users to benefit from improved search performance using them in their searches.

Advantages of subject searching:

• Helps locate articles that use synonyms, variant spellings, plurals
• Search terms don’t have to appear in the title or abstract

Note: Subject headings are often unique to a particular database, so you will need to look for appropriate subject headings in each database you intend to use.

Subject headings are not available for every topic, and it is best to only select them if they relate closely to your area of interest.

MeSH (Medical Subject Headings)

The MeSH thesaurus provides standard terminology, imposing uniformity and consistency on the indexing of biomedical literature. In Pubmed/Medline each record is tagged with  MeSH  (Medical Subject Headings).

The MeSH vocabulary includes:

• Represent concepts found in the biomedical literature
• Some headings are commonly considered for every article (eg. Species (including humans), Sex, Age groups (for humans), Historical time periods)
• attached to MeSH headings to describe a specific aspect of a concept
• describe the type of publication being indexed; i.e., what the item is, not what the article is about (eg. Letter, Review, Randomized Controlled Trial)
• Terms in a separate thesaurus, primarily substance terms

Create a 'gold set'

It is useful to build a ‘sample set’ or ‘gold set’ of relevant references before you develop your search strategy..

Sources for a 'gold set' may include:

• key papers recommended by subject experts or supervisors
• citation searching - looking at a reference list to see who has been cited, or using a citation database (eg. Scopus, Web of Science) to see who has cited a known relevant article
• results of preliminary scoping searches.

The papers in your 'gold set' can then be used to help you identify relevant search terms

• Look up your 'gold set' articles in a database that you will use for your literature review. For the articles indexed in the database, look at the records to see what keywords and/or subject headings are listed.

The 'gold set' will also provide a means of testing your search strategy

• When an article in the sample set that is also indexed in the database is not retrieved, your search strategy can be revised in order to include it (see what concepts or keywords can be incorporated into your search strategy so that the article is retrieved).
• If your search strategy is retrieving a lot of irrelevant results, look at the irrelevant records to determine why they are being retrieved. What keywords or subject headings are causing them to appear? Can you change these without losing any relevant articles from your results?
• Information on the process of testing your search strategy using a gold set can be found in the systematic review guide

Example search strategy

A search strategy is the planned and structured organisation of terms used to search a database.

An example of a search strategy incorporating all three concepts, that could be applied to different databases is shown below:

You will use a combination of search operators to construct a search strategy, so it’s important to keep your concepts grouped together correctly. This can be done with parentheses (round brackets), or by searching for each concept separately or on a separate line.

The above search strategy in a nested format (combined into a single line using parentheses) would look like:

("infection control*" OR "infection prevention") AND ("methicillin resistant staphylococcus aureus" OR "meticillin resistant staphylococcus aureus" OR MRSA) AND ( "aged care home*" OR "nursing home*")

• << Previous: Search strategies - Health/Medical topic example
• Next: Keyword search activity >>

Conducting a Literature Review

• Literature Review
• Developing a Topic
• Planning Your Literature Review

Developing a Search Strategy

• Managing Citations
• Critical Appraisal Tools
• Writing a Literature Review

A search strategy is an organized structure of key terms used to search a database. The search strategy combines the key concepts of your search question in order to retrieve accurate results.

Your search strategy will account for all:

• possible search terms
• keywords and phrases
• truncated and wildcard variations of search terms
• subject headings (where applicable)

Each database works differently so you need to adapt your search strategy for each database. You may wish to develop a number of separate search strategies if your research covers several different areas. 

It is a good idea to test your strategies and refine them after you have reviewed the search results.

This is a sample planner to develop your search terms from a PICO format

Identifying Search Terms

Once you have developed your research question or chosen your topic you can begin to brainstorm terms to use in your database search.

• Brainstorm terms authors or indexers might use to describe your topic
• Make a list of terminology and relevant terms to use in your search
• Include synonyms or similar terms to combine using the Boolean operator OR
• Search for controlled vocabulary in the databases i.e. search PubMed for MeSH terms

Combine the Elements of Your PICO Question with Boolean Operators

Boolean Operators (Using AND, OR NOT):

Boolean logic is a building block of many computer applications and is an important concept in database searching.  Using the correct Boolean operator can make all the difference in a successful search.

AND, OR, NOT

There are three basic Boolean search commands:  AND ,  OR  and  NOT .

• AND  searches find all of the search terms.  For example, searching on dengue  AND  malaria  AND  zika  returns only results that contain all three search terms.  Very limited results.
• OR  searches find one term or the other.  Searching on dengue  OR  malaria  OR  zika returns all items that contain any of the three search terms.  Returns a large number of results.
• NOT  eliminates items that contain the specified term.  Searching on malaria  NOT  zika returns items that are about malaria, but will specifically  NOT  return items that contain the word zika.  This is a way to fine-tune results. Note:  sometimes  AND NOT  is used; serves the same function as  NOT

Using Boolean Search with Exact Phrases:

If you're searching for a phrase rather than just a single word, you can group the words together with quotation marks.  Searching on "dengue fever" will return only items with that exact phrase.  

When to use Parentheses?

Think of your search in concepts, then put those concepts inside parentheses.  Different databases have different rules about combining searches.  To make sure you get the search you want, use parentheses - every database follows those rules.

Run a Preliminary Search

Look at titles and publication dates to decide which articles you want to look at in depth.

• Select an article and begin the skimming and scanning process.
• If the list has too many irrelevant results, consider selecting different keywords and revising your search.
• If the list has too many results, consider setting date limiters or narrowing your results by searching phrases instead of keywords.
• If the list has too few results, consider selecting different keywords

• The Interprofessional Health Sciences Library
• 123 Metro Boulevard
• Nutley, NJ 07110
• [email protected]
• Visiting Campus
• News and Events
• Parents and Families
• Web Accessibility
• Career Center
• Public Safety
• Accountability
• Privacy Statements
• Report a Problem
• Login to LibApps

Trinity College Dublin, The University of Dublin

Trinity Search

Trinity menu.

• Faculties and Schools
• Trinity Courses
• Trinity Research

Writing a Literature Review

• Getting Started
• Defining the Scope
• Finding the Literature

Getting your search right

Keyword searches, widening your search: truncation and wildcards, combining your terms: search operators, being more specific: phrase and proximity searching, subject headings, combining keyword and subject heading searches, using methodological search filters.

• Managing Your Research
• Writing the Review
• Systematic Reviews and Other Review Types
• Useful Books
• Useful Videos
• Useful Links
• Commonly Used Terms

Test your strategy!

• Search the database for each of the test records and make a note of the unique record number for each one - in Medline this is in the UI field.
• Run your search strategy.
• Run a search for all the record numbers for your test set using 'OR' in between each one.
• Lastly combine the result of your search strategy with the test set using 'OR'.
• If the number of records retrieved stays the same then the strategy has identified all the records. If it doesn't, combine the result of your search strategy with the test set, this time using 'NOT'. This will identify the records in your test set which are not being retrieved. Work out why these weren't retrieved and adjust your search strategy accordingly.

Think about...

• abbreviations
• related terms
• UK/US spellings
• singular/plural forms of words
• thesaurus terms (where available)

Your search is likely to be complex and involve multiple steps to do with different subjects, what are often called "strands" or "strings" in the search. Look at the appendices of existing reviews for an idea of what's involved in creating a comprehensive search.

Most people should start by finding all the articles on Topic A, then moving on to Topic B, then Topic C (and so on), then combining those strands together using AND (see Combining your terms: search operators below). This will then give you results that mention all those topics.

You will then need to adapt (or "translate") your strategy for each database depending on the searching options available on each one. A core of terms is used across multiple databases - this is the "systematic" part - BUT with additions and subtractions as necessary. While the words in the title and abstract might remain the same, it's highly likely the thesaurus terms (if they exist) will be different across the databases. You may need to leave out some strings completely; for example, let's say you are doing a study that needs to find Randomised Controlled Trials (RCTs) on a particular disease and its treatment. You will be looking in multiple databases for words to do with the condition, and also words that are used for RCTs. But when you are looking in databases that are composed entirely of RCTs (trials registers), the part of a search looking for RCTs doesn’t need to be included as it's redundant.

The techniques described below will help ensure you cover everything. Contact your Subject Librarian if you would like guidance on constructing your search.

This video from the University of Reading gives a good overview of literature searching tips and tricks:

Jump to 01:45 for truncation and 05:46 for wildcards.

• Contact your Subject Librarian
• How to translate searches between certain databases A fantastic crib sheet from Karolinska Institutet University Library, showing how to translate searches between Medline (Ovid), PsycInfo (Ovid), Embase (Elsevier), Web of Science, Cinahl (Ebsco), Cochrane (Wiley), and PubMed.

Most searches have two elements - the "keywords" part and the "subject headings" part - for each topic. When you are initially constructing your search and trialling it in a database, you are likely to just add your keywords, click Search, and see how many that retrieves. But after that, for any type of comprehensive search, you should look at limiting your keywords to looking in specific search fields .

A field in this context is where the database only looks at one aspect of the information about the article. Common examples are the Author, Title, Abstract, and Journal Name. More esoteric ones could be fields like the CAS Registry Entry or Corporate Author.

In complex reviews like systematic, scoping and rapid reviews, the accepted wisdom is to limit these "keyword" searches to the Title and Abstract fields, plus (if available, and the search is looking to be comprehensive) any available "Author Keyword" or "Contributed Indexing" fields. It is vital that the keywords you use in these fields are identical - you are using the same words in the Title, Abstract and any related fields - and that you combine them using OR (see Combining your terms: search operators below)

Using keyword searching limited to the Title/Abstract/Keywords fields should reduce the number of results which are retrieved in error or are only on the periphery of your subject. If you do this, please be aware that you will need to ensure that you have definitely also included all relevant subject headings in your search strategy (in databases that use controlled vocabulary) otherwise you risk missing out on useful results. It *is* quite possible that there will be no relevant subject headings in a particular search.

Although some databases will automatically search for variant spellings, mostly they will just search for the exact letters you type in. Use wildcard and truncation symbols to take control of your search and include variations to widen your search and ensure you don't miss something relevant.

A truncation symbol (*) retrieves any number of letters  - useful to find different word endings based on the root of a word: africa*  will find africa, african, africans, africaans agricultur*  will find agriculture, agricultural, agriculturalist

A wildcard symbol (?) replaces a single letter . It's useful for retrieving alternate spelling spellings (i.e. British vs American English) and simple plurals: wom?n  will find woman or women behavio?r  will find behaviour or behavior

Hint: Not all databases use the * and ? symbols - some may use different ones (! instead of *, for example), or not have the feature at all, so check the online help section of the database before you start.

• Introduction

Search operators (also called Boolean operators) allow you to include multiple words and concepts in your searches. This means you can search for all of your terms at once rather than carrying out multiple searches for each concept.

There are three main operators:

• OR - for combining alternative words for your concepts and widening your results e.g. women OR gender
• AND - for combining your concepts giving more specific results e.g. women AND Africa
• NOT  - to exclude specific terms from your search - use this with caution as you might exclude relevant results accidentally!

women OR female

Using OR will bring you back records containing either of your search terms. It will return items that include both terms, but will also return items that contain only one of the terms.

This will give you a broader range of results.

OR can be used to link together synonyms. These are then placed in brackets to show that they are all the same concept.

• (cat OR kitten OR feline)
• (women OR female)

women AND Africa

Using AND will find items that contain both of your search terms, giving you a more specific set of results.

If you're getting too many results, using AND can be a good way to narrow your search.

women NOT Africa

Using NOT will find articles containing a particular term, but will exclude articles containing your second term.

Use this with caution - by excluding results you might miss out on key resources.

• Phrase searching
• Proximity searching

Sometimes your search may contain common words (i.e. development, communication) which will retrieve too many irrelevant records, even when using an AND search. On many databases, including Google, to look for a specific phrase, use inverted commas:

• "agricultural development"
• "foot and mouth"

Your search will only bring back items containing these exact phrases.

Some databases automatically perform a phrase search if you do not use any search operators. For example, "agriculture africa" is not a phrase used in English so you may not find any items on the subject. Use AND in between your search words to avoid this.

On Scopus to search for an exact phrase use { } e.g. {agricultural development}. Using quotes on Scopus will find your words in the same field (e.g., title) but not necessarily next to one another. In this database, you need to be very careful with those brackets - {heart-attack} and {heart attack} will return different results because the dash is included. Wildcards are searched as actual characters, e.g. {health care?} returns results such as: Who pays for health care?

Some databases use proximity operators, which are a more advanced search function. You can use these to tell the database how close one word must be to another and, in some cases, in what order. This makes a search more specific and excludes irrelevant records.

For instance, if you were searching for references about women in Africa, you might retrieve irrelevant records for items about women published in Africa. Performing a proximity search will only retrieve the two words in the same sentence, making your search more accurate.

Each database has its own way of proximity searching, often with multiple ways of doing it, so it's important to check the online help before you start . Here are some examples of the variety of possible searches:

• Web of Science : women  same Africa - retrieves records where the words 'women' and 'Africa' appear in the same sentence
• JSTOR : agricultural development ~5  - retrieves records where the words 'agricultural' and 'development' are within five words of one another
• Scopus : agricultural  W/2 development - retrieves records where the word 'agricultural' is within two words of the word 'development'. 

After completing your keywords search on a topic, you can move on to looking for appropriate subject headings.

Most databases have this controlled vocabulary feature (standardised subject headings or thesaurus terms - a bit like standard tags) which can help ensure you capture all the relevant studies; for example, MEDLINE, CENTRAL and PubMed use the exact same headings, which are called MeSH (Medical Subject Headings). Some of these headings will be the same in other related databases like CINAHL, but many of them will be slightly different, could be the same but have subtly different meanings, or not be there at all.

Not all databases have these types of subject headings - Web of Science and JSTOR don't allow you to search for subject headings like these, although you can of course search for subjects in them.

The easiest way to search for a subject heading is to go to the relevant area in the database that searches specifically for them; this might be called something like Thesaurus, Subject Headings, or similar. Then search for some of the words to do with your topic - not all of them at once, just a word on its own or a very simple phrase. Does this bring anything up? When you read the description, are you talking about the same thing?

You can then tell it to search for everything listed under that subject heading, then move on to looking for another subject heading. It's quite common for one topic to have several relevant headings.

Once you have found all the relevant headings, and made the database run searches for them, you will then combine them together using OR.

After you have found all the title/abstract/keywords for Topic A, and then all the relevant subject headings, you then combine those together using OR. You may need to go into the Search History section of the database to do this, and work out whether you can tick boxes next to your various searches to combine them, or have to type out something like "#1 OR #2".

This gives you a "super search" with everything in the database on that topic. It's likely to be a lot!

It might be that adding them together gives no extra results than the amount in either the keywords or the subject headings on their own. This is unusual, but not impossible:

You now go back to the start and for Topic B do the same title/abstract/keywords searches, then the relevant subject headings searches, then combine them as above. Then Topic C, and so on. Again, each of these super searches may have very high numbers - possibly millions.

Finally, you then combine all these super searches together, but this time using AND; they need to mention all the topics. It's possible that there are no articles in that database that mention all those things - the more subjects you AND together, the less results you are likely to find. However, it's also possible to end up with zero as there is a mistake in your search, and in most cases having zero results won't allow you to write your paper or thesis. So contact us if you think you have too few or two many results, and we can advise.

Methodological search filters are search terms or strategies that identify a topic or aspect. They are predefined, tried and tested filters which can be applied to a search.

Study types: 'systematic reviews', 'Randomised Controlled Trials'

Age groups: 'children', 'elderly'

Language: 'English'

They are available to select via the results filters displayed alongside your results and are normally applied at the very end of your search . For instance, on PubMed after running your results it is possible to limit by 'Ages' which gives predefined groupings such as 'Infant: birth-23 months'. These limits and filters are not always the same across the databases, so do be careful .

• << Previous: Finding the Literature
• Next: Managing Your Research >>
• Last Updated: Oct 10, 2023 1:52 PM
• URL: https://libguides.tcd.ie/literature-reviews

An official website of the United States government

The .gov means it's official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• Browse Titles

NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

National Guideline Centre (UK). Evidence review for targets: Hypertension in adults: diagnosis and management: Evidence review D. London: National Institute for Health and Care Excellence (NICE); 2019 Aug. (NICE Guideline, No. 136.)

Evidence review for targets: Hypertension in adults: diagnosis and management: Evidence review D.

Appendix b literature search strategies.

The literature searches for this review are detailed below and complied with the methodology outlined in Developing NICE guidelines: the manual 2014, updated 2017 .

For more detailed information, please see the Methodology Review.

B.1. Clinical search literature search strategy

Searches were constructed using a PICO framework where population (P) terms were combined with Intervention (I) and in some cases Comparison (C) terms. Outcomes (O) are rarely used in search strategies for interventions as these concepts may not be well described in title, abstract or indexes and therefore difficult to retrieve. Search filters were applied to the search where appropriate.

Table 10 Database date parameters and filters used

View in own window

Table 11: Medline (Ovid) search terms

Table 12 embase (ovid) search terms, table 13 cochrane library (wiley) search terms, b.2. health economics literature search strategy.

Health economic evidence was identified by conducting a broad search relating hypertension in adults population in NHS Economic Evaluation Database (NHS EED – this ceased to be updated after March 2015) and the Health Technology Assessment database (HTA) with no date restrictions. NHS EED and HTA databases are hosted by the Centre for Research and Dissemination (CRD). Additional searches were run on Medline and Embase for health economics, economic modelling and quality of life studies.

Table 14 Database date parameters and filters used

Table 15 medline (ovid) search terms, table 16 embase (ovid) search terms, table 17 nhs eed and hta (crd) search terms.

• Cite this Page National Guideline Centre (UK). Evidence review for targets: Hypertension in adults: diagnosis and management: Evidence review D. London: National Institute for Health and Care Excellence (NICE); 2019 Aug. (NICE Guideline, No. 136.) Appendix B, Literature search strategies.
• PDF version of this title (1.3M)

In this Page

• Clinical search literature search strategy
• Health Economics literature search strategy

Other titles in this collection

• NICE Evidence Reviews Collection

Related NICE guidance and evidence

• NICE Guideline 136: Hypertension in adults: diagnosis and management

Supplemental NICE documents

• Methods (PDF)
• Cost-effectiveness analysis: Treatment initiation threshold for people with stage 1 hypertension (PDF)

Recent Activity

• Literature search strategies - Evidence review for targets Literature search strategies - Evidence review for targets

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

Connect with NLM

National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894

Web Policies FOIA HHS Vulnerability Disclosure

Help Accessibility Careers

Your web browser is outdated and may be insecure

The RCN recommends using an updated browser such as Microsoft Edge or Google Chrome

How to undertake a literature search

Introduction.

Undertaking a literature search can be a daunting prospect. By breaking the exercise down into smaller steps, you can make the process more manageable. The following ten steps will help you complete the task from identifying key concepts to choosing databases for your search and saving your results and search strategy. It discusses each of the steps in a little more detail with examples and suggestions of where to get help.

There are ten steps to undertaking a literature search which we'll take you through below:

🎬 - Indicates a video is available with more information.

Please click on the boxes below to get a bit more detail on each step.

First, write out your title and check that you understand all the terms. Look up the meaning of any you don’t understand. An online dictionary or medical encyclopaedia may help with this.

If your search is for a dissertation, you may need to choose your own research question. In this case, you will need to consider whether there is likely to be enough research on your topic. Alternatively, if your topic is too broad, you could be overwhelmed by the number of references.

One way of checking how much is written on your topic is to use Library Search. Most libraries offer a Library Search or discovery tool. It provides a quick search across all the library’s holdings. You can also limit your search by date or type of document. If you just need a few references to help you write an essay, Library Search may be helpful. It also gives quick access to full text items.

Next, you need to identify your key concepts. One way to do this is to look at your title and identify the most important words. Ignore words that tell you what to do with the information you find eg evaluate, assess, compare, as these are not generally used as search terms. In the example below, key concepts have been highlighted:

Evaluate the effectiveness of a mindfulness intervention on the health-related quality of life of rheumatoid arthritis patients

Another way to do this is to break down your title using the PEO framework:

P = Population    E = Exposure    O = Outcome 

This works well where there is no comparison between two types of treatment or intervention.

In our example:

P = rheumatoid arthritis patients

E = mindfulness

O =  health related quality of life

Other question formats are available such as PICO or SPIDER

Tip: Not all search topics will include every element of PICO – some include fewer items.

Once you have identified the key concepts, it’s important to think of any other terms or phrases that might have a very similar meaning. Including such synonyms will make your search as thorough as possible. For example, if your topic is looking for articles on Staff attitudes , you might also use the terms:

• Staff perceptions 
• Staff opinions
• Stereotyping
• Labelling 

If the database you are using has a list of subject heading s , this may help you to find the most appropriate term for your subject. Some databases provide definitions for terms used in the database and may suggest related terms.

A comprehensive search will usually include both subject headings from databases and terms that you have thought of yourself.

Tip: Often your search term will be a phrase instead of a single word. To carry out phrase searches, use double quotes, for example “problem drinking”.

Once you have chosen your search terms, you need to think about the best databases for your topic. The databases you choose will depend on the search question and the libraries you have access to.

Tip: It’s well worth taking a few minutes to get to know the databases available on the Library webpages and what they cover.

The next step is to combine your search terms in such a way that you only retrieve the more relevant references for your search question. In order to do this you need to build a search strategy . This involves using Boolean operators such as AND , OR and NOT .

AND narrows the results of the search by ensuring that all the search terms are present in the results. 

OR broadens the results of the search by ensuring that any of the search terms are present in the results.

NOT limits the results by rejecting a particular search term. Be careful with NOT because it will exclude any results containing that search term regardless of whether other parts of the article might have been of interest.

OR will broaden your number of results while AND will produce fewer results.

Try using this  Search-plan-worksheet   to break your topic down into concepts. These can then be linked together when you run the search. You can also add synonyms within each concept box. The yellow limits box is a prompt to think about any limits you want to apply when searching. This leads us to Step 6.

Tip: Most databases will allow you to use a truncation sign (*) or wildcard (?) to pick up various different endings to words or alternative spellings.

For example:  alcohol* would pick up alcohol, alcoholic, alcoholism, etc

Sm?th would find Smith and Smyth

The next step is to think about any other restrictions you want to make to your results.

Common limiters found on databases include:

• Peer reviewed articles
• Research articles
• Age group (adult, child, older person)
• Document type

Not all databases allow all of the limiters above.

When writing a dissertation, primary research articles are normally required. Where the database allows you, try limiting to research articles only.

Non-research materials can also be useful as an overview of your topic; for example a literature review can give an analysis of what has already been written on a topic.

The video below includes a demonstration of how limits can be applied using the CINAHL database as an example:

CINAHL - advanced

Once you have identified all your search terms and any limits you want to apply, you are ready to run your search on the databases you have chosen. 

Once you have some search results, you can look through them and start to select those that look relevant to your literature search. It is likely you will reject some because they are not quite what you wanted but there will be others that can be marked for further attention.

The title of an article on its own may not tell you very much; read the abstract quite carefully to see if the article is relevant or not.

Tip: You can show more details for each record by clicking on the article title. On some databases, there may be an abstract for the article which you can open. 

If you find you are either generating more results than you can possibly look at or too few results to write about, be prepared to adjust your search terms and the way they are combined.

If you get too many results you could try: •limiting to just the most recent material •adding another term or concept and linking it using “AND” •limiting to a particular country or geographical area such as UK

If you get too few results, you might try: •expanding your date range •removing any geographical limits you have applied  •removing the least important term or concept

Tip: Be prepared to try other databases and keep searching until you feel confident you have found enough relevant material.

Once you have selected some articles that look relevant for your piece of work, you will need to save them so that your hard work is not wasted.

At the same time, you will want to save your search strategy . This is a record of the terms you searched, how you combined them, any limits you applied and how many results you found.

You will also need to choose a way to save your results. One way is to email the results to yourself and this can be done from all the databases .

Another way is to export your results to reference management software such as Zotero, RefWorks, EndNote or Mendeley. This software allows you to collect, organise and cite research. It is suitable for managing references over a long period of time. 

The RCN Library and Archive Service provides help with using Zotero . 

Tip: Keep a record of all the databases you use as you carry out your search. It is also a good idea to note where you found any references you subsequently use for your dissertation.

The final step is to obtain the full text of the articles identified in your search which you believe may be useful for your assignment. If you are lucky, many of these will be available electronically and you may just be able to follow a link to the full text.

Alternatively you can copy and paste your article title into the Library search box  and if it is available as full text, a hyperlink will be shown which will link you to the document.

If you are studying elsewhere and have access to a university or hospital library, they may subscribe to different journals to the RCN Library so it is worth exploring what they can offer. If your library does not have either an electronic copy or a physical copy, you may need to request the article by interlibrary loan .

Tip: It is also worth using Google or other browsers to check for the article title you require. Sometimes the article has been made freely available on the internet by the authors.

Boolean operators – words (AND, OR and NOT) which can be used to combine search terms in order to widen or limit the search results.

Database – this is an online collection of citations to journal articles which have been indexed to make retrieval easier. Some databases which also provide full text access to the articles.

Limits – these are options within a database which allow search results to be broken down further. Common limits are year(s) of publication, document type and language. MEDLINE and CINAHL allow age limits too.

Search Strategy – the list of search terms and limits used to retrieve relevant articles from a database in order to answer a search question.

Subject headings – terms that have been assigned to describe a concept that may have many alternative keywords. All these alternative keywords or terms are brought together under the umbrella of this single term. Most health-related databases use subject headings.

Additional information

If after following these steps, you still can’t find what you are looking for, remember that there is always help available at your library. The RCN Library and Archives Service offers a range of help materials via our Literature searching and training pages . These include: • Databases guides in electronic and printed formats • Video tutorials on how to search the databases • 1-1 training sessions pre-bookable via the RCN website face to face or via zoom

A reading list is also available on dissertation and essay support which provides suggestions for key resources, books and journal articles which may help. Click on the link below to access this list:

Dissertation and essay support reading list

Here are other resources you may also find helpful. You will find links to each resource below too:

• Aveyard H (2019) Doing a literature review in health and social care: a practical guide . 4th edn. London: Open University Press.
• Bettany-Satlikov J (2016) How to do a systematic literature review in nursing: a step-by-step guide . 2nd edn. Maidenhead: Open University Press.
• Coughlan M and Cronin P (2016) Doing a literature review in nursing, health and social care . 2nd edn. Los Angeles: Sage.
• De Brún C, Pearce-Smith N, Heneghan C, Perera R and Badenoch D (2014) Searching skills toolkit: finding the evidence . 2nd edn. Chichester: Wiley Blackwell / BMJ Books.
• Hewitt-Taylor J (2017) The essential guide to doing a health and social care literature review . London: Routledge. 

Critical Appraisal subject guide

Your spaces.

• RCNi Profile
• RCN Starting Out
• Steward Portal
• Careers at the RCN
• RCN Foundation
• RCN Library

Work & Venue

• RCNi Nursing Jobs
• Work for the RCN
• RCN Working with us

Further Info

• Manage Cookie Preferences
• Modern slavery statement
• Accessibility
• Press office

Connect with us:

© 2024 Royal College of Nursing

A Step-by-Step Guide to Writing a Stellar Literature Review (with Help from AI)

Table of contents

Aren’t all of us mini versions of Sherlock Holmes when browsing data and archives for a research piece? As we go through the process, a comprehensive literature review is an essential toolkit to make your research shine.

A literature review consists of scholarly sources that validate the content. Its primary objective is to offer a concise summary of the research and to let you explore relevant theories and methodologies. Through this review, you can identify gaps in the existing research and bridge them with your contribution. 

The real challenge is how to write an excellent literature review. Let’s learn.

What is the purpose of a literature review?

A literature review is an introduction to your research. It helps you put your perspective to the table, along with a summary of the theme.

What does my literature review communicate?

• Explanation of your research: how the information was collected, the research method, the justification of the chosen data sources, and an overview of the data analysis.
• Framework: the journey from where the concept began and how it is presented.
• Connects the previous and current research: 

It presents the broader scope of your research by connecting it to the existing data and debates and underlining how your content fits the prevailing studies. 

In an era of information overload, a literature review must be well-structured. 

Let’s learn all about the structure and style of a literature review that’ll help you strengthen your research.

Literature review– structure and style

Begin with a question and end it with the solution– the key to structuring a literature review. It resembles an essay’s format, with the first paragraph introducing the readers to the topic and the following explaining the research in-depth.

The conclusion reiterates the question and summarizes the overall insights of your research. There’s no word count restriction. —it depends on the type of research. For example, a dissertation demands lengthy work, whereas a short paper needs a few pages. 

In a literature review, maintaining high quality is vital, with a focus on academic writing style. Informal language should be avoided in favor of a more formal tone. 

The content avoids contractions, clearly differentiating between previous and current research through the use of past and present tense. Wordtune assists in establishing a formal tone, enhancing your work with pertinent suggestions. This AI-powered tool ensures your writing remains genuine, lucid, and engaging. 

The option of refining the tonality offers multiple possibilities for rephrasing a single sentence. Thus, pick the best and keep writing.

Get Wordtune for free > Get Wordtune for free >

Your friendly step-by-step guide to writing a literary review (with help from AI)

Do you find it challenging to begin the literature review? Don’t worry! We’re here to get you started with our step-by-step guide.

1. Narrow down the research scope

Simply begin with the question: What am I answering through my research?

Whether it’s cooking or painting, the real challenge is the prep-up for it rather than performing the task. Once you’re done, it smoothly progresses. Similarly, for your literature review, prepare the groundwork by narrowing down the research scope.

Browse and scoop out relevant data inclining well with your research. While you can’t cover every aspect of your research, pick a topic that isn’t too narrow nor too broad to keep your literature review well-balanced. 

2. Hunt relevant literature

The next question: Does this data align with the issue I’m trying to address?

As you review sources of information, hunt out the best ones. Determine which findings help in offering a focused insight on your topic. The best way to pick primary sources is to opt for the ones featured in reliable publications. You can also choose secondary sources from other researchers from a reasonable time frame and a relevant background.

For example, if your research focuses on the Historical Architecture of 18th-century Europe, the first-hand accounts and surveys from the past would hold more weight than the new-age publications. 

3. Observe the themes and patterns in sources

Next comes: What is the core viewpoint in most of the research? Has it stayed constant over time, or have the authors differed in their points of view?

Ensure to scoop out the essential aspects of what each source represents. Once you have collected all this information, combine it and add your interpretations at the end. This process is known as synthesis.

Synthesize ideas by combining arguments, findings and forming your new version.

4. Generate an outline

The next question: How can I organize my review effectively? When navigating multiple data sources, you must have noticed a structure throughout the research. Develop an outline to make the process easier. An outline is a skeletal format of the review, helping you connect the information more strategically.

Here are the three different ways to organize an outline– Chronologically, Thematically, or by Methodology.You can develop the outline chronologically, starting from the older sources and leading to the latest pieces. Another way of organizing is to thematically divide the sections and discuss each under the designated sub-heading.

You can even organize it per the research methods used by the respective authors. The choice of outline depends on the subject. For example, in the case of a science paper, you can divide the information into sections like introduction, types of equipment, method, procedure, findings, etc. In contrast, it’s best to present it in divisions based on timelines like Ancient, Middle Ages, Industrial revolutions, etc., for a history paper.

If you’re confused about how to structure the data, work with Wordtune. 

With the Generate with AI feature, you can mention your research topic and let Wordtune curate a comprehensive outline for your study.

Having a precise prompt is the key to getting the best results.

5. Start filling!

Your next question must be: Am I ready to compose all the parts of the literature review?

Once you’re ready with the basic outline and relevant sources, start filling in the data. Go for an introductory paragraph first to ensure your readers understand the topic and how you will present it. Ensure you clearly explain the section in the first sentence.

However, if beginning from the first paragraph seems intimidating, don’t worry! Add the main body content to the sub-headings, then jump to the introduction. 

Add headings wherever possible to make it more straightforward and guide your readers logically through different sources. Lastly, conclude your study by presenting a key takeaway and summarizing your findings. To make your task easier, work with Wordtune. It helps align your content with the desired tone and refine the structure.

6. Give attention to detail and edit

The last question: Am I satisfied with the language and content written in the literature review? Is it easy to understand?

Once you’re done writing the first draft of a literature review, it’s time to refine it. Take time between writing and reading the draft to ensure a fresh perspective. It makes it easier to spot errors when you disconnect from the content for some time. Start by looking at the document from a bird's eye to ensure the formatting and structure are in order. 

After reviewing the content format, you must thoroughly check your work for grammar, spelling, and punctuation. One of the best approaches to editing and proofreading is to use Wordtune . It helps simplify complex sentences, enhance the content quality, and gain prowess over the tonality.

The dos and don’ts of writing a literature review

Writing a stellar literature review requires following a few dos and don'ts. Just like Sherlock Holmes would never overlook a hint, you must pay attention to every minute detail while writing a perfect narrative. To help you write, below are some dos and don'ts to remember.

Composing a literature review demands a holistic research summary, each part exhibiting your understanding and approach. As you write the content, make sure to cover the following points:

• Keep a historical background of the field of research. Highlight the relevant relation between the old studies and your new research.
• Discuss the core issue, question, and debate of your topic.
• Theories lay the foundation of research. While you’re writing a literature review, make sure to add relevant concepts and ideas to support your statements.
• Another critical thing to keep in mind is to define complex terminologies. It helps the readers understand the content with better clarity. 

Examples of comprehensive literature reviews

Aren’t good examples the best way to understand a subject? Let’s look into a few examples of literature reviews and analyze what makes them well-written.

1. Critical Thinking and Transferability: A Review of the Literature (Gwendolyn Reece)

An overview of scholarly sources is included in the literature review, which explores critical thinking in American education. The introduction stating the subject’s importance makes it a winning literature review. Following the introduction is a well-defined purpose that highlights the importance of research.

As one keeps reading, there is more clarity on the pros and cons of the research. By dividing information into parts with relevant subheadings, the author breaks a lengthy literature review into manageable chunks, defining the overall structure.

Along with other studies and presented perspectives, the author also expresses her opinion. It is presented with minimal usage of ‘I,’ keeping it person-poised yet general. Toward the conclusion, the author again offers an overview of the study. A summary is further strengthened by presenting suggestions for future research as well. 

2. The Use of Technology in English Language Learning: A Literature Review

This literature review is thematically organized on how technology affects language acquisition. The study begins with an introduction to the topic with well-cited sources. It presents the views of different studies to help readers get a sense of different perspectives. After giving these perspectives, the author offers a personalized opinion.

One of the critical aspects that makes this a good literature review is a dedicated paragraph for definitions. It helps readers proceed further with a clear understanding of the crucial terminologies. There’s a comparison of the modern and previous studies and approaches to give an overall picture of the research.

Once the main body is composed, the author integrates recommendations for action-based tips. Thus, the literature review isn’t just summarizing the sources but offering actions relevant to the topics. Finally, the concluding paragraph has a brief overview with key takeaways.

Wordtune: your writing buddy!

A literature review demands the right balance of language and clarity. You must refine the content to achieve a formal tone and clear structure. Do you know what will help you the most? Wordtune !. 

The real-time grammar checker leaves no scope for errors and lets you retain precision in writing. This writing companion is all you need for stress-free working and comprehensive literature review development.

Let the narrative begin

A literary review isn't just about summarizing sources; it's about seamlessly bringing your perspective to the table. Always remember to set a narrative for added interest and a brilliant composition. With structure and style being the pillars of a stellar literature review, work with Wordtune to ensure zero compromises on the quality.

Share This Article:

An Expert Guide to Writing Effective Compound Sentences (+ Examples)

How I Turned Clutter into Cash: 10 Proven Instagram Copywriting Hacks

How to Write a Wikipedia Page So It’ll Get Approved

Looking for fresh content, thank you your submission has been received.

Writing a Literature Review

• What is a Literature Review?
• Step 1: Choosing a Topic
• Step 2: Finding Information
• Step 3: Evaluating Content
• Step 4: Taking Notes
• Step 5: Synthesizing Content
• Step 6: Writing the Review
• Step 7: Citing Your Sources
• Meet the Library Team
• Off-Campus & Mobile Access
• Research Help
• Other Helpful Guides

Welcome to the Citation Style Guide. This guide is designed to help you use the citation style resources we have available to you, and make sure you can find help when you need it.

On this guide you will find: 

• Chicago/Turabian
• << Previous: Step 6: Writing the Review
• Next: Library Services >>
• Last Updated: Mar 22, 2024 11:39 AM
• URL: https://libguides.llu.edu/literaturereview

• Systematic Review
• Open access
• Published: 27 March 2024

Global job satisfaction and fluctuation among community general practitioners: a systematic review and meta-analysis

• Qilin Deng 1   na1 ,
• Yifang Liu 1   na1 ,
• Ziyi Cheng 1 ,
• Qi Wang 2 &
• Junan Liu 1  

BMC Health Services Research volume  24 , Article number:  378 ( 2024 ) Cite this article

Metrics details

Introduction

Community General Practitioners (CGPs) are crucial to primary healthcare worldwide. Their job satisfaction significantly impacts the quality and accessibility of healthcare. However, a comprehensive global perspective on this issue remains absent, necessitating this systematic review and meta-analysis.

This systematic review and meta-analysis sourced literature from PubMed, Web of Science, CNKI, and Wanfang, up to June 14, 2023. Of the 2,742 identified studies, 100 articles were selected for meta-analysis to assess satisfaction levels, and 97 studies were chosen for comparative analysis of influential factors. We employed both meta-analytic and comparative analytic methodologies, focusing on varying geographical, economic, and temporal contexts.

The pooled rate and corresponding 95% confidence interval ( CI ) for job satisfaction among CGPs was 70.82% (95% CI : 66.62–75.02%) globally. Studies utilizing 5-point score scale obtained a random effect size of 3.52 (95% CI : 3.43–3.61). Diverse factors influenced satisfaction, with remuneration and working conditions being predominant. A noticeable decline in job satisfaction has been observed since the coronavirus disease 2019 outbreak, with satisfaction rates dropping from an average of 72.39% before 2009 to 63.09% in those published after 2020.

Conclusions

The downward trend in CGPs’ job satisfaction is concerning and warrants urgent attention from policymakers, especially in regions with an acute shortage of CGPs. The findings from this comprehensive review and meta-analysis provide essential insights for informed healthcare policy-making. It highlights the urgency of implementing strategies to enhance CGP satisfaction, thereby improving the effectiveness of primary healthcare systems globally.

Key message

What is already known?

Community general practitioners (CGPs) are integral to primary healthcare across the world. Existing studies on CGPs’ job satisfaction are region-specific, leaving a gap in a consolidated global perspective.

What are the new findings?

•This study presents the first meta-analysis on global CGPs’ job satisfaction, indicating a moderate general satisfaction level.

•Notable differences in satisfaction levels are observed across countries based on their economic conditions.

•There is a downward trend in global CGPs’ job satisfaction, indicating potential ongoing and systemic challenges.

What do the new findings imply?

The insights from this study provide a foundation for healthcare policymakers and community healthcare managers for informed strategic planning. The observed trends accentuate the necessity for targeted interventions and policy changes. Given the evidence, areas facing significant shortages in CGPs, like China, need to prioritize and recalibrate their strategies focused on CGP recruitment, retention, and well-being.

Peer Review reports

General practitioners (GPs), commonly known as family doctors, constitute the cornerstone of general medical services. The interpretation of this concept varies across different national contexts. In China, Community General Practitioners (CGPs) mainly refer to doctors who work in community health service stations or township health institutions to provide primary health care for residents. Elsewhere, the definition of GPs is close to the concepts of primary care physicians, family physicians in the United States and GPs in the United Kingdom (UK) [ 1 , 2 ].

However, there is a global shortage of primary care professionals and a strong tendency to leave current posts [ 3 ]. In China, the shortage of CGPs is nearly 100,000 in community health service stations in urban areas [ 4 ], and the situation is even more serious in rural areas. In the European Union, the demand gap in healthcare workforce supply is projected to reach about 1 million by 2020, including a shortfall of 230,000 doctors [ 5 ]. Even in the UK, where CGPs are more established, recruitment is difficult and many vacancies exist [ 6 ]. Moreover, a significant proportion of CGPs are contemplating options such as early retirement or looking for some jobs with reduced clinical burden [ 7 ].

Factors that seriously affect the satisfaction level of CGPs include high levels of stress, low salaries, and heavy workloads [ 8 ]. Given the pivotal role of primary care in the healthcare system and its impact on public health, it becomes imperative to thoroughly investigate the current state of job satisfaction among CGPs and to explore the determinants influencing job satisfaction. Despite extensive research on CGPs’ job satisfaction, systematic studies on the job satisfaction status of CGPs worldwide are still lacking. On one hand, different surveys use various assessment scales to evaluate job satisfaction: Chinese studies mostly use the Minnesota studies Questionnaire (MSQ) short-form scale to evaluate job satisfaction, while other countries mostly use the Warr-Cook-Wall (WCW) job satisfaction scale to measure [ 9 ]. Although a large number of studies have been published, there is a lack of global systematic quantitative evaluation of CGPs’ satisfaction. On the other hand, the satisfaction level of CGPs varies with the development of health services, but with the absence of a global study of changes in GP satisfaction and the lack of in-depth analyses of the factors contributing to changes in satisfaction.

This systematic review and meta-analysis report the current status of job satisfaction of CGPs around the world and compare the differences in job satisfaction of CGPs in diverse regions, different levels of economic development, and time periods. It further clarifies the changes in the factors influencing the job satisfaction of global CGPs, provide policy ideas to improve the job satisfaction of CGPs in China, and provides basis for the development of policies on the attractiveness of CGPs.

The protocol of this research was registered with PROSPERO (CRD42023421299) on 5 June 2023, and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Enhancing transparency in reporting the synthesis of qualitative research (ENTREQ) guidelines. (Fig.  1 )

PRISMA flowchart of included studies

Search strategy

We searched PubMed, China National Knowledge Infrastructure (CNKI), Web of Science, and Wan Fang databases, all with a search timeframe from database construction to 14 June 2023. The search strategy was based on the combination of subject terms and keywords, with “general practitioners”, “family physicians”, “job satisfaction” and other related phrases synthesized into the search strategy. (Supplementary 1 ).

Study eligibility

Two researchers (Q.D. and Y.L.) chose potentially relevant articles from reviewed published literature. The eligibility criteria included the following: (1) studies with general practitioners; (2) studies that reported on job satisfaction or included factors influencing job satisfaction; and (3) observational study designs (cross-sectional, case-control, and cohort studies). The study excluded (1) specialists, nurses, and general medical students; (2) literature of a review nature; (3) duplicated literature by the same authors and with similar content; (4) literature with incomplete data; (5) inaccessible full-texts; and (6) literature not published in English or Chinese.

Data extraction

Duplicates were first deleted using Zotero document management software and then screened according to the inclusion and exclusion criteria, divided into three steps. (1) Preliminary screening: Two reviewers excluded literature that did not meet the criteria based on the retrieved citation information, title and abstract. (2) Full-text review and rescreening: reading the literature, resolving disagreements through discussion, and excluding unqualified, such as incomplete data or inconsistency between the study object and the inclusion criteria literature. (3) Data extraction: this stage was performed on high-quality literature that met the criteria and reported the necessary data. (Supplementary 2 ).

Quality assessment

The risk of potential bias was independently conducted by two evaluators (Q.D. and Y.L.). The assessment was grounded in the established criteria for appraising the quality of observational studies as outlined by the Centre for Evidence-Based Management’s Critical Appraisal Skill Program (CASP). Since one question was not relevant to our research, 11 items were used and combined with the evaluation methodology used in the study by Alicja Domagała et al. [ 7 ] to assess the methodological quality of the analysed literature, which was decided by a third reviewer (J.L.) in consultation when the two reviewers had different opinions. The total score was 11 and included studies were grouped into three categories according to the score: high quality (8–11), medium quality (4–7) and low quality (0–3).

Data synthesis

After reviewing all the included literature, the collected studies were subjected to data information extraction into Excel software and narrative data synthesis: publication year, first author, the year studies were conducted, countries and regions where these studies performed, sampling method of the subjects, property of the institution (public or non-public), and influencing factors.

According to the World Bank’s 2022 classification of economies based on Gross National Income ( GNI) per capita, national economies are classified as low-income, lower-middle-income, upper-middle-income, or high-income economies [ 10 ].

The results were presented as two sets of data: dichotomous data (i.e. the number of CGPs in the analysis who were satisfied or very satisfied in the whole group) and continuous data. To address the problem of high questionnaire heterogeneity in studies using diverse scales, job satisfaction as a continuous variable was converted to a common five-point scale: (1) “Very Dissatisfied”, (2) “Dissatisfied”, (3) “Neutral”, (4) “Satisfied”, (5) “Very Satisfied”. Satisfaction = reported score/maximum total score × 5.00. This formula converts satisfaction dimensions with varying total scores to a 5-point scale in the same proportion [ 11 ]. For example, for a questionnaire with a total score of 100, if the reported satisfaction score is 50, the converted score would be 50/100 × 5.00 = 2.50.

Meta-analysis was performed using R v 4.2.3 software and P  < 0.05 was considered statistically significant. Data were tested for heterogeneity using I 2 quantification and Q -tests. In detecting heterogeneity, if the heterogeneity of results across studies was caused by sampling error, the studies were considered homogeneous and a fixed-effects model was used; if the differences between the results of studies were beyond what could be explained by the sampling error ( I 2  > 50%), the random effect model was applied. Apparent heterogeneity was dealt with using subgroup and sensitivity analyses. Random effects models were conducted to test whether differences between groups were statistically significant and to explore possible sources of heterogeneity. Subgroup analyses were performed on data that could be extracted individually, such as the year the study was published, institutional attributes, sample size, region, and economic income level. Sensitivity analyses were conducted using a study-by-study approach to assess the robustness of the studies. Egger’s test combined with funnel plot was used to assess publication bias.

Study characteristic

A total of 2,742 pieces of related literature were obtained from the initial screening. Duplicate publications and data duplication literature were excluded, and after the initial screening to read the title and abstract, and rescreening for full-text reading and quality assessment, 129 publications were finally included into the analysis, and the detailed screening process is shown in Fig.  1 . After excluding publications with incomplete data and other non-conforming studies, 129 unique studies were finalized for inclusion, of which 68 articles provided data both included job satisfaction and related factors affecting job satisfaction, 29 provided only job satisfaction, and 32 only related factors on job satisfaction. Therefore, 97 articles were selected for meta-analysis of job satisfaction and 100 for conducting a comparative analysis of related factors. As the literature may report satisfaction results over multiple periods and with different sample sizes, there exists a single piece of literature that provides results from multiple studies for inclusion in the analysis, and of these 97 pieces of literature, 43 studies provided results in the form of dichotomous data, and 59 studies provided continuous data.

The main characteristics of the included studies are detailed in Table  1 , while the basic information of the studies is detailed in the Supplementary 3 . In this study, 60 studies (47.5%) were from middle-income countries, and 69 studies (53.5%) were from high-income countries. The number of studies from the Asian region accounted for 45.7% of the total, with 98 studies (76.0%) published after 2009. The quality assessment of the studies identified 68 studies (52.7%) as high quality and 61 studies (47.3%) as moderate quality. No low-quality articles was identified. A more detailed summary of the quality of the literature can be seen in the Supplementary 4 .

Overall job satisfaction

Forty-three studies provided satisfaction results in dichotomous data, i.e. the proportion of CGPs who were satisfied or very satisfied. The percentage of satisfied CGPs ranged from 26% up to 94% across studies. The random effect size of the CGPs’ job satisfaction score was 70.82% (95%CI: 66.62–75.02%), I 2  = 99.3% and Q  = 5798.51, P  < 0.01 (Supplement 5 ). Based on a subjective examination of funnel diagram and Egger’s text ( P  > 0.05), there was no evidence of publication bias.

Fifty-nine studies provided satisfaction results in the form of continuous data, i.e., the average results of two scales used in the study, including 27 studies reported on a 5-point Likert scale and 31 studies reported on a 7-scale Likert scale. Converting the different dimensions of job satisfaction to a generic 5-point scale obtained a random effect size of 3.52 (95%CI: 3.43–3.61), I 2  = 100%, P  < 0.01. However, the Egger’s test showed a significant publication bias in overall job satisfaction ( P  = 0.01). Obvious asymmetry was also observed in the funnel plot (Supplement 6 , 7 ). Consequently, the corrected results were achieved by trim-and-fill method and showed that the mean value of job satisfaction was 3.72 (95%CI: 3.62–3.82), I 2  = 100%, P  < 0.01.

Subgroup analysis

For further examining the sources of study heterogeneity, subgroup analyses were conducted in the dichotomous data. As shown in Table  2 , no significant differences in job satisfaction levels were found between study locations, organizational attributes, satisfaction measurement tools, urban and rural areas, and sample sizes. Instead, differences between groups were statistically significant ( P  < 0.05) in terms of income level and the time to publication of the articles in the study economies. Satisfaction among CGPs was lower in upper-middle-income countries 64.38% (95%CI: 57.11–71.65%) compared to high-income countries 74.49% (95%CI: 69.78–79.20%). The highest percentage of satisfied CGPs was 72.39% (95%CI: 65.42–79.35%) in studies conducted before 2009, while the lowest percentage of satisfied CGPs was 63.09% (95%CI: 60.68–65.49%) in studies conducted after 2020.

By further analyzing the studies in different years, we found that global CGPs’ satisfaction fluctuates up and down in the medium-upper stratum. In contrast, there has been a slight downward trend in recent years (Fig.  2 ). Besides, Chinese CGPs’ satisfaction has been lower than the global level in all years.

Trends in job satisfaction among CGPs

Factors associated with job satisfaction

One hundred papers examined the factors influencing CGPs’ satisfaction. Based on previous studies [ 11 , 12 ], we classified the influential factors into eight categories, namely personal traits, personal fulfilment, remuneration, job description, working conditions, governance, social recognition, and doctor-patient relationship. The breakdown of the factors is detailed in the Supplement 8 .

Since the variety of reporting methods for measuring impact factors made it difficult to extract data, a comparative analysis of 100 papers was conducted (Table  3 ).

We found that remuneration was the most frequently meaningful factor amongst the 40 studies in China. This was followed by personal traits (34 studies, 70.8%) and personal fulfillment (30 studies, 62.5%). In the rest of Asia region, personal characteristics (6 studies, 100.0%) and remuneration (3 studies, 50.0%) were the most frequently cited factors contributing to CGPs’ satisfaction. In the Middle East and Africa region, every study noted the influence of personal traits (5 studies, 100.0%) on satisfaction. But working conditions were the most commonly stated factor in the Europe, North America and Oceania regions, with 21 (84.0%) and 15 (93.8%) reports.

In China, the factor that was least found to be statistically significant was doctor-patient relationship (6 studies, 12.5%). Concurrently, social recognition emerged as the least reported influential factor in regions such as the Middle East, Africa, North America, and Oceania.

Overall, remuneration (69 studies, 69.0%), personal traits (67 studies, 67.0%), and job description (63 studies, 63.0%) were noted the most frequently as statistically significant relationship with job satisfaction. Personal fulfillment (43 studies, 43.0%) and governance (45 studies, 45.0%) were reported in lower numbers, but still higher than social recognition (22 studies, 22.0%) and doctor-patient relationship (16 studies, 16.0%).

This article presents the first comprehensive summary and analysis of global literature pertaining to the job satisfaction of CGPs and its principal influencing factors, employing both meta-analysis and comparative analysis. The assessment results of job satisfaction and its influencing factors are vital references for current healthcare policies, which not only reflect the implementation effects of current CGPs policies, but also serve as one of the critical “wind vanes” for policy adjustment [ 13 ].

In China, Jing Feng et al. [ 14 ] showed that CGPs’ job satisfaction was an important factor influencing their turnover intention. Studies in other countries have reached the same conclusion. Ingris Gilled et al. [ 15 ] found that a decrease in overall job satisfaction reduces the willingness of healthcare workers to remain in their jobs. The results of a meta-analysis including 485 articles showed that job dissatisfaction was strongly associated with burnout, psychiatric problems, depression and anxiety [ 16 ]. Therefore, a comprehensive job satisfaction survey among CGPs is an essential factor in evaluating health policies and predicting turnover rates. However, the evidence for evaluating CGPs’ job satisfaction has been fragmented, either only within a particular country [ 17 ], only for rural doctors without considering CGPs in urban areas [ 11 ], or only a systematic review completed without meta-analysis [ 9 ]. This study not only collected the percentage of the number of satisfied CGPs globally, but also collected and integrated job satisfaction presented as continuous data using the Likert 5-level scale as a bridge and evaluated the overall job satisfaction after converting the formula. In addition, the results of studies from China and other countries on related influencing factors were compared and analyzed to provide basis for health care policymakers and community healthcare managers.

This study shows that the overall job satisfaction of CGPs is at a moderate level. As mentioned in the results, 3.52 (95% CI : 3.43–3.61) is the average satisfaction reported using the Likert 5-level scale. Based on the findings of the data presented in dichotomous form, it can be inferred that 70.82% (95% CI : 66.62–75.02%) of the CGPs who obtained the study were satisfied with their jobs. Nevertheless, we must carefully consider the credibility of the results due to the high degree of heterogeneity between studies. The publication year of the study and the income level of the country may be related to the observed heterogeneity.

The overall satisfaction level of CGPs in China is lower than the global average, but the gap with other regions is not obvious, which may be related to the income level of Chinese economy. According to the World Bank’s 2022 classification, China is in the upper-middle income level. In the subgroup analysis, 16 studies were conducted in the upper-middle-income region, and the percentage of CGPs who were satisfied with their jobs in this region (64.38%) was less than the other 28 CGPs who worked in the high-income region (74.49%). This is in line with the results reported in previous studies, where a cross-sectional study undertaken in 34 countries showed that the association between national economic level and satisfaction is considered universal, with the suggestion that national culture and institutions may contribute to this relationship [ 18 ].

Furthermore, this study found differences in satisfaction across time. The studies conducted during the coronavirus disease 2019 (COVID-19) pandemic (63.09%) were notably lower than those conducted during the period 2010–2019 (71.07%), and prior to 2009 (72.39%). These findings may indicate that CGPs have had to take on increasing responsibilities and multitasking during the prevention and control of COVID-19 pandemic, which placed a severe physical and psychological burden on primary care workers [ 19 , 20 ]. Although some studies have shown that at the peak of the COVID-19 pandemic, 20-30% of healthcare workers reached critical levels of anxiety, depression and distress [ 21 ]. This study included only three articles conducted after the COVID-19 pandemic. Therefore, the interpretation of the results should be considered cautiously, and further extensive cohort studies may be needed to provide relevant evidence.

Notably, satisfaction among global CGPs has not been trending in a favorable direction over time and has even experienced a continued downward trend since the COVID-19 pandemic. As early as 2001, the BMJ [ 22 ] expressed concern about doctors’ job dissatisfaction, suggesting that they felt overworked and under-supported. CGPs feel intensely needed, while at the same time, financial overdrafts make it urgent to increase their income, which contributes to doctor burnout and a decline in the care quality [ 23 , 24 , 25 ]. Over the past two decades, several healthcare systems reform measures have been implemented in countries around the globe [ 26 , 27 ]. Still, the results of the reforms are unsatisfactory considering the findings of this study. It is also worth reflecting on what will happen next if physician dissatisfaction continues to spread, and now may be an important point in time to consider the next strategies and changes that countries must implement.

Additionally, this study found a preference for reporting a significant impact from remuneration (79.6%) across Asia when exploring the factors influencing CGPs’ satisfaction. The Europe, North America, and Oceania regions were more concerned with the effects of job description and working conditions compared to the Asia region. We also found that overtime, work facilities, and work hours were more frequently identified as statistically significant factors than income (54.8%), accounting for more than 75% in these regions. This disparity is not only due to the variations in research perspectives across countries but also to the fact that CGPs have unique job demands and expectations depending on different national conditions, economic levels, and institutional attributes. It has been shown that wages are strongly correlated with job satisfaction in low-income countries, but the correlation does not exist in middle- and high-income countries [ 28 ]. Moreover, a large number of studies have shown that job autonomy has a significant effect on job satisfaction [ 29 ]. However, Chinese CGPs valued increased salary compensation more than hospital specialists. And their lower education level and lower demand for job autonomy may partially explain the differences in reporting of influencing factors from China and other countries [ 30 , 31 ].

On the other hand, the workload problem of CGPs in China also deserves attention. In China, the shortage of CGPs has resulted in a heavier work burden and increased overtime work, which has triggered growth in dissatisfaction and higher turnover rates. Regarding work content, Chinese studies more often investigated the impact of management work on CGPs (29 studies, 60.4%). Some articles reported that CGPs need to invest considerable work time in tasks assigned by the public health sector since the National Health System in 2009. CGPs must spend much time and effort coping with excessively frequent performance appraisals [ 32 ]. Also, studies from other countries suggest that CGPs have more unnecessary non-health service tasks than doctors in other positions, which causes them to be more prone to burnout [ 33 , 34 ].

Therefore, we suggest that the Government should prioritize the augmentation of funding community healthcare, with an initial focus on enhancing the compensation mechanisms for CGPs. Next, it is essential to carry out training work for the community health organizations’ personnel, conduct vocational training and quality education, improve the overall quality level, and create a favorable atmosphere of career development. Finally, work optimization based on the multi-professional teamwork model is conducive to higher efficiency and satisfaction levels.

There are some limitations of this study. First, the literature search lacked a global definition of the “community general practitioner” concept. Although the term’s meaning varies worldwide and healthcare systems are not entirely the same, there are sufficient similarities in working conditions to summarize and compare job satisfaction. Second, the diverse array of questionnaires and scales employed in the studies introduced a degree of variation that precluded the complete aggregation of results. However, this study included two types of data outcomes, both of which coherently reflected the general level of job satisfaction among CGPs. Third, in this study, the starting point of Chinese data is inconsistent with that of the global data, partly because China started to build the community health service system in 1997 before forming a genuinely community-based CGPs workforce. Another aspect is that early studies’ quality of CGPs’ job satisfaction needs to be improved based on literature review criteria. Furthermore, the reporting of influencing factors in the primary literature is reported through various methods and categories, making it difficult to extract data. As a result, it was difficult to combine the effects of the factors on job satisfaction. In the future, there is a need to use standardization to better identify the key factors that influence job satisfaction. Lastly, high heterogeneity collected among the studies may lead to a decrease in the credibility of the results.

In this meta-analysis, the level of global job satisfaction among CGPs globally was moderate. Subgroup analyses found that global CGPs’ job satisfaction has not tended to increase over the years and may even decrease further over time. A comparison of changes in satisfaction over time reveals that Chinese CGPs’ satisfaction has been lower than the global level for many years. Additionally, the study highlighted regional variances in the factors influencing job satisfaction. In Asia, the primary focus of research is on salary and compensation, in contrast to the emphasis on working conditions predominant in studies from Europe and North America. Therefore, countries should pay more attention to the dissatisfaction of CGPs at work and take various measures to improve the career satisfaction of CGPs according to local conditions.

Data availability

The datasets supporting the conclusions of this article are included within the article and its supplement.

Abbreviations

General Practitioner

General Practitioners

Coronavirus disease 2019

Minnesota studies Questionnaire

Warr-Cook-Wall

China National Knowledge Infrastructure

Critical Appraisal Skill Program

Gross National Income

Campbell JL, Mendive J, Timmermans A. Primary care and general practice in Europe: West and South. Oxford, UK: Oxford University Press; 2004.

Google Scholar  

Stokes T, Tarrant C, Mainous AG, Schers H, Freeman G, Baker R. Continuity of care: is the personal doctor still important? A survey of general practitioners and family physicians in England and Wales, the United States, and the Netherlands. Annals Family Med. 2005;3:353–9.

Article   Google Scholar  

Shen X, Jiang H, Xu H, et al. The global prevalence of turnover intention among general practitioners: a systematic review and meta-analysis. BMC Fam Pract. 2020;21:246.

Article   PubMed   PubMed Central   Google Scholar  

Xin Rao. Cultivation of General Practitioners in West China Hospital of Sichuan University. West China Med J. 2012;27:1717–20.

European Union. EU level Collaboration on Forecasting Health Workforce Needs, Workforce Planning and Health Workforce Trends—A Feasibility Study. 2012.

Helen Lester SM, Campbell. Ruth McDonald. The present state and future direction of primary care: a qualitative study of GPs’ views. Br J Gen Pract. 2009;59:908–15.

Alicja Domagała, Małgorzata M, Bała et al. Juan Nicolás Peña-Sánchez,. Satisfaction of physicians working in hospitals within the European Union: state of the evidence based on systematic review. European Journal of Public Health 2019; 29: 232–41.

Van Irene AAH, Verhoeven, Klaas H, Groenier JW, Groothoff. Jan De Haan. Job satisfaction among general practitioners: a systematic literature review. Eur J Gen Pract. 2006;12:174–80.

Zihui L, Jing F, Xin S, Yiling L, Yong G. Job satisfaction among general practitioners at home and abroad: a literature review. Mod Prev Med. 2022;49:2194–9.

Nada Hamadeh C, Van Rompaey E, Metreau, Shwetha Grace Eapen. New World Bank country classifications by income level: 2022–2023. 2022; published online July 1. https://blogs.worldbank.org/opendata/new-world-bank-country-classifications-income-level-2022-2023 (accessed Jan 4, 2024).

Chen Y, You Y, Wang Y, Wang Y. Systematic and meta-based evaluation on job satisfaction of village doctors: an urgent need for solution issue. Front Med (Lausanne). 2022;9:856379.

Article   PubMed   Google Scholar  

Tenaw Z, Siyoum M, Tsegaye B, Werba TB, Bitew ZW. Health professionals Job satisfaction and Associated Factors in Ethiopia: a systematic review and Meta-analysis. Health Serv Res Manag Epidemiol. 2021;8:23333928211046484.

PubMed   PubMed Central   Google Scholar  

Guilbert J-J. The World Health Report 2006: working together for health. Educ Health (Abingdon). 2006;19:385–7.

Feng J, Sang W, Lei Z, et al. The impact of burnout on turnover intention among Chinese general practitioners: the mediating effect of job satisfaction and the moderating effect of professional identity. Int J Soc Psychiatry. 2023;69:705–13.

Gilles I, Burnand B, Peytremann-Bridevaux I. Factors associated with healthcare professionals’ intent to stay in hospital: a comparison across five occupational categories. Int J Qual Health care: J Int Soc Qual Health Care. 2014;26. https://doi.org/10.1093/intqhc/mzu006 .

Faragher Eb, Cass M, Cooper C. The relationship between job satisfaction and health: a meta-analysis. Occup Environ Med. 2005;62. https://doi.org/10.1136/oem.2002.006734 .

Bekahegn Girma J, Nigussie A, Molla, Moges Mareg. Health professional’s job satisfaction and its determinants in Ethiopia: a systematic review and meta-analysis. Arch Public Health. 2021;79:141.

Stobbe EJ, Groenewegen PP, Schäfer W. Job satisfaction of general practitioners: a cross-sectional survey in 34 countries. Hum Resour Health. 2021;19:57.

Hamzeh M, Alrawashdeh, Ala’a B, Al-Tammemi MK, Alzawahreh, et al. Occupational burnout and job satisfaction among physicians in times of COVID-19 crisis: a convergent parallel mixed-method study. BMC Public Health. 2021;21. https://doi.org/10.1186/s12889-021-10897-4 .

Schrimpf A, Bleckwenn M, Braesigk A. COVID-19 continues to Burden General practitioners: impact on workload, provision of Care, and intention to leave. Healthc (Basel). 2023;11:320.

Stephen X, Zhang, Jing Liu AA, Jahanshahi, et al. At the height of the storm: Healthcare staff’s health conditions and job satisfaction and their associated predictors during the epidemic peak of COVID-19. Brain Behav Immun. 2020;87:144–6.

Smith R. Why are doctors so unhappy? There are probably many causes, some of them deep. BMJ. 2001;322:1073–4.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Rihab AW, Mahmoud A, Maqsood N. Job Satisfaction and Mental Health among Physicians in Primary Health Care Centers in Kuwait. Health 2019.

Chris O. Ifediora. Assessing the satisfaction levels among doctors who embark on after-hours home visits in Australia. Fam Pract. 2016;33:82–8.

Wu D, Wang Y, Lam KF, Hesketh T. Health system reforms, violence against doctors and job satisfaction in the medical profession: a cross-sectional survey in Zhejiang Province, Eastern China. BMJ OPEN. 2014;4. https://doi.org/10.1136/bmjopen-2014-006431 .

Luft HS. What works and what doesn’t work well in the US healthcare system. PharmacoEconomics. 2006;24(Suppl 2):15–28.

Yip W, Fu H, Chen AT, et al. 10 years of health-care reform in China: progress and gaps in Universal Health Coverage. Lancet. 2019;394:1192–204.

Diaz-Serrano L, Cabral Vieira JA. Low pay, higher pay and job satisfaction within the European Union: Empirical evidence from fourteen countries. Higher Pay and Job Satisfaction within the European Union: Empirical Evidence from Fourteen Countries (April 2005) 2005.

Ilona Buciuniene A, Blazeviciene, Egle Bliudziute. Health care reform and job satisfaction of primary health care physicians in Lithuania. BMC Fam Pract. 2005;6:10.

Xuan, Chang. Tianai Yin. Study on the Relationship among Job Satisfaction,Career Burnout and Intent to Stay in General Practitioners. 2015. https://d.wanfangdata.com.cn/thesis/ChJUaGVzaXNOZXdTMjAyMzAxMTISCFkyNzkwNzg0GghjY3N2cDRlOA%3D%3D .

Zheng C, Chen B, Huang Z, et al. Job satisfaction and influencing factors in the First Batch of Community Health Workers Delivered Pilot Family Doctor Services in Guangdong Province. Chin Gen Pract. 2020;23:964–8.

Yinzi Jin H, Wang D, Wang B, Yuan. Job satisfaction of the primary healthcare providers with expanded roles in the context of health service integration in rural China: a cross-sectional mixed methods study. Hum Resour Health. 2019;17:70.

Werdecker L. Tobias Esch. Burnout, satisfaction and happiness among German general practitioners (GPs): a cross-sectional survey on health resources and stressors. PLoS ONE. 2021;16:e0253447.

Laurenz L, Meier, Norbert K, Semmer. Illegitimate tasks as assessed by incumbents and supervisors: converging only modestly but predicting strain as assessed by incumbents, supervisors, and partners. Eur J Work Organizational Psychol. 2018;27:764–76.

Download references

Acknowledgements

This work was funded by the National Natural Science Foundation of China [Grant no. 72274070].

Author information

Qilin Deng and Yifang Liu are co-first authors

Authors and Affiliations

Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, China

Qilin Deng, Yifang Liu, Ziyi Cheng & Junan Liu

Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 430030, Wuhan, China

You can also search for this author in PubMed   Google Scholar

Contributions

JL and QD conceived the study, participated in quality assessment. QD, YL and JL performed data extraction, analysis, manuscript preparation and revision. ZC and QW participated in the analysis, method discussion and the revision of the article. All authors critically reviewed the manuscript and approved the final version as submitted.

Corresponding author

Correspondence to Junan Liu .

Ethics declarations

Consent for publication.

Not applicable.

Ethics approval and consent to participate

Competing interests.

The authors declare no competing financial interest.

Additional information

Publisher’s note.

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Deng, Q., Liu, Y., Cheng, Z. et al. Global job satisfaction and fluctuation among community general practitioners: a systematic review and meta-analysis. BMC Health Serv Res 24 , 378 (2024). https://doi.org/10.1186/s12913-024-10792-9

Download citation

Received : 22 November 2023

Accepted : 27 February 2024

Published : 27 March 2024

DOI : https://doi.org/10.1186/s12913-024-10792-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Job satisfaction
• General practitioners
• Influencing factor
• Meta-analysis

BMC Health Services Research

ISSN: 1472-6963

• General enquiries: [email protected]

Adherence and Persistence to Basal Insulin Among People with Type 2 Diabetes in Europe: A Systematic Literature Review and Meta-analysis

• Open access
• Published: 23 March 2024

Cite this article

You have full access to this open access article

• Esteban J. Gimeno 1 ,
• Mette Bøgelund 2 ,
• Sara Larsen 3 ,
• Anna Okkels 2 ,
• Signe B. Reitzel 2 ,
• Hongye Ren 3 &
• Domingo Orozco-Beltran 4  

108 Accesses

1 Altmetric

Explore all metrics

Introduction

Diabetes is associated with a number of complications, particularly if glycaemic targets are not achieved. Glycaemic control is highly linked to treatment persistence and adherence. To understand the burden of poor persistence and adherence, this systematic literature review identified existing evidence regarding basal insulin adherence/non-adherence and persistence/non-persistence among people with diabetes in Western Europe (defined as the UK, France, Spain, Switzerland, the Netherlands, Ireland, Austria, Portugal, Denmark, Norway, Sweden, Finland, Italy, Germany, Iceland and Belgium).

Eligible studies were systematically identified from two databases, Medline and Embase (published between 2012 and June 2022). Conference abstracts from ISPOR and EASD were manually included. Identified studies were screened by two independent reviewers in a two-step blinded process. The eligibility of studies was decided on the basis of pre-established criteria. A proportional meta-analysis and comparative narrative analyses were conducted to analyse the included studies.

Twelve studies were identified. Proportions of adherence/non-adherence and persistence/non-persistence varied across studies. Pooled rates of non-persistence at 6, 12 and 18 months were 20.3% (95% CI 13.8; 27.8), 33.8% (95% CI 24.1; 44.3) and 36.5% (95% CI 33.6; 39.4), respectively. In the literature, the proportion of adherent people ranged from 41% to 64% (using the outcome measure medication possession ratio (MPR) > 80%), with a pooled rate of 55.6% (95% CI 45.3; 65.6), suggesting that approximately 44% of people with type 2 diabetes (T2D) are non-adherent.

The results highlight that almost half of patients with T2D in Western Europe have poor adherence to insulin therapy and, at 18 months, one in three patients do not persist on treatment. These findings call for new basal insulin therapies and diabetes management strategies that can improve treatment persistence and adherence among people with T2D.

Similar content being viewed by others

Comparing Real-World Effectiveness of Dulaglutide and Insulin as the First Injectable for Patients with Type 2 Diabetes: An Australian Single-Site Retrospective Chart Review

Jared A. Houssarini, Alan J. M. Brnabic & Marwan Obaid

One in Seven Insulin-Treated Patients in Developing Countries Reported Poor Persistence with Insulin Therapy: Real World Evidence from the Cross-Sectional International Diabetes Management Practices Study (IDMPS)

Juliana C. N. Chan, Juan José Gagliardino, … Pablo Aschner

Achieving HbA1c targets in clinical trials and in the real world: a systematic review and meta-analysis

Edoardo Mannucci, Matteo Monami, … Massimo Porta

Avoid common mistakes on your manuscript.

The prevalence of diabetes is increasing and the number of adults with diabetes in Europe is expected to increase from 61 million in 2021 to 69 million in 2045 [ 1 ]. Type 2 diabetes (T2D) accounts for around 90% of diabetes cases [ 2 ]. As a result of the gradual onset of T2D, the condition can remain undiagnosed for many years, while health complications might develop and progress [ 3 ].

It is well known that diabetes is associated with a high number of health complications (renal, cardiovascular, neurological and retinal) as well as increased mortality, especially if glycaemic targets are not achieved [ 4 , 5 , 6 , 7 , 8 , 9 ]. According to the World Health Organization (WHO), adults with diabetes have more than a twofold risk of vascular outcomes, including both coronary heart disease and stroke [ 4 ], and cardiovascular disease is the most common cause of death among people with diabetes [ 10 ]. Additionally, a registry study including 32,725 people with diabetes found a statistically significant association between glycaemic burden and micro- and macrovascular complications such as diabetes foot, disease of the arteries and cerebrovascular disease [ 6 ]. Diabetes complications are burdensome for both the individual and society, as they are associated with a reduced health-related quality of life among people with diabetes and increased costs due to healthcare utilisation and absence from work [ 11 , 12 ]. This emphasises the need for correct and sufficient treatment of diabetes.

Several factors impact whether people with T2D achieve glycaemic control [ 13 , 14 ]. Long-acting insulin, also called basal insulin, has a longer duration and a lower peak of action, which allows for more flexible treatment. The mechanism of basal insulins contributes to an improved glycaemic control among people with T2D who cannot maintain adequate glycaemic control by other glucose-lowering drugs alone as well as a reduction in the risk of hypoglycaemia [ 15 , 16 , 17 , 18 ]. Thus, basal insulin is associated with clinical benefits and potentially a reduced fear of hypoglycaemia among people with T2D and clinicians [ 17 ]. However, earlier research has shown that one in three people with T2D are unwilling to start insulin treatment [ 19 , 20 ]. Furthermore, some people have difficulties managing the insulin treatment, which may result in discontinuation of the treatment [ 16 ], and evidence has shown that one cause of poor glycaemic control is the lack of adherence (defined as complying with the prescribed medicine in terms of drug schedules and dosages) and persistence (defined as continuing to take medication throughout the prescribed period) to antidiabetic medication, i.e. basal insulin treatment [ 21 , 22 , 23 ]. A previously published systematic literature review has found that improved adherence to antidiabetic medication in people with T2D is associated with improved glycaemic control and fewer hospitalisations and emergency department visits [ 24 ]. Hence, adherence and persistence are essential determinants of improved diabetes control.

In order to support people with diabetes in achieving adherence and persistence to insulin treatment and thus disease control, it is important first to understand the scope of the problem in a real-world setting. Evidence regarding insulin adherence/non-adherence and persistence/non-persistence among people with diabetes is broad. However, hardly any publications compare and pool evidence focusing particularly on adherence/non-adherence and persistence/non-persistence to basal insulin in Western Europe [ 24 , 25 , 26 ]. Newly published reviews by Evans et al. [ 24 ] and Lee et al. [ 26 ] investigated adherence and persistence to major antidiabetic medication classes, including basal insulin, among people with T2D. However, both studies had no eligibility criteria regarding geography, thus including data from all over the world. Another review by Azharuddin et al. [ 27 ] also investigated adherence to antidiabetic medication among all people living with diabetes, but only with evidence from low- and middle-income countries. Inclusion of countries with differences in the organisation and financing of healthcare systems makes direct comparisons across studies and pooled analyses problematic. Therefore, to make more direct comparisons possible, the objective of this systematic literature review was to identify and collate existing evidence on basal insulin adherence/non-adherence and persistence/non-persistence among people with diabetes in Western Europe.

A systematic literature review was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines [ 28 ]. The following research question was addressed in the systematic literature review: What is the persistence/non-persistence and adherence/non-adherence among adults with diabetes using basal insulin in Western Europe? The two electronic databases MEDLINE (via the PubMed platform) and Embase were searched in June 2022. The details of the search strings applied in this systematic literature review are presented in Table  1 . In addition to the systematic search, EASD and ISPOR were manually searched for relevant peer-reviewed conference abstracts. These conferences are some of the leading societies for health economics and outcome research as well as diabetes research, and they are known to publish relevant abstracts on adherence or persistence in diabetes care.

This article is based on previously conducted studies and does not contain any new studies with human participants or animals performed by any of the authors.

Eligibility Criteria

The PICO (population, intervention, comparator and outcomes) reporting system was used to define a relevant review question and to help formulate the search strategy. The eligibility criteria are presented in Table  2 . The systematic literature review included studies in which there was a population of adults from Western Europe (including the UK, France, Spain, Switzerland, Netherlands, Ireland, Austria, Portugal, Denmark, Norway, Sweden, Finland, Italy, Germany, Iceland and Belgium) with diabetes treated with basal insulin. In addition, studies had to present original data and analyses. The predefined outcomes of interest were all findings related to adherence/non-adherence or persistence/non-persistence to basal insulin treatment reported as proportions of patients. Treatment persistence is defined as continuing to take medication throughout the prescribed period, and treatment adherence is defined as complying with the prescribed medicine in terms of drug schedules and dosages [ 21 ]. The included studies were English-language studies published between 2012 and 2022.

Study Selection and Data Collection

All studies were reviewed in a blinded two-step process by two independent reviewers. The first step was screening of title and abstract. In the second step, eligible studies were screened at full-text level. The studies were included in accordance with the predefined eligibility criteria and any case of disagreement about the eligibility of a study was resolved through discussion between the two reviewers or by referral to the project manager. Each study could only be included once, meaning that a publication would be excluded if it presented a study already included through another publication. However, background information such as study characteristics could be combined from both publications if complete information was not available in one of the publications. Silvi was used to ensure a structured review process [ 29 ].

Any measures of adherence/non-adherence and persistence/non-persistence available from the literature were considered relevant regardless of the follow-up period or methodology. Adherence/non-adherence was often measured by medication possession ratio (MPR) which is calculated as the proportion (or percentage) of days covered by the medication dispensed during a specified time period or over a period of refill intervals (using a threshold of 80%). Other measures of adherence/non-adherence included missed doses, mistimed doses and reduced doses. Persistence/non-persistence was measured as uninterrupted treatment administration.

Identified Studies

The systematic literature search of Medline and Embase resulted in 11 eligible studies. Additionally, we identified two relevant poster abstracts from EASD and ISPOR, yielding a total of 13 eligible studies [ 9 , 15 , 16 , 25 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 ]. The flow of studies through the two-step study selection process is presented in a flowchart in Fig.  1 . This manuscript presents results from the studies regarding insulin adherence/non-adherence and persistence/non-persistence among people with T2D. By further excluding studies that do not present any subgroup results stratified by T2D, this manuscript includes 12 eligible studies. From the 12 studies, a total of 30 relevant subgroup results were identified. It should be noted that one subgroup could present results on multiple outcome measures.

Flowchart. † Although the studies were excluded, they contributed with background information about the subpopulations

Of the 12 studies included in this manuscript, four presented results on adherence/non-adherence [ 15 , 30 , 32 , 37 ] and nine presented results on persistence/non-persistence [ 9 , 16 , 25 , 31 , 33 , 34 , 35 , 36 , 37 ], one of which presented results on both adherence/non-adherence and persistence/non-persistence [ 37 ]. This last-mentioned study included people treated with all kinds of insulin, which is why it was not possible to extract results for basal insulin only. Therefore, the insulin type in the study will be categorised as basal-bolus insulin throughout this manuscript.

Data Extraction and Statistical Analyses

A comprehensive data extraction was conducted from all eligible studies following the PRISMA checklist [ 28 ] and using a pre-specified data extraction form in Microsoft Excel. Separate data points were extracted for each population and subpopulation with individual findings, i.e. subgroups by country, insulin type or background therapy. Data extraction included information on study characteristics, i.e. author, year of publication and information about the study population (size, country, mean age, background therapy, diabetes status, insulin status and diabetes-associated complications), methodology, i.e. data source and follow-up time, and findings from all outcomes deemed relevant for the research question.

When appropriate, a proportional meta-analysis calculating pooled rates was performed to assess insulin adherence/non-adherence and persistence/non-persistence among people with T2D in Western Europe. As recommended in the literature, the pooled rates were based on a random-effects model and Freeman–Tukey transformation using the software JBI SUMARI [ 39 , 40 ]. Heterogeneity between the included studies was assessed through tau squared, chi squared and I 2 statistics. As a result of high variance in the outcome definitions applied in the included studies, comparative narrative analyses were performed, when proportional meta-analysis was inappropriate. In studies not reporting non-persistence or non-adherence rates, these were calculated as 1 minus the reported persistence or adherence rate.

To investigate the identified data further, a number of sensitivity analyses were conducted, including an analysis of persistence rates when results on NPH were excluded, and analyses of both persistence and adherence findings when data not differentiating between basal and bolus insulin were excluded.

Identified Outcome Measures

Among the 12 eligible studies, insulin persistence/non-persistence and adherence/non-adherence were evaluated using 19 different outcome measures (persistence, 5; adherence, 14). Table  3 provides an overview of the identified outcome measures for both persistence and adherence, together with the number of subgroup results for the respective outcome measures.

Results on Insulin Persistence

Persistence to basal insulin was measured after either 3, 6, 12, 18 or 24 months in the nine studies reporting results on insulin persistence. The most frequent measure was persistence after 12 months, which was used in five of the nine studies [ 31 , 34 , 35 , 36 , 37 ]. Persistence after 6 months was measured in four of the studies [ 9 , 31 , 36 , 37 ], and persistence after 3 and 18 months was measured in one study each [ 25 , 37 ]. Persistence after 24 months was measured in two studies [ 16 , 33 ]. The majority of the included studies were based on registry data [ 16 , 25 , 31 , 33 , 34 , 35 , 36 , 37 ]; however, one study used self-reported questionnaire data [ 9 ]. The size of study populations varied from 549 included people [ 9 ] to 680,131 included people [ 16 ]. An overview of the studies, study characteristics and respective results regarding persistence to basal insulin among people with T2D is presented in Table  4 .

On the basis of results from the studies reporting 6- and 12-month persistence rates, we calculated non-persistence rates (equal to 1 minus persistence rates). These are shown by different types of basal insulin in Fig.  2 . Within the first 6 months of treatment, non-persistence ranged between 6% and 33% in the included studies. The lowest non-persistence was reported for degludec (6%) [ 31 ], while the highest non-persistence was reported for the group of non-specified basal insulin therapies (33%) [ 9 ]. It should be noted that the majority of the studies reporting results on persistence at 6 months did not specify the insulin type [ 9 , 36 , 37 ]. Non-persistence rates within the first 12 months of treatment ranged from 14% to 52%. The lowest non-persistence rate within the first 12 months of treatment was reported for insulin glargine-300 (14%) and insulin degludec (16%) [ 31 , 35 ]. The highest non-persistence rate was reported for neutral protamine Hagedorn (NPH) insulin (52%) [ 34 ].

Non-persistence within 6 and 12 months of initiation of basal insulin treatment by type of basal insulin, %. The figure present rates of non-persistence from the eligible studies and lists population size and insulin type for each subgroup. Not all included studies reported results for persistence within both 6 and 12 months. Neither did all studies specify the specific type of basal insulin assessed. Estimates of persistence reported by Perez-Nieves et al. [ 9 ] differ across different countries and are reported in the following countries listed from left to right: France, Spain, Germany and the UK

On the basis of the studies, pooled non-persistence rates among people with T2D were calculated for 6, 12 and 18 months. The pooled non-persistence rate within 6 months of initiation of basal insulin was 20.3% (95% CI 13.8; 27.8) (Fig.  S1 ). It should be noted that four of the seven estimates of non-persistence within 6 months were based on self-reported data, whereas the remaining three were based on registry data. The pooled non-persistence rate was 14.6% (95% CI 6.3; 25.5) if only registry-based data were included and 25.9% (95% CI 20.5; 21.8) if only self-reported data were included (Figs.  S2 and S3 ). The pooled rate of non-persistence further increased from 6 to 12 months to 33.8% (95% CI 24.1; 44.3) (Fig.  S4 ). In a sensitivity analysis, data on NPH were excluded from this analysis, which resulted in a pooled non-persistence rate within 12 months of 31.3% (95% CI 21.7; 41.8) (Fig.  S5 ). Finally, the pooled rate of non-persistence within 18 months of initiating basal insulin was 36.5% (95% CI 33.6; 39.4) (Fig.  S6 ). Figures S7 and S8 show the results of sensitivity analyses in which the study by Sicras et al. 2013 was excluded [ 37 ].

Results on Insulin Adherence

Adherence/non-adherence to basal insulin was measured with several methods in the four included studies reporting results on insulin adherence. The most frequently used measure was MPR > 80%, which was used in two of the four studies [ 32 , 37 ]. MPR > 80% was the only measure that was used by more than one of the included studies. Among the included studies, half of them were based on registry data [ 32 , 37 ], whereas the other half were based on self-reported questionnaire data [ 15 , 30 ]. The size of study populations varied from 162 included people [ 15 ] to 2413 included people [ 32 ]. An overview of all included studies reporting results on insulin adherence/non-adherence is presented in Table  5 .

Figure  3 illustrates the proportion of people with T2D who were adherent to basal insulin treatment (defined as MPR > 80%) within the first 12 months of treatment, stratified by different types of basal insulin. The share of people with MPR > 80% ranged from 41% to 64% [ 32 , 37 ]. The pooled rate of people with MPR > 80% across the relevant studies was 55.6% (95% CI 45.3; 65.6). The results reported by Esposti et al. 2019 differed across different types of background therapies (included as separate subgroup results) [ 32 ]. Figure  S10 presents the results of a sensitivity analysis of the pooled rate of people with MPR > 80% when the study by Sicras et al. was excluded [ 37 ].

Share of people with T2D and MPR > 80% by different types of basal insulin, %. The figure presents proportions of MPR > 80% from the eligible studies and lists population size and insulin type for each subgroup. Estimates of adherence reported by Esposti et al. [ 32 ] differed across different types of background therapies, including the following background therapies listed from left to right: No background therapies, other oral glucose-lowering drugs and DPP4 inhibitors

One of the four included studies assessed insulin non-adherence by measuring the share of people with T2D who missed insulin doses during a 30-day period [ 30 ]. The outcome was measured through an online survey sent to people with T2D and healthcare professionals (primary care practitioners, specialists and nurses). The study found that, on average, 16% of people with T2D had one or more missed doses during a 30-day treatment period, while 1.3% had missed five or more doses in that same period. In addition, the study reported that people with T2D on average missed 1.8 doses of basal insulin within a 30-day treatment period.

Wieringa et al. measured adherence using a questionnaire in the Netherlands by asking their study respondents (physicians involved in the management of T2D in primary and secondary care and people with T2D) how many of the last 7 days they took the recommended basal insulin as prescribed. They found that 84% of people with T2D were adherent all 7 days of the last week [ 15 ].

This systematic literature review identified 12 studies that reported findings of persistence/non-persistence or adherence/non-adherence to basal insulin in people with T2D from Western European countries. The findings highlight an important problem with both persistence (defined as continuing to take medication throughout the prescribed period [ 21 ]) and adherence (defined as complying with the prescribed medicine in terms of drug schedules and dosages [ 21 ]) in T2D.

This systematic literature review found pooled non-persistence rates at 6 and 12 months of approximately 20% and 34%, respectively. At 18 months, the pooled non-persistence rate increased to approximately 37%. In the pooled non-persistence rate at 12 months, results for insulin NPH have been included. Insulin NPH might be given more than once per day, and it is therefore likely that a higher non-persistence rate is found among people receiving insulin NPH compared to other types of basal insulin. Information about daily doses of insulin NPH was not available. However, a sensitivity analysis showed that the pooled non-persistence rate within 12 months only changes by three percentage points (from 34% to 31%) when excluding insulin NPH from the analysis. Although direct comparisons across the studies should be made with caution, taking into account different study characteristics, the numbers for persistence over time could suggest that non-persistence among people with T2D is present already within the first 6 months and that it increases over time but at a diminishing rate. Considering that non-persistence could possibly be related to an unpreferable safety profile or dosing scheme, it seems fair to expect that people not experiencing issues with a treatment within the first 6 months do not experience issues after 6 months. Thus, it seems likely that non-persistence will stall over time. Furthermore, this systematic review found that estimates of adherence in the eligible studies were most often measured as MPR > 80%, which is the adherence rate needed for optimal treatment effect [ 41 ]. Using MPR > 80%, this review found a pooled adherence rate to basal insulin treatment over a 12-month period of approximately 56%. This suggests that 44% of people with T2D are non-adherent to basal insulin treatment within 12 months. It should be noted that one study, which was included in both the persistence and adherence analyses, did not differentiate between basal and bolus insulin. However, neither persistence nor adherence findings changed significantly when the study was excluded in a sensitivity analysis.

It is well established that non-persistence with and non-adherence to prescribed diabetes therapy, including basal insulin, can have profound consequences for people with diabetes, including poor glycaemic control [ 21 ]. Medication non-adherence has been shown to be a key reason why antidiabetic medication is less effective in a real-world setting than in clinical studies. For example, a study by Carls et al. from 2017 found significantly smaller reductions in glycaemic level among people with T2D 1 year after initiation of antidiabetic medication than what had been observed in the randomised control trial setting for the same period. The authors concluded that approximately 75% of the gap was due to lack of patient adherence [ 42 ].

The findings in this systematic review indicate that non-persistence and non-adherence have a great impact in Western Europe. It should be noted that there can be several reasons for interrupting insulin therapy. For instance, insulin therapy might be initiated temporarily, or it might be substituted with other medicines. In addition, insulin persistence and adherence might be impacted by diabetes-related complications, which could complicate the treatment regimen. According to the literature identified as part of this review, studies investigating adherence/non-adherence and persistence/non-persistence among people with type 1 diabetes are sparse. This calls for further investigation before any conclusions can be made about adherence/non-adherence and persistence/non-persistence in this population. However, it should be noted that, according to findings by Elek et al. T2D constitutes 90% of the overall population of people with diabetes [ 43 ].

While achievement of glycaemic targets is associated with a reduction in diabetes complications, improper diabetes care, e.g. poor glycaemic control, entails a great risk of long-term complications [ 21 , 44 ]. A systematic literature review from 2019 that investigated the lack of treatment persistence and treatment adherence in people with T2D found that an increase in diabetes complications as a result of poor adherence and persistence is linked to poorer health status and an increase in healthcare resource use and costs [ 9 ]. Additionally, a large study from the UK found a strong association between non-adherence and increased all-cause mortality [ 45 ]. Although a vast number of studies have investigated the cost associated with poor adherence or persistence to insulin treatment among people with T2D, many of these studies have been USA-based; hence, patients’ adherence and persistence are likely to be greatly affected by the high out-of-pocket payments known to be part of the US healthcare system. Thus, in order to understand the complete economic consequences of improper insulin treatment in the Western Europe, where healthcare systems are organised differently from the USA, additional evidence is needed.

Strength and Limitations

As is best practice, this systematic literature review includes a search of two databases, namely Medline (via PubMed) and Embase. For a systematic review literature search, Embase and MEDLINE are key databases. MEDLINE contains more than 22 million records from 5600 journals, whereas Embase has over 29 million records from 8500 journals. Additionally, the systematic literature review complies with the PRISMA guidelines. Inclusion and exclusion criteria used in this study were defined prior to the literature search, and the review process was conducted by two independent reviewers.

The number of studies identified in this systematic literature review was small in light of the seriousness of the challenge with poor control in diabetes. Additionally, they were heterogeneous. The methodological differences, particularly the use of differing outcome measures, problematise the direct comparisons of results across the different studies, countries, insulin products and time. As a result of the lack of a unified criterion for defining adherence and persistence in the identified studies, only a few studies could be meaningfully pooled, thus narrowing the data that went into the calculated pooled rates on persistence/non-persistence and adherence/non-adherence. This constitutes a limitation for the final pooled rates. Furthermore, the statistical tests of heterogeneity in the proportional meta-analyses showed high heterogeneity in the included estimates. It should be noted that the results of the heterogeneity tests should be interpreted with caution, since heterogeneity is expected in prevalence estimates. Therefore, high heterogeneity does not necessarily indicate inconsistent data [ 40 ]. To understand the factors that affect persistence and adherence and thus be able to provide people with T2D with treatment strategies that can improve persistence and adherence in the future, it would be relevant to have a standard practice for the measurement of persistence and adherence. Standardisation of the measurement of persistence and adherence in diabetes care will provide scientists with a guideline for what data should be included in future studies and enable the comparison of results across studies, products etc. Differing data sources in the included studies also poses a challenge in the comparisons. Finally, the inclusion of abstracts of conference papers may be a limitation as they do not include the same information as an article published in a scientific journal. However, the number of studies included from this source was small and it was ensured that they were studies of interest for the systematic review.

Given the clinical and economic consequences associated with non-adherence and non-persistence in T2D, an unmet need remains. These findings call for new basal insulin therapies and diabetes management strategies that can improve treatment persistence and adherence among people with T2D and thus positively affect clinical and economic outcomes. It was outside the scope of this study to investigate reasons for non-persistence and non-adherence. However, several approaches to improve persistence and adherence have been recommended in previous literature, including reduced treatment complexity (fixed-dose combinations and decreased dosing schemes), improved safety profiles, increased knowledge through better educational programmes and improved communication [ 21 , 45 ]. Additionally, knowledge about how other factors, e.g. sociodemographic factors or the presence of diabetes-related complications, influence persistence and adherence should be considered in future research.

This systematic literature review described real-world evidence on basal insulin adherence/non-adherence and persistence/non-persistence among people with T2D from Western Europe. The study identified 12 eligible studies in which non-persistence and non-adherence were evaluated using different outcome measures. Data on non-persistence among people with T2D suggest that non-persistence stagnates over time, with non-persistence rates of 21%, 34% and 37% at 6 months, 12 months and 18 months, respectively. By defining non-adherence as MPR < 20%, this systematic literature review found that 44% of people with T2D are non-adherent within 12 months. These numbers highlight a huge unmet need in the care for people with T2D and indicate that there is a clear opportunity to improve adherence and persistence, while also decreasing the risk of diabetes complications and the healthcare resource utilisation, by providing new diabetes management strategies with reduced treatment complexity, reduced dosing frequency, improved safety profile and better patient education and communication.

International Diabetes Federation. IDF Diabetes Atlas, Tenth Edition. https://diabetesatlas.org/ . Accessed 2022 Nov 14.

International Diabetes Federation. Type 2 diabetes. 2020. https://www.idf.org/aboutdiabetes/type-2-diabetes.html . Accessed 2022 Nov 2.

Beagley J, Guariguata L, Weil C, Motala AA. Global estimates of undiagnosed diabetes in adults. Diabetes Res Clin Pract. 2014;103:150–60.

Article   PubMed   Google Scholar  

World Health Organization. Diabetes. 2022. https://www.who.int/news-room/fact-sheets/detail/diabetes . Accessed 2022 Nov 2.

Mitsios JP, Ekinci EI, Mitsios GP, Churilov L, Thijs V. Relationship between glycated hemoglobin and stroke risk: a systematic review and meta-analysis. J Am Heart Assoc. 2018;7:e007858.

Article   PubMed   PubMed Central   Google Scholar  

van Wijngaarden RPT, Overbeek JA, Heintjes EM, et al. Relation between different measures of glycemic exposure and microvascular and macrovascular complications in patients with type 2 diabetes mellitus: an observational cohort study. Diabetes Ther. 2017;8:1097–109.

Svensson E, Baggesen LM, Johnsen SP, et al. Early glycemic control and magnitude of HbA1c reduction predict cardiovascular events and mortality: population-based cohort study of 24,752 metformin initiators. Diabetes Care. 2017;40:800–7.

Kontopantelis E, Springate DA, Reeves D, et al. Glucose, blood pressure and cholesterol levels and their relationships to clinical outcomes in type 2 diabetes: a retrospective cohort study. Diabetologia. 2015;58:505–18.

Article   CAS   PubMed   Google Scholar  

Perez-Nieves M, Ivanova JI, Hadjiyianni I, et al. Basal insulin initiation use and experience among people with type 2 diabetes mellitus with different patterns of persistence: results from a multi-national survey. Curr Med Res Opin. 2017;33:1833–42.

Morrish NJ, Wang S-L, Stevens LK, Fuller JH, Keen H. Mortality and causes of death in the WHO multinational study of vascular disease in diabetes. Diabetologia. 2001;44:S14-21.

Andersson E, Persson S, Hallén N, et al. Costs of diabetes complications: hospital-based care and absence from work for 392,200 people with type 2 diabetes and matched control participants in Sweden. Diabetologia. 2020;63:2582–94.

Shao H, Yang S, Fonseca V, Stoecker C, Shi L. Estimating quality of life decrements due to diabetes complications in the United States: the Health Utility Index (HUI) diabetes complication equation. Pharmacoeconomics. 2019;37:921–9.

Cheng LJ, Wang W, Lim ST, Wu VX. Factors associated with glycaemic control in patients with diabetes mellitus: a systematic literature review. J Clin Nurs. 2019;28:1433–50.

de Pablos-Velasco P, Parhofer KG, Bradley C, et al. Current level of glycaemic control and its associated factors in patients with type 2 diabetes across Europe: data from the PANORAMA study. Clin Endocrinol (Oxf). 2014;80:47–56.

Wieringa TH, de Wit M, Twisk JW, Snoek FJ. Improved diabetes medication convenience and satisfaction in persons with type 2 diabetes after switching to insulin glargine 300 U/mL: results of the observational OPTIN-D study. BMJ Open Diab Res Care. 2018;6:e000548.

Rathmann W, Czech M, Franek E, Kostev K. Treatment persistence in the use of basal insulins in Poland and Germany. Int J Clin Pharmacol Ther. 2017;55:119–25.

White JR. Advances in insulin therapy: a review of new insulin glargine 300 units/mL in the management of diabetes. Clin Diabetes. 2016;34:86–91.

Bjekić-Macut J, Živković TB, Kocić R. Clinical benefit of basal insulin analogue treatment in persons with type 2 diabetes inadequately controlled on prior insulin therapy: a prospective, noninterventional, multicenter study. Diabetes Ther. 2018;9:651–62.

Polonsky WH, Fisher L, Guzman S, Villa-Caballero L, Edelman SV. Psychological insulin resistance in patients with type 2 diabetes. Diabetes Care. 2005;28:2543–5.

Larkin ME, Capasso VA, Chen C-L, et al. Measuring psychological insulin resistance. Diabetes Educ. 2008;34:511–7.

Guerci B, Chanan N, Simarjeet Kaur, Jasso-Mosqueda JG, Lew E. Lack of treatment persistence and treatment non-adherence as barriers to glycaemic control in patients with type 2 diabetes. Adis Journals; 2019. p. 60641 Bytes. https://adisjournals.figshare.com/articles/Lack_of_Treatment_Persistence_and_Treatment_Non-Adherence_as_Barriers_to_Glycaemic_Control_in_Patients_with_Type_2_Diabetes/7752116 . Accessed 2022 Nov 7.

Hamersky CM, Fridman M, Gamble CL, Iyer NN. Injectable antihyperglycemics: a systematic review and critical analysis of the literature on adherence, persistence, and health outcomes. Diabetes Ther. 2019;10:865–90.

McGovern A, Tippu Z, Hinton W, Munro N, Whyte M, de Lusignan S. Comparison of medication adherence and persistence in type 2 diabetes: a systematic review and meta-analysis. Diabetes Obes Metab. 2018;20:1040–3.

Evans M, Engberg S, Faurby M, Fernandes JDDR, Hudson P, Polonsky W. Adherence to and persistence with antidiabetic medications and associations with clinical and economic outcomes in people with type 2 diabetes mellitus: a systematic literature review. Diabetes Obes Metab. 2022;24:377–90.

Westerbacka J, Mihailov H, Valle T, Jääskeläinen S, Kaukua J. PDB84 Adherence to initiated basal insulin analogue treatment in type 1 and 2 diabetes. Value Health. 2015;18(7):PA612. https://doi.org/10.1016/j.jval.2015.09.2124

Article   Google Scholar  

Lee DSU, Lee H. Adherence and persistence rates of major antidiabetic medications: a review. Diabetol Metab Syndr. 2022;14:12.

Azharuddin M, Adil M, Sharma M, Gyawali B. A systematic review and meta-analysis of non-adherence to anti-diabetic medication: evidence from low- and middle-income countries. Int J Clin Pract. 2021. https://doi.org/10.1111/ijcp.14717 .

Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339:b2700–b2700.

Silvi.ai. Silvi. https://www.silvi.ai . Accessed 2022 Nov 1.

Brod M, Rana A, Barnett AH. Adherence patterns in patients with type 2 diabetes on basal insulin analogues: missed, mistimed and reduced doses. Curr Med Res Opin. 2012;28:1933–46.

Eliasson B, Ekelund J, Miftaraj M, et al. Persistence with IDegLira in patients in clinical practice: a nationwide observational study in Sweden. Diabetes Ther. 2020;11:1807–20.

Esposti LD, Perrone V, Saragoni S, et al. Insulin glargine U100 utilization in patients with type 2 diabetes in an Italian real-world setting: a retrospective study. J Diabetes Res. 2019;2019:1–10.

Pscherer S, Chou E, Dippel F-W, Rathmann W, Kostev K. Treatment persistence after initiating basal insulin in type 2 diabetes patients: a primary care database analysis. Prim Care Diabetes. 2015;9:377–84.

Quinzler R, Ude M, Franzmann A, et al. Treatment duration (persistence) of basal insulin supported oral therapy (BOT) in type-2 diabetic patients: comparison of insulin glargine with NPH insulin. CP. 2012;50:24–32.

Article   CAS   Google Scholar  

Roussel R, Detournay B, Boultif Z, Bahloul A, Teissier C, Charbonnel B. Persistence with basal insulin and frequency of hypoglycemia requiring hospitalization in patients with type 2 diabetes. Diabetes Ther. 2020;11:1861–72.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Roussel R, Charbonnel B, Behar M, Gourmelen J, Emery C, Detournay B. Persistence with insulin therapy in patients with type 2 diabetes in France: an insurance claims study. Diabetes Ther. 2016;7:537–49.

Sicras A, Navarro R, Ruiz L, Morano R. Adherence and persistence in patients initiating treatment with injectable therapies for type 2 diabetes mellitus (T2DM) in Spain. Poster number: PDB82. 2013.

Peyrot M, Barnett AH, Meneghini LF, Schumm-Draeger P-M. Insulin adherence behaviours and barriers in the multinational Global Attitudes of Patients and Physicians in Insulin Therapy study. Diabet Med. 2012;29:682–9.

Munn Z, Aromataris E, Tufanaru C, et al. The development of software to support multiple systematic review types: the Joanna Briggs Institute System for the Unified Management, Assessment and Review of Information (JBI SUMARI). Int J Evid Based Healthc. 2019;17:36–43.

Barker TH, Migliavaca CB, Stein C, et al. Conducting proportional meta-analysis in different types of systematic reviews: a guide for synthesisers of evidence. BMC Med Res Methodol. 2021;21:189.

Kim J, Combs K, Downs J, Tillman F. Medication adherence: the elephant in the room. https://www.uspharmacist.com/article/medication-adherence-the-elephant-in-the-room . Accessed 2022 Nov 14.

Carls GS, Tuttle E, Tan R-D, et al. Understanding the gap between efficacy in randomized controlled trials and effectiveness in real-world use of GLP-1 RA and DPP-4 therapies in patients with type 2 diabetes. Diabetes Care. 2017;40:1469–78.

Elek P, Bíró A. Regional differences in diabetes across Europe – regression and causal forest analyses. Econ Hum Biol. 2021;40: 100948.

Rhee MK, Slocum W, Ziemer DC, et al. Patient adherence improves glycemic control. Diabetes Educ. 2005;31:240–50.

García-Pérez L-E, Álvarez M, Dilla T, Gil-Guillén V, Orozco-Beltrán D. Adherence to therapies in patients with type 2 diabetes. Diabetes Ther. 2013;4:175–94.

Download references

This systematic literature review, the journal’s Rapid Service Fee was funded by Novo Nordisk, Region North West Europe, Kay Fiskers Plads 10, 7th floor, 2300 Copenhagen S, Denmark.

Author information

Authors and affiliations.

Faculty of Medicine, Universidad Europea de Madrid, Madrid, Spain

Esteban J. Gimeno

EY Economics, Dirch Passers Allé 36, 2000, Frederiksberg, Denmark

Mette Bøgelund, Anna Okkels & Signe B. Reitzel

Novo Nordisk, Region North West Europe, Kay Fiskers Plads 10, 7th floor, 2300, Copenhagen S, Denmark

Sara Larsen & Hongye Ren

Cátedra de Medicina de Familia, Departamento de Medicina Clínica, Universidad Miguel Hernández, Alicante, Spain

Domingo Orozco-Beltran

You can also search for this author in PubMed   Google Scholar

Contributions

Conceptualization: Hongye Ren, Mette Bøgelund, Esteban J Gimeno, Domingo Orozco-Beltran and Sara Larsen; Methodology: Mette Bøgelund, Signe B Reitzel and Anna Okkels; Formal analysis and investigation: Signe B Reitzel and Anna Okkels; Writing—original draft preparation: Signe B Reitzel and Anna Okkels; Writing—review and editing: Hongye Ren, Mette Bøgelund, Esteban J Gimeno, Domingo Orozco-Beltran and Sara Larsen. All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Hongye Ren .

Ethics declarations

Conflict of interest.

Hongye Ren and Sara Larsen are employees of Novo Nordisk. Mette Bøgelund, Signe Baattrup Reitzel and Anna Okkels are employees of EY, which is a paid vendor of Novo Nordisk. After completion of the manuscript, Signe Baattrup Reitzel has changed affiliation to Medical Science, Novo Nordisk Foundation. Esteban Jodar reports consultancy services and speaker fees from Audium, Amgen, AstraZeneca, Boehringer, FAES, Eli Lilly, MSD, Novo Nordisk, UCB and ZP pharmaceutica. Domingo Orozco-Beltrán has provided consultancy services to MSD and Novartis and has lectured for Novartis, Mundipharma, Novo Nordisk, Sanofi Aventis and Eli Lilly.

Ethical Approval

Supplementary information.

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 638 KB)

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ .

Reprints and permissions

About this article

Gimeno, E.J., Bøgelund, M., Larsen, S. et al. Adherence and Persistence to Basal Insulin Among People with Type 2 Diabetes in Europe: A Systematic Literature Review and Meta-analysis. Diabetes Ther (2024). https://doi.org/10.1007/s13300-024-01559-w

Download citation

Received : 12 December 2023

Accepted : 27 February 2024

Published : 23 March 2024

DOI : https://doi.org/10.1007/s13300-024-01559-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Basal insulin
• Persistence
• Systematic literature review
• Type 2 diabetes
• Western Europe
• Find a journal
• Publish with us
• Track your research