review of related literature quantitative research

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Quantitative research: literature review .

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Exploring the literature review 

Literature review model: 6 steps.

Adapted from The Literature Review , Machi & McEvoy (2009, p. 13).

Your Literature Review

Step 2: search, boolean search strategies, search limiters, ★ ebsco & google drive.

1. Select a Topic

"All research begins with curiosity" (Machi & McEvoy, 2009, p. 14)

Selection of a topic, and fully defined research interest and question, is supervised (and approved) by your professor. Tips for crafting your topic include:

• Be specific. Take time to define your interest.
• Topic Focus. Fully describe and sufficiently narrow the focus for research.
• Academic Discipline. Learn more about your area of research & refine the scope.
• Avoid Bias. Be aware of bias that you (as a researcher) may have.
• Document your research. Use Google Docs to track your research process.
• Research apps. Consider using Evernote or Zotero to track your research.

Consider Purpose

What will your topic and research address?

In The Literature Review: A Step-by-Step Guide for Students , Ridley presents that literature reviews serve several purposes (2008, p. 16-17).  Included are the following points:

• Historical background for the research;
• Overview of current field provided by "contemporary debates, issues, and questions;"
• Theories and concepts related to your research;
• Introduce "relevant terminology" - or academic language - being used it the field;
• Connect to existing research - does your work "extend or challenge [this] or address a gap;" 
• Provide "supporting evidence for a practical problem or issue" that your research addresses.

★ Schedule a research appointment

At this point in your literature review, take time to meet with a librarian. Why? Understanding the subject terminology used in databases can be challenging. Archer Librarians can help you structure a search, preparing you for step two. How? Contact a librarian directly or use the online form to schedule an appointment. Details are provided in the adjacent Schedule an Appointment box.

2. Search the Literature

Collect & Select Data: Preview, select, and organize

Archer Library is your go-to resource for this step in your literature review process. The literature search will include books and ebooks, scholarly and practitioner journals, theses and dissertations, and indexes. You may also choose to include web sites, blogs, open access resources, and newspapers. This library guide provides access to resources needed to complete a literature review.

Books & eBooks: Archer Library & OhioLINK

Databases: Scholarly & Practitioner Journals

Review the Library Databases tab on this library guide, it provides links to recommended databases for Education & Psychology, Business, and General & Social Sciences.

Expand your journal search; a complete listing of available AU Library and OhioLINK databases is available on the Databases  A to Z list . Search the database by subject, type, name, or do use the search box for a general title search. The A to Z list also includes open access resources and select internet sites.

Databases: Theses & Dissertations

Review the Library Databases tab on this guide, it includes Theses & Dissertation resources. AU library also has AU student authored theses and dissertations available in print, search the library catalog for these titles.

Did you know? If you are looking for particular chapters within a dissertation that is not fully available online, it is possible to submit an ILL article request . Do this instead of requesting the entire dissertation.

Newspapers:  Databases & Internet

Consider current literature in your academic field. AU Library's database collection includes The Chronicle of Higher Education and The Wall Street Journal .  The Internet Resources tab in this guide provides links to newspapers and online journals such as Inside Higher Ed , COABE Journal , and Education Week .

The Chronicle of Higher Education has the nation’s largest newsroom dedicated to covering colleges and universities.  Source of news, information, and jobs for college and university faculty members and administrators

The Chronicle features complete contents of the latest print issue; daily news and advice columns; current job listings; archive of previously published content; discussion forums; and career-building tools such as online CV management and salary databases. Dates covered: 1970-present.

Offers in-depth coverage of national and international business and finance as well as first-rate coverage of hard news--all from America's premier financial newspaper. Covers complete bibliographic information and also subjects, companies, people, products, and geographic areas. 

Comprehensive coverage back to 1984 is available from the world's leading financial newspaper through the ProQuest database. 

Newspaper Source provides cover-to-cover full text for hundreds of national (U.S.), international and regional newspapers. In addition, it offers television and radio news transcripts from major networks.

Provides complete television and radio news transcripts from CBS News, CNN, CNN International, FOX News, and more.

Search Strategies & Boolean Operators

There are three basic boolean operators:  AND, OR, and NOT.

Used with your search terms, boolean operators will either expand or limit results. What purpose do they serve? They help to define the relationship between your search terms. For example, using the operator AND will combine the terms expanding the search. When searching some databases, and Google, the operator AND may be implied.

Overview of boolean terms

About the example: Boolean searches were conducted on November 4, 2019; result numbers may vary at a later date. No additional database limiters were set to further narrow search returns.

Database Search Limiters

Database strategies for targeted search results.

Most databases include limiters, or additional parameters, you may use to strategically focus search results.  EBSCO databases, such as Education Research Complete & Academic Search Complete provide options to:

• Limit results to full text;
• Limit results to scholarly journals, and reference available;
• Select results source type to journals, magazines, conference papers, reviews, and newspapers
• Publication date

Keep in mind that these tools are defined as limiters for a reason; adding them to a search will limit the number of results returned.  This can be a double-edged sword.  How? 

• If limiting results to full-text only, you may miss an important piece of research that could change the direction of your research. Interlibrary loan is available to students, free of charge. Request articles that are not available in full-text; they will be sent to you via email.
• If narrowing publication date, you may eliminate significant historical - or recent - research conducted on your topic.
• Limiting resource type to a specific type of material may cause bias in the research results.

Use limiters with care. When starting a search, consider opting out of limiters until the initial literature screening is complete. The second or third time through your research may be the ideal time to focus on specific time periods or material (scholarly vs newspaper).

★ Truncating Search Terms

Expanding your search term at the root.

Truncating is often referred to as 'wildcard' searching. Databases may have their own specific wildcard elements however, the most commonly used are the asterisk (*) or question mark (?).  When used within your search. they will expand returned results.

Asterisk (*) Wildcard

Using the asterisk wildcard will return varied spellings of the truncated word. In the following example, the search term education was truncated after the letter "t."

Explore these database help pages for additional information on crafting search terms.

• EBSCO Connect: Basic Searching with EBSCO
• EBSCO Connect: Searching with Boolean Operators
• EBSCO Connect: Searching with Wildcards and Truncation Symbols
• ProQuest Help: Search Tips
• ERIC: How does ERIC search work?

★ EBSCO Databases & Google Drive

Tips for saving research directly to Google drive.

Researching in an EBSCO database?

It is possible to save articles (PDF and HTML) and abstracts in EBSCOhost databases directly to Google drive. Select the Google Drive icon, authenticate using a Google account, and an EBSCO folder will be created in your account. This is a great option for managing your research. If documenting your research in a Google Doc, consider linking the information to actual articles saved in drive.

EBSCO Databases & Google Drive

EBSCOHost Databases & Google Drive: Managing your Research

This video features an overview of how to use Google Drive with EBSCO databases to help manage your research. It presents information for connecting an active Google account to EBSCO and steps needed to provide permission for EBSCO to manage a folder in Drive.

About the Video:  Closed captioning is available, select CC from the video menu.  If you need to review a specific area on the video, view on YouTube and expand the video description for access to topic time stamps.  A video transcript is provided below.

• EBSCOhost Databases & Google Scholar

Defining Literature Review

What is a literature review.

A definition from the Online Dictionary for Library and Information Sciences .

A literature review is "a comprehensive survey of the works published in a particular field of study or line of research, usually over a specific period of time, in the form of an in-depth, critical bibliographic essay or annotated list in which attention is drawn to the most significant works" (Reitz, 2014). 

A systemic review is "a literature review focused on a specific research question, which uses explicit methods to minimize bias in the identification, appraisal, selection, and synthesis of all the high-quality evidence pertinent to the question" (Reitz, 2014).

Recommended Reading

About this page

EBSCO Connect [Discovery and Search]. (2022). Searching with boolean operators. Retrieved May, 3, 2022 from https://connect.ebsco.com/s/?language=en_US

EBSCO Connect [Discover and Search]. (2022). Searching with wildcards and truncation symbols. Retrieved May 3, 2022; https://connect.ebsco.com/s/?language=en_US

Machi, L.A. & McEvoy, B.T. (2009). The literature review . Thousand Oaks, CA: Corwin Press: 

Reitz, J.M. (2014). Online dictionary for library and information science. ABC-CLIO, Libraries Unlimited . Retrieved from https://www.abc-clio.com/ODLIS/odlis_A.aspx

Ridley, D. (2008). The literature review: A step-by-step guide for students . Thousand Oaks, CA: Sage Publications, Inc.

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Educational resources and simple solutions for your research journey

How to Write Review of Related Literature (RRL) in Research

A review of related literature (a.k.a RRL in research) is a comprehensive review of the existing literature pertaining to a specific topic or research question. An effective review provides the reader with an organized analysis and synthesis of the existing knowledge about a subject. With the increasing amount of new information being disseminated every day, conducting a review of related literature is becoming more difficult and the purpose of review of related literature is clearer than ever.  

All new knowledge is necessarily based on previously known information, and every new scientific study must be conducted and reported in the context of previous studies. This makes a review of related literature essential for research, and although it may be tedious work at times , most researchers will complete many such reviews of varying depths during their career. So, why exactly is a review of related literature important?    

Table of Contents

Why a review of related literature in research is important  

Before thinking how to do reviews of related literature , it is necessary to understand its importance. Although the purpose of a review of related literature varies depending on the discipline and how it will be used, its importance is never in question. Here are some ways in which a review can be crucial.  

• Identify gaps in the knowledge – This is the primary purpose of a review of related literature (often called RRL in research ). To create new knowledge, you must first determine what knowledge may be missing. This also helps to identify the scope of your study.  
• Avoid duplication of research efforts – Not only will a review of related literature indicate gaps in the existing research, but it will also lead you away from duplicating research that has already been done and thus save precious resources.  
• Provide an overview of disparate and interdisciplinary research areas – Researchers cannot possibly know everything related to their disciplines. Therefore, it is very helpful to have access to a review of related literature already written and published.  
• Highlight researcher’s familiarity with their topic 1  – A strong review of related literature in a study strengthens readers’ confidence in that study and that researcher.

Tips on how to write a review of related literature in research

Given that you will probably need to produce a number of these at some point, here are a few general tips on how to write an effective review of related literature 2 .

• Define your topic, audience, and purpose: You will be spending a lot of time with this review, so choose a topic that is interesting to you. While deciding what to write in a review of related literature , think about who you expect to read the review – researchers in your discipline, other scientists, the general public – and tailor the language to the audience. Also, think about the purpose of your review of related literature .  
• Conduct a comprehensive literature search: While writing your review of related literature , emphasize more recent works but don’t forget to include some older publications as well. Cast a wide net, as you may find some interesting and relevant literature in unexpected databases or library corners. Don’t forget to search for recent conference papers.
• Review the identified articles and take notes: It is a good idea to take notes in a way such that individual items in your notes can be moved around when you organize them. For example, index cards are great tools for this. Write each individual idea on a separate card along with the source. The cards can then be easily grouped and organized.  
• Determine how to organize your review: A review of related literature should not be merely a listing of descriptions. It should be organized by some criterion, such as chronologically or thematically.  
• Be critical and objective: Don’t just report the findings of other studies in your review of related literature . Challenge the methodology, find errors in the analysis, question the conclusions. Use what you find to improve your research. However, do not insert your opinions into the review of related literature. Remain objective and open-minded.  
• Structure your review logically: Guide the reader through the information. The structure will depend on the function of the review of related literature. Creating an outline prior to writing the RRL in research is a good way to ensure the presented information flows well.  

As you read more extensively in your discipline, you will notice that the review of related literature appears in various forms in different places. For example, when you read an article about an experimental study, you will typically see a literature review or a RRL in research , in the introduction that includes brief descriptions of similar studies. In longer research studies and dissertations, especially in the social sciences, the review of related literature will typically be a separate chapter and include more information on methodologies and theory building. In addition, stand-alone review articles will be published that are extremely useful to researchers.  

The review of relevant literature or often abbreviated as, RRL in research , is an important communication tool that can be used in many forms for many purposes. It is a tool that all researchers should befriend.  

• University of North Carolina at Chapel Hill Writing Center. Literature Reviews.  https://writingcenter.unc.edu/tips-and-tools/literature-reviews/  [Accessed September 8, 2022]
• Pautasso M. Ten simple rules for writing a literature review. PLoS Comput Biol. 2013, 9. doi: 10.1371/journal.pcbi.1003149.

Q:  Is research complete without a review of related literature?

A research project is usually considered incomplete without a proper review of related literature. The review of related literature is a crucial component of any research project as it provides context for the research question, identifies gaps in existing literature, and ensures novelty by avoiding duplication. It also helps inform research design and supports arguments, highlights the significance of a study, and demonstrates your knowledge an expertise.

Q: What is difference between RRL and RRS?

The key difference between an RRL and an RRS lies in their focus and scope. An RRL or review of related literature examines a broad range of literature, including theoretical frameworks, concepts, and empirical studies, to establish the context and significance of the research topic. On the other hand, an RRS or review of research studies specifically focuses on analyzing and summarizing previous research studies within a specific research domain to gain insights into methodologies, findings, and gaps in the existing body of knowledge. While there may be some overlap between the two, they serve distinct purposes and cover different aspects of the research process.

Q: Does review of related literature improve accuracy and validity of research?

Yes, a comprehensive review of related literature (RRL) plays a vital role in improving the accuracy and validity of research. It helps authors gain a deeper understanding and offers different perspectives on the research topic. RRL can help you identify research gaps, dictate the selection of appropriate research methodologies, enhance theoretical frameworks, avoid biases and errors, and even provide support for research design and interpretation. By building upon and critically engaging with existing related literature, researchers can ensure their work is rigorous, reliable, and contributes meaningfully to their field of study.

R Discovery is a literature search and research reading platform that accelerates your research discovery journey by keeping you updated on the latest, most relevant scholarly content. With 250M+ research articles sourced from trusted aggregators like CrossRef, Unpaywall, PubMed, PubMed Central, Open Alex and top publishing houses like Springer Nature, JAMA, IOP, Taylor & Francis, NEJM, BMJ, Karger, SAGE, Emerald Publishing and more, R Discovery puts a world of research at your fingertips.  

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Related Posts

Research in Shorts: R Discovery’s New Feature Helps Academics Assess Relevant Papers in 2mins 

How Does R Discovery’s Interplatform Capability Enhance Research Accessibility 

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Literature Reviews

• Qualitative or Quantitative?
• Getting Started
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• Review Articles/ Annual Reviews...?
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Qualitative researchers TEND to:

Researchers using qualitative methods tend to:

• t hink that social sciences cannot be well-studied with the same methods as natural or physical sciences
• feel that human behavior is context-specific; therefore, behavior must be studied holistically, in situ, rather than being manipulated
• employ an 'insider's' perspective; research tends to be personal and thereby more subjective.
• do interviews, focus groups, field research, case studies, and conversational or content analysis.

Image from https://www.editage.com/insights/qualitative-quantitative-or-mixed-methods-a-quick-guide-to-choose-the-right-design-for-your-research?refer-type=infographics

Qualitative Research (an operational definition)

Qualitative Research: an operational description

Purpose : explain; gain insight and understanding of phenomena through intensive collection and study of narrative data

Approach: inductive; value-laden/subjective; holistic, process-oriented

Hypotheses: tentative, evolving; based on the particular study

Lit. Review: limited; may not be exhaustive

Setting: naturalistic, when and as much as possible

Sampling : for the purpose; not necessarily representative; for in-depth understanding

Measurement: narrative; ongoing

Design and Method: flexible, specified only generally; based on non-intervention, minimal disturbance, such as historical, ethnographic, or case studies

Data Collection: document collection, participant observation, informal interviews, field notes

Data Analysis: raw data is words/ ongoing; involves synthesis

Data Interpretation: tentative, reviewed on ongoing basis, speculative

• Qualitative research with more structure and less subjectivity
• Increased application of both strategies to the same study ("mixed methods")
• Evidence-based practice emphasized in more fields (nursing, social work, education, and others).

Some Other Guidelines

• Guide for formatting Graphs and Tables
• Critical Appraisal Checklist for an Article On Qualitative Research

Quantitative researchers TEND to:

Researchers using quantitative methods tend to:

• think that both natural and social sciences strive to explain phenomena with confirmable theories derived from testable assumptions
• attempt to reduce social reality to variables, in the same way as with physical reality
• try to tightly control the variable(s) in question to see how the others are influenced.
• Do experiments, have control groups, use blind or double-blind studies; use measures or instruments.

Quantitative Research (an operational definition)

Quantitative research: an operational description

Purpose: explain, predict or control phenomena through focused collection and analysis of numberical data

Approach: deductive; tries to be value-free/has objectives/ is outcome-oriented

Hypotheses : Specific, testable, and stated prior to study

Lit. Review: extensive; may significantly influence a particular study

Setting: controlled to the degree possible

Sampling: uses largest manageable random/randomized sample, to allow generalization of results to larger populations

Measurement: standardized, numberical; "at the end"

Design and Method: Strongly structured, specified in detail in advance; involves intervention, manipulation and control groups; descriptive, correlational, experimental

Data Collection: via instruments, surveys, experiments, semi-structured formal interviews, tests or questionnaires

Data Analysis: raw data is numbers; at end of study, usually statistical

Data Interpretation: formulated at end of study; stated as a degree of certainty

This page on qualitative and quantitative research has been adapted and expanded from a handout by Suzy Westenkirchner. Used with permission.

Images from https://www.editage.com/insights/qualitative-quantitative-or-mixed-methods-a-quick-guide-to-choose-the-right-design-for-your-research?refer-type=infographics.

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Research Process :: Step by Step

• Introduction
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Organize the literature review into sections that present themes or identify trends, including relevant theory. You are not trying to list all the material published, but to synthesize and evaluate it according to the guiding concept of your thesis or research question.  

What is a literature review?

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

A literature review must do these things:

• be organized around and related directly to the thesis or research question you are developing
• synthesize results into a summary of what is and is not known
• identify areas of controversy in the literature
• formulate questions that need further research

Ask yourself questions like these:

• What is the specific thesis, problem, or research question that my literature review helps to define?
• What type of literature review am I conducting? Am I looking at issues of theory? methodology? policy? quantitative research (e.g. on the effectiveness of a new procedure)? qualitative research (e.g., studies of loneliness among migrant workers)?
• What is the scope of my literature review? What types of publications am I using (e.g., journals, books, government documents, popular media)? What discipline am I working in (e.g., nursing psychology, sociology, medicine)?
• How good was my information seeking? Has my search been wide enough to ensure I've found all the relevant material? Has it been narrow enough to exclude irrelevant material? Is the number of sources I've used appropriate for the length of my paper?
• Have I critically analyzed the literature I use? Do I follow through a set of concepts and questions, comparing items to each other in the ways they deal with them? Instead of just listing and summarizing items, do I assess them, discussing strengths and weaknesses?
• Have I cited and discussed studies contrary to my perspective?
• Will the reader find my literature review relevant, appropriate, and useful?

Ask yourself questions like these about each book or article you include:

• Has the author formulated a problem/issue?
• Is it clearly defined? Is its significance (scope, severity, relevance) clearly established?
• Could the problem have been approached more effectively from another perspective?
• What is the author's research orientation (e.g., interpretive, critical science, combination)?
• What is the author's theoretical framework (e.g., psychological, developmental, feminist)?
• What is the relationship between the theoretical and research perspectives?
• Has the author evaluated the literature relevant to the problem/issue? Does the author include literature taking positions she or he does not agree with?
• In a research study, how good are the basic components of the study design (e.g., population, intervention, outcome)? How accurate and valid are the measurements? Is the analysis of the data accurate and relevant to the research question? Are the conclusions validly based upon the data and analysis?
• In material written for a popular readership, does the author use appeals to emotion, one-sided examples, or rhetorically-charged language and tone? Is there an objective basis to the reasoning, or is the author merely "proving" what he or she already believes?
• How does the author structure the argument? Can you "deconstruct" the flow of the argument to see whether or where it breaks down logically (e.g., in establishing cause-effect relationships)?
• In what ways does this book or article contribute to our understanding of the problem under study, and in what ways is it useful for practice? What are the strengths and limitations?
• How does this book or article relate to the specific thesis or question I am developing?

Text written by Dena Taylor, Health Sciences Writing Centre, University of Toronto

http://www.writing.utoronto.ca/advice/specific-types-of-writing/literature-review

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Systematic Reviews

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What Makes a Systematic Review Different from Other Types of Reviews?

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Reproduced from Grant, M. J. and Booth, A. (2009), A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information & Libraries Journal, 26: 91–108. doi:10.1111/j.1471-1842.2009.00848.x

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What is a literature review?

A literature review is an integrated analysis -- not just a summary-- of scholarly writings and other relevant evidence related directly to your research question.  That is, it represents a synthesis of the evidence that provides background information on your topic and shows a association between the evidence and your research question.

A literature review may be a stand alone work or the introduction to a larger research paper, depending on the assignment.  Rely heavily on the guidelines your instructor has given you.

Why is it important?

A literature review is important because it:

• Explains the background of research on a topic.
• Demonstrates why a topic is significant to a subject area.
• Discovers relationships between research studies/ideas.
• Identifies major themes, concepts, and researchers on a topic.
• Identifies critical gaps and points of disagreement.
• Discusses further research questions that logically come out of the previous studies.

APA7 Style resources

APA Style Blog - for those harder to find answers

1. Choose a topic. Define your research question.

Your literature review should be guided by your central research question.  The literature represents background and research developments related to a specific research question, interpreted and analyzed by you in a synthesized way.

• Make sure your research question is not too broad or too narrow.  Is it manageable?
• Begin writing down terms that are related to your question. These will be useful for searches later.
• If you have the opportunity, discuss your topic with your professor and your class mates.

2. Decide on the scope of your review

How many studies do you need to look at? How comprehensive should it be? How many years should it cover? 

• This may depend on your assignment.  How many sources does the assignment require?

3. Select the databases you will use to conduct your searches.

Make a list of the databases you will search. 

Where to find databases:

• use the tabs on this guide
• Find other databases in the Nursing Information Resources web page
• More on the Medical Library web page
• ... and more on the Yale University Library web page

4. Conduct your searches to find the evidence. Keep track of your searches.

• Use the key words in your question, as well as synonyms for those words, as terms in your search. Use the database tutorials for help.
• Save the searches in the databases. This saves time when you want to redo, or modify, the searches. It is also helpful to use as a guide is the searches are not finding any useful results.
• Review the abstracts of research studies carefully. This will save you time.
• Use the bibliographies and references of research studies you find to locate others.
• Check with your professor, or a subject expert in the field, if you are missing any key works in the field.
• Ask your librarian for help at any time.
• Use a citation manager, such as EndNote as the repository for your citations. See the EndNote tutorials for help.

Review the literature

Some questions to help you analyze the research:

• What was the research question of the study you are reviewing? What were the authors trying to discover?
• Was the research funded by a source that could influence the findings?
• What were the research methodologies? Analyze its literature review, the samples and variables used, the results, and the conclusions.
• Does the research seem to be complete? Could it have been conducted more soundly? What further questions does it raise?
• If there are conflicting studies, why do you think that is?
• How are the authors viewed in the field? Has this study been cited? If so, how has it been analyzed?

Tips: 

• Review the abstracts carefully.  
• Keep careful notes so that you may track your thought processes during the research process.
• Create a matrix of the studies for easy analysis, and synthesis, across all of the studies.
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Literature Review

What exactly is a literature review.

• Critical Exploration and Synthesis: It involves a thorough and critical examination of existing research, going beyond simple summaries to synthesize information.
• Reorganizing Key Information: Involves structuring and categorizing the main ideas and findings from various sources.
• Offering Fresh Interpretations: Provides new perspectives or insights into the research topic.
• Merging New and Established Insights: Integrates both recent findings and well-established knowledge in the field.
• Analyzing Intellectual Trajectories: Examines the evolution and debates within a specific field over time.
• Contextualizing Current Research: Places recent research within the broader academic landscape, showing its relevance and relation to existing knowledge.
• Detailed Overview of Sources: Gives a comprehensive summary of relevant books, articles, and other scholarly materials.
• Highlighting Significance: Emphasizes the importance of various research works to the specific topic of study.

How do Literature Reviews Differ from Academic Research Papers?

• Focus on Existing Arguments: Literature reviews summarize and synthesize existing research, unlike research papers that present new arguments.
• Secondary vs. Primary Research: Literature reviews are based on secondary sources, while research papers often include primary research.
• Foundational Element vs. Main Content: In research papers, literature reviews are usually a part of the background, not the main focus.
• Lack of Original Contributions: Literature reviews do not introduce new theories or findings, which is a key component of research papers.

Purpose of Literature Reviews

• Drawing from Diverse Fields: Literature reviews incorporate findings from various fields like health, education, psychology, business, and more.
• Prioritizing High-Quality Studies: They emphasize original, high-quality research for accuracy and objectivity.
• Serving as Comprehensive Guides: Offer quick, in-depth insights for understanding a subject thoroughly.
• Foundational Steps in Research: Act as a crucial first step in conducting new research by summarizing existing knowledge.
• Providing Current Knowledge for Professionals: Keep professionals updated with the latest findings in their fields.
• Demonstrating Academic Expertise: In academia, they showcase the writer’s deep understanding and contribute to the background of research papers.
• Essential for Scholarly Research: A deep understanding of literature is vital for conducting and contextualizing scholarly research.

A Literature Review is Not About:

• Merely Summarizing Sources: It’s not just a compilation of summaries of various research works.
• Ignoring Contradictions: It does not overlook conflicting evidence or viewpoints in the literature.
• Being Unstructured: It’s not a random collection of information without a clear organizing principle.
• Avoiding Critical Analysis: It doesn’t merely present information without critically evaluating its relevance and credibility.
• Focusing Solely on Older Research: It’s not limited to outdated or historical literature, ignoring recent developments.
• Isolating Research: It doesn’t treat each source in isolation but integrates them into a cohesive narrative.

Steps Involved in Conducting a Research Literature Review (Fink, 2019)

1. choose a clear research question., 2. use online databases and other resources to find articles and books relevant to your question..

• Google Scholar
• OSU Library
• ERIC. Index to journal articles on educational research and practice.
• PsycINFO . Citations and abstracts for articles in 1,300 professional journals, conference proceedings, books, reports, and dissertations in psychology and related disciplines.
• PubMed . This search system provides access to the PubMed database of bibliographic information, which is drawn primarily from MEDLINE, which indexes articles from about 3,900 journals in the life sciences (e.g., health, medicine, biology).
• Social Sciences Citation Index . A multidisciplinary database covering the journal literature of the social sciences, indexing more than 1,725 journals across 50 social sciences disciplines.

3. Decide on Search Terms.

• Pick words and phrases based on your research question to find suitable materials
• You can start by finding models for your literature review, and search for existing reviews in your field, using “review” and your keywords. This helps identify themes and organizational methods.
• Narrowing your topic is crucial due to the vast amount of literature available. Focusing on a specific aspect makes it easier to manage the number of sources you need to review, as it’s unlikely you’ll need to cover everything in the field.
• Use AND to retrieve a set of citations in which each citation contains all search terms.
• Use OR to retrieve citations that contain one of the specified terms.
• Use NOT to exclude terms from your search.
• Be careful when using NOT because you may inadvertently eliminate important articles. In Example 3, articles about preschoolers and academic achievement are eliminated, but so are studies that include preschoolers as part of a discussion of academic achievement and all age groups.

4. Filter out articles that don’t meet criteria like language, type, publication date, and funding source.

• Publication language Example. Include only studies in English.
• Journal Example. Include all education journals. Exclude all medical journals.
• Author Example. Include all articles by Andrew Hayes.
• Setting Example. Include all studies that take place in family settings. Exclude all studies that take place in the school setting.
• Participants or subjects Example. Include children that are younger than 6 years old.
• Program/intervention Example. Include all programs that are teacher-led. Exclude all programs that are learner-initiated.
• Research design Example. Include only longitudinal studies. Exclude cross-sectional studies.
• Sampling Example. Include only studies that rely on randomly selected participants.
• Date of publication Example. Include only studies published from January 1, 2010, to December 31, 2023.
• Date of data collection Example. Include only studies that collected data from 2010 through 2023. Exclude studies that do not give dates of data collection.
• Duration of data collection Example. Include only studies that collect data for 12 months or longer.

5. Evaluate the methodological quality of the articles, including research design, sampling, data collection, interventions, data analysis, results, and conclusions.

• Maturation: Changes in individuals due to natural development may impact study results, such as intellectual or emotional growth in long-term studies.
• Selection: The method of choosing and assigning participants to groups can introduce bias; random selection minimizes this.
• History: External historical events occurring simultaneously with the study can bias results, making it hard to isolate the study’s effects.
• Instrumentation: Reliable data collection tools are essential to ensure accurate findings, especially in pretest-posttest designs.
• Statistical Regression: Selection based on extreme initial measures can lead to misleading results due to regression towards the mean.
• Attrition: Loss of participants during a study can bias results if those remaining differ significantly from those who dropped out.
• Reactive Effects of Testing: Pre-intervention measures can sensitize participants to the study’s aims, affecting outcomes.
• Interactive Effects of Selection: Unique combinations of intervention programs and participants can limit the generalizability of findings.
• Reactive Effects of Innovation: Artificial experimental environments can lead to uncharacteristic behavior among participants.
• Multiple-Program Interference: Difficulty in isolating an intervention’s effects due to participants’ involvement in other activities or programs.
• Simple Random Sampling : Every individual has an equal chance of being selected, making this method relatively unbiased.
• Systematic Sampling : Selection is made at regular intervals from a list, such as every sixth name from a list of 3,000 to obtain a sample of 500.
• Stratified Sampling : The population is divided into subgroups, and random samples are then taken from each subgroup.
• Cluster Sampling : Natural groups (like schools or cities) are used as batches for random selection, both at the group and individual levels.
• Convenience Samples : Selection probability is unknown; these samples are easy to obtain but may not be representative unless statistically validated.
• Study Power: The ability of a study to detect an effect, if present, is known as its power. Power analysis helps identify a sample size large enough to detect this effect.
• Test-Retest Reliability: High correlation between scores obtained at different times, indicating consistency over time.
• Equivalence/Alternate-Form Reliability: The degree to which two different assessments measure the same concept at the same difficulty level.
• Homogeneity: The extent to which all items or questions in a measure assess the same skill, characteristic, or quality.
• Interrater Reliability: Degree of agreement among different individuals assessing the same item or concept.
• Content Validity: Measures how thoroughly and appropriately a tool assesses the skills or characteristics it’s supposed to measure. Face Validity: Assesses whether a measure appears effective at first glance in terms of language use and comprehensiveness. Criterion Validity: Includes predictive validity (forecasting future performance) and concurrent validity (agreement with already valid measures). Construct Validity: Experimentally established to show that a measure effectively differentiates between people with and without certain characteristics.
• Relies on factors like the scale (categorical, ordinal, numerical) of independent and dependent variables, the count of these variables, and whether the data’s quality and characteristics align with the chosen statistical method’s assumptions.

6. Use a standard form for data extraction, train reviewers if needed, and ensure quality.

7. interpret the results, using your experience and the literature’s quality and content. for a more detailed analysis, a meta-analysis can be conducted using statistical methods to combine study results., 8. produce a descriptive review or perform a meta-analysis..

• Example: Bryman, A. (2007). Effective leadership in higher education: A literature review. Studies in higher education, 32(6), 693-710.
• Clarify the objectives of the analysis.
• Set explicit criteria for including and excluding studies.
• Describe in detail the methods used to search the literature.
• Search the literature using a standardized protocol for including and excluding studies.
• Use a standardized protocol to collect (“abstract”) data from each study regarding study purposes, methods, and effects (outcomes).
• Describe in detail the statistical method for pooling results.
• Report results, conclusions, and limitations.

• Example: Yu, Z. (2023). A meta-analysis of the effect of virtual reality technology use in education. Interactive Learning Environments, 31 (8), 4956-4976.
• Essential and Multifunctional Bibliographic Software: Tools like EndNote, ProCite, BibTex, Bookeeper, Zotero, and Mendeley offer more than just digital storage for references; they enable saving and sharing search strategies, directly inserting references into reports and scholarly articles, and analyzing references by thematic content.
• Comprehensive Literature Reviews: Involve supplementing electronic searches with a review of references in identified literature, manual searches of references and journals, and consulting experts for both unpublished and published studies and reports.
• One of the most famous reporting checklists is the Consolidated Standards of Reporting Trials ( CONSORT ). CONSORT consists of a checklist and flow diagram. The checklist includes items that need to be addressed in the report.

References:

Bryman, A. (2007). Effective leadership in higher education: A literature review.  Studies in higher education ,  32 (6), 693-710.

Fink, A. (2019).  Conducting research literature reviews: From the internet to paper . Sage publications.

Yu, Z. (2023). A meta-analysis of the effect of virtual reality technology use in education. Interactive Learning Environments, 31 (8), 4956-4976.

How to Operate Literature Review Through Qualitative and Quantitative Analysis Integration?

• Conference paper
• First Online: 05 May 2022
• Cite this conference paper

• Eduardo Amadeu Dutra Moresi   ORCID: orcid.org/0000-0001-6058-3883 13 ,
• Isabel Pinho   ORCID: orcid.org/0000-0003-1714-8979 14 &
• António Pedro Costa   ORCID: orcid.org/0000-0002-4644-5879 14  

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 466))

Included in the following conference series:

• World Conference on Qualitative Research

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Usually, a literature review takes time and becomes a demanding step in any research project. The proposal presented in this article intends to structure this work in an organised and transparent way for all project participants and the structured elaboration of its report. Integrating qualitative and quantitative analysis provides opportunities to carry out a solid, practical, and in-depth literature review. The purpose of this article is to present a guide that explores the potentials of qualitative and quantitative analysis integration to develop a solid and replicable literature review. The paper proposes an integrative approach comprising six steps: 1) research design; 2) Data Collection for bibliometric analysis; 3) Search string refinement; 4) Bibliometric analysis; 5) qualitative analysis; and 6) report and dissemination of research results. These guidelines can facilitate the bibliographic analysis process and relevant article sample selection. Once the sample of publications is defined, it is possible to conduct a deep analysis through Content Analysis. Software tools, such as R Bibliometrix, VOSviewer, Gephi, yEd and webQDA, can be used for practical work during all collection, analysis, and reporting processes. From a large amount of data, selecting a sample of relevant literature is facilitated by interpreting bibliometric results. The specification of the methodology allows the replication and updating of the literature review in an interactive, systematic, and collaborative way giving a more transparent and organised approach to improving the literature review.

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Moresi, E.A.D., Pinho, I., Costa, A.P. (2022). How to Operate Literature Review Through Qualitative and Quantitative Analysis Integration?. In: Costa, A.P., Moreira, A., Sánchez‑Gómez, M.C., Wa-Mbaleka, S. (eds) Computer Supported Qualitative Research. WCQR 2022. Lecture Notes in Networks and Systems, vol 466. Springer, Cham. https://doi.org/10.1007/978-3-031-04680-3_13

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

Lesson 6 - review of related literature

Competency: Selects relevant literature from reputable journals and cites related literature using standard style (APA, MLA, or Chicago Manual of Style), and follows ethical standards in writing related literature and to illustrates and explain conceptual framework.

Review of Related Literature (RRL)

Old definition of RRL

The RRL is the selection aannotation of available documents (both published and unpublished), which contain information, ideas, data and evidence related to the topic that a person proposes to research on.

New definition of RRL

The RRL is the use of ideas in the literature to justify the particular approach to the topic, the selection of methods, and demonstration that this research contributes something new.

The Review of Related Literature (RRL) is an important component of the research process and the research itself.

Two ways of looking at the RRL

Point of view of the:

From the point of view of the researcher:

It helps shape the research as:

Earlier studies help you identify a research problem;

Broaden your knowledge in the research area;

Provides important clues/leads to help you determine the topic of inquiry;

Shows “what is already known” vs. “what needs to be known”;

Provides the foundation and justification for your research problem;

Helps you framing the valid research methodologies, approaches, goals, and research questions for your study; and

Provides clues/leads with regard the theoretical framework and methodological approach .

From the point of view of reader:

It provides the bigger picture:

Shares with the reader the results of other studies that are closely related to the proposed study;

Relates the proposed study to the on-going conversation on the topic;

Provides the reader a benchmark for comparing your study with other studies;

Helps the reader identify and appreciate the value-added information of your study (originality).

Tips in Writing RRL

Write your references in 3x5 index cards in APA style; take note of page numbers, keywords, ideas in each reference so that it is easy to go back to. Group together references from:

journals and periodicals

unpublished researches (dissertation/theses)

What to include in the review?

Consider what materials is to be extracted from a previous study or journal article.

Potential points to be “extracted” for RRL:

* Problem being addressed

* Central topic/purpose or theme of the study

* Briefly state information about the sample, subjects of the study

* Review key results/ conclusions of the study

* Methodology- strengths and/ or flaws

To avoid plagiarism:

* Review the literature, do not reproduce it.

* Refrain from copying verbatim what authors and researchers say.

* Paraphrasing the literature in your own words also helps your analysis of the text.

* Make sure that the source of text or idea is also indicated with your notes.

What is Citation?

Broadly, a citation is a reference to a published or unpublished source (not always the original source).

More precisely, a citation is an abbreviated alphanumeric expression embedded in the body of an intellectual work that denotes an entry in the bibliographic references section of the work for the purpose of acknowledging the relevance of the works of others to the topic of discussion at the spot where the citation appears.

Generally, the combination of both the in-body citation and the bibliographic entry constitutes what is commonly thought of as a citation (whereas bibliographic entries by themselves are not).

References to single, machine-readable assertions in electronic scientific articles are known as nano-publications, a form of micro-attribution. Citation has several important purposes:

to uphold intellectual honesty (or avoiding plagiarism)

to attribute prior or unoriginal work and ideas to the correct sources,

to allow the reader to determine independently whether the referenced material supports the author's argument in the claimed way, and

to help the reader gauge the strength and validity of the material the author has used.

Which referencing style is the right one?

There are literally hundreds of different referencing styles from which to choose when you are citing the sources of your research material.

Different academic disciplines have differing priorities of what is important to the subsequent reader of an academic paper, and different publishing houses have differing rules about the citation sources.

A Few of the Common Referencing Styles and their Origins

1. APA stands for American Psychological Association and comes from the association of the same name.

Although originally drawn up for use in psychological journal, the APA style is now widely used in the social sciences, in education, in business, and numerous other disciplines.

2. MLA comes from the Modern Language Association of America and is used mainly in English and the Humanities.

3. Chicago is sometimes referred to as Turabian or Chicago/Turabian.

It comes from the Chicago Manual of Style and the simplified version of it, A Manual for Writers of Term Papers, Theses, and Dissertations that Kate Turabian wrote.

Chicago is used mainly in the social sciences, including history, political studies, and theology.

4. Vancouver originally came from the International Committee of Medical Journal Editors which produced the Uniform Requirements for Manuscripts Submitted to Biomedical Journals following a meeting that was held in Vancouver in 1978.

The Vancouver style is used mainly in the medical sciences.

5. Harvard came originally from The Bluebook: A Uniform System of Citation published by the Harvard Law Review Association.

The Harvard style and its many variations are used in law, natural sciences, social and behavioral sciences, and medicine.

Why Should be Cited?

1. Citing identifies sources used in a research project

2. It gives credit to those researchers, authors, and writers whose words or ideas you borrow, acknowledging their role in shaping your research

3. It allows others to follow-up on or retrieve this material

4. To avoid charges of plagiarism

What is Plagiarism?

Plagiarism is:

· The unacknowledged use or appropriation of another person’s words or ideas

· A form of cheating or stealing

· A serious academic offense

When we borrow words or ideas from sources to support our argument or research, we must give proper credit. By crediting our sources, we avoid plagiarism.

If we do not cite a source –intentionally or unintentionally we are guilty of plagiarism.

When should be Cited? When in doubt, give credit to source!

· Many students plagiarize unintentionally.

· Remember, whenever we summarize, paraphrase or quote another author’s material, we must properly credit our source.

· If we are using another person’s idea, we must also cite our source.

· In any of these cases, must credit to source.

Citations, Paraphrasing, and References Using APA 7 th Edition

· APA Style uses the author-date citation system, in which a brief in-text citation direct readers to a full reference list entry.

· The in-text citation appears within the body of the paper (or in a table, figure, footnote, or appendix) and briefly identifies the cited work by its author and date of publication.

· This enables readers to locate the corresponding entry in the alphabetical reference lists at the end of the paper.

· Each work cited must appear n the reference list, and each work in the reference list must be cited in the text (or in a table, figure, footnote, or appendix).

· Both paraphrases and quotations (discourage to use) require citations.

Paraphrasing

· Restates another’s idea (or your own previously published idea) in your own words.

· Allows you to summarize and synthesize information from one or more sources, focus on significant information, and compare and contrast relevant details.

· Requires you to cite the original work using either the narrative or parenthetical citation format.

· Are not the same as Works Cited or Bibliography

· Have four elements: the author, date, title, and source.

* Author: who is responsible for this work?

* Date: when was this work published?

* Title: what is this work called?

* Source: where can I retrieve this work?

What is an In-Text Citation?

In-text citations are citations that appear in the body of an essay or paper. In-text citations have two formats - narrative and parenthetical:

Narrative citations : Author last name/s are included in the text as part of the sentence. The publication year and page number (if applicable) follows in parentheses. The author’s last name can be included any place in the sentence where it makes sense.

Parenthetical citations : Author last name/s and publication year and page number (if applicable) appear in parentheses. A parenthetical citation can appear within or at the end of a sentence.

Narrative citations

* In a narrative citation, the author's name appears in the sentence and not in parentheses.

Example: Walters (2003) wrote that most people tend to follow the path of least resistance.

* When the name of the author appears in a sentence, the year of publication, if available, follows it. If the year of publication is not available, n.d. (no date) is used instead.

Example: Johnson and Travers (2016) discussed the causes of this disaster, while Marston (n.d.) focused on the consequences.

* Page numbers must be used inside the parentheses after a direct quote (a direct quote is a word-for-word quote that is placed within quotation marks). If page numbers are not available, other locators are used, such as paragraph numbers

Example: (para. 10). Page or paragraph numbers are not required when paraphrasing.

* Book titles and the titles of other standalone works are formatted in title case and in italics. Example: Little House in the Big Woods.

* Journal article titles and the titles of other parts of works are formatted in title case and in quotation marks. Example: "The Iridescent History of Light."

Parenthetical citations

* A parenthetical citation is one where all the required information is placed in parentheses.

* In APA style, the information in parentheses consists of the last name(s) of the author(s), the year of publication, and page or paragraph number(s) in the case of an exact quote. Examples: (Smith, 2017); (James, Vargas, & Rhodes, n.d.).

If there is no author, then the title of the article is placed in parentheses, followed by the year (or by n.d. if there is no date).

Example: ("The History of the Circus," 1997).

For long titles, a shortened form of the title is used in parentheses. For example , the title "Milk Chocolate Is Better Than Dark, the End," would be shortened in the parentheses to "Milk Chocolate."

In-text citations and the References list

In-text citations (narrative or parenthetical) must parallel the entries on the References list. She the examples below -- parallel elements are in maroon.

APA 7 th Edition Reference Examples

The American Psychological Association (APA) have provided new manual as their 7 th edition. Here are some of the new guidelines to help researcher to properly format the reference list in APA Style:

Begin with the reference list on a new page after the text.

Place the section label “References” in bold at the top of the page, centered.

Order the reference list entries alphabetically by author.

Double-space the entire reference list (both within and between entries).

Apply a hanging indent of 0.5 in. to each reference list entry, meaning that the first line of the reference is flush left and subsequent lines are indented 0.5 in. from the left margin. Use the paragraph-formatting function of your word-processing program to apply the hanging indent.

Link for In-text Citation

Writing an Annotated Bibliography

APA Formatting Cover Page

Introduction to Citation Styles: APA 7th Edition

APA 7th Edition (In-text and Reference Citations)

For more information about the change of the APA format from 6th to 7th edition, click this link: library.carleton.ca/sites/default/files/help/APA%20Notable%20Changes%206th%20to%207th.pdf

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• Knowledge Base

Methodology

• Systematic Review | Definition, Example, & Guide

Systematic Review | Definition, Example & Guide

Published on June 15, 2022 by Shaun Turney . Revised on November 20, 2023.

A systematic review is a type of review that uses repeatable methods to find, select, and synthesize all available evidence. It answers a clearly formulated research question and explicitly states the methods used to arrive at the answer.

They answered the question “What is the effectiveness of probiotics in reducing eczema symptoms and improving quality of life in patients with eczema?”

In this context, a probiotic is a health product that contains live microorganisms and is taken by mouth. Eczema is a common skin condition that causes red, itchy skin.

Table of contents

What is a systematic review, systematic review vs. meta-analysis, systematic review vs. literature review, systematic review vs. scoping review, when to conduct a systematic review, pros and cons of systematic reviews, step-by-step example of a systematic review, other interesting articles, frequently asked questions about systematic reviews.

A review is an overview of the research that’s already been completed on a topic.

What makes a systematic review different from other types of reviews is that the research methods are designed to reduce bias . The methods are repeatable, and the approach is formal and systematic:

• Formulate a research question
• Develop a protocol
• Search for all relevant studies
• Apply the selection criteria
• Extract the data
• Synthesize the data
• Write and publish a report

Although multiple sets of guidelines exist, the Cochrane Handbook for Systematic Reviews is among the most widely used. It provides detailed guidelines on how to complete each step of the systematic review process.

Systematic reviews are most commonly used in medical and public health research, but they can also be found in other disciplines.

Systematic reviews typically answer their research question by synthesizing all available evidence and evaluating the quality of the evidence. Synthesizing means bringing together different information to tell a single, cohesive story. The synthesis can be narrative ( qualitative ), quantitative , or both.

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Systematic reviews often quantitatively synthesize the evidence using a meta-analysis . A meta-analysis is a statistical analysis, not a type of review.

A meta-analysis is a technique to synthesize results from multiple studies. It’s a statistical analysis that combines the results of two or more studies, usually to estimate an effect size .

A literature review is a type of review that uses a less systematic and formal approach than a systematic review. Typically, an expert in a topic will qualitatively summarize and evaluate previous work, without using a formal, explicit method.

Although literature reviews are often less time-consuming and can be insightful or helpful, they have a higher risk of bias and are less transparent than systematic reviews.

Similar to a systematic review, a scoping review is a type of review that tries to minimize bias by using transparent and repeatable methods.

However, a scoping review isn’t a type of systematic review. The most important difference is the goal: rather than answering a specific question, a scoping review explores a topic. The researcher tries to identify the main concepts, theories, and evidence, as well as gaps in the current research.

Sometimes scoping reviews are an exploratory preparation step for a systematic review, and sometimes they are a standalone project.

Prevent plagiarism. Run a free check.

A systematic review is a good choice of review if you want to answer a question about the effectiveness of an intervention , such as a medical treatment.

To conduct a systematic review, you’ll need the following:

• A precise question , usually about the effectiveness of an intervention. The question needs to be about a topic that’s previously been studied by multiple researchers. If there’s no previous research, there’s nothing to review.
• If you’re doing a systematic review on your own (e.g., for a research paper or thesis ), you should take appropriate measures to ensure the validity and reliability of your research.
• Access to databases and journal archives. Often, your educational institution provides you with access.
• Time. A professional systematic review is a time-consuming process: it will take the lead author about six months of full-time work. If you’re a student, you should narrow the scope of your systematic review and stick to a tight schedule.
• Bibliographic, word-processing, spreadsheet, and statistical software . For example, you could use EndNote, Microsoft Word, Excel, and SPSS.

A systematic review has many pros .

• They minimize research bias by considering all available evidence and evaluating each study for bias.
• Their methods are transparent , so they can be scrutinized by others.
• They’re thorough : they summarize all available evidence.
• They can be replicated and updated by others.

Systematic reviews also have a few cons .

• They’re time-consuming .
• They’re narrow in scope : they only answer the precise research question.

The 7 steps for conducting a systematic review are explained with an example.

Step 1: Formulate a research question

Formulating the research question is probably the most important step of a systematic review. A clear research question will:

• Allow you to more effectively communicate your research to other researchers and practitioners
• Guide your decisions as you plan and conduct your systematic review

A good research question for a systematic review has four components, which you can remember with the acronym PICO :

• Population(s) or problem(s)
• Intervention(s)
• Comparison(s)

You can rearrange these four components to write your research question:

• What is the effectiveness of I versus C for O in P ?

Sometimes, you may want to include a fifth component, the type of study design . In this case, the acronym is PICOT .

• Type of study design(s)
• The population of patients with eczema
• The intervention of probiotics
• In comparison to no treatment, placebo , or non-probiotic treatment
• The outcome of changes in participant-, parent-, and doctor-rated symptoms of eczema and quality of life
• Randomized control trials, a type of study design

Their research question was:

• What is the effectiveness of probiotics versus no treatment, a placebo, or a non-probiotic treatment for reducing eczema symptoms and improving quality of life in patients with eczema?

Step 2: Develop a protocol

A protocol is a document that contains your research plan for the systematic review. This is an important step because having a plan allows you to work more efficiently and reduces bias.

Your protocol should include the following components:

• Background information : Provide the context of the research question, including why it’s important.
• Research objective (s) : Rephrase your research question as an objective.
• Selection criteria: State how you’ll decide which studies to include or exclude from your review.
• Search strategy: Discuss your plan for finding studies.
• Analysis: Explain what information you’ll collect from the studies and how you’ll synthesize the data.

If you’re a professional seeking to publish your review, it’s a good idea to bring together an advisory committee . This is a group of about six people who have experience in the topic you’re researching. They can help you make decisions about your protocol.

It’s highly recommended to register your protocol. Registering your protocol means submitting it to a database such as PROSPERO or ClinicalTrials.gov .

Step 3: Search for all relevant studies

Searching for relevant studies is the most time-consuming step of a systematic review.

To reduce bias, it’s important to search for relevant studies very thoroughly. Your strategy will depend on your field and your research question, but sources generally fall into these four categories:

• Databases: Search multiple databases of peer-reviewed literature, such as PubMed or Scopus . Think carefully about how to phrase your search terms and include multiple synonyms of each word. Use Boolean operators if relevant.
• Handsearching: In addition to searching the primary sources using databases, you’ll also need to search manually. One strategy is to scan relevant journals or conference proceedings. Another strategy is to scan the reference lists of relevant studies.
• Gray literature: Gray literature includes documents produced by governments, universities, and other institutions that aren’t published by traditional publishers. Graduate student theses are an important type of gray literature, which you can search using the Networked Digital Library of Theses and Dissertations (NDLTD) . In medicine, clinical trial registries are another important type of gray literature.
• Experts: Contact experts in the field to ask if they have unpublished studies that should be included in your review.

At this stage of your review, you won’t read the articles yet. Simply save any potentially relevant citations using bibliographic software, such as Scribbr’s APA or MLA Generator .

• Databases: EMBASE, PsycINFO, AMED, LILACS, and ISI Web of Science
• Handsearch: Conference proceedings and reference lists of articles
• Gray literature: The Cochrane Library, the metaRegister of Controlled Trials, and the Ongoing Skin Trials Register
• Experts: Authors of unpublished registered trials, pharmaceutical companies, and manufacturers of probiotics

Step 4: Apply the selection criteria

Applying the selection criteria is a three-person job. Two of you will independently read the studies and decide which to include in your review based on the selection criteria you established in your protocol . The third person’s job is to break any ties.

To increase inter-rater reliability , ensure that everyone thoroughly understands the selection criteria before you begin.

If you’re writing a systematic review as a student for an assignment, you might not have a team. In this case, you’ll have to apply the selection criteria on your own; you can mention this as a limitation in your paper’s discussion.

You should apply the selection criteria in two phases:

• Based on the titles and abstracts : Decide whether each article potentially meets the selection criteria based on the information provided in the abstracts.
• Based on the full texts: Download the articles that weren’t excluded during the first phase. If an article isn’t available online or through your library, you may need to contact the authors to ask for a copy. Read the articles and decide which articles meet the selection criteria.

It’s very important to keep a meticulous record of why you included or excluded each article. When the selection process is complete, you can summarize what you did using a PRISMA flow diagram .

Next, Boyle and colleagues found the full texts for each of the remaining studies. Boyle and Tang read through the articles to decide if any more studies needed to be excluded based on the selection criteria.

When Boyle and Tang disagreed about whether a study should be excluded, they discussed it with Varigos until the three researchers came to an agreement.

Step 5: Extract the data

Extracting the data means collecting information from the selected studies in a systematic way. There are two types of information you need to collect from each study:

• Information about the study’s methods and results . The exact information will depend on your research question, but it might include the year, study design , sample size, context, research findings , and conclusions. If any data are missing, you’ll need to contact the study’s authors.
• Your judgment of the quality of the evidence, including risk of bias .

You should collect this information using forms. You can find sample forms in The Registry of Methods and Tools for Evidence-Informed Decision Making and the Grading of Recommendations, Assessment, Development and Evaluations Working Group .

Extracting the data is also a three-person job. Two people should do this step independently, and the third person will resolve any disagreements.

They also collected data about possible sources of bias, such as how the study participants were randomized into the control and treatment groups.

Step 6: Synthesize the data

Synthesizing the data means bringing together the information you collected into a single, cohesive story. There are two main approaches to synthesizing the data:

• Narrative ( qualitative ): Summarize the information in words. You’ll need to discuss the studies and assess their overall quality.
• Quantitative : Use statistical methods to summarize and compare data from different studies. The most common quantitative approach is a meta-analysis , which allows you to combine results from multiple studies into a summary result.

Generally, you should use both approaches together whenever possible. If you don’t have enough data, or the data from different studies aren’t comparable, then you can take just a narrative approach. However, you should justify why a quantitative approach wasn’t possible.

Boyle and colleagues also divided the studies into subgroups, such as studies about babies, children, and adults, and analyzed the effect sizes within each group.

Step 7: Write and publish a report

The purpose of writing a systematic review article is to share the answer to your research question and explain how you arrived at this answer.

Your article should include the following sections:

• Abstract : A summary of the review
• Introduction : Including the rationale and objectives
• Methods : Including the selection criteria, search method, data extraction method, and synthesis method
• Results : Including results of the search and selection process, study characteristics, risk of bias in the studies, and synthesis results
• Discussion : Including interpretation of the results and limitations of the review
• Conclusion : The answer to your research question and implications for practice, policy, or research

To verify that your report includes everything it needs, you can use the PRISMA checklist .

Once your report is written, you can publish it in a systematic review database, such as the Cochrane Database of Systematic Reviews , and/or in a peer-reviewed journal.

In their report, Boyle and colleagues concluded that probiotics cannot be recommended for reducing eczema symptoms or improving quality of life in patients with eczema. Note Generative AI tools like ChatGPT can be useful at various stages of the writing and research process and can help you to write your systematic review. However, we strongly advise against trying to pass AI-generated text off as your own work.

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

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

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

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

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

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

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

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Annual Review of Psychology

Volume 35, 1984, review article, quantitative methods for literature reviews.

• Bert F. Green , and Judith A. Hall
• Vol. 35:37-54 (Volume publication date February 1984) https://doi.org/10.1146/annurev.ps.35.020184.000345
• © Annual Reviews

Quantitative Methods for Literature Reviews, Page 1 of 1

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Quantitative reviewing: the literature review as scientific inquiry

• PMID: 6869492
• DOI: 10.5014/ajot.37.5.313

The literature review process is conceptualized as a form of scientific inquiry that involves methodological requirements and inferences similar to those employed in primary research. Five stages of quantitative reviewing that parallel stages in primary investigation are identified and briefly described. They include problem formation, data collection, data evaluation, analysis and interpretation, and reporting the results. The first two stages provide information and guidelines relevant to reviewers' employing traditional narrative procedures or conducting reviews of qualitative research literature. The final three stages relate specifically to the methodology of quantitative reviewing. The argument is made that quantitative reviewing procedures represent a paradigm shift that can assist researchers and clinicians in occupational therapy to establish a scientific data base that will serve to guide theory development and validate clinical practice.

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• Published: 02 September 2024

Weaving equity into infrastructure resilience research: a decadal review and future directions

• Natalie Coleman 1 ,
• Xiangpeng Li 1 ,
• Tina Comes 2 &
• Ali Mostafavi 1  

npj Natural Hazards volume  1 , Article number:  25 ( 2024 ) Cite this article

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• Natural hazards
• Sustainability

Infrastructure resilience plays an important role in mitigating the negative impacts of natural hazards by ensuring the continued accessibility and availability of resources. Increasingly, equity is recognized as essential for infrastructure resilience. Yet, after about a decade of research on equity in infrastructure resilience, what is missing is a systematic overview of the state of the art and a research agenda across different infrastructures and hazards. To address this gap, this paper presents a systematic review of equity literature on infrastructure resilience in relation to natural hazard events. In our systematic review of 99 studies, we followed an 8-dimensional assessment framework that recognizes 4 equity definitions including distributional-demographic, distributional-spatial, procedural, and capacity equity. Significant findings show that (1) the majority of studies found were located in the US, (2) interest in equity in infrastructure resilience has been exponentially rising, (3) most data collection methods used descriptive and open-data, particularly with none of the non-US studies using human mobility data, (4) limited quantitative studies used non-linear analysis such as agent-based modeling and gravity networks, (5) distributional equity is mostly studied through disruptions in power, water, and transportation caused by flooding and tropical cyclones, and (6) other equity aspects, such as procedural equity, remain understudied. We propose that future research directions could quantify the social costs of infrastructure resilience and advocate a better integration of equity into resilience decision-making. This study fills a critical gap in how equity considerations can be integrated into infrastructure resilience against natural hazards, providing a comprehensive overview of the field and developing future research directions to enhance societal outcomes during and after disasters. As such, this paper is meant to inform and inspire researchers, engineers, and community leaders to understand the equity implications of their work and to embed equity at the heart of infrastructure resilience plans.

Introduction

Infrastructures are the backbones of our societies, connecting people to essential resources and services. At the same time, infrastructure systems such as power, water, and transportation play a pivotal role in determining whether a natural hazard event escalates into a disaster 1 . Driven by the combination of accelerating climate hazards and increasing vulnerability, a 2022 Reuters report indicated that natural hazards caused infrastructure and building losses between $732 and $845 billion dollars internationally 2 . In another report by the World Bank (2019), the direct damage to power and transportation systems had an estimated cost of $18 billion annually 3 . Not only do infrastructure disruptions result in economic losses but they also lead to health issues and a decline in quality of life 4 . Since infrastructure systems secure the accessibility and availability of water, health, and electricity, among other critical services, disruptions of infrastructure exacerbate disasters. For example, the Nepal earthquake (2015) caused the collapse of 262 micro-hydropower plants and 104 hospitals, which further weakened the community’s ability to recover from the hazardous event 5 . Hurricane Maria (2017) in Puerto Rico led to year-long power disruptions which contributed to the 2975 estimated human fatalities 6 . Therefore, infrastructure resilience is becoming increasingly prominent in research, policy, and practice.

The National Infrastructure Advisory Council defined infrastructure resilience as the ability of infrastructure systems, to absorb, adapt, or recover from disruptive events such as natural hazards 7 , 8 . From an engineering viewpoint, infrastructure resilience ensures no significant degradation or loss of system performance in case of a shock (robustness), establishes multiple access channels to infrastructure services (redundancy), effectively mobilizes resources and adapts to new conditions (resourcefulness), and accomplishes these goals in a timely manner (rapidity) 9 . From these origins, infrastructure resilience has evolved to include the complex interactions of technology, policy, social, and governance structures 10 . The United Nations Office for Disaster Risk Reduction discusses the need to use transdisciplinary and systemic methods to guide infrastructure resilience 11 . In their Principles of Resilient Infrastructure report, the principles of infrastructure resilience are to develop understanding and insights (continual learning), prepare for current and future hazards (proactively protected), positively work with the natural environment (environmentally integrated), develop participation across all levels of society (socially engaged), share information and expertise for coordinated benefits (shared responsibility), and address changing needs in infrastructure operations (adaptively transforming) 12 .

Based on the argument of Schlor et al. 13 that “social equity is essential for an urban resilience concept,” we also argue that equity in infrastructure resilience will not only benefit vulnerable populations but also lead to more resilient communities. Equity, in a broad sense, refers to the impartial distribution and just accessibility of resources, opportunities, and outcomes, which strive for fairness regardless of location and social group 14 , 15 . Equity in infrastructure resilience ensures that everyone in the community, regardless of their demographic background, geographic location, level of community status, and internal capabilities, have access to and benefits from infrastructure services. It would also address the limitations of infrastructure resilience, which brings short-term benefits to a specific group of people but ultimately results in long-term disaster impacts 16 . A failure to recognize equity in infrastructure resilience could exacerbate the disaster impact and lock in recovery processes, which in turn, reduces future resilience and leads to a vicious cycle 17 .

Even though infrastructure resilience has important equity impacts, the traditional definition of infrastructure resilience is antithetical to equity. Socially vulnerable populations (such as lower income, minority, indigenous, or rural populations) have traditionally been excluded from the development, maintenance, and planning of infrastructure resilience 18 . For instance, resilience strategies do not conventionally consider the unique needs and vulnerabilities of different communities, leading to inadequate one-size-fits-all solutions 19 . Conventional approaches to restoring infrastructure after hazard events are based on the number of outages, the number of affected customers, and extent of damage within an area, depending on the company preferences, and rarely prioritize the inherent vulnerability of affected individuals and areas 20 . Thereby, those who are most dependent on infrastructure systems may also be most affected by their outages. Several reports, such as National Institute of Standards and Technology 21 , United Nations Office for Project Services 11 , United Nations Office for Disaster Risk Reduction and Coalition for Disaster Resilient Infrastructure 22 , and the Natural Hazards Engineering Research Infrastructure 23 have recognized the importance of considering vulnerable populations in infrastructure resilience.

Furthermore, infrastructure resilience efforts often require significant investment at individual, community, and societal levels 24 . For instance, lower income households may not be able to afford power generators or water tanks to replace system losses 25 , 26 , which means they are more dependent on public infrastructure systems. Wealthier communities may receive more funding and resources for resilience projects due to better political representation and economic importance 27 . Improvements in infrastructure can also lead to gentrification and displacement, as an area perceived with increased safety may raise property values and push out underrepresented residents 28 . Infrastructure resilience may not be properly communicated or usable for all members of the community 29 . Research has also shown an association between vulnerable groups facing more intense losses and longer restoration periods of infrastructure disruptions due to planning biases, inadequate maintenance, and governance structures 18 . Due to the limited tools that translate equity considerations, infrastructure managers, owners, and operators are unlikely to recognize inequities in service provision 20 . Finally, resilience planning can prioritize rapid recovery which may not allow for sufficient time to address the underlying social inequities. This form of resilience planning overlooks the range of systematic disparities evident in infrastructure planning, management, operations, and maintenance in normal times and hazardous conditions 18 .

The field of equity in infrastructure resilience has sparked increasing interest over the last decade. First, researchers have distinguished equal and equitable treatment for infrastructure resilience. As stated by Kim and Sutley 30 , equality creates equivalence at the beginning of a process whereas equity seeks equivalence at the end. Second, the term has been interpreted through other social-economic concepts such as social justice 16 , sustainability 31 , vulnerability 32 , welfare 33 , 34 , and environmental justice 35 . Third, equitable infrastructure is frequently associated with pre-existing inequities such as demographic features 36 , 37 , spatial clusters 38 , 39 , 40 , and political processes 41 . Fourth, studies have proposed frameworks to analyze the relationship of equity in infrastructure resilience 42 , 43 , adapted quantitative and qualitative approaches 44 , 45 , and created decision-making tools for equity in infrastructure resilience 31 , 46 .

Despite a decade of increasing interest in integrating equity into infrastructure resilience, the research gap is to systematically evaluate collective research progress and fundamental knowledge. To address this gap, this paper presents a comprehensive systematic literature review of equity-related literature in the field of infrastructure resilience during natural hazards. The aim is to provide a thorough overview of the current state of art by synthesizing the growing body of literature of equitable thinking and academic research in infrastructure resilience. From there, we aim to identify gaps and establish a research agenda. This review focuses on the intersection of natural hazard events, infrastructure resilience, and equity to answer three overarching research questions. As such, this research is important because it explores the critical but often neglected integration of equity into infrastructure resilience against natural hazards. It provides a comprehensive overview and identifies future research opportunities to improve societal outcomes during and after disasters.

What are the prevailing concepts, foci, methods, and theories in assessing the inequities of infrastructure services in association with natural hazard events?

What are the similarities and differences in studying pathways of equity in infrastructure resilience?

What are the current gaps of knowledge and future challenges of studying equity in infrastructure resilience?

To answer the research questions, the authors reviewed 99 studies and developed an 8-dimensional assessment framework to understand in which contexts and via which methods equity is studied. To differentiate between different equity conceptualizations, the review distinguishes four definitions of equity: distributional-demographic (D), distributional-spatial (S), procedural (P), and capacity (C). In our study, “pathways” explores the formation, examination, and application of equity within an 8-dimensional framework. Following Meerow’s framework of resilience to what and of what? 47 , we then analyze for which infrastructures and hazards equity is studied. Infrastructures include power, water, transportation, communication, health, food, sanitation, stormwater, emergency, and general if a specific infrastructure is not mentioned. Green infrastructure, social infrastructure, building structures, and industrial structures were excluded. The hazards studied include flood, tropical cyclone, drought, earthquake, extreme temperature, pandemic, and general if there is no specific hazard.

The in-depth decadal review aims to bring insights into what aspects are fully known, partially understood, or completely missing in the conversation involving equity, infrastructure resilience, and disasters. The review will advance the academic understanding of equity in infrastructure resilience by highlighting understudied areas, recognizing the newest methodologies, and advising future research directions. Building on fundamental knowledge can influence practical applications. Engineers and utility managers can use these findings to better understand potential gaps in the current approaches and practices that may lead to inequitable outcomes. Community leaders and advocates could also leverage such evidence-based insights for advocacy and bring attention to equity concerns in infrastructure resilience policies and guidelines.

Infrastructure resilience in the broader resilience debate

To establish links across the resilience fields, this section embeds infrastructure resilience into the broader resilience debate including general systems resilience, ecological resilience, social resilience, physical infrastructure resilience, and equity in infrastructure resilience. From the variety of literature in different disciplines, we focus on the definitions of resilience and draw out the applicability to infrastructure systems.

Resilience has initially been explored in ecological systems. Holling 48 defines resilience as the ability of ecosystems to absorb changes and maintain their core functionality. This perspective recognizes that ecosystems do not necessarily return to a single equilibrium state, but can exist in multiple steady states, each with distinct thresholds and tipping points. Building on these concepts, Carpenter et al. 49 assesses the capacity of socioecological systems to withstand disturbances without transitioning to alternative states. The research compares resilience properties in lake districts and rangelands such as the dependence on slow-changing variables, self-organization capabilities, and adaptive capacity. These concepts enrich our understanding of infrastructure resilience by acknowledging the complex interdependencies between natural and built systems. It also points out the different temporal rhythms across fast-paced behavioral and slow-paced ecological and infrastructural change 50 .

Social resilience brings the human and behavioral dimension to the foreground. Aldrich and Meyer focuses on the concept of social capital in defining community resilience by emphasizing the role of social networks and relationships to enhance a community’s ability to withstand and recover from disasters 51 . Aldrich and Meyer argues that social infrastructure is as important as physical infrastructure in disaster resilience. Particularly, the depth and quality of social networks can provide crucial support in times of crisis, facilitate information sharing, expedite resource allocation, and coordinate recovery efforts. Resilience, in this context, is defined as the enhancement and utilization of its social infrastructure through social capital. It revolves around the collective capacity of communities to manage stressors and return to normalcy post-disaster through cooperative efforts.

Since community resilience relies on collaborative networks, which in turn are driven by accessibility, community and social resilience are intricately linked to functioning infrastructures 52 . To understand the relationships, we first examine the systems of systems approach thinking. Vitae Systems of Systems aims to holistically resolve complex environmental and societal challenges 53 . It emphasizes strategic, adaptive, and interconnected solutions crucial for long-term system resilience. Individual systems, each with their capabilities and purposes, are connected in ways such that they can achieve together what they cannot achieve alone. Additionally, Okada 54 also shows how the Vitae Systems of Systems can detect fundamental areas of concern and hotspots of vulnerability. It highlights principles of survivability (live through), vitality (live lively), and conviviality (live together) to build system capacity in the overall community. In the context of infrastructure resilience, these approaches bring context to the development of systems and their interdependencies, rather than focusing on the resilience of individual components in isolation.

Expanding on the notion of social and community resilience, Hay’s applies key concepts of being adaptable and capable of maintaining critical functionalities during disruptions to infrastructure 55 . This perspective introduces the concept of “safe-to-fail” systems, which suggests that planning for resilience should anticipate and accommodate the potential for system failures in a way that minimizes overall disruption and aids quick recovery.

As such, the literature agrees that social, infrastructural, and environmental systems handle unexpected disturbances and continue to provide essential services. While Aldrich’s contribution lies in underscoring the importance of social ties and community networks, Hay expands this into the realm of physical systems by considering access to facilities. Infrastructure systems traditionally adapt and change slowly, driven by rigid physical structures, high construction costs, and planning regulations. In contrast, behavioral patterns are relatively fast-changing, even though close social connections and trust also take time to build. Yet, infrastructures form the backbone that enables—or disrupts—social ties. By adopting resilience principles that enable adaptation across infrastructure and social systems, better preparedness, response, and recovery can be achieved.

Given the dynamic, complex nature of resilience, infrastructure resilience, by extension, should not just be considered through the effective engineering of the built environment. Rather, infrastructure resilience must be considered as an integral part of the multi-layered resilience landscape. Crucial questions that link infrastructure to the broader resilience debate include: How will it be used and by whom? How are infrastructure resilience decisions taken, and whose voices are prioritized? These critical questions necessitate the integration of equity perspectives into the infrastructure resilience discourse.

Equity in infrastructure resilience ensures all community members have equitable access to essential services and infrastructure. In her commentary paper, Cutter 56 examines disaster resilience and vulnerability, challenging the prevalent ambiguity in the definitions of resilience. The paper poses two fundamental questions of “resilience to what?” and “resilience to whom?” . Later, Meerow and Newell 47 expanded on these questions in the context of urban resilience, “for whom, what, where, and why?” . They also stress the need for “resilience politics,” which include understanding of how power dynamics shape resilience policies, creating winners and losers 47 .

In a nutshell, resilience strategies must proactively address systemic inequities. This can also be framed around the concept of Rawls’ Theory of Justice principles, such as equal basic rights and fair equality of opportunity 57 , 58 . Rawls advocates for structuring social and economic inequalities to benefit the least advantaged members of society. In the context of infrastructure resilience, the theory would ensure vulnerable communities, such as lower-income households, have priority in infrastructure restoration. Incorporating Walker’s Theory of Abundant Access, this could also mean prioritizing those most dependent on public transit. Access to public transit, especially in lower-income brackets, allows for greater freedom of movement and connection to other essential facilities in the community like water, food, and health 59 , 60 . At the same time, Casali et al. 61 show that access to infrastructures alone is not sufficient for urban resilience to emerge. Such perspectives integrate physical and social elements of a community to equitably distribute infrastructure resilience benefits. Table 1 summarizes the selected definitions of resilience.

Definitions of equity

Equity in infrastructure resilience ensures that individuals have the same opportunity and access to infrastructure services regardless of differing demographics, spatial regions, involvement in the community, and internal capacity. Equity is a multifaceted concept that requires precise definitions to thoroughly assess and address it within the scope of infrastructure resilience. Based on the literature, our systematic literature review proposes four definitions of equity for infrastructure resilience: distributional-demographic (D), distributional-spatial (S), procedural (P), and capacity (C). Distributional-demographic (D) equity represents accessibility to and functionality of infrastructure services considering the vulnerability of demographic groups 62 . Distributional-spatial (S) equity focuses on the equitable distribution of infrastructure services to all spatial regions 63 . Procedural (P) equity refers to inclusive participation and transparent planning with stakeholders and community members 31 . Capacity equity (C) connect the supporting infrastructure to the hierarchy of needs which recognizes the specific capacities of households 64 .

Distributional-demographic (D) addresses the systemic inequities in communities to ensure those of differing demographic status have equitable access to infrastructure services 37 . The purpose is to equitably distribute the burdens and benefits of services by reducing disparity for the most disadvantaged populations 42 . These groups may need greater support due to greater hardship to infrastructure losses, greater dependency on essential services, and disproportionate losses to infrastructure 43 , 65 , 66 . In addition, they may have differing abilities and need to mitigate service losses 33 . Our research bases distributional-demographic on age for young children and elderly, employment, education, ethnicity, people with disabilities, gender, income, tenure of residence, marginalized populations based on additional demographic characteristics, intergenerational, and general-social inequities 67 .

Distributional-spatial (S) recognizes that the operation and optimizations of the systems may leave certain areas in isolation 68 , 69 , 70 . For example, an equitable access to essential services (EAE) approach to spatial planning can identify these service deserts 46 . Urban and rural dynamics may also influence infrastructure inequities. Rural areas have deficient funding sources compared to urban areas 17 while urban areas may have greater vulnerability due to the interconnectedness of systems 71 . Our research labels distributional-spatial as spatial and urban-rural. Spatial involves spatial areas of extreme vulnerability through spatial regression models, spatial inequity hotspots, and specific mentions of vulnerable areas. Urban-rural references the struggles of urban-rural areas.

Procedural (P) equity ensures the inclusion of everyone in the decision-making process from the collection of data to the influence of policies. According to Rivera 72 , inequities in the disaster recovery and reconstruction process originate from procedural vulnerabilities associated with historical and ongoing power relations. The validity of local cultural identities is often overlooked in the participation process of designing infrastructure 73 . Governments and institutions may have excluded certain groups from the conversation to understand, plan, manage, and diminish risk in infrastructure 74 . As argued by Liévanos and Horne 20 , such utilitarian bureaucratic decision rules can limit the recognition of unequal services and the development of corrective actions. These biases can be present in governmental policies, maintenance orders, building codes, and distribution of funding 30 . Our research labels procedural equity as stakeholder input and stakeholder engagement. Stakeholder input goes beyond collecting responses from interviews and surveys. Rather, researchers will ask for specific feedback and validation on final research deliverables like models, results, and spatial maps, but they are not included in the research planning process. Stakeholder engagement are instances where participants took an active role in the research deliverables to change elements of their community.

Capacity (C) equity is the ability of individuals, groups, and communities to counteract or mitigate the effect of infrastructure loss. As mentioned by Parsons, et al. 75 , equity can be enhanced through a network of adaptive capacities at the household or community level. These adaptive capacities are viewed as an integral part of community resilience 76 . Regarding infrastructure, households can prepare for infrastructure losses and have service substitutes such as power generators or water storage tanks 77 , 78 . It may also include the household’s ability to tolerate disruptions and the ability to perceive risk to infrastructure losses 66 . However, capacity can be limited by people’s social connections, social standing, and access to financial resources and personal capital 79 . Our research categorizes capacity equity as adaptations, access, and susceptibility. Adaptations include preparedness strategies before a disaster as well as coping strategies during and after the disaster. Access includes a quantifiable metric in reaching critical resources which may include but is not limited to vehicles, public transportation, or walking. Susceptibility involves a household internal household capability such as tolerance, suffering, unhappiness, and willingness-to-pay models. Although an important aspect of capability, the research did not include social capital since it is outside the scope of research.

Methods of systematic literature review

Our systematic literature review used the Covidence software 80 , which is a production tool to make the process of conducting systematic reviews more efficient and streamlined 80 . As a web-based platform, it supports the collaborative management of uploaded journal references and processes journals through 4-step screening and analysis including title and abstract screening, full-text screening, data abstraction, and quality assessment. The software also follows the guidelines of PRIMSA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis), which provides a clear, transparent way for researchers to document their findings 81 . PRIMSA includes a 27-item checklist and 4-phase flow diagram of identification, screening, eligibility, and inclusion. Figure 1 summarizes the PRIMSA method we followed during our review process by showing the search criteria and final selected articles at each stage, including identification, screening, eligibility, and inclusion.

The figure shows the 4-step screening process of identification, screening, eligibility, and inclusion as well as the specific search criteria for each step. From the initial 2991 articles, 99 articles were selected.

Identification

The search covered Web of Science and Science Direct due to their comprehensive coverage and interdisciplinary sources. To cover a broad set of possible disasters and infrastructures, our search focused on the key areas of equity (“equit- OR fair- OR justice- OR and access-“), infrastructure (“AND infrastructure system- OR service-”), and disasters (“ AND hazard- OR, cris- OR, disaster- OR”). We limited our search to journal articles published in engineering, social sciences, and interdisciplinary journals during January 2010 to March 2023. Excluding duplicates, the combined results of the search engines resulted in 2991 articles.

The articles were screened on their title and abstract. These had to explicitly mention both an infrastructure system (water, transportation, communication, etc.) and natural hazards (tropical cyclone, earthquake, etc.) The specific criteria for infrastructure and natural hazard is found in the 8-dimension framework. This initial screening process yielded 398 articles for full-text review.

Eligibility

The articles were examined based on the extent of discussion in infrastructure, natural hazard, and equity dimension. Insufficient equity discussion means that the paper did not fall within the distributional-demographic, distributional-spatial, procedural, or capacity forms of equity (98). Studies were also excluded for not directly including equity analysis in the infrastructure system (19). Limited infrastructure focus means that the article may have focused on infrastructure outside the scope of the manuscript such as industrial, green, building, or social infrastructure (74). Limited disaster focus means that the article did not connect to the direct or indirect impacts of disasters on infrastructure systems (45). Wrong study design included literature reviews, opinion pieces, policy papers, and unable to access (56). This stage yielded 99 final articles.

Inclusion and assessment framework

To analyze the 99 articles, we designed an 8-dimensional assessment framework (see Fig. 2 ) to analyze the literature. In Fig. 2 , the visualization focuses on equity, infrastructure, and natural hazards since these are the 3 main dimensions of the systematic literature review. The icons on the bottom are the remaining 5 dimensions which add more analysis and context to the first 3 dimensions. Here, we refer to research question 1: what are the prevailing concepts, foci, methods, and theories, in assessing the inequities of disrupted infrastructure services? The framework distinguished the concepts (equity dimensions, infrastructure system, and natural hazard event), foci (geographical scale, geographic location, temporal scale), methods (nature of study and data collection), and theories (theoretical perspective) (Fig. 2 ). The following details each subquestion:

Equity dimensions, infrastructure type, and hazard event type are the main 3 dimensions while geographical location, geographic scale, temporal, nature of the study, and theoretical perspectives are the remaining 5 dimensions which add more information and context.

How is equity conceptualized and measured? First, we label equity into 4 definitions (DPSC). Second, it summarizes the equity conclusions.

Infrastructure type

Which infrastructure services were most and least commonly studied? This category is divided into power, water, transportation, communication, health, food, sanitation, stormwater, emergency, and general if a specific infrastructure is not mentioned. Studies can include more than one infrastructure service. Green infrastructure, social infrastructure, building structures, and industrial structures were excluded.

Hazard event type

Which hazard events are most or least frequently studied? This category includes flood, tropical cyclone, drought, earthquake, extreme temperature, pandemic, and general if there is no specific hazard. To clarify, tropical cyclones include hurricanes and typhoons while extreme temperatures are coldwaves and heatwaves. It determines which studies are specific to hazards and which can be applied to universal events.

Geographic location

Which countries have studied equity the most and least? This category is at the country scale such as the United States, Netherlands, China, and Australia, among others.

Geographic scale

What geographic unit of scale has been studied to represent equity? Smaller scales of study can reveal greater insights at the household level while larger scales of study can reveal comparative differences between regional communities. It ranges from individual, local, regional, and country as well as project. To clarify, ‘individual’ can include survey respondents, households, and stakeholder experts; ‘local’ is census block groups, census tracts, and ZIP codes equivalent scales; ‘regional’ is counties, municipalities, and cities equivalent; ‘project’ refers to studies that focused on specific infrastructure/ construction projects.

Temporal scale

When did themes and priority of equity first emerge? This category determines when equity in infrastructure research is published and whether these trends are increasing, decreasing, or constant.

Nature of the study

How is data for equity being collected and processed? This category analyzed data types used including conceptual, descriptive, open-data, location-intelligence, and simulation data. To clarify, conceptual refers to purely conceptual frameworks or hypothetical datasets; descriptive refers to surveys, questionnaires, interviews, or field observations performed by the researcher; open-data refers to any open-data source that is easily and freely attainable such as census and flood data; location-intelligence refers to social media, human mobility, satellite and aerial images, visit data, and GIS layers; and finally, simulation data can be developed through simulation models like numerical software, Monte-Carlo, or percolation methods. Second, the data can be processed through quantitative or qualitative methods. Quantitative methods may include correlation, principal component analysis, and spatial regression while qualitative methods may include validation, thematic coding, participatory rural appraisal, and citizen science. We focused on analysis explicitly mentioned in the manuscript. For example, it can be assumed that studies of linear regression discussed correlation analysis and other descriptive statistics in their data processing.

Theoretical perspective

Which theoretical frameworks have been created and used to evaluate equity? This category summarizes the reasoning behind the theoretical frameworks which may have informal or formal names such as a service-gap model, well-being approach, and capability approach.

Based on the 8-dimensional assessment framework, the research first examines the spatiotemporal patterns as well as data and methods to evaluate equity. Then, it investigates the definitions of equity to the intersections with infrastructure and hazards. It concludes with a discussion of theoretical frameworks. We use the term “pathways” to identify how equity is constructed, analyzed, and used in relation to the 8-dimensional framework. For instance, the connection between equity and infrastructure is considered a pathway. By defining specific “pathways,” we are essentially mapping out the routes through which equity interacts with various dimensions of a framework, such as infrastructure. The following analysis directly addresses research question 1 (prevailing concepts, focuses, methods, and theories, in assessing the inequities of disrupted infrastructure services) and research question 2 (similar and different pathways of equity). Supplementary Figures 1A – 12A provide additional context to the research findings and can be found in the Supplementary Information .

Spatiotemporal patterns of equity

Overall, there is an increasing number of publications about equity in infrastructure management (Fig. 3 ). A slight decrease observed in 2021 could be because of the focus on COVID-19 research. Spatially, by far the most studies focus on the US (69), followed by India (3), Ghana (3), and Bangladesh (3) (Fig. 5 ). This surprising distribution seems to contradict the intuition that equity and fairness in infrastructure resilience are certainly global phenonmena. Besides the exact phrasing of the search term, this result can be explained by the focus of this review on the intersection of infrastructure resilience and inequity. For infrastructure resilience, prominent reports, such as the CDRI’s 2023 Global Infrastructure Resilience Report 82 still fail to address it. Even though research has called for increasing consideration of equity and distributive justice in infrastructure and risk assessment, inequity is still all too often viewed as a social and economic risk 83 . At the same time, persistent imbalances in terms of data availability have been shown to shift research interest to the US, especially for data intense studies on urban infrastructures 84 . Finally, efforts to mainstream of equity and fairness across all infrastructures as a part of major transitions may explain why equity discussion is less pronounced in the context of crises. For instance, in Europe, according to the EU climate act (Article 9(1)) 85 , all sectors need to be enabled and empowered to make the transition to a climate-resilient society fair and equitable .

The bar graph shows an overall increasing from 2011 to 2023 in publications about equity in infrastructure resilience during natural hazard events. The pie chart shows that countries in the global north with United States (US), England, Australia, Germany, Taiwan, Norway, South Korea, and Japan and global south with Bangladesh, India, Ghana, Mexico, Mozambique, Brazil, Tanzania, Sri Lanka, Pakistan, Nigeria, Kenya, Nepal, Zimbabwe, Central Asia, and South Africa.

Data and methods to interpret equity

Our Sankey diagram (Fig. 4 ) sketches the distribution of data collection pathways which connects quantitative-qualitative data to data type to scale. Most studies start from quantitative data (120) with fewer using mixed (34) or qualitative (18) data. Quantitative studies use descriptive (58), open-data (50) location-intelligence (36), simulation (19), and conceptual (9). The most prominent spatial scale was local (66) which consisted of census tract, census block group, zip code, and equivalent spatial scale of analysis. This was followed by individual or household scale (64) which largely stems from descriptive data of interviews, surveys, and field observations. Within the context of infrastructure, equity, and hazards, non-US studies did not use human mobility data, a specific type of location-intelligence data. This could be due to limitations in data availability and different security restrictions to these researchers such as the European Union’s General Data Protection Regulation 86 . Increasingly, the application of location-intelligence data was used to supplement the understanding of service disruptions. For example, satellite information 87 , telemetry-based data 37 , and human mobility data 88 were used to evaluate the equitable restoration of power systems and access to critical facilities. Social media quantified public emotions to disruptions 89 , 90 .

The Sankey diagram shows the flow from studies containing quantitative, qualitative, or quantitative–qualitative data to the specific type of data of descriptive, open-data, location-intelligence, simulation, and conceptual to spatial scale of data of local, individual, regional, country, and project.

As shown in Fig. 5 , there are distinct quantitative and qualitative methods to interpret equity. Most quantitative methods were focused on descriptive analysis and linear models which can assume simple relationships within equity dimensions. Simple relationships would assume that dependent variables have a straightforward relationship with independent variables. Regarding quantitative analysis, descriptive statistics were correlation (12), chi-square (6), and analysis of variance (ANOVA) (5) means. Spatial analysis included geographic information system (GIS) (15), Moran’s-I spatial autocorrelation (6), and spatial-regression (5). Variables were also grouped together through principal component analysis (PCA) (9) and Index-Weighting (9). Logit models (13) and Monte-Carlo simulations (7) were used to analyze data. Thus, more complex models are needed to uncover the underlying mechanisms associated with equity in infrastructure. In analyzing quantitative data, most research has focused on using descriptive statistics, linear models, and Moran’s I statistic which have been effective in pinpointing areas with heightened physical and social vulnerability 25 , 91 , 92 .

The quantitative pie chart has geographic information system (GIS), logit model, correlation, index-weighting, principal component analysis (PCA), monte-carlo simulation, chi-square, Moran’s- I spatial autocorrelation, analysis of variance (ANOVA), and spatial regression. The qualitative pie chart has validation, thematic coding, citizen science, sentiment analysis, conceptual analysis, participatory rural appraisal, document analysis, participatory assessment, photovoice, and ethnographic.

However, there has been a less frequent yet insightful use of advanced techniques like machine learning, agent-based modeling, and simulation. For example, Esmalian, et al. 66 employed agent-based modeling to explore how social demographic characteristics impact responses to power outages during Hurricane Harvey. In a similar vein, Baeza, et al. 93 utilized agent-based modeling to evaluate the trade-offs among three distinct infrastructure investment policies: prioritizing high-social-pressure neighborhoods, creating new access in under-served areas, and refurbishing aged infrastructure. Simulation models have been instrumental in understanding access to critical services like water 43 , health care 92 , and transportation 33 . Beyond these practical models, conceptual studies have also contributed innovative methods. Notably, Clark, et al. 94 proposed gravity-weighted models, and Kim and Sutley 30 explored the use of genetic algorithms to measure the accessibility to critical resources. These diverse methodologies indicate a growing sophistication in the field, embracing a range of analytical tools to address the complexities of infrastructure resilience.

Regarding qualitative analysis, the methods included thematic coding (7), validation of stakeholders (9), sentiment (4), citizen science (5), conceptual analysis (3) participatory rural appraisal (2), document analysis (2), participatory assessment (1), photovoice (1), and ethnographic (1). Qualitative methods were used to capture diverse angles of equity, offering a depth and context not provided by quantitative data alone. These methods are effective in understanding capacity equity, such as unexpected strategies and coping mechanisms that would go otherwise unnoticed 95 . Qualitative research can also capture the perspectives and voices of stakeholders through procedural equity. Interviews and focus groups can validate and enhance research frameworks 96 . Working collaboratively with stakeholders, as shown with Masterson et al. 97 can lead to positive community changes in updated planning policies. Qualitative methods can narratively convey the personal hardships of infrastructure losses 98 . This approach recognizes that infrastructure issues are not just technical problems but also deeply intertwined with social, economic, and cultural dimensions.

Interlinkages of equity definitions

As shown in Fig. 6 , the frequency of type of equity was distributional-demographic (90), distributional-spatial (55), capacity (54), and procedural (16). It is notable to reflect on the intersections between the four definitions of equity. Between two linkages, the top three linkages between DC (20), DS (16), and DP (9), which all revealed a connection to distributional-demographic equity. There were comparatively fewer studies linking 3 dimensions except for DSC which had 25 connections. Only 3 studies had 4 connections.

Distributional-demographic had the highest number of studies and the greatest overlap with the remaining equity definitions of capacity, procedural, and distributional-spatial. Only 3 studies overlapped with the four equity definitions.

Distributional-demographic equity was the most studied equity definition. Table 2 shows how pathways of demographic equity relate to the different infrastructure systems and variables within distributional-demographic, including 728 unique pathways. As a reminder, pathways explore equity across an 8-dimensional framework. In this case, the distributional-demographic equity is connected to infrastructure, treating these connections as pathways Pathways with power (165), water (147), and transportation (112) were the most frequent while those with stormwater (23) and emergency (9) services were the least frequent. Referencing demographics, the most pathways were income (148), ethnicity (115), and age (122) while least studied were gender (63), employment (35), marginalized populations (5) and intergenerational (1). Note the abbreviations for Tables 2 and 3 are power (P), water (W), transportation (T), food (F), health (H), sanitation (ST), communication (C), stormwater (SW), emergency (E), and general (G). Regarding distributional-demographic, several research papers showed that lower income and minority households were most studied in comparison to the other demographic variables. Lower-income and minority households faced greater exposure, more hardship, and less tolerance to withstand power, water, transportation, and communication outages during Hurricane Harvey 99 . These findings were replicated in disasters such as Hurricane Florence, Hurricane Michael, COVID-19 pandemic, Winter Storm Uri, and Hurricane Hermine, respectively 65 , 91 , 100 , 101 . Several studies found that demographic vulnerabilities are interconnected and compounding, and often, distributional-demographic equity is a pre-existing inequality condition that is exacerbated by disaster impact 102 . For instance, Stough, et al. 98 identified that respondents with disabilities faced increased struggles due to a lack of resources to access proper healthcare and transportation after Hurricane Katrina. Women were often overburdened by infrastructure loss as they were expected to “pick up the pieces,” and substitute the missing service 103 , 104 . Fewer studies involved indigenous populations, young children, or considered future generations. Using citizen-science methods, Ahmed, et al. 105 studied the struggles and coping strategies of the Santal indigenous group to respond to water losses in drought conditions. Studies normally did not account for the direct infrastructure losses on children and instead concentrated on the impacts on their caretakers 106 ; however, this is likely due to restrictions surrounding research with children. Lee and Ellingwood 107 discussed how, “intergenerational discounting makes it possible to allocate costs and benefits more equitably between the current and future generations” (pg.51) A slight difference in discounting rate can lead to vastly different consequences and benefits for future generations. For example, the study found that insufficient investments in design and planning will only increase the cost and burden of infrastructure maintenance and replacement.

Distributional-spatial equity was the second most studied aspect, which includes spatial grouping and urban-rural designation, particularly given the rise of open-data and location-intelligence data with spatial information. Table 3 shows the pathways of spatial equity connected to different infrastructures and variables. In total, 109 unique pathways were found with spatial (83) and urban-rural (26) characteristics. Power (27), transportation (22), water (16), and health (15) systems were the most frequent pathways with stormwater (4), emergency (2), and communication (3) the least frequent. Urban-rural studies on communication and emergency services are entirely missing. Distributional-spatial equity studies, including spatial inequities and urban-rural dynamics, were often linked with distributional-demographic equity. For example, Logan and Guikema 46 defined “access rich” and “access poor” to measure different sociodemographic populations’ access to essential facilities. White populations had less distance to travel to open supermarkets and service stations in North Carolina 46 . Esmalian et al. 108 found that higher income areas had a lower number of stores in their areas, but they still had better access to grocery stores in Harris County, Texas. This could be because higher income areas live in residential areas, but they have the capability to travel further distances and visit more stores. Vulnerable communities could even be indirectly impacted by spatial spillover effects from neighboring areas 26 . Regarding urban-rural struggles, Pandey et al. 17 argued that inequities emerge when urban infrastructure growth lags with respect to the urban population while rural areas face infrastructure deficits. Rural municipalities had fewer resources, longer restoration times, and less institutional support to mitigate infrastructure losses 95 , 109 , 110 .

Capacity was the third most studied dimension and had 150 unique pathways to adaptations (54), access (43), and susceptibility (53). In connecting to infrastructure systems, power (29), water (27), transportation (25), and food (22) had the greatest number of pathways. There were interesting connections between different infrastructures and variables of capacity. Access was most connected to food (11), transportation (10), and health systems (10). Adaptations were most connected to water (15) and power (12) systems. This highlights how capacity equity is reflected differently to infrastructure losses. Capacity equity was often connected with distributional-equity since different sociodemographic groups have varying adaptations to infrastructure losses 78 . For example, Chakalian, et al. 106 found that white respondents were 2.5 more likely to own a power generator while Kohlitz et al. 95 found that poorer households could not afford rainwater harvesting systems. These behaviors may also include tolerating infrastructure disruptions 111 , cutting back on current resources 112 , or having an increased suffering 113 . The capabilities approach offers a valuable perspective on access to infrastructure services 94 . It recognizes the additional time and financial resources that certain groups may need to access the same level of services, especially if travel networks are disrupted 114 , 115 and travel time is extended 33 . In rural regions, women, children, and lower income households often reported traveling further distances for resources 105 , 116 . These disparities are often influenced by socioeconomic factors, emphasizing the need for a nuanced understanding on how different communities are affected by and respond to infrastructure losses. As such, building capacity is not just increasing the preparedness of households but also accommodating infrastructure systems to ensure equitable access, such as the optimization of facility locations 69 .

Procedural was the least studied equity definition with only 26 unique pathways, involving stakeholder input and stakeholder engagement. Pathways to communication and emergency systems were not available. The greatest number of pathways were water services to stakeholder input (7) and stormwater services to stakeholder engagement (4). Stakeholder input can assist researchers in validating and improving their research deliverables. This approach democratizes the decision-making process and enhances the quality and relevance of research and planning outcomes. For instance, the involvement of local experts and residents in Tanzania through a Delphi process led to the development of a more accurate and locally relevant social resilience measurement tool 117 . Stakeholder engagement, such as citizen science methods, can incorporate environmental justice communities into the planning process, educate engineers and scientists, and collect reliable data which can be actively incorporated back to the community 118 , 119 , 120 . Such participatory approaches, including citizen science, allow for a deeper understanding of community needs and challenges. In Houston, TX, the success of engaging high school students in assessing drainage infrastructure exemplified how community involvement can yield significant, practical data 119 . The data was approximately 74% accurate to trained inspectors, which were promising results for communities assessing their infrastructure resilience 119 . In a blend of research and practice, Masterson, et al. 97 illustrated the practical application of procedural equity. By interweaving equity in their policy planning, Rockport, TX planners added accessible services and upgrades to infrastructure for lower-income and racial-ethnic minority neighborhoods, directly benefiting underserved communities.

Pathways between equity, hazard, and infrastructure

For the hazards, tropical cyclones (34.6%) and floods (30.8%) make up over half of the studied hazards (Supplementary Figure 2A ) while power (21.2%), water (19.2%), transportation (15.4%), and health (12.0%) were the most frequently studied infrastructure services (Supplementary Figure 3A ). A pathway is used to connect equity to different dimensions of the framework, in this case, equity to infrastructure to hazard (Fig. 7 ). When considering these pathways, distributional-demographic (270) had the most pathways followed by capacity (175), distributional-spatial (140), and procedural (28). The most common pathway across all infrastructure services was a tropical cyclone and flooding with distributional-demographic equity (Supplementary Figures 6A – 8A ). As shown in Fig. 7 , tropical cyclone (229) and flood (192) had the most pathways while extreme temperatures (20) and pandemic (14) had the least. Although pandemic is seemingly the least studied, it is important to note that most of these studies were post COVID-19. Power (120), transportation (107), and water (104) had the most pathways whereas sanitation (33), communication (27), stormwater (21), and emergency (14) had the least pathways. The figure shows specific gaps in the literature. Whereas the other three equity definitions had connections to each hazard event, procedural equity only had connections to tropical cyclone, flood, general, and drought. There were only pathways from health infrastructure to tropical cyclone, flood, general, earthquake, and pandemic. There were 106 pathways connecting equity to general hazards, which may suggest the need to look at the impacts of specific hazards to equity in infrastructure resilience.

The Sankey diagram shows the flow from the different types of equity, or equity definitions, of distributional-demographic (D), capacity (C), distributional-spatial (S), and procedural (P) to hazard of tropical cyclone, flood, general, drought, earthquake, extreme temperature, and pandemic to infrastructure of power, transportation, water, health, food, communication, general, stormwater, emergency, and sanitation.

Research frameworks

Regarding research question 2, this research aims to understand frameworks of equity in infrastructure resilience. As an exploration of the frameworks. we found common focus areas of adaptations, access, vulnerability, validation, and welfare economics (Table 4 ). The full list of frameworks can be found in the online database that was uploaded in DesignSafe Data Depot. Supplementary Information .

Adaptations

Household adaptations included the ability to prepare before a disaster as well as coping strategies during and after the disaster. Esmalian et al. 111 developed a service gap model based on survey data of residents affected by Hurricane Harvey. Lower-income households were less likely to own power generators, which could lead to an inability to withstand power outages 111 . To understand household adaptations, Abbou et al. 78 asked residents of Los Angeles, California about their experiences in electrical and water losses. The study showed that when compared to men, women used more candles and flashlights. People with higher education, regardless of gender, were more likely to use power generators. In a Pressure and Release model, Daramola et al. 112 examined the level of preparedness to natural hazards in Nigeria. The study found that rural residents tended to use rechargeable lamps while urban areas used generators, likely due to the limited availability of electricity systems. Approximately 73% of participants relied on chemist shops to cope with constrained access to health facilities.

Other frameworks focused on the accessibility to resources. Clark et al. 94 developed the social burden concept which uses resources, conversion factors, capabilities, and functioning into a travel cost method to access critical resources. In an integrated physical-social vulnerability model, Dong et al. 92 calculated disrupted access to hospitals in Harris County, Texas. Logan and Guikema 46 integrated spatial planning, diverse vulnerabilities, and community needs into EAE services. In the case study of Willimgton, North Carolina, they showed how lower-income households had fewer access to grocery stores. In a predictive recovery monitoring spatial model, Patrascu and Mostafavi 26 found that the percentage of Black and Asian subpopulations were significant features to predict recovery of population activity, or the visits to essential services in a community.

Vulnerability

Several of the infrastructure resilience frameworks were grounded in social vulnerability assessments. For instance, Toland et al. 43 created a community vulnerability assessment based on an earthquake scenario that resulted in the need for emergency food and water resources. Using GIS, Oswald and Mohammed developed a transportation justice threshold index that integrated social vulnerability into transportation understanding 121 . In a Disruption Tolerance Index, Esmalian et al. 25 showed how demographic variables are connected with disproportionate losses in power and transportation losses.

Additional studies were based on stakeholder input and expert opinion. Atallah et al. 36 established an ABCD roadmap for health services which included acute life-saving services, basic institutional aspects for low-resource settings, community-driven health initiatives, and disease specific interventions. Health experts were instrumental in providing feedback for the ABCD roadmap. Another example is the development of the social resilience tool for water systems validated by experts and community residents by Sweya et al. 117 . To assess highway resilience, Hsieh and Feng had transportation experts score 9 factors including resident population, income, employment, connectivity, dependency ratio, distance to hospital, number of substitutive links, delay time in substitutions, and average degenerated level of services 122 .

Welfare economics

Willingness-to-pay (WTP) models reveal varied household investments in infrastructure resilience. Wang et al. 123 showed a wide WTP range, from $15 to $50 for those unaffected by disruptions to $120–$775 for affected, politically liberal individuals. Islam et al. 124 found households with limited access to safe drinking water were more inclined to pay for resilient water infrastructure. Stock et al. 125 observed that higher-income households showed greater WTP for power and transportation resilience, likely due to more disposable income and expectations for service quality. These findings highlight the need to consider economic constraints in WTP studies to avoid misinterpreting lower income as lower willingness to invest. Indeed, if a study does not adequately account for a person’s economic constraints, the findings may incorrectly interpret a lower ability to pay as a lower willingness to pay.

In terms of policy evaluation for infrastructure resilience, studies like Ulak et al. 126 prioritized equitable power system recovery for different ethnic groups, favoring network renewal over increasing response crews. Baeza et al. 93 noted that infrastructure decisions are often swayed by political factors rather than technical criteria. Furthermore, Lee and Ellingwood 107 introduced a method for intergenerational discounting in civil infrastructure, suggesting more conservative designs for longer service lives to benefit future generations. These studies underscore the complex factors influencing infrastructure resilience policy, including equity, political influence, and long-term planning.

This systematic review is the first to explore how equity is incorporated into infrastructure resilience against natural hazards. By systematically analyzing the existing literature and identifying key gaps, the paper enhances our understanding of equity in this field and outlines clear directions for future research. This study is crucial for understanding the fundamental knowledge that brings social equity to the forefront of infrastructure resilience. Table 5 summarizes the primary findings of this systematic review of equity in infrastructure resilience literature, including what the studies are currently focusing on and the research gaps and limitations.

Our findings show a great diversity of frameworks and methods depending on the context, in which equity is applied (Table 5 ). Moreover, we identify a lack of integrative formal and analytical tools. Therefore, a clear and standard framework is needed to operationalize inequity across infrastructures and hazards; what is missing are analytical tools and approaches to integrate equity assessment into decision-making.

Referring to question 3, we will further explore the current gaps of knowledge and future challenges of studying equity in infrastructure resilience. In elaborating on the gaps identified in our review, we propose that the next era of research questions and objectives should be (1) monitoring equity performance with improved data, (2) weaving equity in computational models, and (3) integrating equity into decision-making tools. Through principles of innovation, accountability, and knowledge, such objectives would be guided by moving beyond distributional equity, recognizing understudied gaps of equity, and inclusion of all geographic regions, and by extension stakeholders (Fig. 8 ).

The figure demonstrates that previous research has focused on detecting and finding evidence of disparity in infrastructure resilience in hazard events. It supports that the next phase of research will monitor equity performance with improved data, weave equity in computational models, and integrate equity in decision making tools in order to move beyond social and spatial distributions, recognize understudied gaps of equity, and include all geographic regions.

The first research direction is the monitoring equity performance with improved data at more granular scales and greater representation of impacted communities. Increased data availability provides researchers, stakeholders, and community residents with more detailed and accurate assessment of infrastructure losses. Many studies have used reliable, yet inherently approximate data sources, for infrastructure service outages. These sources include human mobility, satellite, points-of-interest visitation, and telemetry-based data (such as refs. 69 , 100 ). Private companies are often reluctant to share utility and outage data with researchers 127 . Thus, we encourage the shift towards transparent and open datasets from utility companies in normal times and outage events. This aligns with open-data initiatives such as Open Infrastructure Outage Data Initiative Nationwide (ODIN) 128 , Invest in Open Infrastructure 129 , and Implementing Act on a list of High-Value Datasets 130 . Transparency in data fosters an environment of accountability and innovation to uphold equity standards in infrastructure resilience 131 . An essential aspect of this transparency involves acknowledging and addressing biases that may render certain groups ‘invisible’ within datasets. These digitally invisible populations may well be among the most vulnerable, such as unhoused people that may not have a digital footprint yet are very vulnerable to extreme weather 132 . Gender serves as a poignant example of such invisibility. Historical biases and societal norms often result in gender disparities being perpetuated in various facets of infrastructure design and resilience planning 133 . Women are frequently placed in roles of caregiving responsibilities, such as traveling to reach water (as shown in refs. 105 , 116 , 134 ) or concern over the well-being of family members (as shown in refs. 103 , 135 ), which have been overlooked or marginalized in infrastructure planning processes.

If instances of social disparities are uncovered, researchers and practitioners could collaboratively cultivate evidence-based recommendations to manage infrastructure resilience. At the same time, approaches for responsible data management need to be developed that protect privacy of individuals, especially marginalized and vulnerable groups 136 . There is a trade-off between proper representation of demographic groups and ensuring the privacy of individuals 45 , 67 . Despite this, very few studies call into question the fairness of the data collection in capturing the multifaceted aspects of equity 137 , or the potential risks to communities as described in the EU’s forthcoming Artificial Intelligence Act 138 .

By extension, addressing the problem of digitally invisible populations and possible bias, Gharaibeh et al. 120 also emphasizes that equitable data should represent all communities in the study area. Choices about data collection and storage can directly impact the management of public services, by extension the management of critical information 139 . For example, a significant problem with location-intelligence data collection is properly representing digitally invisible populations as these groups are often marginalized in the digital space leading to gaps in data 132 , 140 . Human mobility data, a specific type of location-intelligence data derived from cell phone pinpoint data, illustrates this issue. Vulnerable groups may not afford or have frequent access to cell phones, resulting in a skewed understanding of population movements 141 . However, other studies have shown that digital platforms can be empowering for marginalized populations to express sentiments of cultural identity and tragedies through active sharing and communication 142 . Ultimately, Hendricks et al. 118 recommend a “triangulation of data sources,” to integrate quantitative and qualitative data, which would mitigate potential data misrepresentation and take advantage of the online information. Moving ahead, approaches need to be developed for fair, privacy-preserving, and unbiased data collection that empowers especially vulnerable communities. At the same time, realizing that data gaps especially in infrastructure-poor regions may not be easy to address, we also follow Casali et al. 84 in calling for synthetic approaches and models that work on sparse data.

Few studies, such as refs. 45 , 66 , have created computational models to capture equity-infrastructure-hazards interactions, which are initial attempts to quantify both the social impacts and the physical performance of infrastructure. This is echoed in the work of Soden et al. 143 which found only ~28% of studies undertake a quantitative evaluation of differential impacts experienced in disasters. To enhance analytical and computational methods in supporting equitable decision-making, it is imperative for future studies to comprehensively integrate social dimensions of infrastructure resilience. Therefore, the next research direction is the intentional weaving of equity in computational models. Where the majority of studies used descriptive statistics and non-linear modeling, complex computational models—such as agent-based simulations—offer the advantage of capturing the nonlinear interactions of equity in infrastructure systems. These tools also allow decision-makers to gain insights into the emergence of complex patterns over time. These simulation models can then be combined with specific metrics that measure infrastructural or social implications. Metrics might include susceptibility curves 144 , social burden costs estimates 94 , or social resilience assessment 76 . Novel metrics for assessing adaptive strategies, human behaviors, and disproportionate impacts (such as 113 ) could also be further quantified through empirical deprivation costs for infrastructure losses 145 . These metrics also are a stepping-stone for formalizing and integrating equity into decision-making tools.

Another research direction is the integration of equity into decision-making tools. Key performance indicators and monitoring systems are essential for clarifying equity processes and outcomes and creating tangible tools for infrastructure planners, managers, engineers, and policy-makers. In particular, the literature discussed the potential for using equity in infrastructure resilience to direct infrastructure investments (such as refs. 93 , 126 , 146 ). Infrastructure resilience requires significant upfront investment and resource allocations, which generally favors wealthier communities. Communities may hold social, cultural, and environmental values that are not properly quantified in infrastructure resilience 147 . Since traditional standards of cost-benefit analyses used by infrastructure managers and operators primarily focus on monetary gains or losses, they would not favorably support significant investments to mitigate the human impacts of infrastructure losses on those most vulnerable 148 . This limitation also delays investments and leads to inaction in infrastructure resilience, resulting in unnecessary loss of services and social harm, potentially amplifying inequities, and furthering societal fragmentation. To bridge this gap, we propose to measure the social costs of infrastructure service disruptions as a way to determine the broad benefits of resilience investments 147 .

As the literature review found, several studies are following a welfare economics approach to quantify social costs associated with infrastructure losses such as the evaluation of policies (such as ref. 93 ) and willingness-to-pay models (such as ref. 125 ). Such economic functions are preliminary steps in quantifying equity as a cost measure; however, these models must avoid misinterpreting lower income as a lower willingness to invest. Lee and Ellingwood 107 proposed using intergenerational discounting rate; however, it is important to recognize the flexibility of options for future generations 149 . Teodoro et al. 149 points to the challenges of using (fixed) discount rates and advocate for a procedural justice-based approach that maximizes flexibility and adaptability. Further research is needed to quantify the social costs of infrastructure disruptions and integrate them into infrastructure resilience assessments, such as calculating the deprivation costs of service losses for vulnerable populations.

Our review shows that certain demographic groups such as indigenous populations, persons with disabilities, and intergenerational equity issues have not been sufficiently studied 150 . This aligns with the conclusions of Seyedrezaei et al. 151 , who found that the majority of studies about equity in the built-environment focused on lower-income and minority households. Indigenous populations face significant geographical, cultural, and linguistic barriers that make their experiences with disrupted infrastructure services distinct from those of the broader population 152 .

Even though intergenerational justice issues have increasingly sparked attention on the climate change discussion, intergenerational equity issues in infrastructure resilience assessments have received limited attention. We argue that intergenerational equity warrants special attention as infrastructure systems have long life cycles that span across multiple generations, and ultimately the decisions on the finance, restoration, and new construction will have a significant impact on the ability of future generations to withstand the impact of stronger climate hazard events. Non-action may lead to tremendous costs in the long run 149 . It is the responsibility of current research to understand the long-term effects of equity in infrastructure management to mitigate future losses and maintain the flexibility of future generations. As a means of procedural justice, these generations should have the space to make choices, instead of being locked in by today’s decisions. Future studies should develop methods to measure and integrate intergenerational inequity in infrastructure resilience assessments.

Given the specific search criteria and focus on equity, infrastructure, and natural hazard, we found a major geographic focus on the United States. Large portions of the global north and global south were not included in the analysis. This could be due to the search criteria of the literature review; however, it is important to recognize potential geographic areas that are isolated from the academic studies on infrastructure resilience. Different infrastructure challenges (e.g., intermittent services) are present through data availability in the region. A dearth of studies on equitable infrastructure resilience could contribute to greater inequity in those regions due to the absence of empirical evidence and proper methodological solutions. This aligns with other findings on sustainable development goals and climate adaptation broadly 153 . Global research efforts, along with common data platforms, standards and methods (see above), that include international collaborations among researchers across the global north and global south regions can bridge this gap and expand the breadth of knowledge and solutions for equitable infrastructure resilience.

Finally, while significant attention has been paid to distributional demographic and spatial inequity issues 151 , there remain several underutilized definitions of equity. Procedural and capacity equity hold the greatest potential for people to feel more included in the infrastructure resilience process. Instead of depending directly on the infrastructure systems, individual households can adapt to disrupted periods through substituted services and alternative actions (such as ref. 78 ). To advance procedural equity in infrastructure resilience, citizen-science research or participatory studies can begin by empowering locals to understand and monitor their resilience (such as ref. 76 ) or failures in their infrastructure systems (such as ref. 120 ). As referenced by Masterson and Cooper 154 , the ladder of citizen power can serve as a framework for how to ethically engage with community partners for procedural equity. The ladder, originally developed by Arnstein 155 , includes non-participation, tokenism, and citizen power. Table 3 shows that most research falls into non-participation: survey data and information are extracted without any community guidance. Limited studies that have branched into community involvement still stay restricted in the tokenism step, such as models that are validated by stakeholders or receive expert opinions on their conceptual models. Future studies should expand inquiries regarding the procedural and capacity dimension of equity in infrastructure resilience assessments and management. For instance, research could map out where inequities occur in the decision-making process and targeted spatial regions as well as allocate of resources for infrastructure resilience. It could also continue pursuing inclusive methodologies such as participatory action research and co-design processes. It should investigate effective methods to genuinely integrate different stakeholders and community members from conception through evaluation of research.

Although the primary audience of the literature review is academic scholars and fellow researchers, the identified gaps are of importance for practitioners, governmental agencies, community organizations, and advocates. By harnessing the transformative power of equity, studies in infrastructure resilience can transcend its traditional role and develop equity-focused data, modeling, and decision-making tools which considers everyone in the community. The integration of equity aspects within the framework of infrastructure resilience not only enhances the resilience of infrastructure systems but also contributes to the creation of inclusive and resilient communities. Infrastructure resilience would not just be a shield against adversity but also a catalyst for positive social and environmental change.

Data availability

The created excel database which includes information on the key parts of the 8-dimensional equity framework will be uploaded to DesignSafe-CI.

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Acknowledgements

This material is based in part upon work supported by the National Science Foundation under Grant CMMI-1846069 (CAREER) and the support of the National Science Foundation Graduate Research Fellowship. We would like to thank the contributions of our undergraduate students: Nhat Bui, Shweta Kumaran, Colton Singh, and Samuel Baez.

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Coleman, N., Li, X., Comes, T. et al. Weaving equity into infrastructure resilience research: a decadal review and future directions. npj Nat. Hazards 1 , 25 (2024). https://doi.org/10.1038/s44304-024-00022-x

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• Corpus ID: 272230078

Defining mental health literacy: a systematic literature review and educational inspiration

• Shengnan Zeng , Richard Bailey , +1 author Xiaohui Chen
• Published in Journal of Public Mental… 2 September 2024
• Psychology, Education

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A systematic review of the limitations and associated opportunities of chatgpt, deductive qualitative analysis: evaluating, expanding, and refining theory, conceptualising and measuring positive mental health literacy: a systematic literature review, mental health education integration into the school curriculum needs to be implemented, review: school-based mental health literacy interventions to promote help-seeking - a systematic review., public opinion towards mental health (the case of the vologda region), quantifying the global burden of mental disorders and their economic value, mental health literacy: it is now time to put knowledge into practice, clarifying the concept of mental health literacy: protocol for a scoping review, positive mental health literacy: a concept analysis, related papers.

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High-cycle fatigue performance of laser powder bed fusion ti-6al-4v alloy with inherent internal defects: a critical literature review.

1. Introduction

2. The Internal Defects Problem of L-PBF Ti-6Al-4V

2.1. the role of internal defects on the fatigue performance.

2.2. Crack Initiation and Micro-Short Crack (MSC) Propagation

2.3. crack propagation, 3. microstructure, 3.1. microstructure in different states, 3.1.1. as-built alloys, 3.1.2. after post heat treatments, 3.1.3. after hip, 3.2. microstructure’s role in high-cycle fatigue performance, 4. post processing treatments, 4.1. machining, 4.2. heat treatment, 5. machine learning models of predicting fatigue life, 6. conclusions and perspective for future research.

• Research on different types of internal defects was extremely uneven, partially due to the occurrence frequency, detriment level, and difficulty of analysis for each defect type. As a result, gas porosity has been extensively and quantitatively investigated, recently followed by LOF defects. However, studies on other internal defect types, such as keyholes, balling, and α-phase facets, were rare. There is an urgent need for detailed research on these types of defects.
• Quantitatively correlating LOFs with fatigue life performance is challenging due to their complex topology. Recent studies suggested that LOFs can be simplified based on their main profile and most critical embedded features, using an adapted SWT method to evaluate fatigue life. Comprehensive investigations are needed to further digitalize the geometric features of LOFs with a validated analytical approach. Additionally, the influence of un-melted powders embedded in LOFs needs to be investigated and clarified.
• The microstructure composition of L-PBF Ti-6Al-4V alloy, especially in the as-built state, is distinct from conventionally manufactured Ti-6Al-4V alloy. Additionally, L-PBF Ti-6Al-4V alloy have more microstructural imperfections, such as dislocations, which introduce uncertainties in quantifying the microstructure’s role in early-stage crack evolution. To address this, the microstructures of L-PBF Ti-6Al-4V alloy under various conditions need to be standardized. Subsequently, the quantification of the microstructure’s role in fatigue life performance should be progressively investigated, starting with simple cases and advancing to more complex scenarios. This could begin with the fine α + β structure after heat treatment, progress to the α′ in the β phase of the as-built condition, and eventually include the coupling effects with internal defects.
• The surrounding microstructures around internal defects significantly influence fatigue crack initiation and MSC propagation. However, relevant research on AM Ti-6Al-4V alloy was very limited. While similar investigations on other types of metal alloys can be referenced, their findings cannot be directly applied due to distinct microstructures and properties. The CPFE approach may be an ideal solution to clarify the role of microstructures in fatigue life performance and reveal the mechanisms and behaviors of MSC propagation.
• The distribution of residual stresses in L-PBF Ti-6Al-4V alloy, in both as-built and post-treated states (e.g., machining, heat treatments, and HIP), has been investigated and visualized in recent years. Understanding the mechanism by which fatigue life performance is altered is straightforward: residual stresses superpose the remote stresses. However, there is an urgent need to quantitatively correlate residual stresses in different states with fatigue crack evolution. Numerical analysis of residual stress formation during L-PBF processing and post-processing treatments, as well as its impact on fatigue crack evolution, can be both necessary and valuable.
• Post-processing techniques have a considerable impact on the fatigue life performance of L-PBF Ti-6Al-4V alloy. There have been in-depth investigations into various post-processing parameters (e.g., heat treatment at different temperatures, HIP) and studies combining different post-processing treatments (e.g., machining, heat treatment, and HIP), as suggested by previous review papers. Further research in this direction is needed to establish standardized post-processing treatments and combinations to achieve an optimal balance of mechanical properties for various application purposes.
• Data-driven ML models seriously rely on the quantity and quality of dataset, and their contribution to the physical mechanism might be limited. Physics-informed ML models are more promising as they improve the prediction accuracy while requiring less data. In addition, they provide a deeper understanding of the physical mechanism than the pure data-driven models. FEA is an efficient solution for enlarging the dataset, on the premise of being validated.

Author Contributions

Data availability statement, conflicts of interest.

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Li, Z.; Affolter, C. High-Cycle Fatigue Performance of Laser Powder Bed Fusion Ti-6Al-4V Alloy with Inherent Internal Defects: A Critical Literature Review. Metals 2024 , 14 , 972. https://doi.org/10.3390/met14090972

Li Z, Affolter C. High-Cycle Fatigue Performance of Laser Powder Bed Fusion Ti-6Al-4V Alloy with Inherent Internal Defects: A Critical Literature Review. Metals . 2024; 14(9):972. https://doi.org/10.3390/met14090972

Li, Zongchen, and Christian Affolter. 2024. "High-Cycle Fatigue Performance of Laser Powder Bed Fusion Ti-6Al-4V Alloy with Inherent Internal Defects: A Critical Literature Review" Metals 14, no. 9: 972. https://doi.org/10.3390/met14090972

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