excludes results from the search term and reduces the number of results.
Adult learning online education:
Adult learning online education:
Adult learning online education:
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.
Archer Librarians
Schedule an appointment.
Contact a librarian directly (email), or submit a request form. If you have worked with someone before, you can request them on the form.
Types of Literature Review — A Guide for Researchers
Table of Contents
Researchers often face challenges when choosing the appropriate type of literature review for their study. Regardless of the type of research design and the topic of a research problem , they encounter numerous queries, including:
What is the right type of literature review my study demands?
How do we gather the data?
How to conduct one?
How reliable are the review findings?
How do we employ them in our research? And the list goes on.
If you’re also dealing with such a hefty questionnaire, this article is of help. Read through this piece of guide to get an exhaustive understanding of the different types of literature reviews and their step-by-step methodologies along with a dash of pros and cons discussed.
Heading from scratch!
What is a Literature Review?
A literature review provides a comprehensive overview of existing knowledge on a particular topic, which is quintessential to any research project. Researchers employ various literature reviews based on their research goals and methodologies. The review process involves assembling, critically evaluating, and synthesizing existing scientific publications relevant to the research question at hand. It serves multiple purposes, including identifying gaps in existing literature, providing theoretical background, and supporting the rationale for a research study.
What is the importance of a Literature review in research?
Literature review in research serves several key purposes, including:
Background of the study: Provides proper context for the research. It helps researchers understand the historical development, theoretical perspectives, and key debates related to their research topic.
Identification of research gaps: By reviewing existing literature, researchers can identify gaps or inconsistencies in knowledge, paving the way for new research questions and hypotheses relevant to their study.
Theoretical framework development: Facilitates the development of theoretical frameworks by cultivating diverse perspectives and empirical findings. It helps researchers refine their conceptualizations and theoretical models.
Methodological guidance: Offers methodological guidance by highlighting the documented research methods and techniques used in previous studies. It assists researchers in selecting appropriate research designs, data collection methods, and analytical tools.
Quality assurance and upholding academic integrity: Conducting a thorough literature review demonstrates the rigor and scholarly integrity of the research. It ensures that researchers are aware of relevant studies and can accurately attribute ideas and findings to their original sources.
Types of Literature Review
Literature review plays a crucial role in guiding the research process , from providing the background of the study to research dissemination and contributing to the synthesis of the latest theoretical literature review findings in academia.
However, not all types of literature reviews are the same; they vary in terms of methodology, approach, and purpose. Let's have a look at the various types of literature reviews to gain a deeper understanding of their applications.
1. Narrative Literature Review
A narrative literature review, also known as a traditional literature review, involves analyzing and summarizing existing literature without adhering to a structured methodology. It typically provides a descriptive overview of key concepts, theories, and relevant findings of the research topic.
Unlike other types of literature reviews, narrative reviews reinforce a more traditional approach, emphasizing the interpretation and discussion of the research findings rather than strict adherence to methodological review criteria. It helps researchers explore diverse perspectives and insights based on the research topic and acts as preliminary work for further investigation.
The first step in conducting a narrative literature review is to clearly define the research question or topic of interest. Defining the scope and purpose of the review includes — What specific aspect of the topic do you want to explore? What are the main objectives of the research? Refine your research question based on the specific area you want to explore.
Conduct a thorough literature search
Once the research question is defined, you can conduct a comprehensive literature search. Explore and use relevant databases and search engines like SciSpace Discover to identify credible and pertinent, scholarly articles and publications.
Select relevant studies
Before choosing the right set of studies, it’s vital to determine inclusion (studies that should possess the required factors) and exclusion criteria for the literature and then carefully select papers. For example — Which studies or sources will be included based on relevance, quality, and publication date?
*Important (applies to all the reviews): Inclusion criteria are the factors a study must include (For example: Include only peer-reviewed articles published between 2022-2023, etc.). Exclusion criteria are the factors that wouldn’t be required for your search strategy (Example: exclude irrelevant papers, preprints, written in non-English, etc.)
Critically analyze the literature
Once the relevant studies are shortlisted, evaluate the methodology, findings, and limitations of each source and jot down key themes, patterns, and contradictions. You can use efficient AI tools to conduct a thorough literature review and analyze all the required information.
Synthesize and integrate the findings
Now, you can weave together the reviewed studies, underscoring significant findings such that new frameworks, contrasting viewpoints, and identifying knowledge gaps.
Discussion and conclusion
This is an important step before crafting a narrative review — summarize the main findings of the review and discuss their implications in the relevant field. For example — What are the practical implications for practitioners? What are the directions for future research for them?
Write a cohesive narrative review
Organize the review into coherent sections and structure your review logically, guiding the reader through the research landscape and offering valuable insights. Use clear and concise language to convey key points effectively.
Structure of Narrative Literature Review
A well-structured, narrative analysis or literature review typically includes the following components:
Introduction: Provides an overview of the topic, objectives of the study, and rationale for the review.
Background: Highlights relevant background information and establish the context for the review.
Main Body: Indexes the literature into thematic sections or categories, discussing key findings, methodologies, and theoretical frameworks.
Discussion: Analyze and synthesize the findings of the reviewed studies, stressing similarities, differences, and any gaps in the literature.
Conclusion: Summarizes the main findings of the review, identifies implications for future research, and offers concluding remarks.
Pros and Cons of Narrative Literature Review
Flexibility in methodology and doesn’t necessarily rely on structured methodologies
Follows traditional approach and provides valuable and contextualized insights
Suitable for exploring complex or interdisciplinary topics. For example — Climate change and human health, Cybersecurity and privacy in the digital age, and more
Subjectivity in data selection and interpretation
Potential for bias in the review process
Lack of rigor compared to systematic reviews
Example of Well-Executed Narrative Literature Reviews
Paper title: Examining Moral Injury in Clinical Practice: A Narrative Literature Review
Source: SciSpace
While narrative reviews offer flexibility, academic integrity remains paramount. So, ensure proper citation of all sources and maintain a transparent and factual approach throughout your critical narrative review, itself.
2. Systematic Review
A systematic literature review is one of the comprehensive types of literature review that follows a structured approach to assembling, analyzing, and synthesizing existing research relevant to a particular topic or question. It involves clearly defined criteria for exploring and choosing studies, as well as rigorous methods for evaluating the quality of relevant studies.
It plays a prominent role in evidence-based practice and decision-making across various domains, including healthcare, social sciences, education, health sciences, and more. By systematically investigating available literature, researchers can identify gaps in knowledge, evaluate the strength of evidence, and report future research directions.
Here are the key steps involved in conducting a systematic literature review
Formulate a clear and focused research question
Clearly define the research question or objective of the review. It helps to centralize the literature search strategy and determine inclusion criteria for relevant studies.
Develop a thorough literature search strategy
Design a comprehensive search strategy to identify relevant studies. It involves scrutinizing scientific databases and all relevant articles in journals. Plus, seek suggestions from domain experts and review reference lists of relevant review articles.
Screening and selecting studies
Employ predefined inclusion and exclusion criteria to systematically screen the identified studies. This screening process also typically involves multiple reviewers independently assessing the eligibility of each study.
Data extraction
Extract key information from selected studies using standardized forms or protocols. It includes study characteristics, methods, results, and conclusions.
Critical appraisal
Evaluate the methodological quality and potential biases of included studies. Various tools (BMC medical research methodology) and criteria can be implemented for critical evaluation depending on the study design and research quetions .
Data synthesis
Analyze and synthesize review findings from individual studies to draw encompassing conclusions or identify overarching patterns and explore heterogeneity among studies.
Interpretation and conclusion
Interpret the findings about the research question, considering the strengths and limitations of the research evidence. Draw conclusions and implications for further research.
The final step — Report writing
Craft a detailed report of the systematic literature review adhering to the established guidelines of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). This ensures transparency and reproducibility of the review process.
By following these steps, a systematic literature review aims to provide a comprehensive and unbiased summary of existing evidence, help make informed decisions, and advance knowledge in the respective domain or field.
Structure of a systematic literature review
A well-structured systematic literature review typically consists of the following sections:
Introduction: Provides background information on the research topic, outlines the review objectives, and enunciates the scope of the study.
Methodology: Describes the literature search strategy, selection criteria, data extraction process, and other methods used for data synthesis, extraction, or other data analysis..
Results: Presents the review findings, including a summary of the incorporated studies and their key findings.
Discussion: Interprets the findings in light of the review objectives, discusses their implications, and identifies limitations or promising areas for future research.
Conclusion: Summarizes the main review findings and provides suggestions based on the evidence presented in depth meta analysis.
*Important (applies to all the reviews): Remember, the specific structure of your literature review may vary depending on your topic, research question, and intended audience. However, adhering to a clear and logical hierarchy ensures your review effectively analyses and synthesizes knowledge and contributes valuable insights for readers.
Pros and Cons of Systematic Literature Review
Adopts rigorous and transparent methodology
Minimizes bias and enhances the reliability of the study
Provides evidence-based insights
Time and resource-intensive
High dependency on the quality of available literature (literature research strategy should be accurate)
Potential for publication bias
Example of Well-Executed Systematic Literature Review
Paper title: Systematic Reviews: Understanding the Best Evidence For Clinical Decision-making in Health Care: Pros and Cons.
Read this detailed article on how to use AI tools to conduct a systematic review for your research!
3. Scoping Literature Review
A scoping literature review is a methodological review type of literature review that adopts an iterative approach to systematically map the existing literature on a particular topic or research area. It involves identifying, selecting, and synthesizing relevant papers to provide an overview of the size and scope of available evidence. Scoping reviews are broader in scope and include a diverse range of study designs and methodologies especially focused on health services research.
The main purpose of a scoping literature review is to examine the extent, range, and nature of existing studies on a topic, thereby identifying gaps in research, inconsistencies, and areas for further investigation. Additionally, scoping reviews can help researchers identify suitable methodologies and formulate clinical recommendations. They also act as the frameworks for future systematic reviews or primary research studies.
Scoping reviews are primarily focused on —
Emerging or evolving topics — where the research landscape is still growing or budding. Example — Whole Systems Approaches to Diet and Healthy Weight: A Scoping Review of Reviews .
Broad and complex topics : With a vast amount of existing literature.
Scenarios where a systematic review is not feasible: Due to limited resources or time constraints.
Steps to Conduct a Scoping Literature Review
While Scoping reviews are not as rigorous as systematic reviews, however, they still follow a structured approach. Here are the steps:
Identify the research question: Define the broad topic you want to explore.
Identify Relevant Studies: Conduct a comprehensive search of relevant literature using appropriate databases, keywords, and search strategies.
Select studies to be included in the review: Based on the inclusion and exclusion criteria, determine the appropriate studies to be included in the review.
Data extraction and charting : Extract relevant information from selected studies, such as year, author, main results, study characteristics, key findings, and methodological approaches. However, it varies depending on the research question.
Collate, summarize, and report the results: Analyze and summarize the extracted data to identify key themes and trends. Then, present the findings of the scoping review in a clear and structured manner, following established guidelines and frameworks .
Structure of a Scoping Literature Review
A scoping literature review typically follows a structured format similar to a systematic review. It includes the following sections:
Introduction: Introduce the research topic and objectives of the review, providing the historical context, and rationale for the study.
Methods : Describe the methods used to conduct the review, including search strategies, study selection criteria, and data extraction procedures.
Results: Present the findings of the review, including key themes, concepts, and patterns identified in the literature review.
Discussion: Examine the implications of the findings, including strengths, limitations, and areas for further examination.
Conclusion: Recapitulate the main findings of the review and their implications for future research, policy, or practice.
Pros and Cons of Scoping Literature Review
Provides a comprehensive overview of existing literature
Helps to identify gaps and areas for further research
Suitable for exploring broad or complex research questions
Doesn’t provide the depth of analysis offered by systematic reviews
Subject to researcher bias in study selection and data extraction
Requires careful consideration of literature search strategies and inclusion criteria to ensure comprehensiveness and validity.
In short, a scoping review helps map the literature on developing or emerging topics and identifying gaps. It might be considered as a step before conducting another type of review, such as a systematic review. Basically, acts as a precursor for other literature reviews.
Example of a Well-Executed Scoping Literature Review
Paper title: Health Chatbots in Africa Literature: A Scoping Review
Check out the key differences between Systematic and Scoping reviews — Evaluating literature review: systematic vs. scoping reviews
4. Integrative Literature Review
Integrative Literature Review (ILR) is a type of literature review that proposes a distinctive way to analyze and synthesize existing literature on a specific topic, providing a thorough understanding of research and identifying potential gaps for future research.
Unlike a systematic review, which emphasizes quantitative studies and follows strict inclusion criteria, an ILR embraces a more pliable approach. It works beyond simply summarizing findings — it critically analyzes, integrates, and interprets research from various methodologies (qualitative, quantitative, mixed methods) to provide a deeper understanding of the research landscape. ILRs provide a holistic and systematic overview of existing research, integrating findings from various methodologies. ILRs are ideal for exploring intricate research issues, examining manifold perspectives, and developing new research questions.
Steps to Conduct an Integrative Literature Review
Identify the research question: Clearly define the research question or topic of interest as formulating a clear and focused research question is critical to leading the entire review process.
Literature search strategy: Employ systematic search techniques to locate relevant literature across various databases and sources.
Evaluate the quality of the included studies : Critically assess the methodology, rigor, and validity of each study by applying inclusion and exclusion criteria to filter and select studies aligned with the research objectives.
Data Extraction: Extract relevant data from selected studies using a structured approach.
Synthesize the findings : Thoroughly analyze the selected literature, identify key themes, and synthesize findings to derive noteworthy insights.
Critical appraisal: Critically evaluate the quality and validity of qualitative research and included studies by using BMC medical research methodology.
Interpret and present your findings: Discuss the purpose and implications of your analysis, spotlighting key insights and limitations. Organize and present the findings coherently and systematically.
Structure of an Integrative Literature Review
Introduction : Provide an overview of the research topic and the purpose of the integrative review.
Methods: Describe the opted literature search strategy, selection criteria, and data extraction process.
Results: Present the synthesized findings, including key themes, patterns, and contradictions.
Discussion: Interpret the findings about the research question, emphasizing implications for theory, practice, and prospective research.
Conclusion: Summarize the main findings, limitations, and contributions of the integrative review.
Pros and Cons of Integrative Literature Review
Informs evidence-based practice and policy to the relevant stakeholders of the research.
Contributes to theory development and methodological advancement, especially in the healthcare arena.
Integrates diverse perspectives and findings
Time-consuming process due to the extensive literature search and synthesis
Requires advanced analytical and critical thinking skills
Potential for bias in study selection and interpretation
The quality of included studies may vary, affecting the validity of the review
Example of Integrative Literature Reviews
Paper Title: An Integrative Literature Review: The Dual Impact of Technological Tools on Health and Technostress Among Older Workers
5. Rapid Literature Review
A Rapid Literature Review (RLR) is the fastest type of literature review which makes use of a streamlined approach for synthesizing literature summaries, offering a quicker and more focused alternative to traditional systematic reviews. Despite employing identical research methods, it often simplifies or omits specific steps to expedite the process. It allows researchers to gain valuable insights into current research trends and identify key findings within a shorter timeframe, often ranging from a few days to a few weeks — unlike traditional literature reviews, which may take months or even years to complete.
When to Consider a Rapid Literature Review?
When time impediments demand a swift summary of existing research
For emerging topics where the latest literature requires quick evaluation
To report pilot studies or preliminary research before embarking on a comprehensive systematic review
Steps to Conduct a Rapid Literature Review
Define the research question or topic of interest. A well-defined question guides the search process and helps researchers focus on relevant studies.
Determine key databases and sources of relevant literature to ensure comprehensive coverage.
Develop literature search strategies using appropriate keywords and filters to fetch a pool of potential scientific articles.
Screen search results based on predefined inclusion and exclusion criteria.
Extract and summarize relevant information from the above-preferred studies.
Synthesize findings to identify key themes, patterns, or gaps in the literature.
Prepare a concise report or a summary of the RLR findings.
Structure of a Rapid Literature Review
An effective structure of an RLR typically includes the following sections:
Introduction: Briefly introduce the research topic and objectives of the RLR.
Methodology: Describe the search strategy, inclusion and exclusion criteria, and data extraction process.
Results: Present a summary of the findings, including key themes or patterns identified.
Discussion: Interpret the findings, discuss implications, and highlight any limitations or areas for further research
Conclusion: Summarize the key findings and their implications for practice or future research
Pros and Cons of Rapid Literature Review
RLRs can be completed quickly, authorizing timely decision-making
RLRs are a cost-effective approach since they require fewer resources compared to traditional literature reviews
Offers great accessibility as RLRs provide prompt access to synthesized evidence for stakeholders
RLRs are flexible as they can be easily adapted for various research contexts and objectives
RLR reports are limited and restricted, not as in-depth as systematic reviews, and do not provide comprehensive coverage of the literature compared to traditional reviews.
Susceptible to bias because of the expedited nature of RLRs. It would increase the chance of overlooking relevant studies or biases in the selection process.
Due to time constraints, RLR findings might not be robust enough as compared to systematic reviews.
Example of a Well-Executed Rapid Literature Review
Paper Title: What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature
A Summary of Literature Review Types
Literature Review Type
Narrative
Systematic
Integrative
Rapid
Scoping
Approach
The traditional approach lacks a structured methodology
Systematic search, including structured methodology
Combines diverse methodologies for a comprehensive understanding
Quick review within time constraints
Preliminary study of existing literature
How Exhaustive is the process?
May or may not be comprehensive
Exhaustive and comprehensive search
A comprehensive search for integration
Time-limited search
Determined by time or scope constraints
Data Synthesis
Narrative
Narrative with tabular accompaniment
Integration of various sources or methodologies
Narrative and tabular
Narrative and tabular
Purpose
Provides description of meta analysis and conceptualization of the review
Comprehensive evidence synthesis
Holistic understanding
Quick policy or practice guidelines review
Preliminary literature review
Key characteristics
Storytelling, chronological presentation
Rigorous, traditional and systematic techniques approach
Diverse source or method integration
Time-constrained, systematic approach
Identifies literature size and scope
Example Use Case
Historical exploration
Effectiveness evaluation
Quantitative, qualitative, and mixed combination
Policy summary
Research literature overview
Tools and Resources for Conducting Different Types of Literature Reviews
Online scientific databases.
Platforms such as SciSpace , PubMed , Scopus , Elsevier , and Web of Science provide access to a vast array of scholarly literature, facilitating the search and data retrieval process.
Reference management software
Tools like SciSpace Citation Generator , EndNote, Zotero , and Mendeley assist researchers in organizing, annotating, and citing relevant literature, streamlining the review process altogether.
Automate Literature Review with AI tools
Automate the literature review process by using tools like SciSpace literature review which helps you compare and contrast multiple papers all on one screen in an easy-to-read matrix format. You can effortlessly analyze and interpret the review findings tailored to your study. It also supports the review in 75+ languages, making it more manageable even for non-English speakers.
Goes without saying — literature review plays a pivotal role in academic research to identify the current trends and provide insights to pave the way for future research endeavors. Different types of literature review has their own strengths and limitations, making them suitable for different research designs and contexts. Whether conducting a narrative review, systematic review, scoping review, integrative review, or rapid literature review, researchers must cautiously consider the objectives, resources, and the nature of the research topic.
If you’re currently working on a literature review and still adopting a manual and traditional approach, switch to the automated AI literature review workspace and transform your traditional literature review into a rapid one by extracting all the latest and relevant data for your research!
There you go!
Frequently Asked Questions
Narrative reviews give a general overview of a topic based on the author's knowledge. They may lack clear criteria and can be biased. On the other hand, systematic reviews aim to answer specific research questions by following strict methods. They're thorough but time-consuming.
A systematic review collects and analyzes existing research to provide an overview of a topic, while a meta-analysis statistically combines data from multiple studies to draw conclusions about the overall effect of an intervention or relationship between variables.
A systematic review thoroughly analyzes existing research on a specific topic using strict methods. In contrast, a scoping review offers a broader overview of the literature without evaluating individual studies in depth.
A systematic review thoroughly examines existing research using a rigorous process, while a rapid review provides a quicker summary of evidence, often by simplifying some of the systematic review steps to meet shorter timelines.
A systematic review carefully examines many studies on a single topic using specific guidelines. Conversely, an integrative review blends various types of research to provide a more comprehensive understanding of the topic.
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University of Texas Libraries
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Systematic Reviews & Evidence Synthesis Methods
Types of reviews.
Formulate Question
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Searching Systematically
Supplementary Searching
Managing Results
Deduplication
Critical Appraisal
Glossary of terms
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Systematic Review & Evidence Synthesis Boot Camp
Not sure what type of review you want to conduct?
There are many types of reviews --- narrative reviews , scoping reviews , systematic reviews, integrative reviews, umbrella reviews, rapid reviews and others --- and it's not always straightforward to choose which type of review to conduct. These Review Navigator tools (see below) ask a series of questions to guide you through the various kinds of reviews and to help you determine the best choice for your research needs.
Which review is right for you? (Univ. of Manitoba)
What type of review is right for you? (Cornell)
Review Ready Reckoner - Assessment Tool (RRRsAT)
A typology of reviews: an analysis of 14 review types and associated methodologies. by Grant & Booth
Meeting the review family: exploring review types and associated information retrieval requirements | Health Info Libr J, 2019
Label
Description
Search
Appraisal
Synthesis
Analysis
Critical Review
Aims to demonstrate writer has extensively researched literature and critically evaluated its quality. Goes beyond mere description to include degree of analysis and conceptual innovation. Typically results in hypothesis or model
Seeks to identify most significant items in the field
No formal quality assessment. Attempts to evaluate according to contribution
Typically narrative, perhaps conceptual or chronological
Significant component: seeks to identify conceptual contribution to embody existing or derive new theory
Literature Review
Generic term: published materials that provide examination of recent or current literature. Can cover wide range of subjects at various levels of completeness and comprehensiveness. May include research findings
May or may not include comprehensive searching
May or may not include quality assessment
Typically narrative
Analysis may be chronological, conceptual, thematic, etc.
Mapping review/ systematic map
Map out and categorize existing literature from which to commission further reviews and/or primary research by identifying gaps in research literature
Completeness of searching determined by time/scope constraints
No formal quality assessment
May be graphical and tabular
Characterizes quantity and quality of literature, perhaps by study design and other key features. May identify need for primary or secondary research
Meta-analysis
Technique that statistically combines the results of quantitative studies to provide a more precise effect of the results
Aims for exhaustive, comprehensive searching. May use funnel plot to assess completeness
Quality assessment may determine inclusion/exclusion and/or sensitivity analyses
Graphical and tabular with narrative commentary
Numerical analysis of measures of effect assuming absence of heterogeneity
Mixed studies review/mixed methods review
Refers to any combination of methods where one significant component is a literature review (usually systematic). Within a review context it refers to a combination of review approaches for example combining quantitative with qualitative research or outcome with process studies
Requires either very sensitive search to retrieve all studies or separately conceived quantitative and qualitative strategies
Requires either a generic appraisal instrument or separate appraisal processes with corresponding checklists
Typically both components will be presented as narrative and in tables. May also employ graphical means of integrating quantitative and qualitative studies
Analysis may characterise both literatures and look for correlations between characteristics or use gap analysis to identify aspects absent in one literature but missing in the other
Overview
Generic term: summary of the [medical] literature that attempts to survey the literature and describe its characteristics
May or may not include comprehensive searching (depends whether systematic overview or not)
May or may not include quality assessment (depends whether systematic overview or not)
Synthesis depends on whether systematic or not. Typically narrative but may include tabular features
Analysis may be chronological, conceptual, thematic, etc.
Method for integrating or comparing the findings from qualitative studies. It looks for ‘themes’ or ‘constructs’ that lie in or across individual qualitative studies
May employ selective or purposive sampling
Quality assessment typically used to mediate messages not for inclusion/exclusion
Qualitative, narrative synthesis
Thematic analysis, may include conceptual models
Rapid review
Assessment of what is already known about a policy or practice issue, by using systematic review methods to search and critically appraise existing research
Completeness of searching determined by time constraints
Time-limited formal quality assessment
Typically narrative and tabular
Quantities of literature and overall quality/direction of effect of literature
Scoping review
Preliminary assessment of potential size and scope of available research literature. Aims to identify nature and extent of research evidence (usually including ongoing research)
Completeness of searching determined by time/scope constraints. May include research in progress
No formal quality assessment
Typically tabular with some narrative commentary
Characterizes quantity and quality of literature, perhaps by study design and other key features. Attempts to specify a viable review
State-of-the-art review
Tend to address more current matters in contrast to other combined retrospective and current approaches. May offer new perspectives on issue or point out area for further research
Aims for comprehensive searching of current literature
No formal quality assessment
Typically narrative, may have tabular accompaniment
Current state of knowledge and priorities for future investigation and research
Systematic review
Seeks to systematically search for, appraise and synthesis research evidence, often adhering to guidelines on the conduct of a review
Aims for exhaustive, comprehensive searching
Quality assessment may determine inclusion/exclusion
Typically narrative with tabular accompaniment
What is known; recommendations for practice. What remains unknown; uncertainty around findings, recommendations for future research
Systematic search and review
Combines strengths of critical review with a comprehensive search process. Typically addresses broad questions to produce ‘best evidence synthesis’
Aims for exhaustive, comprehensive searching
May or may not include quality assessment
Minimal narrative, tabular summary of studies
What is known; recommendations for practice. Limitations
Systematized review
Attempt to include elements of systematic review process while stopping short of systematic review. Typically conducted as postgraduate student assignment
May or may not include comprehensive searching
May or may not include quality assessment
Typically narrative with tabular accompaniment
Reproduced from Grant MJ, Booth A. A typology of reviews: an analysis of 14 review types and associated methodologies . Health Info Libr J. 2009 Jun;26(2):91-108. doi: 10.1111/j.1471-1842.2009.00848.x
Literature Review: The What, Why and How-to Guide — Introduction
Getting Started
How to Pick a Topic
Strategies to Find Sources
Evaluating Sources & Lit. Reviews
Tips for Writing Literature Reviews
Writing Literature Review: Useful Sites
Citation Resources
Other Academic Writings
What are Literature Reviews?
So, what is a literature review? "A literature review is an account of what has been published on a topic by accredited scholars and researchers. 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." Taylor, D. The literature review: A few tips on conducting it . University of Toronto Health Sciences Writing Centre.
Goals of Literature Reviews
What are the goals of creating a Literature Review? A literature could be written to accomplish different aims:
To develop a theory or evaluate an existing theory
To summarize the historical or existing state of a research topic
Identify a problem in a field of research
Baumeister, R. F., & Leary, M. R. (1997). Writing narrative literature reviews . Review of General Psychology , 1 (3), 311-320.
What kinds of sources require a Literature Review?
A research paper assigned in a course
A thesis or dissertation
A grant proposal
An article intended for publication in a journal
All these instances require you to collect what has been written about your research topic so that you can demonstrate how your own research sheds new light on the topic.
Types of Literature Reviews
What kinds of literature reviews are written?
Narrative review: The purpose of this type of review is to describe the current state of the research on a specific topic/research and to offer a critical analysis of the literature reviewed. Studies are grouped by research/theoretical categories, and themes and trends, strengths and weakness, and gaps are identified. The review ends with a conclusion section which summarizes the findings regarding the state of the research of the specific study, the gaps identify and if applicable, explains how the author's research will address gaps identify in the review and expand the knowledge on the topic reviewed.
Example : Predictors and Outcomes of U.S. Quality Maternity Leave: A Review and Conceptual Framework: 10.1177/08948453211037398
Systematic review : "The authors of a systematic review use a specific procedure to search the research literature, select the studies to include in their review, and critically evaluate the studies they find." (p. 139). Nelson, L. K. (2013). Research in Communication Sciences and Disorders . Plural Publishing.
Example : The effect of leave policies on increasing fertility: a systematic review: 10.1057/s41599-022-01270-w
Meta-analysis : "Meta-analysis is a method of reviewing research findings in a quantitative fashion by transforming the data from individual studies into what is called an effect size and then pooling and analyzing this information. The basic goal in meta-analysis is to explain why different outcomes have occurred in different studies." (p. 197). Roberts, M. C., & Ilardi, S. S. (2003). Handbook of Research Methods in Clinical Psychology . Blackwell Publishing.
Example : Employment Instability and Fertility in Europe: A Meta-Analysis: 10.1215/00703370-9164737
Meta-synthesis : "Qualitative meta-synthesis is a type of qualitative study that uses as data the findings from other qualitative studies linked by the same or related topic." (p.312). Zimmer, L. (2006). Qualitative meta-synthesis: A question of dialoguing with texts . Journal of Advanced Nursing , 53 (3), 311-318.
Example : Women’s perspectives on career successes and barriers: A qualitative meta-synthesis: 10.1177/05390184221113735
Literature Reviews in the Health Sciences
UConn Health subject guide on systematic reviews Explanation of the different review types used in health sciences literature as well as tools to help you find the right review type
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.
Also, we can define a literature review as the collected body of scholarly works related to a topic:
Summarizes and analyzes previous research relevant to a topic
Includes scholarly books and articles published in academic journals
Can be an specific scholarly paper or a section in a research paper
The objective of a Literature Review is to find previous published scholarly works relevant to an specific topic
Help gather ideas or information
Keep up to date in current trends and findings
Help develop new questions
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.
Helps focus your own research questions or problems
Discovers relationships between research studies/ideas.
Suggests unexplored ideas or populations
Identifies major themes, concepts, and researchers on a topic.
Tests assumptions; may help counter preconceived ideas and remove unconscious bias.
Identifies critical gaps, points of disagreement, or potentially flawed methodology or theoretical approaches.
Indicates potential directions for future research.
All content in this section is from Literature Review Research from Old Dominion University
Keep in mind the following, a literature review is NOT:
Not an essay
Not an annotated bibliography in which you summarize each article that you have reviewed. A literature review goes beyond basic summarizing to focus on the critical analysis of the reviewed works and their relationship to your research question.
Not a research paper where you select resources to support one side of an issue versus another. A lit review should explain and consider all sides of an argument in order to avoid bias, and areas of agreement and disagreement should be highlighted.
A literature review serves several purposes. For example, it
provides thorough knowledge of previous studies; introduces seminal works.
helps focus one’s own research topic.
identifies a conceptual framework for one’s own research questions or problems; indicates potential directions for future research.
suggests previously unused or underused methodologies, designs, quantitative and qualitative strategies.
identifies gaps in previous studies; identifies flawed methodologies and/or theoretical approaches; avoids replication of mistakes.
helps the researcher avoid repetition of earlier research.
suggests unexplored populations.
determines whether past studies agree or disagree; identifies controversy in the literature.
tests assumptions; may help counter preconceived ideas and remove unconscious bias.
As Kennedy (2007) notes*, it is important to think of knowledge in a given field as consisting of three layers. First, there are the primary studies that researchers conduct and publish. Second are the reviews of those studies that summarize and offer new interpretations built from and often extending beyond the original studies. Third, there are the perceptions, conclusions, opinion, and interpretations that are shared informally that become part of the lore of field. In composing a literature review, it is important to note that it is often this third layer of knowledge that is cited as "true" even though it often has only a loose relationship to the primary studies and secondary literature reviews.
Given this, while literature reviews are designed to provide an overview and synthesis of pertinent sources you have explored, there are several approaches to how they can be done, depending upon the type of analysis underpinning your study. Listed below are definitions of types of literature reviews:
Argumentative Review This form examines literature selectively in order to support or refute an argument, deeply imbedded assumption, or philosophical problem already established in the literature. The purpose is to develop a body of literature that establishes a contrarian viewpoint. Given the value-laden nature of some social science research [e.g., educational reform; immigration control], argumentative approaches to analyzing the literature can be a legitimate and important form of discourse. However, note that they can also introduce problems of bias when they are used to to make summary claims of the sort found in systematic reviews.
Integrative Review Considered a form of research that reviews, critiques, and synthesizes representative literature on a topic in an integrated way such that new frameworks and perspectives on the topic are generated. The body of literature includes all studies that address related or identical hypotheses. A well-done integrative review meets the same standards as primary research in regard to clarity, rigor, and replication.
Historical Review Few things rest in isolation from historical precedent. Historical reviews are focused on examining research throughout a period of time, often starting with the first time an issue, concept, theory, phenomena emerged in the literature, then tracing its evolution within the scholarship of a discipline. The purpose is to place research in a historical context to show familiarity with state-of-the-art developments and to identify the likely directions for future research.
Methodological Review A review does not always focus on what someone said [content], but how they said it [method of analysis]. This approach provides a framework of understanding at different levels (i.e. those of theory, substantive fields, research approaches and data collection and analysis techniques), enables researchers to draw on a wide variety of knowledge ranging from the conceptual level to practical documents for use in fieldwork in the areas of ontological and epistemological consideration, quantitative and qualitative integration, sampling, interviewing, data collection and data analysis, and helps highlight many ethical issues which we should be aware of and consider as we go through our study.
Systematic Review This form consists of an overview of existing evidence pertinent to a clearly formulated research question, which uses pre-specified and standardized methods to identify and critically appraise relevant research, and to collect, report, and analyse data from the studies that are included in the review. Typically it focuses on a very specific empirical question, often posed in a cause-and-effect form, such as "To what extent does A contribute to B?"
Theoretical Review The purpose of this form is to concretely examine the corpus of theory that has accumulated in regard to an issue, concept, theory, phenomena. The theoretical literature review help establish what theories already exist, the relationships between them, to what degree the existing theories have been investigated, and to develop new hypotheses to be tested. Often this form is used to help establish a lack of appropriate theories or reveal that current theories are inadequate for explaining new or emerging research problems. The unit of analysis can focus on a theoretical concept or a whole theory or framework.
* Kennedy, Mary M. "Defining a Literature." Educational Researcher 36 (April 2007): 139-147.
All content in this section is from The Literature Review created by Dr. Robert Larabee USC
Robinson, P. and Lowe, J. (2015), Literature reviews vs systematic reviews. Australian and New Zealand Journal of Public Health, 39: 103-103. doi: 10.1111/1753-6405.12393
What's in the name? The difference between a Systematic Review and a Literature Review, and why it matters . By Lynn Kysh from University of Southern California
Systematic review or meta-analysis?
A systematic review answers a defined research question by collecting and summarizing all empirical evidence that fits pre-specified eligibility criteria.
A meta-analysis is the use of statistical methods to summarize the results of these studies.
Systematic reviews, just like other research articles, can be of varying quality. They are a significant piece of work (the Centre for Reviews and Dissemination at York estimates that a team will take 9-24 months), and to be useful to other researchers and practitioners they should have:
clearly stated objectives with pre-defined eligibility criteria for studies
explicit, reproducible methodology
a systematic search that attempts to identify all studies
assessment of the validity of the findings of the included studies (e.g. risk of bias)
systematic presentation, and synthesis, of the characteristics and findings of the included studies
Not all systematic reviews contain meta-analysis.
Meta-analysis is the use of statistical methods to summarize the results of independent studies. By combining information from all relevant studies, meta-analysis can provide more precise estimates of the effects of health care than those derived from the individual studies included within a review. More information on meta-analyses can be found in Cochrane Handbook, Chapter 9 .
A meta-analysis goes beyond critique and integration and conducts secondary statistical analysis on the outcomes of similar studies. It is a systematic review that uses quantitative methods to synthesize and summarize the results.
An advantage of a meta-analysis is the ability to be completely objective in evaluating research findings. Not all topics, however, have sufficient research evidence to allow a meta-analysis to be conducted. In that case, an integrative review is an appropriate strategy.
Some of the content in this section is from Systematic reviews and meta-analyses: step by step guide created by Kate McAllister.
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Last Updated: Jul 15, 2024 10:34 AM
URL: https://guides.lib.udel.edu/researchmethods
Conducting a Literature Review
What is a Literature Review?
Review Comparison Chart
Tutorials This link opens in a new window
Research Iteration
Guides & Handbooks
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"Review Comparison Chart" from Which review is that? A guide to review types by the University of Melbourne Library is used with permission.
A selection of the common review types found in the literature is presented and compared in the following table using the SALSA framework developed by Grant and Booth (2009).
Name
Description
Search
Appraisal
Synthesis
Analysis
Critical review
Aims to demonstrate writer has extensively researched literature and critically evaluated its quality. Goes beyond mere description to include degree of analysis and conceptual innovation. Typically results in hypothesis or mode.
Seeks to identify most significant items in the field.
No formal quality assessment. Attempts to evaluate according to contribution.
No formal quality assessment. Attempts to evaluate according to contribution.
Significant component: seeks to identify conceptual contribution to embody existing or derive new theory.
Literature review
Generic term: published materials that provide examination of recent or current literature. Can cover wide range of subjects at various levels of completeness and comprehensiveness. May include research findings.
May or may not include comprehensive searching.
May or may not include quality assessment.
Typically narrative.
Analysis may be chronological, conceptual, thematic, etc.
Mapping review/ systematic map
Map out and categorize existing literature from which to commission further reviews and/or primary research by identifying gaps in research literature.
Completeness of searching determined by time/scope constraints.
No formal quality assessment.
May be graphical and tabular.
Characterizes quantity and quality of literature, perhaps by study design and other key features. May identify need for primary or secondary research.
Meta-analysis
Technique that statistically combines the results of quantitative studies to provide a more precise effect of the results. Often used within a systematic review.
Aims for exhaustive, comprehensive searching. May use funnel plot to assess completeness.
Quality assessment may determine inclusion/ exclusion and/or sensitivity analyses.
Graphical and tabular with narrative commentary.
Numerical analysis of measures of effect assuming absence of heterogeneity.
Mixed Methods Review
Refers to a combination of review approaches for example combining quantitative with qualitative research or outcome with process studies.
Requires either very sensitive search to retrieve all studies or separately conceived quantitative and qualitative strategies.
Requires either a generic appraisal instrument or separate appraisal processes with corresponding checklists.
Typically both components will be presented as narrative and in tables. May also employ graphical means of integrating quantitative and qualitative studies.
Analysis may characterise both literatures and look for correlations between characteristics or use gap analysis to identify aspects absent in one literature but missing in the other.
Overview
Generic term: summary of the [medical] literature that attempts to survey the literature and describe its characteristics.
May or may not include comprehensive searching (depends whether systematic overview or not).
May or may not include quality assessment (depends whether systematic overview or not).
Synthesis depends on whether systematic or not. Typically narrative but may include tabular features.
Analysis may be chronological, conceptual, thematic, etc.
Qualitative Review
Method for integrating or comparing the findings from qualitative studies. It looks for ‘themes’ or ‘constructs’ that lie in or across individual qualitative studies.
May employ selective or purposive sampling.
Quality assessment typically used to mediate messages not for inclusion/exclusion.
Qualitative, narrative synthesis.
Thematic analysis, may include conceptual models.
Rapid review
Assessment of what is already known about a policy or practice issue, by using systematic review methods to search and critically appraise existing research.
Completeness of searching variable, determined by time constraints.
Time-limited formal quality assessment.
Typically narrative and tabular.
Quantities of literature and overall quality/direction of effect of literature.
Scoping review
Preliminary assessment of potential size and scope of available research literature. Aims to identify nature and extent of research evidence (usually including ongoing research).
Completeness of searching determined by time/scope constraints. May include research in progress.
No formal quality assessment.
Typically tabular with some narrative commentary.
Characterizes quantity and quality of literature, perhaps by study design and other key features. Attempts to specify a viable review.
Adapted 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. https://doi.org/10.1111/j.1471-1842.2009.00848.x
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
Capstone and PICO Project Toolkit
Starting a Project: Overview
Developing a Research Question
Selecting Databases
Expanding a Search
Refining/Narrowing a Search
Saving Searches
Critical Appraisal & Levels of Evidence
Citing & Managing References
Database Tutorials
Types of Literature Reviews
Finding Full Text
Term Glossary
Choosing a Review Type
For guidance related to choosing a review type, see:
"What Type of Review is Right for You?" - Decision Tree (PDF) This decision tree, from Cornell University Library, highlights key difference between narrative, systematic, umbrella, scoping and rapid reviews.
Reviewing the literature: choosing a review design Noble, H., & Smith, J. (2018). Reviewing the literature: Choosing a review design. Evidence Based Nursing, 21(2), 39–41. https://doi.org/10.1136/eb-2018-102895
What synthesis methodology should I use? A review and analysis of approaches to research synthesis Schick-Makaroff, K., MacDonald, M., Plummer, M., Burgess, J., & Neander, W. (2016). What synthesis methodology should I use? A review and analysis of approaches to research synthesis. AIMS Public Health, 3 (1), 172-215. doi:10.3934/publichealth.2016.1.172 More information less... ABSTRACT: Our purpose is to present a comprehensive overview and assessment of the main approaches to research synthesis. We use "research synthesis" as a broad overarching term to describe various approaches to combining, integrating, and synthesizing research findings.
Right Review - Decision Support Tool Not sure of the most suitable review method? Answer a few questions and be guided to suitable knowledge synthesis methods. Updated in 2022 and featured in the Journal of Clinical Epidemiology 10.1016/j.jclinepi.2022.03.004
Types of Evidence Synthesis / Literature Reviews
Literature reviews are comprehensive summaries and syntheses of the previous research on a given topic. While narrative reviews are common across all academic disciplines, reviews that focus on appraising and synthesizing research evidence are increasingly important in the health and social sciences.
Most evidence synthesis methods use formal and explicit methods to identify, select and combine results from multiple studies, making evidence synthesis a form of meta-research.
The review purpose, methods used and the results produced vary among different kinds of literature reviews; some of the common types of literature review are detailed below.
Common Types of Literature Reviews 1
Narrative (literature) review.
A broad term referring to reviews with a wide scope and non-standardized methodology
Search strategies, comprehensiveness of literature search, time range covered and method of synthesis will vary and do not follow an established protocol
Integrative Review
A type of literature review based on a systematic, structured literature search
Often has a broadly defined purpose or review question
Seeks to generate or refine and theory or hypothesis and/or develop a holistic understanding of a topic of interest
Relies on diverse sources of data (e.g. empirical, theoretical or methodological literature; qualitative or quantitative studies)
Systematic Review
Systematically and transparently collects and categorize existing evidence on a question of scientific, policy or management importance
Follows a research protocol that is established a priori
Some sub-types of systematic reviews include: SRs of intervention effectiveness, diagnosis, prognosis, etiology, qualitative evidence, economic evidence, and more.
Time-intensive and often takes months to a year or more to complete
The most commonly referred to type of evidence synthesis; sometimes confused as a blanket term for other types of reviews
Meta-Analysis
Statistical technique for combining the findings from disparate quantitative studies
Uses statistical methods to objectively evaluate, synthesize, and summarize results
Often conducted as part of a systematic review
Scoping Review
Systematically and transparently collects and categorizes existing evidence on a broad question of scientific, policy or management importance
Seeks to identify research gaps, identify key concepts and characteristics of the literature and/or examine how research is conducted on a topic of interest
Useful when the complexity or heterogeneity of the body of literature does not lend itself to a precise systematic review
Useful if authors do not have a single, precise review question
May critically evaluate existing evidence, but does not attempt to synthesize the results in the way a systematic review would
May take longer than a systematic review
Rapid Review
Applies a systematic review methodology within a time-constrained setting
Employs methodological "shortcuts" (e.g., limiting search terms and the scope of the literature search), at the risk of introducing bias
Useful for addressing issues requiring quick decisions, such as developing policy recommendations
Umbrella Review
Reviews other systematic reviews on a topic
Often defines a broader question than is typical of a traditional systematic review
Most useful when there are competing interventions to consider
1. Adapted from:
Eldermire, E. (2021, November 15). A guide to evidence synthesis: Types of evidence synthesis. Cornell University LibGuides. https://guides.library.cornell.edu/evidence-synthesis/types
Nolfi, D. (2021, October 6). Integrative Review: Systematic vs. Scoping vs. Integrative. Duquesne University LibGuides. https://guides.library.duq.edu/c.php?g=1055475&p=7725920
Delaney, L. (2021, November 24). Systematic reviews: Other review types. UniSA LibGuides. https://guides.library.unisa.edu.au/SystematicReviews/OtherReviewTypes
Further Reading: Exploring Different Types of Literature Reviews
A typology of reviews: An analysis of 14 review types and associated methodologies Grant, M. J., & Booth, A. (2009). A typology of reviews: An analysis of 14 review types and associated methodologies. Health Information and Libraries Journal, 26 (2), 91-108. doi:10.1111/j.1471-1842.2009.00848.x More information less... ABSTRACT: The expansion of evidence-based practice across sectors has lead to an increasing variety of review types. However, the diversity of terminology used means that the full potential of these review types may be lost amongst a confusion of indistinct and misapplied terms. The objective of this study is to provide descriptive insight into the most common types of reviews, with illustrative examples from health and health information domains.
Clarifying differences between review designs and methods Gough, D., Thomas, J., & Oliver, S. (2012). Clarifying differences between review designs and methods. Systematic Reviews, 1 , 28. doi:10.1186/2046-4053-1-28 More information less... ABSTRACT: This paper argues that the current proliferation of types of systematic reviews creates challenges for the terminology for describing such reviews....It is therefore proposed that the most useful strategy for the field is to develop terminology for the main dimensions of variation.
Are we talking the same paradigm? Considering methodological choices in health education systematic review Gordon, M. (2016). Are we talking the same paradigm? Considering methodological choices in health education systematic review. Medical Teacher, 38 (7), 746-750. doi:10.3109/0142159X.2016.1147536 More information less... ABSTRACT: Key items discussed are the positivist synthesis methods meta-analysis and content analysis to address questions in the form of "whether and what" education is effective. These can be juxtaposed with the constructivist aligned thematic analysis and meta-ethnography to address questions in the form of "why." The concept of the realist review is also considered. It is proposed that authors of such work should describe their research alignment and the link between question, alignment and evidence synthesis method selected.
Meeting the review family: Exploring review types and associated information retrieval requirements Sutton, A., Clowes, M., Preston, L., & Booth, A. (2019). Meeting the review family: Exploring review types and associated information retrieval requirements. Health Information & Libraries Journal, 36(3), 202–222. doi: 10.1111/hir.12276
Integrative Reviews
"The integrative review method is an approach that allows for the inclusion of diverse methodologies (i.e. experimental and non-experimental research)." (Whittemore & Knafl, 2005, p. 547).
The integrative review: Updated methodology Whittemore, R., & Knafl, K. (2005). The integrative review: Updated methodology. Journal of Advanced Nursing, 52 (5), 546–553. doi:10.1111/j.1365-2648.2005.03621.x More information less... ABSTRACT: The aim of this paper is to distinguish the integrative review method from other review methods and to propose methodological strategies specific to the integrative review method to enhance the rigour of the process....An integrative review is a specific review method that summarizes past empirical or theoretical literature to provide a more comprehensive understanding of a particular phenomenon or healthcare problem....Well-done integrative reviews present the state of the science, contribute to theory development, and have direct applicability to practice and policy.
Conducting integrative reviews: A guide for novice nursing researchers Dhollande, S., Taylor, A., Meyer, S., & Scott, M. (2021). Conducting integrative reviews: A guide for novice nursing researchers. Journal of Research in Nursing, 26(5), 427–438. https://doi.org/10.1177/1744987121997907
Rigour in integrative reviews Whittemore, R. (2007). Rigour in integrative reviews. In C. Webb & B. Roe (Eds.), Reviewing Research Evidence for Nursing Practice (pp. 149–156). John Wiley & Sons, Ltd. https://doi.org/10.1002/9780470692127.ch11
Scoping Reviews
Scoping reviews are evidence syntheses that are conducted systematically, but begin with a broader scope of question than traditional systematic reviews, allowing the research to 'map' the relevant literature on a given topic.
Scoping studies: Towards a methodological framework Arksey, H., & O'Malley, L. (2005). Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology, 8 (1), 19-32. doi:10.1080/1364557032000119616 More information less... ABSTRACT: We distinguish between different types of scoping studies and indicate where these stand in relation to full systematic reviews. We outline a framework for conducting a scoping study based on our recent experiences of reviewing the literature on services for carers for people with mental health problems.
Scoping studies: Advancing the methodology Levac, D., Colquhoun, H., & O'Brien, K. K. (2010). Scoping studies: Advancing the methodology. Implementation Science, 5 (1), 69. doi:10.1186/1748-5908-5-69 More information less... ABSTRACT: We build upon our experiences conducting three scoping studies using the Arksey and O'Malley methodology to propose recommendations that clarify and enhance each stage of the framework.
Methodology for JBI scoping reviews Peters, M. D. J., Godfrey, C. M., McInerney, P., Baldini Soares, C., Khalil, H., & Parker, D. (2015). The Joanna Briggs Institute reviewers’ manual: Methodology for JBI scoping reviews [PDF]. Retrieved from The Joanna Briggs Institute website: http://joannabriggs.org/assets/docs/sumari/Reviewers-Manual_Methodology-for-JBI-Scoping-Reviews_2015_v2.pdf More information less... ABSTRACT: Unlike other reviews that address relatively precise questions, such as a systematic review of the effectiveness of a particular intervention based on a precise set of outcomes, scoping reviews can be used to map the key concepts underpinning a research area as well as to clarify working definitions, and/or the conceptual boundaries of a topic. A scoping review may focus on one of these aims or all of them as a set.
Systematic vs. Scoping Reviews: What's the Difference?
YouTube Video 4 minutes, 45 seconds
Rapid Reviews
Rapid reviews are systematic reviews that are undertaken under a tighter timeframe than traditional systematic reviews.
Evidence summaries: The evolution of a rapid review approach Khangura, S., Konnyu, K., Cushman, R., Grimshaw, J., & Moher, D. (2012). Evidence summaries: The evolution of a rapid review approach. Systematic Reviews, 1 (1), 10. doi:10.1186/2046-4053-1-10 More information less... ABSTRACT: Rapid reviews have emerged as a streamlined approach to synthesizing evidence - typically for informing emergent decisions faced by decision makers in health care settings. Although there is growing use of rapid review "methods," and proliferation of rapid review products, there is a dearth of published literature on rapid review methodology. This paper outlines our experience with rapidly producing, publishing and disseminating evidence summaries in the context of our Knowledge to Action (KTA) research program.
What is a rapid review? A methodological exploration of rapid reviews in Health Technology Assessments Harker, J., & Kleijnen, J. (2012). What is a rapid review? A methodological exploration of rapid reviews in Health Technology Assessments. International Journal of Evidence‐Based Healthcare, 10 (4), 397-410. doi:10.1111/j.1744-1609.2012.00290.x More information less... ABSTRACT: In recent years, there has been an emergence of "rapid reviews" within Health Technology Assessments; however, there is no known published guidance or agreed methodology within recognised systematic review or Health Technology Assessment guidelines. In order to answer the research question "What is a rapid review and is methodology consistent in rapid reviews of Health Technology Assessments?", a study was undertaken in a sample of rapid review Health Technology Assessments from the Health Technology Assessment database within the Cochrane Library and other specialised Health Technology Assessment databases to investigate similarities and/or differences in rapid review methodology utilised.
Rapid Review Guidebook Dobbins, M. (2017). Rapid review guidebook. Hamilton, ON: National Collaborating Centre for Methods and Tools.
NCCMT Summary and Tool for Dobbins' Rapid Review Guidebook National Collaborating Centre for Methods and Tools. (2017). Rapid review guidebook. Hamilton, ON: McMaster University. Retrieved from http://www.nccmt.ca/knowledge-repositories/search/308
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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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v.37(16); 2022 Apr 25
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 .
Quantitative research questions
Quantitative research hypotheses
Descriptive research questions
Simple hypothesis
Comparative research questions
Complex hypothesis
Relationship research questions
Directional hypothesis
Non-directional hypothesis
Associative hypothesis
Causal hypothesis
Null hypothesis
Alternative hypothesis
Working hypothesis
Statistical hypothesis
Logical hypothesis
Hypothesis-testing
Qualitative research questions
Qualitative research hypotheses
Contextual research questions
Hypothesis-generating
Descriptive research questions
Evaluation research questions
Explanatory research questions
Exploratory research questions
Generative research questions
Ideological research questions
Ethnographic research questions
Phenomenological research questions
Grounded theory questions
Qualitative case study questions
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 .
Quantitative research questions
Descriptive research question
- Measures responses of subjects to variables
- Presents variables to measure, analyze, or assess
What is the proportion of resident doctors in the hospital who have mastered ultrasonography (response of subjects to a variable) as a diagnostic technique in their clinical training?
Comparative research question
- Clarifies difference between one group with outcome variable and another group without outcome variable
Is there a difference in the reduction of lung metastasis in osteosarcoma patients who received the vitamin D adjunctive therapy (group with outcome variable) compared with osteosarcoma patients who did not receive the vitamin D adjunctive therapy (group without outcome variable)?
- Compares the effects of variables
How does the vitamin D analogue 22-Oxacalcitriol (variable 1) mimic the antiproliferative activity of 1,25-Dihydroxyvitamin D (variable 2) in osteosarcoma cells?
Relationship research question
- Defines trends, association, relationships, or interactions between dependent variable and independent variable
Is there a relationship between the number of medical student suicide (dependent variable) and the level of medical student stress (independent variable) in Japan during the first wave of the COVID-19 pandemic?
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 .
Quantitative research hypotheses
Simple hypothesis
- Predicts relationship between single dependent variable and single independent variable
If the dose of the new medication (single independent variable) is high, blood pressure (single dependent variable) is lowered.
Complex hypothesis
- Foretells relationship between two or more independent and dependent variables
The higher the use of anticancer drugs, radiation therapy, and adjunctive agents (3 independent variables), the higher would be the survival rate (1 dependent variable).
Directional hypothesis
- Identifies study direction based on theory towards particular outcome to clarify relationship between variables
Privately funded research projects will have a larger international scope (study direction) than publicly funded research projects.
Non-directional hypothesis
- Nature of relationship between two variables or exact study direction is not identified
- Does not involve a theory
Women and men are different in terms of helpfulness. (Exact study direction is not identified)
Associative hypothesis
- Describes variable interdependency
- Change in one variable causes change in another variable
A larger number of people vaccinated against COVID-19 in the region (change in independent variable) will reduce the region’s incidence of COVID-19 infection (change in dependent variable).
Causal hypothesis
- An effect on dependent variable is predicted from manipulation of independent variable
A change into a high-fiber diet (independent variable) will reduce the blood sugar level (dependent variable) of the patient.
Null hypothesis
- A negative statement indicating no relationship or difference between 2 variables
There is no significant difference in the severity of pulmonary metastases between the new drug (variable 1) and the current drug (variable 2).
Alternative hypothesis
- Following a null hypothesis, an alternative hypothesis predicts a relationship between 2 study variables
The new drug (variable 1) is better on average in reducing the level of pain from pulmonary metastasis than the current drug (variable 2).
Working hypothesis
- A hypothesis that is initially accepted for further research to produce a feasible theory
Dairy cows fed with concentrates of different formulations will produce different amounts of milk.
Statistical hypothesis
- Assumption about the value of population parameter or relationship among several population characteristics
- Validity tested by a statistical experiment or analysis
The mean recovery rate from COVID-19 infection (value of population parameter) is not significantly different between population 1 and population 2.
There is a positive correlation between the level of stress at the workplace and the number of suicides (population characteristics) among working people in Japan.
Logical hypothesis
- Offers or proposes an explanation with limited or no extensive evidence
If healthcare workers provide more educational programs about contraception methods, the number of adolescent pregnancies will be less.
- This involves the formation of a hypothesis, collection of data in the investigation of the problem, analysis and use of the data from the investigation, and drawing of conclusions to validate or nullify the hypotheses.
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 research questions
Contextual research question
- Ask the nature of what already exists
- Individuals or groups function to further clarify and understand the natural context of real-world problems
What are the experiences of nurses working night shifts in healthcare during the COVID-19 pandemic? (natural context of real-world problems)
Descriptive research question
- Aims to describe a phenomenon
What are the different forms of disrespect and abuse (phenomenon) experienced by Tanzanian women when giving birth in healthcare facilities?
Evaluation research question
- Examines the effectiveness of existing practice or accepted frameworks
How effective are decision aids (effectiveness of existing practice) in helping decide whether to give birth at home or in a healthcare facility?
Explanatory research question
- Clarifies a previously studied phenomenon and explains why it occurs
Why is there an increase in teenage pregnancy (phenomenon) in Tanzania?
Exploratory research question
- Explores areas that have not been fully investigated to have a deeper understanding of the research problem
What factors affect the mental health of medical students (areas that have not yet been fully investigated) during the COVID-19 pandemic?
Generative research question
- Develops an in-depth understanding of people’s behavior by asking ‘how would’ or ‘what if’ to identify problems and find solutions
How would the extensive research experience of the behavior of new staff impact the success of the novel drug initiative?
Ideological research question
- Aims to advance specific ideas or ideologies of a position
Are Japanese nurses who volunteer in remote African hospitals able to promote humanized care of patients (specific ideas or ideologies) in the areas of safe patient environment, respect of patient privacy, and provision of accurate information related to health and care?
Ethnographic research question
- Clarifies peoples’ nature, activities, their interactions, and the outcomes of their actions in specific settings
What are the demographic characteristics, rehabilitative treatments, community interactions, and disease outcomes (nature, activities, their interactions, and the outcomes) of people in China who are suffering from pneumoconiosis?
Phenomenological research question
- Knows more about the phenomena that have impacted an individual
What are the lived experiences of parents who have been living with and caring for children with a diagnosis of autism? (phenomena that have impacted an individual)
Grounded theory question
- Focuses on social processes asking about what happens and how people interact, or uncovering social relationships and behaviors of groups
What are the problems that pregnant adolescents face in terms of social and cultural norms (social processes), and how can these be addressed?
Qualitative case study question
- Assesses a phenomenon using different sources of data to answer “why” and “how” questions
- Considers how the phenomenon is influenced by its contextual situation.
How does quitting work and assuming the role of a full-time mother (phenomenon assessed) change the lives of women in Japan?
- This involves data collection from study participants or the literature regarding a phenomenon of interest, using the collected data to develop a formal hypothesis, and using the formal hypothesis as a framework for testing the hypothesis.
- Qualitative exploratory studies explore areas deeper, clarifying subjective experience and allowing formulation of a formal hypothesis potentially testable in a future quantitative approach.
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.
Variables
Unclear and weak statement (Statement 1)
Clear and good statement (Statement 2)
Points to avoid
Research question
Which is more effective between smoke moxibustion and smokeless moxibustion?
“Moreover, regarding smoke moxibustion versus smokeless moxibustion, it remains unclear which is more effective, safe, and acceptable to pregnant women, and whether there is any difference in the amount of heat generated.”
1) Vague and unfocused questions
2) Closed questions simply answerable by yes or no
3) Questions requiring a simple choice
Hypothesis
The smoke moxibustion group will have higher cephalic presentation.
“Hypothesis 1. The smoke moxibustion stick group (SM group) and smokeless moxibustion stick group (-SLM group) will have higher rates of cephalic presentation after treatment than the control group.
1) Unverifiable hypotheses
Hypothesis 2. The SM group and SLM group will have higher rates of cephalic presentation at birth than the control group.
2) Incompletely stated groups of comparison
Hypothesis 3. There will be no significant differences in the well-being of the mother and child among the three groups in terms of the following outcomes: premature birth, premature rupture of membranes (PROM) at < 37 weeks, Apgar score < 7 at 5 min, umbilical cord blood pH < 7.1, admission to neonatal intensive care unit (NICU), and intrauterine fetal death.”
3) Insufficiently described variables or outcomes
Research objective
To determine which is more effective between smoke moxibustion and smokeless moxibustion.
“The specific aims of this pilot study were (a) to compare the effects of smoke moxibustion and smokeless moxibustion treatments with the control group as a possible supplement to ECV for converting breech presentation to cephalic presentation and increasing adherence to the newly obtained cephalic position, and (b) to assess the effects of these treatments on the well-being of the mother and child.”
1) Poor understanding of the research question and hypotheses
2) Insufficient description of population, variables, or study outcomes
a These statements were composed for comparison and illustrative purposes only.
b These statements are direct quotes from Higashihara and Horiuchi. 16
Variables
Unclear and weak statement (Statement 1)
Clear and good statement (Statement 2)
Points to avoid
Research question
Does disrespect and abuse (D&A) occur in childbirth in Tanzania?
How does disrespect and abuse (D&A) occur and what are the types of physical and psychological abuses observed in midwives’ actual care during facility-based childbirth in urban Tanzania?
1) Ambiguous or oversimplistic questions
2) Questions unverifiable by data collection and analysis
Hypothesis
Disrespect and abuse (D&A) occur in childbirth in Tanzania.
Hypothesis 1: Several types of physical and psychological abuse by midwives in actual care occur during facility-based childbirth in urban Tanzania.
1) Statements simply expressing facts
Hypothesis 2: Weak nursing and midwifery management contribute to the D&A of women during facility-based childbirth in urban Tanzania.
2) Insufficiently described concepts or variables
Research objective
To describe disrespect and abuse (D&A) in childbirth in Tanzania.
“This study aimed to describe from actual observations the respectful and disrespectful care received by women from midwives during their labor period in two hospitals in urban Tanzania.”
1) Statements unrelated to the research question and hypotheses
2) Unattainable or unexplorable objectives
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.
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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
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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'Qualitative' and 'quantitative' methods and approaches across subject fields: implications for research values, assumptions, and practices
Open access
Published: 30 September 2023
Volume 58 , pages 2357–2387, ( 2024 )
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Nick Pilcher ORCID: orcid.org/0000-0002-5093-9345 1 &
Martin Cortazzi 2
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There is considerable literature showing the complexity, connectivity and blurring of 'qualitative' and 'quantitative' methods in research. Yet these concepts are often represented in a binary way as independent dichotomous categories. This is evident in many key textbooks which are used in research methods courses to guide students and newer researchers in their research training. This paper analyses such textbook representations of 'qualitative' and 'quantitative' in 25 key resources published in English (supported by an outline survey of 23 textbooks written in German, Spanish and French). We then compare these with the perceptions, gathered through semi-structured interviews, of university researchers (n = 31) who work in a wide range of arts and science disciplines. The analysis of what the textbooks say compared to what the participants report they do in their practice shows some common features, as might be assumed, but there are significant contrasts and contradictions. The differences tend to align with some other recent literature to underline the complexity and connectivity associated with the terms. We suggest ways in which future research methods courses and newer researchers could question and positively deconstruct such binary representations in order to free up directions for research in practice, so that investigations can use both quantitative or qualitative approaches in more nuanced practices that are appropriate to the specific field and given context of investigations.
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1 Introduction: qualitative and quantitative methods, presentations, and practices
Teaching in research methods courses for undergraduates, postgraduates and newer researchers is commonly supported or guided through textbooks with explanations of 'qualitative' and 'quantitative' methods and cases of how these methods are employed. Student dissertations and theses commonly include methodology chapters closely aligned with these textbook representations. Unexceptionally, dissertations and theses we supervise and examine internationally have methodology chapters and frequently these consider rationales and methods associated with positivist or interpretivist paradigms. Within such positivist or interpretivist frameworks, research approaches are amplified with elaborations of the rationale, the methods, and reasons for their choice over likely alternatives. In an apparent convention, related data are assigned as quantitative or qualitative in nature, with associated labelling as ‘numerical’ or ‘textual'. The different types of data yield different values and interpretive directions, and are clustered conceptually with particular research traditions, approaches, and fields or disciplines. Frequently, these clusters are oriented around 'quantitative' and 'qualitative' conceptualizations.
This paper seeks to show how ‘qualitative’ and ‘quantitative’, whether stereotyped or more nuanced, as binary divisions as presented in textbooks and published resources describing research methods may not always accord with the perceptions and day-to-day practices of university researchers. Such common binary representations of quantitative and qualitative and their associated concepts may hide complexities, some of which are outlined below. Any binary divide between ‘qualitative’ and ‘quantitative’ needs caution to show complexity and awareness of disparities with some researchers’ practices.
To date, as far as the present authors are aware, no study has first identified a range of binary representations of ‘quantitative’ and ‘qualitative’ methods and approaches in a literature review study of the many research methods textbooks and sources which guide students and then, secondly, undertaken an interview study with a range of established participant researchers in widely divergent fields to seek their understandings of ‘quantitative’ and ‘qualitative’ in their own fields. The findings related here complement and extend the complexities and convergences of understanding the concepts in different disciplines. Arguably, this paper demonstrates how students and novice researchers should not be constrained in their studies by any binary representations of ‘quantitative’ and ‘qualitative’ the terms. They should feel free to use either (or neither) or both in strategic combinations, as appropriate to their fields.
1.1 Presentations
Characteristically, presentations in research methods textbooks distinguish postivist and interpretivist approaches or paradigms (e.g. Guba and Lincoln 1994 ; Howe 1988 ; Denzin and Lincoln 2011 ) or ‘two cultures’ (Goertz and Mahoney 2012 ) with associated debates or ‘wars’ (e.g. Creswell 1995 ; Morse 1991 ). Quantitative data are shown as ‘numbers’ gathered through experiments (Moore 2006 ) or mathematical models (Denzin and Lincoln 1998 ), whereas qualitative data are usually words or texts (Punch 2005 ; Goertz and Mahoney 2012 ), characteristically gathered through interviews or life stories (Denzin and Lincoln 2011 ). Regarding analysis, some sources claim that establishing objective causal relationships is key in quantitative analysis (e.g. Goertz and Mahoney 2012 ) whereas qualitative analysis uses more discursive and interpretative procedures.
Thus, much literature presents research in terms of two generally distinct methods—quantitative and qualitative—which many students are taught in research methods courses. The binary divide may seem to be legitimated in the titles of many academic journals. This division prevails as designated strands of separated research methods in courses which apparently handle both (cf. Onwuegbuzie and Leech 2005 ). Consequently, students may follow this seemingly stereotyped binary view or feel uncomfortable to deviate from it. Arguably, PhD candidates need to demonstrate understanding of such concepts and procedures in a viva—or risk failure (cf. Trafford and Leshem 2002 ). The Cambridge Dictionary defines ‘quality’ as “how good or bad something is”; while ‘quantity' is “the amount or number of something, especially that can be measured” (Cambridge 2022 ). But definitions of ‘Qualitative' can be elusive, since “a precise definition of qualitative research, and specifically… its distinctive feature of being “qualitative”, the literature is meager” (Aspers and Corte 2019 , p.139). Some observe a “paradox… that researchers act as if they know what it is, but they cannot formulate a definition” and that “there is no consensus about specific qualitative methods nor… data” (Aspers and Corte 2019 , p40). In general, ‘qualitative research’ is an iterative process to discover more about a phenomenon (ibid.). Elsewhere, 'qualitative’ is defined negatively: "It is research that does not use numbers” (Seale 1999b , p.119). But this oversimplifies and hides possible disciplinary variation. For example, when investigating criminal action, numeric information (quantity) always follows an interpretation (De Gregorio 2014 ), and consequently this is a quantity of a quality (cf. Uher 2022 ).
Indeed, many authorities note the presence of elements of one in the other. For example, in analysis specifically, that what are considered to be quantitative elements such as statistics are used in qualitative analysis (Miles and Huberman 1994 ). More generically, that “a qualitative dimension is present in quantitative work as well” (Aspers and Corte 2019 , p.139). In ‘mixed methods’ research (cf. Tashakkori et al. 1998 ; Johnson et al. 2007 ; Teddlie and Tashakkori 2011 ) many researchers ‘mix’ the two approaches (Seale 1999a ; Mason 2006 ; Dawson 2019 ), either using multiple methods concurrently, or doing so sequentially. Mixed method research logically depends on prior understandings of quantitative and qualitative concepts but this is not always obvious (e.g. De Gregorio 2014 ); for instance Heyvaert et al. ( 2013 ) define mixed methods as combining quantitative and qualitative items, but these key terms are left undefined. Some commentators characterize such mixing as a skin, not a sweater to be changed every day (Marsh and Furlong 2002 , cited in Grix 2004 ). In some disciplines, these terms are often blurred, interchanged or conjoined. In sociology, for instance, “any quality can be quantified. Any quantity is a quality of a social context, quantity versus quality is therefore not a separation” (Hanson 2008 , p.102) and characterizing quantitative as ‘objective’ and qualitative as ‘subjective’ is held to be false when seeking triangulation (Hanson 2008 ). Additionally, approaches to measuring and generating quantitative numerical information can differ in social sciences compared to physics (Uher 2022 ). Indeed, quantity may consist of ‘a multitude’ of divisible aspects and a ‘magnitude’ for indivisible aspects (Uher 2022 ). Notably, “the terms ‘measurement’ and ‘quantification’ have different meanings and are therefore prone to jingle-jangle fallacies” (Uher 2022 ) where individuals use the same words to denote different understandings (cf. Bakhtin 1986 ). Comparatively, the words ‘unit’ and ‘scale’ are multitudinous in different sciences, and the key principles of numerical traceability and data generation traceability arguably need to be applied more to social sciences and psychology (Uher 2022 ). The interdependence of the terms means any quantity is grounded in a quality of something, even if the inverse does not always apply (Uher 2022 ).
1.2 Practices
The present paper compares representations found in research methods textbooks with the reported practices of established researchers given in semi-structured interviews. The differences revealed between what the literature review of methods texts showed and what the interview study showed both underlines and extends this complexity, with implications for how such methodologies are approached and taught. The interview study data (analysed below) show that many participant researchers in disciplines commonly located within an ostensibly ‘positivist’ scientific tradition (e.g. chemistry) are, in fact, using qualitative methods as scientific procedures (contra Tashakkori et al 1998 ; Guba and Lincoln 1994 ; Howe 1988 ; Lincoln and Guba 1985 ; Teddlie and Tashakkori 2011 ; Creswell 1995 ; Morse 1991 ). These interview study data also show that many participant researchers use what they describe as qualitative approaches to provide initial measurements (geotechnics; chemistry) of phenomena before later using quantitative procedures to measure the quantity of a quality (cf. Uher 2022 ). Some participant researchers also say they use quantitative procedures to reveal data for which they subsequently use qualitative approaches to interpret and understand (biology; dendrology) through their creative imaginations or experience (contra e.g. Hammersley, 2013 ). Participant researchers in ostensibly ‘positivist’ areas describe themselves as doubting ‘facts’ measured by machines programmed by humans (thus showing they feel researchers are not outside the world looking in (contra. e.g. Punch 2005 )) or doubting the certainty of quantitative data over time (contra e.g. Punch 2005 ). Critically, the interview study data show that these participant researchers often engage in debate over what a ‘number’ is and the extent to which ‘numbers’ can be considered ‘quantitative’. For example the data show how a mathematician considers that many individuals do not know what they mean by the word ‘quantitative’, and an engineer interprets any numbers involving human judgements as ‘qualitative’. Further, both a chemist and a geotechnician routinely define and use ‘qualitative’ methods and analysis to arrive at numerical values (contra. Davies and Hughes 2014 ; Denzin and Lincoln 2011 ).
Such data refute many textbook and key source representations of quantitative and qualitative as being binary and separately ringfenced entities as shown in the literature review study below (contra e.g. Punch 2005 ; Goertz and Mahoney 2012 ). Nevertheless, they resonate with much recent and current literature in the field (e.g. Uher 2022 ; De Gregorio 2014 ). They also arguably extend the complexities of the terms and approaches. In some disciplines, these participant researchers only do a particular type of research and never need anything other than clear ‘quantitative’ definitions (Mathematics), and some only ever conduct research involving text and never numbers (Literature). Moreover, some participant researchers consider certain aspects lie outside the ‘qualitative’ or ‘quantitative’ (the theoretical in German Literature), or do research which they maintain does not contain ‘knowledge’ (Fine-Art Sculpture), while others outline how they feel they do foundational conceptual research which they believe comes at a stage before any quantity or quality can be assessed (Philosophy). Indeed, of the 31 participant researchers we spoke to, nine of them considered the terms ‘quantitative’ and ‘qualitative’ to be of little relevance for their subject.
1.3 Outline of the two studies
This paper reports and discusses findings from a constructivist grounded approach interview study that interviewed experienced participant researchers (N = 31) in various disciplines (see Table 1 below) about their understandings of ‘qualitative’ and ‘quantitative’ in their subject areas. Findings from this interview study were compared with findings from a research methods literature review study that revealed many disparities with received and often binary presentations of the concepts in much key literature that informs student research methods courses. In this section we outline the review criteria, the method of analysis, and our findings. The findings are grouped according to how the sources reviewed consider ‘quantitative’ and ‘qualitative’ approaches the aspects of positivism and constructivism; the nature of research questions; research methods; analysis; issues of reliability, validity and generalizability; and the value and worth of the different approaches. Following this. We outline the approach, method, and procedure adopted for the interviews with research participants; sampling and saturation; and analysis; beside details of the participant researchers. Subsequently, Theme 2 focuses on contrasts of the interview data with ‘binary’ textbook and key source representations. Theme 3 focuses on what the interview data show about participant researcher perceptions of the value of ‘quantitative’ and ‘qualitative’ methods and approaches. This section outlines where, how, and sometimes why, participant researchers considered ‘quantitative’ and ‘qualitative’ methods approaches to be (or to not be) useful to them. These interview study findings show a surprising range of understandings, usage, and often perceived irrelevance of the terms. In the Discussion section, these findings form the focus of comparison with the literature as well as a consideration of possible implications for approaching and teaching research methods. In the conclusion we summarise the implications for research methods courses, for researchers in different disciplines and interdisciplinary contexts and discuss limitations and suggest future research. Besides adding to the debate on how ‘quantitative’ and ‘qualitative’ are conceptualized and how they are related, the paper appeals to those delivering research methods courses and to novice researchers to consider the concepts as highly complex and overlapping, to loosen constraints, and elaborate nuances of the commonplace binary representations of the terms.
2 Literature review study: some key textbooks and sources for teaching Research Methods.
2.1 review criteria.
To identify how concepts are presented in key materials we undertook a literature review study by consulting research methods course reading lists, library search engines, physically available shelves in institutional libraries, and Google Scholar. We wanted to encompass textbooks and some key texts which are recommended to UG, PG Masters and PhD students., for example, ‘textbooks’ like ‘Doing Your Research Project: A Guide for first-time researchers’ (Bell and Waters 2014 ) and ‘Introduction to Research Methods: A Practical Guide for Anyone Undertaking a Research project (5th Edition)’ (Dawson 2019 ). Such sources were frequently mentioned on reading lists and are freely available in many institutional libraries. We consulted seminal thinkers who have published widely on research methods, such as Denzin and Lincoln, or Cresswell, but we also considered texts which are likely less known such as ‘A tale of two cultures’ (Goertz and Mahoney 2012 ) and key articles such as ‘Five misunderstandings about case-study research’ (Flyvbjerg 2006 ). Students can freely find such sources, and are easily directed to them by supervisors. Although a more comprehensively robust search is possible, we nevertheless followed procedures and standard criteria for literature reviews (Atkinson et al. 2015 ).
3 Method of analysis
We assembled a total of 25 sources to look for a number of key tenets. We examined the sources for occurrence of the following: whether quantitative was described as positivist and qualitative was described as constructivist; whether quantitative was said to be science-based and qualitative was more reflective and non-science based; whether the research questions were presented as predetermined in quantitative methods and initially less focused in qualitative methods; whether quantitative methods were structured and qualitative methods were discussed as less structured; whether quantitative analysis focused on cause-effect type relationships and qualitative analysis was more exploratory; whether reliability, validity and generalizability were achieved through large numbers in quantitative research and through in-depth study in qualitative research; whether for particular subjects such as the sciences quantitative approaches were perceived to be of value (and qualitative was implied to have less value) and whether the converse was the case for other subjects such as history and anthropology; and whether mixed methods were considered possible or not possible. The 25 sources are detailed in Appendix 1 . As a confirmatory but less detailed exercise, and also detailed in Appendix 1 , we checked a further 23 research methods textbooks in German, Spanish and French, authored in those languages (rather than translations from English).
3.1 Findings
Overall, related to what quantitative and qualitative approaches, methods and analysis are, we found many key, often binary representations in this literature review. We outline these here below.
3.2 Positivism and constructivism
Firstly, 20 of the sources we reviewed stated that quantitative is considered positivist, and qualitative constructivist (e.g. Tashakkori et al 1998 ; Guba and Lincoln 1994 ; Howe 1988 ; Lincoln and Guba 1985 ; Teddlie and Tashakkori 2011 ; Creswell 1995 ; Morse 1991 ). Even if not everyone doing quantitative research (e.g. in sociology) consider themselves positivists (Marsh 1979 ), it is generally held quantitative research is positivist. Here, 12 of the sources noted that quantitative is considered ‘scientific’, situating observers outside the world looking in, e.g. through gathering numerical data (Punch 2005 ; Davis and Hughes 2014 ) whereas qualitative “locates the observer in the world” (Denzin and Lincoln 2011 , p.3). Quantitative researchers “collect facts and study the relationship of one set of facts to another”, whereas qualitative researchers “doubt whether social ‘facts’ exist and question whether a ‘scientific’ approach can be used when dealing with human beings” (Bell and Waters 2014 , p. 9).
3.3 The nature of research questions
Secondly, regarding research questions, “qualitative research… typically has… questions and methods… more general at the start, and… more focused as the study progresses” (Punch 2005 , p.28). In contrast, quantitative research uses “numerical data and typically… structured and predetermined research questions, conceptual frameworks and designs” (Punch 2005 , p.28). Of the sources we reviewed, 16 made such assertions. This understanding relates to type, and nature, of data, which is in turn anchored to particular worldviews. Punch ( 2005 , p 3–4) writes of how “in teaching about research, I find it useful to approach the qualitative-quantitative distinction primarily through…. the nature of the data. Later, the distinction can be broadened to include …. ways of conceptualising the reality being studied, and methods.” Here, the nature of data influences approach: numbers are for quantitative, and not-numbers (commonly words) for qualitative. Similarly, for Miles et al. ( 2018 ) “the nature of qualitative data” is “primarily on data in the form of words, that is, language in the form of extended text” (Miles et al. 2018 , no page). These understandings in turn relate to methods used.
Commonly, specific types of methods are said to be related to the type of approach adopted, and 18 of the sources we reviewed presented quantitative methods as being structured, and qualitative methods as less structured. For example, Davies and Hughes ( 2014 , p.23) claim “there are two principal options open to you: 1… quantitative research methods, using the traditions of science. 2… qualitative research, employing a more reflective or exploratory approach.” Here, quantitative methods are “questionnaires or structured interviews” whereas qualitative methods are “such as interviews or focus groups” (Dawson 2019 , no page given). Quantitative methods are more scientific, involve controlling a set of variables, and may involve experiments, something which, “qualitative researchers are agreed in their opposition to this definition of scientific research, or at least its application to social inquiry” (Hammersley 2013 , p. ix). As Punch notes ( 2005 , p.208), “the experiment was seen as the basis for establishing cause-effect relationships between variables, and its outcome (and control) variables had to be measured.”
4.1 Analysis
Such understandings often relate to analysis, and 16 of the sources we reviewed presented quantitative analysis as being statistical and number related, and qualitative analysis as being text based. With quantitative methods, “the data is subjected to statistical analysis, using techniques… likely to produce quantified, and, if possible, generalizable conclusions” (Bell and Waters 2014 , p.281). With qualitative research, however, this “calls for advanced skills in data management and text-driven creativity during the analysis and write-up” (Davies and Hughes 2014 ). Again, the data’s nature is key, and whilst qualitative analysis may condense data, it does not seek numbers. Indeed, “by data condensation, we do not necessarily mean quantification”, however, “occasionally, it may be helpful to convert the data into magnitudes… but this is not always necessary” (Miles et al. 2018 , npg). Qualitative analysis may involve stages such as assigning codes, subsequently sorting and sifting them, isolating patterns, then gradually refining any assertions made and comparing them to other literature (Miles et al. 2018 ). This could involve condensing, displaying, then drawing conclusions from the data (Miles et al. 2018 ). In this respect, some sources consider qualitative and quantitative analysis broadly similar in overall goals, yet different because quantitative analyses use “well-defined, familiar methods; are guided by canons; and are usually more sequential than iterative or cyclical” (Miles et al. 2018 , npg). In contrast, “qualitative researchers are… more fluid and… humanistic” in meaning making (Miles et al. 2018 , npg). Here, both approaches seek causation and may attempt to reveal ‘cause and effect’ but qualitative approaches often seek multiple and interacting influences, and effects and are less rigid (Miles et al. 2018 ). In quantitative inquiry search for causation relates to “causal mechanisms (i.e. how did X cause Y)” whereas in “the human sciences, this distinction relates to causal effects (i.e. whether X causes Y)” (Teddlie and Tashakkori 2011 , p.286). Similarly, that “scientific research in any area… seeks to trace out cause-effect relationships” (Punch 2005 , p.78). In contrast, qualitative research seeks interpretative understandings of human behaviour, “not ‘caused’ in any mechanical way, but… continually constructed and reconstructed” (Punch 2005 , p.126).
4.2 Issues of reliability, validity and generalizability
Regarding reliability, validity and generalizability, 19 of the sources we reviewed presented ideas along the lines that quantitative research is understood to seek large numbers, so quantitative researchers, “use techniques… likely to produce quantified and, if possible, generalizable conclusions (Bell and Waters 2014 , p.9). This means quantitative “research researches many more people” (Dawson 2019 , npg). Given quantitative researchers aim, “to discover answers to questions through the application of scientific procedures” it is anticipated these procedures will “increase the likelihood that the information… will be reliable and unbiased” (Davies and Hughes 2014 , p.9). Conversely, qualitative researchers are considered “more concerned to understand individuals’ perceptions of the world” (Bell and Waters 2014 , p.281) and consequently aim for in-depth data with smaller numbers, “as it is attitudes, behaviour and experiences that are important” (Dawson 2019 , npg). Consequently, generalizability of data is not key, as qualitative research has its “emphasis on a specific case, a focused and bounded phenomenon embedded in its context” (Miles et al. 2018 , npg). Yet, such research is considered generalizable in theoretical insight if not actual data (Flyvbjerg 2006 ).
4.3 The value and worth of the different approaches
Regarding ‘value’ and ‘worth’, many see this related with appropriacy to the question being researched. Thus, if questions involve more quantitative approaches, then these are of value, and if more qualitative, then these are of value, and 6 of the sources we reviewed presented these views (e.g. Bell and Waters 2014 ; Punch 2005 ; Dawson 2019 ). This resonates with disciplinary orientations where choices between given approaches are valued more in specific disciplines. History and Anthropology are seen more qualitative, whereas Economics and Epidemiology may be more quantitative (Kumar 1996 ). Qualitative approaches are valuable to study human behaviour and reveal in-depth pictures of peoples’ lived experience (e.g. Denzin and Lincoln 2011 ; Miles et al. 2018 ). Many consider there to be no real inherent superiority for one approach over another, and “asking whether quantitative or qualitative research is superior to the other is not a useful question” (Goertz and Mahoney 2012 , p.2).
Nevertheless, some give higher pragmatic value to quantitative research for studying individuals and people; neoliberal governments consistently value quantitative over qualitative research (Barone 2007 ; Bloch 2004 ; St Pierre 2004 ). Concomitantly, data produced by qualitative research is criticised by quantitative proponents “because of their problematic generalizability” (Bloor and Wood 2006 , p.179). However, other studies find quantitative researchers see qualitative methods and approaches positively (Pilcher and Cortazzi 2016 ). Some even question the qualitative/quantitative divide, and suggest “a more subtle and realistic set of distinctions that capture variation in research practice better” (Hammersley 2013 , p.99).
The above literature review study of key texts is hardly exhaustive, but shows a general outline of the binary divisions and categorizations that exist in many sources students and newer researchers encounter. Thus, despite the complex and blurred picture as outlined in the introduction above, many key texts students consult and that inform research methods courses often present a binary understanding that quantitative is positivist, focused on determining cause and effect, numerical or magnitude focused, uses experiments, and is grounded in an understanding the world can be observed from the outside in. Conversely, qualitative tends to be constructivist, focused on determining why events occur, is word or textual based (even if these elements are measured by their magnitude in a number or numerical format) and grounded in understanding the researcher is part of the world. The sciences and areas such as economics are said to tend towards the quantitative, and areas such as history and anthropology towards the qualitative.
We also note that in our literature review study we focused on English language textbooks, but we also looked at outline details, descriptions, and contents lists of texts in the languages of German, Spanish and French. We find that these broadly confirm the perception of a division between quantitative and qualitative research, and we detail a number of these in Appendix 1 . These examples are all research methods handbooks and student guides intended for under and post-graduates in social sciences and humanities; many are inter-disciplinary but some are more specifically books devoted to psychology, health care, education, politics, and management. Among the textbooks and handbooks examined in other languages, more recent books pay attention to online research and uses of the internet, social media and sometimes to big data and software for data analysis.
In these sources in languages other than English we find massive predominance of two (quantitative/qualitative) or three approaches (mixed). These are invariably introduced and examined with related theories, examples and cases in exactly that order: quantitative; qualitative; mixed. Here there is perhaps the unexamined implication that this is a historical order of research method development and also of acceptability of use (depending on research purposes). Notably, Molina Marin (2020) is oriented to Latin America and makes the point that most European writing about research methods is in English or German, while there are far fewer publications in Spanish and few with Latin American contextual relevance, which may limit epistemological perspectives. This point is evident in French and Spanish publications (much less the case in German) where bibliographic details seem dominated by English language publications (or translations from them). We now turn to outline our interview study.
5 Interview study
5.1 approach and choice of method.
We approached our interview study from a constructivist standpoint of exploring and investigating different subject specialists’ understandings of quantitative and qualitative. Critically, we were guided by the key constructivist tenet that knowledge is not independent of subjects seeking it (Olssen 1996 ), nor of subjects using it. Extending from this we considered interviews more appropriate than narratives or focus groups. Given the exploratory nature of our study, we considered interviews most suited as we wanted to have a free dialogue (cf. Bakhtin 1981 ) regarding how the terms are understood in their subject contexts as opposed to their neutral dictionary definitions (Bakhtin 1986 ), and not to focus on a specific point with many individuals. Specifically, we used ‘semi’-structured interviews. ‘Semi’ can mean both ‘half in quantity or value’ but also ‘to some extent: partly: incompletely’ (e.g. Merriam Webster 2022 ). Our interviews, following our constructionist and exploratory approach, aligned with the latter definition (see Appendix 2 for the Interview study schedule). This loose ‘semi’ structure was deliberately designed to (and did) lead to interviews directed by the participants, who themselves often specifically asked what was meant by the questions. This created a highly technical dialogue (Buber, 1947) focused on the subject.
5.2 Sampling and saturation
Our sampling combined purposive and snowball sampling (Sharma 2017 ; Levitt et al. 2018 ). Initially, participants were purposively identified by subject given the project sought to understand different subject perspectives of ‘qualitative’ and ‘quantitative.’ Later, a combined purposive and snowball sampling technique was used whereby participants interviewed were asked if they knew others teaching particular subjects. Regarding priorities for participant eligibility, this was done according to subject, although generally participants also had extensive experience (see Table 1 ). For most, English was their first language, where it was not, participants were proficient in English. The language of interview choice was English as it was most familiar to both participants and interviewer (Cortazzi et al. 2011 ).
Regarding saturation, some argue saturation occurs within 12 interviews (Guest et al. 2006 ), others within 17 (Francis et al. 2010 ). Arguably, however, saturation cannot be determined in advance of analysis and is “inescapably situated and subjective” (Braun and Clarke 2021 , p.201). This critical role of subjectivity and context guided how we approached saturation, whereby it was “operationalized in a way consistent with the research question(s) and the theoretical position and analytic framework adopted” (Saunders et al. 2018 , p.1893). We recognise that more could always be found but are satisfied that 31 participants provided sufficient data for our investigation. Indeed, our original intention was to recruit 20 participants, feeling this would provide sufficient saturation (Francis et al. 2010 ; Guest et al. 2006 ) but when we reached 20, and as we had already started analysis (cf. Braun and Clarke 2021 ) as we ourselves transcribed the interviews (Bird 2005 ) we wanted to explore understandings of ‘qualitative’ and ‘quantitative’ with other subject fields. As Table 1 shows, ‘English Literature’, ‘Philosophy, and ‘Sculpture’ were only explored after interview 20. These additional subject fields added significantly (see below) to our data.
5.3 Analysis and participant researcher details
Our analysis followed Braun and Clarke’s ( 2006 ) thematic analysis. Given the study’s exploratory constructionist nature, we combined ‘top down’ deductive type analysis for anticipated themes, and ‘bottom up’ inductive type analysis for any unexpected themes. The latter was similar to a constructivist grounded theory analysis (Charmaz 2010 ) whereby the transcripts were explored through close repeated reading for themes to emerge from the bottom up. We deliberately did not use any CAQDAS software such as NVivo as we wanted to manually read the scripts in one lengthy word document. We recognise that such software could allow us to do this but we were familiar with the approach we used and have found it effective for a number of years. We thus continued to use it here as well. We counted instances of themes through cross-checking after reading transcripts and discussing them, thereby heightening reliability and validity (Golafshani 2003 ). All interviews were undertaken with informed consent and participants were assured all representation was anonymous (Christians 2011 ). The study was approved by relevant ethics committees. Table 1 above shows the subject area, years of experience, and first language of the participant researchers. We also bracket after each subject area whether we consider it to be ‘Science’ or ‘Arts’ or whether we consider them as ‘Arts/Science’ or ‘Science/Arts’. This is of course subjective and in many ways not possible to do, but we were guided in how we categorised these subjects by doing so according to how we feel the methodology sources form the literature review study would categorize them.
5.4 Presentation of the interview study data compared with data from the literature review study
We present our interview study data in the three broad areas that emerged through analysis. Our approach to thematic analysis was to deductively code the interview transcripts manually under the three broad areas of: where data aligns with textbook and key source ‘binary’ representations; where the data contrasts with such representations; and where the data relates to interviewee perceptions of the value of ‘qualitative’ and ‘quantitative’. The latter relates to whether participant researchers expressed views that suggested they considered each approach to be useful, valuable, or not. We also read through the transcripts inductively with a view to being open to emerging and unanticipated themes. For each data citation, we note the subject field to show the range of subject areas. We later discuss these data in terms of their implications for research values, assumptions and practices and for their use when teaching about different methods. We provide illustrative citations and numbers of participant researchers who commented in relation to the key points below, but first provide an overview in Table 2 .
5.4.1 Theme 1: Alignments with ‘binary’ textbook and key source representations
The data often aligned with textbook representations. Seven participant researchers explicitly said, or alluded to the representation that ‘quantitative’ is positivist and seeks objectivity whereas ‘qualitative’ is more constructivist and subjective. For example: “the main distinction… is that qualitative is associated with subjectivity and quantitative being objective.” This was because “traditionally quantitative methods they’ve been associated with the positivist scientific model of research whereas qualitative methods are rooted in the constructivist and interpretivist model” (Psychology). Similarly, “quantitative methods… I see that as more… logical to a scientific mode of generating knowledge so… largely depends on numbers to establish causal relations… qualitative, I want to more broadly summarize that as anything other than numbers” (Communication Studies). One Statistics researcher had “always associated quantitative research more with statistics and numbers… you measure something… I think qualitative… you make a statement… without saying to what extent so… so you run fast but it’s not clear how fast you actually run…. that doesn’t tell you much because it doesn’t tell you how fast.” One mathematics participant researcher said mathematics was “ super quantitative… more beyond quantitative in the sense that not only is there a measurement of size in everything but everything is defined in… really careful terms… in how that quantity kind of interacts with other quantities that are defined so in that sense it’s kind of beyond quantitative.” Further, this applied at pre-data and data integration stages. Conversely, ‘qualitative’ “would be more a kind of verbalistic form of reasoning or… logic.”
Another representation four participant researchers noted was that ‘quantitative ‘ has structured predetermined questions whereas ‘qualitative’ has initially general questions that became more focused as research proceeded. For example, in Tourism, “with qualitative research I would go with open ended questions whereas with quantitative research I would go with closed questions.” This was because ‘qualitative’ was more exploratory: “quantitative methods… I would use when the parameters… are well understood, qualitative research is when I’m dealing with topics where I’m not entirely sure about… the answers.” As one Psychology participant researcher commented: “the main assumption in quantitative… is one single answer… whereas qualitative approaches embrace… multiplicity.”
Nineteen participant researchers considered ‘quantitative’ numbers whereas ‘qualitative’ was anything except numbers. For example, “quantitative research… you’re generating numbers and the analysis is involving numbers… qualitative is… usually… text-based looking for something else… not condensing it down to numbers” (Psychology). Similarly, ‘quantitative’ was “largely… numeric… the arrangement of larger scale patterns” whereas, “in design field, the idea of qualitative…is about the measure… people put against something… not [a] numerical measure” (Design). One participant researcher elaborated about Biology and Ecology, noting that “quantitative it’s a number it’s an amount of something… associated with a numerical dimension… whereas… qualitative data and… observations… in biology…. you’re looking at electron micrographs… you may want to describe those things… purely in… QUALitative terms… and you can do the same in… Ecology” (Human Computer Interaction). One participant researcher also commented on the magnitude of ‘quantitative’ data often involving more than numbers, or having a complex involvement with numbers: “I was thinking… quantitative… just involves numbers…. but it’s not… if… NVivo… counts the occurrence of a word… it’s done in a very structured way…. to the point that you can even… then do statistical analysis” (Logistics).
Regarding mixed methods, data aligned with the textbook representations that there are two distinct ‘camps’ but also that these could be crossed. Six participants felt opposing camps and paradigms existed. For example, in Nursing, that “it does feel quite divided in Nursing I think you’re either a qualitative or a quantitative researcher there’s two different schools… yeah some people in our school would be very anti-qualitative.” Similarly, in Music one participant researcher felt “it is very split and you’ll find… some people position themselves in one or the other of those camps and are reluctant to consider the other side. In Psychology, “yes… they’re quite… territorial and passionately defensive about the rightness of their own approaches so there’s this… narrative that these two paradigms… of positivistic and interpretivist type… cannot be crossed… you need to belong to one camp.” Also, in Communication Studies, “I do think they are kind of mutually exclusive although I accept… they can be combined… but I don’t think they, they fundamentally… speak to each other.” One Linguistics participant researcher felt some Linguists were highly qualitative and never used numbers, but “then you have… the corpus analysts who quantify everything and always under the headline ‘Corpus linguistics finally gets to the point… where we get rid of researcher bias; it objectifies the analysis’ because you have big numbers and you have statistical values and therefore… it’s led by the data not by the researcher.” This participant researcher found such striving for objectivity a “very strange thing” as any choice was based on previously argued ideas, which themselves could not be objective: “because all the decisions that you need to put into which software am I using, which algorithm am I using, which text do I put in…. this is all driven by ideas.”
Nevertheless, three participant researchers felt the approaches not diametrically opposed. For example, the same Psychology participant researcher cited immediately above felt people’s views could change: “some people although highly defensive over time… may soften their view as mixed method approaches become more prominent.” Comparatively flexibly, a Historian commented “I don’t feel very concerned by the division between qualitative and quantitative; I think they’re just two that are separate sometimes complementary approaches to study history.” In Translation and Interpreting, one participant researcher said methods could be quantitative, but have qualitative analysis, saying one project had: “an excellent use of quantitative tools… followed by not a qualitative method but qualitative analysis of what that implied.” Thus, much of the data did align with the binary representations of the key textbooks reviewed above and also the representation that approaches could be combined.
5.4.2 Theme 2: Contrasts with ‘binary’ textbook and key source representations
One recurrent contrast with common textbook representations was where both qualitative and quantitative were used in some sciences; nine participant researchers felt this. For example, in Geotechnics, when ascertaining soil behaviour: “the first check, the Qualitative check is to look whether those [the traditional and new paths of soil direction] bear resemblance, [be] coz if that doesn’t have that shape how can I expect there to be a quantitative comparison or… fit.” Both qualitative and quantitative approaches combined helped “rule out coincidence” and using both represented “a check which moves through qualitative… to quantitative.” Quantitative was a “capital Q for want of a better expression” and consisted of ‘bigger numbers’, which constituted “the quantitative or calculated strength.” However, this ‘capital Q’ quantitative data aimed to quantify a qualitatively measured numerically estimated phenomenon. So both were numerical. Nevertheless, over the long-term, even the quantitative became less certain because: “when you introduce that time element… you create… circumstances in which you need to be careful with the way you define the strength… different people have come up with different values… so the quantitative match has to be done with an element of uncertainty.”
Similarly, in Chemistry, both qualitative and quantitative methods and analysis were used, where “ the qualitative is the first one, and after you have the other ones [I—Right to kind of verify] if… if you need that.” Both were used because, “we need to know what is there and how much of each component is there… and a knowledge of what is there is a qualitative one, how much of each one is a quantitative one.” Moreover, “they are analysed sometimes by the same technique ” which could be quantitative or qualitative: “[I—and chromatography, again… would that be qualitative or quantitative or both?] Both, both… the quantitative is the area of the peak, the qualitative is the position in which this characteristic appears.” Here, both were key, and depending on the research goal: “we… use them according to what we need… sometimes it’s enough to detect [qualitative] … other times you need to know how much [quantitative] ”.
For Biology also, both were key: “quantitative is the facts and… qualitative is the theory you’re trying to make fit to the facts you can’t do it the other way around… the quantitative data… just doesn’t tell you anything without the qualitative imagination of what does it mean?” Inversely, in an area commonly understood as quantitative, Statistics, the qualitative was an initial, hypothetical stage requiring later quantitative testing. For example: “very often the hypothesis is a qualitative hypothesis” and then, “you would test it by putting in all sorts of data and then the test result would give you a p-value… and the p-value of course is quantitative because that’s a number.”
In Engineering, both helped research sound frequencies: “we need to measure the spectrum of the different frequencies… created… all those things were quantifiable, but then we need to get participants to listen and tell us… which one do you prefer?… this is a qualitative answer.” Mathematical Biology also used both: qualitative for change in nature of a state, and quantitative for the magnitude of that change. Here: “quantitative changes the numerical value of the steady state but it doesn’t change its stability… but qualitative change is when you… change the parameters and you either change its stability or you change whether it exists or not… and that point over which you cross to change it from being stable to unstable is called a bifurcation point… that’s where I use quantitative and qualitative the most in my research.”
The idea of ‘quantitative’ involving large data sets was expressed; however, the ‘qualitative’ could help represent these. In Computing Mathematics one participant researcher commented that: “quantitative… I do almost 90% of the time…. calculating metrics… and using significance testing to determine whether the numbers mean anything.” Yet, this participant researcher also used qualitative representations for simplified visual representation of large number sets: “I think for me QUALitative work is almost always about visualizing things in a way that tries to illustrate the trends… so I’m not actually calculating numbers but I’m just saying if I somehow present it in in this way.” Concomitantly, ‘quantitative’ could be smaller scale. For example, in Architecture: “my expectation is it wouldn’t be valid until you have a certain quantity of response but that said [I] have had students use… quantitative analysis on a small sample.” Similarly, in History: “you could have a quantitative study of a small data set or a small… number of statistics I really think it’s determined by the questions… you’re asking.”
Interestingly, two participant researchers questioned their colleagues’ understandings of ‘quantitative’ and of ‘numbers’. For example, one Mathematician considered some researchers did not know what ‘quantitative’ meant, because “when they say quantitative… I think what they mean is the same as qualitative except it’s got numbers in it somewhere.” For example, “I’m talking to a guy who does research in pain and, so I do know now what he means by quantitative research, and what he means is that he doesn’t know what he means [both laugh] and he wants me to define what it means… I think he means he wants some form of modelling with data and… he’s not quite sure how to go about doing that.” For this Mathematician, engineers would, “Mean that purposefully when they talk about quantitative modelling” whereas, “generically you know when politicians [consider these things] quantitative just means there’s a number in it somewhere.”
Three participant researchers felt that when ‘quantitative’ involved human elements or decisions, subjectivity was inevitable. One Logistics participant researcher felt someone doing materials research was “Doing these highly quantitative analyses still there is a degree of subjectivity because… this involves human assessment… they’re using different photometric equipment… taking photos… what is the angle.” Another researcher in Sciences similarly noted, “I don’t know why people believe in machines so much because they’re built by humans and there’s so many errors.” An Engineer commented: “To me, just the involvement of humans… gives it a qualitative element no matter what.” For this researcher, with people’s ‘quantitative’ reaction times and memory recall, “I would call that again qualitative you know… yes we did quantify the reaction time… the correct number of answers, but… it’s a person… I could get somebody else now doing it and not get exactly the same answer, so that uncertainty of human participants to me make it a qualitative approach.” For this participant researcher, anything involving human participants was ‘qualitative’: “I would say anything that is measurable, but by measurable I mean physically measurable… or predictable through numbers is quantitative [and] anything that involves a judgment, therefore human participants… is qualitative.”
‘Qualitative’ was often highly subject-specific. For example, in Film Studies and Media—English, ‘qualitative’ was: “about… the qualities of particular texts…. I’ve read a lot about silence as a texture and a technique in cinema… so silence is a quality, and also what are the qualities of that silence.” One Sciences researcher felt ‘qualitative’ involved experience applied to interpreting data: “Qualitative I would define as using your own experience to see if the data makes sense… and… something that… cannot be measured so far by machine… like the shape of a tree.” One Historian also highlighted the importance of subject-sub-branches, saying, “I’d situate myself in history but I guess you’d probably get a different response depending on… whether that historian saw themselves as a cultural historian or as a social and economic historian or… an intellectual historian.”
A fluidity regarding ‘quantitative’ and ‘qualitative’ was characterized. One Human Computer Interaction participant researcher commented, “I think sometimes people can use both terms quite loosely without really sort of thinking about [them] .” Comparatively, one Psychology participant researcher commented that “even within the Qual[itative] people they disagree about how to do things [laughs] … so you have people talking about doing IPA [Interpretative Phenomenological Analysis] and they’re doing… and presenting it in completely different ways.” Another Psychologist felt using ‘quantitative’ and ‘qualitative’ as an ‘either/or’ binary division erroneously suggested all questions were answerable, whereas: “no method… can… answer this question… and this is something… many people I don’t think are getting is that those different methodologies come with huge limitations… and as a researcher you need… to appreciate… how far your work can go.” One Communication Studies participant researcher even perceived the terms were becoming less used in all disciplines, and that, “we’re certainly in a phase where even these labels now are becoming so arbitrary almost… that they’re not, not carrying a lot of meaning.” However, the terms were considered very context dependent: “I think I’d be very hesitant about… pigeonholing any particular method I’d want to look very closely at the specific context in which that particular method or methodology is being used.” Further, some concepts were considered challenging to align with textbook representations. One German Literature participant researcher, reflecting on how the ‘theoretical’ worked, concluded, “… the theoretical… I’m not sure whether… that is actually within the terms quantitative or qualitative or whether that’s a term… on a different level altogether .” Indeed, many participant researchers (nine in total across many subject areas e.g. Design, Film and Media, Philosophy, Mathematical Biology) confirmed they were fully aware of the commonplace representations, but felt they did not apply to their own research, only using them to communicate with particular audiences (see below).
5.4.3 Theme 3: Perceptions on the value of ‘Quantitative’ and ‘Qualitative’ methods and approaches
As the data above show, many participant researchers valued both ‘quantitative’ and ‘qualitative’, including many scientists (in Geotechnics; Biology, Chemistry, Engineering). Many considered the specific research question key. For example: “I certainly don’t think quantitative bad, qualitative good: it’s horses for courses, yeah” (Tourism). Participant researchers in History and Music Education felt similarly; the latter commenting how “I do feel it’s about using the right tools which is why I wouldn’t want to… enter into this kind of vitriolic negative mud-slinging thing that does happen within the fields because I think people… get too entrenched in one or the other and forget about the fact that these are just various ways to approach inquiry.” Similarly, one Psychologist observed, “I’m always slightly irritated [laughs] when I hear people you know say ‘Oh I’m only doing… qualitative research’ or ‘I’m only doing quantitative research’… I think it’s the research question that should drive the methodological choices.” This participant researcher had “seen good quality in both quantitative and qualitative research.”
Five participant researchers considered quantitative approaches to be of little value if they were applied inappropriately. For example, a Translation and Interpreting participant researcher felt quantitative data-generating eye tracking technology was useful “for marketing,… product placement,… [or] surgeons.” However, for Translation and Interpreting, “I don’t think… it is a method that would yield results… you could find better in a more nuanced manner through other methods, interviews or focus groups, or even ethnographic observation.” One Chemist questioned the value of quantitative methods when the sample was too small. For example, when students were asked about their feedback on classes, and one student in 16 evaluated the classes badly, “4% it was one person [laughs] in 16, one person, but I received that evaluation and I think this is not correct… because sometimes…. I think that one person probably he or she didn’t like me… well, it’s life, so I think these aspects… may happen also but it’s with the precision of the system… the capacity of the system to detect and to measure.” Meaningfulness was held to be key: “When we do the analysis the sample has meaning” . Similarly, a Theoretical Physicist felt quantitative approaches unsuited to education: “in the context of education… we all produce data all the time… we grade students… we assess creativity… people will say… ‘you measure somebody's IQ using this made-up test and you get this kind of statis[tic]..’ and then you realize that all of those things are just bogus… or at least… doesn't measure anything of any real serious significance.” Comparatively, one participant researcher in Design felt ‘quantitative’ had a danger to “lead to stereotypes”; for example, when modern search engines use quantitative data to direct people to particular choices, “There’s potential there to constrain kind of broader behaviours and thinking… and therefore it can become a programmer in its own right.” One Mathematical Biologist commented how statistics can be misused, and how a popular Maths book related “How statistics are a light shone on a particular story from a particular angle to paint a picture that people want you to see but… it’s almost never the whole picture, it’s a half-truth, if you like, at best.”
Seven participant researchers considered that their disciplines valued quantitative over qualitative. This could be non-judgmental, and perhaps inherent in major areas of a discipline, as in Theoretical Physics, where precision is crucial, although this was said not to be ‘disparaging’: “theoretical physics… or physics in general… we… tend to think of ourselves as being very, very quantitative and very precise, and we think of qualitative, I guess… as being a bit vague, right?… which is not disparaging, because sometimes… we have to be a bit vague… and we're working things out.” In Psychology, however, despite “a call to advocate for more qualitative methods”, there, “definitely… is a bias toward quantitative… measures in psychology; all the high impact factor journals advocate for quantitative measures.” In Nursing, quantitative was also deemed paramount, with “the randomized control trial seen as being… you know the apex and… some researchers in our school would absolutely say it’s the only reliable thing… would be very anti-qualitative.”
Yet, four participant researchers were positively oriented towards anything qualitative. For example, one Tourism researcher felt that, “in an uncertain world, such as the one we’re living in today, qualitative research is the way forward.” Also, an Architect highlighted that in one of their studies, “I think the most important finding of my questionnaires was in the subjective comments.” One Music education participant researcher personally favoured qualitative approaches but regretted how their field was biased toward quantitative data, saying they had been informed: “ ‘what journals really care about is that p-value…’ and I remember… thinking… that’s a whole area of humanity… you’re failing to acknowledge.”
Nevertheless, side-stepping this debate, nine researchers considered the terms of little value, and simply irrelevant for their own research. One Film and Media—English participant researcher commented: “I have to say… these are terms I’m obviously familiar with, but… not terms… I… tend to really use in my own research… to describe what I do … mainly because everything that I do is qualitative.” As an English Literature participant researcher noted in email correspondence: “they are not terms we use in literary research, probably because most of what we do is interpretation of texts and substantiating arguments through examples. I have really only encountered these terms in the context of teaching and have never used them myself.” In the interview, this participant researcher commented that “I can imagine… they would be terms… quite common in the sciences and mathematics, but not Social Sciences and Arts.” A German Literature participant researcher felt similarly, commenting that in “German Literature… the term quantitative hadn’t even entered my vocabulary all the way through the PhD [laughs] … because… you could argue the methods in literary research are always qualitative.”
Complementing such perspectives, in Theoretical Physics ‘qualitative’ and ‘quantitative’ was: “not something that ever comes up… I don’t think I read a paper ever that will say we do qualitative research in any way, but I never… or hardly ever handle any data… I just have a bunch of principles that are sort of either taken to be true or are… a model… we’re exploring.” In Mathematics, ‘quantitative’ was simply never used as all mathematics research was quantitative: “I never use the word in the company of my colleagues, never, it’s a non-vocabulary word, for the simple reason that when everything is so well defined why do you need a generic term when you’ve got very specific reference points in the language that you’re using?”.
One Philosopher felt the terms did not fit conceptual analysis in philosophy, given that the object of consideration was uncertain: “I guess… I thought it didn’t fit conceptual analysis… you need to know what you’re dealing with in order to then do the quantitative or qualitative whereas in philosophy it feels like… you don’t quite know what you’re dealing with you’re trying to work out… what are rights?… What is knowledge? What is love?… and then look at its qualities.” For this researcher, Philosophy was tentatively pre-quantitative or pre-qualitative, because philosophy “feels like it’s before then.” The terms were not considered valuable for Philosophy or for the humanities generally: “in philosophy we wouldn’t use the term qualitative or quantitative research… you just use the tools… you need… to develop your argument and so you don’t see the distinction… I would say in the humanities that’s relatively similar.” Further, a Fine Art—Sculpture participant researcher said: “they’re not words I would use… partly because… I’m engaged with… through… research and… teaching… what I’d call practice research… and… my background’s in fine art, predominantly in making sculpture and that doesn’t contain knowledge.” Here, the participant researcher related how they may consider a student’s work hideous but if the student had learned a lot through creating the work, they should be rewarded. This participant researcher spoke of a famous sound artist, concluding, “if you asked him about qualitative and quantitative… it just wouldn’t come into his thing at all…. He doesn’t need to say well there were a thousand visitors plus you know it’s just ‘bang’… he wouldn’t think about those things… not as an artist.”
Six participant researchers said they only ever used the terms for particular audiences. For example, for ‘quantitative’ in Film and Media: “the only time is when it’s been related to public engagement that we’ve ever sort of produced anything that is more along quantitative lines,” and that “it was not complex data we were giving them.” In Fine-Art Sculpture, too, the terms were solely used with a funder, for example, to measure attendance at an exhibition for impact, but “that’s not the type of research that I’m involved with necessarily.” One Logistics participant researcher commented that “it really depends on the audience how you define qualitative or quantitative.” For this researcher, if communicating with “statisticians econometricians or a bunch of people who are number crunchers” then “they will be very precise on what quantitative is and what qualitative is” and would only recognise mathematical techniques as quantitative. Indeed, “they wouldn’t even recognize Excel as quantitative because it’s not that hard.” In contrast, for social scientists, Excel would be quantitative, as would “anything to do with numbers… I suppose you know a questionnaire where you have to analyse responses would be probably classed as quantitative.”
Conversely, a Mathematical Biology participant researcher commented they had been doing far more public outreach work, “using quantitative data so numbers… even with things that might often be treated in a qualitative way… so stuff which… is often treated I think qualitatively we try to quantify… I think partly because it’s easier to make those comparisons when you quantify something.” One researcher in Communication Studies said they advised a student that “it depends on your research objectives; if you are focusing on individual experiences… I think naturally that’s going towards qualitative, but if you’re … doing this research oriented to a leader of … [a] big number of people… for informing policy… then you need some sort of insights that can be standardized… so it’s a choice.”
Another Communication participant researcher felt political shifts in the 1990s and 2000s meant that a ‘third way’ now dominated with a move towards hybridity and a breakdown in ‘qualitative’ and ‘quantitative’ with everything now tied to neoliberalism. Therefore, since “the late 90s and early noughties I’ve seen this kind of hybridity in research methods almost as being in parallel with the third way there seems to be… no longer opposition between left and right everything… just happens to buy into neoliberalism so likewise… with research methods… there’s a breakdown of qual and quant.” Comparatively, a Historian felt underpinning power structures informed approaches, commenting that “the problem is not the terminology it’s the way in which power is working in the society in which we live in that’s the root problem it seems to me and what’s valued and what’s not.” A Philosopher felt numbers appealed to management even when qualitative data were more suitable: “I think management partly… are always more willing to listen to numbers… finding the right number can persuade people of things that actually… you think really a better persuasion would do something more qualitative and in context.” One Fine Art participant researcher felt ‘quantitative’ and ‘qualitative’ only became important when they focused on processes related to the Research Excellence Framework but not for their research as such: “I guess we are using qualitative and quantitative things in the sense of moving ourselves through the process as academics but that’s not what I’d call research.”
6 Discussion: implications for teaching research methods
Research Methods teaching for undergraduate, postgraduate and newer researchers is commonly guided by textbook and seminal text understandings of what constitutes ‘qualitative’ and ‘quantitative’. Often, the two are treated in parallel, or interlinked, and used in combination or sequentially in research. But the relations between these are complex. The above analysis of the interview study with established participant researchers underlines and often extends this complexity, with implications for how such methodologies are approached and taught. Many of these participant researchers in disciplines commonly located within an ostensibly ‘positivist’ scientific tradition are, in fact, using qualitative methods as scientific procedures. They do so to provide initial measurements of phenomena before later using quantitative procedures to measure the quantity of a quality. They also use quantitative procedures to reveal data for which they subsequently use qualitative approaches to interpret and understand through their creative imaginations or experience. Participant researchers in ostensibly positivist disciplines describe themselves as doubting ‘facts’ measured by machines programmed by humans or doubting the certainty of quantitative data over time. Critically, these participant researchers engage in debate over what a ‘number’ is and the extent to which ‘numbers’ can be considered ‘quantitative’. One mathematician spoke of how many individuals do not know what they mean by the word ‘quantitative’, and an engineer interpreted any numbers involving human judgements as ‘qualitative’. Both a chemist and a geotechnician routinely defined and use ‘qualitative’ methods and analysis to arrive at numerical values.
Although this analysis of participant researchers’ reported practices refutes many textbook and key research methods source representations of quantitative and qualitative as being binary and separately ringfenced entities (contra e.g. Punch 2005 ; Goertz and Mahoney 2012 ), they resonate with much recent and current literature in the field (e.g. Uher 2022 ; De Gregorio 2014 ). In some disciplines, participant researchers only do a particular type of research and never need anything other than clear ‘quantitative’ definitions (Mathematics); others only ever conduct research involving text and never numbers (Literature). Further, other participant researchers considered how certain aspects lie outside the ‘qualitative’ or ‘quantitative’ (the ‘theoretical’ in German Literature), or they did research which they maintain does not contain ‘knowledge’ (Fine-Art Sculpture), while others do foundational ‘conceptual’ research which they claim comes at a stage before any quantity or quality can be assessed (Philosophy). Nine researchers considered the terms of little relevance at all to their subject areas.
This leads to subsequent questions. Firstly, do the apparently emerging tensions and contradictions between commonplace textbook and key source presentations and on-the-ground participant researcher practices matter? Secondly, what kind of discourse might reframe the more conventional one?
Regarding whether tensions and contradictions matter: in one practical way, perhaps not, since participant researchers in all these areas continue to be productive in their current research practices. Nevertheless, the foundations of the binary quantitative and qualitative divide are discourse expressions common to research methods courses. These expressions frame how the two terms are understood as the guide for novices to do research. This guiding discourse is evident in specifically designated chapters in research handbooks, in session titles in university research methods modules, and in entries for explanations of research terms within glossaries. The literature review study detailed above illustrates this. ‘Quantitative’ means numbers, ‘qualitative’ means words. ‘Quantitative’ connotes positivist, objective, scientific; ‘qualitative’ implies constructivist, subjective, non-science-based. Arguably, any acceptance of the commonplace research method understanding gives an apparent solidity which can sometimes be a false basis that masks the complexities or inadequacies involved. Such masking can, in turn, allow certain agencies or individuals to claim their policies and practices are based on ‘objective’ numerical data when they are merely framing something as ‘quantitative’ when, as a cited Mathematician participant researcher observed above, it is simply something with a number in it somewhere. Conventionally, limitations are mentioned in research studies, but often they seem ritualized remarks which refer to insufficient numbers, or restricted types of participants, or a constrained focus on a particular area. Rarely do research studies (let alone handbooks and guides for postgraduates) question a taken-for-granted understanding, such as whether the very idea of using numbers with human participants may mean the number is not objective. Ironically, it is the field of Qualitative Inquiry itself in which occasionally some of these issues are mentioned. Concurrently, while the quantitative is promoted as ‘scientific’ and ‘objective evidence’, we find some scientists researching in sciences often question the terms, or consciously set them aside in their practices.
Concerning what could replace the commonplace terms and reframe the research discourse environment: arguably, any discussion of ‘quantitative’/‘qualitative’ should be preceded by key questions of how they are understood by researchers. Hammersley ( 2013 ) has suggested the value of a more nuanced approach. As the Communication Studies participant researcher here commented, the two terms seem to be breaking down somewhat. Nevertheless, alongside the data and arguments here, we see some value in considering things as being ‘quantitative’ or ‘qualitative’, and other value in viewing them as separate. The terms can still be simply outlined, not just as methodological listings of characteristics, but as a critical point, Outlines of methods should include insider practitioner views—illustrations of how they are used and understood by practising researchers in different disciplines (as in Table 2 above). This simple suggestion has benefits. When outlining approaches as qualitative or quantitative, we suggest space is devoted to how this is understood in disciplines, together with the opportunity to question the issues raised by these understandings. This would help to position the understandings of qualitative and quantitative within specific disciplinary contexts, especially in inter-disciplinary fields and, implicitly, it encourages reflection on the objectivity and subjectivity evoked by the terms. Such discussion can be included in research methods texts and in research methods courses, dissertations and frameworks for viva examinations (Cortazzi and Jin 2021 ). Here, rather than start with outlining what the terms mean by using concrete definitions such as ‘Quantitative means X’ the terms should be outlined using subject contextualised phrases such as ‘In the field of X quantitative is understood to mean Y’. In this way, quantitative and qualitative methods and approaches can be seen, understood and contextualised within their subject areas, rather than prescriptively outlined in a generic or common form. Furthermore, if the field is one that has no use for such terms, this can also be stated, to prevent any unnecessary need for their use. Discourse around the terms can be extended if they are seen in line with much current literature and the data above that shows their complexities and overlaps, and goes beyond the binary choices and representations of many textbooks.
7 Conclusion
This paper has presented and discussed data from an interview study with experienced participant researchers (n = 31) regarding their perceptions of ‘qualitative’ and ‘quantitative’ in their research areas. This interview study data was compared with findings from a literature review study of common textbooks and research methods publications (n = 25) that showed often binary and reified representations of the terms and related concepts. The interview study data show many participant researcher understandings do in some ways align with the binary and commonplace representations of ‘qualitative ‘and ‘quantitative’ as shown to be presented in many research methods textbooks and sources from the literature review study. However, the interview study data more often illustrate how such representations are somewhat inaccurate regarding how research is undertaken in the different areas researched by the participant researchers. Rather, they corroborate much of the current literature that shows the blurring and complexity of the terms. Often, they extend this complexity. Sometimes they bypass complexity when these terms are considered irrelevant to their research fields by many researcher participants. For some researchers, the terms are simply valueless. We propose that future research methods courses could present and discuss the data above, perhaps using something akin to Table 2 as a starting point, so that students and novice researchers are able to loosen or break free of the chains of any stereotypical representations of such terms or use them reflectively with awareness of disciplinary specific usage. This could help them to advance their research, recognizing complex caveats related to the boundaries of what they do, what methods they use, and how to conduct research using both quantitative and qualitative approaches, as interpreted and used in their own fields. In multi- or inter-disciplinary research, such reflective awareness seems essential. Future research could also study the impact of the use of the data here in research methods courses so that such courses encompass both qualitative and quantitative methods (cf. Onwuegbuzie and Leech 2005 ) yet also question and contextualise such terms in specific subject areas order to free research from any constraints created by binary representations of the terms.
Whilst we interviewed 31 participant researchers to approach what seems a reasonable level of saturation, clearly future research could add to what we have found here by speaking to a wider range and larger number of researchers. The 25 research methods sources in English (supplemented by 23 sources in German, Spanish and French) examined here can clearly be expanded for a wider analysis of ‘quantitative’ and ‘qualitative’ in other languages for a more comprehensive European perspective. This strategy might ascertain likely asymmetries between the numerous English language texts (and their translations) and relatively smaller numbers of texts written by national or local experts in other languages. As a world-wide consideration, given the relative paucity of published research guidance in many languages, this point is especially significant related to fitting research methods to local contexts and cultures without imposition. Translating and discussing the terms ‘qualitative’ and ‘quantitative’, in and beyond European languages, will need care to avoid binary stereotyped or formulaic expression and to maintain some of the insight, resonances and complexities shown here.
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Appendix 1: Literature review study
The table below contains details of the binary representations and possibilities in the two columns on the left and in the right it contains the numbers of the key sources that conveyed or adhered to these binary representations. The details of these sources and their respective numbers are listed below.
Table: Textbook and key source binary representations
Value: for specific subjects and approaches—for e.g. Economics, the Sciences and to research large numbers—may see Qualitative of little value
Value: for specific subjects and approaches—for e.g. History, Anthropology and to research individuals’ lived experiences—may see Quantitative of little value
Bell, J., & Waters, S. (2014). Doing your research Project: A Guide for first-time researchers. McGraw-Hill Education (UK). 6 th edn
Bloor, M., & Wood, F. (2006). Keywords in qualitative methods: A vocabulary of research concepts. London, UK: Sage Publications.
Bryman, A. (2008). Social research methods. Oxford, UK: Oxford University Press. [with caveats for many but still using the divide as ‘useful’]
Bryman, A., & Cramer, D. (2009). Quantitative data analysis with SPSS 14, 15 and 16: A guide for social scientists. London, UK: Routledge.
Ceglowski, D., Bacigalupa, C., & Peck, E. (2011). Aced out: Censorship of qualitative research in the age of "scientifically based research." Qualitative Inquiry, 17(8), 679–686.
Daly, K. J. (2007). Qualitative Methods for Family Studies and Human Development. London, UK: Sage.
Davies, M. B., & Hughes, N. (2014). Doing a successful research project: Using qualitative or quantitative methods . Bloomsbury Publishing.
Dawson, C. (2019). Introduction to Research Methods 5th Edition: A Practical Guide for Anyone Undertaking a Research Project . Robinson.
Denzin, N. K., & Lincoln, Y. S. (Eds.). (1998). The landscape of qualitative research: Theories and issues. Thousand Oaks, CA: Sage Publications. [with caveat that original qual was positivist in root but not now]
Denzin and Lincoln (2011) Introduction: The Discipline and Practice of Qualitative Research. In Denzin, N. K., & Lincoln, Y. S. (2011). The Sage handbook of qualitative research . Thousand Oaks, Calif: Sage. Pp1-20
Goertz, G., & Mahoney, J. (2012). A tale of two cultures . Princeton University Press.
Grix, J. (2004). The foundations of research. New York, NY: Palgrave Macmillan.
Hammersley, M. (2007). The issue of quality in qualitative research. International Journal of Research & Method in Education, 30(3), 287–305.
Hammersley, M. (2013). What is qualitative research? London, UK: Bloomsbury Academic. [caveat that some qual do use causal analysis – and if you mix you abandon key assumptions associated with qualitative work]
Harman, W. W. (1996). The shortcomings of western science. Qualitative Inquiry, 2(1), 30–38.
Howe, K. R. (2011). Mixed methods, mixed causes? Qualitative Inquiry, 17(2), 166–171.
Mason, J. (2006). Mixing methods in a qualitatively driven way. Qualitative Research, 6(1), 9–25.
Miles, M. B., Huberman, A. M., & Saldaña, J. (2018). Qualitative data analysis: A methods sourcebook . Sage publications.
Punch, K. (2005). Introduction to Social Research Quantitative and Qualitative Approaches. Sage.
Sandelowski, M. (1997). "To be of use": Enhancing the utility of qualitative research. Nursing Outlook, 45(3), 125–132 [caveat – does rebut many of the ideas but nevertheless outlines them as how the two are seen – e.g. of generalizability]
Seale, C. (1999). Quality in qualitative research. Qualitative Inquiry, 5, 465–478.
Silverman, D. (2016). Introducing qualitative research. Qualitative research , 3 (3), 14–25.
Tashakkori, A., Teddlie, C., & Teddlie, C. B. (1998). Mixed methodology: Combining qualitative and quantitative approaches (Vol. 46). sage. [with the caveat that they talk about the differences as existing even though say they are not that wide]
Teddlie, C., & Tashakkori, A. (2011). Mixed methods research. Contemporary Issues in an emerging Field. in The Sage handbook of qualitative research , 4 , 285–300.
Torrance, H. (2008). Building confidence in qualitative research: Engaging the demands of policy. Qualitative Inquiry, 14(4), 507–527.
1.1 Sources in languages other than English, and brief notes regarding their focus and content
Whilst not part of the literature review study, we also consulted the outline details, abstracts and contents lists of a number of sources in languages other than English. We put brief notes about after each source. Each source, unless specifically noted, adhered to similar binary treatment of quantitative and qualitative methods and approaches as the English language sources outlined above.
1.1.1 German
Blandz, M. (2021) Forschungsmethoden und Statistik für die Soziale Arbeit : Grundlage und Anwendingen. 2 nd . edit. Stuttgart: Kohlhammer Verlag. – this is a multidisciplinary source that focuses mostly on quantitative and mixed methods. It follows the suggestion that a qualitative study can be a preliminary study for the main quantitative study.
Caspari, D; Klippel, F; Legutke, M. & Schram, K. (2022) Forschungsmethoden: in der Fremdsprachendidaktik; Ein Handbuch. Tübingen: Narr Franke Altempo Verlag. [Focused on foreign language teaching, details quantitative, then qualitative and then mixed; all separately]
Dōring, N. (2023) Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften. 6. th edit. Berlin: Springer. [Focused on the Social Sciences and humanities; as with the previous source it has separate chapters on quantitative and qualitative and a section on mixed, and contains some critical commentary]
Frankenberger, N. (Ed.) (2022) Grundlagen der Politikwissenschaft : Forschungsmethoden und Forschendes Lernen. Stuttgart: Kohlhammer Verlag. [Political science focused and based around distinctions between quantitative and qualitative approaches, each of which is elaborated with different methods; there is no obvious section on mixed methods]
Hussy, W; Schiener, M; Echterhoff, G. (2013) Forschungsmethoden in Psychologie und Sozialwissenschaften für Bachelor. Berlin: Springer. [This book is focused on psychology and social sciences for undergraduates. It has separate parts to focus on quantitative and on qualitative and then a chapter on mixed, identifying mixed methods as an emerging trend]
Niederberger, M. & Finne, E. (Eds.) (2021) Forschungsmethoden in der Gesundsheitsfōrderung und Prävention. Berlin: Springer. [Focused on Health and wellbeing; develops the roles of quantitative, qualitative and mixed (in combinations) in multidisciplinary, interdisciplinary and transdisciplinary research. Notes much research is exclusively quantitative and that social sciences are more qualitative or mixed. Makes the argument that the quantitative versus qualitative divide was surpassed by ‘post-positivist’ versus ‘combined’ thinking and that integrated approaches are now widely accepted]
1.1.2 Spanish
Campos-Arenas, A. (2014) Métodos mixtos de investigación. Bogota: Magisterio Editorial. [Social science focused; devoted to mixed or combined approaches in Latin American contexts]
Hernandez-Sampieri, R. & Mendoza Torres, C. P. (2018) Metodología de investigación: Las rutas cuantitativa , cualitativa y mixta. Mexico: McGrw-Hill. [Social science focused with an introduction and conclusion focused on ‘three routes to research’ that are exceptionally and thoroughly elaborated; quantitative given 8 chapters; qualitative 3 and mixed just one]
Léon-García, O. G. & Carda-Celay, I. M. (2020) Méthodos de investigación en psicología y educación: Las tradiciones cuantitativas y qualitativas. 5. th edit. Barcelona : McGraw-Hill, España. [Psychology and education focused; based on relatively clearly cut distinctinos between ‘the two traditions’ of quantitative and qualitative]
Molina Marin, G. (Ed.) (2020) Integración de métodos de investigación : Estrategias metodológicas u experiencias en salud pública. Bogotá: Universidad de Antioquia. [Public health focused; gives most attention to multi-method combinations and asks questions about the epistemological integrity of integrating different approaches]
Ortega-Sanchez, D, (Ed.) (2023) ¿Como investigar en didáctica de las ciencias sociales? Fundamentos metodológicos , técnicas e instrumentos de investigación. Barcelona: Octaedro. [Education, research, pedagogy of teaching social sciences; focused on quantitative, qualitative and mixed methods in Spanish contexts]
Páramo-Reales, D. (2020) Métodos de investigación caulitativa : Fundamentos y aplicaciones . Bogota: Editorial Unimagdalena. [Social sciences: basic applications of qualitative approaches in Latin America]
Ponce, O. A. (2014) Investigación de métodos mixtos en educación, 2. nd edit. San Jaun: Publicaciones Puertoriqueñas. [Education and Pedagogy; Puerto Rican context and entirely about mixed methods]
Vasilachis de Giradino, I. (Ed.) (2009) Estrategias de investigación cauitativa. Barcelona: Editorial Gedisa. [Social sciences; much detail on research design; focus exclusively on qualitative methods in Spanish contexts]
1.1.3 French
Bouchard, S. & Cyr, C. (Eds.) (2005) Reserche psycosocial pour harmoniser reserche st pratique. Quebec: Prese de la Université de Quebec. [Focused on psychology and sociology. Despite its title about ‘harmonizing’ research it is mainly focused on quantitative approaches, with a small section on qualitative and nothing on mixed approaches]
Corbière, M. & Lamviere, N. (2021) Méthodes quantitatives , qualitatives et mixtes , dans la reserche en sciences humaines et de la santé. 2. nd edit. Quebec : PU Quebec. [Focused on Humanities and health care; highlights the division between quantitative, qualitative and mixed methods]
Devin, G. (Ed.) (2016) Méthodes de recherche en relations internationals. Paris: Sciences Po. [Focused on politics and international relations; mostly wholly focused on quantitative; only a little on qualitative]
Gavard-Perret, M.L; Gotteland, D; Haon, C. & Jolibert, A. (2018) Methodologie de la recherche en sciences de gestion : Réussir son mémoire ou sa these. Paris: Pearson. [Business and management focused and geared towards thesis research; notes clear distinctions between quantitative and qualitative approaches with nothing on mixed]
Komu, S. C. S. (2020) Le receuil des méthodes en sciences sociales : Mèthodo;ogies en reserche. Manitoba: Sciences Script. [Social sciences focused; mostly quantitative methods with some attention to focus groups and participatory research]
Lepillier, O; Fournier, T; Bricas, N. & Figuié, M. (2011 ) Méthodes d’investigation de l’alimentation et des mangeurs. Versailles: Editions Quae. [Focused on nutrition, health studies and diet; details quantitative and qualitative methods and has very little on mixed]
Millette, M; Millerand, F; Myles, D. & Latako-Toth, T. (2021) Méthodes de reserches en contexte humanique , une orientation qualiificative. Montreal: PU Montreal. [Humanities focused; outlines quantitative and qualitative methods and, unusually, attends to ‘qualitative investigations in numerical contexts’ in Canada]
Moscarda, J. (2018) Faire parler les donées: Méthodologies quantitatives et qualitatives. Caen: Editions EMS. [Has a multidisciplinary focus on ‘let the data talk’; deals with quantitative methods and then qualitative methods and also mixed]
Vallerand, R. J. (2000) Méthodes de recherche en psychologie. Quebec: Gaetan Morin. [Focused on psychology; emphasis on quantitative research; brief section on qualitative; Canadian contexts]
Appendix 2: Interview study schedule
2.1 understandings of ‘qualitative’ and ‘quantitative’.
This research project is exploratory and intends to delve into understandings of the specific terms ‘quantitative’ and ‘qualitative’ as they are perceived, used, and interpreted by researchers in very different fields. Such research is intended to shed light on the fields of quantitative and qualitative research. The idea for the research arises from a previous project where the researcher interviewed quantitative focused researchers and saw the use of qualitative and quantitative being used and interpreted very differently to how the terms are presented and understood in the research methods literature. It is expected that exploring these understandings further will add to the field by shedding light on the subtleties of how they are used and also in turn help researchers make informed decisions about the optimum approaches and methods to use in their own research.
2.2 Interview questions
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Pilcher, N., Cortazzi, M. 'Qualitative' and 'quantitative' methods and approaches across subject fields: implications for research values, assumptions, and practices. Qual Quant 58 , 2357–2387 (2024). https://doi.org/10.1007/s11135-023-01734-4
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Published : 30 September 2023
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DOI : https://doi.org/10.1007/s11135-023-01734-4
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Research on the dynamic evaluation of the competitiveness of listed seed enterprises in china.
1. Introduction
2. research design, 2.1. indicator system construction, 2.1.1. scale strength, 2.1.2. benefit strength, 2.1.3. operational capacity, 2.1.4. technological innovation capability, 2.2. research methodology and sample selection, 2.2.1. global principal component analysis, 2.2.2. cluster analysis, 2.2.3. sample selection and data source, 3. evaluation and classification of the competitiveness of listed seed enterprises, 3.1. descriptive statistics analysis, 3.2. global principal component analysis, 3.2.1. applicability analysis, 3.2.2. principal component extraction, 3.2.3. principal component naming, 3.2.4. principal component scores and ranking, 3.3. cluster analysis, 4. a vertical and horizontal comparative analysis of the competitiveness of listed seed enterprises, 4.1. comparison of the dynamic competitiveness of seed enterprises, 4.2. comparison of the static competitiveness of seed enterprises, 4.3. industry heterogeneity of seed enterprises’ competitiveness, 4.3.1. criteria for classifying industry differences in seed enterprises, 4.3.2. comparison of seed enterprises’ competitiveness, 4.4. competitiveness comparison between chinese listed seed enterprises and multinational seed industry giants, 5. discussion, 6. conclusions and policy implications, 6.1. conclusions, 6.2. recommendations, author contributions, institutional review board statement, data availability statement, conflicts of interest.
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Click here to enlarge figure
Overall Target
Level 1 Indicators
Secondary Indicators
Tertiary Indicators
Indicator Code
Competitiveness of listed seed enterprises
Explicit Competitiveness
Scale Strength
Revenues
x1
Enterprise scale
x2
Net assets
x3
Benefits Strength
Return on net assets
x4
Return on total assets
x5
Gross profit margin
x6
Output per employee
x7
Year-on-year growth in basic earnings per share
x8
Potential Competitiveness
Operating Capacity
Total asset turnover
x9
Current asset turnover ratio
x10
Inventory turnover
x11
Technological Innovation Capacity
R&D capital investment
x12
R&D labor investment
x13
Secondary Indicator Variables
Third-Level Indicator Variables
Mean
S.D.
Min
p50
Max
Scale Strength
Revenues
12.39
34.28
0.0184
1.773
324.0
Enterprise size
17.75
37.22
0.0849
3.514
311.7
Net assets
9.911
20.23
−0.0216
1.868
130.4
Benefits Strength
Return on net assets
7.961
16.69
−98.30
7.415
91.44
Net interest rate on total assets
5.379
9.195
−26.32
4.129
62.40
Gross sales margin
28.89
16.67
−32.92
27.88
85.86
Output per employee
0.0142
0.0131
0
0.0113
0.109
Year-on-year growth in basic earnings per share
−38.90
69.82
−96
5.882
41.50
Operating Capacity
Total asset turnover
0.635
0.387
0.0299
0.543
3.113
Current asset turnover ratio
1.071
0.636
0.0657
0.933
4.522
Inventory turnover
2.290
3.061
0.208
1.538
40.94
Technological Innovation Capacity
R&D capital investment
4.410
4.764
0.0300
3.725
55.02
R&D labor investment
11.94
7.716
0.0917
12.73
30.52
Test Methods
Indicator Variables
Results
KMO test
KMO statistic
0.662
Bartlett’s test
approximate chi-square (math.)
1558.519
Df
78
Sig
0.000
Principal Component
Eigenvalue (Math.)
Contribution (%)
Cumulative Contribution (%)
F1
4.357
33.515
33.515
F2
2.968
22.833
56.348
F3
2.077
15.976
72.325
F4
1.443
11.1
83.425
Principal Component Name
Variables
F1
F2
F3
F4
operational capability
Current asset turnover ratio
0.893
−0.011
0.244
−0.016
Revenues
0.856
0.133
−0.362
0.195
Total asset turnover
0.836
−0.048
0.469
0.056
Inventory turnover
0.738
−0.184
0.182
−0.011
net assets
0.718
0.306
−0.572
0.123
asset size
0.714
0.216
−0.591
0.226
growth capacity
Net interest rate on total assets
0.108
0.894
0.244
−0.219
return on net assets
0.113
0.884
0.297
−0.131
Gross sales margin
−0.335
0.74
−0.227
−0.2
Year-on-year growth in basic earnings per share
0.087
0.643
0.38
−0.019
production efficiency
Output per employee
0.262
−0.195
0.7
0.439
Technological innovation capacity
R&D labor intensity
−0.344
0.306
0.231
0.766
R&D capital investment intensity
−0.476
0.316
−0.262
0.671
Indicator
F1
F2
F3
F4
Current asset turnover ratio
0.205
−0.004
0.118
−0.011
revenues
0.197
0.045
−0.175
0.135
Total asset turnover
0.192
−0.016
0.226
0.039
Inventory turnover
0.169
−0.062
0.088
−0.007
net assets
0.165
0.103
−0.275
0.086
asset size
0.164
0.073
−0.284
0.156
Net interest rate on total assets
0.025
0.301
0.118
−0.152
return on net assets
0.026
0.298
0.143
−0.091
Gross sales margin
−0.077
0.249
−0.109
−0.139
Year-on-year growth in basic earnings per share
0.02
0.217
0.183
−0.013
Output per employee
0.06
−0.066
0.337
0.304
R&D labor intensity
−0.079
0.103
0.111
0.531
R&D capital investment intensity
−0.476
0.316
−0.262
0.671
Rankings
Operational Capability
Growth Capacity
Production Efficiency
Technological Innovation Capacity
Enterprise Competitiveness
Corporations
F1 Score
Corporations
F2 Score
Corporations
F3 Score
Corporations
F4 Score
Corporations
F Score
1
A1
10.36
B1
2.2
C1
3.86
D1
3.72
E1
3.88
2
A2
4.7
B2
1.79
C2
2.29
D2
2.01
E2
2.09
3
A3
3.64
B3
1.73
C3
0.83
D3
1.63
E3
1.56
4
A4
3.42
B4
1.01
C4
0.53
D4
1.46
E4
1.34
5
A5
1.99
B5
1
C5
0.11
D5
0.86
E5
1.08
6
A6
1.51
B6
0.61
C6
−1.07
D6
0.53
E6
0.82
7
A7
1.04
B7
0.57
C7
−2.13
D7
0.26
E7
0.7
8
A8
1.01
B8
−0.03
C8
−2.76
D8
0.06
E8
0.56
9
A9
0.58
B9
−0.05
C9
−3.79
D9
−1.18
E9
0.45
10
A10
−0.3
B10
−1.52
C10
−6.54
D10
−1.2
E10
0.17
Type of Seed Enterprise
Number of Seed Enterprises
Name of the Seed Company
Type I
2
F1 and F2
Type II
6
F3–F8
Type III
19
F9–F27 and 19 other seed enterprises
Type IV
22
F28–49 and 22 other seed enterprises
Seed Enterprises
Operational Capability
Growth Capacity
Production Efficiency
Technological Innovation Capacity
Enterprise Competitiveness
G1
1.99
−1.52
3.86
1.63
1.34
G2
1.85
−0.73
0.73
0.96
0.81
G3
0.69
−0.63
−4.2
2.6
−0.35
G4
−0.41
0.74
−0.98
1.03
−0.01
G5
1.01
0.57
0.11
0.86
0.7
G6
3.64
−0.03
2.29
1.46
2.09
G7
4.7
0.61
−2.76
0.26
1.56
G8
−0.33
0.46
−0.18
−0.85
−0.15
G9
10.36
1.73
−6.54
3.72
3.88
G10
3.42
1
−2.13
−1.18
1.08
Rankings
Enterprise Abbreviation
Country
Operating Income for 2018
Rankings
Enterprise Abbreviation
Operating Income for 2018
1
Bayer Monsanto
German
741.75
1
H1
193.02
2
Cordova Agricultural Technology
America
551.31
2
H2
48.84
3
Syngenta (ChemChina)
China
206.83
3
H3
35.80
4
BASF
German
137.71
4
H4
34.46
5
Limagrain
French
125.38
5
H5
32.65
6
Covos (brand)
German
108.31
6
H6
19.27
7
Dannon
Denmark
46.68
7
H7
16.52
8
Sakata Seedling Co.
Japan
39.52
8
H8
12.84
9
Long Ping High-Tech
China
35.80
9
H9
9.10
10
Rijk Zwaan
Holland
33.26
10
H10
8.49
11
TAKII SEED
Japan
32.43
11
H11
7.67
12
Floremont I Depay Breeding Co.
French
NA
12
H12
7.61
13
Bejo
Holland
22.17
13
H13
6.27
14
Barenburg
Holland
20.93
14
H14
3.24
15
Enza Zaden
Holland
NA
15
H15
2.78
16
RAGT Semences
French
17.70
16
H16
2.64
17
Andean Seeds (United Phosphorus)
India
NA
17
H17
2.55
18
Heilongjiang Agriculture Company Limited
China
16.52
18
H18
2.48
19
Euralis
French
15.63
19
H19
2.43
20
invivo
French
9.91
20
H20
2.07
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Li, L.; Zhang, L.; Wang, X. Research on the Dynamic Evaluation of the Competitiveness of Listed Seed Enterprises in China. Agriculture 2024 , 14 , 1213. https://doi.org/10.3390/agriculture14081213
Li L, Zhang L, Wang X. Research on the Dynamic Evaluation of the Competitiveness of Listed Seed Enterprises in China. Agriculture . 2024; 14(8):1213. https://doi.org/10.3390/agriculture14081213
Li, Lanlan, Lu Zhang, and Xiudong Wang. 2024. "Research on the Dynamic Evaluation of the Competitiveness of Listed Seed Enterprises in China" Agriculture 14, no. 8: 1213. https://doi.org/10.3390/agriculture14081213
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IMAGES
VIDEO
COMMENTS
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;
1. Narrative Literature Review. A narrative literature review, also known as a traditional literature review, involves analyzing and summarizing existing literature without adhering to a structured methodology. It typically provides a descriptive overview of key concepts, theories, and relevant findings of the research topic.
Reviewing related literature provides a great deal of guidance in quantitative research studies. Learning what others have done previously can inform decisions regarding research design, sampling, instrumentation, data col-lection procedures, and data analysis. 4. Development of a written literature review. Once the related literature has been
The literature review is the backbone of all types of research which includes a comprehensive summary of previous research on a topic. It should be e numerated, described, summarised, objectively ...
Refers to any combination of methods where one significant component is a literature review (usually systematic). ... Within a review context it refers to a combination of review approaches for example combining quantitative with qualitative research or outcome with process studies ... an analysis of 14 review types and associated methodologies ...
The conventional focus of rigorous literature reviews (i.e., review types for which systematic methods have been codified, including the various approaches to quantitative systematic reviews [2-4], and the numerous forms of qualitative and mixed methods literature synthesis [5-10]) is to synthesize empirical research findings from multiple ...
What kinds of literature reviews are written? Narrative review: The purpose of this type of review is to describe the current state of the research on a specific topic/research and to offer a critical analysis of the literature reviewed. Studies are grouped by research/theoretical categories, and themes and trends, strengths and weakness, and gaps are identified.
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.. Also, we can define a literature review as the collected body of scholarly works related to a topic:
As mentioned previously, there are a number of existing guidelines for literature reviews. Depending on the methodology needed to achieve the purpose of the review, all types can be helpful and appropriate to reach a specific goal (for examples, please see Table 1).These approaches can be qualitative, quantitative, or have a mixed design depending on the phase of the review.
Method details Overview. A Systematic Literature Review (SLR) is a research methodology to collect, identify, and critically analyze the available research studies (e.g., articles, conference proceedings, books, dissertations) through a systematic procedure [12].An SLR updates the reader with current literature about a subject [6].The goal is to review critical points of current knowledge on a ...
In all types of review of literature consider how to help the reader assimilate the information neces- sary to see the logic between the literature and the new study. Use carefully crafted sentences and, when appropriate, simple tables to illustrate key points. For most, writing the review of literature is laborious, but the outcome is a work ...
Abstract. Literature reviews establish the foundation of academic inquires. However, in the planning field, we lack rigorous systematic reviews. In this article, through a systematic search on the methodology of literature review, we categorize a typology of literature reviews, discuss steps in conducting a systematic literature review, and ...
Maidenhead, England (Chapter on writing a literature review) Boote, and Beile (2005). Scholars before researchers: On the centrality of the dissertation literature review in research preparation. Educational Researcher. 34: 3‐15. Petticrew, M. and Roberts, H. (2006).
Quantities of literature and overall quality/direction of effect of literature. Scoping review: Preliminary assessment of potential size and scope of available research literature. Aims to identify nature and extent of research evidence (usually including ongoing research). Completeness of searching determined by time/scope constraints.
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 ...
CHAPTER 2. REVIEW OF RELA TED LITERA TURE. INTRODUCTION. A review of literature is a classification and evaluation of what accredited scholars and. researchers have written on a topic, organized ...
Relies on diverse sources of data (e.g. empirical, theoretical or methodological literature; qualitative or quantitative studies) Systematic Review. Systematically and transparently collects and categorize existing evidence on a question of scientific, policy or management importance; Follows a research protocol that is established a priori
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 ...
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 ...
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.
As the literature related to almost any topic is vast, the authors of literature reviews must set limitations as to what literature they will or will not be covering. Some common criteria for inclusion and exclusion include: Language of publication (e.g., English only) Type of publication (e.g., scholarly journals, books, dissertations)
There is considerable literature showing the complexity, connectivity and blurring of 'qualitative' and 'quantitative' methods in research. Yet these concepts are often represented in a binary way as independent dichotomous categories. This is evident in many key textbooks which are used in research methods courses to guide students and newer researchers in their research training. This paper ...
multitude of variables examined in the literature on job seeking and employment success. We conducted a quantitative synthesis of the literature to test relationships between job-search self-regulation, job-search behavior, and employment success outcomes. We also quantitatively review key antecedents (i.e.,
The report is based on a targeted literature review, an exploration of the available data on the relevant population, and a review of public and private programs that aid this population. While the study team found no recent studies or national datasets that cover target population as defined in the statute, it did identify related data and ...
We conducted a thorough search of the topic area and employed systematic quantitative literature review (SQLR) technique to methodically review and assess the relevant literature, consistently with previous key scientific works (Fisch and Block, 2018, Zupic and Čater, 2015).The data for this study was collected by gathering documents from two major databases: Scopus and Web of Science (WOS).
Seed enterprises are crucial for ensuring national food security, the driving force behind the seed industry's advancement, and the core entity in constructing a modern seed industry system. At the micro and macro levels, agricultural seed enterprises face challenges and pressures in earning excess profits, enhancing their competitive edge, and resisting the incursion of multinational seed ...