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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

A Guide to Evidence Synthesis: 4. Write a Search Strategy

• Meet Our Team
• Our Published Reviews and Protocols
• What is Evidence Synthesis?
• Types of Evidence Synthesis
• Evidence Synthesis Across Disciplines
• Finding and Appraising Existing Systematic Reviews
• 0. Develop a Protocol
• 1. Draft your Research Question
• 2. Select Databases
• 3. Select Grey Literature Sources
• 4. Write a Search Strategy
• 5. Register a Protocol
• 6. Translate Search Strategies
• 7. Citation Management
• 8. Article Screening
• 9. Risk of Bias Assessment
• 10. Data Extraction
• 11. Synthesize, Map, or Describe the Results
• Evidence Synthesis Institute for Librarians
• Open Access Evidence Synthesis Resources

Video: Databases and search strategies (3:40 minutes)

Writing a Search Strategy

It is recommended that you work with a librarian to help you design comprehensive search strategies across a variety of databases. Writing a successful search strategy takes an intimate knowledge of bibliographic databases.  

Using Boolean logic is an important component of writing a search strategy: 

• "AND" narrows the search, e.g.  children AND exercise
• "OR" broadens the search, e.g.  (children OR adolescents) AND (exercise OR diet) 
• "NOT" excludes terms, e.g.  exercise NOT diet 
• "*" at the root of a word finds all forms of that word, e.g.  (child* OR adolescen*) AND (exercise* OR diet*)
• parentheses ensure all terms will be searched together as a set 
• quotations around a phrase searches that exact phrase, e.g.  (child* OR adolescen* OR "young adult*") 

Evidence Synthesis Search Strategy Examples

Agriculture example: .

• Research question:  What are the strategies that farmer organizations use, and what impacts do those strategies have on small-scale producers in Sub Saharan Africa and India? 
• Key concepts from the question combined with AND:  (farmer organizations) AND (Sub-Saharan Africa OR India) 
• Protocol and search strategies for this question in CAB Abstracts, Scopus, EconLit, and grey literature
• Published scoping review for this question

Nutrition Example: 

• Research question:  What are the health benefits and safety of folic acid fortification of wheat and maize flour (i.e. alone or in combination with other micronutrients) on folate status and health outcomes in the overall population, compared to wheat or maize flour without folic acid (or no intervention)? 
• Key concepts from the question combined with AND:  (folic acid) AND (fortification) 
• Protocol on PROSPERO
• Published systematic review for this question with search strategies used in 14 databases

Search Strategy Template and Filters

• Human Studies Filter
• Randomized Controlled Trial Filters
• Other Methodology Search Filters

If you want to exclude animal studies from your search results, you may add a "human studies filter" to the end of your search strategy. This approach works best with databases that use Medical Subject Headings (MeSH) or other controlled vocabulary. You can see an example of how this was used in the MEDLINE(Ovid) search strategy of this published review (lines 13-14).

A simplified explanation of this filter can be seen below:

Add the following lines to the end of your search strategy to filter for randomized controlled trials. These are "validated search filters" meaning they have been tested for sensitivity and specificity, and the results of those tests have been published as a scientific article. The ISSG Search Filters Resource provides validated search filters for many other study design types. 

Highly Sensitive MEDLINE (via PubMed) Filter from Cochrane  

(randomized controlled trial [pt] OR controlled clinical trial [pt] OR randomized [tiab] OR placebo [tiab] OR drug therapy [sh] OR randomly [tiab] OR trial [tiab] OR groups [tiab])

Highly Sensitive MEDLINE (OVID) Filter from Cochrane 

((randomized controlled trial.pt. or controlled clinical trial.pt. or randomized.ab. or placebo.ab. or drug therapy.fs. or randomly.ab. or trial.ab. or groups.ab.) not (exp animals/ not humans.sh.)) ​

CINAHL Filter from Cochrane 

TX allocat* random* OR (MH "Quantitative Studies") OR (MH "Placebos") OR TX placebo* OR TX random* allocat* OR (MH "Random Assignment") OR TX randomi* control* trial* OR TX ( (singl* n1 blind*) OR (singl* n1 mask*) ) OR TX ( (doubl* n1 blind*) OR (doubl* n1 mask*) ) OR TX ( (tripl* n1 blind*) OR (tripl* n1 mask*) ) OR TX ( (trebl* n1 blind*) OR (trebl* n1 mask*) ) OR TX clinic* n1 trial* OR PT Clinical trial OR (MH "Clinical Trials+")

PsycINFO Filter from ProQuest:

SU.EXACT("Treatment Effectiveness Evaluation") OR SU.EXACT.EXPLODE("Treatment Outcomes") OR SU.EXACT("Placebo") OR SU.EXACT("Followup Studies") OR placebo* OR random* OR "comparative stud*" OR  clinical NEAR/3 trial* OR research NEAR/3 design OR evaluat* NEAR/3 stud* OR prospectiv* NEAR/3 stud* OR (singl* OR doubl* OR trebl* OR tripl*) NEAR/3 (blind* OR mask*)

Web Of Science (WoS) Filter from University of Alberta - Not Validated

TS= clinical trial* OR TS=research design OR TS=comparative stud* OR TS=evaluation stud* OR TS=controlled trial* OR TS=follow-up stud* OR TS=prospective stud* OR TS=random* OR TS=placebo* OR TS=(single blind*) OR TS=(double blind*)

Scopus Filter from Children's Mercy Kansas City

TITLE-ABS-KEY((clinic* w/1 trial*) OR (randomi* w/1 control*) OR (randomi* w/2 trial*) OR (random* w/1 assign*) OR (random* w/1 allocat*) OR (control* w/1 clinic*) OR (control* w/1 trial) OR placebo* OR (Quantitat* w/1 Stud*) OR (control* w/1 stud*) OR (randomi* w/1 stud*) OR (singl* w/1 blind*) or (singl* w/1 mask*) OR (doubl* w/1 blind*) OR (doubl* w/1 mask*) OR (tripl* w/1 blind*) OR (tripl* w/1 mask*) OR (trebl* w/1 blind*) OR (trebl* w/1 mask*)) AND NOT (SRCTYPE(b) OR SRCTYPE(k) OR SRCTYPE(p) OR SRCTYPE(r) OR SRCTYPE(d) OR DOCTYPE(ab) OR DOCTYPE(bk) OR DOCTYPE(ch) OR DOCTYPE(bz) OR DOCTYPE(cr) OR DOCTYPE(ed) OR DOCTYPE(er) OR DOCTYPE(le) OR DOCTYPE(no) OR DOCTYPE(pr) OR DOCTYPE(rp) OR DOCTYPE(re) OR DOCTYPE(sh))

Sources and more information:

• Cochrane Handbook for Systematic Reviews of Interventions
• Cochrane RCT Filters for Different Databases
• American University of Beirut University Libraries Search Filters / Hedges
• Methodology Search Filters by Study Design - Countway Library of Medicine, Harvard University Filters for RCTs, CCTs, Non-randomized/observational designs, and tests of diagnostic accuracy.
• Search Filters - American University of Beirut University Libraries Filters for RCTs, GUIDELINEs, systematic reviews, qualitative studies, etc.

Pre-generated queries in Scopus for the UN Sustainable Development Goals

Pre-written SDG search strategies available in Scopus 

Scopus, a multidisciplinary research database, provides pre-written search strategies to capture articles on topics about each of the 17 United Nations Sustainable Development Goals  (SDGs). These search strategies were updated in 2023 and are no longer available directly on "Advanced Document Search". To use these SDG search strategies:

• Go to the Elsevier 2023 Sustainable Development Goals (SDGs) Mapping page.
• Under Files , click on the SDG 2023 Queries folder.
• Download the .txt file for each pre-written search strategy you are interested in. You will need to know the number of the SDG of interest (e.g., SDG01.txt is for SDG 1: No Poverty). This .txt file will contain the entire search string for the SDG, already written in Scopus syntax .
• In Scopus , click on "Advanced Document Search".
• Copy and paste the pre-written SDG search strategy into the search field.

More about the Sustainable Development Goals: 

" The 2030 Agenda for Sustainable Development,  adopted by all United Nations Member States in 2015, provides a shared blueprint for peace and prosperity for people and the planet, now and into the future. At its heart are the 17 Sustainable Development Goals (SDGs), which are an urgent call for action by all countries - developed and developing - in a global partnership. They recognize that ending poverty and other deprivations must go hand-in-hand with strategies that improve health and education, reduce inequality, and spur economic growth – all while tackling climate change and working to preserve our oceans and forests."

Source:  https://sdgs.un.org/goals 

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Introduction

The literature search process

• Develop an effective search strategy 
• Determine the type of information
• Identify where to search
• Search and manage results
• Locate and evaluate
• Keep up-to-date

Library resources and support

Develop an effective search strategy

• 1. Identify key concepts
• 2. Identify alternate terms
• 3. Incorporate search techniques

If all concepts are not identified, your search strategy may not be correct and the literature identified may not address your research.  

For example, if your research topic is:

 "The role of social media for promoting participation in sport by refugees living in rural areas" 

Four concepts are included in this research question: 

Several frameworks are available that assist when developing a search strategy associated with the key concepts in a research question.

While your research question may not always fit the formats suggested here, using a framework for guidance can still be a helpful starting point. 

For  clinical questions,  effectiveness of interventions, treatments or the impact of exposures need to be answered.

For qualitative research , and evaluating experiences of a specific phenomenon use the following frameworks: 

It is important to note that sometimes not all the concepts in a research question should be included in a search strategy. Some concepts may be less important than others or may unnecessarily complicate or restrict a search strategy. If including a concept in a strategy increases the chance of missing relevant references, it is best to exclude that concept. 

Once you have identified the key concepts in your research question, the next step is to think laterally and identify alternate terms, such as synonyms, abbreviations, colloquialisms, and acronyms that other researchers may have used to describe the same concept. 

Tips for identifying search terms : 

• Conduct a preliminary search in a subject database within your research field to clarify the topic  
• Identify common terms used in the literature 
• Note any relevant subject headings used in the databases. 
• Check their definitions to confirm whether they are suitable for your research 
• Check titles, abstracts, and author keywords on articles you have already identified as relevant to your research 
• Use the reference list at the end of these articles to identify further research that may guide you, then search for these articles in the key databases within your research area. 

It is important to understand the terminology used in your research field. Dictionaries and encyclopaedias can help to clarify the meaning of terms; specialist dictionaries and encyclopaedias may assist to define discipline-specific terms.   Check the Subject Resource Guides for links to specialist dictionaries and encyclopaedias .

Checking for variations   

Keeping track of search terms .

Returning to the example research topic :

The role of social media for promoting participation in sport by refugees living in rural areas

Synonyms and related terms which may be identified as useful for this research question could include the following:

New terms and concepts can be added when found during the literature search.

Use the search planning form  or something similar to document your key concepts, with any synonyms and related terms.

Various techniques such as truncation, phrase and proximity searching, nesting,  Boolean operators and wildcards, can help to maximise the effectiveness of search strategies.These techniques are explained below.

When used together the techniques and strategies included in this section will enhance the potential and scope of results in your research topic.

Phrase searching

Proximity searching, boolean operators.

Using the research question:

The concept terms and their synonyms can be truncated and phrases identified. 

These terms and concepts can now be incorparted into any search strategy associated with the research question used as our example.

• Last Updated: Apr 22, 2024 3:31 PM
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Systematic Reviews

• Search Strategy
• Work with a Search Expert
• Covidence Review Software
• Types of Reviews
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• 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
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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

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Systematic reviews & evidence synthesis methods.

• Schedule a Consultation / Meet our Team
• What is Evidence Synthesis?
• Types of Evidence Synthesis
• Evidence Synthesis Across Disciplines
• Finding and Appraising Existing Systematic Reviews
• 1. Develop a Protocol
• 2. Draft your Research Question
• 3. Select Databases
• 4. Select Grey Literature Sources
• 5. Write a Search Strategy
• 6. Register a Protocol
• 7. Translate Search Strategies
• 8. Citation Management
• 9. Article Screening
• 10. Risk of Bias Assessment
• 11. Data Extraction
• 12. Synthesize, Map, or Describe the Results
• Open Access Evidence Synthesis Resources

Writing a Search Strategy

It is recommended that you work with a librarian to help you design comprehensive search strategies across a variety of databases. Writing a successful search strategy takes an intimate knowledge of bibliographic databases.  

Using Boolean logic is an important component of writing a search strategy: 

• "AND" narrows the search, e.g. children AND exercise
• "OR" broadens the search, e.g. (children OR adolescents) AND (exercise OR diet) 
• "NOT" excludes terms, e.g. exercise NOT diet 
• "*" at the root of a word finds all forms of that word, e.g. (child* OR adolescen*) AND (exercise* OR diet*)
• parentheses ensure all terms will be searched together as a set 
• quotations around a phrase searches that exact phrase, e.g. (child* OR adolescen* OR "young adult*") 

Evidence Synthesis Search Strategy Examples

Agriculture Example: 

• Research question: What are the strategies that farmer organizations use, and what impacts do those strategies have on small-scale producers in Sub Saharan Africa and India? 
• Key concepts from the question combined with AND: (farmer organizations) AND (Sub-Saharan Africa OR India) 
• Protocol and search strategies for this question in CAB Abstracts, Scopus, EconLit, and grey literature
• Published scoping review for this question

Nutrition Example: 

• Research question: What are the health benefits and safety of folic acid fortification of wheat and maize flour (i.e. alone or in combination with other micronutrients) on folate status and health outcomes in the overall population, compared to wheat or maize flour without folic acid (or no intervention)? 
• Key concepts from the question combined with AND: (folic acid) AND (fortification) 
• Protocol on PROSPERO
• Published systematic review for this question with search strategies used in 14 databases

Search Strategy Template and Filters

• Human Studies Filter
• Randomized Controlled Trial Filters
• Other Methodology Search Filters

If you want to exclude animal studies from your search results, you may add a "human studies filter" to the end of your search strategy. This approach works best with databases that use Medical Subject Headings (MeSH) or other controlled vocabulary.

See Appendix 2 at the end of this published search strategy for an example of a human studies filter in a MEDLINE(Ovid) search strategy.

Line 13 searches for all animal studies, and then line 14 searches for only the full search results in line 12, NOT including any of the animal studies from line 13 (#12 NOT #13).

Add the following lines to the end of your search strategy to filter for randomized controlled trials. These are "validated search filters" meaning they have been tested for sensitivity and specificity, and the results of those tests have been published as a scientific article. The ISSG Search Filters Resource provides validated search filters for many other study design types.

Highly Sensitive MEDLINE (via PubMed) Filter from Cochrane

(randomized controlled trial [pt] OR controlled clinical trial [pt] OR randomized [tiab] OR placebo [tiab] OR drug therapy [sh] OR randomly [tiab] OR trial [tiab] OR groups [tiab])

Highly Sensitive MEDLINE (OVID)Filter from Cochrane

((randomized controlled trial.pt. or controlled clinical trial.pt. or randomized.ab. or placebo.ab. or drug therapy.fs. or randomly.ab. or trial.ab. or groups.ab.) not (exp animals/ not humans.sh.))​

CINAHL Filter from Cochrane

TX allocat* random* OR (MH "Quantitative Studies") OR (MH "Placebos") OR TX placebo* OR TX random* allocat* OR (MH "Random Assignment") OR TX randomi* control* trial* OR TX ( (singl* n1 blind*) OR (singl* n1 mask*) ) OR TX ( (doubl* n1 blind*) OR (doubl* n1 mask*) ) OR TX ( (tripl* n1 blind*) OR (tripl* n1 mask*) ) OR TX ( (trebl* n1 blind*) OR (trebl* n1 mask*) ) OR TX clinic* n1 trial* OR PT Clinical trial OR (MH "Clinical Trials+")

PsycINFO Filter from ProQuest

SU.EXACT("Treatment Effectiveness Evaluation") OR SU.EXACT.EXPLODE("Treatment Outcomes") OR SU.EXACT("Placebo") OR SU.EXACT("Followup Studies") OR placebo* OR random* OR "comparative stud*" OR  clinical NEAR/3 trial* OR research NEAR/3 design OR evaluat* NEAR/3 stud* OR prospectiv* NEAR/3 stud* OR (singl* OR doubl* OR trebl* OR tripl*) NEAR/3 (blind* OR mask*)

Web Of Science (WoS) Filter from University of Alberta - Not Validated

TS= clinical trial* OR TS=research design OR TS=comparative stud* OR TS=evaluation stud* OR TS=controlled trial* OR TS=follow-up stud* OR TS=prospective stud* OR TS=random* OR TS=placebo* OR TS=(single blind*) OR TS=(double blind*)

Scopus Filter from Children's Mercy Kansas City

 Copy/paste into 'advanced search':

TITLE-ABS-KEY((clinic* w/1 trial*) OR (randomi* w/1 control*) OR (randomi* w/2 trial*) OR (random* w/1 assign*) OR (random* w/1 allocat*) OR (control* w/1 clinic*) OR (control* w/1 trial) OR placebo* OR (Quantitat* w/1 Stud*) OR (control* w/1 stud*) OR (randomi* w/1 stud*) OR (singl* w/1 blind*) or (singl* w/1 mask*) OR (doubl* w/1 blind*) OR (doubl* w/1 mask*) OR (tripl* w/1 blind*) OR (tripl* w/1 mask*) OR (trebl* w/1 blind*) OR (trebl* w/1 mask*)) AND NOT (SRCTYPE(b) OR SRCTYPE(k) OR SRCTYPE(p) OR SRCTYPE(r) OR SRCTYPE(d) OR DOCTYPE(ab) OR DOCTYPE(bk) OR DOCTYPE(ch) OR DOCTYPE(bz) OR DOCTYPE(cr) OR DOCTYPE(ed) OR DOCTYPE(er) OR DOCTYPE(le) OR DOCTYPE(no) OR DOCTYPE(pr) OR DOCTYPE(rp) OR DOCTYPE(re) OR DOCTYPE(sh))

Sources and more information:

• Cochrane Handbook for Systematic Reviews of Interventions
• Cochrane RCT Filters for Different Databases
• American University of Beirut University Libraries Search Filters / Hedges
• Methodology Search Filters by Study Design Filters for RCTs, CCTs, Non-randomized/observational designs, and tests of diagnostic accuracy. Source: Countway Library of Medicine. (2019). Systematic Reviews and Meta Analysis: Methodology Filters.
• American University of Beirut University Libraries Search Filters Filters for RCTs, GUIDELINEs, systematic reviews, qualitative studies, etc. Source: American University of Beirut University Libraries. (2019). Systematic Reviews: Search Filters / Hedges.
• Search Filter (Search Hedge) Developed to define certain criteria for your search, many databases feature a built-in set of search filters that are commonly used to limit search results by age group, publication type, study type, and more. The Centre for Reviews and Dissemination has a list of published filters along with information on appraisal of search filters, links to articles that have evaluated filters, etc. When selecting a filter, be sure to look at the date of development as changes to database terms and structure can affect the performance of the search filter.

Video: Databases and search strategies (3:40 minutes)

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• Last Updated: Apr 22, 2024 7:04 PM
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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

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Guiding Research Papers: Developing a Search Strategy

Tags: reading strategies , research skills , writing

Categories: Working with Student Writing

By Diane Matlock, English

A search strategy is a systematic plan for tracking down sources. No single search strategy works for every topic. For some topics, it may be appropriate to search for information in newspapers, magazines, and websites. For others, the best sources may be found in scholarly journals, books, and specialized reference works. Still other topics might be enhanced by field research, such as interviews, surveys, or direct observation.

Things to consider: You want to think about what will make the most interesting and effective evidence for your argument. Will you need primary sources, secondary sources, or both? Often what constitutes a primary or secondary source will depend on your purpose or field.

Primary and Secondary Sources

Primary sources enable the researcher to get as close as possible to what actually happened during a historical event or time period. A primary source reflects the individual viewpoint of a participant or observer. (Examples of primary sources include diaries, journals, speeches, interviews, letters, memos, manuscripts, memoirs, autobiographies, records of or information collected by government agencies, records of organizations, published materials written at the time about a particular event — books, magazine and journal articles, newspaper articles — photographs, audio recordings, moving pictures, video recordings, materials that document the attitudes and popular thought of a historical time period — public opinion polls, mass media, literature, film, popular fiction, textbooks — research data, artifacts.)

Some primary sources, such as diaries or letters, are original manuscripts which exist in only one place in the world. Others, such as newspaper articles or transcripts of speeches, exist in multiple copies but may be hard to find. You can look for reprinted primary sources.

A secondary source is a work that interprets or analyzes an historical event or phenomenon. It is generally at least one step removed from the event.

What kind of sources does the assignment require? How current do your sources need to be? Do you need to consult sources contemporary with an event or a person’s life? How many sources should you consult?

Finding Sources

One reason for doing research is to find information, data, and evidence bearing on a problem — the raw material of primary sources that become either support for your argument or the object of analytical scrutiny. The other reason for doing research is so you can place your argument in conversation with other scholars who have written on the topic — previous and contemporary scholars with whom you will agree or disagree. In other words, you need to understand the critical context for your argument. In addition, by reading secondary sources, you can examine how scholars in different disciplines use their sources.

To begin finding sources:

• Identify key participants, dates, and publications associated with your topic (for example, you can look at reports, newsletters, magazines, and pamphlets that were produced in conjunction with the event or developments you are researching)
• Search by subject (Library of Congress Library Subject Headings)
• Look up people, organizations, and agencies as authors
• Identify contemporary books from the era
• Use periodical and newspaper indexes from the time period
• Go to special collections of primary source material (look at the Bancroft materials online)
• Find popular fiction, movies, television from the time period
• Find public opinion polls from the period
• Use indexes to government documents
• Look at the bibliography of the secondary sources you examine

Research Process :: Step by Step

• Introduction
• Select Topic
• Identify Keywords
• Background Information
• Develop Research Questions
• Refine Topic
• Search Strategy
• Popular Databases
• Evaluate Sources
• Types of Periodicals
• Reading Scholarly Articles
• Primary & Secondary Sources
• Organize / Take Notes
• Writing & Grammar Resources
• Annotated Bibliography
• Literature Review
• Citation Styles
• Paraphrasing
• Privacy / Confidentiality
• Research Process
• Selecting Your Topic
• Identifying Keywords
• Gathering Background Info
• Evaluating Sources

Are you finding too much information or perhaps not enough? Use alternative, narrower, or broader keywords  to vary your results.

General Search Strategies

The easiest way to search for information electronically is to enter a couple of keywords into the search box of the resource and see what type of results you get. This strategy, however, will often result in too few, too many, or irrelevant results.

In order to retrieve the most relevant results, you will need to construct a search string .  A search string is a combination of keywords, truncation symbols, and boolean operators you enter into the search box of an electronic library resource or an Internet search engine.

Boolean searching is the traditional way to search for information in most online databases and on the Internet. Boolean operators  are connector words (AND, OR, and NOT) used to create phrases and concepts based on specific rules of search logic.  

AND and NOT will both narrow your results, while OR will broaden your results. These operators can be used in a longer string to refine your results.

Google Search Strategies

Many of us begin building content knowledge through Google. Use the following notes to help understand how to navigate Google more efficiently.

Results will typically include each word or punctuation mark included in the search query. Some stop words or  exceptions apply.

If your initial search query does not produce the desired results, keep these functions in mind:

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• 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

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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

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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.

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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.

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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)

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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

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Boolean Operators

Boolean operators (AND, OR, and NOT) are used to connect keywords and concepts when searching.

• Boil your topic down to the most important words .  Ignore superfluous words like in, the, of, with, against, affect, impact.  Begin with a keyword search. 
• Put each "different piece" of your topic in a separate search box, if available.  Using the topic of criticism of Van Gogh's Starry Night as an example below, each different piece of the topic is entered on a separate line.  Synonyms for the pieces are connected by OR--and kept on the same line--as seen below with criticize...

•  Too many results?  Focus your search by searching for your keywords in the ABSTRACT field or the TITLE field.  Click on the All - Smart Search to select  the abstract or title field.  Or focus your search by using "an exact phrase" search.
• Too few results?  Think of synonyms.  Add synonyms to your search--using OR-- and keep your synonyms all on the same line . 
• Increase your results by removing the least important "piece" of your search while still retaining the "essence" of your search (in the case above, it might be Van Gogh). 
• Still no results?  Broaden your search slightly.  Can't find specific criticism on the Starry Night?  Look for criticism of Van Gogh--within these articles/books, you'll find criticism of Starry Night.  Still no luck?  Try a different journal article database.
• When reviewing your results, look for relevant "subject" or "descriptor" words.  Find subject terms either on the results page, or at the end of individual records.  Write down relevant subject terms that you find.  
• Go back to the search screen and using the subject terms you discovered, search your subject terms in the subject or descriptor field.  Subject terms are gold threads--they will almost always lead you to the most relevant results.
• Be sure to take advantage of:
• Boolean connectors (AND, OR, NOT)
• Exact phrase searching -- "starry night" 
• Field searches (search within the title, abstract, or subject fields)

• No full-text?  Use the L ooking for Full-Text (a Get It link will appear if the full-text links fails) OR Request from LVC Tipasa link to receive a copy of the article or book from another library.

If your initial search query does not produce the desired results, try:

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• 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.

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A systematic approach to searching: an efficient and complete method to develop literature searches

Associated data.

Creating search strategies for systematic reviews, finding the best balance between sensitivity and specificity, and translating search strategies between databases is challenging. Several methods describe standards for systematic search strategies, but a consistent approach for creating an exhaustive search strategy has not yet been fully described in enough detail to be fully replicable. The authors have established a method that describes step by step the process of developing a systematic search strategy as needed in the systematic review. This method describes how single-line search strategies can be prepared in a text document by typing search syntax (such as field codes, parentheses, and Boolean operators) before copying and pasting search terms (keywords and free-text synonyms) that are found in the thesaurus. To help ensure term completeness, we developed a novel optimization technique that is mainly based on comparing the results retrieved by thesaurus terms with those retrieved by the free-text search words to identify potentially relevant candidate search terms. Macros in Microsoft Word have been developed to convert syntaxes between databases and interfaces almost automatically. This method helps information specialists in developing librarian-mediated searches for systematic reviews as well as medical and health care practitioners who are searching for evidence to answer clinical questions. The described method can be used to create complex and comprehensive search strategies for different databases and interfaces, such as those that are needed when searching for relevant references for systematic reviews, and will assist both information specialists and practitioners when they are searching the biomedical literature.

INTRODUCTION

Librarians and information specialists are often involved in the process of preparing and completing systematic reviews (SRs), where one of their main tasks is to identify relevant references to include in the review [ 1 ]. Although several recommendations for the process of searching have been published [ 2 – 6 ], none describe the development of a systematic search strategy from start to finish.

Traditional methods of SR search strategy development and execution are highly time consuming, reportedly requiring up to 100 hours or more [ 7 , 8 ]. The authors wanted to develop systematic and exhaustive search strategies more efficiently, while preserving the high sensitivity that SR search strategies necessitate. In this article, we describe the method developed at Erasmus University Medical Center (MC) and demonstrate its use through an example search. The efficiency of the search method and outcome of 73 searches that have resulted in published reviews are described in a separate article [ 9 ].

As we aimed to describe the creation of systematic searches in full detail, the method starts at a basic level with the analysis of the research question and the creation of search terms. Readers who are new to SR searching are advised to follow all steps described. More experienced searchers can consider the basic steps to be existing knowledge that will already be part of their normal workflow, although step 4 probably differs from general practice. Experienced searchers will gain the most from reading about the novelties in the method as described in steps 10–13 and comparing the examples given in the supplementary appendix to their own practice.

CREATING A SYSTEMATIC SEARCH STRATEGY

Our methodology for planning and creating a multi-database search strategy consists of the following steps:

• Determine a clear and focused question
• Describe the articles that can answer the question
• Decide which key concepts address the different elements of the question
• Decide which elements should be used for the best results
• Choose an appropriate database and interface to start with
• Document the search process in a text document
• Identify appropriate index terms in the thesaurus of the first database
• Identify synonyms in the thesaurus
• Add variations in search terms
• Use database-appropriate syntax, with parentheses, Boolean operators, and field codes
• Optimize the search
• Evaluate the initial results
• Check for errors
• Translate to other databases
• Test and reiterate

Each step in the process is reflected by an example search described in the supplementary appendix .

1. Determine a clear and focused question

A systematic search can best be applied to a well-defined and precise research or clinical question. Questions that are too broad or too vague cannot be answered easily in a systematic way and will generally result in an overwhelming number of search results. On the other hand, a question that is too specific will result into too few or even zero search results. Various papers describe this process in more detail [ 10 – 12 ].

2. Describe the articles that can answer the question

Although not all clinical or research questions can be answered in the literature, the next step is to presume that the answer can indeed be found in published studies. A good starting point for a search is hypothesizing what the research that can answer the question would look like. These hypothetical (when possible, combined with known) articles can be used as guidance for constructing the search strategy.

3. Decide which key concepts address the different elements of the question

Key concepts are the topics or components that the desired articles should address, such as diseases or conditions, actions, substances, settings, domains (e.g., therapy, diagnosis, etiology), or study types. Key concepts from the research question can be grouped to create elements in the search strategy.

Elements in a search strategy do not necessarily follow the patient, intervention, comparison, outcome (PICO) structure or any other related structure. Using the PICO or another similar framework as guidance can be helpful to consider, especially in the inclusion and exclusion review stage of the SR, but this is not necessary for good search strategy development [ 13 – 15 ]. Sometimes concepts from different parts of the PICO structure can be grouped together into one search element, such as when the desired outcome is frequently described in a certain study type.

4. Decide which elements should be used for the best results

Not all elements of a research question should necessarily be used in the search strategy. Some elements are less important than others or may unnecessarily complicate or restrict a search strategy. Adding an element to a search strategy increases the chance of missing relevant references. Therefore, the number of elements in a search strategy should remain as low as possible to optimize recall.

Using the schema in Figure 1 , elements can be ordered by their specificity and importance to determine the best search approach. Whether an element is more specific or more general can be measured objectively by the number of hits retrieved in a database when searching for a key term representing that element. Depending on the research question, certain elements are more important than others. If articles (hypothetically or known) exist that can answer the question but lack a certain element in their titles, abstracts, or keywords, that element is unimportant to the question. An element can also be unimportant because of expected bias or an overlap with another element.

Schema for determining the optimal order of elements

Bias in elements

The choice of elements in a search strategy can introduce bias through use of overly specific terminology or terms often associated with positive outcomes. For the question “does prolonged breastfeeding improve intelligence outcomes in children?,” searching specifically for the element of duration will introduce bias, as articles that find a positive effect of prolonged breastfeeding will be much more likely to mention time factors in their titles or abstracts.

Overlapping elements

Elements in a question sometimes overlap in their meaning. Sometimes certain therapies are interventions for one specific disease. The Lichtenstein technique, for example, is a repair method for inguinal hernias. There is no need to include an element of “inguinal hernias” to a search for the effectiveness of the Lichtenstein therapy. Likewise, sometimes certain diseases are only found in certain populations. Adding such an overlapping element could lead to missing relevant references.

The elements to use in a search strategy can be found in the plot of elements in Figure 1 , by following the top row from left to right. For this method, we recommend starting with the most important and specific elements. Then, continue with more general and important elements until the number of results is acceptable for screening. Determining how many results are acceptable for screening is often a matter of negotiation with the SR team.

5. Choose an appropriate database and interface to start with

Important factors for choosing databases to use are the coverage and the presence of a thesaurus. For medically oriented searches, the coverage and recall of Embase, which includes the MEDLINE database, are superior to those of MEDLINE [ 16 ]. Each of these two databases has its own thesaurus with its own unique definitions and structure. Because of the complexity of the Embase thesaurus, Emtree, which contains much more specific thesaurus terms than the MEDLINE Medical Subject Headings (MeSH) thesaurus, translation from Emtree to MeSH is easier than the other way around. Therefore, we recommend starting in Embase.

MEDLINE and Embase are available through many different vendors and interfaces. The choice of an interface and primary database is often determined by the searcher’s accessibility. For our method, an interface that allows searching with proximity operators is desirable, and full functionality of the thesaurus, including explosion of narrower terms, is crucial. We recommend developing a personal workflow that always starts with one specific database and interface.

6. Document the search process in a text document

We advise designing and creating the complete search strategies in a log document, instead of directly in the database itself, to register the steps taken and to make searches accountable and reproducible. The developed search strategies can be copied and pasted into the desired databases from the log document. This way, the searcher is in control of the whole process. Any change to the search strategy should be done in the log document, assuring that the search strategy in the log is always the most recent.

7. Identify appropriate index terms in the thesaurus of the first database

Searches should start by identifying appropriate thesaurus terms for the desired elements. The thesaurus of the database is searched for matching index terms for each key concept. We advise restricting the initial terms to the most important and most relevant terms. Later in the process, more general terms can be added in the optimization process, in which the effect on the number of hits, and thus the desirability of adding these terms, can be evaluated more easily.

Several factors can complicate the identification of thesaurus terms. Sometimes, one thesaurus term is found that exactly describes a specific element. In contrast, especially in more general elements, multiple thesaurus terms can be found to describe one element. If no relevant thesaurus terms have been found for an element, free-text terms can be used, and possible thesaurus terms found in the resulting references can be added later (step 11).

Sometimes, no distinct thesaurus term is available for a specific key concept that describes the concept in enough detail. In Emtree, one thesaurus term often combines two or more elements. The easiest solution for combining these terms for a sensitive search is to use such a thesaurus term in all elements where it is relevant. Examples are given in the supplementary appendix .

8. Identify synonyms in the thesaurus

Most thesauri offer a list of synonyms on their term details page (named Synonyms in Emtree and Entry Terms in MeSH). To create a sensitive search strategy for SRs, these terms need to be searched as free-text keywords in the title and abstract fields, in addition to searching their associated thesaurus terms.

The Emtree thesaurus contains more synonyms (300,000) than MeSH does (220,000) [ 17 ]. The difference in number of terms is even higher considering that many synonyms in MeSH are permuted terms (i.e., inversions of phrases using commas).

Thesaurus terms are ordered in a tree structure. When searching for a more general thesaurus term, the more specific (narrower) terms in the branches below that term will also be searched (this is frequently referred to as “exploding” a thesaurus term). However, to perform a sensitive search, all relevant variations of the narrower terms must be searched as free-text keywords in the title or abstract, in addition to relying on the exploded thesaurus term. Thus, all articles that describe a certain narrower topic in their titles and abstracts will already be retrieved before MeSH terms are added.

9. Add variations in search terms (e.g., truncation, spelling differences, abbreviations, opposites)

Truncation allows a searcher to search for words beginning with the same word stem. A search for therap* will, thus, retrieve therapy, therapies, therapeutic, and all other words starting with “therap.” Do not truncate a word stem that is too short. Also, limitations of interfaces should be taken into account, especially in PubMed, where the number of search term variations that can be found by truncation is limited to 600.

Databases contain references to articles using both standard British and American English spellings. Both need to be searched as free-text terms in the title and abstract. Alternatively, many interfaces offer a certain code to replace zero or one characters, allowing a search for “pediatric” or “paediatric” as “p?ediatric.” Table 1 provides a detailed description of the syntax for different interfaces.

Field codes in five most used interfaces for biomedical literature searching

Searching for abbreviations can identify extra, relevant references and retrieve more irrelevant ones. The search can be more focused by combining the abbreviation with an important word that is relevant to its meaning or by using the Boolean “NOT” to exclude frequently observed, clearly irrelevant results. We advise that searchers do not exclude all possible irrelevant meanings, as it is very time consuming to identify all the variations, it will result in unnecessarily complicated search strategies, and it may lead to erroneously narrowing the search and, thereby, reduce recall.

Searching partial abbreviations can be useful for retrieving relevant references. For example, it is very likely that an article would mention osteoarthritis (OA) early in the abstract, replacing all further occurrences of osteoarthritis with OA . Therefore, it may not contain the phrase “hip osteoarthritis” but only “hip oa.”

It is also important to search for the opposites of search terms to avoid bias. When searching for “disease recurrence,” articles about “disease free” may be relevant as well. When the desired outcome is survival , articles about mortality may be relevant.

10. Use database-appropriate syntax, with parentheses, Boolean operators, and field codes

Different interfaces require different syntaxes, the special set of rules and symbols unique to each database that define how a correctly constructed search operates. Common syntax components include the use of parentheses and Boolean operators such as “AND,” “OR,” and “NOT,” which are available in all major interfaces. An overview of different syntaxes for four major interfaces for bibliographic medical databases (PubMed, Ovid, EBSCOhost, Embase.com, and ProQuest) is shown in Table 1 .

Creating the appropriate syntax for each database, in combination with the selected terms as described in steps 7–9, can be challenging. Following the method outlined below simplifies the process:

• Create single-line queries in a text document (not combining multiple record sets), which allows immediate checking of the relevance of retrieved references and efficient optimization.
• Type the syntax (Boolean operators, parentheses, and field codes) before adding terms, which reduces the chance that errors are made in the syntax, especially in the number of parentheses.
• Use predefined proximity structures including parentheses, such as (() ADJ3 ()) in Ovid, that can be reused in the query when necessary.
• Use thesaurus terms separately from free-text terms of each element. Start an element with all thesaurus terms (using “OR”) and follow with the free-text terms. This allows the unique optimization methods as described in step 11.
• When adding terms to an existing search strategy, pay close attention to the position of the cursor. Make sure to place it appropriately either in the thesaurus terms section, in the title/abstract section, or as an addition (broadening) to an existing proximity search.

The supplementary appendix explains the method of building a query in more detail, step by step for different interfaces: PubMed, Ovid, EBSCOhost, Embase.com, and ProQuest. This method results in a basic search strategy designed to retrieve some relevant references upon which a more thorough search strategy can be built with optimization such as described in step 11.

11. Optimize the search

The most important question when performing a systematic search is whether all (or most) potentially relevant articles have been retrieved by the search strategy. This is also the most difficult question to answer, since it is unknown which and how many articles are relevant. It is, therefore, wise first to broaden the initial search strategy, making the search more sensitive, and then check if new relevant articles are found by comparing the set results (i.e., search for Strategy #2 NOT Strategy #1 to see the unique results).

A search strategy should be tested for completeness. Therefore, it is necessary to identify extra, possibly relevant search terms and add them to the test search in an OR relationship with the already used search terms. A good place to start, and a well-known strategy, is scanning the top retrieved articles when sorted by relevance, looking for additional relevant synonyms that could be added to the search strategy.

We have developed a unique optimization method that has not been described before in the literature. This method often adds valuable extra terms to our search strategy and, therefore, extra, relevant references to our search results. Extra synonyms can be found in articles that have been assigned a certain set of thesaurus terms but that lack synonyms in the title and/or abstract that are already present in the current search strategy. Searching for thesaurus terms NOT free-text terms will help identify missed free-text terms in the title or abstract. Searching for free-text terms NOT thesaurus terms will help identify missed thesaurus terms. If this is done repeatedly for each element, leaving the rest of the query unchanged, this method will help add numerous relevant terms to the query. These steps are explained in detail for five different search platforms in the supplementary appendix .

12. Evaluate the initial results

The results should now contain relevant references. If the interface allows relevance ranking, use that in the evaluation. If you know some relevant references that should be included in the research, search for those references specifically; for example, combine a specific (first) author name with a page number and the publication year. Check whether those references are retrieved by the search. If the known relevant references are not retrieved by the search, adapt the search so that they are. If it is unclear which element should be adapted to retrieve a certain article, combine that article with each element separately.

Different outcomes are desired for different types of research questions. For instance, in the case of clinical question answering, the researcher will not be satisfied with many references that contain a lot of irrelevant references. A clinical search should be rather specific and is allowed to miss a relevant reference. In the case of an SR, the researchers do not want to miss any relevant reference and are willing to handle many irrelevant references to do so. The search for references to include in an SR should be very sensitive: no included reference should be missed. A search that is too specific or too sensitive for the intended goal can be adapted to become more sensitive or specific. Steps to increase sensitivity or specificity of a search strategy can be found in the supplementary appendix .

13. Check for errors

Errors might not be easily detected. Sometimes clues can be found in the number of results, either when the number of results is much higher or lower than expected or when many retrieved references are not relevant. However, the number expected is often unknown, and very sensitive search strategies will always retrieve many irrelevant articles. Each query should, therefore, be checked for errors.

One of the most frequently occurring errors is missing the Boolean operator “OR.” When no “OR” is added between two search terms, many interfaces automatically add an “AND,” which unintentionally reduces the number of results and likely misses relevant references. One good strategy to identify missing “OR”s is to go to the web page containing the full search strategy, as translated by the database, and using Ctrl-F search for “AND.” Check whether the occurrences of the “AND” operator are deliberate.

Ideally, search strategies should be checked by other information specialists [ 18 ]. The Peer Review of Electronic Search Strategies (PRESS) checklist offers good guidance for this process [ 4 ]. Apart from the syntax (especially Boolean operators and field codes) of the search strategy, it is wise to have the search terms checked by the clinician or researcher familiar with the topic. At Erasmus MC, researchers and clinicians are involved during the complete process of structuring and optimizing the search strategy. Each word is added after the combined decision of the searcher and the researcher, with the possibility of directly comparing results with and without the new term.

14. Translate to other databases

To retrieve as many relevant references as possible, one has to search multiple databases. Translation of complex and exhaustive queries between different databases can be very time consuming and cumbersome. The single-line search strategy approach detailed above allows quick translations using the find and replace method in Microsoft Word (<Ctrl-H>).

At Erasmus MC, macros based on the find-and-replace method in Microsoft Word have been developed for easy and fast translation between the most used databases for biomedical and health sciences questions. The schema that is followed for the translation between databases is shown in Figure 2 . Most databases simply follow the structure set by the Embase.com search strategy. The translation from Emtree terms to MeSH terms for MEDLINE in Ovid often identifies new terms that need to be added to the Embase.com search strategy before the translation to other databases.

Schematic representation of translation between databases used at Erasmus University Medical Center

Dotted lines represent databases that are used in less than 80% of the searches.

Using five different macros, a thoroughly optimized query in Embase.com can be relatively quickly translated into eight major databases. Basic search strategies will be created to use in many, mostly smaller, databases, because such niche databases often do not have extensive thesauri or advanced syntax options. Also, there is not much need to use extensive syntax because the number of hits and, therefore, the amount of noise in these databases is generally low. In MEDLINE (Ovid), PsycINFO (Ovid), and CINAHL (EBSCOhost), the thesaurus terms must be adapted manually, as each database has its own custom thesaurus. These macros and instructions for their installation, use, and adaptation are available at bit.ly/databasemacros.

15. Test and reiterate

Ideally, exhaustive search strategies should retrieve all references that are covered in a specific database. For SR search strategies, checking searches for their recall is advised. This can be done after included references have been determined by the authors of the systematic review. If additional papers have been identified through other non-database methods (i.e., checking references in included studies), results that were not identified by the database searches should be examined. If these results were available in the databases but not located by the search strategy, the search strategy should be adapted to try to retrieve these results, as they may contain terms that were omitted in the original search strategies. This may enable the identification of additional relevant results.

A methodology for creating exhaustive search strategies has been created that describes all steps of the search process, starting with a question and resulting in thorough search strategies in multiple databases. Many of the steps described are not new, but together, they form a strong method creating high-quality, robust searches in a relatively short time frame.

Our methodology is intended to create thoroughness for literature searches. The optimization method, as described in step 11, will identify missed synonyms or thesaurus terms, unlike any other method that largely depends on predetermined keywords and synonyms. Using this method results in a much quicker search process, compared to traditional methods, especially because of the easier translation between databases and interfaces (step 13). The method is not a guarantee for speed, since speed depends on many factors, including experience. However, by following the steps and using the tools as described above, searchers can gain confidence first and increase speed through practice.

What is new?

This method encourages searchers to start their search development process using empty syntax first and later adding the thesaurus terms and free-text synonyms. We feel this helps the searcher to focus on the search terms, instead of on the structure of the search query. The optimization method in which new terms are found in the already retrieved articles is used in some other institutes as well but has to our knowledge not been described in the literature. The macros to translate search strategies between interfaces are unique in this method.

What is different compared to common practice?

Traditionally, librarians and information specialists have focused on creating complex, multi-line (also called line-by-line) search strategies, consisting of multiple record sets, and this method is frequently advised in the literature and handbooks [ 2 , 19 – 21 ]. Our method, instead, uses single-line searches, which is critical to its success. Single-line search strategies can be easily adapted by adding or dropping a term without having to recode numbers of record sets, which would be necessary in multi-line searches. They can easily be saved in a text document and repeated by copying and pasting for search updates. Single-line search strategies also allow easy translation to other syntaxes using find-and-replace technology to update field codes and other syntax elements or using macros (step 13).

When constructing a search strategy, the searcher might experience that certain parentheses in the syntax are unnecessary, such as parentheses around all search terms in the title/abstract portion, if there is only one such term, there are double parentheses in the proximity statement, or one of the word groups exists for only one word. One might be tempted to omit those parentheses for ease of reading and management. However, during the optimization process, the searcher is likely to find extra synonyms that might consist of one word. To add those terms to the first query (with reduced parentheses) requires adding extra parentheses (meticulously placing and counting them), whereas, in the latter search, it only requires proper placement of those terms.

Many search methods highly depend on the PICO framework. Research states that often PICO or PICOS is not suitable for every question [ 22 , 23 ]. There are other acronyms than PICO—such as sample, phenomenon of interest, design, evaluation, research type (SPIDER) [ 24 ]—but each is just a variant. In our method, the most important and specific elements of a question are being analyzed for building the best search strategy.

Though it is generally recommended that searchers search both MEDLINE and Embase, most use MEDLINE as the starting point. It is considered the gold standard for biomedical searching, partially due to historical reasons, since it was the first of its kind, and more so now that it is freely available via the PubMed interface. Our method can be used with any database as a starting point, but we use Embase instead of MEDLINE or another database for a number of reasons. First, Embase provides both unique content and the complete content of MEDLINE. Therefore, searching Embase will be, by definition, more complete than searching MEDLINE only. Second, the number of terms in Emtree (the Embase thesaurus) is three times as high as that of MeSH (the MEDLINE thesaurus). It is easier to find MeSH terms after all relevant Emtree terms have been identified than to start with MeSH and translate to Emtree.

At Erasmus MC, the researchers sit next to the information specialist during most of the search strategy design process. This way, the researchers can deliver immediate feedback on the relevance of proposed search terms and retrieved references. The search team then combines knowledge about databases with knowledge about the research topic, which is an important condition to create the highest quality searches.

Limitations of the method

One disadvantage of single-line searches compared to multi-line search strategies is that errors are harder to recognize. However, with the methods for optimization as described (step 11), errors are recognized easily because missed synonyms and spelling errors will be identified during the process. Also problematic is that more parentheses are needed, making it more difficult for the searcher and others to assess the logic of the search strategy. However, as parentheses and field codes are typed before the search terms are added (step 10), errors in parentheses can be prevented.

Our methodology works best if used in an interface that allows proximity searching. It is recommended that searchers with access to an interface with proximity searching capabilities select one of those as the initial database to develop and optimize the search strategy. Because the PubMed interface does not allow proximity searches, phrases or Boolean “AND” combinations are required. Phrase searching complicates the process and is more specific, with the higher risk of missing relevant articles, and using Boolean “AND” combinations increases sensitivity but at an often high loss of specificity. Due to some searchers’ lack of access to expensive databases or interfaces, the freely available PubMed interface may be necessary to use, though it should never be the sole database used for an SR [ 2 , 16 , 25 ]. A limitation of our method is that it works best with subscription-based and licensed resources.

Another limitation is the customization of the macros to a specific institution’s resources. The macros for the translation between different database interfaces only work between the interfaces as described. To mitigate this, we recommend using the find-and-replace functionality of text editors like Microsoft Word to ease the translation of syntaxes between other databases. Depending on one’s institutional resources, custom macros can be developed using similar methods.

Results of the method

Whether this method results in exhaustive searches where no important article is missed is difficult to determine, because the number of relevant articles is unknown for any topic. A comparison of several parameters of 73 published reviews that were based on a search developed with this method to 258 reviews that acknowledged information specialists from other Dutch academic hospitals shows that the performance of the searches following our method is comparable to those performed in other institutes but that the time needed to develop the search strategies was much shorter than the time reported for the other reviews [ 9 ].

CONCLUSIONS

With the described method, searchers can gain confidence in their search strategies by finding many relevant words and creating exhaustive search strategies quickly. The approach can be used when performing SR searches or for other purposes such as answering clinical questions, with different expectations of the search’s precision and recall. This method, with practice, provides a stepwise approach that facilitates the search strategy development process from question clarification to final iteration and beyond.

SUPPLEMENTAL FILE

Acknowledgments.

We highly appreciate the work that was done by our former colleague Louis Volkers, who in his twenty years as an information specialist in Erasmus MC laid the basis for our method. We thank Professor Oscar Franco for reviewing earlier drafts of this article.

Literature Reviews: systematic searching at various levels

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Search strategy template

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You can map out your search strategy in whatever way works for you.

Some people like lists and so plan their search strategy out in a grid-box or table format. Some people are more visual and like to draw their strategy out using a mind-map approach (either on paper or using mind-mapping software). Some people use sticky notes or Trello or a spreadsheet.

If it works for you then as long as it enables you to search systematically and thoroughly there's no need to change the way you work. 

If your search strategies are not very developed, the method you use doesn't lead to a good search, then consider using one of the other methods to see if changing your approach helps.

• Search Strategy Document
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• Last Updated: Apr 12, 2024 11:57 AM
• URL: https://libguides.derby.ac.uk/literature-reviews

Beyond PICO: the SPIDER tool for qualitative evidence synthesis

Affiliation.

• 1 Central Manchester NHS Foundation Trust, Manchester, United Kingdom. [email protected]
• PMID: 22829486
• DOI: 10.1177/1049732312452938

Standardized systematic search strategies facilitate rigor in research. Current search tools focus on retrieval of quantitative research. In this article we address issues relating to using existing search strategy tools, most typically the PICO (Population, Intervention, Comparison, Outcome) formulation for defining key elements of a review question, when searching for qualitative and mixed methods research studies. An alternative search strategy tool for qualitative/mixed methods research is outlined: SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, Research type). We used both the SPIDER and PICO search strategy tools with a qualitative research question. We have used the SPIDER tool to advance thinking beyond PICO in its suitable application to qualitative and mixed methods research. However, we have highlighted once more the need for improved indexing of qualitative articles in databases. To constitute a viable alternative to PICO, SPIDER needs to be refined and tested on a wider range of topics.

• Information Storage and Retrieval / methods*
• Meta-Analysis as Topic
• Qualitative Research*
• Review Literature as Topic*
• Sensitivity and Specificity

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Expert Commentary

Research strategy guide for finding quality, credible sources

Strategies for finding academic studies and other information you need to give your stories authority and depth

Republish this article

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Keely Wilczek, The Journalist's Resource May 20, 2011

This <a target="_blank" href="https://journalistsresource.org/home/research-strategy-guide/">article</a> first appeared on <a target="_blank" href="https://journalistsresource.org">The Journalist's Resource</a> and is republished here under a Creative Commons license.<img src="https://journalistsresource.org/wp-content/uploads/2020/11/cropped-jr-favicon-150x150.png" style="width:1em;height:1em;margin-left:10px;">

Knowing how to conduct deeper research efficiently and effectively is a critical skill for journalists — especially in the information age. It is, like other facets of the profession such as interviewing, a matter of practice and establishing good habits. And once you find a successful routine for information-gathering, it will pay dividends time and again.

Journalists need to be able to do many kinds of research. This article focuses on creating a research strategy that will help you find academic studies and related scholarly information. These sources can, among other things, give your stories extra authority and depth — and thereby distinguish your work. You can see examples of such studies — and find many relevant ones for your stories — by searching the Journalist’s Resource database . But that is just a representative sample of what exists in the research world.

The first step is to create a plan for seeking the information you need. This requires you to take time initially and to proceed with care, but it will ultimately pay off in better results. The research strategy covered in this article involves the following steps:

Get organized

Articulate your topic, locate background information.

• Identify your information needs

List keywords and concepts for search engines and databases

Consider the scope of your topic, conduct your searches, evaluate the information sources you found, analyze and adjust your research strategy.

Being organized is an essential part of effective research strategy. You should create a record of your strategy and your searches. This will prevent you from repeating searches in the same resources and from continuing to use ineffective terms. It will also help you assess the success or failure of your research strategy as you go through the process. You also may want to consider tracking and organizing citations and links in bibliographic software such as Zotero . (See this helpful resource guide about using Zotero.)

Next, write out your topic in a clear and concise manner. Good research starts with a specific focus.

For example, let’s say you are writing a story about the long-range health effects of the explosion at the Chernobyl Nuclear Power Plant based on a study published in Environmental Health Perspectives titled, “The Chernobyl Accident 20 Years On: An Assessment of the Health Consequences and the International Response.” (The study is summarized in Journalist’s Resource here .)

A statement of your topic might be, “Twenty years after the Chernobyl disaster, scientists are still learning the affects of the accident on the health of those who lived in the surrounding area and their descendants.”

If you have a good understanding of the Chernobyl disaster, proceed to the next step, “Identify the information you need.” If not, it’s time to gather background information. This will supply you with the whos and the whens of the topic. It will also provide you with a broader context as well as the important terminology.

Excellent sources of background information are subject-specific encyclopedias and dictionaries, books, and scholarly articles, and organizations’ websites. You should always consult more than one source so you can compare for accuracy and bias.

For your story about Chernobyl, you might want to consult some of the following sources:

• Frequently Asked Chernobyl Questions , International Atomic Agency
• Chernobyl Accident 1986 , World Nuclear Association
• Chernobyl: Consequences of the Catastrophe for People and the Environment , New York Academy of Sciences, 2009.
• “Chernobyl Disaster,” Encyclopedia Britannica, last updated 2013.

Identify the information you need

What information do you need to write your story? One way to determine this is to turn your overall topic into a list of questions to be answered. This will help you identify the type and level of information you need. Some possible questions on consequences of the Chernobyl accident are:

• What are the proven health effects?
• What are some theorized health effects?
• Is there controversy about any of these studies?
• What geographic area is being studied?
• What are the demographic characteristics of the population being studied?
• Was there anything that could have been done at the time to mitigate these effects?

Looking at these questions, it appears that scientific studies and scholarly articles about those studies, demographic data, disaster response analysis, and government documents and publications from the Soviet Union and Ukraine would be needed.

Now you need to determine what words you will use to enter in the search boxes within resources. One way to begin is to extract the most important words and phrases from the questions produced in the previous step. Next, think about alternative words and phrases that you might use. Always keep in mind that different people may write or talk about the same topic in different ways. Important concepts can referred to differently or be spelled differently depending on country of origin or field of study.

For the Chernobyl health story, some search keyword options are: “Chernobyl,” “Chornobyl”; “disaster,” “catastrophe,” “explosion”; “health,” “disease,” “illness,” “medical conditions”; “genetic mutation,” “gene mutation,” “germ-line mutation,” “hereditary disease.” Used in different combinations, these can unearth a wide variety of resources.

Next you should identify the scope of your topic and any limitations it puts on your searches. Some examples of limitations are language, publication date, and publication type. Every database and search engine will have its own rules so you may need to click on an advanced search option in order to input these limitations.

It is finally time to start looking for information but identifying which resources to use is not always easy to do. First, if you are part of an organization, find out what, if any, resources you have access to through a subscription. Examples of subscription resources are LexisNexis and JSTOR. If your organization does not provide subscription resources, find out if you can get access to these sources through your local library. Should you not have access to any subscription resources appropriate for your topic, look at some of the many useful free resources on the internet.

Here are some examples of sources for free information:

• PLoS , Public Library of Science
• Google Scholar
• SSRN , Social Science Research Network
• FDsys , U.S. Government documents and publications
• World Development Indicators , World Bank
• Pubmed , service of the U.S. National Library of Medicine

More quality sites, and search tips, are here among the other research articles at Journalist’s Resource.

As you only want information from the most reliable and suitable sources, you should always evaluate your results. In doing this, you can apply journalism’s Five W’s (and One H):

• Who : Who is the author and what are his/her credentials in this topic?
• What: Is the material primary or secondary in nature?
• Where: Is the publisher or organization behind the source considered reputable? Does the website appear legitimate?
• When: Is the source current or does it cover the right time period for your topic?
• Why: Is the opinion or bias of the author apparent and can it be taken into account?
• How: Is the source written at the right level for your needs? Is the research well-documented?

Were you able to locate the information you needed? If not, now it is time to analyze why that happened. Perhaps there are better resources or different keywords and concepts you could have tried. Additional background information might supply you with other terminology to use. It is also possible that the information you need is just not available in the way you need it and it may be necessary to consult others for assistance like an expert in the topic or a professional librarian.

Keely Wilczek is a research librarian at the Harvard Kennedy School. Tags: training

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Keely Wilczek

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Computer Science > Human-Computer Interaction

Title: agentcoord: visually exploring coordination strategy for llm-based multi-agent collaboration.

Abstract: The potential of automatic task-solving through Large Language Model (LLM)-based multi-agent collaboration has recently garnered widespread attention from both the research community and industry. While utilizing natural language to coordinate multiple agents presents a promising avenue for democratizing agent technology for general users, designing coordination strategies remains challenging with existing coordination frameworks. This difficulty stems from the inherent ambiguity of natural language for specifying the collaboration process and the significant cognitive effort required to extract crucial information (e.g. agent relationship, task dependency, result correspondence) from a vast amount of text-form content during exploration. In this work, we present a visual exploration framework to facilitate the design of coordination strategies in multi-agent collaboration. We first establish a structured representation for LLM-based multi-agent coordination strategy to regularize the ambiguity of natural language. Based on this structure, we devise a three-stage generation method that leverages LLMs to convert a user's general goal into an executable initial coordination strategy. Users can further intervene at any stage of the generation process, utilizing LLMs and a set of interactions to explore alternative strategies. Whenever a satisfactory strategy is identified, users can commence the collaboration and examine the visually enhanced execution result. We develop AgentCoord, a prototype interactive system, and conduct a formal user study to demonstrate the feasibility and effectiveness of our approach.

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Journal of Materials Chemistry A

Zn alloying strategy to improve the photoluminescence of cugas 2 /zns core/shell quantum dots †.

* Corresponding authors

a Department of Physics, Savitribai Phule Pune University, Pune 411 007, India E-mail: [email protected]

b Symbiosis Center for Nanoscience and Nanotechnology, Symbiosis International University, Lavale, Pune 412 115, India

c Atomic & Molecular Physics Division, Bhabha Atomic Research Centre, Mumbai 400 094, India

d Beamline Development and Application Section, Bhabha Atomic Research Centre, Mumbai 400 094, India

Research efforts are being devoted to realize colloidal, heavy metal ion free, and luminescent quantum dots. We address radiative recombination in Zn alloyed CuGaS 2 /ZnS core/shell chalcopyrite quantum dots (CQDs) emitting in the blue-green spectral region. QDs show a systematic increase in the optical band gap and emission energy with an increasing amount of Zn in their core. Intentionally making non-stoichiometric CQDs with core/shell geometry enables defect related emission with high intensity. The location of Cu related defect levels along with the valence band and conduction band edge was determined from electrochemical cyclic voltammetry (CV) measurements. The evolution of band gap energies with respect to Zn concentration examined using CV measurements matches well with the optical absorption data. The presence of Cu vacancies in off-stoichiometric samples introduces intra-gap levels, which serve as common acceptor levels for optical transitions. Luminescence transitions in these materials stem from the radiative recombination of electrons from conduction levels as well as donor levels, with holes localized at acceptor levels. Temperature dependent and excitation laser intensity dependent emission measurements confirm the role of the Cu vacancy related acceptor level in the emission. Local structure studies via extended X-ray absorption fine structure and X-ray absorption near edge structure analysis were carried out to understand how Zn is incorporated in CuGaS 2 quantum dots and affects the luminescence. Electron spin resonance measurements confirm the presence of paramagnetic defect complexes. X-ray absorption near edge structure measurements indicate that Cu co-exists in +1 and +2 oxidation states in CuGaS 2 quantum dots.

• This article is part of the themed collection: Journal of Materials Chemistry A HOT Papers

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Zn alloying strategy to improve the photoluminescence of CuGaS 2 /ZnS core/shell quantum dots

M. A. Haque, A. Lohar, Y. Jadhav, R. Kumar, S. N. Jha, D. Bhattacharyya, S. Jadkar, S. Sartale and S. Mahamuni, J. Mater. Chem. A , 2024, Advance Article , DOI: 10.1039/D4TA01134A

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